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Statistical Methods for Financial Engineering (Paperback)
Loot Price: R1,363
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Statistical Methods for Financial Engineering (Paperback)
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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, Levy 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 MATLAB (R) illustrate the
application of the techniques to solve real-world financial
problems. MATLAB and R programs are available on the author's
website.
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