Название: Statistical Quantitative Methods in Finance: From Theory to Quantitative Portfolio ManagementАвтор: Samit Ahlawat
Издательство: Apress
Год: 2025
Страниц: 301
Язык: английский
Формат: pdf (true)
Размер: 25.8 MB
Statistical quantitative methods are vital for financial valuation models and benchmarking Machine Learning models in finance. This book explores the theoretical foundations of statistical models, from ordinary least squares (OLS) to the generalized method of moments (GMM) used in econometrics. It enriches your understanding through practical examples drawn from applied finance, demonstrating the real-world applications of these concepts. Additionally, the book delves into non-linear methods and Bayesian approaches, which are becoming increasingly popular among practitioners thanks to advancements in computational resources. By mastering these topics, you will be equipped to build foundational models crucial for applied Data Science, a skill highly sought after by software engineering and asset management firms. These enhancements are illustrated through real-world examples from finance and econometrics, accompanied by Python code. This book assumes the reader is familiar with Python programming. Knowledge of libraries such as Statsmodels and Sklearn is not required. During the course of reading this book, the reader will acquire a synoptic understanding of frequently used APIs available for the model implementations supported by these libraries. For Data scientists, Machine Learning engineers, finance professionals, and software engineers.
