Understanding organizations’ role in bargaining tariffs

July 12, 2025 by 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.

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

July 12, 2025 by 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

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.

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

July 12, 2025 by 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

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.

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).

Bitcoin : Défis et Opportunités

June 30, 2025June 30, 2025 by Jean-Marie CHOFFRAY

Dans cet article, Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology) introduit son recent article “Bitcoin : Défis et Opportunités”.

Nier la réalité de bitcoin n’en change pas la nature… Cette courte note a pour objet de fournir au lecteur une première synthèse des principaux Défis et Opportunités engendrés par l’adoption et la diffusion de Bitcoin (avec « B » majuscule, le réseau informatique). C’est une Révolution Technologique dont les conséquences s’observeront dans les décennies à venir. En effet, le dernier bitcoin (avec « b » minuscule, le moyen d’échange) sera produit vers 2140 ! Suivent sept propositions de réflexion et d’action.

Les trois ANNEXES – Le Triomphe de la Vie dans la Victoire de Bitcoin ; Bitcoin est un rêve, un idéal, un espoir ; Mille quatre cent milliards de dollars – offrent au lecteur un complément d’information lui permettant d’approfondir sa compréhension du phénomène et son analyse de la situation actuelle. De nombreuses et excellentes sources d’informations sont disponibles et consultables sur internet, notamment : https://bitcoin.org/fr/ ; Bitcoin Statistics ; Strategy’s Bitcoin for Corporations.

Qu’est-ce que Bitcoin ?

La Technologie Bitcoin comporte deux éléments : (1) une Base de Données Séquentielle qui intègre aujourd’hui (~) 1,5 milliard de transactions irréversibles, incorruptibles et inviolables entre des agents réels et/ou virtuels – robots ? et (2) un Système d’Exploitation Décentralisé (Bitcoin Core) permettant de valider, de sécuriser et d’enregistrer de telles transactions. Un bitcoin est un moyen d’accès à cette base de données, permettant à son détenteur d’effectuer une transaction irréversible, incorruptible et inviolable ; reconnue comme telle par le réseau. Selon l’objet de la transaction, il s’agit donc d’un droit de propriété digital, d’un moyen d’échange et/ou d’une réserve de valeur ; monnaie et/ou capital digital ?

Ainsi, bitcoin est un objet digital qui peut être stocké, accumulé, transféré et/ou vendu. Le nombre de bitcoins émis diminue exponentiellement dans le temps et le dernier exemplaire sera produit vers 2140. Leur nombre est également limité dans l’espace ; le réseau n’en produira jamais que vingt et un millions. (cf. article original de Satoshi Nakamoto : Bitcoin, un système de paiement électronique). La capitalisation boursière actuelle du réseau (~ $2T : deux mille milliards de dollars) en fait le cinquième actif financier mondial. Soit, plus que la capitalisation cumulée des six plus grandes banques mondiales ; de l’ordre de trois fois le total de bilan de la Banque Centrale Européenne ; ou, encore, deux fois le PIB de la Suisse…

Défis et opportunités

On peut considérer aujourd’hui que la Technologie Bitcoin est quasiment indestructible. Sa probabilité d’effondrement total est estimée à moins de 1%. Pour deux raisons : (1) un éventuel dysfonctionnement du réseau n’affecterait que marginalement la base de transactions séquentielle actuelle (i.e. l’histoire exhaustive des transactions cryptées et encodées depuis 2009) et (2) la décentralisation géographique, technologique et financière du réseau garantit la robustesse – fiabilité et validité – de son mécanisme de gouvernance (e.g. Proof of work). Il va donc falloir apprendre à vivre avec bitcoin, qu’on le veuille ou non, qu’on le souhaite ou pas ! Ceci est d’autant plus vrai que plusieurs pays, dont les États-Unis d’Amérique, ont officialisé leur soutien à cette évolution digitale de l’écosystème bancaire et financier (cf. Strategic Bitcoin Reserve Bill).

Propositions de réflexion et d’action

Pour toute entité publique ou privée soucieuse de marquer sa présence dans ce nouvel espace économique, caractérisé par une forte croissance (~ 60%/an) et une volatilité comparable (~ 60%/cycle de 4 ans) :

Contribuer à créer un Centre Interuniversitaire d’intelligence, d’expertise et de compétence centré sur Bitcoin et les technologies annexes ou induites.
Organiser un Symposium Annuel, destiné à rassembler les acteurs du secteur, à diffuser les bonnes pratiques et à susciter l’innovation.
Constituer un Réseau d’Opérateurs (i.e. bitcoin Miners) assurant une présence effective à l’échelle mondiale et sécurisant l’accès aux transactions (cf. mise en place de Mining Pools).
Inviter les entreprises – et toute autre institution dotée de Fonds Propres – à adopter le Standard Bitcoin, en y consacrant (~3-5%) de leur Actif Net.
Destiner les Excédents Énergétiques – sources intermittentes, surplus nucléaire, cycles d’inférence (Intelligence Artificielle) etc. – à la production et au transfert de bitcoins ; au développement technologique – matériels et logiciels – sous-jacent ; et à la création de produits et services nouveaux.
Constitution d’une Réserve Stratégique – régionale et/ou nationale – de bitcoins tendant vers 3-5% de la richesse économique (cf. Senateur C. Lummis).
Émission de BitBonds : emprunts obligataires adossés (~10%) à bitcoin (cf. Andrew Hohns : BitBonds, An Idea Whose Time Has Come)

Lire la suite de l’article

Autres articles sur le blog

▶ Snehasish CHINARA Bitcoin: the mother of all cryptocurrencies

Ressources utiles

Choffray Jean-Marie (2025) Bitcoin : Défis et Opportunités Liège Université

Choffray Jean-Marie List des publications Liège Université

A propos de l’auteur

L’article a été rédigé en juin 2025 par Jean-Marie CHOFFRAY (Professeur Ordinaire Honoraire d’Informatique Décisionnelle à l’Université de Liège, PhD-77, Management Science, Massachusetts Institute of Technology).

Behavioral finance

June 30, 2025 by Mahé FERRET

In this article, Mahe FERRET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026) explains the appeal and challenges of behavioral finance when investing.

Introduction

Behavioral finance is a psychological and economic finance field that allows us to understand how investors – individuals and institutions – make financial decisions. Unlike traditional finance, which assumes that investors are rational actors who always make the optimal decisions to maximize profits based on all available information, behavioral finance recognizes that decisions are often influenced by cognitive biases and emotional responses.

As the financial industry becomes more complex, understanding the psychological biases of investor behavior becomes essential. Behavioral finance includes a more realistic human-centered perspective for analyzing market reactions, making it a crucial area of study for academics, investors, and policymakers alike.

History and Theoretical Foundations

Behavioral finance challenges the classical economic model of the “Homo Economicus”, which states that an investor is a fully rational decision-maker. Instead, it builds on theories about cognitive biases, unconscious and systematic errors that occur when people make a decision.

It also challenges classical theories such as the Efficient Market Hypothesis and Expected Utility Theory. These models presume that markets are efficient (stock prices reflect all available information) and that investors act logically. However, evidence from historical events (financial asset bubbles and market crashes) suggests otherwise, with investors having irrational behavior leading to mispricing (an over or undervaluation of the market price) and high volatility, which could result in potential negative return investments.

Overconfidence is one of the most studied biases. This bias leads investors to overestimate their knowledge and ability to make decisions, often resulting in excessive trading and poor returns. On the other hand, confirmation bias influences investors to seek information that supports their preexisting beliefs, sometimes ignoring evidence. Continuing along this path, herding bias reflects the tendency to mimic the actions of the majority, ignoring personal beliefs or individual analysis. This can generate bubble behavior, such as buying simply because of a trend, even when it seems irrational. Finally, among the long list of other biases, the disposition effect can harm long-term returns. Most of the time, investors sell assets that have increased in value to secure gains but keep assets that have dropped in value to avoid facing a loss.

These biases are not just theory and can explain some behaviors as seen in market crisis, where collective overconfidence and optimism fueled risky lending and investment practices.

Case Study: The 2008 Financial Crisis and Cognitive Biases

The 2008 financial crisis is a significant example of how cognitive biases can influence market behavior. While traditional economists tried to explain the irrational behaviors behind the collapse of global markets, behavioral finance offered an explanation: cognitive biases.

The crisis was a result of years of rising home prices in the U.S. housing market, which created a false sense of security. Financial institutions, driven by overconfidence in their risk management and in the fact that housing prices would continue to rise, issued endless subprime mortgages to borrowers with low credit profiles. These loans were then turned into complex financial instruments like mortgage-backed securities (MBS) and collateralized debt obligations (CDOs), sold to investors worldwide.

According to Montgomery (2011), a collective psychological bias led to this irrational behavior. Overconfidence pushed investors and institutions to underestimate the high risk of the defaults and overtrade, while confirmation bias caused them to ignore warning signs and only select information that supported their vision of the future. The investors were also too optimistic about the market, thinking that it would be in their favor, leading to an underestimation of systemic risk (risk that affects the entire financial system).

Evolution of the S&P 500 index in 2008.
Evolution of the S&P 500 index in 2008
Source : invezz

This chart visually demonstrates the decline of the S&P 500 index during the market crash, illustrating how cognitive biases affect investor decisions. The index reached a high of 1576, marking the peak of the pre-crisis bull market. The market crashed by 57.7% from its peak and lasted for a total a year and a half. As the crisis progressed, panic selling spread rapidly, as a symbol of herd behavior, accelerating the decline and increasing the losses. Many investors also sold off assets at a loss to avoid more losses, despite fundamental research suggesting long-term recovery potential, which can be translated as a loss aversion bias.

These biases all contributed to the formation of a speculative bubble, which exploded when the housing prices began to fall and defaults rose, triggering a global credit freeze and economic recession.

Nudges, a strategy to mitigate biases ?

Behavioral finance offers an explanation for anomalies in market behavior but can also be used as a tool to improve decision-making. Strategies such as “nudges” (Thaler & Sunstein, 2008) could improve structured environments for decision making without restricting individual freedom. By changing the choice architecture, or “organizing the context in which people make decisions”, such as with default options or checklists, biases can be mitigated.

An example of a nudge strategy from “Nudge” (Thaler and Sunstein, 2008) is the use of automatic enrollment in retirement savings plan, such as 401(k)s in the U.S. Traditionally, employees had to opt in to participate in their company’s retirement savings plan. Many did not enroll because they procrastinated or found the process confusing. The nudge would be to change the default option so that employees are automatically enrolled in the retirement plan, but can opt out if they choose. Like in the finance industry, the choice architecture has changed concerning the default option, and this small change led to high increases in participation rates among employees. Changing the choice architecture in the decision-making process could be the solution to minimize cognitive biases and their negative impact on investments.

Why should I be interested in this post?

As a business student, understanding market anomalies—such as overreactions to news or momentum effects—is essential because they reveal limitations in classical finance theories that assume investors are always rational and markets efficient. Real markets often behave differently, with phenomena like speculative bubbles and panic selling challenging these traditional views. Studying behavioral finance offers valuable insights into the psychological factors and cognitive biases that influence investor decisions. This knowledge is crucial for future business professionals, as it helps improve decision-making, risk management, and strategy development in finance and beyond. Recognizing how human behavior impacts markets prepares business students to navigate real-world complexities more effectively.

Useful resources

CFA Institute (2025). Market Efficiency.

Montgomery, H. (2011). The Financial Crisis – Lessons for Europe from Psychology.

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk.

Thaler, R.H. and Sunstein, C.R. (2008). Nudge: Improving Decisions about Health, Wealth, and Happiness. London: Penguin Books.

About the author

The article was written in June 2025 by Mahe FERRET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026).

Selling Structured Products in France

June 30, 2025 by Mahé FERRET

In this article, Mahé FERRET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026) explains the appeal and challenges of selling structured products in France.

Introduction

Structured products are investment products combining traditional assets (stocks, bonds, indexes…) with derivatives (options, futures…) to offer customized returns tailored to an investor’s risk profile.

In recent years, structured products have gained popularity due to persistent low interest rates and increased market volatility. For instance, buffered ETFs reached $43.4 billion in assets in 2024 according to N.S Huang (Kiplinger, 2024). In France, the market has grown significantly, reaching €42 billion in 2023, an 82% increase over two years, showing investors’ interest in higher returns with safety. Sales teams in investment banks actively seek to answer this demand by offering structured solutions to wealth managers, private banks and institutional investors, using payoff strategies and risk scenarios to support which product to choose.

Why Structured Products Appeal to French Investors

These products are particularly interesting for France’s investment culture, known for capital protection and an income preference due to low interest rates and relatively more risk-averse type of investors. The structured products appeal to French investors as they aim to protect the initial investments and offer higher returns than traditional bonds.

Capital protection means that an investor will not lose their initial investment, even if the market is dropping, and will earn a profit if the market performs well. As an example, BNP Paribas offers Capital Protection Notes (CPNs) tied to the S&P500 that guarantees the initial investment amount at maturity and 130% of the average performance of the index if it rises. If the index’s performance is zero or negative, the investor will only receive its capital back, with no additional return. In client meetings, sales professionals use scenario simulations and historical data to demonstrate the potential returns under different market conditions. Another type of structured product that could interest sustainable caring French investors could be an ESG (Environmental, Social, Governance) note tied to a renewable energy index. As an example, an ESG-linked structured product is tied to indices like the Euronext Eurozone ESG Large 80 Index, with a fixed or conditional coupon of 3 to 5% annually and a maturity of usually 5 to 8 years. With the increasing demand for these products, ESG investments are more and more promoted by Sales through a sustainable aspect, especially to family offices and pension funds committed to responsible investing. ESG products include ESG factors while still using traditional assets like stocks, allowing investors to search for both financial returns and positive societal impact. They often include stock from companies with already strong ESG processes, green bonds supporting environmental projects or derivatives linked to sustainability indicators.

Regulatory Environment in France

In France, the Autorité des marchés financiers (AMF) regulates the sales of structured products to ensure fairness and transparency. These products are complex, and regulations like PRIIPs (Packaged retail and insurance-based investment products) require a Key Information Document (KID) to explain them in simple terms. MiFID II (Markets in Financial Instruments Directive II) also mandates clear disclosure of risks and costs. ESG products, in particular, are under scrutiny to prevent greenwashing. It is an important aspect for the Sales team to consider, as they must respect regulatory requirements at every step with the clients, from pre-trade client conversations to post-sale documentation, and integrate it into their sales pitch.

Client Segments and Tailored Offerings

As complex as these products can be, one of their benefits is that they can be tailored to each investor’s profile risk (more or less tolerance to risk). The structured products can be ideal for retail investors needing safe products. A retail investor could be a retiree seeking a complementary source of revenue and would seek a PPN guaranteeing €10,000 principal with a 3% coupon if the CAC 40 stays flat or rises. The product can be chosen according to the risk level and could be a principal-protected note (PPN), for safer investments. However, less risk-averse investors could seek customized high-return options like a Rainbow note (a derivative-based product designed to offer potential returns based on the performance of a basket of assets, often with a focus on the best or worst performers within that basket) and institutions would need complex products for portfolio strategies like a buffered note. A rainbow note is a product linked to at least two assets and answers a diversification benefit, with a growth and stability balance. Sales teams must match the product structure to the investor’s objectives by collaborating with structuring desks (Department of the trading room that creates the structure that best fits the demands of the client) and traders to design personalized solutions. For a pension fund, a buffered note, designed to allow you to earn a return based on the performance of a stock but with a “buffer” to protect from some losses, offers risk management characteristics, with protection against the first 10% of losses on a global equity index.

Benefits

Structured financial products offer several advantages that make them attractive to a wide range of investors. From a sales perspective, they are attractive tools to meet a client’s needs with a lot of advantages. First, they often include capital protection, meaning that even if the underlying asset’s performance declines, the investor’s capital will be preserved at a predetermined protection level. Additionally, these products can provide regular income, but only to the extent that specific market conditions are met during the investment period. Structured products also allow investors to bet on market volatility, meaning that the products’ prices tend to fall when volatility rises. This creates an opportunity to buy low during periods of high volatility and sell when the volatility declines. Furthermore, these instruments both answer the client’s investment preferences and the diversification potential by offering many investment options across different asset classes. Sales professionals often highlight how these products provide a unique combination of stability and performance that standard products cannot offer.

Challenges

Structured products, despite their benefits, also present common obstacles for investors and for the sales team. Sales must be able to clearly explain these risks using simplified language to make it understandable to even non-expert clients. First, there is the issuer’s risk. Since these tools are issued by banks or other intermediaries, there is a risk that the issuer becomes insolvent or unable to meet its obligations, and the investor may not receive their returns at maturity. There is also an underlying risk, as the value of a structured product depends directly on the performance of the underlying asset, which is subject to high volatility. In extreme cases, the product’s value could go to zero if the asset performs poorly. A second aspect is sometimes the lack of liquidity that can be common for such unique products. Although some products are listed and supported by market makers there is no guarantee of continuous availability in the market. Investors may have difficulties buying or selling the product before maturity, which could lead to unexpected losses due to the absence of market participants at the time of the transaction. Finally, the product can be seen as complex because they are multi-layered, combining different asset types (indices, funds) with different payoff conditions and risk levels.

Complexity of a basket of equity indices.

Source: AMF.

On this graph, each added asset increases the product’s complexity, making it harder to assess risk, performance and transparency. An investor needs then to evaluate each asset but also their own impact within a basket.

Why should I be interested in this post?

As an ESSEC student interested in business and finance, I found that learning about structured products really helped me understand how financial institutions create investment solutions based on different risk profiles. They’re a great example of how finance can combine both protection and performance. For anyone considering a career in sales, asset management, or investment banking, getting familiar with these products is a great way to build practical knowledge and better understand how finance works in the real world.

Useful resources

AMF & ACPR Analysis of the French structured product market

Kiplinger Buffered ETFs: What are they and should you invest in one?

Itransact BNP PARIBAS S&P 500 100% CAPITAL PROTECTED NOTE 5

Yassien Yousfi ESG structured products: challenges and opportunities

Klara Gjorga Equity Derivatives and Structured Products Sales

Line Grinden Quinn – Structured Products: Sound strategy or sales pitch?

About the author

The article was written in June 2025 by Mahe FERRET (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026).

How blockchain challenges traditional financial systems: Lessons from my ESSEC thesis

July 1, 2025May 29, 2025 by Alexandre GANNE

In this article, Alexandre GANNE (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2025) shares key insights from his bachelor thesis on blockchain technology and its implications for traditional banking systems.

Introduction

This post is the result of a year-long academic research project conducted as part of my final thesis at ESSEC Business School. It explores how the growing adoption of blockchain technology is redefining core principles of traditional financial systems and the strategic implications this transformation holds for banking institutions.

The disruptive nature of blockchain

Blockchain is often described as the cornerstone of the next technological revolution in finance. It allows for the decentralization of data storage and value exchange, eliminating the need for central authorities to validate transactions. With distributed consensus mechanisms and cryptographic security, blockchain systems can operate autonomously and transparently. These features make it not just a new tool, but a foundational shift that could reshape core banking functions such as recordkeeping, interbank transfers, and credit issuance. Its key characteristics, immutability, programmability, disintermediation, and transparency, pose significant challenges to the centralized model of traditional finance.

From intermediation to decentralization

One of blockchain’s most radical promises is disintermediation. Traditional financial systems are heavily reliant on intermediaries such as banks, brokers, and clearinghouses to establish trust and validate transactions. Blockchain introduces the ability to execute trustless peer-to-peer exchanges using cryptographic proofs and decentralized ledgers. For example, platforms like Ethereum enable the deployment of smart contracts, self-executing programs that automatically enforce the terms of a contract without human intervention, drastically reducing friction and cost.

Security and auditability

Unlike traditional databases that are vulnerable to manipulation or single points of failure, blockchain offers a tamper-proof and chronologically auditable data structure. This makes it a valuable tool for regulatory compliance and fraud prevention.

Implications for the banking sector

Custody and settlement

Traditional banks act as intermediaries for the settlement of securities and custody of assets. Blockchain-based tokenization could eliminate the need for such intermediaries by allowing real-time settlement and direct ownership recording on-chain.

Compliance

Know Your Customer (KYC) and Anti-Money Laundering (AML) procedures are critical, yet often duplicative and costly for financial institutions. Blockchain can streamline these processes by allowing users to maintain a single, verified digital identity that can be securely shared across multiple entities. Through permissioned blockchain networks, institutions can access and update identity records in real time, increasing efficiency while maintaining regulatory compliance. Additionally, immutable audit trails enhance traceability and accountability.

New business models

The rise of decentralized finance (DeFi) introduces new paradigms in financial services, automated lending, yield farming, insurance, and derivatives, all operating without traditional intermediaries. In response, incumbent banks are exploring strategic partnerships, investments in blockchain startups, and internal initiatives to tokenize assets or build proprietary custodial solutions. Hybrid models, blending regulated infrastructure with decentralized services, are likely to emerge as a dominant trend over the next decade.

Why should I be interested in this post?

For any ESSEC student or finance professional interested in the frontier of financial innovation, this article distills the key findings of a year-long academic thesis dedicated to understanding how blockchain is transforming our industry. It bridges theory and practice, highlighting both opportunities and risks. As regulators, institutions, and entrepreneurs continue to shape the future of financial systems, understanding blockchain is no longer optional, it is essential to navigate and lead in tomorrow’s economy.

Useful resources

BIS – The implications of decentralised finance

ECB Blockchain

FSB The Financial Stability Risks of Decentralised Finance

About the author

The article was written in May 2025 by Alexandre GANNE (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2025).

Pricing Weather Risk: How to Value Agricultural Derivatives with Climate-Based Volatility Inputs

May 29, 2025 by Mathias DUMONT

In this article, Mathias DUMONT (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026) explains how weather risk impacts the pricing of agricultural derivatives like futures and options, and how climate-based data can be integrated into stochastic pricing models. Combining academic insights and practical examples, including a mini-case from the SimTrade Blé de France simulation, the article illustrates adjustments to models such as the Black-Scholes-Merton model for temperature and rainfall variables in valuing agricultural contracts.

Introduction

Extreme weather has always been a critical factor in agriculture, but climate change is amplifying the frequency and severity of these events. From prolonged droughts to unseasonal floods, weather shocks can send crop yields and commodity prices on wild rides. This rising uncertainty has given birth to weather derivatives – financial instruments designed to hedge weather-related risks – and has made volatility forecasting a key challenge in pricing agricultural contracts. In fact, as businesses grapple with climate volatility, trading volume in weather derivatives has surged. CME Group saw a 260% increase last year (CME Group, 2023). The question for traders and risk managers is: how do we quantitatively factor weather risk into the pricing of futures and options on crops like wheat and corn?

Weather Risk and Agricultural Markets

Weather directly affects crop supply. A bumper harvest following ideal weather can flood the market and depress prices, whereas a drought or frost can decimate yields and trigger price spikes. These supply swings translate into volatility for agricultural commodity markets. For example, during the U.S. drought of 2012, corn prices skyrocketed, and the implied volatility of corn futures jumped by over 14 percentage points within a month, reaching ~49% in mid-July. Such surges reflect the market rapidly repricing risk as participants absorb new climate information (in this case, worsening crop prospects). Seasonal patterns are also evident: harvest seasons tend to coincide with higher price volatility because that’s when weather uncertainty is at its peak. Studies show that harvesting cycles create predictable seasonal volatility patterns in crop markets – when a critical growth period is underway, any shift in rainfall or temperature forecasts can send prices swinging.

Beyond affecting supply quantity, weather can influence crop quality (e.g., excessive rain can spoil grain quality) and even logistic costs (flooded transport routes, etc.), further feeding into prices. The interconnected global nature of agriculture means a drought in one region can reverberate worldwide. As noted in the SimTrade Blé de France case, weather conditions in France influence the quantity and quality of wheat the company harvests, while weather conditions around the world influence the international wheat price. In the Blé de France simulation (which models a French wheat producer’s stock), participants see how news of floods or droughts translate into stock price moves. For instance, the company might project a 7-million-ton wheat harvest, but analysts’ forecasts range from 6.5 to 7.2 Mt – with the realized level highly weather-dependent in the final weeks of the season. A poor weather turn not only shrinks the crop but boosts global wheat prices, creating a complex revenue impact on the firm. This mini-case underlines that weather risk entails both volume uncertainty and price uncertainty, a double-whammy for agricultural firms and their investors.

Case Study: Weather Shocks in Wheat Markets

To illustrate the impact of weather risk on commodity pricing, consider three simulated scenarios for an upcoming wheat growing season: (1) **Favorable weather**, (2) **Moderate conditions**, and (3) **Severe weather** such as drought. Each scenario generates a distinct price trajectory in the wheat market. Under favorable weather, prices tend to remain stable or decline slightly, particularly at harvest, due to strong yields and potential oversupply. In moderate conditions, prices may rise modestly as the market adjusts to balanced supply and demand. In contrast, severe weather triggers early price rallies as concerns about yield shortfalls emerge, followed by sharp spikes once crop damage becomes evident. For producers and traders, anticipating these divergent price paths is essential for pricing contracts, managing risk exposure, and structuring hedging strategies effectively.

Figure 1. Simulated commodity price paths under three weather scenarios.
Simulated Price Paths
Source: Author’s simulation.

Figure 1. shows the simulation of commodity price paths under three weather scenarios: severe weather (red), moderate weather (orange), and favorable weather (green). A mid-season weather forecast alert (Day 15) triggers a shift in market expectations, causing price divergence. This simulation illustrates how weather shocks and forecasts impact commodity pricing through volatility and revised yield expectations.

From a risk management perspective, tools exist to handle these contingencies. Farmers or firms concerned about catastrophic weather can turn to weather derivatives for protection. Weather derivatives are financial contracts (often based on indexes like temperature or rainfall levels) that pay out based on specific weather outcomes, allowing businesses to offset losses caused by adverse conditions. They have been used by a wide range of players – from utilities hedging warm winters, to breweries hedging late frosts. These instruments can be customized over-the-counter or traded on exchanges. Notably, CME Group lists standardized weather futures and options tied to indices such as heating degree days (HDD) and cooling degree days (CDD) for various cities. The existence of such contracts means that even when commodity producers cannot fully insure their crop yield, they might hedge certain aspects of weather risk (like an unusually hot summer) via financial markets. In our context, a wheat farmer worried about drought could, say, buy a weather option that pays off if rainfall falls below a threshold, providing funds when their crop output (and thus futures position) suffers.

Climate-Based Volatility in Derivatives Pricing

How can weather uncertainty be incorporated into derivative pricing models? Classic option pricing, such as the Black-Scholes-Merton model, assumes a fixed volatility for the underlying asset’s returns. For agricultural commodities, that volatility is anything but constant – it ebbs and flows with the weather and seasonal progress. Practitioners thus often use stochastic volatility models or at least adjust the volatility input over time. For example, one might use higher volatility estimates during the crop’s growing season and lower volatility post-harvest when output is known. This practice parallels how equity traders anticipate higher volatility in stock prices ahead of major earnings or profit announcements, and lower volatility after the announcement of profits by the firm.

Like companies facing performance surprises, weather shocks inject information asymmetry into the market, which must be priced into the option premiums. This aligns with the observed Samuelson effect, where futures contracts on commodities tend to have higher volatility when they are near maturity (coinciding with harvest uncertainty).

Market prices of options themselves reflect these expectations. When a looming weather event is expected to cause turmoil, options premiums will rise. The metric capturing this is implied volatility – the volatility level implied by current option prices. Implied vol is essentially forward-looking and will jump if traders foresee choppy waters ahead. Empirical evidence shows that extreme weather forecasts translate into higher implied vols for crop options. In 2012, as drought fears intensified, corn option implied volatility spiked (alongside futures prices). Conversely, once a forecasted drought started being relieved by rains, implied volatility eased off, signaling that some uncertainty had been resolved. A recent study also found that integrating meteorological data (like rainfall and temperature anomalies) into volatility modeling significantly improves the ability to hedge risk in agricultural markets. In other words, the more information we feed into our models about the climate, the more accurately we can price and hedge these derivatives.

Figure 2. Implied Volatility of Crop Options Over Time with Weather Events
Line chart showing implied volatility of crop options over 12 months with spikes linked to weather events
Source: Author’s simulation.

This simulation illustrates the evolution of implied volatility over a 12-month crop cycle. Forecasted climate events—drought (Month 3), frost (Month 6), heatwave (Month 8), and rainfall shortage (Month 11)—lead to moderate but distinct volatility spikes. As uncertainty resolves, volatility returns to baseline.

One practical approach to pricing under climate uncertainty is to use scenario-based or simulation-based models. Instead of assuming a single volatility number, an analyst can simulate thousands of possible weather outcomes (perhaps using historical climate data or meteorological forecast models) and the corresponding price paths for the commodity. Each simulated price path yields a payoff for the derivative (e.g. an option’s payoff at expiration), and by averaging those payoffs (and discounting appropriately), one can derive a weather-adjusted theoretical price. This Monte Carlo style approach effectively treats weather as an external random factor influencing the commodity’s drift and volatility. It’s particularly useful for complex derivatives or when the payoff depends explicitly on weather indices (such as a derivative that pays out if rainfall is below X mm).

When the derivative’s underlying is the commodity itself (e.g. a corn futures option), traditional risk-neutral pricing arguments still apply, but the challenge is forecasting volatility. Traders often adjust the volatility smile/skew on agricultural options to account for asymmetric weather risks – for instance, if a drought can cause a much bigger upside move than a rainy season can cause a downside move, call options might embed a higher implied volatility (reflecting that upside risk of price spikes). This is observed in practice as well; extreme weather events can distort the implied volatility “skew” of crop options, as out-of-the-money calls become more sought after as disaster insurance.

In contrast, if the derivative’s underlying is a pure weather index (say an option on cumulative rainfall), then pricing becomes more complex because the underlying (rainfall) is not a tradable asset. In such cases, the Black-Scholes-Merton formula is not directly applicable. Instead, pricing relies on actuarial or risk-neutral methodologies that incorporate a market price of risk for weather. For example, one method is to estimate the probability distribution of the weather index from historical data, then add a risk premium to account for investors’ risk aversion to weather variability, and discount expected payoffs accordingly. Another method uses “burn analysis” – taking historical weather outcomes and the associated financial losses/gains had the derivative been in place, to gauge a fair premium. Academic research has proposed models ranging from modified Black-Scholes-Merton-type formulas for rainfall (with adjustments for the non-tradability) to advanced statistical models (e.g. Ornstein-Uhlenbeck processes with seasonality for temperature indices. The key takeaway is that whether it’s directly in commodity options or in dedicated weather derivatives, climate factors force us to go beyond textbook models and embrace more dynamic, data-driven pricing techniques.

Why should I be interested in this post?

For an ESSEC student or a young finance professional, this topic sits at the intersection of finance and real-world impact. Understanding weather risk in markets is not just about farming – it’s about how big data and climate science are increasingly intertwined with financial strategy. Agricultural commodities remain a cornerstone of the global economy, and volatility in these markets can affect food prices, inflation, and even economic stability in various countries. By grasping how to value derivatives with climate-based volatility inputs, you are gaining insight into a growing niche of finance that deals with sustainability and risk management. Moreover, the skills involved – scenario analysis, simulation modeling, blending of economic and scientific data – are highly transferable to other domains (think energy markets or any sector where uncertainty reigns). In a world facing climate change, expertise in weather-related financial products could open career opportunities in commodity trading desks, insurance/reinsurance firms, or specialized hedge funds. Ultimately, this post encourages you to think creatively and interdisciplinarily: the best hedging or valuation solutions may come from combining financial theory with environmental intelligence.

Useful resources

Chicago Mercantile Exchange (CME) Weather futures and options product information. (Exchange-traded weather derivative contracts on temperature and other indices)

U.S. Energy Information Administration Drought increases price of corn, reduces profits to ethanol producers (2012). (Article discussing the 2012 drought’s impact on corn prices and volatility)

Nature Communications (2024) Financial markets value skillful forecasts of seasonal climate. (Research showing that seasonal climate outlooks have measurable effects on implied volatility and market uncertainty)

Das, S. et al. (2025) Predicting and Mitigating Agricultural Price Volatility Using Climate Scenarios and Risk Models. (Academic study demonstrating the integration of climate data into volatility models and using Black-Scholes to value a government price support as a put option)

Pai, J. & Zheng, Z. (2013) Pricing Temperature Derivatives with a Filtered Historical Simulation Approach. (Discussion of why Black-Scholes is not directly applicable to weather derivatives and alternative pricing approaches)

About the author

The article was written in May 2025 by Mathias DUMONT (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2022-2026).

Understanding Break-even Analysis: A Key Financial Technique

July 1, 2025May 29, 2025 by Olivia BRÜN

In this article, Olivia BRÜN (ESSEC Business School, Global Bachelor in Business Administration (BGBA), and ESIC Business School, Bachelor of Business Administration and Management (BBAM), 2022–2026) analyses the concept of break-even analysis, a widely used financial technique employed to determine business profitability. This article illustrates the method in a case study of Watches of Switzerland Group, a publicly listed upscale watch retailer with its headquarters in the United Kingdom.

Introduction and Context

Break-even analysis is a critical component of managerial decision-making and financial planning. It allows companies to determine the level (volume) of sales that will cover all costs, both variable and fixed, before the company can be profitable. The break-even point is a crucial milestone in the operations of a firm. Sales below the break-even point create losses, while sales above it enable every extra unit sold to contribute to overall profitability.

This method is widely used in various industries to evaluate new projects, determine pricing strategies, and examine the financial feasibility of corporate decisions. Especially in capital-intensive industries or businesses focused on product offerings, understanding the break-even point is key to sound financial management and setting realistic sales targets.

History of the Concept

Break-even analysis stems from cost-volume-profit (CVP) analysis. Originating in managerial accounting in the early 20th century, CVP distinguishes between fixed costs (independent of production volume) and variable costs (dependent on production volume). By comparing these costs to projected revenues, decision-makers can identify the break-even point.

Case Study: Watches of Switzerland Group

This case study applies the break-even method to Watches of Switzerland Group PLC, a retailer of high-end watches. The following figures are taken from the company’s 2022 Annual Report:

For full financial details, see the official Watches Annual Report (2022).

Using these values, we compute the variable cost per unit and contribution margin per unit as follows:

Variable cost per unit: £3,132 (= £966.5 million / 308,560)
Contribution margin per unit: £1,868 (= £5,000 – £3,132 )

Break-even point (units): 220,128 units (= Fixed Costs / Contribution Margin per Unit = £411.2 million / £1,868).

At the break-even point, total revenues and total costs are approximately £1.1 billion. Sales above this point generate operating profit.

Break-even Chart from Excel

The chart below illustrates the relationship between total revenue and total cost across different sales volumes. The break-even point is located where the two lines intersect, at approximately 220,128 units, equivalent to around £1.1 billion in revenue. This marks the threshold at which the company covers all fixed and variable costs, resulting in neither profit nor loss.

The underlying Excel model (see “READ ME” tab for detailed explanations) allows for interactive analysis. Users can adjust inputs such as fixed costs, average selling price, and variable cost per unit. The break-even point updates automatically, making the tool highly practical for scenario analysis and financial planning. This kind of sensitivity analysis is essential in real world decision making, especially in industries with high fixed costs like luxury retail.

Break-even Analysis for Watches of Switzerland Group
Source: Excel computation based on data from Watches of Switzerland Group

You may download the Excel file used to do the computations and produce the chart above.

Why should I be interested in this post?

Break-even analysis is fundamental in both theoretical and applied finance. It is widely used in consultancy, financial planning, and entrepreneurship. Understanding this concept allows business professionals to assess cost structures, pricing strategies, and financial viability of new projects.

For an ESSEC student pursuing business or finance, mastering break-even analysis equips you to analyze operational leverage and forecast how profits change with varying sales levels. This insight helps in making informed strategic decisions, managing risk, and ensuring sustainable business growth.

Useful resources

Academic resources

Horngren, C. T., Datar, S. M., & Rajan, M. V. (2015) Cost Accounting: A Managerial Emphasis (15th ed.). Pearson Education. – This foundational textbook offers detailed explanations of break-even analysis, cost behavior, and their relevance in managerial decision-making.

Atrill, P., McLaney, E. (2022) Management Accounting for Decision Makers (10th ed.). Pearson.
– This book focuses on applying break-even and contribution analysis in real business contexts, helping students and professionals make informed financial decisions.

Gallo, A. (2014) A Quick Guide to Breakeven Analysis Harvard Business Review.

Business resources

Watches of Switzerland Group

Watches of Switzerland Group (2022) Annual Report and Accounts 2022

About the author

The article was written in May 2025 by Olivia BRÜN (ESSEC Business School, Global Bachelor in Business Administration (BGBA), and ESIC Business School, Bachelor of Business Administration and Management (BBAM), 2022–2026), 2022–2026).

Retained Earnings

June 18, 2025May 1, 2025 by Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) delves into Retained Earnings, providing a comprehensive analysis on type of retained earnings, explaining its theoretical foundations, discussing the other financial metrics compared to it, its valuation and limitations.

Introduction

Retained Earnings (RE) represent the portion of a company’s net income that is reinvested in the business rather than distributed to shareholders as dividends. This financial metric is a crucial indicator of a firm’s long-term growth potential, profitability, and financial stability. For students pursuing finance, understanding retained earnings is essential for evaluating corporate financial health, capital structure decisions, and strategic reinvestment policies.

Unlike dividends, which provide immediate shareholder returns, retained earnings are used for reinvestments such as research and development (R&D), acquisitions, debt reduction, and business expansion. The strategic management of retained earnings plays a vital role in a company’s value creation, influencing stock price appreciation and long-term shareholder wealth.

Definition and Formula

Retained earnings are calculated as follows:

Formula of Retained Earnings

A positive retained earnings balance indicates profitability and reinvestment potential, whereas negative retained earnings (also known as an accumulated deficit) suggest financial distress or excessive dividend payouts.

Theoretical Foundations of Retained Earnings

Retained earnings have been widely analyzed in financial theory, particularly in relation to dividends, investor behavior, and market efficiency.

Dividend Irrelevance Theory (Miller & Modigliani, 1961)

According to Miller and Modigliani’s capital structure theory, in a perfect market, dividend policy and retained earnings allocation do not affect firm value. However, in reality, taxes, transaction costs, and capital constraints make retained earnings a critical internal financing source.

Pecking Order Theory

According to Oxford Research Encyclopedias, this theory suggests that firms prefer internal financing (retained earnings) over external financing (debt or equity issuance) due to lower costs and reduced information asymmetry. Companies with strong retained earnings can fund expansion without diluting ownership or increasing leverage.

Growth Theory (Gordon Growth Model)

The Gordon Growth Model highlights the trade-off between paying dividends and reinvesting earnings. Higher retained earnings lead to greater reinvestment, potentially boosting future earnings and stock price appreciation.

Importance of Retained Earnings in Finance

Retained Earnings is vital in Finance to learn about a company’s growth, expansion, capital investments, and debt reductions.

Capital Investment and Expansion – Retained earnings finance business growth, acquisitions, and infrastructure improvements.
Debt Reduction – Companies use retained earnings to pay down debt, reducing interest costs and financial risk.
Shareholder Wealth Creation – Reinvested earnings contribute to higher stock valuations, benefiting long-term investors.
Liquidity and Financial Stability – Firms with substantial retained earnings have greater financial flexibility in economic downturns.
Dividend Policy Decisions – Retained earnings influence dividend payout ratios and corporate distribution policies.

Retained Earnings vs. Other Financial Metrics

There are many return metrics apart from Retained earnings, such as dividends, Net income, cash reserves, and shareholder equity as follows below:

Retained Earnings vs Other metrics

While these metrics provide valuable insights into a company’s financial health, retained earnings remain unique in their ability to capture the total accumulated profits and give an idea for reinvestments.

When it comes to net income, retained earnings include accumulated profits and not just the current income; it excludes payout dividends, and can be reinvested but not obtained as cash. Retained earnings are a component of shareholder equity.

Factors Influencing Retained Earnings

Several factors influence retained earnings:

Profitability – Higher net income leads to higher retained earnings.
Dividend Policy – Companies paying higher dividends retain less for reinvestment.
Capital Expenditure Needs – Firms requiring heavy reinvestment often retain more earnings.
Industry Trends – High-growth sectors (e.g., tech) tend to reinvest more, while mature industries may prioritize dividend payouts.
Economic Conditions – In downturns, firms may retain more earnings to maintain liquidity.

Retained Earnings in Corporate Valuation

Retained earnings play a vital role in corporate valuation models:

Discounted Cash Flow (DCF) Analysis

Retained earnings affect future cash flow projections and reinvestment rates.

Earnings Per Share (EPS) Growth

Higher retained earnings contribute to EPS expansion, driving stock value.

Case Studies in Retained Earnings Utilization

Apple Inc. (AAPL) – Apple has historically retained earnings for R&D and acquisitions, fueling innovation and stock price appreciation.
Amazon (AMZN) – Amazon reinvests nearly all its earnings into business expansion, prioritizing long-term growth over dividends.
General Motors (GM) – During financial crises, GM retained earnings to strengthen its balance sheet, ensuring long-term survival.

Challenges and Limitations of Retained Earnings

Underutilization Risks – Excessive retained earnings without reinvestment plans may lead to inefficient capital allocation.
Shareholder Expectations – Investors seeking dividends may view high retained earnings as a lack of returns.
Inflation and Depreciation – Inflation can erode the real value of retained earnings over time.

Conclusion

Retained earnings serve as a powerful financial tool, influencing corporate growth, shareholder returns, and financial stability. Understanding their impact on valuation, reinvestment strategies, and dividend policies is essential for finance professionals aiming to make data-driven investment and corporate finance decisions. By mastering retained earnings analysis, finance students can enhance their analytical skills and prepare for careers in investment banking, corporate finance, and asset management.

Why should I be interested in this post?

For finance students, understanding retained earnings is crucial as it directly impacts financial modeling and company valuation. Mastery of financial statement analysis, including retained earnings, is essential for roles in asset management, equity research, and financial consulting.

Useful resources

Academic resources

Myers, S. C., & Majluf, N. S. (1984) Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187–221.

Other resources

Bajaj Finserve What is the meaning of retained earnings?

About the author

The article was written in May 2025 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Dividends

June 18, 2025May 1, 2025 by Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) delves into Dividends, providing a comprehensive analysis on type of dividends, explaining its theoretical foundations, discussing the policy strategies, its valuation and limitations.

Introduction

Dividends are a fundamental component of shareholder returns, representing a direct distribution of a company’s profits to its investors. They play a crucial role in corporate finance, investment decision-making, and equity valuation. Dividends not only signal financial health but also serve as a means of returning excess capital to shareholders. For finance students, understanding the theoretical foundations, types, determinants, and impact of dividends is essential for analyzing investment opportunities and corporate strategies.

Definition and Types of Dividends

A dividend is a payment made by a corporation to its shareholders, typically derived from net profits. Companies distribute dividends as a reward to shareholders for their investment, either in cash or additional shares.

There are different types of dividends:

Cash Dividends – The most common form, where companies pay shareholders a fixed amount per share.
Stock Dividends – Companies issue additional shares instead of cash, increasing the number of outstanding shares while retaining cash reserves.
Property Dividends – Non-cash distributions, such as physical assets or securities of a subsidiary.
Scrip Dividends – A promissory note issued by a company, committing to pay dividends at a later date.
Liquidating Dividends – Distributed when a company is winding up operations, returning capital to investors beyond retained earnings.

Theoretical Foundations of Dividends

Dividends have been widely analyzed in financial theory, particularly in relation to firm value, investor behavior, and market efficiency.

Dividend Irrelevance Theory (Miller & Modigliani, 1961)

Miller and Modigliani argue that in a perfect capital market, dividend policy is irrelevant to a company’s valuation. The theory rests on several idealized assumptions. Miller and Modigliani asserted that in a perfect capital market (no taxes, transaction costs, or information asymmetry), a company’s dividend policy does not affect its market value or cost of capital. According to this theory, investors are indifferent between dividends and capital gains because they can generate “homemade dividends” by selling a portion of their shares if they desire cash.

Bird-in-the-Hand Theory

This theory suggests that investors prefer dividends over capital gains because they perceive dividends as more certain, reducing risk. It argues that firms with higher dividend payouts are more attractive to risk-averse investors.

Tax Preference Theory

Investors may prefer capital gains over dividends due to favorable tax treatment. In many jurisdictions, capital gains are taxed at a lower rate or deferred until realized, whereas dividends are often taxed immediately.

Signaling Theory (Bhattacharya, 1979)

Dividends serve as a signal of financial health. Since poorly performing firms cannot afford sustained dividend payments, an increase in dividends suggests management confidence in future earnings. Conversely, a dividend cut can signal financial distress.

Agency Theory and Free Cash Flow Hypothesis (Jensen, 1986)

Dividends can mitigate agency problems by reducing the free cash flow available to managers, thus limiting their ability to engage in inefficient spending or empire-building. Regular dividend payments force companies to be disciplined in capital allocation.

Determinants of Dividend Policy

Several factors influence a firm’s dividend decisions:

Profitability – Firms with stable and growing profits are more likely to pay consistent dividends.
Growth Opportunities – High-growth firms often reinvest earnings into expansion, leading to lower or no dividends.
Liquidity Position – Even profitable firms may avoid dividends if they face cash flow constraints.
Debt Levels – Highly leveraged firms prioritize debt repayments over dividend distributions.
Taxation Policies – Tax treatment of dividends vs. capital gains affects investor preference and corporate policies.
Market Expectations – Investors expect stable or gradually increasing dividends; sudden reductions can lead to stock price declines.
Macroeconomic Conditions – Economic downturns, inflation, and interest rate changes impact corporate profitability and dividend policies.

Dividend Policy Strategies

In practice, companies adopt different dividend policies based on their financial strategy and market positioning:

Stable Dividend Policy – Fixed payouts irrespective of earnings fluctuations (e.g., Coca-Cola).
Constant Payout Ratio – A fixed percentage of earnings is paid as dividends.
Residual Dividend Policy – Dividends are paid after funding all capital investment opportunities.
Hybrid Dividend Policy – A mix of stable dividends and periodic special dividends.

Dividends and Valuation

Dividends are critical in valuation models, as they represent cash flows to shareholders.

Dividend Discount Model (DDM)

The Gordon Growth Model is a fundamental valuation tool:

Formula of Dividend Discount Model (DDM)

where:

P₀ = Current stock price
DIV₁ = Expected next-year dividend
r = Required rate of return
g = Dividend growth rate

This model applies to firms with stable dividend growth but is less effective for high-growth or non-dividend-paying companies.

Discounted Cash Flow (DCF) Model

DCF considers total cash flows, incorporating dividends as part of Free Cash Flow to Equity (FCFE). It provides a broader valuation approach beyond just dividends.

Comparative Valuation

Dividend yield (DP\frac{D}{P}PD) is commonly used to compare income-generating stocks. A higher yield may indicate undervaluation but could also signal financial distress.

Empirical Evidence and Case Studies

Apple: Initially avoided dividends but introduced payouts in 2012 after accumulating substantial cash reserves, balancing growth and shareholder returns.
General Electric (GE): A significant dividend cut in 2018 led to a major stock price decline, showing the impact of investor expectations.

Limitations of Dividend Analysis

Does Not Reflect Total Returns – Dividends exclude capital gains, potentially underestimating true investor returns.
Influence of External Factors – Regulatory policies, tax changes, and economic conditions impact dividend sustainability.
Not Suitable for Growth Stocks – Many high-growth firms reinvest profits, making dividend-based valuation ineffective.
Potential for Financial Misinterpretation – High dividends may indicate strong profitability or a lack of profitable reinvestment opportunities.

Conclusion

Dividends remain a crucial aspect of financial analysis, providing insights into corporate strategy, investor expectations, and firm valuation. While theories like M&M’s irrelevance hypothesis argue that dividends do not affect firm value, real-world evidence suggests that dividends play a significant role in investor preferences and market perception. Understanding dividend policies and valuation models equips finance students with the necessary analytical skills to evaluate investment opportunities and corporate strategies effectively.

Why should I be interested in this post?

For master’s students in finance, understanding dividends is essential for making informed investment decisions, evaluating corporate financial strategies, and mastering valuation techniques. Dividends are a key component of Total Shareholder Return (TSR) and play a crucial role in equity pricing models like the Dividend Discount Model (DDM) and Discounted Cash Flow (DCF) analysis. By studying dividends, students gain insights into capital allocation, corporate governance, and investor behavior—fundamental areas in asset management, investment banking, and financial advisory.

Useful resources

Academic articles

Bhattacharya, S. (1979) Imperfect Information, Dividend Policy, and “The Bird in the Hand” Fallacy. The Bell Journal of Economics, 10(1), 259–270.

Jensen, M. C. (1986) Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers. American Economic Review, 76(2), 323–329.

Miller, M. H., & Modigliani, F. (1961) Dividend Policy, Growth, and the Valuation of Shares. The Journal of Business, 34(4), 411–433.

Business

Dividend University Dividend Irrelevance Theory

Harvard Business School Publications The Effect of Dividends on Consumption

Other resources

Religare Broking What are Different Types of Dividends?

Munich Business School Dividend explained simply

CNBC What are dividends and how do they work?

About the author

The article was written in May 2025 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Greenwashing

May 1, 2025 by Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) delves into Greenwashing, providing a comprehensive analysis on forms of greenwashing, explaining its theoretical foundations, discussing the pros and cons in financial markets, and combating strategies.

Introduction

Greenwashing refers to the deceptive practice where companies exaggerate or falsely claim environmental responsibility to appear more sustainable than they actually are. In the financial world, this phenomenon has significant implications for investors, regulators, and corporate governance. As Environmental, Social, and Governance (ESG) investing gains prominence, understanding greenwashing is essential for finance students to critically assess sustainable investment strategies, corporate disclosures, and regulatory policies.

The increasing demand for ESG-compliant investments has led to a surge in “sustainable” financial products. However, without proper oversight, some firms manipulate ESG metrics to attract investors without making substantive environmental improvements. This raises concerns about misallocated capital, ethical investing dilemmas, and potential financial risks associated with misleading sustainability claims.

Definition and Forms of Greenwashing

Greenwashing can take various forms, including:

Misleading Environmental Claims – Companies overstate or fabricate their sustainability achievements (e.g., claiming “100% eco-friendly” without verifiable data).
Selective Disclosure – Highlighting positive environmental efforts while concealing negative impacts (e.g., focusing on carbon-neutral initiatives but ignoring pollution).
Weak ESG Integration – Investment funds labeling themselves as “green” without rigorous ESG screening processes.
Third-Party Certification Abuse – Using unverified or non-standard sustainability labels to mislead investors.
Carbon Offsetting vs. Actual Reduction – Relying on carbon credits rather than actively reducing emissions.

Theoretical Foundations of Greenwashing in Finance

Several financial theories and principles help explain greenwashing’s impact on markets:

Signaling Theory

Companies use sustainability claims as market signals to attract investors. However, without proper verification, these signals can be misleading, distorting investment decisions.

Agency Theory

Conflicts of interest arise when management prioritizes short-term stock price gains over long-term sustainability. Greenwashing allows firms to create a perception of ESG compliance while avoiding substantive environmental actions.

Market Efficiency Hypothesis (EMH)

If markets are efficient, greenwashing should be priced in once uncovered. However, due to information asymmetry, investors may fail to detect deceptive ESG claims, leading to mispriced assets.

Stakeholder Theory

Companies engage in greenwashing to appease stakeholders—especially ESG-conscious investors and consumers—without necessarily implementing meaningful sustainability initiatives.

Why Greenwashing Matters for Finance Students

Several factors influence a firm’s dividend decisions:

Investment Risk Assessment – Identifying greenwashing helps investors avoid unsustainable firms that may face regulatory penalties or reputational damage.
ESG Portfolio Management – As ESG investing grows, finance professionals must differentiate genuine sustainability efforts from deceptive claims.
Regulatory Compliance – Understanding greenwashing is crucial for financial analysts and corporate advisors to ensure compliance with evolving ESG regulations.
Corporate Valuation and Due Diligence – Misleading ESG claims can artificially inflate stock prices, leading to incorrect valuation models.
Impact on Sustainable Finance – Greenwashing undermines the credibility of sustainable finance, affecting capital allocation and long-term environmental goals.

Greenwashing in Financial Markets

Greenwashing has infiltrated financial markets, particularly in:

ESG Investment Funds – Some “green” funds include companies with poor sustainability records, misleading investors.
Corporate Bonds & Sustainability-Linked Loans – Firms issue green bonds with vague sustainability targets that lack proper enforcement mechanisms.
Carbon Credit Markets – Companies buy carbon offsets instead of reducing emissions, creating an illusion of sustainability.
Stock Market Reactions – Firms accused of greenwashing often suffer stock price declines, highlighting its financial impact.

Case Studies in Greenwashing

Volkswagen Emissions Scandal (2015) – VW falsely claimed its diesel vehicles met environmental standards while using software to cheat emissions tests. The scandal led to billions in fines and reputational damage.
DWS Group (Deutsche Bank) ESG Fraud Investigation (2021) – DWS misrepresented its ESG investment practices, leading to regulatory scrutiny and financial losses.
HSBC’s Misleading ESG Advertising (2022) – HSBC was fined for promoting its green initiatives while failing to disclose its continued financing of fossil fuel projects.
Fast Fashion’s False Sustainability Claims – Brands like H&M and Zara have faced accusations of greenwashing by launching “eco-friendly” lines while continuing unsustainable practices.

Combating Greenwashing in Finance

Enhanced ESG Disclosures – Standardized and transparent ESG reporting requirements, such as the EU’s SFDR and the SEC’s climate disclosure rules.
Third-Party ESG Ratings – Relying on independent ESG rating agencies to verify sustainability claims.
Regulatory Actions – Government policies imposing strict penalties for false sustainability claims.
Stronger Due Diligence by Investors – Institutional investors integrating forensic ESG analysis to uncover misleading claims.

Conclusion

Greenwashing presents a major challenge in sustainable finance, misleading investors, distorting markets, and undermining genuine ESG efforts. For finance students, understanding greenwashing is crucial for responsible investment practices, corporate analysis, and financial decision-making. By developing a critical approach to ESG claims, finance professionals can drive real sustainability while protecting financial markets from misleading practices.

Why should I be interested in this post?

For finance students, greenwashing is not just an ethical issue—it has real financial consequences. As sustainable investing grows, ESG factors are increasingly integrated into portfolio management, risk assessment, and corporate valuation. However, misleading sustainability claims distort investment decisions, misallocate capital, and expose firms to reputational and regulatory risks.

Useful resources

Wikipedia Greenwashing

United Nations Greenwashing – the deceptive tactics behind environmental claims

Plan A What is greenwashing and how to identify it?

IBM What is greenwashing?

About the author

The article was written in May 2025 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Understanding Sustainable Finance through ESG Indexes

April 11, 2025 by Pablo COHEN

Understanding Sustainable Finance through ESG Indexes

In this article, Pablo COHEN (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2024–2025) explores how sustainable finance is reshaping investment strategies through ESG indexes.

Introduction and Context

For decades, success was measured through financial indicators. Profits defined companies, and GDP per capita ranked nations. But as Robert F. Kennedy pointed out, GDP “measures air pollution and cigarette advertising… and ambulances to clear our highways of carnage.” It reflects economic activity, not societal well-being”.

Our actions shape the climate, ecosystems, and social outcomes — and those same forces now pose real risks to economies. France may have a far higher GDP per capita than El Salvador, but which emits more carbon per citizen? Which has a credible plan for net-zero by 2050? These questions are more relevant to long-term sustainability.

To enable meaningful comparisons, global bodies like the UN and EU have created frameworks and standards for sustainability reporting. Tools such as the EU Taxonomy, SFDR, and CSRD bring structure and consistency to ESG disclosures, helping investors assess corporate impact and redirect capital toward sustainable outcomes. If we don’t change what we measure, we won’t change what we prioritize — or what we build.

How ESG Indexes Work

We have an impact on the world, and the world has an impact on us. That’s the essence of double materiality — a foundational concept in sustainable finance. Sustainability risks, whether physical (like climate disasters) or transitional (like policy shifts), can directly affect financial performance through credit risk, operational disruption, legal exposure, and reputational damage.

Just as external events shape a company’s bottom line, financial decisions influence the environment and society. This two-way relationship is increasingly recognized by regulators and investors alike. Navigating it requires tools that make ESG performance measurable, comparable, and investable. This is where ESG indexes come into play.

ESG indexes allow investors to evaluate companies based on their sustainability profile. Depending on their design, they may exclude controversial sectors, highlight ESG leaders, track themes like clean energy, or align with climate targets such as the 1.5°C scenario. Examples include the MSCI ESG Leaders and Climate Paris Aligned Indexes, the S&P 500 ESG Index, FTSE4Good, and the Dow Jones Sustainability Index. These indexes are used not only as benchmarks, but as a basis for constructing portfolios that reflect long-term sustainability goals.

The growth of ESG indexes and sustainable funds has mirrored the rising demand for more responsible investment strategies. The following chart shows how both active and passive sustainable funds have surged over the past decade:

ESG Fund Growth Chart.

Source: Morningstar Direct.

ESG in Practice and Market Performance

Index construction starts with exclusions — companies involved in fossil fuels, weapons, or major ESG controversies are filtered out. Then comes ESG scoring, based on data from corporate disclosures, regulatory filings, and third-party assessments. Companies are evaluated across environmental impact, social responsibility, and governance quality. This might include emissions intensity, labor practices, or board independence. Based on these scores, indexes select and weight constituents and are rebalanced periodically to reflect updated data.

The MSCI Climate Paris Aligned Index is designed to align with a 1.5°C scenario. It reduces both physical and transition risks by excluding fossil-fuel-intensive companies and emphasizing those with low emissions and strong climate governance. Compared to its parent index, the MSCI ACWI, it includes fewer companies but achieves a 50% reduction in portfolio carbon intensity. It’s a forward-looking tool that anticipates tightening regulations and evolving investor expectations.

Some ESG funds have even outperformed traditional benchmarks like the S&P 500. The chart below shows that several ESG funds delivered significantly higher year-to-date returns in early 2021:

ESG Fund performance compared to the S&P 500 index.

Source: S&P Global Market Intelligence.

This outperformance isn’t just recent. In 2019, sustainable large-blend index funds consistently beat the S&P 500 — with many delivering returns above 32%, as the following chart demonstrates:

Sustainable Funds Performance (year 2019).
Sustainable Funds 2019 Performance
Source: Morningstar Direct.

The rise of ESG is also visible in fund flows. More sustainable funds are being launched each year, and investor inflows have reached record levels — confirming that ESG isn’t just a trend, it’s a lasting shift in investment priorities.

Why should I be interested in this post?

As an ESSEC student preparing for a career in finance, understanding sustainable finance is no longer optional. ESG principles are reshaping how capital is allocated, how companies report, and how investment strategies are built. Whether you’re pursuing a role in banking, asset management, consulting, or entrepreneurship, knowledge of ESG frameworks and sustainable indexes will be essential for making informed, future-ready decisions in a rapidly changing financial landscape.

Useful resources

Morgan Stanley (2023) Sustainable Funds Outperformed Peers in 2023

IEEFA ESG Investing: Steady Growth Amidst Adversity

Morgan Stanley (2024) Sustainable Funds Modestly Outperform in First Half of 2024

IEEFA ESG Funds Continue to Outperform

S&P Global Most ESG Funds Outperformed S&P 500 in Early 2021

Morningstar U.S. ESG Funds Outperformed Conventional Funds in 2019

The Economist American Sustainable Funds Outperform the Market

About the author

This article was written in April 2025 by Pablo COHEN (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2024–2025).

Gini index

March 3, 2025February 24, 2025 by Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) delves into the Gini Index, provides a comprehensive overview of the Gini Index, explaining its calculation, interpretation, and significance in understanding income inequality.

Introduction

In the world of economics and finance, understanding inequality and concentration is crucial for making informed decisions. Whether you’re an investment analyst assessing market dynamics, a wealth advisor guiding clients through portfolio diversification, or a finance student delving into the intricacies of econometrics, the Gini Index is an indispensable tool in your analytical arsenal.

But what exactly is the Gini Index, and why does it matter to finance professionals? Buckle up, because we’re about to embark on a journey through the fascinating world of income inequality measurement!

The Birth of a Revolutionary Concept

Picture this: It’s 1912, and an Italian statistician named Corrado Gini is burning the midnight oil, pondering the complexities of wealth distribution. Little did he know that his work would lead to the creation of one of the most widely used measures of inequality in the world.

The Gini Index, also known as the Gini Coefficient, was born out of Gini’s desire to quantify the disparity in wealth distribution across populations. It’s a testament to human ingenuity that a single number could encapsulate such a complex socio-economic concept.

Cracking the Code: Understanding the Gini Formula

At the core, the Gini Index is a mathematical marvel. But let’s break it down so that every mathematically inclined and non-inclined person understands it:

Perfect Equality Line: A diagonal line from (0,0) to (1,1) represents perfect equality – where everyone has the same income or wealth.
The Lorenz Curve: Imagine a graph where the x-axis represents the cumulative percentage of the population, and the y-axis represents the cumulative percentage of income or wealth. In a perfectly equal society, this would be a straight 45-degree line. In reality, it curves below this line, and the more it curves, the higher the inequality.
The Gini Coefficient: It’s the area between the Lorenz Curve and the Perfect Equality Line, divided by the total area under the Perfect Equality Line. It ranges from 0 (perfect equality) to 1 (perfect inequality). In other words, if everyone had exactly the same income, the Gini would be 0. If one person had all the income and everyone else had none, the Gini would be 1.

Gini Index coefficient in case of maximum equality
Gini Index co-efficient in case of maximum equality
Source: The author

Gini Index coefficient in case of maximum inequality
Gini Index co-efficient in case of maximum inequality
Source: The author

Gini Index coefficient in case of inequality
Gini Index co-efficient in case of inequality
Source: The author

The below Excel file contains the Gini Index illustration in all the three cases namely, maximum equality, maximum inequality and inequality. For more clear information please download the attached Excel file.

At its core, the Gini Index is elegantly simple yet profoundly insightful. It’s represented by a single number between 0 and 1, where:

0 represents perfect equality (everyone has the same income)
1 represents perfect inequality (one person has all the income)

The mathematical formula is based on the Lorenz curve, which plots the cumulative share of income against the cumulative share of the population.

Formula of Gini coefficient
Formula of Gini Co-efficient

Where:

A is the area between the line of perfect equality and the Lorenz curve
B is the area under the Lorenz curve

Applying the Gini Index in Financial Analysis

There are multiple applications of the Gini Index, but in this article let’s discuss a bit more on how it’s used in Income Inequality Analysis and Market Concentration Assessment.

Income Inequality Analysis

Imagine you’re an investment analyst tasked with evaluating the economic stability of different countries for potential investments. The Gini Index becomes your compass. Understanding income inequality can help you to:

Contextualize your clients’ wealth positions
Identify potential social and political risks to their investments
Guide philanthropic efforts for those interested in addressing inequality

Case Study: In 2022, the U.S. had a Gini coefficient of 0.488. What does this mean for your clients? It suggests a significant wealth gap, potentially indicating social tensions that could affect investment strategies.

Money Income Gini Index and Real Household Income at selected Percentiles from 1993 to 2022

Source: United States Census Bureau

Market Concentration Assessment

For investment analysts, the Gini Index isn’t just about personal incomes. It’s a powerful tool for assessing market dynamics: understanding market concentration can help you:

Evaluate industry competitiveness
Identify potential monopolistic trends
Assess risk in sector-specific investments

Conclusion

The Gini index serves as a crucial tool for understanding and measuring income inequality within a society (individuals, firms, etc.). By quantifying the disparity in income distribution, it provides policymakers, economists, and researchers with valuable insights for developing strategies to promote greater economic equity and social well-being.

Why should I be interested in this post?

The Gini index provides a crucial lens for finance professionals to understand the broader economic and social context within which financial markets operate. By incorporating insights from income inequality analysis, they can make more informed investment decisions, contribute to a more sustainable financial system, and play a role in promoting a more equitable and prosperous society.

Useful resources

Gini, C. (1912). Variabilità e mutabilità (Variability and Mutability). C. Cuppini, Bologna.

Wikipedia Gini coefficient

United states Census bureau Gini Index

Our world in data Measuring inequality: what is the Gini coefficient?

US Census Bureau Income Inequality Down Due to Drops in Real Incomes at the Middle and Top, But Post-Tax Income Estimates Tell a Different Story

Tommorow One How the Gini coefficient measures inequality

About the author

The article was written in February 2025 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

US Treasury Bonds

February 24, 2025 by Nithisha CHALLA

In this article, Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024) gives a comprehensive overview of U.S. Treasury bonds, covering their features, benefits, risks, and how to invest in them

Introduction

Treasury bonds, often referred to as T-bonds, are long-term debt securities issued by the U.S. Department of the Treasury. They are regarded as one of the safest investments globally, offering a fixed interest rate and full backing by the U.S. government. This article aims to provide an in-depth understanding of Treasury bonds, from their basics to advanced concepts, making it an essential read for finance students and professionals.

What Are Treasury Bonds?

Treasury bonds are government debt instruments with maturities ranging from 10 to 30 years. Investors receive semi-annual interest payments and are repaid the principal amount upon maturity. Due to their low risk, Treasury bonds are a popular choice for conservative investors and serve as a benchmark for other interest-bearing securities.

Types of Treasury Securities

Treasury bonds are part of a broader category of U.S. Treasury securities, which include:

Treasury Bills (T-bills): Short-term securities with maturities of one year or less, sold at a discount and matured at face value.
Treasury Notes (T-notes): Medium-term securities with maturities between 2 and 10 years, offering fixed interest payments.
Treasury Inflation-Protected Securities (TIPS): Securities adjusted for inflation to protect investors’ purchasing power.
Treasury Bonds (T-bonds): Long-term securities with maturities of up to 30 years, ideal for investors seeking stable, long-term income.

Historical Performance of Treasury Bonds

Historically, Treasury bonds have been a cornerstone of risk-averse portfolios. During periods of economic uncertainty, they act as a haven, preserving capital and providing reliable income. For instance, during the 2008 financial crisis and the COVID-19 pandemic, Treasury bond yields dropped significantly as investors flocked to their safety.

Despite their stability, T-bonds are sensitive to interest rate fluctuations. When interest rates rise, bond prices typically fall, and vice versa. Over the long term, they have delivered modest returns compared to equities but excel in capital preservation.

Investing in Treasury Bonds

Investing in Treasury bonds can be done through various channels like Direct Purchase, Brokerage Accounts, Mutual Funds and ETFs, and Retirement Accounts:

Direct Purchase: Investors can buy T-bonds directly from the U.S. Treasury via the TreasuryDirect website.
Brokerage Accounts: Treasury bonds are also available on secondary markets through brokers.
Mutual Funds and ETFs: Investors can gain exposure to Treasury bonds through funds that focus on government securities.
Retirement Accounts: T-bonds are often included in 401(k) plans and IRAs for diversification.

Factors Affecting Treasury Bond Prices

Several factors influence the prices and yields of Treasury bonds such as Interest Rates, Inflation Expectations, Federal Reserve Policy, and Economic Conditions:

Interest Rates: An inverse relationship exists between bond prices and interest rates.
Inflation Expectations: Higher inflation erodes the real return on bonds, causing prices to drop.
Federal Reserve Policy: The Federal Reserve’s actions, such as changing the federal funds rate or engaging in quantitative easing, directly impact Treasury yields.
Economic Conditions: In times of economic turmoil, demand for Treasury bonds increases, driving up prices and lowering yields.

Relationship between bond price and current bond yield

Let us consider a US Treasury bond with nominal value M, coupon C, maturity T, and interests paid twice a year every semester. The coupon (or interest paid every period) is computed with the coupon rate. The nominal value is reimbursed at maturity. The current yield is the market rate, which may be lower or greater than the rate at the time of issuance of the bond (the coupon rate used to compute the dollar value of the coupon). The formula below gives the formula for the price of the bond (we consider a date just after the issuance date and different yield rates.

Formula for the price of the bond

Source: Treasury Direct

Relationship between bond price and current bond yield

Source: Treasury Direct

Risks and Considerations

While Treasury bonds are low-risk investments, they are not entirely risk-free, there are several factors to consider, such as Interest Rate Risk (Rising interest rates can lead to capital losses for bondholders), Inflation Risk (Fixed payments lose purchasing power during high inflation periods), Opportunity Cost (Low returns on T-bonds may be less attractive compared to higher-yielding investments like stocks).

Treasury Bond Futures

Treasury bond futures are standardized contracts that allow investors to speculate on or hedge against future changes in bond prices. These derivatives are traded on exchanges like the Chicago Mercantile Exchange (CME) and are essential tools for managing interest rate risk in sophisticated portfolios.

Treasury Bonds in the Global Market

The U.S. Treasury market is the largest and most liquid government bond market worldwide. It plays a pivotal role in the global financial system:

Reserve Currency: Many central banks hold U.S. Treasury bonds as a key component of their foreign exchange reserves.
Benchmark for Other Securities: Treasury yields serve as a reference point for pricing other debt instruments.
Foreign Investment: Countries like China and Japan are significant holders of U.S. Treasury bonds, underscoring their global importance.

Conclusion

Treasury bonds are fundamental to the financial landscape, offering safety, stability, and insights into broader economic dynamics. Whether you’re a finance student building foundational knowledge or a professional refining investment strategies, understanding Treasury bonds is indispensable. As of 2023, the U.S. Treasury market exceeds $24 trillion in outstanding debt, reflecting its vast scale and importance. By mastering the nuances of Treasury bonds, you gain a competitive edge in navigating the complexities of global finance.

Why should I be interested in this post?

Understanding Treasury bonds is crucial for anyone pursuing a career in finance. These instruments provide insights into Monetary Policy, Fixed-Income Analysis, Portfolio Management, and Macroeconomic Indicators.

Useful resources

Treasury Direct Treasury Bonds

Fiscal data U.S. Treasury Monthly Statement of the Public Debt (MSPD)

Treasury Direct Understanding Pricing and Interest Rates

Wikipedia United States Treasury security

About the author

The article was written in February 2025 by Nithisha CHALLA (ESSEC Business School, Grande Ecole Program – Master in Management (MiM), 2021-2024).

Understanding the Discount Rate: A Key Concept in Finance

February 12, 2025February 7, 2025 by Yann-Ray KAMANOU TAWAMBA

In this article, Yann-Ray KAMANOU TAWAMBA (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2024-2025) explains the discount rate, which is a key concept in finance.

About the Discount Rate

The discount rate is a fundamental concept in finance, playing a crucial role in investment valuation, corporate finance, and monetary policy. It represents the interest rate used to determine the present value of future cash flows, making it essential for evaluating investment opportunities and financial decision-making. The discount rate is widely applied in areas such as capital budgeting, bond pricing, and central banking policy, making it a critical concept for students and professionals in finance.

The discount rate is a fundamental concept in finance, used in both monetary policy and investment valuation. In central banking, it represents the interest rate at which commercial banks borrow from the central bank, influencing economic activity and inflation. In corporate finance, it is used to discount future cash flows in investment valuation, often calculated using the Weighted Average Cost of Capital (WACC) or the Capital Asset Pricing Model (CAPM). It reflects the opportunity cost of capittal, risk, and expected returns, playing a crucial role in decision-making for investors, businesses, and policymakers.

The Discount Rate in Investment Analysis

One of the most common applications of the discount rate is in the Discounted Cash Flow (DCF) model, which is used to assess the intrinsic value of an investment. In this method, future cash flows are discounted to the present using an appropriate discount rate. The formula for present value (PV) and net present value (NPV) of future cash flows is:

PV formula of cash flows

NPV formula of cash flows

Where CF represents the expectation of the future cash flow, r is the discount rate, and T is the number of periods. If the NPV of an investment is positive, it indicates that the project is expected to generate more value than its cost, making it a viable option.

The discount rate affects bond prices and yields. When it rises, borrowing becomes expensive. New bonds offer higher yields, making them more attractive. Older bonds with lower fixed rates lose value. Investors use the discount rate to calculate the present value of a bond’s future payments:

Central banks, like the Federal Reserve in the US and the European Central Bank in the Eurozone, set the discount rate as the interest rate for banks borrowing directly from them. When central banks increase the discount rate, loans become expensive. Banks lend less, slowing inflation and economic growth. When they lower the discount rate, borrowing is cheaper. Banks lend more, encouraging spending and investment.

Why should I be interested in this post?

Understanding the discount rate is essential. Whether you are aiming for roles in investment banking, asset management, financial consulting, or central banking, a solid grasp of this concept will allow you to make informed financial decisions. This topic is particularly relevant for students preparing for financial modeling exercises, valuation case studies, and investment strategy planning.

Useful resources

Berk, J. B., & van Binsbergen, J. H. (2017) How Do Investors Compute the Discount Rate? They Use the CAPM Financial Analysts Journal 73(2), 25–32.

Hirshleifer, J. (1961) Risk, The Discount Rate, and Investment Decisions, The American Economic Review, 51 (2), 112-120.

Roley, V. V., & Troll, R. (1984) The impact of discount rate changes on market interest rates. University of Washington. Center for the Study of Banking and Financial Markets, Graduate School of Business Administration.

Woon, G.C. (1999) Estimating the discount rate policy reaction function of the monetary authority, Journal of Applied Econometrics, 14(4), 379-401.

About the author

The article was written in February 2025 by Yann-Ray KAMANOU TAWAMBA (ESSEC Business School, Master in Strategy & Management of International Business (SMIB), 2024-2025).

The importance of data in finance to support small business managers

January 15, 2025January 15, 2025 by Sylvain GILIBERT

In this article, Yann FONTAINE (head of Marketing of atometrics) and Sylvain GILIBERT (co-founder of atometrics) explain about the importance of data in finance to support small business managers. They discuss how their platform, atometrics, helps transform complex market data into actionable insights for small businesses and their stakeholders (like accountants, banks, brokers, and consultants) throughout different stages of the business lifecycle – from creation to development, through difficult phases, and during transmission/acquisition processes.

Today economic context

Did you know that 29% of local businesses in France fail within their first three years , often due to a lack of market understanding?

In today’s fast-moving economy, access to relevant and actionable data is critical for businesses—whether they are launching, growing, or overcoming challenges. Yet, small business managers and their advisors often struggle to find and interpret the right information —strategic insights about their market, including prospects, customers, competitors, and the business environment—, particularly at a local level. By local level, we mean the geographic scope tailored to the company’s market: from the catchment area of a neighbourhood for a local retail store to the entire country for national markets.

The power of local data

For businesses operating in local markets, understanding the economic environment, consumer behavior, competition and market transactions is essential. In France, open data sources provide valuable insights, but the sheer volume and complexity of this information can be overwhelming without the right tools.

atometrics: turning data into decisions

At atometrics, we simplify this process. Our platform automates the collection, analysis, and visualization of market data across all sectors and locations of the economy. By combining financial and non-financial information, we provide clear, actionable insights to support small business managers and their trusted partners, such as certified accountants, bankers, and consulting firms.

Logo of atometrics.

Source: the company.

Description of the product: atometrics platform

Atometrics is a cutting-edge platform that connects in real-time to numerous public and private databases via APIs, such as SIRENE (the national directory of businesses in France), BODACC (official bulletins for company announcements, including bankruptcies and mergers), public financial records from Infogreffe, INSEE census data (socio-economic and demographic statistics), DVF property transaction data (detailing real estate sales), Damodaran’s valuation datasets (global financial benchmarks), and more. By leveraging this vast data network, the platform enables users to generate comprehensive market studies instantly.

Searching for a company.

Source: atometrics.

Users simply select an industry (e.g., bakery, hairdressing) and a location, and Atometrics delivers a detailed report. This includes financial insights on competitors, transaction prices for nearby properties or businesses, valuation tools for businesses or shares, competitor mapping, and local demographic and economic data. Additionally, qualitative market insights are provided. The platform also features customizable email alerts to notify users of critical events, such as new tenders or competitors.

Report on a company.

Source: atometrics.

The platform allows users to either work with specific datasets (e.g., Excel exports, map visuals) or generate complete reports in PDF or PPT format.

Supporting small businesses at every stage

atometrics empowers small businesses through their stakeholders — accountants, banks, brokers, consultants — to access key information at the different stages of the business life cycle:

Creation: assess market feasibility, validate business plans, and identify the best locations for new businesses.
Development: monitor trends, spot opportunities, and manage risks. For example, our platform can alert managers to new competitors or relevant public tenders in real time.
Difficulty phases: respond quickly to economic shifts with up-to-date market intelligence, ensuring resilience during challenging times.
Transmission and acquisition: conduct reliable valuations of businesses, assets, or securities based on accurate market multiples.

A concrete example: how atometrics enhances banking efficiency and risk assessment

Banks leveraging atometrics gain a significant advantage by accessing a uniform and structured source of information. When client managers and risk analysts evaluate a funding request or a business plan, they need to determine whether the entrepreneur is likely to achieve their revenue targets. This requires reliable market data: have similar projects succeeded or failed? Does the targeted catchment area show strong potential?

Atometrics simplifies this process by providing objective, data-driven insights that streamline the assessment of funding requests and accelerate the time to market of loan drawdowns. Instead of spending hours collecting and interpreting scattered information, bank advisors can access clear, actionable insights in real time.

Furthermore, the shared use of atometrics across commercial and risk departments fosters a common source of information among them, hence improving communication and collaboration between teams.

Conclusion

In today’s data-driven world, success belongs to those who can transform information into action. atometrics equips small business stakeholders with the tools and insights they need to unlock opportunities, navigate challenges, and drive sustainable growth—at every stage of the journey.

Why should I be interested in this post?

In today’s era of open finance and open data, financial professionals need cutting-edge tools to better serve their clients. This article reveals how atometrics, an innovative French fintech, is transforming the way banks, brokers, accountants, and business advisors support companies through data analytics. Whether you’re an ESSEC student preparing for a career in finance, a banker looking to streamline credit processes, or a consultant aiming to provide better market insights, you’ll want to know how the latest data-driven tools are reshaping financial decision-making and improving client service.

Useful resources

atometrics

About the authors

The article was written in January 2025 by Yann FONTAINE (head of Marketing of atometrics) and Sylvain GILIBERT (co-founder of atometrics).

The G of ESG: The Critical Role of Governance

January 10, 2025January 6, 2025 by Majd MAHRSI

In this article, Majd MAHRSI (ESSEC Business School, Global BBA Program, 2021-2025) delves into the critical role of governance in fostering sustainable business practices, particularly in emerging economies. Drawing from professional experiences such as an internship at DiliTrust, this article explains how strong governance frameworks can transform businesses and create new career opportunities.

ESG and Its Components

ESG (Environmental, Social, and Governance) is a framework used to evaluate a company’s sustainability practices and ethical commitments. It assesses corporate behavior across three dimensions:

Environmental (E): Focuses on a company’s impact on the environment, including energy use, waste management, and carbon emissions.
Social (S): Examines how a company interacts with its stakeholders, such as employees, customers, and communities, covering diversity, labor rights, and community relations.
Governance (G): Relates to a company’s internal systems for ethical decision-making, leadership accountability, and shareholder rights.

ESG has gained significant traction in recent years, with investors prioritizing companies that integrate sustainability into their core operations. This trend has driven the rise of Socially Responsible Investing (SRI), a strategy where investments are made based on a company’s ESG performance alongside financial returns. According to the Global Sustainable Investment Alliance (GSIA), global SRI assets surpassed $35 trillion in 2022, accounting for nearly 36% of all professionally managed assets. This rapid growth reflects the increasing demand for ethical and sustainable investment options, demonstrating how ESG principles are reshaping financial markets.

Further emphasizing the importance of ESG performance, Friede, Busch, and Bassen (2015) conducted a comprehensive meta-analysis of over 2,000 empirical studies, concluding that approximately 90% of the research found a non-negative relationship between ESG performance and financial performance, with the majority indicating a positive correlation. This underscores the financial benefits of robust governance practices as part of an ESG strategy.

Chart: Below is a graphical representation of the growth of Sustainable and Responsible Investing (SRI) assets in the United States from 1995 to 2018.

Growth of Sustainable and Responsible Investing (SRI) assets

Source: Green America / US SIF Foundation.

Focus on Governance

Governance, the “G” in ESG, refers to the structures, principles, and processes that dictate how a company is controlled and directed. It encompasses:

Board Diversity and Independence: A diverse and independent board ensures balanced decision-making, reducing conflicts of interest.
Shareholder Rights: Empowering shareholders with voting rights and transparent reporting fosters accountability.
Executive Accountability: Ensuring executive compensation aligns with long-term company performance promotes ethical leadership.
Risk Management: Establishing frameworks for identifying and mitigating financial, operational, and ESG-related risks.
Transparency and Reporting: Clear and consistent disclosure of governance practices builds stakeholder trust.

According to Eccles, Ioannou, and Serafeim (2014), companies adopting sustainability policies, including strong governance practices, tend to outperform their peers in both stock market returns and accounting metrics, further emphasizing the financial value of ethical leadership.

Without robust governance, even the strongest environmental and social efforts can falter due to poor oversight and unethical practices.

Why Governance Matters in ESG

Good governance forms the foundation for a company’s long-term sustainability and financial stability. It ensures that leadership decisions align with stakeholder interests and corporate ethics.

Trust and Reputation

Strong governance builds stakeholder trust by promoting ethical decision-making and transparency. Companies with robust governance frameworks are better positioned to manage crises and maintain reputational integrity. In contrast, scandals like Enron and Wirecard have shown how governance failures can lead to significant financial and reputational damage.

Attraction of Investors

Investors increasingly view governance as a critical factor when evaluating a company’s sustainability and risk profile. Firms with strong governance, such as Unilever and Microsoft, consistently outperform peers in financial performance and stakeholder trust. According to a study published on Academia.edu, both companies have demonstrated strong financial performance due to their governance practices.

Key Elements of Strong Governance

The importance of effective governance is further highlighted by the OECD Principles of Corporate Governance, which provide a globally recognized framework for transparent and accountable corporate practices.

Board Diversity and Independence: Diverse and independent boards contribute to better strategic decision-making and accountability. SpringerLink confirms that diversity enhances decision-making quality.
Transparency and Reporting: Transparent reporting builds trust among investors and regulators. AB Academies highlights its importance for investor confidence.
Executive Accountability: Linking executive pay to long-term performance ensures leadership integrity. Research from AB Academies supports the link between performance and pay.
Risk Management: Effective risk management protects against both financial and reputational risks.
Ethical Practices: Implementing anti-corruption measures and maintaining compliance with laws.

Governance in Emerging Economies

In emerging economies, strong governance frameworks play a transformative role in fostering investor confidence and driving sustainable economic growth. Countries like Saudi Arabia, with Vision 2030, and South Africa, with its King IV Code of Governance, have implemented significant reforms emphasizing transparency, accountability, and ethical leadership to attract foreign investment and modernize corporate practices.

Family-owned businesses, prevalent in regions like the Middle East and Africa, often face unique governance challenges. Implementing independent boards and family charters can help professionalize these businesses, ensuring long-term stability.

Leveraging Technology for Governance

Technological tools, such as those provided by DiliTrust, are transforming governance practices. Platforms for secure document management, compliance tracking, and board meeting organization improve transparency and decision-making efficiency. During my internship at DiliTrust, I witnessed firsthand how these tools streamline governance processes, ensuring accountability across various operational levels.

Career Opportunities in Governance

Governance expertise can lead to several impactful career paths:

Independent Board Member: Certifications like those from the ITA in Tunisia equip professionals to serve on corporate boards, ensuring strategic oversight.
Governance Consulting: ESG consulting firms assist businesses in enhancing governance practices, ESG compliance, and sustainability reporting.
ESG Rating Specialist: Working in agencies that assess corporate governance and sustainability standards.
Risk and Compliance Management: Roles focusing on enforcing governance frameworks within financial institutions and multinational corporations.

Useful Resources

Saudi Arabia’s Vision 2030

South Africa’s King IV Code of Governance

DiliTrust Official Website

OECD Principles of Corporate Governance

Global Reporting Initiative

Institut Tunisien des Administrateurs (ITA)

SpringerLink on Board Diversity

AB Academies on Governance

Academia.edu on Unilever and Microsoft

Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: Aggregated evidence from more than 2,000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233.

Eccles, R. G., Ioannou, I., & Serafeim, G. (2014). The impact of corporate sustainability on organizational processes and performance. Management Science, 60(11), 2835–2857.

About the Author

The article was written in January 2025 by Majd MAHRSI (ESSEC Business School, Global Bachelor in Business Administration (GBBA), 2021-2025).

Valuation methods

March 4, 2025January 5, 2025 by 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

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.

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.

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).

Real-Time Risk Management in the Trading Arena

February 5, 2025December 16, 2024 by Vardaan CHAWLA

Real-Time Risk Management in the Trading Arena

In this article, Vardaan CHAWLA (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2020-2023) shares a case study on real-time risk management in the trading arena.

As an individual investor venturing into the dynamic world of financial markets, it’s crucial to understand and implement effective risk management strategies. The following article, explores the key principles and techniques to safeguard your investments and navigate the potential risks.

Financial markets are very dynamic, interesting, and filled with opportunities and risks. Learning to manage risks in the always-changing world of financial markets is crucial. In the following article I discuss the effective methods to manage, navigate, and avoid risk while dealing in financial markets to help you make informed decisions and safeguard your money.

Understanding Your Risk Tolerance

The first principle of effective risk management is self-awareness. Before diving into financial markets one must assess one’s own risk tolerance meaning the amount of losses you are able to manage comfortably.

Ask yourself critical questions:

How much capital can I realistically afford to lose?
How would a significant loss impact my financial well-being?
Am I prone to emotional decision-making during market fluctuations?

After answering these questions you can start making your trading and risk management strategies and techniques. A very aggressive investor will be open to taking a high amount of risk with more potential results while a conservative investor will be the opposite, low risk with less potential returns. One must invest based on their own loss tolerance.

Core Risk Management Strategies

Once you understand your risk tolerance, equip yourself with these key risk management strategies:

Position Sizing: This describes how much capital is devoted to a specific deal. Starting small is a vital notion, particularly for novices. A typical place to start is with 1% to 2% of your entire portfolio for each deal. With a diversified portfolio, you can progressively raise position size as your experience and risk tolerance permits.
Stop-Loss: Stop orders are vital instruments for safeguarding your investment. To limit potential losses if the market swings against your position, a stop-loss order automatically sells an asset when the price hits a predefined level (lower than the current market price). It’s critical to create stop-loss levels that balance possible asset recovery with risk minimization.
Take Profit: Limit orders work similarly to stop-loss orders in that they automatically lock in profits by selling an asset when the price hits a predefined level (higher than the current market price). This lessens the chance of losing gains if the market turns south. To safeguard your earnings and resist the need to cling to a winning position for too long, use take-profit orders wisely.
Diversification: Avoid putting all of your money in one place. Distribute your investments throughout several industries, sectors, and asset classes. This lessens the effect that a fall in one asset will have on the value of your entire portfolio. Diversification makes your portfolio more stable and less vulnerable to changes in the market.
Risk-Reward Ratio: This measure contrasts the possible gain with the possible loss on a certain transaction. Seek for transactions where the possible profit margin outweighs the potential loss margin. A better risk profile is indicated by a greater ratio. Prior to making a trade, evaluating the risk-reward ratio will help you make well-informed judgments regarding potential gain vs downside.

The figures below illustrate how take-profit and stop-loss can be implemented for a given stock (Meta around August 15,2024). Two orders are sent to the market (at the same time): a sell limit order with a limit price of $290 and a stop order with a trigger price of $280. Note that it is not always possible to place both a limit order an stop order at the same time (it depends on the brokers or trading platforms).

In Figure 1, the stock price stays below the limit price and above the trigger price.

Figure 1. No order execution.

Source: computation by the author.

In Figure 2, the sell limit order is executed as the market price reaches the limit price of the order; the transaction price is $290.

Figure 2. Take profit: execution of the limit order.

Source: computation by the author.

In Figure 3, the sell stop order is executed as the market price reaches the trigger price of the order; the transaction price is $280 (or lower if the market is not very liquid).

Figure 3. Stop loss: execution of the stop order.

Source: computation by the author.

Advanced Risk Management Techniques

As you gain experience, consider incorporating these advanced techniques:

Hedging: This is the process of offsetting possible losses in your underlying holdings by employing derivative instruments, such as option contracts. Before putting hedging methods into practice, careful thought and comprehension are necessary because they can be complicated.
Volatility Targeting: This strategy modifies the overall risk exposure of your portfolio in response to fluctuations in the market. You may lower the sizes of your positions or devote more capital to less volatile assets during times of high volatility. On the other hand, you may decide to take on larger positions or invest in riskier assets during times of low volatility.

Disciplined Execution: The Key to Success

Risk management is not just about having the right tools; it’s about disciplined execution. Here are some essential practices to cultivate:

Trading Plan: One must work meticulously in developing a comprehensive trading plan that clearly defines your entry, exit, risk management strategies, and what you aim to achieve from trading and avoid emotional and impulsive decision-making.
Monitoring and Adjustment: You must also regularly monitor your portfolio and be updated on financial news in order to prepare for potential future losses or opportunities. To maximize your gains utilize Stop loss orders and take profit orders and adjust your trades and position as and when needed.
Emotional Control: When we receive surprise losses or surprise gains we are inclined to make emotional and impulsive decisions that can lead to further future losses. The trader must always make decisions with a calm composed mind to make sound decisions.

By adopting these risk management principles and maintaining disciplined execution, you can navigate the real-time financial markets with greater confidence and minimize the possibility of significant losses. Remember, risk management is an ongoing process that requires constant evaluation and adaptation.

Useful resources

SimTrade course Trade orders

Justin Kuepper (June 12, 2023) Risk Management Techniques for Active Traders

Amir Samimi & Alireza Bozorgian (2022) An Analysis of Risk Management in Financial Markets and Its Effects, Jounrnal of Engineering in Industrial Research, 3(1): 1-7

About the author

The article was written in December 2024 by Vardaan CHAWLA (ESSEC Business School, Master in Strategy and Management of International Business (SMIB), 2020-2023).

The World Trade Organization (WTO)

Trade Negotiation Teams – Representatives

Examples of governments’ Tariffs – a case study

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

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Break-even Chart from Excel