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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. This self-contained book guides current and future practitioners on implementing the most useful stochastic models used in financial engineering. Each chapter introduces powerful and practical statistical tools necessary to implement the models. Throughout the text, examples using MATLAB® illustrate the application of the techniques to solve real-world financial problems. MATLAB and R programs are available on the author's website.