Market-Based Estimation of Default Probabilities and its Application to Financial Market Surveillance

This paper reviews a number of different techniques for estimating default probabilities from the prices of publicly traded securities. These techniques are useful for assessing credit exposure, systemic risk, and stress testing financial systems. The choice of techniques was guided by their ease of...

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Bibliographic Details
Main Author: Chan-Lau, Jorge
Format: eBook
Language:English
Published: Washington, D.C. International Monetary Fund 2006
Series:IMF Working Papers
Subjects:
Online Access:
Collection: International Monetary Fund - Collection details see MPG.ReNa
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651 4 |a United States 
653 |a Inflation 
653 |a Credit 
653 |a Institutional Investors 
653 |a Stocks 
653 |a Pension Funds 
653 |a Asset valuation 
653 |a Finance 
653 |a Monetary economics 
653 |a Financial institutions 
653 |a Financial Instruments 
653 |a Deflation 
653 |a Monetary Policy, Central Banking, and the Supply of Money and Credit: General 
653 |a General Financial Markets: General (includes Measurement and Data) 
653 |a Asset and liability management 
653 |a Investments: Bonds 
653 |a Money 
653 |a Asset prices 
653 |a International Financial Markets 
653 |a Non-bank Financial Institutions 
653 |a Price Level 
653 |a Bonds 
653 |a Investments: Stocks 
653 |a Asset-liability management 
653 |a Prices 
653 |a Credit default swap 
653 |a Macroeconomics 
653 |a Investment & securities 
653 |a Financial Risk Management 
653 |a Money and Monetary Policy 
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520 |a This paper reviews a number of different techniques for estimating default probabilities from the prices of publicly traded securities. These techniques are useful for assessing credit exposure, systemic risk, and stress testing financial systems. The choice of techniques was guided by their ease of implementation and their applicability to a wide cross-section of countries and markets. Simple one-period cases are studied to sharpen the reader's intuition, and the usefulness of each technique for enhancing financial surveillance is illustrated with real applications