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  • Book Overview & Buying TradeStation EasyLanguage for Algorithmic Trading
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TradeStation EasyLanguage for Algorithmic Trading

TradeStation EasyLanguage for Algorithmic Trading

By : Domenico D'Errico
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TradeStation EasyLanguage for Algorithmic Trading

TradeStation EasyLanguage for Algorithmic Trading

3 (2)
By: Domenico D'Errico

Overview of this book

With AI revolutionizing financial markets, every trader will soon get easy access to AI models through free Python libraries and datasets, with all of them making the same trades! This behavior will modify prices and trading volumes, potentially altering future datasets, leading to major corporations investing heavily in technology, big data, and expert teams. However, individual traders need not be intimidated because this dynamic has been seen before whenever new technologies have entered the trading market. Written by a quantitative algorithmic trading developer with over 15 years of experience in the finance industry, this book will ground you by taking a rational approach to algorithmic trading, where EasyLanguage, datasets, charts, and AI are tools for your journey toward mastering the markets. Your unique human intelligence remains invaluable in navigating and understanding market complexities as you explore the realm of institutional insights, satisfying your hunger to learn real-world algorithmic trading applications from the institutional perspective. By the end of this book, you’ll be able to confidently apply TradeStation EasyLanguage to algorithmic trading, integrate machine learning to refine your strategies, and craft a personalized approach to confidently navigate the financial markets.
Table of Contents (13 chapters)
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Summary

In this chapter, we delved into a very important market pattern: trend pullback. Initially, we learned the rationale behind such market behavior and split it into three components: a trend, a pullback, and an impulse. After that, we wrote several algorithms to identify the different components and assemble them in various ways, akin to playing with bricks. Then, we conducted a multiple-sensitivity analysis to check strategy robustness.

As you may have noticed thus far, we focused solely on entry logic, leaving exits to only some holding periods. As you will better understand in the next chapter, dedicated to risk management, the choice of building algorithms that separate entries from exits is not arbitrary but, rather, has a valid reason behind it.

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TradeStation EasyLanguage for Algorithmic Trading
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