Automated Trading with R provides all the tools you need to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage’s API, and the source code is plug-and-play.
Automated Trading with R explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform.
The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage.
- Provides a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders.
- Offers an understanding of the internal mechanisms of an automated trading system.
- Standardizes discussion and notation of real-world strategy optimization problems.
What You’ll Learn
- To optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library.
- How to best simulate strategy performance to derive accurate performance estimates.
- Important optimization criteria for statistical validity in the context of time series.
- An understanding of critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital.
Where to Buy
Visit our forum site, r.chrisconlan.com, to discuss and build on finance and programming topics detailed in the text. The site contains information on how to obtain the source code, instructions and reference materials for new R users, and hosts the text’s developer community. The community is encouraged to modify and contribute improvements to the Community Platform hosted at Github.