The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.

The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.

Black and Scholes (1973) and Merton (1974) (hereafter referred to as BSM) introduced the contingent claim approach (CCA) to the valuation of corporate debt and equity. The BSM modeling framework is also named the 'structural' approach to risky debt valuation. The CCA approach considers all stakeholders of the corporation as holding contingent claims on the assets of the corporation. Each claim holder has different priorities, maturities and conditions for payouts. It is based on the principle that all the assets belong to all the liability holders.In the structural approach the arrival of the default event relies on economic arguments for why firms default as it is explicitly related to the dynamics of the economic value of the firm. A standard structural model of default timing assumes that a corporation defaults when its assets drop to a sufficiently low level relative to its liabilities.The BSM modeling framework gives the basic fundamental version of the structural model where default is assumed to occur when the net asset value of the firm at the maturity of the pure-discount debt becomes negative, i.e., market value of the assets of the firm falls below the market value of the firm's liabilities. In a regime of limited liability, the shareholders of the firm have the option to default on the firm's debt. Equity can be viewed as a European call option on the firm's assets with a strike price equal to the face value of the firm's debt. Actually, CCA can be used to value all the components of the firm's liabilities. Option pricing models are used to value stocks, bonds, and many other types of corporate claims.Different versions of the model correspond to different assumptions about the conditions when a firm defaults. Merton (1974) assumes that the firm only defaults at the maturity date of the firm's outstanding debt when the net asset value of the firm, in market value terms, is negative. Others introduce other conditions for default. Also, different authors introduce more complicated capital structure with different kinds of bonds (e.g. senior and junior), warrants, corporate taxes, ESOP, and more. Volume 1: Foundations of CCA and Equity ValuationVolume 1 presents the seminal papers of Black and Scholes (1973) and Merton (1973, 1974). This volume also includes papers that specifically price equity as a call option on the corporation. It introduces warrants, convertible bonds and taxation as contingent claims on the corporation. It highlights the strong relationship between the CCA and the Modigliani-Miller (M&M) Theorems, and the relation to the Capital Assets Pricing Model (CAPM). Volume 2: CCA Approach to Corporate Debt ValuationVolume 2 concentrates on corporate bond valuation by introducing various types of bonds with different covenants as well as introducing various conditions that trigger default. While empirical evidence indicates that the simple Merton's model underestimates the credit spreads, additional risk factors like jumps can be used to resolve it. Volume 3: Issues in Corporate Finance with CCA ApproachVolume 3 includes papers that look at issues in corporate finance that can be explained with the CCA approach. These issues include the effect of dividend policy on the valuation of debt and equity, the pricing of employee stock options and many other issues of corporate governance. Volume 4: CCA Approach to Banking and Financial IntermediationVolume 4 focuses on the application of the contingent claim approach to banks and other financial intermediaries. Regulation of the banking industry led to the creation of new financial securities (e.g., CoCos) and new types of stakeholders (e.g., deposit insurers).

Little progress has been made so far in addressing—in a comprehensive way—the externalities caused by impact of the interconnectedness within institutions and markets on funding and market liquidity risk within financial systems. The Systemic Risk-adjusted Liquidity (SRL) model combines option pricing with market information and balance sheet data to generate a probabilistic measure of the frequency and severity of multiple entities experiencing a joint liquidity event. It links a firm’s maturity mismatch between assets and liabilities impacting the stability of its funding with those characteristics of other firms, subject to individual changes in risk profiles and common changes in market conditions. This approach can then be used (i) to quantify an individual institution’s time-varying contribution to system-wide liquidity shortfalls and (ii) to price liquidity risk within a macroprudential framework that, if used to motivate a capital charge or insurance premia, provides incentives for liquidity managers to internalize the systemic risk of their decisions. The model can also accommodate a stress testing approach for institution-specific and/or general funding shocks that generate estimates of systemic liquidity risk (and associated charges) under adverse scenarios.

In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.

The analysis of interconnectedness and contagion is an important part of the financial stability and risk assessment of a country’s financial system. This paper offers detailed and practical guidance on how to conduct a comprehensive analysis of interconnectedness and contagion for a country’s financial system under various circumstances. We survey current approaches at the IMF for analyzing interconnectedness within the interbank, cross-sector and cross-border dimensions through an overview and examples of the data and methodologies used in the Financial Sector Assessment Program. Finally, this paper offers practical advice on how to interpret results and discusses potential financial stability policy recommendations that can be drawn from this type of in-depth analysis.

The recent financial crisis and the difficulty of using mainstream macroeconomic models to accurately monitor and assess systemic risk have stimulated new analyses of how we measure economic activity and the development of more sophisticated models in which the financial sector plays a greater role. Markus Brunnermeier and Arvind Krishnamurthy have assembled contributions from leading academic researchers, central bankers, and other financial-market experts to explore the possibilities for advancing macroeconomic modeling in order to achieve more accurate economic measurement. Essays in this volume focus on the development of models capable of highlighting the vulnerabilities that leave the economy susceptible to adverse feedback loops and liquidity spirals. While these types of vulnerabilities have often been identified, they have not been consistently measured. In a financial world of increasing complexity and uncertainty, this volume is an invaluable resource for policymakers working to improve current measurement systems and for academics concerned with conceptualizing effective measurement.

I construct a systemic liquidity risk index (SLRI) from data on violations of arbitrage relationships across several asset classes between 2004 and 2010. Then I test whether the equity returns of 53 global banks were exposed to this liquidity risk factor. Results show that the level of bank returns is not directly affected by the SLRI, but their volatility increases when liquidity conditions deteriorate. I do not find a strong association between bank size and exposure to the SLRI - measured as the sensitivity of volatility to the index. Surprisingly, exposure to systemic liquidity risk is positively associated with the Net Stable Funding Ratio (NSFR). The link between equity volatility and the SLRI allows me to calculate the cost that would be borne by public authorities for providing liquidity support to the financial sector. I use this information to estimate a liquidity insurance premium that could be paid by individual banks in order to cover for that social cost.

This paper explains specifics of stress testing at the IMF. After a brief section on the evolution of stress tests at the IMF, the paper presents the key steps of an IMF staff stress test. They are followed by a discussion on how IMF staff uses stress tests results for policy advice. The paper concludes by identifying remaining challenges to make stress tests more useful for the monitoring of financial stability and an overview of IMF staff work program in that direction. Stress tests help assess the resilience of financial systems in IMF member countries and underpin policy advice to preserve or restore financial stability. This assessment and advice are mainly provided through the Financial Sector Assessment Program (FSAP). IMF staff also provide technical assistance in stress testing to many its member countries. An IMF macroprudential stress test is a methodology to assess financial vulnerabilities that can trigger systemic risk and the need of systemwide mitigating measures. The definition of systemic risk as used by the IMF is relevant to understanding the role of its stress tests as tools for financial surveillance and the IMF’s current work program. IMF stress tests primarily apply to depository intermediaries, and, systemically important banks.

To mitigate systemic risk, some regulators have advocated the greater use of centralized counterparties (CCPs) to clear Over-The-Counter (OTC) derivatives trades. Regulators should be cognizant that large banks active in the OTC derivatives market do not hold collateral against all the positions in their trading book and the paper proves an estimate of this under-collateralization. Whatever collateral is held by banks is allowed to be rehypothecated (or re-used) to others. Since CCPs would require all positions to have collateral against them, off-loading a significant portion of OTC derivatives transactions to central counterparties (CCPs) would require large increases in posted collateral, possibly requiring large banks to raise more capital. These costs suggest that most large banks will be reluctant to offload their positions to CCPs, and the paper proposes an appropriate capital levy on remaining positions to encourage the transition.