Financial risk management [electronic resource] : models, history, and institutions / Allan M. Malz.

"An in-depth look at the tools and techniques professionals use to address financial risksRisk and uncertainty, as Allan Malz explains in his ground-breaking new book, are two completely different concepts. Risk is a quantifiable uncertainty that can be modeled, while uncertainty defines non-quantif...

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Bibliographic Details
Main Author: Malz, Allan M.
Language:English
Published: Hoboken, N.J. : Wiley, c2011.
Series:Wiley finance series.
Subjects:
Online Access:
Variant Title:
Financial Risk Management: Models, History, and Institutions
Format: Electronic eBook
Contents:
  • Machine generated contents note: Preface.
  • 1 Financial risk in a crisis-prone world.
  • 1.1 Some history: why is risk a separate discipline today?
  • 1.2 The scope of financial risk.
  • 2 Market risk basics.
  • 2.1 Arithmetic, geometric, and logarithmic security returns.
  • 2.2 Risk and securities prices: the standard asset pricing model.
  • 2.3 The standard asset distribution model.
  • 2.4 Portfolio risk in the standard model.
  • 2.5 Benchmark interest rates.
  • 3 Value-at-Risk.
  • 3.1 Definition of value-at-risk.
  • 3.2 Volatility estimation.
  • 3.3 Modes of computation.
  • 3.4 Short positions.
  • 3.5 Expected shortfall.
  • 4 Nonlinear risks and the treatment of bonds and options.
  • 4.1 Nonlinear risk measurement and options.
  • 4.2 Yield curve risk.
  • 4.3 Fixed-income VaR using duration and convexity.
  • 5 Portfolio VaR for market risk.
  • 5.1 The covariance and correlation matrices.
  • 5.2 Mapping and treatment of bonds and options.
  • 5.3 Delta-normal VaR.
  • 5.4 Portfolio VaR viaMonte Carlo simulation.
  • 5.5 Option vega risk.
  • 6 Credit and counterparty risk.
  • 6.1 Defining credit risk.
  • 6.2 Credit risky securities.
  • 6.3 Transaction cost problems in credit contracts.
  • 6.4 Default and recovery: analytic concepts.
  • 6.5 Assessing creditworthiness.
  • 6.6 Counterparty risk.
  • 6.7 TheMerton model.
  • 6.8 Credit factor models.
  • 6.9 Credit risk measures.
  • 7 Spread risk and default intensity models.
  • 7.1 Credit spreads.
  • 7.2 Default curve analytics.
  • 7.3 Risk-neutral estimates of default probabilities.
  • 7.4 Spread risk.
  • 8 Portfolio credit risk.
  • 8.1 Default correlation.
  • 8.2 Credit portfolio risk measurement.
  • 8.3 Credit VaR with the single-factor model.
  • 8.4 Using simulation and copulas to estimate portfolio credit risk.
  • 9 Structured credit risk.
  • 9.1 Structured credit basics.
  • 9.2 Credit scenario analysis of a securitization.
  • 9.3 Measuring structured credit risk via simulation.
  • 9.4 Standard tranches and implied correlation.
  • 9.5 Issuer and investor motivations for structured credit.
  • 10 Alternatives to the standard market risk model.
  • 10.1 Real-world asset price behavior.
  • 10.2 Alternative modeling approaches.
  • 10.3 The evidence on non-normality in derivatives prices.
  • 11 Assessing the quality of risk measures.
  • 11.1 Model risk.
  • 11.2 Backtesting of VaR.
  • 11.3 Coherence of VaR estimates.
  • 12 Liquidity and leverage.
  • 12.1 Funding liquidity risk.
  • 12.2 Markets for collateral.
  • 12.3 Leverage and forms of credit in contemporary finance.
  • 12.4 Transactions liquidity risk.
  • 12.5 Liquidity risk measurement.
  • 12.6 Liquidity and systemic risk.
  • 13 Risk control and mitigation.
  • 13.1 Defining risk capital.
  • 13.2 Risk contributions.
  • 13.3 Stress testing.
  • 13.4 Sizing positions.
  • 13.5 Risk reporting.
  • 13.6 Hedging and basis risk.
  • 14 Financial crises.
  • 14.1 Panics, runs, and crashes.
  • 14.2 Self-reinforcing mechanisms.
  • 14.3 Behavior of asset prices during crises.
  • 14.4 Causes of financial crises.
  • 14.5 Anticipating financial crises.
  • 15 Financial regulation.
  • 15.1 Scope and structure of regulation.
  • 15.2 Methods of regulation.
  • 15.3 Public policy toward financial crises.
  • 15.4 Pitfalls in regulation.
  • A Technical notes.
  • A.1 Binomial distribution.
  • A.2 Quantiles and quantile transformations.
  • A.3 Normal and lognormal distributions.
  • A.4 Hypothesis testing.
  • A.5 Monte Carlo simulation.
  • A.6 Homogeneous functions.
  • B Notation.
  • C Abbreviations.
  • D References.