An Introduction to Analysis of Financial Data with R

This book provides a systematic and mathematically accessible introduction to financial econometric models and their applications in modeling and predicting financial time series data. It emphasizes empirical financial data and focuses on real-world examples. Following this approach, readers will master key aspects of financial time series, including volatility modeling, neural...

This book provides a systematic and mathematically accessible introduction to financial econometric models and their applications in modeling and predicting financial time series data. It emphasizes empirical financial data and focuses on real-world examples. Following this approach, readers will master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure, and high-frequency financial data. S-Plus® commands and illustrations are used extensively throughout the book in order to highlight accurate interpretations and graphical representations of financial data. Exercises are included in order to provide readers with more opportunities to put the models and methods into everyday practice. The tools provided in the text aid readers in developing a deeper understanding of financial markets through firsthand experience in working with financial data, most importantly without needless computation.

Ruey S. Tsay（蔡瑞胸），美国芝加哥大学布斯商学院计量经济学与统计学的 H.G.B. Alexander 讲席教授，美国统计协会、数理统计学会及英国皇家统计学会的会士，中国台湾“中央研究院”院士。他是 Journal of Forecasting 的联合主编，也是 Asia-Pacific Financial Markets、Studies in Nonlinear Dynamics and Econometrics 和 Metron 等期刊的副主编。Tsay 教授在商务和经济预测、数据分析、风险管理以及过程控制等领域发表学术论文100多篇，还拥有美国专利“System and method for building a time series model (2005)”。