A Framework For Assessing The Systemic Risk Of Major Financial Institutions

A Framework For Assessing The Systemic Risk Of Major Financial Institutions

A Framework For Assessing The Systemic Risk Of Major Financial Institutions

Xin Huang

Board of Governors of the Federal Reserve System

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Hao Zhou

Tsinghua University – PBC School of Finance

Haibin Zhu

Bank for International Settlements (BIS)

April 2009

BIS Working Paper No. 281


In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro-macro model, takes into account dynamic linkages between the health of major US banks and macro-financial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15% of total liabilities of 12 major US financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008.

A Framework For Assessing The Systemic Risk Of Major Financial Institutions – Introduction

Banks have been the most important financial intermediaries in the economy, by providing liquidity transformation and monitoring services. The malfunctioning of the banking system can be extremely costly to the real economy, as illustrated in a number of financial crises in both industrial and developing economies in the past few decades, including the current global credit-liquidity turmoil. Therefore, financial regulators and central banks have devoted much effort to monitoring and regulating the banking industry. Such regulation has been traditionally focused on assuring the soundness of individual banks. More recently, there has been a trend towards focusing on the stability of the banking system as a whole, which is known as the macro-prudential perspective of banking regulation (see Borio (2003) and Crocket (2000)). For instance, Aspachs et al. (2007), Goodhart et al. (2005, 2006) and Lehar (2005) propose measures of financial fragility that apply at both the individual and aggregate levels. At the international level, the Financial Sector Assessment Program (FSAP), a joint IMF and World Bank effort introduced in May 1999, aims to increase the effectiveness of efforts to promote the soundness of financial systems in their member countries.

In order to assess the health of a financial system, two related questions need to be addressed. First, how to measure the systemic risk of a financial system, where systemic risk defined as multiple simultaneous defaults of large financial institutions? Second, how to assess the vulnerability of the financial system to potential downside risks?

In answering the first question, traditional measures have focused on banks’ balance sheet information, such as non-performing loan ratios, earnings and profitability, liquidity and capital adequacy ratios. However, given that balance sheet information is only available on a relatively low-frequency (typically quarterly) basis and often with a significant lag, there have been growing efforts recently to measure the soundness of a financial system based on information from financial markets. For example, Chan-Lau and Gravelle (2005) and Avesani et al. (2006) suggest to treat a banking system as a portfolio and use the nth-to-default probability to measure the systemic risk by employing liquid equity market or CDS market data with a modern portfolio credit risk technology. Similarly, Lehar (2005) and Allenspach and Monnin (2006) propose to measure systemic risk, defined as the probability of a given number of simultaneous bank defaults, from equity return data. The market-based measures have two major advantages. First, they can be updated in a more timely fashion. Second, they are usually forward-looking, in that asset price movements reflect changes in market anticipation on future performance of the underlying entities.

In addressing the second question, stress-testing is a popular risk management tool to evaluate the potential impact of an extreme event on a financial firm or a financial sector. The stress testing exercise typically consists of two major steps. In the first step, an economic model is used to examine the dynamic linkages between the asset quality and underlying driving factors (macro-financial variables or latent factors). In the second step, stress testing scenarios (either historical or hypothetical ones), which are based on extreme movements of the driving factors, are fed into the model to assess the resilience of the financial sector. Avesani et al. (2006) and Basurto and Padilla (2006), among others, are examples of stress testing exercises on the financial sector using market-based information.

systemic risk

In this paper, we propose a framework for measuring and stress testing the systemic risk of the banking sector. Our framework follows the direction of using market information, but with interesting extensions that are designed to overcome a number of shortcomings in existing studies.

Echoing some earlier studies, we propose to construct the measure of systemic risk based on forward-looking price information of two highly-liquid markets, the credit default swap (CDS) spreads and the equity prices of individual banks. Both are available on a daily basis in real time. We are able to derive two key default risk parameters, the (risk-neutral) probability of default (PD) of individual banks and the asset return correlations, from the CDS spreads and the co-movement of equity returns, respectively. This approach does not rely on the balance sheet or accounting information that may be available only on a quarterly or longer time frequency, with a significant reporting lag.

systemic risk

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