After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management. There are six chapters in this book, categorized into three parts: Financial Market and Financial Theory, Data Processing and High Performance Computing of R, and Financial Strategy Practice. Every chapter is a holistic knowledge system. Section One is Financial Market and Financial Theory (including Chapters 1 and 2), which starts with an understanding of finance to establish a basic idea of financial quantification. Chapter 1, Financial Market Overview, is the opening chapter of this book, which mainly introduces the ideas and methods of how to use R language to make quantitative investments. Chapter 2, Financial Theory, mainly introduces the classic theoretical models of finance and the R implementation methods. In Section Two, Data Processing and High Performance Computing of R (including Chapters 3 and 4), essential tools of R language for data processing and their usage are introduced in detail. Chapter 3, Data Processing of R, cored with the data processing technology of R, introduces the methods of processing different types of data with R language. In Chapter 4, High Performance Computing of R, three external technologies are introduced to help the performance of R language meet the production environment requirements. Section Three, Financial Strategy Practice (including Chapters 5 and 6), combines the R language technology and the financial market rules to solve the practical problems in financial quantification field. In Chapter 5, Bonds and Repurchase, readers can learn the market and the methods of low-risk investment. In Chapter 6, Quantitative Investment Strategy Cases, the investment research methods from theory to practice are introduced in whole. Since knowledge of different areas is comprehensively applied in this book, it is suggested that you read all the chapters in order. Some of the technical implementations mentioned in this book use the information from the other two books of the series, R for Programmers: Mastering the Tools and R2 for Programmers: Advanced Techniques, so it is recommended that you read those two as well.

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