Measuring Risk in Complex Stochastic Systems

Name: Measuring Risk in Complex Stochastic Systems
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Häftad, Engelska, 2000

Av J. Franke, Wolfgang Härdle, Gerhard Stahl

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This collection of articles by leading researchers will be of interest to people working in the area of mathematical finance.

Produktinformation

Utgivningsdatum2000-06-15
Mått155 x 235 x 16 mm
Vikt423 g
SpråkEngelska
SerieLecture Notes in Statistics
Antal sidor260
FörlagSpringer-Verlag New York Inc.
EAN9780387989969

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1 Allocation of Economic Capital in loan portfolios.- 1.1 Introduction.- 1.2 Credit portfolios.- 1.3 Economic Capital.- 1.4 Capital allocation based on Var/Covar.- 1.5 Allocation of marginal capital.- 1.6 Contributory capital based on coherent risk measures.- 1.7 Comparision of the capital allocation methods.- 1.8 Summary.- 2 Estimating Volatility for Long Holding Periods.- 2.1 Introduction.- 2.2 Construction and Properties of the Estimator.- 2.3 Monte Carlo Illustrations.- 2.4 Applications.- 2.5 Conclusion.- 3 A Simple Approach to Country Risk.- 3.1 Introduction.- 3.2 A Structural No-Arbitrage Approach.- 3.3 Description of Data and Parameter Setting.- 3.4 Pricing Capability.- 3.5 Hedging.- 3.6 Management of a Portfolio.- 3.7 Summary and Outlook.- 4 Predicting Bank Failures in Transition.- 4.1 Motivation.- 4.2 Improving “Standard” Models of Bank Failures.- 4.3 Czech banking sector.- 4.4 Data and the Results.- 4.5 Conclusions.- 5 Credit Scoring using Semiparametric Methods.- 5.1 Introduction.- 5.2 Data Description.- 5.3 Logistic Credit Scoring.- 5.4 Semiparametric Credit Scoring.- 5.5 Testing the Semiparametric Model.- 5.6 Misclassification and Performance Curves.- 6 On the (Ir) Relevancy of Value-at-Risk Regulation.- 6.1 Introduction.- 6.2 VaR and other Risk Measures.- 6.3 Economic Motives for VaR Management.- 6.4 Policy Implications.- 6.5 Conclusion.- 7 Backtesting beyond VaR.- 7.1 Forecast tasks and VaR Models.- 7.2 Backtesting based on the expected shortfall.- 7.3 Backtesting in Action.- 7.4 Conclusions.- 8 Measuring Implied Volatility Surface Risk using PCA.- 8.1 Introduction.- 8.2 PCA of Implicit Volatility Dynamics.- 8.3 Smile-consistent pricing models.- 8.4 Measuring Implicit Volatility Risk using VaR.- 9 Detection and estimation of changes in ARCHprocesses.- 9.1 Introduction.- 9.2 Testing for change-point in ARCH.- 9.3 Change-point estimation.- 10 Behaviour of Some Rank Statistics for Detecting Changes.- 10.1 Introduction.- 10.2 Limit Theorems.- 10.3 Simulations.- 10.4 Comments.- 10.5 Acknowledgements.- 11 A stable CAPM in the presence of heavy-tailed distributions.- 11.1 Introduction.- 11.2 Empirical evidence for the stable Paretian hypothesis.- 11.3 Stable CAPM and estimation for ?-coefficients.- 11.4 Empirical analysis of bivariate symmetry test.- 11.5 Summary.- 12 A Tailored Suit for Risk Management: Hyperbolic Model.- 12.1 Introduction.- 12.2 Advantages of the Proposed Risk Management Approach.- 12.3 Mathematical Definition of the P & L Distribution.- 12.4 Estimation of the P & L using the Hyperbolic Model.- 12.5 How well does the Approach Conform with Reality.- 12.6 Extension to Credit Risk.- 12.7 Application.- 13 Computational Resources for Extremes.- 13.1 Introduction.- 13.2 Computational Resources.- 13.3 Client/Server Architectures.- 13.4 Conclusion.- 14 Confidence intervals for a tail index estimator.- 14.1 Confidence intervals for a tail index estimator.- 15 Extremes of alpha-ARCH Models.- 15.1 Introduction.- 15.2 The model and its properties.- 15.3 The tails of the stationary distribution.- 15.4 Extreme value results.- 15.5 Empirical study.- 15.6 Proofs.- 15.7 Conclusion.

Measuring Risk in Complex Stochastic Systems

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