Valuation methods

Andrea ALOSCARI

In this article, Andrea ALOSCARI (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2024-2025) explains about three fundamental valuation methods—Comparable Companies Analysis, Precedent Transactions Analysis, and Discounted Cash Flow (DCF) Analysis—and their role in achieving successful deal outcomes.

Which are the main valuation methods?

At the heart of M&A, or Mergers and Acquisitions, stands the concept of valuation, which helps businesses evaluate the idea of expanding or consolidating their position in the market. The estimation of the target company’s implied share price is vitally important both for buyers and sellers and can be conducted with three main valuation methods: Comparable Companies analysis, Precedent Transactions analysis, and Discounted Cash Flow analysis.

Comparable Companies Analysis

The Comparable Companies analysis, colloquially known as “trading comps,” is one of the most common methodologies in M&A valuation. This methodology depends upon the analysis of the target company in comparison to other similar publicly traded companies. The rationale driving this valuation method is simple: a company is valued at a multiple equivalent to that of comparable companies operating in the same industry, same geography and similar financial profiles.

It starts by selecting an industry peer group of companies. Industry, size, geographical location, growth prospects, and profitability usually influence the choice of these groups of companies.

When conducting the valuation of a company, it is necessary to calculate different multiples for the comparable firms and consecutively apply them to the company financials, in order to estimate the value of the target. The most frequently used multiples are Enterprise Value/EBITDA, Price per share/Earnings per share, and Enterprise Value/Revenues.

In specific cases, the analysis can be extended to include industry metrics. For instance, in the case of the telecommunications field, price-per-subscriber metrics may be considered more relevant, while revenue-per-user or annual recurring revenue multiples are more applicable in the case of software companies. Such metrics allow deeper insight, giving a closer approximation for valuation.

While Comparable Companies analysis is market-reflective and easy to apply, there are some limitations. In real life, it is very hard and sometimes impossible to find really comparable companies, especially for niche industries or highly diversified firms. Valuation metrics may also be distorted by recent market volatility and temporary anomalies; therefore analysts need to use judgment when interpreting the results.

Precedent Transactions Analysis

Precedent transaction analysis includes the analysis of past M&A transactions to derive an estimated value of the target company. This technique provides, therefore, an indication of the price that the market has paid in the past, for companies which are similar in some respects.

In carrying out this type of analysis, analysts gather data on transactions similar in nature, deal size, industry and time. Application of the relevant metrics-such as EV/EBITDA and EV/Sales- will subsequently yield a set of valuation multiples. Later on, these are adjusted for synergies, market conditions, and strategic importance, among other factors, to arrive at an estimation of the target company’s value.

The major advantage of Precedent transaction analysis is that this method is derived from actual transaction data, which includes premiums for control and synergies. Despite that, also this methodology has several disadvantages; the historic transactions may not indicate the existing market conditions, and exhaustive data of private deals could be pretty hard to find out. Notwithstanding these disadvantages, this method is one of the main ways to find out the valuation trends in the merger and acquisition market.

Discounted Cash Flow (DCF) Analysis

Discounted Cash Flow Analysis works on a completely different tangent, focusing on the intrinsic value of the company. Whereas both Comparable Company analysis and Precedent Transactions analysis estimate the value of a company based on market comparables, unlike them, DCF estimates a company’s value based on its future expected cash flows. This is useful in cases where the companies have a very different business model or operate in an industry with few comparables.

Essentially, DCF starts off with projecting free cash flows for the target company over some predefined period of projection. These are then discounted back to the present using the firm’s cost of capital, reflecting risks involved in the business. Further, will be necessary to calculate the terminal value of the company, discounting it to the present value and adding it back to the value of the projection period.

The strengths of DCF lie in its flexibility and that it is based on fundamental performance, rather than on market sentiment. However, it is highly sensitive to assumptions like growth rates, discount rates, and terminal value calculations. Even small changes in these inputs may strongly affect the final valuation outcome. It therefore requires analysts to be very strict in justifying their assumptions and testing the robustness of their models via sensitivity analysis.

For example, we can consider a technology start-up with very high growth potential. Analysts would project cash flows considering very rapid revenue increases and very significant reinvestments in technology. In contrast, one would focus on stable cash flows and incremental growth while valuing a mature industrial firm. The DCF model would be flexible enough to accommodate those contexts.

Combining Valuation Techniques

No valuation approach is ideal on its own. Each of the techniques gives a different insight and is hence suited for different situations. For instance, Comparable Company analysis would be perfect in judging the relative value of a company with its peers, whereas Precedent Transactions analysis provides a reality check based on actual market transactions. On the other hand, DCF provides an intrinsic in-depth analysis of the business, independent of the market noise.

In order to provide a more complete assessment, the triangulation approach is increasingly being used by incorporating findings from valuations of different techniques. As an example, in technology industries, Comparable Company analysis might provide a view on how markets valued comparable businesses, DCF might be applied with respect to long-term intellectual property value and growth potentials, Precedent Transactions analysis could help identify synergies from historical deals and therefore complement an otherwise forward-looking DCF approach.

Finally, the values are presented through a football field chart, a type of graph that is particularly helpful in visualizing the results and comparing various approaches to valuation. This chart usually assists stakeholders, but not only, in rapidly identifying overlap and outliers by portraying ranges of value generated from multiple approaches on one horizontal axis.

Example of a DCF valuation

In the following section, you can download an Excel file containing a valuation performed using the discounted cash flow (DCF) method. The file includes all the calculation details, such as projected cash flows, the discount rate applied, and the resulting net present value. Additionally, it contains sheets where various assumptions were made, along with the forecasting of financial statement items.

Example of DCF valuation
 Example of DCF valuation
Source: Personal analysis

In this discounted cash flow (DCF) analysis, the valuation is performed by projecting future free cash flows to the firm (FCFF) over a specified forecast period. Key assumptions, such as revenue growth, cost of goods sold (COGS) percentage, EBITDA margin, depreciation, capital expenditures (CapEx), and changes in net working capital (NWC), are made to forecast the financial statement items.

The projected FCFF values are then discounted using a weighted average cost of capital (WACC) to estimate their present value. A terminal value is calculated at the end of the forecast period, representing the business’s residual value. The total enterprise value is obtained by summing the discounted FCFFs and the discounted terminal value. Lastly, adjustments for net debt and outstanding shares are made to derive the implied equity value and share price.

Additionally, the file includes a sensitivity analysis to show how changes in growth rate and WACC impact the enterprise value.

You can download below the Excel file for valuation.

Download the Excel file  with a valuation example

Why should I be interested in this post?

The following post outlines some of the key valuation techniques in M&A transactions and is hence very useful for finance professionals, students, and anyone interested in the corporate world. This article offers practical tools that help make an appropriate assessment of deal value utilizing methodologies like Comparable Companies Analysis, Precedent Transactions Analysis, and Discounted Cash Flow Analysis.

Whether it is for an investment banking career or an intrinsic desire to understand how things work in corporate finance, it is possible to find some real actionable insight in this article. The combination of a theoretical base with real applications allows the reader to take these concepts into dynamic market environments.

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Useful resources

Joshua Rosenbaum and Joshua Pearl (2024) “Investment Bnaking : Valuaito, LBOs, M&A and IPOs” Wiley, Third Edition.

Alexandra Reed Lajoux (2019) “The Art of M&A, Fifth Edition: A Merger, Acquisition, and Buyout Guide” McGraw-Hill Education.

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

Aswath Damodaran (2024) Valuation Modeling: Excel as a tool (YouTube video).

About the author

The article was written in January 2025 by Andrea ALOSCARI (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2024-2025).

My Internship Experience in the Corporate & Investment Banking division of IMI – Intesa Sanpaolo

Andrea ALOSCARI IMI Intesa Sanpaolo

In this article, Andrea ALOSCARI (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2024-2025) shares his professional experience as a Summer Intern in the Corporate & Investment Banking Division of IMI – Intesa Sanpaolo.

About IMI – Intesa Sanpaolo

IMI – Intesa Sanpaolo is one of the largest and known banking groups in Italy, standing at the forefront of the Italian financial system and among major international banking groups. Based on the creation by the merger of two historic Italian banks, IMI – Intesa Sanpaolo stands today for innovation and sustainability as a leader in financial services. It operates a variety of services ranging from retail to corporate and investment banking, serving a vast clientele of millions of individuals and companies worldwide. It is committed long-term to creating value for its clients through sustainable performance combined with social responsibility.

Market Hub is Intesa Sanpaolo Group’s specialized department within IMI Corporate & Investment Banking Division. It is a business unit covering advanced trading and investment solutions for institutional and corporate clients. The Market Hub, in this regard, combines capital markets services with advanced technology in the said business unit to offer financial solutions that are efficient, transparent, and reliable. Thus, Market Hub acts as one of the leaders in the capital market world, offering everything from advanced electronic trading platforms to custom-designed investment solutions. It is here that I got an opportunity to work as a summer intern and hence acquire so much insight into the world of modern financial markets, working alongside some of the brightest brains in the industry.

Logo of IMI – Intesa Sanpaolo.
Logo of IMI - Intesa Sanpaolo
Source: the company.

My internship at IMI – Intesa Sanpaolo

In the Market Hub team of Intesa Sanpaolo, I was assigned diverse responsibilities that gave me a wide view of capital markets. Among the main tasks I carried out each day, I prepared reports summarizing and analyzing the results of the activity of my team in the previous day on fixed income, derivatives, and bonds. These reports were crucial in providing the proper overview of how the market was performing, how the team was doing, and whether it was hitting its goals. These reports required me to distill complex financial data into clear, concise, actionable insights for internal stakeholders and more senior bankers. It was there that I learned to present findings to both senior and peer colleagues.

Another important responsibility was to analyze the performance of Market Hub on different platforms such as Bloomberg, Tradeweb, BondVision, and MarketAxess. This included analysis of trading data and platform-specific metrics for market trend analysis and efficiency of performance. In the process, I gained significant knowledge of how technology fits into financial operations and how different trading platforms are designed in today’s investment banking world.

Every day, I actively participated in morning calls, where I discussed the most relevant market news with Milan, New York and London branches teams, regarding the current trends and the Market Hub results. This role called for being informed on all current global financial events and sharing the most relevant information that could have an impact on the team’s activity. Furthermore, I supported the sales team with client contract preparation, making sure everything was accurate in the paperwork, and facilitating smooth coordination with both sales and trading teams.

Finally, I received theoretical and practical training from Bloomberg, both at Intesa Sanpaolo and at its Milan headquarters. These really helped to boost my knowledge of the Bloomberg Terminal, from a basic to upper-intermediate level and hence to navigate market data more effectively.

The fast-paced environment of a trading desk.
The fast-paced environment of a trading desk
Source: StockCake.

My missions

My internship responsibilities were diverse and challenging, reflecting the dynamic nature of the Market Hub’s operations. My missions included:

Preparing Analytical Reports: I have collected and analyzed data in order to prepare reports on market trends, trading performance, and product evaluations. These reports were of utmost importance for internal strategy discussions and client presentations, requiring precision and a keen understanding of financial concepts. Producing these also helped me build a stronger command of data visualization techniques and financial storytelling.

Supporting Trading Desk Operations: I analyzed real-time market data to assist traders in making informed decisions. This entailed monitoring key indicators, assessing liquidity conditions, and identifying opportunities for optimizing trade execution strategies. The depth of analysis required for this role provided me with a strong foundation in market mechanics and trading dynamics.

Collaborating with the Sales Team: I worked with the sales team where I analyzed client needs, helped the sales to prepare tailored financial solutions, and ensured effective communication between the sales and trading teams. This experience has allowed me to learn how to manage client relationships and how product offers must be made, in order to meet clients’ expectations and consequently establish important partnerships.

Required skills and knowledge

The internship required technical expertise, analytical acumen, and interpersonal skills. From a technical point of view, it engaged my knowledge of financial instruments such as derivatives, bonds, and fixed-income products. Knowledge of data analysis and data visualization by tools such as Excel, Bloomberg and Power-BI has been fundamental in the execution of data analysis. Proficiency in Excel allowed me to go through big spreadsheets of data and extrapolate for the team important information. Similarly, Bloomberg Terminal was helpful to access market data, monitor trading activity, or conduct deep research on any financial security.

Another very useful aspect was the quantitative and statistical knowledge. My comprehension of the main concepts such as regression analysis and time series forecasting, also if not strictly necessary, enabled me to interpret complex datasets and support predictive analysis tasks on Power-BI.

Equally important were the soft skills that enabled me to thrive in a high-pressure environment. Effective communication was extremely important because it called for frequent presentation of the results, on quite a technical level, to the Heads of the team. Adaptability and problem-solving were other critical skills during my internship, especially in periods when the workload was heavy and there was the necessity to reorganize the priorities. Lastly, teamwork ability played a significant role when I was assigned collaborative tasks with other interns and analysts.

What I learned

My internship at Intesa Sanpaolo was really enriching and opened my eyes to the world of financial markets and the strategic relevance of technology in modern banking. One of the most important lessons learned during this experience, if not the most important, is surely the precision and attention to detail that every operation of a financial nature should have. Whether in the analysis of market data or in the preparation of presentations for clients, everything had to be extremely precise and had to respect high standard.

I also learned a lot about how trading and market analysis works. How customer behavior, market dynamics, and technology systems interact allowed me to gain a comprehensive understanding of the variables affecting trading results. The internship has also made clear the importance of teamwork and communication toward the success of an organization. The interpersonal skills developed in working closely with leaders of the sector will undoubtedly help me in the future.

The use of Bloomberg Terminal, a very important tool in researching market data, real-time financial news, and deep research into different asset classes, was another skill I was further refining. Bloomberg allowed me to find instantly relevant information and develop actionable insight, crucial both for the trading strategy and for client presentations. This not only helped me to improve my technical knowledge but also instilled in me the need to use the right tools to perform efficient analysis.

Perhaps, most importantly, this experience allowed me to dive into the transformative impact of technology on the financial industry: from automated trading systems to advanced analytics tools, integration of technology into financial processes changes how institutions operate. Overall, this experience encouraged me to go deeper into the area where finance and technology meet.

Bloomberg Terminal, an essential tool for market analysis and decision-making.
Bloomberg Terminal, an essential tool for market analysis and decision-making IMI Intesa Sanpaolo
Source: Bloomberg.

Financial concepts related my internship

I present below three financial concepts that were particularly relevant to my internship experience: market liquidity, derivatives and bond pricing, and trade execution algorithms.

Market Liquidity

Market liquidity refers to the ease with which an asset can be bought or sold in the market without causing a significant change in its price. Trading volumes, bid-ask spreads, and other indicators are only a few aspects that must be analyzed in an attempt to assess the depth and stability of markets. I learned that various events in the market such as the decisions made by central banks or geopolitical events, have huge influences on liquidity. This knowledge also underlined timing in trading decisions for maximum efficiency and minimum risk exposure.

Derivatives and Bond Pricing

The internship gave me an opportunity to learn and understand some of the intricacies related to derivatives and bond pricing. I understood, also if not personally performed, the ways of pricing derivatives, options, and futures based on volatility, interest rates, and prices of the underlying assets. I mastered methodologies for bond pricing, including the time value of future cash flows and periodic coupon payments in addition to the face value at maturity. This is based on interest rate dynamics and credit spreads, which affect fixed-income valuation. Although I did not perform the valuations myself, this experience really improved my capabilities to interpret quantitative models and to read complex financial data.

Trade Execution Algorithms

These advanced trading tools are engineered to achieve the best possible outcome in trades at an extremely low market impact and with a low transaction cost. In an electronic trading environment, I was privileged to pick up some concepts on the design and application of these algorithms. Knowledge about how the algorithms were calibrated in a balance between speed, cost, and market conditions gave me valuable insight into technological changes shaping today’s practices of trading.

An example of market liquidity trends analysis.
Bloomberg Terminal, an essential tool for market analysis and decision-making IMI Intesa Sanpaolo
Source: ETFstream.

Why should I be interested in this post?

This article will be really helpful for all students who want to orient their careers in finance, investment banking, and trading. It underlines the importance of practical experience within such a prestigious institution as IMI – Intesa Sanpaolo and the knowledge and abilities necessary for such a career. Understanding how markets and technology interact, in fact, becomes key for every finance aspirant, and this internship is a great illustration of that.

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Useful resources

IMI Intesa Sanpaolo – Corporate & Investment Banking Division

Market HUB Intesa Sanpaolo

About the author

The article was written in December 2024 by Andrea ALOSCARI (ESSEC Business School, Global Bachelor in Business Administration (GBBA) – 2024-2025).