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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

Writing a reversal strategy

To detect a reversal, we need to write an algorithm for any of the following three components:

  • Existing trend, where we are going to use the simple moving average
  • Volatility compression, where we are going to use a VoltyRatio indicator
  • Final trend, where we are going to use a breakout

Existing trend

To catch the existing trend, according to what we presented in Chapter 3, we know that we can use the simple moving average. So, to catch a downtrend, we can write the following condition:

close<average(close,PullLen)

Here, PullLen represents the length to calculate the simple moving average.

Adding such a condition to the long entry strategy’s rules will allow long trades only when the price is below the simple moving average selected. Conversely, to detect an existing uptrend, we can write this condition:

close>average(close,PullLen)

Adding this condition to the short entry strategy’s rules will allow...

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