Statistical Methods for Financial Engineering av Bruno Remillard

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<P>While many financial engineering books are available, the statistical aspects behind the implementation of stochastic models used in the field are often overlooked or restricted to a few well-known cases. <STRONG>Statistical Methods for Financial Engineering</STRONG> guides current and future practitioners on implementing the most useful stochastic models used in financial engineering. </P><br/><br/><P></P><br/><br/><P>After introducing properties of univariate and multivariate models for asset dynamics as well as estimation techniques, the book discusses limits of the Black-Scholes model, statistical tests to verify some of its assumptions, and the challenges of dynamic hedging in discrete time. It then covers the estimation of risk and performance measures, the foundations of spot interest rate modeling, L¿ processes and their financial applications, the properties and parameter estimation of GARCH models, and the importance of dependence models in hedge fund replication and other