Automated Trading with R: Quantitative Research and Platform Development

This book 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 backtester, strategy optimizer, and fully functional trading platform.

Automated Trading with R provides automated traders with all the tools they need to trade algorithmically with their existing brokerage, from data management, to strategy optimization, to order execution, using free and publically available data. If your brokerage’s API is supported, the source code is plug-and-play.

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. The book’s three objectives are:

• To provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders.
  
• To offer an understanding the internal mechanisms of an automated trading system.
  
• To standardize discussion and notation of real-world strategy optimization problems.
  

What you’ll learn

• Programming an automated strategy in R gives the trader access to R and its package library for optimizing strategies, generating real-time trading decisions, and minimizing computation time.
  
• How to best simulate strategy performance in their specific use case to derive accurate performance estimates.
  
• Important machine-learning 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.
  

Who This Book Is For

This book is for traders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science. Graduate level finance or data science students. 

本書解釋了自動交易的廣泛主題，從數學開始，進而涉及計算和執行。讀者將獲得對於構建回測器、策略優化器和完全功能的交易平台所需的機械和計算考慮的獨特洞察力。

《使用R進行自動交易》為自動交易者提供了一切所需的工具，以現有的券商進行算法交易，從數據管理到策略優化，再到訂單執行，使用免費和公開可用的數據。如果您的券商的API受支持，源代碼即可即插即用。

本書中構建的平台可以作為零售交易者和小型基金使用的商業平台的完全替代品。軟件組件嚴格解耦且易於擴展，提供了替換任何數據源、交易算法或券商的機會。本書的三個目標是：

- 為小型基金和零售交易者提供一個靈活的替代方案，取代常見的策略自動化框架，如Tradestation、Metatrader和CQG。
- 提供對自動交易系統內部機制的理解。
- 標準化討論和記號現實世界策略優化問題。

你將學到什麼：

- 在R中編寫自動策略使交易者能夠使用R及其套件庫來優化策略、生成實時交易決策並最小化計算時間。
- 如何在特定用例中最佳模擬策略表現，以獲得準確的性能估計。
- 在時間序列上的統計有效性背景下，重要的機器學習準則。
- 對於投資組合管理和績效評估的關鍵現實變量的理解，包括延遲、回撤、交易規模變化、投資組合增長和未使用資本的懲罰。

本書適合對金融或計算機科學至少具有本科背景的零售或小型基金交易者/從業人員，以及研究生級別的金融或數據科學學生。