Statistical Methods for Financial Engineering

Statistical Methods for Financial Engineering

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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. Statistical Methods for Financial Engineering guides current and future practitioners on implementing the most useful stochastic models used in financial engineering. 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, LAcvy 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 applications. It concludes with the topic of filtering and its financial applications. This self-contained book offers a basic presentation of stochastic models and addresses issues related to their implementation in the financial industry. Each chapter introduces powerful and practical statistical tools necessary to implement the models. The author not only shows how to estimate parameters efficiently, but he also demonstrates, whenever possible, how to test the validity of the proposed models. Throughout the text, examples using MATLABAr illustrate the application of the techniques to solve real-world financial problems. MATLAB and R programs are available on the authora€™s website.Suppose that the estimated parameters of a GARCH(1, 1) are I¼ = 0.002, I‰ = 2.5A— 10aˆ’6, I² = .88 and Ip = .105. Here we assume ... Consider the random variable X = 4 I€2 aˆžaˆ‘ k=1Z2k(2kaˆ’1)2 , where Z1 , Z2 , ... are independent and identically distributed standard Gaus- sian variables. Show that the law ... Construct a MATLAB function to simulate a E-GARCH, a NGARCH, a GARCH-M, and a GJR- GARCH.

Title:Statistical Methods for Financial Engineering
Author: Bruno Remillard
Publisher:CRC Press - 2013-04-05

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