Understanding Financial Regulation

Just like HEC Paris, financial regulation spans many scientific areas, such as finance, law, accounting, economics, decision and incentives theory (among others). As a result, the HEC faculty, in all its richness and diversity, is ideally positioned to have a significant impact on the current debate on regulation.

This newsletter contains two main parts. It starts by presenting the main conclusions of recent academic articles written by the HEC faculty. Professors David Restrepo Amariles and Matteo Winkler from HEC Paris’ Law department study the extraterritorial application of US law on European corporations. Finance professor Guillaume Vuillemey, along with colleagues Darrell Duffie from Stanford University and Martin Scheicher from the European Central Bank, show how new rules on Credit Default Swaps can make derivatives markets safer. With his colleague Co-Pierre Georg from the Deutsche Bundesbank, HEC Paris’ Professor Jean-Edouard Colliard develops new ways of measuring regulatory complexity and ultimately making regulation more efficient.

In the second part, the newsletter shows how world-class academic analysis conducted at HEC can have impact beyond the research community. First, it focuses on its influence in the classroom. Professor Jean-Edouard Colliard explains how research benefits HEC students through the creation of novel and differentiating courses on financial regulation, which are typically not offered in other top business schools. Second, in an interview, three HEC Professors, Thierry Foucault, Christophe Pérignon and Guillaume Vuillemey explain how their research feeds the national debate on regulation through their scientific collaboration with major national supervisors.

We hope you will enjoy the read!

In the wake of the 2008-9 global financial crisis, the stability of derivatives markets has been brought into question, leading to regulatory reform. In these markets, hundreds of trillions of dollars were previously traded bilaterally in over-the-counter transactions with little regulation or control. “Derivative markets are based on long-term commitments,” explains Guillaume Vuillemey. “Counterparties agree to complete a trade in the future – maybe 10 years from now – but there is a risk that one party could default in the meantime making the commitment worthless”. In an attempt to reduce this counterparty risk, regulators worldwide have put mandates in place to safeguard trades through central clearing. 

Central clearing parties: counterparty to every trade

Central clearing parties are private institutions set up to mediate counterparty risk. Parties that trade standardized derivative contracts in the bilateral market go through central clearing parties to ensure all long-term contracts will be executed. A central clearing party thus become counterparty to every trade: essentially a buyer to every seller, and a seller to every buyer. “And what if these central clearing parties default?” asks Vuillemey. “This would be very dramatic as the centralization of all trades with these clearing parties exposes them to trillions of derivatives trades made by all banks and other financial institutions in the market”. 

Collateral demand of central clearing parties

One way central clearing parties can manage this risk is to call collateral from the parties involved in the trade. They store this, keeping it as a buffer to enable the future trade to go through, even if something goes wrong and one of the parties defaults before the trade is due. Creating these buffering reserves of collateral removes it from the market, which sparked debate within the financial community. They saw a trade-off between the enhanced financial stability offered by central clearing, and the cost of the possible collateral shortages that this may cause. This led to the question, with more stringent collateral requirements, would banks be able to preserve sufficient lending? In turn, how large will the cost of financial security be?  

Conditional on having the new requirements on bilateral trades, central clearing does not lead to increased margins.

A unique dataset

Vuillemey and co-workers had unique access to confidential data about bilateral derivative exposures worldwide. They used this real data in a simple model that enabled them to measure how much collateral is needed to safely clear derivatives in the market. It also enables determination of how estimates change with changes in market structure. “Suppose that we are trading today: I commit to sell you something in the future,” he explains. “The value of this contract changes on a daily basis, and we soon find out if it was bought at a good or bad price.

It then becomes an asset for you and a liability for me, or vice versa”. He adds, “The model says that the amount of collateral that has to be posted depends on how large a liability the contract is for me or for you, and on the volatility of its market value”. Initially, the model shows how much collateral is needed in the bilateral network before the regulatory reforms were put in place. It is then possible to determine how much collateral needs to be posted if there is a central clearing party involved. The number of these clearing parties can be altered and the effects on collateral requirements observed. 

Bilateral or centrally cleared trades?

The financial reform did not prohibit traditional over-the-counter bilateral transactions. Instead, these can coexist alongside central clearing parties but are subject to higher requirements that are now in place to push trades towards going through central clearing. Vuillemey’s results show that, conditional on having the new requirements on bilateral trades, central clearing does not lead to increased margins. Although the total collateral demanded does increase, the hypothesized collateral shortage does not necessarily follow. “When new trades are cleared, collateral requirements will initially increase,” explains Vuillemey. “But if everything in the market is cleared, requirements go down and clearing become less costly”. 

Financial stability and cost reduction are achievable

Vuillemey provides the following example: “For a trader with a diversified portfolio containing many types of derivatives that all go through central clearing, more collateral will be required and they will receive the benefits associated with diversification of trades. In addition, there will be netting benefits; as a buyer and seller with many different counterparties, having both long and short commitments, all of this can be netted out by the trader when going through the central clearing party. Resultantly, the collateral requirement for the trader will be lower, not higher”.

Vuillemey thus condemns the idea that to reduce costs, only a proportion of transactions should go through central clearing. He concludes, “The real benefits of financial stability and reduction of costs can only be achieved when the majority of trades go through.

The 2007-8 financial crisis revived debate about financial market regulation and these markets’ often-incomprehensible complexity. Itzhak Gilboa believes economists have a role to play in this debate, not necessarily by producing absolute answers, but more by listening to what people are saying, critiquing arguments, and raising new questions. In this paper, Gilboa and his co-authors focus on a common argument in microeconomic theory that says the standard model for trade under certainty can also apply to trade with uncertainty. They hold that, while mathematically valid, this argument may not be sufficient to justify trade in financial markets involving diametrically different beliefs. 

Motives for trade: differences in taste vs. differences in beliefs

In microeconomic theory, the concept of Pareto efficiency has become central for determining trade desirability. An allocation of resources is Pareto efficient if it cannot be improved upon in the eyes of one individual without harming another. It is generally thought that if an allocation is not Pareto efficient, it is worth improving on. The First Welfare Theorem offers one of the many arguments for free trade in competitive markets, as it shows that free competitive markets induce Pareto efficient allocations (1), whereas government intervention is likely to lead to non-Pareto efficient equilibria. Gilboa illustrates this notion with the following example. Suppose Mary is willing to pay up to 100€ for a service, and John is willing to provide it for at least 90€. A free market allows them to trade and be both better off. On the other hand, if John is required to pay 40% income tax, the net income of 60€ will not be worth his while, so he will refrain from offering his services. The resulting equilibrium would be Pareto inefficient; both Mary and John would have been better off if the transaction had taken place. Since the 1950s, the concept of Pareto efficiency has provided a strong argument for free trade under conditions of certainty, or when uncertainty is present but everyone shares the same beliefs about it.

Gilboa and his co-authors do not take issue with this argument, where trade is based on differences in personal taste. If one person trades his apple for another person’s banana such that each person ends up with the fruit he prefers, there is no reason to question the ethical or social desirability of the trade. On the other hand, when uncertainty in the form of differing beliefs about a situation is behind a trade, the ethical issue becomes far more elusive. People can be wrong about their beliefs in a way that they cannot be wrong about their tastes. A person who trades an apple for a banana cannot be convinced that she is wrong in liking bananas and would probably never have a reason to regret her trade. On the other hand, a person who trades/sells an option on the price of a good or financial asset may well live to regret her choice. When we see two agents “betting” on the future price of an asset, we can conclude that they have different beliefs and that at least one of them is wrong, even if at the time we cannot say which one. In an attempt to theoretically distinguish between the two types of motivations for trade, Gilboa and his co-authors have introduced a variation on the Pareto dominance concept that they call “No-Betting-Pareto”. It says that, to be considered an improvement, a trade should not only be desired by all the parties involved because of their (differing) beliefs; it should also be desirable for each party because of at least one (hypothetically) shared belief.

The standard model, based on the concept of Pareto efficiency, may not be sufficient to justify trade in financial markets involving agents with diametrically different beliefs.

Betting vs. risk-sharing

To illustrate the type of Pareto improvements being questioned, Gilboa presents a “zero-sum game” situation where there are two agents, and one gains solely at the expense of the other. Gilboa offers the image of dueling cavaliers, each of whom is wholly convinced that he is the best shot. Given these beliefs, they both wish a duel to take place (2), however their agreement stems from diametrically opposed preferences and diametrically opposed beliefs, which cancel out the agreement. Betting on the outcome of a horse race or the future price of oil are similar examples of the same principle. In sum, two parties may voluntarily choose to engage in a transaction, but the absence of any common interest or potential surplus means the transaction is only justified by a potentially dangerous difference in beliefs. Still, the No-Betting-Pareto criterion does not always rule out trade among agents who disagree on probabilities. Consider a start-up seeking to raise funds. Because there is potential gain for all the parties involved, the No-Betting Pareto criterion would not rule out investments in the company. Perhaps the parties involved have different beliefs, i.e., company founders are much more optimistic than potential investors, but as long as there exists a belief according to which the investment will be profitable to both parties, the No-Betting-Pareto criterion would endorse it.

Use a shared-belief criterion to determine trade desirability 

According to Gilboa and his colleagues, a shared belief that justifies trade for all parties makes it possible to distinguish between pure betting and the valid risk-sharing that financial markets allow. Their paper features convincing mathematical results that support this notion. On the other hand, it does not purport to offer practical advice for regulating financial markets. “Partly because of the financial crisis,” Gilboa comments, “many researchers have begun questioning whether the market should be trusted to reach a desirable equilibrium. It seems obvious that people are often unable to comprehend the financial instruments used in investing their savings, and it also seems clear that traders who invest other people’s money may not make the same decisions they would make if they were dealing with their own funds. These are all important issues, but our purpose in this paper is merely to highlight worthwhile reasons to rethink our standard means of analysis.”

1- Adam Smith’s intuition.
2- A situation called “spurious unanimity” by HEC professor Philippe Mongin.

Since the crisis, regulators have employed a range of tools and metrics to identify weaknesses within the banking system, focusing their efforts to identify the most risky banks. But, according to Christophe Pérignon, many of the tools they use are still ad hoc; they may not even be fit for purpose. “Although academic research shows it is not the safety of individual banks that matters but the resilience of the system as a whole, new regulations still try to control specific sources of risk and measure the risk of individual banks,” he explains. “There is a gap between regulatory tools and academic theory, so we decided to look at the two together. We have tried to connect existing theories with regulatory practice. Where are the gaps and flaws in our understanding?”

Sources of risk

The research team carried out a major review of research on system risk published in peer-reviewed journals over the past 35 years. With such a broad perspective, they identified three principal categories of systemic risk: 

• Systemic risk-taking – why banks tend to be exposed to similar risks
• Contagion – how failure spreads through the system via direct and indirect interbank connectivity and information flows
• Amplification – the mechanisms that turn small, localised problems into a widespread crisis

Based on these three channels, academics have proposed many measures of systemic risk. In order to compare them, the authors derived the most popular ones, such as SRISK and ΔCoVaR, in a unified framework. Pérignon explains why this framework is so important: “A model enables you to compare different measures and metrics. So this is the first time we have been able to look at different proposed and actual regulatory measures and compare how well they perform at evaluating system-wide risk. It also allows us to see how well the measures fit with theory.”

Regulators focus so much on identifying SIFIs that they risk losing track of the stability of the entire system.

Failing formulas

Their analysis also highlights some of the gaps and flaws in some of the regulatory instruments, such as an incorrect formula for identifying systemically important financial institutions (SIFIs). The SIFI scoring methodology developed by the Basel Committee on Banking Supervision (BCBS) uses 12 metrics to aggregate information about the size, activity, connectivity and complexity of an institution and the uniqueness of its services.

Equal importance is given to each measure. Jean-Edouard Colliard points out that the error is something one learns about in an undergraduate statistics class. “The sub-measure with the biggest range is the one that will most influence the overall score, yet this individual measure may not be the most significant.” The researchers have written to the relevant regulatory authority and proposed a simple correction to the formula. “It’s just a question of doing the maths differently,” says Pérignon. “Of course, changing a formula that affects how you set regulatory capital has huge implications, but this serves to demonstrate how our work is highlighting opportunities for improving regulation.” Colliard adds that regulators focus so much on identifying SIFIs that they risk losing track of the stability of the entire system.

For instance, the so-called stress testing of banks in the United States may have increased their individual resilience, but by herding them all in the same direction the system is less heterogeneous and thus more at risk in some circumstances. Pérignon also calls for closer collaboration between regulators and academics. “Regulators have access to a wealth of confidential data, but we show their tools are relatively simple. On the other hand, academics have developed much more sophisticated tools and measures using the limited market and public data they have available. It’s time to bring these two sets together through research collaboration.”

Collaboration across communities

A promising example of fruitful collaboration between supervisors and academics is the ACPR Chair on Regulation and Systemic Risks recently launched by the French Banking Supervisor (Autorité de Controle Prudentiel et de Résolution) in collaboration with researchers from ENSAE and HEC Paris. It is a massive undertaking, he concedes, and will require significant international coordination, standardisation of data and interoperability between systems. “It definitely needs to be done. The rather sad, but useful, conclusion from our review is that no methodology is yet available to capture all the risk within a system. If we can do that perhaps we could simply regulate banks with a Pigovian tax on the contribution of given institution to overall risk. But we can’t really start to develop such methodologies on unavailable data. That’s why collaboration is so imperative.”