The concept of wrong-way risk (WWR) has recently gained significant attention in the field of risk management. This blog delves into the importance of WWR, as highlighted by the European Central Bank (ECB). WWR can be classified into two categories: generic wrong-way risk (GWWR) and specific wrong-way risk (SWWR). Both types occur when exposure to a counterparty increases concurrently with the risk of that counterparty defaulting.
Understanding Wrong-Way Risk and Its Methodologies
GWWR and SWWR pose considerable challenges for financial institutions. GWWR arises when the likelihood of default for counterparties is correlated with general market risk factors, while SWWR encompasses the correlation between exposure to a specific counterparty and its probability of default. These definitions emphasize the significance of comprehending WWR to effectively manage counterparty credit risk (CCR).
The ECB document acknowledges that although most institutions have established tools for CCR management, many lack a holistic view and fail to leverage stress testing and WWR analysis results effectively in their CCR management practices. Less sophisticated institutions often lack essential tools, such as counterparty and portfolio-specific exposure stress tests or a comprehensive understanding of GWWR. This observation highlights the need for further improvements in risk management practices to address WWR adequately.
This case underscores the importance of implementing robust methodologies for stress testing in scenarios involving SWWR. By adopting such methodologies, institutions may potentially avoid similar situations.
Credit Suisse and Archegos: A Case Study on Specific Wrong-Way Risk
The recent case involving Credit Suisse and Archegos Capital Management (Archegos) serves as a classic example of SWWR. As Archegos incurred losses while covering its highly concentrated equity positions, such as the $5.1 billion investment in ViacomCBS as of March 22, 2021, it approached default. Concurrently, during this period, the equity swaps between Archegos and Credit Suisse were increasing in value for Credit Suisse.
These trades executed between Credit Suisse and Archegos were highly leveraged and had long maturities, which exponentially increased Credit Suisse’s exposure to Archegos. Consequently, the variation margin, a form of collateral, surged from $177 million on March 24 to $2.5 billion on March 25. Regrettably, Archegos failed to meet this increased margin requirement, resulting in a default.
This case underscores the importance of implementing robust methodologies for stress testing in scenarios involving SWWR. By adopting such methodologies, institutions may potentially avoid similar situations. For instance, they could limit or prohibit leveraged equity trades with counterparties that exhibit high concentrations in similar trades with other banks. Furthermore, incorporating WWR calculations into the XVA analytics framework allows for a comprehensive assessment of the profitability of specific trades, by comparing profit and loss (P&L) with various valuation adjustments.
Drawing Lessons from Archegos and the Monoliners
Archegos’ strategy bears resemblances to the actions of monoliners leading up to the 2008 Credit Crisis, as these entities primarily sold credit risk. Both cases exemplify the dangers of concentrated risk and the potential consequences of SWWR. Failing to adequately assess the correlation between exposure and the probability of default can result in significant losses and systemic risks.
The Archegos incident highlights the importance of implementing comprehensive risk management frameworks that consider not only individual counterparty risk, but also the broader implications of market conditions and concentration of trades. Effective risk management practices should include stress testing methodologies that account for SWWR, providing a comprehensive view of potential losses and exposures.
Enhancing Risk Management Practices
To address the challenges posed by WWR, financial institutions should consider several key measures:
- Comprehensive Stress Testing: Institutions should develop robust stress testing frameworks that incorporate WWR scenarios. These stress tests should evaluate the impact of counterparty default and market risks on exposures, ensuring that risk limits and controls are appropriately set.
- Holistic View of Counterparty Risk: It is essential for institutions to have a holistic view of counterparty risk, including exposure stress tests and a concise understanding of GWWR. By analyzing the interplay between specific counterparty exposure and default probabilities, institutions can effectively manage their risks.
- Limits and Controls: Financial institutions should establish appropriate limits and controls to mitigate the impact of WWR. This includes monitoring concentrations in trades and counterparty exposures, especially when dealing with highly leveraged transactions.
- Collaboration and Information Sharing: Regulatory bodies should foster collaboration among financial institutions to enhance risk management practices and share information on potential risks and exposures. This collaborative approach can facilitate the identification and mitigation of WWR effectively.
By addressing WWR adequately, financial institutions can enhance their risk management frameworks and safeguard against potential losses arising from counterparty defaults and market risks.
Robust Stress Testing Methodologies
Understanding and effectively managing WWR is crucial for financial institutions to mitigate counterparty credit risk. The case involving Credit Suisse and Archegos Capital Management exemplifies the impact of SWWR and the need for robust stress testing methodologies, like those provided by Quantifi. Institutions must take a holistic approach to risk management, incorporating comprehensive stress tests, counterparty exposure analysis, and effective limits and controls. By addressing WWR adequately, financial institutions can enhance their risk management frameworks and safeguard against potential losses arising from counterparty defaults and market risks.
Typically stress testing does not require additional modelling. Instead, it involves selecting scenarios that effectively capture market stress conditions or utilising historical market data from notable periods, such as September 2008.
On the contrary, WWR requires the implementation of additional tools that can correlate market factors and probability or time of counterparty default. From an analytics standpoint, there is minimal disparity between SWWR) and GWWR, as both cases involve specifying a market factor and its correlation with default. The difference lies in SWWR, where the market factor can be a stock or CDS spread of an individual company, while in GWWR, it can encompass multiple market factors such as stock and credit indexes, interest rate and foreign exchange curves, and more.
Efficiency becomes a significant concern in XVA calculations, particularly when dealing with numerous WWR scenarios. However, there are methodologies available that enable exposure calculations to be performed only once, incorporating WWR by reweighing Monte Carlo paths. It is also crucial to consider jumps-at-default, which account for abrupt market shifts at the time of default. Even a well-collateralized position may experience substantial losses in such cases.