Titlebook: Applied Quantitative Finance; Theory and Computati Wolfgang H?rdle,Torsten Kleinow,Gerhard Stahl Book 20021st edition Springer-Verlag Berli

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Sensitivity analysis of credit portfolio modelsor Banking Supervision to allow sophisticated banks to use their own internal credit portfolio risk models has further highlighted the importance of a critical evaluation of such models. A crucial input for a model of credit-risky portfolios is the dependence structure of the underlying obligors. We

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The Analysis of Implied Volatilitiestfolio hedging, or option pricing, we need to have a precise notion of the market’s expectation of volatility. Much research has been done on the analysis of realized historic volatilities, Roll (1977) and references therein. However, since it seems unsettling to draw conclusions from past to expect

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How Precise Are Price Distributions Predicted by Implied Binomial Trees?row-nian Motion (GBM) model of Black and Scholes. The GBM model with constant volatility leads to a log-normal price distribution at any expiration date: All options on the underlying must have the same Black-Scholes (BS) implied volatility, and the Cox-Ross-Rubinstein (CRR) binomial tree makes use

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Estimating State-Price Densities with Nonparametric Regressionay derive the whole risk-neutral probability distribution of the underlying asset price at the maturity date of the options. Once this distribution also called State-Price Density (SPD) is estimated, it may serve for pricing new, complex or illiquid derivative securities.

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Trading on Deviations of Implied and Historical Densities 8. Instead of comparing this density to a historical density extracted from the observed time series of the underlying asset prices, i.e. a risk neutral density to an actual density, Ait-Sahalia, Wang and Yared (2000) propose to compare two risk neutral densities, one obtained from cross sectional

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An Empirical Likelihood Goodness-of-Fit Test for Diffusionsely on the actual model assumed for the drift and diffusion coefficient functions. Mismodelling these coefficients might result in biased prediction and incorrect parameter specification. We show in this chapter how the empirical likelihood technique, Owen (1988) and Owen (1990), may be used to cons

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A simple state space model of house priceshe development of its price will have a major impact on the buyer’s wealth over the life cycle. It will, for instance, affect her ability to obtain credit from commercial banks and therefore influence her consumption and savings decisions and opportunities. The behavior of house prices is therefore

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