The Two-Stage Valuation Method and its challenges

Cornelius HEINTZE

In this article, Cornelius HEINTZE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) explains how the two-stage valuation model and the segmentation in growth stage and stable phase impact the valuation of companies and which problems tend to arise with the use of this model.

Why this is important

The valuation of companies is always present in the world of finance. We see it in Mergers and Acquisitions (M&A), initial public offerings (IPOs) and daily stock market pricing where firms are valued within seconds based on new information. For markets to function properly, valuations need to represent the underlying company as precisely as possible. Otherwise, information asymmetries increase, leading to inefficient or even dysfunctional markets.

The Two-Stage Model

The Two-Stage Model is the traditional model that is used by finance experts across the world. What makes it stand out is the segmentation of the valuation in two steps:

  • Growth phase (explicit forecast period): In this phase, the company’s future cash flows are projected in detail for each year t = 1 … T. These cash flows are then discounted back to the valuation date using the discount rate r:

    PV(Growth phase) = Σt=1…T ( CFt ) / (1 + r)t

  • Stable phase (terminal value): After the explicit forecast horizon, the company is assumed to enter a stable stage. There are two assumptions needed to fulfill this stage and its equations. First it is assumed that the company can realize the cashflows over an indefinite timespan. Second, it is assumed that the perpetual growth rate g does not exceed the growth rate of the whole economy. The two common resulting equations are:
    • No growth (steady state):
      PV(Stable phase) = CFstable / (r * (1 + r)T)

    • Constant growth in perpetuity:
      PV(Stable phase) = CFT+1 / ((r − g) * (1 + r)T)

Total firm value is then the sum of both parts:

Value = PV(Growth phase) + PV(Stable phase)

Problems with the Two-Stage Model

If we look closer at the equations for the stable phase you will realize that they show a perpetuity. Looking at the assumptions given, this is also the only possible outcome. But given this circumstance we encounter the first big problem of the Two-Stage Model: the stable phase often makes up over 50% of the firm value. This is a problem as the assumptions for the stable phase are often very subjective and not very realistic. The problem evolves even more when it is assumed that there is a constant growth rate. Let’s look at this through an example:

Assumptions: discount rate r = 10%, explicit forecast over T = 5 years with free cash flows (in €m): 80, 90, 95, 98, 100. After year 5, we consider two terminal cases.

Phase 1 – Present value of explicit cash flows

  • Year 1: 80 / (1.10)1 = 72.73
  • Year 2: 90 / (1.10)2 = 74.38
  • Year 3: 95 / (1.10)3 = 71.37
  • Year 4: 98 / (1.10)4 = 66.94
  • Year 5: 100 / (1.10)5 = 62.09

PV(Phase 1) ≈ 347.51 (€m)

Phase 2 – Stable phase

  • (a) No growth: CFstable = 100 ⇒ TV at t=5
    PV(Terminal) = 100 /(0.1*(1.10)5) = 620.92

  • (b) Constant growth g = 2%: CFT+1 = 100 ⇒ TV at t=5
    PV(Terminal) = 100/((0.10-0.08) * (1.10)5) = 776.15

Total value and weights

  • No growth: Total = 347.51 + 620.92 = 968.43 ⇒ Stable Phase share ≈ 64.1%, Phase-1 share ≈ 35.9%
  • g = 2%: Total = 347.51 + 776.15 = 1,123.66 ⇒ Stable Phase share ≈ 69.1%, Phase-1 share ≈ 30.9%
  • Impact of growth: Increase in the firm value of 155.23 or ≈ 16%

Takeaway: A modest increase in the perpetual growth rate from 0% to 2% raises the terminal present value by ~155 (€m) and lifts its weight from ~64% to ~69% of total value. This illustrates the strong sensitivity of the two-stage model to terminal assumptions.

If you want to try out for yourself and learn more about the sensitivity of the growth rate in relation to the firm value you can do so in the excel-file I have created in order for this example as shown below:

Two-Stage Model Example 1

Another very interesting fact gets visible, while trying out the model, which is commonly seen in early tech startups or general startups, that have very high early investment costs (for example software development). They will have a negative firm value in the growth phase but in the long run it is assumed that these companies will have a constant growth rate and positive cashflows, therefore evening out the negative growth phase. This again shows how much of an impact the stable and the growth phase has on the firm value.

Two-Stage Model Example Startup

You can download the excel file here:

Download the Excel file for Two-Stage-Model Analysis

Implications for practical use and solutions

As seen in the example, the impact of the stable phase and therefore the assumptions about the cashflows and the circumstances of the company as to whether it is appropriate to use a growth rate plays a big role in on the valuation of the firm. Deciding these assumptions lies at the feet of the firms that valuate the company or at the company valuating itself. Therefore, they are highly subjective and must be transparent at all times to ensure an appropriate valuation of the firm. If this is not the case firms can be valued at a much higher value than it is appropriate and therefore convey false information.

To fight this it is recommended to incorporate various valuation methods to verify that the value is not too high or too low but rather on a bandwidth of values which are plausible. This is often times part of a fairness opinion which is issued by an independent company. You can see an example here when Morgan Stanley drafted a fairness opinion for Monsanto for the merger with Bayer:

Full SEC Statement for the merger

To sum up…

The Two-Stage Valuation Model remains a cornerstone in corporate finance because of its simplicity and structured approach. However, as the example shows, the stable phase dominates the overall result and makes valuation highly sensitive to small changes in assumptions. In practice, analysts and other users of the information provided by the valuing company should therefore apply the model with caution, test alternative scenarios, and complement it with other methods. Looking ahead, the combination of traditional models with advanced techniques such as multi-stage models, sensitivity analyses, or even simulation approaches can provide a more balanced and reliable picture of a company’s value.

Why should I be interested in this post?

Whether you are a student of finance, an investor, or simply curious about how firms are valued, understanding the Two-Stage Valuation Model is essential. It is one of the most widely used approaches in practice and often determines the prices we see in the markets, from IPOs to M&A. By being aware of both its strengths and its limitations, you can better interpret valuation results and make more informed financial decisions.

Related posts on the SimTrade blog

   ▶ All posts about financial techniques

   ▶ Jorge KARAM DIB Multiples valuation methods

   ▶ Andrea ALOSCARI Valuation methods

   ▶ Samuel BRAL Valuing the Delisting of Best World International Using DCF Modeling

Useful resources

Paul Pignataro (2022) “Financial modeling and valuation: a practical guide to investment banking and private equity” Wiley, Second edition.

Tim Koller, Marc Goedhart, David Wessels (2010) “Valuation: Measuring and Managing the Value of Companies”, McKinsey and Company.

Fairness Opinion Example

About the author

The article was written in October 2025 by Cornelius HEINTZE (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025

My Internship Experience at Alstom as a Market Research Intern

Rishika YADAV

In this article, Rishika YADAV (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2023–2027) shares her professional experience as a Market Research Intern at Alstom in India.

Introduction

As a Global BBA student at ESSEC Business School, I had the opportunity to join Alstom India as a Market Research Intern. This experience allowed me to work at the intersection of strategy, policy, and innovation in the transport sector. My missions ranged from analysing the outlook of the Indian Railways industry to benchmarking global players in the hydrogen-powered engine market and delivering data-driven insights for decision-making.

In this post, I will share my professional journey at Alstom, provide an overview of the industry context in India, and reflect on how market research contributes to shaping strategic positioning in a highly dynamic sector.

About Alstom

Alstom is a global leader in sustainable mobility, designing and manufacturing rolling stock, signaling systems, and railway services. Headquartered in Saint-Ouen, France, Alstom operates in more than 70 countries and employs over 80,000 people worldwide. Its portfolio covers a wide range of solutions, from high-speed trains to metro systems and innovative propulsion technologies, including hydrogen-powered engines.

Logo of Alstom.
Logo of Alstom
Source: the company.

The company plays a central role in the modernization of the Indian Railways, where large-scale infrastructure projects and government initiatives are reshaping mobility. Alstom’s presence in India includes major manufacturing plants, research centers, and long-term partnerships with the Indian government, making it a critical player in the country’s transport ecosystem.

Industry Context: Indian Railways and the Push for Modernization

India’s railway network is the fourth largest in the world, transporting more than 8 billion passengers annually and serving as the backbone of both passenger and freight mobility. With urbanization, growing demand for logistics, and sustainability imperatives, the government has launched ambitious modernization projects.

To structure my analysis, I applied a PESTEL framework (Political, Economic, Social, Technological, Environmental, Legal), which helped me capture the multifaceted drivers shaping the industry:

  • Political: Strong government commitment to railway electrification by 2030 and the development of high-speed rail projects such as the Mumbai–Ahmedabad bullet train.
  • Economic: Massive infrastructure spending, growing freight demand, and India’s ambition to become a global logistics hub.
  • Social: Rapid urbanization and rising middle-class demand for safe, reliable, and sustainable transport.
  • Technological: Deployment of digital signaling, automation in metro systems, and investments in green technologies such as hydrogen propulsion.
  • Environmental: Climate change policies driving the shift away from diesel and the adoption of zero-emission mobility solutions.
  • Legal: “Make in India” requirements for domestic production and procurement rules encouraging partnerships between multinational firms and local manufacturers.

For companies like Alstom, this environment presents both opportunities and challenges. Success depends on aligning with government priorities, anticipating regulatory frameworks, and delivering sustainable solutions that address the mobility needs of a rapidly urbanizing population.

Market Research and Strategic Outlook

Building on the PESTEL framework, my primary task was to translate macro-level industry dynamics into strategic insights for Alstom’s marketing team. I applied elements of Porter’s Five Forces to evaluate competitive pressures, particularly the bargaining power of government procurement agencies, the threat of substitute technologies, and the intensity of rivalry among global players.

For instance, the Indian government’s procurement model places strong emphasis on cost-effectiveness and local value creation. This heightened the importance of analyzing procurement cycles and budget allocations, as these factors directly determine entry opportunities. Similarly, the rise of indigenous technology developers suggested a potential medium-term substitution risk for foreign OEMs (Original Equipment Manufacturers).

My contribution was to synthesize these complex dynamics into actionable recommendations for Alstom’s leadership. By mapping government initiatives (such as 100% electrification by 2030) against Alstom’s innovation pipeline, I helped highlight priority areas for investment and partnership. This showed how market research acts as a bridge between public policy directions and private strategic decisions.

Competitive Analysis in the Hydrogen-Powered Engine Market

A key part of my internship involved conducting a competitive benchmarking study on the hydrogen-powered engine market, an emerging field in sustainable transport. My analysis compared Alstom’s positioning with that of leading competitors, including Siemens Mobility (Germany), CRRC (China), and Stadler Rail (Switzerland). The benchmarking exercise focused on three dimensions:

  1. Technological efficiency – energy conversion rates, operational range, and adaptability to existing rail infrastructure.
  2. Regulatory compliance – alignment with safety standards, certification requirements, and government adoption incentives.
  3. Innovation roadmaps – timelines for pilot projects, R&D collaborations, and commercial deployments.

As part of the study, I also examined India’s first hydrogen train initiative, announced under the “Hydrogen Mission” in 2021 and piloted on the Jind–Sonipat route in Haryana. This project provided a reference point for assessing how domestic adoption could influence demand for hydrogen solutions and how foreign players like Alstom might participate in future collaborations.

The outcome of this competitive analysis was a set of strategic benchmarks that highlighted Alstom’s strengths (global experience, proven prototypes in Europe) and areas where adaptation to the Indian context would be critical (local supply chain integration, cost competitiveness).

Conclusion

My internship at Alstom was more than an introduction to the transport sector — it was a formative experience that sharpened my analytical, strategic, and collaborative skills. Through market research, I learned how to transform complex and unstructured data into clear insights that directly supported executive decision-making. By benchmarking global competitors and tracking procurement patterns, I discovered the importance of combining rigorous analysis with an understanding of policy and technology trends.

Equally important, I developed strong stakeholder management skills by working with senior leadership, and I learned to deliver results under tight deadlines in a fast-moving industry. These experiences deepened my interest in strategy and finance, particularly in industries undergoing technological and regulatory transformation. Looking ahead, I aspire to build a career where I can contribute to shaping sustainable and innovative solutions at the crossroads of business strategy, financial decision-making, and global infrastructure development.

Business concepts related to my internship

I present below three concepts related to my internship and explain how they connect to my missions at Alstom: Total Cost of Ownership (TCO), Public Procurement Economics, and Benchmarking & Competitive Advantage.

Total Cost of Ownership (TCO)

Total Cost of Ownership refers to the overall cost of an asset across its life cycle, including purchase, operation, maintenance, and disposal. In railway procurement, decision-makers often evaluate not only the initial price of rolling stock or propulsion systems but also long-term operating costs such as energy consumption and maintenance. During my internship, I integrated TCO considerations into market analyses by comparing the long-run economics of hydrogen-powered versus diesel and electric trains. This helped demonstrate how Alstom could position its products as cost-efficient over their lifetime, even if initial capital expenditure was higher.

Public Procurement Economics

Public procurement represents a large share of railway investment in India. It is shaped by budget cycles, fiscal priorities, and policy objectives such as “Make in India.” Understanding procurement economics was central to my internship, since I analysed over 500 data points on tenders, contracts, and project timelines. By linking procurement patterns with budget allocations, I helped Alstom anticipate periods of high demand (for example, after fiscal budget announcements) and adapt bid strategies accordingly. This ensured better alignment of Alstom’s proposals with the financial and institutional realities of government buyers.

Benchmarking & Competitive Advantage

Benchmarking involves comparing a company’s performance, costs, and capabilities against competitors to identify strengths and gaps. In my competitive analysis of the hydrogen-powered engine market, I benchmarked Alstom’s offerings against Siemens Mobility, CRRC, and Stadler Rail. This comparison focused on efficiency ratios, regulatory readiness, and innovation timelines. By identifying areas where Alstom’s European experience was a strength, and where local cost competitiveness needed improvement, the benchmarking exercise informed strategic positioning in India. It demonstrated how analytical tools can translate into competitive advantage in bidding and partnerships.

Why Should You Be Interested in This Post?

This post offers a first-hand view of how market research bridges the gap between public policy and private strategy in one of the most dynamic transport markets in the world. If you are curious about:

  • How global companies adapt to government-driven reforms,
  • How benchmarking and data analysis inform business positioning,
  • Or how sustainability goals like hydrogen-powered mobility are transforming traditional industries,

…then this post provides a concrete example from inside Alstom’s operations in India. Beyond an internship story, it illustrates how analytical tools and strategic thinking can shape the future of mobility.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Max ODEN Leveraged Finance: My Experience as an Analyst Intern at Haitong Bank

   ▶ Anouk GHERCHANOC My Internship Experience as a Corporate Finance Analyst in the 2IF Department of Inter Invest Group

   ▶ Lara HADDAD My Internship Experience as a Market Analyst at L’Oréal

   ▶ Samia DARMELLAH My Experience as a Credit Risk Portfolio Analyst at Société Générale Private Banking

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

Useful resources

Alstom — official website

Indian Railways Official portal

Press Information Bureau of India Government announcements and policy updates

NITI Aayog (Indian government think tank) Reports on hydrogen policy and sustainable transport

International Energy Agency (IEA) The Future of Rail Report

About the Author

This article was written in October 2025 by Rishika YADAV (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2023–2027). Her academic interests lie in strategy, finance, and global industries, with a focus on the intersection of policy, innovation, and sustainable development.

My Internship Experience with the Economic and Market Intelligence Team at Daimler Truck

Vincent WALGENBACH

In this article, Vincent WALGENBACH (ESSEC Business School, Grande Ecole Program – Master in Management, Exchange Student) compares the role of an economic analyst within the financial industry to that in the corporate sector and highlights the associated career trade-offs.

Daimler Truck AG

Daimler Truck is the world’s largest manufacturer of commercial vehicles, selling over 460,000 trucks globally in 2024 and generating €54.1 billion in revenue. Headquartered near Stuttgart, Germany, the company designs, produces, and sells trucks and buses. As of Q2 2025, it employs more than 110,000 people worldwide and operates dozens of production sites. Daimler Truck was established in 2021 as a spin-off from Mercedes-Benz and builds on a long-standing tradition in the industry.

Logo of the company.
Logo of Daimler Truck
Source: Daimler Truck.

A Comparison of an Analyst Position in the Financial and Corporate Sectors

During an internship in the Economic and Market Intelligence Team, the author gained insight into how economists work within a multinational corporation. While economists are often associated with banks, insurance companies, or financial service providers, many large industrial firms also maintain economics departments. Unlike in banks, where teams are highly specialized, corporate economics departments are smaller and require team members to cover a wide range of expertise.

Economists in the Financial Industry: Specialists in a Complex Organization

In banks and other financial institutions, economics teams are typically large and highly specialized. Each economist focuses on a narrow field – such as monetary policy in a specific country, credit risk, or commodity markets. This high degree of specialization reflects the complexity of modern financial markets and the importance of precise analysis.

For example, one analyst might dedicate their entire career to analyzing the U.S. Federal Reserve’s policy decisions and their impact on bond yields, others may focus on niche areas such as energy markets, foreign exchange dynamics, or the effects of fiscal policy on sovereign debt.

Another important aspect of their work is risk assessment. Analysts in banks are tasked with stress-testing portfolios against different macroeconomic scenarios – such as a sudden spike in inflation, a geopolitical crisis, or a global recession.

In summary, these are some core features of the economist’s role within financial institutions:

  • Focus areas: Interest rates, inflation forecasts, financial market dynamics
  • Work style: Highly quantitative, model-driven, and often tied to investment decisions
  • Career tradeoff: Economists gain deep expertise in a niche area but may have limited exposure to broader economic questions

Economists in the Corporate Sector: Generalists with a Broad View

By contrast, economics departments in multinational corporations are usually smaller. At Daimler Truck, the Economic and Market Intelligence Team had only five employees covering a wide range of topics, from global macroeconomic trends to industry-specific market forecasts, and energy markets.

Because the team was small, each member had to be flexible and work across multiple domains. This required not only strong analytical skills but also the ability to communicate insights to non-economists, such as managers in strategy, sales, or procurement. The main responsibility of the team was to provide both quantitative and qualitative insights into the global truck market as well as the macroeconomic outlook of key regions for decision-makers. To this end, the team prepared a weekly briefing for the board and a more extensive report for the CFO, in addition to delivering analyses for the strategy department. Beyond top management, we also supported other departments, for example, providing inflation analyses to procurement or HR to assist them in their ongoing negotiations. In addition to supporting the team with day-to-day requests and briefings, I was also assigned independent projects. These included analyzing potential growth markets and assessing the economic impact of carbon neutrality policies.

The three most important concerns for the team were economic growth, inflation, and energy economics.

Economic Growth

Economic growth, measured primarily by Gross domestic product (GDP), was a key focus due to its strong correlation with truck sales. The company operates on a B2B model, and growth in the broader economy typically encourages firms to invest and expand their vehicle fleets—especially under favorable economic conditions. To assess this, the team relied on data from various economic research institutes and providers such as S&P Global. These datasets were then adjusted and evaluated according to internal standards, with models like Aggregate Supply and Aggregate Demand (AS/AD) serving as analytical frameworks.

Inflation

Inflation – both consumer and producer price inflation – was another critical factor. On one hand, the company runs a large procurement division responsible for sourcing truck components, and inflation plays a central role in supplier negotiations. On the other hand, inflation directly affects the financial department, especially in areas like leasing and financing, where trucks are often acquired through loans or lease agreements. Moreover, inflation influences monetary policy, and interest rate decisions by the ECB and the Fed are highly relevant for investment planning, leasing conditions, and overall demand.

Energy Economics

At the time, Europe was facing significant energy supply challenges and sharp price increases. As a result, energy economics, typically not a core focus for the team, became critically important. This was due both to the fact that trucks primarily run on fuel, which affects customer investment decisions, and because the company’s own operations and production processes consume large amounts of electricity and gas. In fact, the firm operates its own power plants. To navigate this, the team applied classical supply-and-demand analysis and closely monitored geopolitical developments and energy market news.

In summary, these are some core features of the economist’s role within the corporate sector:

  • Focus areas: macroeconomics, Industry trends, global trade flows
  • Work style: Broader scope, combining quantitative analysis with qualitative judgment
  • Career tradeoff: Economists develop versatility but may not reach the same level of technical specialization as in finance

Key Takeaways from My Internship – Career Implications

For those considering an Analyst position, the choice between the financial industry and the corporate sector involves a tradeoff between specialization and versatility.

  • If you enjoy mastering a narrow field and working with advanced models, the financial industry may be the right fit.
  • If you prefer applying economics to a wide range of real-world business challenges, a corporate economics department is super interesting.

Economists in financial institutions often occupy a central role at the very heart of the organization. Their analyses directly influence investment strategies, risk management, and overall business performance. By contrast, within multinational corporations, economists tend to hold a more specialized and somewhat “exotic” position. Their insights are primarily directed toward senior management and the board, supporting strategic decision-making rather than day-to-day operations.

This distinction has important career implications. In the corporate world, economists may find it more challenging to climb the organizational ladder, as their role is less integrated with the core functions of the firm. Unlike finance, marketing, or operations, economics is not always seen as a natural pathway to executive leadership. As a result, corporate economists often remain valuable advisors rather than becoming decision-makers themselves.

My internship provided a comprehensive introduction to the wide range of fields an economic analyst can pursue. This broad exposure is particularly valuable for those considering future specialization, as it offers a clear overview of the different domains and helps in identifying which areas may be most rewarding to pursue in greater depth.

Why should I be interested in this post?

This post compares the role of an analyst in an economics team within the financial industry to that in the corporate sector, highlighting key differences in specialization and the career trade-offs involved.

Related posts on the SimTrade blog

Professional experiences

   ▶ All posts about Professional experiences

   ▶ Max ODEN Leveraged Finance: My Experience as an Analyst Intern at Haitong Bank

   ▶ Anouk GHERCHANOC My Internship Experience as a Corporate Finance Analyst in the 2IF Department of Inter Invest Group

   ▶ Lara HADDAD My Internship Experience as a Market Analyst at L’Oréal

   ▶ Samia DARMELLAH My Experience as a Credit Risk Portfolio Analyst at Société Générale Private Banking

   ▶ Nithisha CHALLA Job description – Financial analysts

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

Economics and data

   ▶ Bijal GANDHI Inflation Rate

   ▶ Nithisha CHALLA Bloomberg

   ▶ Nithisha CHALLA S&P Global Market Intelligence

Useful resources

Daimler Truck AG

European Central Bank (ECB)

Federal Reserve (Fed)

Eurostat Data

Federal Reserve Economic Data

International Energy Agency (IEA)

About the author

The article was written in September 2025 by Vincent WALGENBACH (ESSEC Business School, Grande Ecole Program – Master in Management, Exchange Student).

Valuing the Delisting of Best World International Using DCF Modeling

Samuel BRAL

In this article, Samuel BRAL (ESSEC Business School, Global BBA – Exchange at NUS, 2025) shares how he conducted a valuation of Best World International using a Discounted Cash Flow model in Excel. This modeling exercise was part of a corporate finance case during his exchange at the National University of Singapore.

Context of the project

During my exchange at NUS, I was asked to evaluate the fair price at which Best World International, a Singaporean skincare and wellness company, could be taken private. The company had announced its intention to delist from the Singapore Exchange (SGX). My role was to determine the intrinsic value per share using a discounted cash flow approach that distinguishes between a high-growth projection period and a long-term steady-state phase. The goal was to assess whether the proposed buyout price was fair to minority shareholders.

Understanding the DCF method

The Discounted Cash Flow method estimates the value of a company by forecasting its future free cash flows and discounting them back to their present value using the firm’s Weighted Average Cost of Capital. This method is widely used by investment banks, private equity firms, and corporate finance teams for valuing companies, especially in the context of M&A and privatizations.

Well-known examples of its application include the valuation of Twitter during its acquisition by Elon Musk in 2022 and the fairness opinions issued by investment banks in LBO transactions such as the Bain Capital acquisition of Kioxia.

Step-by-step technical implementation

The Excel model followed a two-stage DCF approach: an explicit forecast period from 2024 to 2028 and a terminal value from 2029 onward. Below is a breakdown of the modeling process:

1. Revenue Forecasting

I projected revenue growth using a blended approach. I considered:

  • The average historical CAGR of BWI’s revenues between 2021 and 2023.
  • The expected CAGR for the ASEAN cosmetics and wellness industry (7–9%) based on Statista and Euromonitor data.

Revenue = Previous Year Revenue × (1 + Growth Rate)

2. EBIT Estimation

I calculated EBIT by projecting the cost structure of the business:

  • I took historical averages of cost items such as COGS and SG&A as a percentage of revenue.
  • Assumed that operating leverage would allow fixed costs to grow slower than revenue, improving margins over time.

EBIT = Revenue – Operating Costs

3. Tax Adjustment and NOPAT

I applied a normalized effective tax rate based on BWI’s historical tax filings and Singapore’s corporate tax regime (17%).

NOPAT = EBIT × (1 – Tax Rate)

4. Depreciation and CAPEX

I assumed CAPEX as a stable % of revenue, using 2023 data as the benchmark. Depreciation was projected using the historical ratio of D&A to CAPEX.

Free Cash Flow = NOPAT + Depreciation – CAPEX – ΔWorking Capital

5. Net Working Capital (NWC)

NWC = Current Assets – Current Liabilities. I used the average NWC-to-revenue ratio from past years to forecast changes in NWC.

6. Terminal Value and Discounting

The Terminal Value, which captures the value of a business beyond the explicit forecast period in a DCF analysis – often 5 or 10 years into the future. was calculated using the Gordon Growth formula:

TV = FCF_2028 × (1 + g) / (WACC – g)

Where g was estimated at 2.5%, reflecting long-term GDP and sector growth rates in the ASEAN region.

Both FCFs and Terminal Value were discounted using WACC (5.55%). The present values were then summed to calculate Enterprise Value.

7. Equity Value per Share

Enterprise Value – Net Debt + Cash = Equity Value

Equity Value / Number of Shares = Value per Share

WACC and Beta calculation

WACC reflects the average cost of capital from both equity and debt, weighted by their proportions in the firm’s capital structure, it serves as the discount rate for projecting future cash flows. For companies like BWI, which operate in niche, consumer-focused markets, WACC provides a benchmark for evaluating whether future growth justifies current valuations

  • Cost of equity was derived using the Capital Asset Pricing Model (CAPM):
  • Cost of Equity = Risk-Free Rate + Beta × Market Risk Premium
  • Beta was computed by unlevering and relevering betas of comparable firms in China, Taiwan, and Malaysia. This accounts for business and financial risk.
  • Cost of debt was based on comparable bond yields and company-specific risks.
  • Capital structure weights were based on BWI’s most recent financial statements.

The photos below are showing how I proceeded

WACC Computation

Beta Computation

Key results and analysis

The model output was:

  • Enterprise Value = SGD 4.8 billion
  • Equity Value = SGD 4.18 billion
  • Intrinsic Value per Share = SGD 9.72 (vs. proposed delisting price of SGD 7.00)

This suggests that the buyout offer undervalued the company by more than 30%. This raised questions of fairness for minority shareholders, echoing similar cases in Asia such as the privatization of Wing Tai Holdings or the delisting of Global Logistic Properties.

Download the Excel file

If you want to access a part of my work on the projections and DCF, click the link below:

Download the Excel file for WACC and Beta analysis

Why should I be interested in this post?

This modeling project not only strengthened my technical finance skills but also helped me think critically about shareholder rights, valuation fairness, and the role of financial modeling in defending minority interests. Mastering the DCF approach is essential for anyone pursuing investment banking, private equity, or corporate strategy roles.

Related posts on the SimTrade blog

   ▶All posts about Technical techniques

   ▶ Andrea ALOSCARI Valuation Methods

   ▶ Yann-Ray KAMANOU TAWAMBA Understanding the Discount Rate: A Key Concept in Finance

   ▶ William LONGIN How to compute the present value of an asset?

   ▶ Andrea ALOSCARI Internship: Corporate & Investment Banking (Intesa Sanpaolo)

Useful resources

SimTrade Platform

Monetary Authority of Singapore

About the author

This article was written in September 2025 by Samuel BRAL (ESSEC Business School, Global Bachelor in Business Administration – Exchange at NUS).

Forecasting Airline Route Profitability with Monte Carlo Simulation

Samuel BRAL

In this article, Samuel BRAL (ESSEC Business School, Global BBA – Exchange at NUS, 2025) explains how he applied Monte Carlo simulations to support Emirates Airlines in evaluating the profitability of launching a new long-haul route under conditions of uncertainty.

Context of the project

This project was part of the course “Decision Analytics using Spreadsheets” at the National University of Singapore (NUS). I was asked to provide a quantitative recommendation to Emirates Airlines on selecting a new international route from Dubai. The available destination options included Buenos Aires, Tokyo, Cape Town, and Cairo.

Due to the complexity of airline operations and the uncertainty surrounding factors such as demand, ticket prices, no-show rates, and operating costs, a traditional static financial model would not be sufficient. Instead, I built a Monte Carlo simulation model to capture the dynamic range of possible outcomes and assess the risk-return profile of each destination.

What is a Monte Carlo simulation?

A Monte Carlo simulation is a mathematical technique used to estimate the probability distribution of outcomes when there is uncertainty in the input variables. By running thousands of simulations using random values generated from defined probability distributions, the method provides insights into the range, likelihood, and volatility of potential results.

This approach is commonly used in financial modeling, risk analysis, and engineering. For example, investment banks use Monte Carlo models to simulate portfolio returns and Value at Risk (VaR), while oil and gas companies apply them to forecast drilling success and production volumes.

Simulation approach and methodology

I built a simulation model in Excel that executed 2,000 trials per route. Each trial simulated a potential outcome based on randomly generated values for key variables. The profit was calculated using the following formula:

Profit = (Tickets Sold × Ticket Price) – Operating Costs – Compensation Costs

Here is how each component was modeled:

  • Passenger demand: Modeled as a normal distribution using historical demand averages and standard deviations for each route. For example, Tokyo exhibited more stable demand, while Buenos Aires showed higher variance due to geopolitical and economic volatility in Argentina.
  • Ticket price: Ticket prices were generated using NORM.INV(RAND(), mean, stdev) to account for fluctuations caused by competitive pricing, seasonal variation, and macroeconomic factors like fuel costs and currency movements.
  • No-show rate: Modeled with a uniform distribution between 5% and 10%, based on IATA statistics and academic studies on airline overbooking behavior (source: IATA Global Passenger Survey, 2023).
  • Aircraft assignment: Simulated using a discrete probability distribution based on the actual Emirates fleet composition (e.g., A380, Boeing 777). Larger aircraft allowed more passengers but incurred higher operating costs.
  • Compensation cost: Incurred when demand exceeded seat capacity, reflecting the cost of rebooking, refunds, and customer service. These costs were calibrated using Emirates’ historical compensation data for overbooking cases (source: Emirates Annual Report 2023).

To execute the simulations, I used Excel’s Data Table function to loop through trials and capture the output profit distribution for each destination. From this distribution, I calculated:

  • Expected profit (mean)
  • Standard deviation of profit (volatility)
  • Probability of a loss (profit < 0)
  • Probability of a significant loss (loss > SGD 100,000)

Key results and insights

The simulation identified Buenos Aires as the most profitable option with an expected profit of SGD 292,247 and a 99.65% chance of profitability. However, the route also exhibited a small 0.1% risk of incurring losses above SGD 100,000 due to volatile demand and long travel distance.

Cape Town, while less profitable, offered near-zero downside risk. Tokyo had moderate returns and relatively low variance. This reflects a classic risk-return tradeoff that airlines often face: should the company pursue high-reward but volatile destinations, or opt for stable but lower-margin routes?

Additionally, I tested various overbooking strategies. An overbooking rate of 9.3% was found to optimize expected profits while keeping the cost of passenger compensation within an acceptable range. This mirrors real-world practices, where carriers like Delta and Lufthansa use algorithmic overbooking based on historical no-show patterns to maximize seat utilization (source: MIT Airline Data Project). If you want to have access to the work, here is the Excel file on the overview of all routes as well as the work for Buenos Aires.

Download the Excel file for Monte Carlo simulation

Why should I be interested in this post?

This project demonstrates how Monte Carlo simulations transform business decision-making under uncertainty. Instead of relying on single-point forecasts, the model enabled me to quantify risk, test strategic decisions (like overbooking), and provide data-driven recommendations.

For students and professionals in finance, consulting, or operations, Monte Carlo simulation is a core technique for scenario planning and risk assessment. It enhances decision quality in fields as diverse as project finance, asset management, supply chain optimization, and policy modeling.

Related posts on the SimTrade blog

   ▶All posts about Technical Subjects

   ▶Professional experience: Head of Data Modelling

   ▶Professional experience: Business Data Analyst at Tikehau Capital

Useful resources

SimTrade Platform

IATA Global Passenger Survey 2023

Emirates Annual Report and Press Releases

MIT Airline Data Project

About the author

This post was written in September 2025 by Samuel BRAL (ESSEC Business School, Global Bachelor in Business Administration – Exchange at NUS).

My internship experience as a Financial Controller at Talan

Samuel BRAL

In this article, Samuel BRAL (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026) shares his professional experience as Assistant Financial Controller at Talan.

About the company

Talan is a French consulting and IT services firm that supports large organizations in their digital transformation. Founded in 2002, the group now operates in over 15 countries with more than 5,000 employees. Its activities cover business consulting, data & AI, transformation management, and IT systems integration.

The company has experienced rapid growth in recent years, reaching €600 million in revenue in 2023. Talan’s value proposition lies in combining business understanding with technical expertise to create tailored, high-impact solutions.

Logo of Talan.
Logo of Talan
Source: the company.

I worked within the Group FP&A (Financial Planning & Analysis) department at the Paris headquarters. This central team oversees the performance monitoring and financial reporting for all business units (BU), directly supporting the CFO and COMEX.

My internship

My missions

During my internship at Talan, my missions focused on supporting financial reporting, tool optimization, and performance monitoring across Talan’s international business units. My first responsibility was to assist in producing monthly management reports and P&L statements for each business unit. To do so, I extracted and reconciled financial data from systems such as Kimble, Jedox, and SuccessFactors. I created detailed revenue and margin reports used by the CFO and COMEX during monthly performance reviews. In one instance, I was tasked with explaining a sudden drop in margin for the Iberia BU, which led me to identify under-reported subcontractor costs and propose adjustments that improved margin accuracy by 15%.

In parallel, I was assigned to enhance and maintain our internal reporting tools. I updated Power BI dashboards to reflect changes in budget KPIs, created dynamic filters to allow managers to track performance by project or team, and integrated new reporting metrics requested by HR. A concrete example includes building a resource utilization dashboard that tracked billable vs. non-billable hours across 20+ consultants. This became a key element in weekly performance meetings.

I also contributed to the improvement of the Jedox budgeting model by testing input logic and spotting misalignments between operational forecasts and financial planning. My test case simulation revealed a recurring mismatch between headcount forecasts in SuccessFactors and budgeted salaries in Jedox, this insight helped improve the accuracy of HR cost planning. Lastly, I supported daily project performance follow-up. I maintained Excel trackers for monitoring project delivery rates, billing status, and work-in-progress (WIP). In one project, I flagged €1.2 million in delayed invoices at our UK subsidiary and proposed a process with the project manager and billing team to correct invoice triggers and reduce WIP exposure the following month.

Required skills and knowledge

This internship demanded both technical and soft skills. Technically, I had to master Excel (pivot tables, advanced formulas), Power BI, and become comfortable with integrated tools like Jedox, Kimble, and SuccessFactors. A solid understanding of accounting principles and management control basics was essential to analyze P&Ls and challenge budget assumptions.

But beyond tools and numbers, what really made a difference was my ability to adapt quickly, communicate clearly, and collaborate with different teams: from business unit managers to the finance department. I learned how to handle pressure during closing periods and gained confidence in presenting insights to senior stakeholders.

What I learned

This experience allowed me to apply classroom knowledge to real-world challenges. I saw how data, when properly structured and analyzed, can support strategic decision-making. I also learned the importance of data reliability, reconciling figures between systems and ensuring consistency across dashboards was a daily concern. Finally, I came out of the internship with a clearer picture of what FP&A means in practice: it’s not just about reporting, but about driving performance.

Financial concepts related to my internship

I present below three financial concepts related to my internship: variance analysis, working capital, and margin optimization.

Variance Analysis

Variance analysis was at the heart of my role. Each month, we compared actual figures with the budget and previous year (N-1) to explain key deviations in revenue, costs, and margins. This involved discussions with business unit heads to understand operational reasons behind the numbers: new project delays, staffing issues, or cost overruns. It’s a fundamental tool for financial control and performance steering.

Working Capital

Although I didn’t manage working capital directly, I learned how crucial it is in project-based firms like Talan. Delays in project billing or collection can quickly impact cash flow. Some of our dashboards tracked project completion status vs. invoicing, helping identify WIP (Work in Progress) accumulation. It gave me a concrete view of how accounting flows translate into liquidity risks.

Margin Optimization

One of our KPIs was project margin, calculated using resource allocation, billing rates (TJM), and direct costs. I worked on visualizing these margins in Power BI and exploring scenarios with the team. For example, we modelled the impact of raising the average billing rate or optimizing staffing on low-yield projects. This showed me how financial insight directly supports business decisions.

Why should I be interested in this post?

If you’re an ESSEC student interested in corporate finance, FP&A is a great field to explore. This internship gave me exposure to reporting, performance analysis, budgeting, and tools like Power BI and Jedox. It’s also a great entry point to understand how strategy and operations connect through numbers.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

Useful resources

Talan website

Microsoft Power BI

Jedox EPM platform

About the author

The article was written in September 2025 by Samuel BRAL (ESSEC Business School, Global Bachelor in Business Administration, 2022–2026).

My experience at Schneider Electric Singapore as a Finance Intern

William LONGIN

In this article, William LONGIN (Sorbonne School of Economics, Master in Money Banking Finance Insurance, 2024-2026) discusses his experience as a Finance intern at Schneider Electric Singapore.

About Schneider Electric

Schneider Electric is a French multinational company (MNC) that is specialized in energy management and automation solutions. It was founded in 1836 during the Industrial Revolution in Europe. Its headquarters are in Rueil-Malmaison (France). Schneider Electric develops technologies that help businesses and households optimize energy use. The relevance of the activities of Schneider Electric has increased with the increasing demand for electrical power with the surge in data center and electrical power demand. The company operates in more than 100 countries and is one of the global leaders in electrical equipment and industrial solutions.

Schneider Electric Singapore

After a year of study at Nanyang Business School in Singapore, I joined Schneider Electric’s Singapore office as an intern. As a French citizen, I obtained a Work Holiday Pass (WHP), which allowed me to remain in Singapore for six months. The building itself showcases Schneider Electric’s expertise in energy management and automation, being partly powered by renewable energy and retrofitted with energy-efficient systems.

Schneider Electric Singapore Kallang offices also called “Kallang Pulse”
Schneider Electric Singapore Kallang office
Source: Schneider Electric Singapore.

Global Supply Chain Finance Manufacturing

Quarterly reporting

During my 6 months internship I integrated the Finance team of the Global Supply Chain (GSC) division of Schneider Electric Singapore. The Finance division plays a central role in the creation of financial forecasts and accurate financial reporting for both internal and external purposes. The primary goal in quarterly reporting is to provide reliable financial data that reflects the performance of operations across regions and business units. The quarterly results are the fruit of the cooperation between the Finance Business Partners (FBPs) and accounting teams of Schneider Electric in several East Asian countries (Thailand, Vietnam, Indonesia, etc.). Finance Business Partners (FBPs) play a coordination role in the process of quarterly reporting and ensure the accuracy of financial statements with regard to manufacturing realities.

Standardization of financial reporting across East Asia

As an intern at Schneider Electric Singapore I contributed to the standardization of financial reporting across East Asia (EA). The process of standardization of financial reporting is key to make comparable metrics. The harmonization of cost centers reduces errors and improves efficiency and was done through direct communication with Finance Business Partners and accountants. Over the course of my internship cost centers were standardized meaning that entities would report similar type costs under the same line item (code number). Overall the work of the Finance team contributed to support more accurate decision-making.

In factory missions

The Schneider Electric Singapore GSC Finance team works closely with the factories/plants of the region. During my internship I had the opportunity to visit plants in Singapore and Indonesia. The proximity with employees on site allowed for more accurate tracking of material flows and stock levels, reducing discrepancies between financial records and actual usage. By monitoring inventories closely, the team maintained a balance between cost efficiency and operational continuity. The finance team places strong value on visits and human contact as part of its role within the Global Supply Chain.

Excel methods

The Finance team relied on advanced Excel techniques. During my internship, I used Power Query to build dynamic spreadsheets that cleaned and transformed large datasets and presented information for easy comparisons. Schneider Electric leverages SAP databases, so I also extracted internal data using Data Format Layout (DFL) to support analysis.

Transversal role

In addition to my core finance responsibilities, I had the chance to explore other parts of the global supply chain, particularly Procurement. In Procurement, the team validates supplier cost structures and reconciles material prices against assumptions. One of my missions was to perform some data analysis on a very large data set. My analysis gave the tools to Procurement to negotiate more effectively with suppliers.

Nomenclature

Purchase Orders (POs): Formal documents issued by a buyer to a supplier to authorize a purchase, specifying items, quantities, and agreed prices. The Global Supply Chain (GSC) finance team is sometimes brought to analyse samples of them.

Consolidated Standard Costing (CSC): A unified costing method that standardizes cost structures across plants or regions, enabling consistent financial comparisons.

Base vs. Variable Costs:

  • Base costs (fixed costs) remain stable regardless of production volume (e.g., rent, salaries, depreciation).
  • Variable costs fluctuate with activity or output (e.g., raw materials, utilities, logistics).

Steps of the Purchase Process: Typically include requisition, approval, purchase order issuance, supplier confirmation, delivery, and invoice/payment processing.

Lean manufacturing

Beyond financial forecasting and reporting, the GSC Finance team in Singapore has adopted a systematic philosophy when working on projects. My mentor was an advocate of Six Sigma Lean Manufacturing principles. These principles include reducing variability and defects, relying on data-driven analysis and structured steps such as DMAIC (Define, Measure, Analyze, Improve, Control). The application of lean manufacturing principles increased the efficiency of processes. During my internship I passed some internal training and obtained my green belt of six sigma. An example of six sigma lean manufacturing was a project to create an app that allows to track inventories and makes auditing more reliable and efficient.

Conclusion

My internship at Schneider Electric Singapore was more than a professional experience — it was a learning journey. I discovered how finance is not only about producing figures but also about supporting operations and connecting people across cultures.

Why should you be interested in this post?

If you are curious about how finance operates at the crossroads of global supply chains, this post offers a concrete view from inside Schneider Electric’s East Asia hub. Beyond numbers, it shows how financial teams play a transversal role in harmonizing reporting across countries.

About the author

The article was written in September 2025 by William LONGIN (Sorbonne School of Economics, Master in Money Banking Finance Insurance, 2024-2026)

Excel Dashboards in HR and Finance: Visualizing Data for Smarter Decision-Making

 Snehasish CHINARA

In this article, Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025) describes the benefits of using Excel dashboards in human resources (HR) and financial management.

Also, how Excel dashboards help to accurately evaluate, clearly display and efficiently analyze important key figures such as fluctuation, absences, turnover or cash flow.

What is an Excel dashboard (for example in the HR or finance department)?

Excel dashboard in HR management or finance department is a visual analysis tool that provides a clear overview of important key figures in a company. These include, for example: key personnel figures, employee absences, fluctuation and more. It helps the HR department in the company to quickly evaluate data and ensure that everything is accurate, helping them to make the right decisions. With the help of tables or diagrams and the right formatting, important information can be captured, and anomalies are quickly visible. Dashboards save time, increase transparency and support data-based personnel management.

Advantage

How can Excel dashboards be an advantage in finance?

Excel dashboards offer a number of advantages in finance, for example, the ability to filter and update data at any time, providing a clear and transparent overview of the various financial developments. The use of Excel dashboards in a company promotes transparency in areas such as income, expenses, budgets and forecasts, which is very important for the controlling and HR departments. Another important reason why Excel dashboards are beneficial in a company is that dashboards can play a major role in important decisions, as they clearly show important key figures such as cash flow, profit margins or ROI. Dashboards also save a company an enormous amount of time when processing data.

Key components and application areas of financial dashboards in Excel

A financial dashboard shows all relevant key figures to present the financial situation of a company as simply and comprehensibly as possible. Among other things, a financial dashboard shows the development of turnover over various periods of time and also provides a detailed cost analysis, breaking down into fixed and variable costs. Other important components that a financial dashboard shows are the profit and loss statement, cash flow overviews and key financial figures such as ROI or liquidity ratios. Excel dashboards are used in numerous areas such as controlling, financial planning, capital budgeting and reporting. They support employees in the respective departments in their analyses and strategic decisions through the acquired data they find there.

Efficient data processing and analysis with Excel tools and functions

Excel provides a variety of tools and functions that simplify the processing of data and provide a clear overview. The useful tools and functions include, for example, tables and charts, which enable flexible and dynamic data analysis in companies, slicers and timeline filters facilitate control. Formulas and functions such as “IF” or “INDEX” can be used to perform calculations and automatically adapt to changes. Another important point regarding the efficient use of Excel dashboards is the help of Power Query and Power Pivot, which allows large amounts of data to be easily and efficiently evaluated, adjusted, imported or modalized.

To summarize

It is a great advantage for companies to introduce Excel dashboards into their departments, especially in departments such as HR and financial management. They help to work more efficiently and simplify processes, create a clear and transparent overview of data processing and visualize important key figures such as employee turnover, absenteeism, sales or cash flow.

Thanks to the elements and functions such as filters, charts, pivot tables, Power Query and Power Pivot offered by Excel Dashboards, the large and unclear amount of data can be filtered, analyzed and updated in a targeted manner so that the data is as up to date as possible.

Excel dashboards also promote strategic planning and save valuable time when creating reports. They support data-based management, are flexible and cost-effective for the company and save time.

Why should I be interested in this post?

As an ESSEC student, this article may be of interest because it shows how Excel dashboards in HR and finance can contribute to data-based decision-making and the important role they play in a company. Tools such as Excel dashboards are an important component in today’s world and a skill that is in great demand both in studies and in the professional world, as Excel dashboards help to analyze processes efficiently and present important key figures in an understandable way.

Related posts on the SimTrade blog

   ▶ Alisa-Arifa AGALI ABDOU TOURÉ My Experience at DHL- Bremen in the HR department

About the author

The article was written in August 2025 by Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025).

My Experience at DHL- Bremen in the HR department

 Snehasish CHINARA

In this article, Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025) shares her professional experience as an intern at DHL.

About the company

DHL was founded in San Francisco in 1969 by Adrian Dalsey, Larry Hillblom and Robert Lynn. The company’s global headquarters are located in Bonn, Germany. In 1998, Deutsche Post AG began the takeover and fully integrated DHL into the Group in 2002, which today operates under the name DHL Group.

HR DHL
Logo of DHL
Source: the company.

My internship

During my time in the HR department at DHL Bremen, I was able to gain valuable insights, for example, I was able to see and understand the HR processes. The department is responsible for several aspects such as recruiting & onboarding, employee support, payroll accounting and supporting personnel development. In a company as large as DHL, the HR team ensures smooth communication between management and employees within the company.

My Mission

My internship involved a range of responsibilities, including employer branding & engagement, administrative support for employees, and the recruiting process.

  • Employer Branding & Engagement: Participation in employee events, surveys and employee retention initiatives
  • Administrative support for employees: planning, maintaining sick notes and absences, master data management
  • Recruiting process: This includes determining requirements, creating job advertisements and organizing structured onboarding for the successful integration of new employees.

What have I learned

During my time at DHL in Bremen, I was able to get to know important processes that I had already learned theoretically during my studies, but was able to apply practically in my job in the HR department. I was able to get to know processes such as how recruiting, onboarding and personnel administration are developed. I learned how important it is to plan vacation and absence management as accurately as possible and how important it is for the company that everything happens as smoothly as possible. I was also able to expand my knowledge in the areas of personnel budget planning, fluctuation rates and remuneration models. The close cooperation with different departments and employees was particularly valuable for me. I was able to learn a lot of new things and apply and expand my existing skills and knowledge.

Required skills

The position requires communication and organizational skills. To be able to plan and organize employee events as accurately as possible, this requires precise analysis, coordination of surveys to meet the expectations and wishes of the employees. It also requires knowledge in the administration of personnel planning, such as vacation planning, sick leave and absence control. Another important skill for this position is working together as a team to determine requirements, create job descriptions and organize a structured onboarding process. Teamwork and empathy are also very important.

Business concepts related to my internship

Personnel budget planning

An important financial concept in HR activities is personnel budget planning, HR key figures, salary structures and remuneration models. Personnel budget planning is an important component of strategic HR work. Personnel budget planning shows exactly what budget is available to the company in relation to personnel costs. Costs such as salaries, social security contributions, recruiting costs and others are planned and allocated for the year. It is important to plan this as accurately as possible in order to avoid staff shortages and act as efficiently as possible. The HR department works very closely with the Controlling department, the planning of the budget is an important point for an efficient and sustainable personnel strategy.

HR key figures

HR KPIs include the analysis of key figures such as turnover rate. The turnover rate describes the number of employees who voluntarily or involuntarily leave the company in a year. It is also an important aspect, as it reflects the stability and satisfaction of employees. In addition, the turnover rate must always be kept in mind, as a high fluctuation rate can indicate structural problems in the company. If you have this well under control, you can avoid additional costs in the company.

Salary structures and remuneration models

Remuneration must be planned as accurately and appropriately as possible. Salary structures and remuneration models lead to fair remuneration management in the company. The salary structures and remuneration models determine how the employees’ salaries are composed, including aspects such as the employee’s position and function, experience and qualifications. The Salary structures and remuneration model also incorporates active plus points such as awards and bonuses. This serves to increase the motivation of existing employees and to attract new employees for various positions.

Why should I be interested in this post?

As an ESSEC Business School student, the position at DHL can be very interesting, as the company shows you how theoretical knowledge from the areas of HR, controlling and organization is applied in practice in the company. In the company, you gain valuable insights into various areas such as recruiting, personnel budget planning and employer branding, giving you valuable insights into strategic HR work in an international group.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

Useful resources

careers.dhl.com/global/en/job/

About the author

The article was written in August 2025 by Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025).

My internship at the law firm Maître Abouba Aly Maiga et Associés

 Snehasish CHINARA

In this article, Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025) shares her professional experience as an intern at the law firm Maître Abouba Aly Maiga et Associés in Mali.

About the company

The law firm was founded in 1990 by Mr. Maître Abouba Aly Maiga. Since then, the firm has provided services in a wide range of legal fields. The areas of law offered by Maître Abouba Aly Maiga and Associes are commercial law, business law, national and international criminal law, administrative law, matrimonial law, labor law and international law. One of the reasons for the firm’s success is that it offers its clients services in various areas of law.

Logo of the law firm Abouba Aly Maiga et Associés.
Logo of Maître Abouba Aly Maiga et Associés
Source: the company.

The firm represents not only civilians but also, for example, ministers, soldiers and large companies and deals with international relations and litigation. Maître Abouba Aly Maiga began his career in Bamako, Mali. In addition to the firm, he is the first Vice President and President Africa of the International Bar Association and Vice President of the A.E.A. (European Bar Association), he is also a former member of the Council of the Order.

My internship

My 6 months of my internship abroad at the law firm was an extremely valuable experience for me and gave me a deep insight into a law firm. During my time there, I was able to take part in many exciting and enriching tasks that not only helped me professionally, but also personally. In particular, the work in the field of corporate law and international law as well as the participation in court proceedings and hearings have shaped me a lot and broadened my view of legal practice.

My missions

During my internship at the law firm, I had a variety of tasks that gave me a deep insight into the day-to-day work of a law firm and showed me what the process in a law firm is like. My tasks included, for example, taking part in client meetings and helping lawyers to develop individual legal solutions. Another important insight was to see how professional client communication works.

Another task I was allowed to take on during my internship at the law firm was to read case files and follow legal processes, especially in the areas of corporate and international law. I regularly attended court hearings, where I was able to experience the lawyers’ argumentation strategies first-hand. Furthermore, I was able to learn the practical handling of complex cases. In addition, I prepared the team meetings and created presentations, took minutes and thus contributed to the internal communication of the law firm.

Required skills and knowledge

Certain skills and knowledge were particularly important for my internship at the Law firm Maître Abouba Aly Maiga. These included basic knowledge of international and corporate law, and a good understanding of legal structures and procedures. Another important point is strong communication skills and intercultural competence to work successfully with colleagues and clients from different backgrounds.

Language skills, especially in French, were also very helpful in order to be able to actively participate in discussions and court hearings. In addition, strategic thinking, initiative, confidentiality in dealing with sensitive information and confident use of digital tools were also important skills.

What I learned

During my internship, I was able to gain valuable insights, such as the internal processes of an international law firm, and I was able to apply my theoretical knowledge from my studies in practice. Especially the work in the area of international and corporate law helped me to better understand the processes. I was also able to improve my French language skills through daily exchanges with colleagues and clients. Overall, I learned to act more confidently in a new environment and to adapt flexibly to different professional and cultural situations.

Financial concepts related to my internship

I present below three financial concepts related to my internship: invoicing and cost management, SWOT analysis for strategic planning, and client retention through advertising and pricing.

Invoicing and Cost Management

During my internship, I was made aware of the importance of structured invoicing for a law firm’s cash flow. Accurate documentation of services rendered, and timely invoicing are crucial to ensure regular income for the law firm. Efficient cost management was a key issue at the law firm, as the firm constantly strives to control and document its expenditure, for example on personnel, technology and office infrastructure. A good cost structure has a direct impact on the profit margin and competitiveness in the market.

Strategic Planning using SWOT Analysis

Another important point is the SWOT analysis. Through the SWOT analysis, I quickly understood how financial opportunities and risks are identified and integrated into strategic planning. Aspects such as investing in technology or recognizing threats from cheaper online law firms play an important role.

Client Retention through Advertising and Pricing

Targeted advertising campaigns and appropriate prices are effective ways of retaining customers in the long term and ensuring financial stability. It was particularly important to adapt the price structure to the target groups’ willingness to pay in order to ensure financial stability.

Why should I be interested in this post?

As an exchange student ESSEC Business School student, I am interested in the position at Maître Abouba Aly Maiga et Associés because it offers a combination of international business law and strategic thinking. The internship at the law firm offers a very deep insight into the areas of legal work and business aspects such as SWOT analyses or cost management. It is particularly interesting to work on real cases, attend court hearings and carry out financial and legal analyses relevant to the firm and make decisions. The internship is ideal for students who are interested in business law or who want to work at the interface of law and business.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

Useful resources

Cabinet Abouba Aly Maiga et Associés

About the author

The article was written in August 2025 by Alisa-Arifa AGALI ABDOU TOURÉ (ESSEC Business School, Global Bachelor of Business Administration – Exchange student from Germany, 2024-2025).

My professional experience as Head of Data Modelling

Rohit SALUNKE

In this article, Rohit SALUNKE (ESSEC Business School, Grande Ecole Program – Master in Management, 2018-2021) shares his professional experience as Head of Data Modelling, leading advanced analytics, AI, and reporting solutions for a global investment organisation.

About the company

Tikehau Capital is a global alternative asset management group headquartered in Paris, France. Founded in 2004, it has become a multi-billion-euro investment house with expertise across private debt, real assets, private equity, and capital markets strategies. The company manages assets for institutional and private investors worldwide, relying on a long-term investment philosophy and strong entrepreneurial culture.

Tikehau Capital is listed on Euronext Paris and operates in over a dozen countries. Its diversified investment strategies and robust risk management have contributed to consistent growth and resilience across market cycles.

Logo of Tikehau Capital.
Logo of Tikehau Capital
Source: Tikehau Capital.

About the role

As Head of Data Modelling, I was responsible for the strategic design, architecture, and delivery of the organisation’s enterprise-wide analytics infrastructure. My role bridged technology, quantitative modelling, and business strategy, ensuring that investment, risk, and operational teams had access to powerful, automated, and reliable data-driven tools. I oversaw the entire lifecycle of data and analytics projects—from ideation and design to deployment and continuous improvement—while directly coordinating with C-level executives and department heads to align technology solutions with organisational goals.

My Experience

My core responsibility was managing the architecture of our Databricks and PowerBI/Python reporting ecosystem, making it the central platform for the organisation’s portfolio analytics and operational reporting. I led the data strategy for our IT-Quant Cell, which served as a specialised unit delivering high-value analytics to investment and risk teams across multiple asset classes.

One of my most impactful projects was the full-stack development of an AI assistant for answering investor due diligence questionnaires (DDQs). This system combined Databricks Genie with open-webui, enabling internal teams to query complex datasets interactively. Additionally, I built NLP-based solutions to parse and extract information from unstructured documents—such as contracts, company filings, and financial statements—streamlining internal research and reporting workflows.

On the quantitative modelling front, I developed a bond valuation engine capable of pricing both individual securities and portfolios, as well as default probability models for issuers and securities. These tools allowed risk managers to proactively identify watchlist names, foresee covenant breaches, and anticipate coupon defaults. I also delivered full-stack stress testing and credit spread models for private debt and distressed debt portfolios, enabling portfolio managers to assess market scenarios and security-level risks with precision.

For cash flow management, I designed a forecasting engine tailored to private debt portfolios, integrating it with operational and client service functions to automate forecast reporting for investors. I also led the development of large-scale automated reporting solutions capable of generating PDF, PPTX, Word, and Excel outputs, meeting the regulatory and investor requirements of multiple jurisdictions.

Collaboration and Leadership

My role demanded close coordination with the CTO, COO, CFO, department heads, and technical leads to define priorities, allocate resources, and ensure delivery. I managed multi-departmental projects spanning Risk, Investment, Operations, Sales, and Finance, as well as asset class–specific initiatives in Private Debt and Equity, Fixed Income, CLOs, and Real Estate. This cross-functional exposure ensured our solutions were both technically sound and operationally relevant.

Beyond technical delivery, I implemented interactive dashboards for risk monitoring, fundraising, investor onboarding, and portfolio analytics—empowering top management, risk managers, and portfolio managers with actionable insights. I also provided mentorship to analysts and senior executives, guiding them through the adoption of new tools, processes, and workflows.

Required skills and knowledge

This role required deep expertise in data architecture (Databricks, SQL), advanced analytics (Python, NLP, quantitative finance), and visualisation (PowerBI). The ability to translate complex business needs into scalable, maintainable, and user-friendly systems was critical. Equally important were leadership and stakeholder management skills, enabling me to bring together technical and non-technical teams to achieve common objectives.

What I learned

In this position, I learned how to combine cutting-edge technology with robust quantitative frameworks to address the evolving demands of a global investment business. I developed a stronger appreciation for the balance between innovation and operational stability—ensuring that every model, dashboard, or AI system could be trusted by those making high-stakes decisions. Most importantly, I saw firsthand how data strategy, when aligned with business objectives, can transform portfolio monitoring, risk management, and investor communication.

Financial concepts related to my role

Credit spread modelling

Credit spread modelling is the process of estimating the additional yield or premium investors require to compensate for the credit risk of a bond or loan compared to a risk-free benchmark, typically government securities. This spread reflects the market’s perception of the issuer’s default risk, liquidity risk, and other factors affecting creditworthiness. In my role, I built sophisticated credit spread models that integrated multiple layers of data, including macroeconomic variables (such as interest rates, GDP growth, and inflation), issuer-specific fundamentals (like leverage ratios, profitability, and cash flow stability), and real-time market indicators (credit default swap spreads, bond prices, and trading volumes). These models enabled risk managers and portfolio managers to estimate fair value spreads, detect deviations from expected spreads, and identify mispriced securities. The ability to quantify and forecast credit spreads was critical for pricing, risk management, and strategic asset allocation across private debt and distressed debt portfolios.

Stress testing

Stress testing involves evaluating how a portfolio or individual securities would perform under severe but plausible adverse market conditions. It is a key risk management tool that helps identify vulnerabilities and potential losses in extreme scenarios, such as economic recessions, interest rate shocks, or credit market disruptions. I developed full-stack stress testing models that allowed users to apply shocks and scenario analyses both at the individual security level and the aggregated portfolio level. These models incorporated changes in key variables including interest rates, credit spreads, default rates, and macroeconomic indicators. By simulating various stress scenarios, investment and risk teams could assess the resilience of portfolios, anticipate potential covenant breaches or defaults, and plan mitigation strategies. This was especially important for private debt and special opportunities portfolios, where cash flows and valuations can be highly sensitive to changing market environments.

Default probability modelling

Default probability modelling quantifies the likelihood that an issuer or specific security will fail to meet its financial obligations within a defined time horizon. Accurate default prediction is fundamental to credit risk management, pricing, and portfolio construction. I designed models leveraging a combination of financial statement ratios (such as debt coverage, liquidity, and profitability metrics), market-based indicators (equity volatility, credit spreads), and qualitative industry or sector factors to generate forward-looking default probabilities. These models powered watchlists and early-warning systems, enabling portfolio managers to identify issuers at risk of covenant breaches, coupon defaults, or bankruptcy. By anticipating potential defaults, the investment teams could proactively adjust exposures, engage with issuers, or hedge positions, thereby reducing portfolio losses and improving overall risk-adjusted returns.

Why should I be interested in this post?

This post offers valuable insights for students and professionals keen on the intersection of quantitative finance, data architecture, and AI-driven solutions within the asset management industry. It illustrates how leadership in data modelling and technology can directly impact critical investment functions such as portfolio strategy, risk assessment, and investor communications. Understanding how sophisticated models and automated analytics tools are developed and deployed equips aspiring quants, data scientists, and financial engineers with a clearer picture of real-world applications beyond theory—highlighting the importance of cross-functional collaboration, scalable system design, and continuous innovation in today’s complex financial markets.

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Useful resources

Academic articles

Duffie, D., & Singleton, K. J. (2012). Credit Risk: Pricing, Measurement, and Management (illustrated edition). Princeton, NJ: Princeton University Press.

Business resources

Tikehau Capital

Tikehau Capital Solutions

Claessens S., Pazarbasioglu C., Laeven L., Dobler M., Valencia F., Nedelescu O., and Seal K. (2011) Crisis Management and Resolution: Early Lessons from the Financial Crisis, IMF

Preqin Alternative data platform

BlackRock eFront – Portfolio Management Solution

About the author

The article was written in August 2025 by Rohit SALUNKE (ESSEC Business School, Grande Ecole Program – Master in Management, 2018-2021).

My professional experience as Business & Data Analyst at Tikehau Capital

Rohit SALUNKE

In this article, Rohit SALUNKE (ESSEC Business School, Grande Ecole Program – Master in Management, 2018-2021) shares his professional experience as Business & Data Analyst at Tikehau Capital.

About the company

Tikehau Capital is a global alternative asset management group headquartered in Paris, France. Founded in 2004, it has become a multi-billion-euro investment house with expertise across private debt, real assets, private equity, and capital markets strategies. The company manages assets for institutional and private investors worldwide, relying on a long-term investment philosophy and strong entrepreneurial culture.

Tikehau Capital is a public company listed on Euronext Paris and operates in over a dozen countries. Its diversified investment strategies and robust risk management have contributed to consistent growth and resilience across market cycles.

Logo of Tikehau Capital.
Logo of Tikehau Capital
Source: Tikehau Capital.

I worked in the Information & Technology (IT) department of Tikehau Capital, and collaborated extensively across various teams within the organisation. My projects focused on building tools and processes that directly supported investment decision-making and portfolio monitoring.

My Experience

As a Business & Data Analyst in the IT department, my role was to design, develop, and deploy technology solutions for the company. I collaborated with several stakeholders such as Investment team, Risk, Operations, Sales and Marketing, Client Services and Top Management. Within the Investment teams I touched on topics across the TKO strategies, Private Debt, Private Equity, Tactical Strategies, Real Assets and Capital Market Strategies. This included working closely with investment professionals to understand their analytical needs and then translating those into scalable, automated systems for data processing, quantitative analysis and reporting.

My missions

As the technical lead and subject matter expert for a major digitisation project in an agile environment, I drove revenue and productivity enhancements through automation, data analysis, and improvements in data quality and reporting. My role involved analysing TKO’s portfolio of private investments, building automated reporting engines, developing quantitative analytics modules for portfolio monitoring, and creating ETL pipelines to consolidate data from multiple internal and external sources. I collaborated extensively across functions—including Sales, Product, Marketing, Finance, Client Services, Fund Operations, Risk, Investment, Private Debt, Private Equity, and Real Estate—to ensure the successful delivery of technology solutions aligned with business needs.

Key projects included: developing quarterly investor reporting automation tools for several business units (Python, Databricks, Microsoft PowerPoint, Word, Excel); leading the private markets data migration to Databricks and introducing company-wide KPI harmonisation, boosting efficiency by 12x; implementing dashboards for use by both cross-functional teams and top management (Databricks, PowerBI); and automating report delivery to clients (Power Automate). I also led analysts through project lifecycles, providing coaching to both junior and senior team members on in-house and external tools.

From an analytics perspective, I delivered asset performance analyses across funds and asset classes, supported fundraising and investor onboarding analytics, conducted risk assessments on asset performance under economic stress, and developed in-house benchmarking for Private Debt funds in collaboration with external partners. On the investor relations side, I handled institutional investor performance reporting requests. For data quality, I monitored internal platforms, managed escalation processes, and mitigated risks, issues, and dependencies to maintain the integrity and reliability of critical datasets.

Required skills and knowledge

In my role at Tikehau Capital, I developed a combination of technical, analytical, and cross-functional skills that enabled me to deliver technology solutions supporting investment decision-making across multiple asset classes. One of the key technical skills I applied was advanced programming in Python and SQL, which I used to design ETL pipelines, automate reporting processes, and integrate data from multiple sources into Databricks. I also gained deep expertise in dashboard creation and visualisation using PowerBI, allowing me to present complex portfolio performance metrics in a clear and actionable format for both senior management and investment teams.

I strengthened my understanding of private markets data structures, particularly within private debt, private equity, and real estate. This included learning how to manage and standardise KPIs across the organisation to ensure consistency in reporting and analysis. My work required strong knowledge of data governance and quality control, as I was responsible for monitoring internal platforms, managing data integrity issues, and implementing processes to improve accuracy and reliability.

On the soft skills side, I honed my ability to gather business requirements from diverse stakeholders and translate them into technical specifications. This meant working closely with colleagues from Sales, Product, Marketing, Finance, Client Services, Fund Operations, Risk, and Investment teams in an agile environment. I also developed leadership skills by guiding analysts through the project lifecycle and providing coaching to both junior and senior professionals on the use of in-house and external tools. Finally, I gained significant experience in investor relations support by preparing data for performance reporting, responding to institutional investor requests, and ensuring clear, professional communication of complex investment information.

What I learned

One of the most valuable lessons I learned at Tikehau Capital was how technology teams can act as strategic partners to investment teams across multiple asset classes, including Private Debt, Private Equity, Capital Market Strategies (CMS), Tactical Strategies, and Real Assets. Working in the IT department while collaborating closely with investment specialists taught me how to align technical solutions with diverse investment strategies and operational requirements. For example, during the digitisation project, I learned how to translate complex business requirements from each asset class into scalable automation, analytics, and reporting tools that directly improved portfolio monitoring, decision-making, and investor communication.

I gained a deeper understanding of asset class–specific analytics: in Private Debt and Private Equity, I worked on performance tracking, KPI harmonisation, and risk analytics; in CMS and Tactical Strategies, I learned how derivative positions and macro-driven strategies required different data models and stress-testing frameworks; and in Real Assets, I helped design systems that tracked physical asset performance alongside market and operational metrics. This cross-asset exposure enhanced my ability to adapt technical workflows to varied investment approaches.

From a technical perspective, I refined my proficiency in Python, SQL, Databricks, and PowerBI, using them to build ETL pipelines, automation workflows, and dashboards that served both analysts and senior management. I also honed my problem-solving skills by identifying bottlenecks in reporting processes and implementing solutions that improved efficiency by more than 10x in some areas. Additionally, I learned the importance of outcome evaluation—ensuring that every dataset, whether for an internal management dashboard or an institutional investor report, was accurate, consistent, and presented in a clear, actionable format tailored to the needs of each asset class.

Financial concepts related to my internship

I present below three financial concepts related to my internship and how they were applied in my work at Tikehau Capital: Portfolio monitoring, Credit risk metrics, and Cash flow forecasting.

Portfolio monitoring

Portfolio monitoring is the ongoing process of tracking an investment portfolio’s performance, risk profile, and compliance status to ensure it aligns with its strategic objectives. This involves assessing metrics such as returns, volatility, drawdowns, asset allocation shifts, and adherence to investment guidelines. Effective portfolio monitoring enables timely decision-making, allowing managers to rebalance, hedge, or adjust positions in response to market movements or changes in portfolio objectives. During my time in the IT department working closely with investment specialists across private debt, private equity, CMS strategies, tactical asset allocation, and real assets, I learned how technology can streamline this process. The reporting engines I built automated large parts of the workflow—integrating data from multiple sources, applying valuation models, and generating performance dashboards—allowing investment teams to access accurate, real-time insights without the delays and potential errors of manual data handling. This experience deepened my understanding of how portfolio monitoring supports not only performance measurement but also risk management, regulatory compliance, and informed strategic decision-making.

Credit risk metrics

Credit risk metrics are quantitative and qualitative measures used to evaluate the likelihood that a borrower will default on their obligations and to estimate the potential loss to the portfolio in such an event. These metrics include probability of default (PD), loss given default (LGD), exposure at default (EAD), credit spreads, and internal credit ratings, all of which help investment teams assess both individual counterparty risk and overall portfolio vulnerability. Accurate credit risk assessment is essential for pricing loans, structuring debt instruments, and determining capital allocation. While working closely with investment specialists across private debt, private equity, CMS strategies, tactical strategies, and real assets, I developed tools that integrated multiple credit risk data feeds into interactive dashboards. These systems consolidated financial statement data, market indicators, and external credit ratings into a unified view, enabling faster and more reliable risk assessments. By automating data aggregation and providing visual, real-time insights, these tools not only improved assessment accuracy but also allowed portfolio managers to respond more proactively to emerging credit concerns.

Cash flow forecasting

Cash flow forecasting is the process of estimating the timing and magnitude of future inflows and outflows for an investment or portfolio. It is essential for assessing expected returns, ensuring sufficient liquidity to meet obligations, and supporting capital allocation decisions. Accurate forecasting allows investment teams to anticipate funding needs, optimise debt schedules, and stress test portfolios under different market conditions. This is particularly important in asset classes such as private debt, private equity, CMS strategies, tactical strategies, and real assets, where cash flows can be irregular and heavily dependent on deal structures, economic cycles, and market events. To support this, I built ETL pipelines that extracted deal-level data from multiple internal and external sources, transformed it into a consistent structure, and integrated it with dynamic forecasting models. These pipelines enabled investment teams to perform real-time scenario analyses, adjusting for variables such as interest rate changes, market shocks, and asset performance trends. By automating data preparation and linking it directly to forecasting tools, the process became faster, more transparent, and more adaptable to shifting market conditions.

Why should I be interested in this post?

For ESSEC students interested in finance and technology, this experience shows how a role in IT within an investment firm can offer direct exposure to financial markets, portfolio analytics, and data-driven decision-making—skills highly valuable in both finance and quantitative career paths.

Related posts on the SimTrade blog

   ▶ All posts about Professional experiences

   ▶ Alexandre VERLET Classic brain teasers from real-life interviews

Useful resources

Academic articles

Altman, E. I., & Saunders, A. (1997). Credit risk measurement: Developments over the last 20 years, Journal of Banking & Finance, 21(11–12):1721–1742.

DeFond, Mark L. & Hung, Mingyi. (2003). An empirical analysis of analysts’ cash flow forecasts, Journal of Accounting and Economics, 35(1):73–100.

Business resources

Tikehau Capital

Tikehau Capital Solutions

Preqin Preqin – Alternative data platform

BlackRock eFront – Portfolio Management Solution

About the author

The article was written in August 2025 by Rohit SALUNKE (ESSEC Business School, Grande Ecole Program – Master in Management, 2018-2021).

Academic perspectives on optimal debt structure and bankruptcy costs

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025) explores the academic evolution of capital structure theory, focusing on the delicate balance between debt and equity financing. Starting from the foundational Modigliani and Miller propositions, this post delves into how the introduction of real-world frictions—particularly bankruptcy costs and financial distress—gave rise to the Trade-Off Theory.

Introduction to Capital Structure

Capital structure refers to the mix of debt and equity financing that a company uses to fund its operations and growth. It is a critical component of corporate finance, as it directly impacts a firm’s cost of capital, financial risk, and overall valuation.

Capital structure is reflected in a company’s balance sheet, which provides a snapshot of its financial position at a given point in time. Specifically, it is composed of two primary financing sources:

1. Debt (Liabilities) – Found under the Liabilities section, debt includes short-term borrowings, long-term loans, bonds payable, and lease obligations. Debt financing requires periodic interest payments and repayment of principal, increasing financial obligations but also benefiting from potential tax shields.

2.Equity (Shareholders’ Equity) – Located under the Shareholders’ Equity section, equity includes common stock, preferred stock, retained earnings, and additional paid-in capital. Equity financing does not require fixed interest payments but dilutes ownership among shareholders.

Table 1 below gives a simplified version of a balance sheet.

Table 1 – Simplified Balance Sheet Example

Table 1 shows that the firm finances its $350M in assets with $140M in debt (40%) and $210M in equity (60%), demonstrating a debt-to-equity ratio of 0.67 (=140/210). Additionally, the debt ratio, D/(D+E), measures the proportion of total financing that comes from debt 40% (=140/(140+210)). This indicates that a significant portion of capital is funded through borrowed money, allowing the company to take advantage of the use of debt, but also exposing it to higher financial risk if it faces difficulties in meeting debt obligations. These ratios are a few key indicators used to assess a company’s financial leverage and risk exposure.

Beyond Taxes — The Real-World Cost of Debt

Capital structure theory begins with Modigliani and Miller (1958), who argued that in a perfect market—with no taxes or distress costs—a firm’s value is unaffected by its mix of debt and equity. This implies that financing decisions are irrelevant: the firm’s cost of capital remains unchanged regardless of leverage.

Their later work in 1963 introduced corporate taxes, shifting the narrative. Since interest is tax-deductible, debt creates a tax shield that reduces taxable income, lowering the firm’s WACC and increasing its value. In theory, this would mean the more debt a firm uses, the better.

However, this doesn’t match real-world behaviour. Firms rarely use excessive debt. To explain this, Miller (1977) brought personal taxes into the picture. While firms benefit from interest deductibility, investors may face higher taxes on interest income compared to equity income. This reduces the net benefit of debt. At the market level, an equilibrium emerges where additional debt offers no further advantage—explaining why firms stop before 100% leverage.

Together, M&M and Miller show why debt can be attractive due to tax savings—but they don’t account for the costs of debt, which are crucial in practice. This article now turns to academic perspectives that build on these theories by introducing bankruptcy costs, financial distress, and agency issues, offering a more complete view of how firms decide on an optimal capital structure.

The Trade-Off Theory: Balancing Tax Shields and Bankruptcy Costs

While M&M (1963) and Miller (1977) emphasize the tax advantages of debt, real-world firms don’t pursue unlimited leverage. Why? Because with higher debt comes higher financial risk. This leads to the Trade-Off Theory—a more realistic and widely taught framework in modern corporate finance.

At the heart of this theory lies a simple question: How much debt is too much?

The Trade-Off Theory proposes that firms weigh the benefits of debt (primarily the interest tax shield) against the costs of debt (most notably bankruptcy risk and financial distress costs). The optimal capital structure is achieved when the marginal benefit of taking on more debt equals its marginal cost. Therefore, firms pick capital structure by trading off the benefits of the tax shield from debt against the costs of financial distress (including agency costs of debt).

This framework leads to a simple but powerful relationship:

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

  • Tax shield benefits: arising from the tax deductibility of interest payments

  • Expected bankruptcy cost: a function of both the probability of distress and the magnitude of associated losses (probability of distress x cost if distress occurs)

The Trade-Off Theory argues that the value of a firm initially increases with debt due to tax savings from interest deductibility, but only up to a point. Beyond that, the probability of bankruptcy and the costs associated with financial distress begin to outweigh the benefits of the tax shield. Due to this, there exists an optimal capital structure where the marginal benefit of debt exactly equals its marginal cost.

Tax shield benefit: This term represents the annual tax saving due to deductible interest.

where:

  • TC: Corporate tax rate

  • rD: Interest rate on debt

  • D is the amount of debt of the firm

Expected Bankruptcy Cost:

This cost includes:

  • Direct costs (legal, administrative): typically 2–5% of firm value

  • Indirect costs (reputation, supplier reactions, customer attrition): potentially far higher

How Firm Value Changes with Debt

According to the Trade-off Theory, the total value of a levered firm equals the value of the firm without leverage plus the present value of the expected tax savings from debt, less the present value of the expected financial distress costs.

It is represented as follows:

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

Firms should increase leverage until they reach the optimal level where the firm value (and the net benefit of debt) is maximized. At the optimal leverage, the marginal benefits of interest tax shields that result from increasing leverage are perfectly offset by the marginal costs of financial distress.

Figure 1 – Trade-Off Theory Optimal Leverage

Source: “The Static Theory of Capital Structure” Brealey, Myers, & Allen

Figure 1 above illustrates the Trade-Off Theory of capital structure, which posits that a firm’s value is influenced by two opposing forces: the benefits of debt and the costs of financial distress.

  • The upward-sloping blue line represents the firm’s value if we consider only the corporate tax advantage of debt, where each additional unit of debt increases firm value by the present value of the tax shield (Tc×D). However, this idealized trajectory (as per M&M 1963) does not account for real-world frictions.

  • As leverage rises, so too does the probability of financial distress, bringing with it both direct costs (legal and administrative expenses) and indirect costs (reputation damage, lost sales, supplier concerns). These rising costs are reflected by the gap between the blue and pink curves.

  • The pink curve represents the actual value of a levered firm after subtracting distress costs. It shows the actual value of the firm once these financial distress costs are taken into account. Initially, this curve rises along with the tax shield benefits. But after a certain point, the marginal cost of debt begins to exceed its marginal benefit, causing the curve to flatten and then decline.

  • The pink curve peaks at the point marked D∗—the firm’s optimal capital structure. The point D∗ is the optimal amount of debt where the marginal benefit of the tax shield is exactly offset by the marginal expected cost of financial distress.

  • To the left of D∗, adding more debt increases firm value; to the right of it, further leverage diminishes value. The curve therefore reflects a concave relationship between debt and firm value, with the maximum point corresponding to the firm’s optimal capital structure.

Figure 1 delivers three core insights:

  • Leverage is a double-edged sword—it creates value through tax savings but erodes it through risk.

  • The optimal debt level is not universal—it depends on a firm’s industry, asset type, cash flow stability, and access to capital markets.

  • Real-world capital structure decisions are about finding a balance, not maximizing one benefit in isolation.

Static vs. Dynamic Trade-Off Models: From Simplified Theory to Real-World Complexity

The traditional Trade-Off Theory provides a powerful intuition: firms balance the benefits of debt (tax shields) against its costs (financial distress). However, how firms actually make capital structure decisions over time is more complex than the simple static view. This brings us to an important academic distinction: static vs. dynamic trade-off models.

Static Trade-Off Models: A Snapshot of Capital Structure

A static trade-off model is a one-period, one-time optimization framework. It assumes that a firm evaluates all its financing options at a single point in time and selects the capital structure that maximizes firm value. The firm is thought to instantly move to its optimal leverage ratio and maintain it indefinitely.

This model gives us a clean formula for firm value:

While this is helpful in teaching and early analysis, it oversimplifies real-world decision-making. Firms don’t reset their debt every day based on a formula. Instead, they must plan, adjust, and adapt—which is where dynamic models offer deeper insight.

Dynamic Trade-Off Models: Capturing Real-World Decision-Making

Dynamic trade-off models build on the static framework by recognizing that:

Capital structure is adjusted over time, not all at once. Firms face adjustment costs when issuing new debt or equity (e.g., flotation costs, signaling effects).

Business conditions, tax environments, interest rates, and risk evolve. Managers are forward-looking—they consider not only current benefits and costs but also future risks, taxes, and financing needs.

In these models, the optimal debt level is not a fixed point. Instead, firms operate within a target range of leverage and make gradual adjustments toward it when the benefits outweigh the costs of doing so.

For example:

A firm may not issue new debt today even if it’s slightly under-leveraged, because issuing comes with costs. It might instead wait for a better interest rate, a tax law change, or an internal cash flow event.

Dynamic models are particularly well-captured in the work of:

  • Fischer, Heinkel, and Zechner (1989) – who modelled how firms behave in a stochastic environment where recapitalization is costly.

  • Leland (1994) – who showed that default thresholds and optimal leverage depend on firm value and volatility over time.

Types of Bankruptcy Costs: The Hidden Burden of Excessive Leverage

While tax benefits of debt are quantifiable and immediate, the costs of financial distress—especially bankruptcy—are more nuanced, less visible, and often underestimated. These costs are central to the Trade-Off Theory, and understanding their components is essential for evaluating real-world capital structures.

Bankruptcy costs can be broadly classified into three types:

1. Direct Bankruptcy Costs

These are the explicit, out-of-pocket expenses incurred during legal bankruptcy proceedings.

  • Legal fees, court costs, bankruptcy consultants

  • Administrative expenses, such as auditing and trustee services

Empirical studies suggest that direct costs range from 2–5% of firm value, though they may be higher in complex bankruptcies. While these are easier to measure, they are not necessarily the largest component.

Example: A manufacturing firm with a $500 million valuation that enters Chapter 11 could incur $10–25 million in legal and court-related costs alone.

2. Indirect Bankruptcy Costs

These are opportunity costs or value losses incurred even if bankruptcy does not occur—simply being in distress can harm the business.

  • Loss of customers: Buyers lose trust in a distressed brand.

  • Supplier tightening: Suppliers demand advance payments or withdraw credit.

  • Employee turnover: Top talent exits due to job insecurity.

  • Delayed investments: Management focuses on liquidity over strategy.

Indirect costs are often much larger than direct ones—estimated at 10–20% of firm value in some studies.

Example: A hotel chain facing debt pressure may see a fall in bookings, reduced vendor support, and higher staff attrition—impacting operations even before legal proceedings begin.

3. Agency Costs of Debt

As financial distress increases, so do agency conflicts between debt holders and equity holders.

Two prominent issues are:

  • Asset Substitution Problem – Shareholders may prefer riskier projects with higher upside (but higher default risk) because they capture the gains, while losses are partially borne by creditors.

  • Underinvestment Problem – Highly leveraged firms might pass on positive NPV projects because the gains would go to debt holders, not shareholders. Thus, debt discourages investment when it is most needed.

These agency costs distort management incentives, especially when firms are close to violating debt covenants or already under pressure.

Academic Contributions on Bankruptcy and Alternative Views on Capital Structure

Pecking Order Theory and Information Asymmetry

Contrasting the Trade-Off Theory, Myers and Majluf (1984) introduced the Pecking Order Theory, which prioritizes financing sources based on information asymmetry. Firms prefer internal financing (retained earnings) first, then debt, and issue equity only as a last resort. This hierarchy arises because managers possess more information about the firm’s value than external investors, leading to adverse selection concerns when issuing new equity.

Dynamic Models of Capital Structure

Recognizing that capital structure decisions are not static, researchers have developed dynamic models to reflect real-world complexities. Leland (1994) incorporated factors such as agency costs, taxes, and bankruptcy costs into a continuous-time framework, providing insights into how firms adjust their leverage over time in response to changing conditions.

Human Capital and Bankruptcy Risk

Recent studies have explored the interplay between human capital and capital structure. For instance, research by Berk, Stanton, and Zechner (2010) examines how firms with significant human capital considerations may adopt lower leverage to mitigate the adverse effects of financial distress on their workforce and overall operations.

Empirical Evidence and Contemporary Reviews

Empirical studies have tested these theories across various contexts. For example, research published in the Journal of Finance investigates how bankruptcy risk influences firms’ capital structure choices, revealing an inverse relationship between bankruptcy risk and leverage. Comprehensive literature reviews, such as those by Cerkovskis et al. (2022) and Visinescu and Micuda (2023), provide critical analyses of the evolution and empirical validation of capital structure theories, offering valuable insights for both scholars and practitioners.

Practical Considerations in Capital Structure Decisions

While theories like Modigliani-Miller (M&M), the Trade-Off Theory, and Agency Cost Theory provide useful frameworks for understanding capital structure, real-world evidence shows that firms consider multiple factors beyond theory when making financing decisions. Empirical studies highlight how industries, economic conditions, credit ratings, and market perceptions influence a company’s choice between debt and equity.

Real-World Capital Structure Choices

Empirical research supports the idea that firms do not strictly follow any single capital structure theory but instead balance tax advantages, financial flexibility, and risk. Some key observations from real-world studies include:

  • Myers (1984) found that firms follow a “Pecking Order” when raising funds, preferring internal financing (retained earnings) first, followed by debt, and issuing equity as a last resort due to information asymmetry.

  • Graham (2000) estimated that firms use only about 60% of the potential tax benefits of debt, indicating that firms hesitate to take on excessive leverage due to bankruptcy risks.

  • Frank & Goyal (2009) confirmed that larger, more profitable firms tend to have higher leverage, while smaller, riskier firms avoid debt due to financial distress concerns.

These studies suggest that firms do not maximize leverage, but rather choose a debt level that balances benefits and risks based on firm size, profitability, and market conditions.

Why Should I Be Interested in This Post?

Understanding a firm’s optimal debt structure is essential for anyone involved in finance, strategy, or investment analysis. Whether you’re an investor evaluating risk, a finance professional shaping capital decisions, or a student building foundational knowledge, the trade-off between debt and equity lies at the core of corporate financial strategy. This post offers a deep dive into the academic perspectives on capital structure, highlighting how bankruptcy costs, financial distress, and tax considerations influence real-world financing decisions. By mastering these concepts, you’ll be better equipped to assess firm value, understand risk-return dynamics, and make more informed financial judgments in a world where leverage can both create and destroy value.

Related posts on the SimTrade blog

   ▶ Snehasish CHINARA Optimal capital structure with corporate and personal taxes: Miller 1977

   ▶ Snehasish CHINARA Optimal capital structure with taxes: Modigliani and Miller 1963

   ▶ Snehasish CHINARA Optimal capital structure with no taxes: Modigliani and Miller 1958

   ▶ Snehasish CHINARA Solvency and Insolvency in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Liquidity and Illiquidity in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Solvency & Insolvency : A Link to Bankruptcy Procedures

   ▶ Snehasish CHINARA Chapter 7 vs Chapter 11 Bankruptcies: Insights on the Distinction between Liquidations & Reorganisations

   ▶ Snehasish CHINARA Chapter 7 Bankruptcies: A Strategic Insight on Liquidations

   ▶ Snehasish CHINARA Chapter 11 Bankruptcies: A Strategic Insight on Reorganisations

   ▶ Akshit GUPTA The bankruptcy of Lehman Brothers (2008)

   ▶ Akshit GUPTA The bankruptcy of the Barings Bank (1996)

   ▶ Anant JAIN Understanding Debt Ratio & Its Impact On Company Valuation

Useful resources

US Courts Data – Bankruptcy

S&P Global – Bankruptcy Stats

Statista – Bankruptcy data

About the author

The article was written in July 2025 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025).

Optimal capital structure with corporate and personal taxes: Miller 1977 

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025) explores the optimal capital structure for firms, which refers to the balance between debt and equity financing. This post focuses on how the impact of personal taxes on the firm capital structure. The author unpacks Miller’s 1977 proposition, which presents a formula for calculating the right tax advantage of debt, and explains how it helps reconcile theory with what we actually observe in practice.

Introduction

When Modigliani and Miller introduced their capital structure theory in 1958, they shook the foundations of corporate finance. They argued that, in a perfect market with no taxes, no bankruptcy costs, and no frictions, a firm’s value is completely independent of how it is financed. In other words, it doesn’t matter whether a firm uses debt, equity, or a combination of both—the total firm value remains the same.

In 1963, Modigliani and Miller revised their theory to incorporate corporate taxes. With this adjustment, interest payments on debt are tax-deductible, and then provide firms with a “tax shield” that effectively reduces the cost of debt. This made debt financing more attractive than equity, leading to the conclusion that firms should increase their leverage to maximize their value (ideally reaching a 100 debt ratio). In the extreme, this version of the theory suggested that firms should be financed entirely with debt to benefit from the maximum tax advantage.

However, the real world tells a different story. Very few firms rely solely on debt. In fact, most maintain a balanced mix of debt and equity. If debt is supposedly so advantageous under corporate tax rules, why don’t we see more of it being used? This is where Merton Miller’s 1977 work offers a crucial refinement to the theory.

Miller introduced a critical yet often overlooked component into the capital structure discussion: personal taxes. While interest payments are tax-deductible at the corporate level, the income received by investors—whether as interest or dividends—is also subject to personal taxation. Importantly, interest income is often taxed at a higher rate than equity income (like capital gains or dividends). This means the supposed advantage of debt at the corporate level may be offset—or even completely nullified—by the higher tax burden borne by investors.

Modigliani-Miller 1963 Theorem (M&M 1963)

Let us first remind you about the main findings of Modigliani and Miller (1963). In their revision of their first article published a few years earlier (1958), their theory about the firm capital structure introduced corporate taxes, which has a crucial impact on their earlier conclusions which found that the capital structure was irrelevant. They recognized that, in most economies, governments impose corporate income tax, but companies can deduct interest payments on debt from their taxable income. This interest tax-shield increases the after-tax profits of a firm and thereby raises its overall value.

The tax shield refers to the reduction in taxable income that results from interest payments on debt. Since interest expenses are tax-deductible, they effectively reduce the amount of taxes a company owes. This provides a direct financial benefit to firms that use debt financing, making it a valuable tool for optimizing capital structure.

The formula for the tax shield is:

This means that, under the M&M (1963) proposition, the value of a leveraged firm is given by:

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

  • Tc is the Corporate tax rate

  • D is the amount of debt of the firm

This formula shows that the value of a firm increases by the amount of tax shield (Tc⋅D) when debt is introduced into the capital structure. The more debt a company takes on, the greater the tax benefit, making debt financing more attractive than equity financing.

Miller (1977): The Role of Personal Taxes in Capital Structure

Modigliani and Miller’s 1963 revision made a powerful case for debt: because interest payments are tax-deductible, firms enjoy a tax shield that reduces their cost of capital. The logical (but extreme) implication of this idea was that firms should maximize debt in their capital structure. However, the theory still fell short of explaining reality—most firms do not load up on debt. Why?

This is where Merton Miller’s 1977 paper brought a major refinement. While M&M (1963) focused on corporate taxes, Miller highlighted the crucial role of personal taxes paid by investors. Specifically, he noted that:

  • Interest income (from bonds or loans) is typically taxed at a higher personal rate (TPi),

  • While equity income (via dividends or capital gains) is often taxed at a lower rate (TPe).

Thus, although the firm saves taxes through debt, the investor receiving interest income may lose part of that advantage due to higher personal taxes. Miller argued that the tax benefit of debt is not universal—it depends on the relative tax positions of the firm and its investors.

Miller quantified the net tax advantage of debt with the following formula:

where:

  • TPi is the personal tax rate on interest income

  • TPe is the personal tax rate on equity income (dividends/capital gains)

  • Tc is the corporate tax rate

This expression compares the after-tax returns from debt and equity financing, from both the firm’s and investor’s perspectives.

Value of a Levered Firm according to Miller (1977)

In Miller (1977), the value of the firm incorporates both:

1. The corporate tax shield (from M&M 1963), and

2. The personal tax disadvantage from investor taxation on interest income.

Unlike M&M 1963 (which assumed value keeps increasing with leverage due to tax shields), Miller showed that the firm’s value plateaus at an equilibrium level, reflecting the offsetting effect of personal taxes.

There isn’t a single formula as elegant as in M&M 1963 because Miller focuses on market equilibrium, not firm-level maximization. But we can express the adjusted value of a levered firm relative to the unlevered firm as:

that is,

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

  • Tc is the Corporate tax rate

  • TPi is the personal tax rate on interest income

  • TPe is the personal tax rate on equity income (dividends/capital gains)

  • D is the amount of debt of the firm

Figure 1. Firm Value vs Debt according to Miller 1977 Theorem

where:

  • Tc is the Corporate tax rate

  • TPi is the personal tax rate on interest income

  • TPe is the personal tax rate on equity income (dividends/capital gains)

The Equilibrium Capital Structure Across Firms

One of the most insightful—and often misunderstood—contributions of Miller (1977) is that there is no single “optimal” capital structure for all firms. Instead of recommending that every company should maximize debt (as M&M 1963 might suggest), Miller argued that the optimal mix of debt and equity depends on the broader market, not just individual firm decisions. His approach introduced a market-level equilibrium perspective, which helps us understand the diverse financing strategies we observe in the real world.

Miller recognized that not all investors are taxed equally. Some investors—like pension funds, endowments, or individuals in low tax brackets—are less affected by taxes on interest income. These investors prefer debt because they can earn stable interest income without facing significant tax penalties. On the other hand, investors in higher tax brackets might favour equity, particularly because capital gains and dividends are often taxed at lower rates than interest income.

This diversity in investor preferences (from different personal tax rates) creates a kind of natural balance in the financial markets. Some firms will issue more debt to attract income-focused investors, while others will rely more on equity to appeal to investors who value capital gains. Over time, this leads to a market equilibrium in which different firms adopt different capital structures based on the preferences of the investors they attract.

In reality, we do not see all firms aggressively using debt to lower their tax bills. Instead, we see some firms—like utilities or financial institutions—using higher levels of debt, while others—like tech startups or growth firms—rely more on equity. This variation observed in practice aligns perfectly with Miller’s theory. The aggregate tax advantage of debt is “used up” across the economy, so not every firm needs to (or should) leverage itself heavily.

Firms essentially compete for investor types, and their capital structure decisions reflect the marginal investor’s personal tax situation. In this way, the equilibrium is not found at the level of a single firm, but across the entire set of firms.

How Miller (1977) Redefined the Cost of Equity and WACC from Modigliani-Miller (1963)

In M&M (1963), the introduction of corporate taxes led to a crucial insight: because interest payments are tax-deductible, debt financing creates a tax shield that reduces the firm’s Weighted Average Cost of Capital (WACC). The model predicted that, as leverage increases, WACC decreases, and firm value rises—implying that a firm should use as much debt as possible to minimize its cost of capital.

This had a direct impact on the cost of equity as well. In M&M (1963), the cost of equity (rE) increases with leverage to compensate for the rising risk faced by shareholders:

where:

  • rE is the cost of equity for a levered firm

  • rU is the cost of equity for an unlevered firm

  • rD is the cost of debt

  • D/E is the debt to equity ratio measuring leverage

Here, while the cost of equity increases due to higher financial risk, the overall WACC falls, thanks to the tax shield:

Where: V is the Value of the firm (V= D + E)

Miller (1977) introduced personal taxes into the equation—something that M&M (1963) completely ignored. He observed that investors are not only taxed at the corporate level but also at the personal level:

  • Interest income is taxed at the personal level (personal tax rate on interest income: TPi)

  • Equity dividends and capital gains are taxed at the personal level (personal tax rate on equity: TPe)

Crucially, interest income is taxed more heavily than equity dividends and capital gains: TPi > TPe. This is the case in the United States and most developed countries.

This alters the perceived tax advantage of debt as the benefit of corporate tax deductibility may be neutralized—or even outweighed—by the higher taxes on interest income.

While Miller (1977) didn’t give a neatly adjusted cost of equity formula like Modigliani and Miller (1963), he did show that the tax advantage of debt financing is not universal—it depends on both corporate and personal tax rates. This led to a redefinition of the net tax advantage of debt, which in turn affects WACC:

And so, the adjusted value of the tax shield, and by extension the impact of debt on WACC, becomes:

Using this expression, the WACC becomes:

where,

  • Tc is the Corporate tax rate

  • TPi is the personal tax rate on interest income

  • TPe is the personal tax rate on equity income (dividends/capital gains)

  • D/V is the proportion of debt in the capital structure

  • E/V is the Proportion of equity in the capital structure

  • rE is the cost of equity for a levered firm

  • rD is the cost of debt

This means that the WACC no longer declines indefinitely with debt. Instead, as the tax burden on interest income increases (via Ti ), the marginal benefit of debt diminishes. At market equilibrium, the advantage of debt disappears, and WACC flattens—explaining why we observe moderate, not extreme, debt usage in practice.

  • If Ti > Te and corporate tax Tc is high, debt still offers a net tax advantage, though smaller than in M&M (1963).

  • If the term in brackets equals zero, there is no net tax advantage—WACC remains flat regardless of leverage.

  • If the term becomes negative, equity becomes more tax-efficient, and adding debt raises the WACC.

Why Should I Be Interested in This Post?

In corporate finance, the debate around how much debt a firm should take on is far from settled. While traditional models like Modigliani-Miller (1963) emphasize the tax benefits of debt, they ignore the taxes investors pay. This post introduces the groundbreaking Miller (1977) framework, which shows how personal taxes can offset corporate tax advantages, reshaping our understanding of optimal capital structure. If you’re a finance student, investor, or aspiring professional, understanding this equilibrium-based view will give you a more realistic—and nuanced—perspective on how real-world firms decide between debt and equity.

Related posts on the SimTrade blog

   ▶ Snehasish CHINARA Optimal capital structure with taxes: Modigliani and Miller 1963

   ▶ Snehasish CHINARA Optimal capital structure with no taxes: Modigliani and Miller 1958

   ▶ Snehasish CHINARA Solvency and Insolvency in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Liquidity and Illiquidity in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Solvency & Insolvency : A Link to Bankruptcy Procedures

   ▶ Snehasish CHINARA Chapter 7 vs Chapter 11 Bankruptcies: Insights on the Distinction between Liquidations & Reorganisations

   ▶ Snehasish CHINARA Chapter 7 Bankruptcies: A Strategic Insight on Liquidations

   ▶ Snehasish CHINARA Chapter 11 Bankruptcies: A Strategic Insight on Reorganisations

   ▶ Akshit GUPTA The bankruptcy of Lehman Brothers (2008)

   ▶ Akshit GUPTA The bankruptcy of the Barings Bank (1996)

   ▶ Anant JAIN Understanding Debt Ratio & Its Impact On Company Valuation

Useful resources

US Courts Data – Bankruptcy

S&P Global – Bankruptcy Stats

Statista – Bankruptcy data

About the author

The article was written in July 2025 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025).

Optimal capital structure with taxes: Modigliani and Miller 1963

 Snehasish CHINARA

In this article, Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025) explores the optimal capital structure for firms, which refers to the balance between debt and equity financing. This post dives into the article written by Modigliani and Miller (1963) which explores the case of corporate tax and a frictionless market (no bankruptcy costs).

Introduction to Modigliani and Miller Propositions

In 1958, Franco Modigliani and Merton Miller introduced a groundbreaking theory on capital structure, famously known as the M&M Proposition. Their research concluded that, under certain ideal conditions, the way a company finances itself—whether through debt or equity—does not affect its overall value. This result, known as the Capital Structure Irrelevance Principle, was based on assumptions such as no corporate taxes, no bankruptcy costs, and perfect capital markets. The intuition behind this idea is simple: if investors can create their own leverage by borrowing personally at the same rate as firms, then a company’s financing mix should not matter for its value.

According to M&M Proposition I (1958), in a frictionless world:

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

Key Assumptions:

  • No taxes (in reality, firms pay corporate taxes).

  • No bankruptcy costs (in reality, firms pay costs if they go bankrupt).

  • No financial distress (in reality, too much debt can make investors nervous).

However, this initial model had a major limitation: it ignored the effect of corporate taxes. In reality, most governments tax corporate profits, but they allow firms to deduct interest expenses on debt from taxable income. This means that using debt provides a tax advantage, which was missing from the 1958 model. Recognizing this, Modigliani and Miller revised their original work in 1963, introducing the impact of corporate taxes. Their new findings dramatically changed the conclusion: debt financing increases firm value because interest payments reduce taxable income, creating a tax shield. This update laid the foundation for modern corporate finance by showing that, with corporate taxes, firms should prefer debt over equity.

Modigliani-Miller 1963 Theorem (M&M 1963)

Modigliani and Miller’s 1963 revision to their capital structure theory introduced the concept of corporate taxes, which has a crucial impact on their earlier conclusions. They recognized that, in most economies, governments impose corporate income tax, but companies can deduct interest payments on debt from their taxable income. This interest tax-shield increases the after-tax profits of a firm and thereby raises its overall value.

The tax shield refers to the reduction in taxable income that results from interest payments on debt. Since interest expenses are tax-deductible, they effectively reduce the amount of taxes a company owes. This provides a direct financial benefit to firms that use debt financing, making it a valuable tool for optimizing capital structure.

The formula for the tax shield is:

Since interest expense is calculated as:

Therefore, the tax shield for a single year becomes:

The Modigliani-Miller (1963) model assumes perpetual debt primarily for simplification and mathematical clarity. The use of perpetual debt helps in calculating the present value of the tax shield without the need for complex discounting over a finite period.

If the firm has perpetual debt, meaning it never repays the principal and continues paying interest forever, the total value of the tax shield is found by calculating the present value of all future tax shield benefits. Since the tax shield is received every year indefinitely, its present value is:

Using the cost of debt (rd) as the discount rate, we get:

The (rd) cancels out, simplifying to:

This means that, under the M&M (1963) proposition, the value of a leveraged firm is given by:

where:

  • VL is the value of a levered firm using debt.

  • VU is the value of a unlevered firm not using debt but only equity

  • Tc is the Corporate tax rate

  • D is the amount of debt of the firm

This formula shows that the value of a firm increases by the amount of tax shield (Tc⋅D) when debt is introduced into the capital structure. The more debt a company takes on, the greater the tax benefit, making debt financing more attractive than equity financing.

Figure 1. Firm Value vs Debt according to M&M 1963 Theorem

In simple terms, taxes make debt financing more beneficial because firms pay interest on debt before paying taxes, reducing their taxable income. On the other hand, dividends paid to equity shareholders are not tax-deductible, meaning that firms must pay taxes on their entire profit before distributing dividends.

Implication for Capital Structure Decisions:

Firms benefit from using debt due to the tax shield, leading to a preference for more leverage.

The Modigliani-Miller (1963) model with taxes suggests that because of the tax shield on debt, a firm’s value increases as it takes on more debt. The formula for value of a levered firm according to M&M(1963) shows that every additional unit of debt directly increases firm value by the tax savings it provides. In theory, this means that a firm should finance itself entirely with debt (100% debt financing) to maximize its value. This is a significant departure from M&M (1958), where capital structure had no effect on firm value.

Limitations

However, in real-world scenarios, firms do not rely solely on debt. This is because excessive debt increases the risk of financial distress and bankruptcy costs, which M&M (1963) did not initially consider.

Case Study: Implications of M&M 1963 (Optimal Capital Structure with corporate taxes)

Alpha Corp operates in an imperfect capital market (with taxes only). It has two financing options for the capital structure:

  • Option 1: equity only (100% equity, 0% debt)

  • Option 2: debt and equity (60% equity, 40% debt)

Each option funds a $100 million investment that generates an annual operating income of $10 million. The risk-free interest rate is 5%, and the corporate tax rate is 30%.

Figure 2. Simplified Balance Sheet of Alpha Corp

Table 1. M&M 1963: an Example

Based on Table 1, the key takeaways are as follows:

1.Debt Creates a Tax Shield:

  • Under Option 2 (40% debt, 60% equity), Alpha Corp pays €2 million in interest expense, reducing taxable income from €10 million to €8 million.

  • This results in a lower corporate tax payment (€2.4 million instead of €3 million), leading to a €600,000 tax shield benefit.

2.Net Income is Lower with Debt, But Firm Value Increases:

  • Despite reducing tax liability, net income under Option 2 (€5.6 million) is lower than Option 1 (€7 million) because of interest expenses.

  • However, the firm’s total value increases due to the tax shield, meaning equity holders still benefit from debt financing.

How Modigliani-Miller (1963) Redefined the Cost of Equity and WACC from Modigliani-Miller (1958)

In Modigliani-Miller (1958), the firm’s capital structure—the mix of debt and equity—was considered irrelevant to its overall cost of capital (WACC) and, by extension, its firm value. This proposition, based on ideal market conditions (no taxes, no bankruptcy costs), argued that whether a firm is financed by debt or equity, the overall cost of capital remains unchanged. The cost of equity increases with leverage because equity holders demand higher returns to compensate for the additional financial risk, but this increase in cost of equity was offset by the lower cost of debt. Therefore, WACC stayed constant regardless of a firm’s capital structure.

However, when Modigliani and Miller (1963) introduced corporate taxes into their model, they demonstrated a significant change in the cost of capital (WACC) and cost of equity dynamics. With the tax deductibility of interest payments on debt, the cost of debt is effectively reduced, which leads to a reduction in WACC. This creates a clear benefit for firms that use more debt in their capital structure, making debt financing a value-enhancing tool. Let’s explore these key differences in detail.

Impact on the Cost of Equity (rE)

MM (1958) – Cost of Equity Increases with Leverage

Under the Modigliani-Miller (1958) framework, the cost of equity (rE) increases as a firm takes on more debt because equity holders demand higher returns for taking on additional risk due to leverage. The relationship between cost of equity and leverage is described by the following formula:

where:

  • rE is the cost of equity for a levered firm

  • rU is the cost of equity for an unlevered firm

  • rD is the cost of debt

  • D/E is the debt to equity ratio measuring leverage

This formula shows that as a firm increases its debt, its cost of equity increases to compensate for the increased financial risk borne by equity holders. However, since debt is cheaper than equity, the overall WACC remains unchanged.

MM (1963) – Tax Shield Reduces the Impact on Cost of Equity In MM (1963), the introduction of corporate taxes changes the scenario. Since interest expenses on debt are tax-deductible, the effective cost of debt (rD) becomes lower. This reduces the overall risk for the firm and, therefore, the increase in the cost of equity (rE) is less severe than in MM (1958). The new formula for cost of equity becomes:
where Tc is the corporate tax rate. The (1 – Tc) term reduces the increase in cost of equity (rE), because the firm’s debt is now partially subsidized by the tax shield. This shows that while leverage still increases the cost of equity (rE), the effect is less pronounced in the presence of tax deductibility of interest payments.

Impact on the Weighted Average Cost of Capital (WACC)

M&M (1958) – WACC Remains Constant Regardless of Leverage

In MM (1958), because the increase in the cost of equity (rE) offsets the benefit of cheaper cost of debt (rD), the WACC remains constant no matter the debt-to-equity ratio. The formula for WACC in this model is:

where:

  • V=D+E is the total firm value

  • rE is the cost of equity for a levered firm

  • rD is the cost of debt

  • D is the total debt

  • E is the total equity

According to MM (1958), since debt and equity are in perfect balance (i.e., the increase in the cost of equity (rE) is offset by the lower cost of debt (rD)), the WACC stays constant. The capital structure—how much debt or equity a firm uses—has no effect on the overall cost of capital or the firm’s value in a world without taxes.

MM (1963) – WACC Declines as Debt Increases

With the introduction of taxes, MM (1963) shows that WACC decreases as a firm increases its debt. The tax shield created by the deductibility of interest payments lowers the effective cost of debt (rD), making debt financing more attractive.

The formula for after-tax WACC in MM (1963) is:

In this scenario, debt financing becomes more advantageous because the firm can lower its overall WACC by utilizing debt, which reduces the tax burden. The WACC decreases as a firm increases its leverage (debt) because the cost of debt (rD) is reduced due to the tax shield, and the cost of equity (rE) increases at a slower rate due to the reduced impact of debt on financial risk.

Figure 3. Modigliani-Miller View Of Gearing And WACC: With Taxation (MM 1963)

Case Study: Implications of M&M 1963 (Optimal Capital Structure with corporate taxes)

Alpha Corp operates in a capital market (no bankruptcy costs, and no market imperfections). It has two financing options:

  • Option 1: Fully equity-financed (No debt with Corporate Taxes of 30%)

  • Option 2: 40% Debt, 60% Equity (without Corporate Taxes)

  • Option 3: 40% Debt, 60% Equity (with Corporate Taxes of 30% )

Each option funds a $100 million investment that generates an annual operating income of $10 million. The risk-free interest rate is 5%, and the required return on equity is 10%.

Figure 4. Modigliani-Miller View Of Gearing And WACC: With Taxation (MM 1963)

Table 2. M&M 1963: an Example

Key takeaways from this example are as follows :

1. Corporate Taxes Make Debt Financing More Attractive by Reducing the Effective Cost of Debt

  • In a no-tax world (M&M 1958, Option 2), firms are indifferent between debt and equity, as capital structure does not affect WACC.

  • However, M&M (1963) proves that in a taxed environment (Option 3), debt financing creates value because interest payments reduce taxable income, leading to lower corporate taxes.

  • This is called the “tax shield” effect, where firms pay less in taxes by using debt, increasing after-tax cash flows available to shareholders.

2. WACC Declines with Leverage When Corporate Taxes Exist, Unlike in M&M (1958)

  • In M&M (1958) (no taxes, Option 2), WACC remains constant at 10%, regardless of leverage.

  • M&M (1963) (Option 3) introduces taxes, causing WACC to drop to 8.80% due to the tax shield.

  • Strategic Takeaway: Firms can reduce their cost of capital and increase firm value by incorporating moderate levels of debt into their capital structure.

3. Cost of Equity Increases with Debt, But the Tax Shield Reduces the Rate of Increase

  • Higher leverage increases financial risk for shareholders, leading to a higher required return on equity (rE).

  • In Option 2 (M&M 1958, No Taxes), introducing 40% debt raises the cost of equity to 13.33% due to added risk.

  • In Option 3 (M&M 1963, With Taxes), the cost of equity only increases to 12.33%, because the tax shield offsets part of the financial risk.

4. After-Tax Cost of Debt is Lower than the Cost of Equity, Making Debt a Cheaper Financing Option

  • The cost of debt before taxes is 5%.

  • Due to the corporate tax rate (30%), the effective cost of debt is reduced: rDafter-tax= rD ×(1−Tc)

  • Comparing Financing Costs in Option 3:

    • Cost of Equity (rE) = 12.33%

    • After-Tax Cost of Debt (rD) = 3.5%

  • Debt financing is significantly cheaper than equity financing after adjusting for the tax shield.

  • Firms should utilize debt strategically to lower overall financing costs.

5. The Trade-Off Between Tax Benefits and Financial Distress Risk Determines the Optimal Capital Structure

  • M&M (1963) suggests using more debt to reduce WACC, but in reality, excessive debt increases financial distress risks.

  • While debt reduces WACC through the tax shield, too much debt leads to higher bankruptcy risks, credit downgrades, and operational constraints.

  • Most firms balance debt and equity to optimize WACC, using debt to take advantage of tax savings without excessive financial risk.

Takeaways on Optimal Debt Structure and Bankruptcy Costs from M&M 1963 Theorem

The Modigliani-Miller (1963) proposition demonstrated that the presence of corporate taxes fundamentally changes the implications of capital structure on firm value. Unlike their earlier 1958 proposition, where capital structure was deemed irrelevant, the 1963 revision highlighted the benefits of debt financing due to the tax shield effect. Since interest expenses on debt are tax-deductible, firms can reduce their taxable income and, consequently, their tax obligations. This finding suggests that, in a world with corporate taxes and no other frictions, firms should finance themselves entirely with debt to maximize their value.

The M&M (1963) proposition remains a cornerstone in understanding capital structure decisions, demonstrating that debt financing enhances firm value through tax savings. However, in practice, firms must carefully balance leverage to avoid excessive financial distress. The optimal capital structure is not purely debt-driven but rather a carefully calibrated mix of debt and equity that maximizes firm value while maintaining financial stability.

Why Should I Be Interested in This Post?

This post explains a key concept in corporate finance—how debt financing affects firm value through corporate tax benefits and financial risks. If you’re a student, finance professional, or investor, understanding the Modigliani-Miller (1963) proposition will help you grasp why companies use debt. With clear explanations, real-world examples, and Excel-based analysis, this post provides practical insights into optimal capital structure decisions.

Related posts on the SimTrade blog

   ▶ Snehasish CHINARA Optimal capital structure with no taxes: Modigliani and Miller 1958

   ▶ Snehasish CHINARA Solvency and Insolvency in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Liquidity and Illiquidity in the Corporate World

   ▶ Snehasish CHINARA Illiquidity, Solvency & Insolvency : A Link to Bankruptcy Procedures

   ▶ Snehasish CHINARA Chapter 7 vs Chapter 11 Bankruptcies: Insights on the Distinction between Liquidations & Reorganisations

   ▶ Snehasish CHINARA Chapter 7 Bankruptcies: A Strategic Insight on Liquidations

   ▶ Snehasish CHINARA Chapter 11 Bankruptcies: A Strategic Insight on Reorganisations

   ▶ Akshit GUPTA The bankruptcy of Lehman Brothers (2008)

   ▶ Akshit GUPTA The bankruptcy of the Barings Bank (1996)

   ▶ Anant JAIN Understanding Debt Ratio & Its Impact On Company Valuation

Useful resources

US Courts Data – Bankruptcy

S&P Global – Bankruptcy Stats

Statista – Bankruptcy data

About the author

The article was written in January 2025 by Snehasish CHINARA (ESSEC Business School, Grande Ecole Program – Master in Management, 2022-2025).

Understanding organizations’ role in bargaining tariffs

Annie YEUNG

In this article, Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) explains about understanding tariff bargaining that involves international organizations, governments, and industries..

The World Trade Organization (WTO)

The WTO was established in 1995 and is the most influential international organization in managing and negotiating for global trade. The WTO includes 164 member countries, and its main goal includes facilitating trade negations and monitor trade policies, especially tariffs. There has been statistics showing that average global tariffs has decreased since the establishment of WTO. For example, average bound tariffs for decreased by nearly 3 percent from 1995 to 2023.

The WTO is also plays an important role in bargaining tariffs. For example, the Doha Development Round, launched in 2001 under the WTO has focused on improving trading for developing nations. This negotiation, initiated by the WTO, has aimed to make global trade equitable. Its missions include reducing agricultural subsidies, lowering tariffs, which all have effect in order to help developing nations improve access to trading in the global market. There has been negotiations created amongst developed and undeveloped countries, with these negotiations focusing on farm subsidies and market access, as well as lowering industrial tariffs to allow developed nations to better participate in global trading activities . however it is important to note that despite ongoing talks, this round of negotiation has not been successful in delivering an agreement. This failure could have been attributed to the challenges in different trading activity interests amongst different countries. For example, there has been different perspectives in trading such as agricultural subsidies, and tariffs on services, resulting in unresolved conflicts despite negotiation.

WTO negotiations reflect deeper global power imbalances, which are manifested in trading activities and tariffs imposed. The more influential and wealthier nations often hold more bargaining power and power in the global trading market landscapes. For example, these influential countries, particularly those in the G20, often set agenda in the trade negotiations and possess more negotiating capacity. As a result these countries often dominate in negotiations, setting a dynamic that advocate for their trade interests during the process of bargaining of tariffs.

The African Group, the Association of Southeast Asian Nations (ASEAM) are organizations that have become more active, which these countries have formed organizations in order to bargain for equity in the global trading landscape. These organizations that are forming alliances in order to bargain for equitable trading systems that are recognizing asymmetries between economies to push for stabilization for less developed countries. While developed nations are pushing for lower tariffs across all sectors. However, the countries with large economies often contend that decreased tariffs will destabilize economies. As a result, the WTO plays a crucial role to address this imbalance. For example, the “Special Differential Treatment” proposed by the WTO framework promotes more support for developing countries in implementing trade agreements and reducing tariffs. This could reduce unfair trade advantages and reconcile global trade liberalization amongst developed and undeveloped countries..

Trade Negotiation Teams – Representatives

Trade negotiations are often led by high-ranking officials representing their nations. For example, the U.S. Trade Representative (USTR) is a team of experts that are specializing in multiple fields in industries, including agriculture, technology, labor, environment etc. For example, the negotiation team participating in the 2024 Trade Policy Agenda which the USTR emphasized on commitments for their countries interests, negotiating for high-standard commitments in sustainable trade practice to bolster supply chain resilience. The USTR also participates in the World Trade Organization to unify positions with other organizations such as the African Group and the ASEAN to implement trade agreements with other developing countries.

For example, the United States imposes an average agricultural tariff of 5.1%. India has an average agriculture tariff of 38% to protect domestic producers. The European Union imposes 11% in agricultural tariffs. These disparities often lead complex negotiations, especially with agriculture which is crucial for food security .Hence, negotiation objectives often focus on reciprocity. This means to maximize benefits, which trading partners much seek for equivalent concessions, and negotiate on agreements to match others. For example, if one agrees to lower tariffs, the trading partner shall agree to provide benefits on a similar traded product. This ensures mutual benefit in policy making and reaching political goals. However, reciprocity could sometimes be challenging when two countries are under asymmetrical power dynamics, such as negotiating between developed and developing countries, Furthermore, during negotiation, while trade liberation is a long-term mission in tariff negotiations, each country approaches tariff negotiation seeking to protect strategic sectors, preserve jobs, and ensuring their own country’s interests. In negotiating for tariff cuts, some countries may insist on tariffs in protection for their own domestic producers, or in goal to safeguard their own strategic sectors.

Examples of governments’ Tariffs – a case study

Trump – the U.S. – China Trade War during 2018 to 2020

The U.S. China trade war during the 2018-2020 led to higher prices for American consumers. China responded with retaliatory tariffs on U.S. goods, and global trade dynamics were disrupted. The trade wars between U.S. and China also casted an effect on the economies globally, as the two countries have such large economies.

As a result from the trade war, both the U.S. and China have experienced profound effects in multiple perspectives of their economies. The U.S> economy were affected in their GDP and employment. According to a report from Bloomberg Economics, the trade war in 2019 has costed the US economy at $316 billion. The trade wars has also resulted U.S. in stock market losses, with research from the federal reserve Bank of New York finding U.S. firms losing at least $1.7 trillion in market value as a result from the tariffs imposed on imports from China. China has also experienced economic challenges as a result from the trade wars, with export decline and experiencing economic pressures. China has experienced an export growth slow-down, indicating deepened economic challenges.

Furthermore, the trade wars has casted a great effect to the global economic markets. With the two countries being two of the world’s largest economies, their trade tensions has led to significant shifts in market dynamics and economic growth on a global scale. According to data from Banque de France, 10 percent increase in tariffs could reduce global GDP by 3%. This decline as a result from the trade wars and increased tariffs is a result of increased prices that leads to decreased productivity, higher financing costs and reduced investment demand. According to data from The World Economic Forum, it is documented that the trade war has resulted a decrease of global GDP growth to 2.8% in 2019.

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Useful resources

A Quick Review of 250 Years of Economic Theory About Tariffs

Tariff Negotiations and Renegotiations under the GATT and the WTO — Procedures and Practices

A quantitative analysis of multi-party tariff negotiations

About the author

This article was written in June 2025 by Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).

Understanding the Evolution of Tariffs

Annie YEUNG

In this article, Annie YEUNG discusses the historical development of tariffs and the evolution of tariffs over economic landscapes overtime.

Brief explanation of history of global tariffs

In the 19th century, tariffs were the main source of government revenue in aim for protectionism. Tariffs were widely used to protect domestic industries that were in their beginning stages. Many countries such as the United States and Europe has imposed high tariffs in order to ensure the development of their industrializing economies. For example, the U.S. implemented tariffs, such as the Tariff of Abominations in 1828 to protect its manufacturing industry. During the post World War II era, the General Agreement on Tariffs and Trade was established in 1947. In response to the post war devastation, countries lowered their tariffs in order to promote economic growth. Reciprocal lower tariffs were also implemented amongst countries and trading partners. Starting in near the beginning of the 21st center, the launch of the World Trade Organization in 1995 marked a significant evolution in global trade, where governance of trade tariffs were established through the launch of the WTO. The WTO emphasized on the trading of goods and introduced a governance structure for development considerations, granting special support for developing and less developed countries. The WTO also introduced an institutional structure for the dispute settlement procedures on global trading. Today, tariff reductions have continued due to negotiations and regional trade agreements, which deepened the harmonization of the global markets, facilitating increased global trade volumes. However, during the last decade, there has been an introduction of resurgence of tariffs amongst increased instability in the current geopolitical grounds. Tariffs has served as a political tool. For example, the U.S.- China trade war has seen tariffs as an economic tool under rising geopolitical tensions where billions of dollars of goods subject to tariffs. As two of biggest economies globally, this trade war has disrupted global supply chains. This has posed challenges as other countries have also employed tariffs for protectionism goals.

The Protectionism Approach

The United States has been maintaining high tariffs to nurture for its developing domestic industries during the 19th centuries. The United States has seen an increase in the average tariff rate over a century of time. During the beginning of the 19th century, the U.S.Average Tariff Rate was 35%, whereas by 1913, the U.S. Average Tariff Rate has increased to 40%. This historical evolution could be attributed to the need for domestic protection; early industrialization period during the early 19th century required protection, whereas in the beginning of the 20th century, tariffs needed to support the growing industry. European countries such as Germany and France also utilized tariffs to protect industrial growth during this period of time. However, developing countries struggled developing tariffs as threir internal markets were still in developing stages. However, beginning from the early 1900s, there has been a further rise in nationalism. Some tariffs rates exceeded 60%, and as a result, global trade decreased by 66% between 1929 to 1934. This was also during the period of the Great Depression, in which these tariff hikes and set-back in economy was a result of reduced international trade.

Trade Liberalization

After the establishment of the General Agreement on Tariffs and Trade in 1947 to reduce tariffs, there have been successful negotiation amongst nations to cut average tariffs worldwide in order to reduce protectionism and open up markets to global trading activity. This is seen from the data presented from the World Bank World Development Indicators, which there has been a gradual deduction in average global tariff rate from 15% to 6% from from the year 1950 to 2000. Since the beginning of tariff reductions and the start of post-war rehabilitation and rebuilding of the economy in 1950, continued multilateral negotiations has resulted in a historic low of tariffs in the year 2000. As a result, trade volumes increased and there was a global economic growth.

Complex Socio-economical landscapes

Despite the decreasing of average global tariff rate, trade policies in the 21st century, especially in the recent years, has grown to become more complex. For example, there has been targeted tariffs and trade conflicts, leading. To increased uncertainty in global trading markets. For example, U.S. has increased its tariffs from the year 2017 to 2020, with the average U.S. Tariff Rate of 1.6% in 2017 plummeting to 3.1% in the year 2020. This could have been attributed to the increased policies on tariffs on steel, aluminum, and the trade wars with China, resulting to much higher tariff rates compared to the beginning of the 2000s. For example, targeted tariffs has become a strategic target tariff, a tool with political goals. For example, the steel and aluminum tariff was to protective domestic industries, which the Trump administrated imposed a 25% tariff on steel and 10% on aluminum in March 2018. These tariffs were to uphold national security to maintain the U.S. domestic metals industry. However, this tariff led to price increases and resulted in retaliation of tariff policies from its trading partners.

< p> Increased tariffs from one country often results in retaliatory tariffs from its trading partners. Not just China, but there were also other countries that have responded to U.S.’s tariff hikes, including Canada, the European Union, and India. As a result, the increase in tariff has resulted in increased uncertainty to the global trade environment, affecting stock markets, companies, local businesses etc. Hence, the tariff can cast direct effects to each producer and consumer domestically, as investors raise concern over costs, and supply chains are rendered volatile, slowing businesses.

A Case Study: The European Union’s tariff on Chinese Electric Vehicles

In the year 2024, the European Union imposed tariffs of 38.1% on Chinese imported electrical vehicles. This is an example of the shifting grounds of global trading market environments. Today, tariffs have increased globally, and this tariff is an example that has marked a shift in the European Union trade policy and has great implications for the global automotive industry as well as the international trading landscapes. For example, the EU has imposed different tariffs targeting on specific different companies. The SAIC Motor has an 38.1% tariff, whereas Geely experiences a 20% tariff, while BYD has a 17.4% tariff for all goods imported into the European Union from China. These tariffs were imposed by the EU due to the low prices that Chinese manufacturers deliver to the European market, which may potentially undermine local producers through competition. In response to the tariff, China has filed a complaint with the World Trade Organization to contend for EU’s actions, appealing that the EU may have constituted to protectionism under fair competition. The tariff casts a large impact on the European EV market, which European consumers are facing higher prices. Market share also shifts, as the tariffs has changed the competitive landscape; Chinese manufactured EVs are facing higher costs, which may benefit domestic European manufacturers. Hence, the EU’s recent tariffs on Chinese manufactured electric vehicles marks today’s international trade policies amongst the historical evolution of global trade and tariffs, and has sparked debate and challenges.

Evolution of tariffs
Evolution of tariffs
Source: ACEA.

Why should I be interested in this post?

Evolution of tariffs is crucial as it reveals how economic policies shape international trade dynamics, and this affects to domestic industries, producers, consumers, and also has a wider effect to the global market. Studying the changes of tariffs throughout time can allow us to gain insights into historical trends, and stay informed upon future policy decisions.

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Useful resources

A history of free trade — and the deep irony of ‘liberation day’

The Evolution of Tariffs

History of U.S. tariffs and why it matters today

The Problem of the Tariff in American Economic History, 1787–1934

Financial Times Transcript: Tariffs past, present and future. With Doug Irwin

About the author

The article was written in June 2025 by Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).

Understanding the Economics of Tariffs

Annie YEUNG

In this article, Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) explains about understanding how tariffs are crucial for consumers, suppliers, and policymakers.

Introduction: What are tariffs?

Tariffs is a tax that is placed on imported and exported goods, essentially, a duty on goods when they cross international borders. Tariffs are taxes that is imposed by a government, and they are often utilized by governments to protect domestic industries, raise government revenue, and influent foreign policy. Tariffs are always impacting global economies on a large scale, as the effect they bring are always to large bodies of consumers and suppliers internationally, especially if the tariffs are imposed by a country with large export or import volumes. Trade tariffs make a direct effect by making imported goods more expensive, and they can often shift increased consumptions towards domestically produced goods. Tariffs take effect by rendering international imported goods more expensive, which consumers would, due to effect of demand, increase their quantity demanded towards domestic goods. Hence, tariffs take effect in protecting domestically produced goods, and may achieve political goals. However, as prices are increased, consumers often need to pay a higher price, which this may lead to inefficiencies and deadweight loss; this may lead to trade disputes.

Evolution of tariffs
 Evolution of tariffs
Source: Average of World Tariffs, Adapted from Mitchell (1992) and Coatsworth and Williamson (2002).

Different types of tariffs

Ad Valorem Tariffs

An Ad Valorem Tariff is a tariff that is added onto the price of the imported good as a percentage. For example, an ad valorem tariff may be a 10 percent tax that is added onto the price of each good imported. Hence, an ad valorem tariff means that the more expensive a good is, the more tariff is added on. This may mean that higher valued imported goods are rendered much more expensive and takes greater effect as a result from the tariff.

Specific tariffs

Specific tariffs are tariffs that charges a fixed fee on the quantity or physical unit of the imported good. Hence, special tariffs are imposed on goods that are regardless of their price, and it would be a fixed fee that is imposed per physical unit of the imported good. For example, a specific tariff could be a $1 imposed on per kilogram of wheat that is imported wheat into the country. The economic impact are easier to administer and do not adjust with the market price of the good.

Compound tariffs

A compound tariff is a combination of both ad valorem and specific tariffs. Compound tariffs may include both an ad valorem tariff and a specific tariff combined to be imposed on an imported good.

Sliding Scale tariffs

Sliding scale tariffs are a variable tariff rate that are adjusted based on global commodity prices, domestic supply levels, inflation volatility etc. The tariff is dependent on when world prices of the good increases or rises. When world prices decrease, the sliding scale tariff increases, and when world prices increase, the tariff decreases. Hence, this tariff takes an economic effect by helping to maintain a minimum domestic price of a good, and helping to balance price stabilization. Hence, sliding scale tariffs may help stabilize domestic goods’ prices, and smooths the supply and demand for domestic goods, protecting domestic producers and reducing market volatility in face of global economic changes.

Protective tariffs

Protective tariffs take effect by protecting domestic industries from foreign competition. The goal of imposing a protective tariff is to encourage consumers to purchase more from domestic by raising the price of internationally imported goods. As a result, when demand for domestic goods increase as a result from protective tariffs, more domestic jobs can be created, and growth of local industries are secured, which exemplifies the protection for these domestic sectors.

Revenue tariffs

Revenue tariffs are tariffs to raise government revenue instead of protecting domestic producers. The purpose of imposing revenue tariffs is to generate an income for the government, especially when the country’s economic system heavily depends on imported goods and has a high volume of imported goods. However, revenue tariffs may be a great burden for domestic consumers as they bear the higher prices of goods, and may affect trade flows and consumption choices within the population, as consumers are the major price payers under a revenue tariff.

Economic Effects of Tariffs

Tariffs can create multidimensional impacts on the global economy both in short term and long term, and consumers, producers, governments, as well as international relations may all be affected. Hence, tariffs are a very important factor in influencing the international landscape and may cast a great effect on global economic markets.

The effect of tariffs on consumers

Tariffs firstly directly impacts consumers. When a government imposes tariffs, suppliers importing a good internationally will need to pay an extra cost to the government. As a result, this will raise prices of goods, reducing the purchasing power of consumers. Furthermore, as pries increase for imported goods, consumers may find more limited choices in the market, and this may lead to consumer dissatisfaction.

The effect of tariffs on domestic producers

Tariffs are generally casting a more beneficial effect for domestic producers as they often result in increased output and employment to domestic industries. With more demand turned to domestic producers, they may result in higher sales and revenue outputs, boosting the economic return for domestic producers. While tariffs may provide protection to domestic industries as they gain a price advantage over foreign producers, there may be reduced competition. Furthermore, domestic producers may also be harmed through tariffs if they rely on foreign inputs. For example, when domestic producers rely on imported raw materials, their input cost increases, and this may result in less profit earned.

The effect on governments and the international landscapes

Trade tariffs may generate positive impacts to governments, as trade tariffs may act as a channel for revenue generation. Governments also utilize trade tariffs for political goals, and may cast a strategic effect on trade negotiations and affect the economic diplomacy. Simultaneously, trade tariffs may manipulate trade flows, and cause dissatisfaction, as rising consumer prices may lead to domestic unrest and trade wars. When one country imposes a tariff, this may often provoke retaliation from other countries, leading to a spiral of protective tariffs, that rises global prices and slows global economies. Hence, tariffs can lead to trade wars and lead to geopolitical instability.

Why should I be interested in this post?

This post discusses how trade policies may affect all actors in the economy. Understanding tariffs help you understand global events, and this can influence your everyday life as well.

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Useful resources

CEPR Trump’s China tariffs: Lessons from first principles of classic trade policy welfare analysis

Knowledge.deck Trade and Tariff Impact Analysis

Wall Street Journal Tariffs Are More Than Just Taxes. They Are a Tool of Geopolitics.

About the author

The article was written in July 2025 by Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).

My internship experience at Partner plus Investments Limited

Annie YEUNG

In this article, Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) shares her summer internship experience at Partner Plus Investments Limited as the Junior Analyst.

About the company

Partner Plus Investments Limited is an asset management company particularly focusing on fund of funds company. Partner plus investments limited operates by intersecting finance and technology and leverages sophisticated financial data analysis and modeling. The company is high-tech, and the team retrieves and develops insights from big data in order to make analytical insights and help our clients make informed investment decision. The company also aims to create and share reports to make investment decisions and specializes in sophisticated financial big data for extract valuable information. Partner Plus Investments limited meticulously curate portfolios and is driven by the exceptional commitment to deliver investment outcomes and value to the company’s clients. With an expertise and financial analysis and strong understanding of market dynamics, the company utilizes cutting edge, tools and technology to extract insights from vast amounts of financial data, which enables the company to make investment decisions and suggestions for clients with confidence and precision by staying on top of market trend and continuously monitoring the funds performance, Partner plus investments, limited strives to adapt their strategies, proactively to capture opportunities and make the best outcomes for clients in face of market dynamics. Therefore, partner plus investments limited focuses on transparency, integrity approaches, and builds long-term relationships with their clients based on trust and efficient communication, whilst always putting their clients first. Therefore, partner plus investment Limited serves its clients as being a trusted partner in achieving its clients’ financial goals.

Partnerplus Investments logo.
Partnerplus Investments logo
Source: Partnerplus Investments.

My internship

As the summer intern, I took on the role of being the junior analyst, contributing to the team with asset management and portfolio monitoring through daily analysis of financial data. At partner plus investments, I went beyond traditional data analysis through the creation of interactive reports that help empower and engage clients to understand macroeconomic environments and how it is related to our own investment decisions.

During the internship, one of my main tasks included conducting macroeconomic research. One of my important tasks included updating macroeconomic indicators on our data base. Based on the conducted research, we compiled and analyzed the data to create reports that not only showcase our findings but also provide a comprehensive summary and overview of our teams’s collaborative decision making and making sure that our investment strategies are reasoned and aligned with our client’s financial goals.

My missions

Hence, during the internship, I was able to combine technological knowledge with financial expertise and contribute to our team. I learned to use softwares and navigate through sophisticated financial data bases, including Bloomberg terminal, to compile data in order to drive insights and conduct interactive reporting. For example, we used graphic model for visualization of the fund performance for our clients.

Required skills and knowledge

In partner plus investments I learned about the skills and knowledge to retrieve vast amounts of financial data in order to analyze them and transform them into our known own knowledge that allow us to make well informed investment choices.

The first skill I learned was portfolio management skills which I understood about how we strategically allocate assets in order to optimize returns and effectively manage risks in our asset allocation. I also learned about performance analysis as I kept track of our companies investment and evaluated the performance of our portfolios by performing benchmark analysis to assess our investment outcomes. I also gained knowledge about fund of funds. During our fun selection I understood how we identified and selected funds in order to construct our diversified portfolios. I also learned about fund monitoring by making informed decisions, and keeping ourselves informed under changing market conditions, and trying to identify market patterns and apply them into our investment strategies. another skill that I learned was client reporting. as part of our daily job, it was important for us to communicate clearly to our clients. For example, we developed and wrote clear client reports in order to communicate effectively our investment strategies and performances to our clients. I learned about presenting complex financial information and to clear and concise formats for our clients. This included visualization of our data through software such as Excel and simplifying our data in order to make it clear to our clients.

What I learned

Another skill that I learned was how to perform financial modeling and utilize problem solving skills to solve and project financial situations. Financial modeling comes in large variety, and one may create models in order to address situations for different financial issues. I understood the importance of employing an analytical mindset.

I learned about problem solving and financial modeling during my internship at partner plus investments for example in one of my financial modeling tasks I learned to identify and manipulate different variables in order to address different investment outcomes as a result of our investment choices this was crucial in understanding and applying investment strategies in order to optimize our portfolio performance. I also learned about understanding the significance of periodic investments. during one of my tasks, I utilized periodic investments as a dependent variable and I saw how they impact overall portfolio growth and how they also allowed us to mitigate risks. I also gained technical proficiency as I was able to hone my skills in using excel and I applied my prior knowledge that I gained in previous academic settings to professional settings. I also honed my analytical thinking, as I was able to understand relationship more skillfully between target returns and investment timelines; I was able to apply this in analyzing for our fun performance metrics. I also learned about outcome evaluation; in our client reporting stages, I learned about analyzing data and scrutinizing the credibility of source of information before we included it in our reports.

Financial concepts related to my internship

I present below three financial concepts related to my internship: efficient market hypothesis, client Relationship management, and Sharpe ratio.

Efficient market hypothesis

The first important financial concept that I learned from my internship was the efficient market hypothesis. This hypothesis explains that share price reflects all available information. Hence, in an efficient market, it would be impossible for invewstors to purchase undervalued stocks or sell stocks for inflated prices; it would be Impossible to outperform market through expert stock selections. Indeed, there are studies that find only 23% active managers were able to outperform their passive peers. With a stock market with such large amount of actors, some investors would outperform the market, and some investors would underperform the market. However, it is important to note that in our current world’s markets, it may be hard to have a completely efficient market. This means that due to other outside factors, some investors may have more information than others, which this leads to an inefficient market. Hence, in inefficient markets, asset prices don’t accurately reflect true value due to info asymmetries, lack of buyers and sellers, and high transaction costs.

Client Relationship management

Another important financial concept that was important to my internship was Client Relationship management. As I refine my skills in evaluating for our investment outcomes through client reporting, I understood the importance of client relationship management. this involved managing our interactions with clients and potential clients which was essential for our company by effectively building relationships we were able to tailor our investment strategies to meet our clients’ needs and help our clients better reach their financial goals. during our client relationship management, it was also important that we we’re able to generate accurate performance assessments in order to report our performance to our clients and provide frequent performance updates and investment recommendations effectively. hence only through ensuring reliable credible and transparent reporting could we provide our clients with detailed insights about our portfolios and enhance our partnership with them.

Sharpe ratio

The third financial concept that was incredibly important to my internship was the Sharpe ratio. The Sharpe ratio is a measure of risk-adjusted return, and it defines as the excess return of an investment compared to the risk free rate per unit of risk. during the internship by calculating and interpreting sharpie ratios we were able to better assess the performance of our investment portfolios, and this could effectively allow us to evaluate the returns generated by our portfolio. a higher ratio indicates better risk-adjusted returns; hence we could use the Sharpe ratio to compare the risk-adjusted performance and better understand how much risk we are taking to achieve a certain level of return.

Why should I be interested in this post?

This post should interest you if you are also looking for gaining valuable professional experience in a fund related company, as it introduces and discusses what it is like to work in one! You will be able to learn many hands-on knowledge about portfolio management and conducting financial research.

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About the author

The article was written in July 2025 by Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).

My internship experience at FTI Consulting

Annie YEUNG

In this article, Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025) shares her experience as an Intern at FTI Consulting.

About the firm

FTI consulting Is a business consultancy firm and global management advisory company. It is one of the leading global expert firms to help organizations that are facing crisis or transformation. fti consulting is a global company with a great presence in 33 countries and it has become a market leading global consulting firm that has experts to serve and help their clients as the trusted advisor for their clients to cope with challenges and leverage opportunitIes. FTI Consulting Has been recognized globally for their comprehensive services to assist their clients businesses and make a global impact under dynamic business cycles and unexpected crises. Therefore fti consulting is a prominent firm in the financial consultancy and services landscape and the company is largely recognized for its expertise and professionalism offering its clients financial services that are tailored to meet to meet their diverse nfti consulting . Fti consulting advises on risk management as well as it assists organizations on navigating through complex financial challenges and restructuring processes.

FTI Consulting Logo.
FTI Consulting Logo
Source: FTI Consulting.

FTI consulting operates across various departments and each are specializing in distinct areas of professionalism and expertise to help solve diverse and comprehensive solutions for their clients.

  1. Corporate finance and restructuring focuses on providing financial advisory services to companies who are undergoing financial distress, restructuring processes. Services may include success, debt restructuring, turnaround strategies, financial analysis, which FTI consulting may help optimize their clients’ financial performance.
  2. Forensic and litigation consulting includes investigating and litigation support services which FTI consulting assist their clients in addressing legal challenges, regulate increase, and fraud investigations. FTI consulting acts as the expert to provide analysis and support legal proceedings for their clients.
  3. Economic consulting, help their clients to conduct economic analysis, and provides analysis and insights into complex economic issues. FTI, consulting, economic, and financial consulting, helps their clients to understand more about economic and financial regulatory opportunities, and challenges in order to better support their companies, legal and business decisions.
  4. Technology helps clients to manage and leverage technology and enhance their IT infrastructure as well as security protocols and their businesses.
  5. Strategic communication helps clients to navigate through crisis and manage their reputation through effective communication with stakeholders. Strategic communication helps clients to reduce risk, and specializes in multiple areas, including corporate reputation, crisis communications, financial communications, public and government affairs, transaction communications, communications and insights.
  6. Risk and compliance focuses on helping organizations navigate through regulatory requirements as well as compliance procedures.
  7. Transaction advisory services provides support and advisory services to clients and mergers and acquisitions and other strategic transactions. FTI consulting provides valuation financial advisory services to support their clients in making their informed business decisions.
  8. Health solutions specializes in providing healthcare organizations and management support and helps them address challenges and seize opportunities

My internship

During my internship at FTI consulting as the corporate finance and restructuring summer intern, I was able to gain valuable experience in immersing in a dynamic environment that provided me with invaluable, hands-on experience in financial analysis as well as restructuring procedures. One of the many important rules, I undertook during my internship included conducting detailed company research and delving into various legal papers. I conducted detail company re-and also organized for the adjudication of debts. in conducting from our financial analysis I enjoyed researching through numerous financial data from our clients, reviewing searching, checking sorting and grouping for these data. By organizing transaction data, I was able to learn more about a company and also practice my attention to detail.

Required skills and knowledge

Through my involvement in various tasks during my internship, I understood more about the important skills and knowledge required during my work. For example, I realized it was important important to develop a keen eye for detail and hold a meticulous approach when scrutinizing financial data. The ability to gather interpret understand and organized complex financial data was important. I also realize the importance of effective communication in the field of corporate finance and restructuring while working in FTI consulting. For example, whether if it is engaging in internal discussions with my team or communicating with clients, I realize the importance of delivering clear and concise communication in order to better convey our financial analysis and concepts. It was also crucial in building relationship with our clients as well as facilitating teamwork within our department in order to ensure the process was smooth. Furthermore, for more technical skills I learned how important it was to understand how companies manage their finances to optimize value. my exposure to transaction analysis and financial analysis as well as understanding the transparency and financial reporting processes allowed me to understand How to during restructuring assessments. It is important to evaluate a companies financial health and implement strategic planning to improve its overall financial position.

What I learned

The internship experience was extremely rewarding to me. I learned how restructuring process works, restructuring involves assessing a company’s financial situation and making changes to its structure or capital structure in order to improve on the companies financial health. Incorporate financial and restructuring I learned about the transactional, valuation and advising procedures of FTI consulting. Through taking the role on advising for our clients, I learned how to advise companies in managing their finances in order to maximize their company value and minimize their risks. Furthermore, the internship experience not only gave me exposure to financial procedures scrutiny, but also honed my skills of being attentive to detail, ability gather and interpret complex information, which is a vital skill in financial analysis. I was able to hone my analytical skills, make informative decisions based on multifaceted data.

Financial concepts related to my internship

I present below three financial concepts related to my internship: debt restructuring, financial analysis, and valuation techniques.

Debt restructuring

The first financial concept I gained insight into during my intern internship was debt restructuring. Debt restructuring means modifying the terms of existing debt agreements to alleviate companies financial or improve its financial position. Debt restructuring processes may include various steps such as refinancing debt, extending maturity dates, negotiating interest rates etc. I learned about how companies may effectively manage their debt obligations in order to optimize their financial structure, and ensure their financial position’s health.

Financial analysis

The second financial concept I learned during my intern intern internship was financial analysis. By looking at bank statements and financial reports, I realize how critical financial analysis is to corporate finance and restructuring. I developed a deep understanding of this concept and skills in evaluating financial statements, understanding the meaning behind each number on the financial report as well as understood more about performance metrics in order to assess the companies financial health and performance. By reviewing detailed ledgers and analyzing and identifying significant transactions, I was better able to interpret complex financial data as part of the process in helping our client make better informed business decisions.

Valuation techniques

The third financial concept I learned was valuation techniques, as it is utilized to determine a companies asset or investment value. Not only did I learn more about cash flows, market trends and cash flow, I was also able to hone my skills in learning about valuation models in order to determine the fair value of assets, which was an important procedure in the restructuring process .

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About the author

The article was written in June 2025 by Annie YEUNG (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – Exchange Student, 2025).