金融计量经济学：理论、案例与 R 语言 (Financial Econometrics: Theory, Cases, and R Language)

This is a Chinese-language textbook on financial econometrics.

This textbook provides a comprehensive introduction to financial econometrics, covering fundamental theories and practical applications, with a strong emphasis on R programming. It offers an in-depth understanding of how econometric methods are applied in the context of financial markets, institutions, and financial instruments. The book is designed to address critical issues such as price formation, risk measurement, and policy transmission, making it an essential resource for both students and practitioners in the field.

The content is structured progressively from foundational concepts to advanced techniques, including regression analysis, time series models, ARCH/GARCH models, nonparametric methods, asset pricing models, continuous-time models, and yield curve modeling. Special emphasis is placed on volatility modeling, risk management, and tail risk estimation, with the final chapters exploring the integration of artificial intelligence and machine learning with financial econometrics.

The book places a strong focus on hands-on implementation using R, ensuring that readers not only gain theoretical insights but also develop practical data analysis skills. Each chapter is accompanied by runnable R code examples and structured exercises, providing a step-by-step guide for applying econometric methods to real-world financial data.

This work is intended for graduate students, advanced undergraduates in economics and finance, and professionals engaged in quantitative finance and economic research. It is ideal for those who seek a thorough and practical understanding of financial econometrics, with the added benefit of mastering R as a tool for financial analysis and modeling.

Full book materials are not hosted on this website due to copyright restrictions.

Recommended citation: Sun, J., Hong, Y., & Linton, O. (forthcoming 2026). 金融计量经济学：理论、案例与 R 语言 (Financial Econometrics: Theory, Cases, and R). Higher Education Press.