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TradeStation EasyLanguage for Algorithmic Trading

You're reading from   TradeStation EasyLanguage for Algorithmic Trading Discover real-world institutional applications of Equities, Futures, and Forex markets

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835881200
Length 282 pages
Edition 1st Edition
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Author (1):
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Domenico D'Errico Domenico D'Errico
Author Profile Icon Domenico D'Errico
Domenico D'Errico
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Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Introduction to Algorithmic Trading and the TradeStation Platform FREE CHAPTER 2. Chapter 2: Getting Hands-On with EasyLanguage 3. Chapter 3: Writing a Trend Strategy 4. Chapter 4: Strategy Backtesting and Validation 5. Chapter 5: Reversal Strategies 6. Chapter 6: Trend Pullback Strategies 7. Chapter 7: Risk Management 8. Chapter 8: Futures and Forex Algorithmic Trading 9. Chapter 9: The Trading Operational Plan 10. Chapter 10: EasyLanguage in AI – Bridging Traditional Trading and Advanced Analytics 11. Chapter 11: EasyLanguage for Machine Learning 12. Index

Backtesting short strategies

Now, we’ll attempt to set up a reversal short strategy. Here, we need to make a few considerations: from an algorithmic programming standpoint, a short strategy is simply a long strategy written with conditions reversed. However, from a financial market perspective, it’s not the same thing. The stock market trends upward around 90% of the time, so the strategy we’re outlining is purely demonstrative.

In this section, we are going to do the following:

  • Run a multiple-sensitivity analysis on the SPDR S&P 500 ETF Trust (SPY)
  • Export data into an Excel file and create an ROA heatmap
  • Select the best input set

Running multiple-sensitivity analysis on the SPY

Let’s run an optimization with the settings shown in Table 5.2:

Inputs

Values

Dir

-1

...
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