Market Risk Analysis, Value at Risk ModelsWritten by leading market risk academic, Professor Carol Alexander, ValueatRisk Models forms part four of the Market Risk Analysis four volume set. Building on the three previous volumes this book provides by far the most comprehensive, rigorous and detailed treatment of market VaR models. It rests on the basic knowledge of financial mathematics and statistics gained from Volume I, of factor models, principal component analysis, statistical models of volatility and correlation and copulas from Volume II and, from Volume III, knowledge of pricing and hedging financial instruments and of mapping portfolios of similar instruments to risk factors. A unifying characteristic of the series is the pedagogical approach to practical examples that are relevant to market risk analysis in practice. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CDROM . Empirical examples and case studies specific to this volume include:

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Bible fo VaR models. Have used if for my Advanced Quant Finance and MarketCredit Risk analysis course and continue using in my professional career.
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aggregate apply approximation asset assume assumption autocorrelation backtest banks basis points beta calculated copula covariance matrix credit spread daily log returns daily returns delta delta–gamma denotes discounted dynamic equity example excess kurtosis expected return forex formula FTSE FTSE 100 index gamma GARCH model hedged Hence historical data historical simulation implied volatility interest rate iTraxx LIBOR linear portfolio linear VaR model market risk measured model risk multivariate normal normal distribution normal linear normal mixture option portfolio P&L distribution parameters parametric linear portfolio returns portfolio value principal component quantile rebalancing return distribution risk factor mapping risk factor returns risk factor sensitivities risk horizon risk management risk metric risk model RiskMetrics sample scenario Section spreadsheet square root standalone standard deviation standard normal static stress testing Student t distribution systematic Table trading VaR estimates variance vector vega volatility adjustment volatility clustering volatility risk