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How to Develop a Simple Machine Learning Trading Algorithm Within TradeStation EasyLanguage: Writing EasyLanguage Programs to Automate Gene
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In chapter 1, entitled Developing a Simple Trading Algorithm, the book starts out by streamlining a two-step process for developing functional TradeStation EasyLanguage code. This process is illustrated in the development of a simple and functional automated trading algorithm. Upon the completion of step 1, a pseudo code is produced in which the analytical and executional components of the algorithmic trading strategy are described. Step 2 marks the transition of the trading algorithm from pseudocode to fully functional EasyLanguage syntax. In chapter 2, entitled Working with Inputs and Variables, many numerical (hardcoded) variables that exist within the working strategy code are substituted with input variable counterparts. This process enables such strategy components to be read, and therefore, optimized by TradeStation’s optimization engine.
In chapter 3, entitled Adding More Complex Money Management Logic, more complex money management logic is added to the existing strategy code. Through the implementation of various reserved TradeStation functions and the creation of a handful of simple proprietary formulas the updated strategy code is enabled to handle additional important logical entry parameters such as checking to see if the daily loss limit has been breached and if the maximum portfolio exposure in the trading account has been reached. Both of these money management components act as switches that, when activated, instruct the trading algorithm to ignore additional entry signals for the remainder of that trading day. In chapter 4, entitled Implementing Dynamic Execution Functionality, the existing exit execution logic is changed from a static form to a dynamic executional form. This is done through modifying the existing exit code syntax. Specifically, the existing exit execution (namely the setstoploss and setprofittarget functions) are tied to the output of a newly declared input variable called ExitType. Then additional types of exit executions are introduced within the strategy code and subsequently also tied to the output of the ExitType input variable, each exit with its own unique ExitType output value. This transformation enables the exit execution logic, that was once static, to now be readable by the TradeStation optimization engine, and thus, can now be optimized accordingly across the various types of exit executions.
Chapter 5, entitled Planning Out the Trading Application, outlines the planning and organization (i.e. step 1 one of the streamlined development process) of a trading application (built within TradeStation) that will automate the process of optimizing the parameters of the existing trading algorithm and then will, upon completion of said optimization, send the results to a designated excel file and then save that file. In chapter 6, entitled Building the Auto-Optimizer Trading Application in C#, the book presents and discusses the working code of the fully functional trading application (written in C# syntax) described in chapter 5.
- Sales Rank: #508238 in eBooks
- Published on: 2016-02-14
- Released on: 2016-02-14
- Format: Kindle eBook
Most helpful customer reviews
2 of 2 people found the following review helpful.
Don't buy it
By Hecman
The book tile is misleading. Totally unrelated to machine learning
1 of 1 people found the following review helpful.
Fraud warning
By Amazon Customer
Contents of the book has very little to do with the title
0 of 0 people found the following review helpful.
Excellent
By Edward E.
Excellent book, highly recommended to all traders and investors that use trade station platform for their investments, highly recommended even before I started reading this book.
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