The 'lectures' are free to read through online, and provide examples and exercises. Maybe not the best for learning the basics of programming, because it goes through them relatively fast - but it does start assuming that you have zero knowledge of Python (for example goes through step-by-step on how to setup a Python environment, installing and using Git etc.). Upon completion of the book, readers will know how to research, analyze, backtest, and code up a successful trading strategy.QuantEcon is a really good resource, albeit more focused on economics. Chapters contain a balanced mix of mathematics, finance, and programming theory, and cover such topics as linear algebra, matrix manipulations, statistics, data analysis, and programming constructs. Individual case studies are split up into smaller modules for impact and retention. Multiple examples are included throughout the work containing useful computer code that can be applied directly to real-world trading models. Georgakopoulos outlines basic trading concepts and walks the reader through the necessary math, data analysis, finance, and programming concepts necessary to successfully implement a strategy. No prior programming knowledge is assumed on the part of the reader. This is an introductory work for students, researchers, and practitioners interested in applying statistical-programming, mathematical, and financial concepts to the creation and analysis of simple and practical trading strategies. Based on the author's own experience as a professor and high-frequency trader, this book provides a step-by-step approach to understanding complex quantitative finance problems and building functional computer code. Quantitative Trading with R offers readers a winning strategy for devising expertly-crafted and workable trading models using the R open-source programming language.
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