Statistical Methods for Financial Engineering

Statistical Methods for Financial Engineering is a book that provides a comprehensive guide to implementing stochastic models in financial engineering, covering topics such as asset dynamics, estimation techniques, Black-Scholes model limitations, risk and performance measures, spot interest rate modeling, Lévy processes, GARCH models, dependence models, and filtering. It offers practical statistical tools and examples using MATLAB to solve real-world financial problems.

Format: Paperback / softback
Length: 496 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

While a plethora of financial engineering books exist, the statistical intricacies underlying the implementation of stochastic models in the field often receive inadequate attention or are confined to a limited number of well-known cases. Statistical Methods for Financial Engineering serves as a comprehensive guide for both current and aspiring practitioners, empowering them to effectively employ the most valuable stochastic models in financial engineering.

After providing an overview of univariate and multivariate models for asset dynamics, along with estimation methodologies, the book delves into the limitations of the Black-Scholes model, statistical tests to validate its assumptions, and the complexities of dynamic hedging in discrete time. It then explores the estimation of risk and performance metrics, the foundations of spot interest rate modeling, Lévy processes and their financial applications, the characteristics and parameter estimation of GARCH models, and the significance of dependence models in hedge fund replication and other applications. The book concludes with a discussion on filtering and its financial implications.

This self-contained book offers a foundational exploration of stochastic models and addresses concerns related to their practical application within the financial industry. Each chapter introduces robust and practical statistical tools essential for implementing these models. The author not only showcases efficient parameter estimation techniques but also demonstrates, whenever feasible, the validation of proposed models through rigorous testing. Throughout the text, real-world financial problems are illustrated using MATLAB®, showcasing the practical application of the discussed techniques. Additionally, MATLAB and R programs are readily accessible on the author's website for further exploration and implementation.

Weight: 920g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032477497