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Python Algorithmic Trading Cookbook

Python Algorithmic Trading Cookbook

By : Dagade
3.8 (10)
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Python Algorithmic Trading Cookbook

Python Algorithmic Trading Cookbook

3.8 (10)
By: Dagade

Overview of this book

If you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help. Starting by setting up the Python environment for trading and connectivity with brokers, you’ll then learn the important aspects of financial markets. As you progress, you’ll learn to fetch financial instruments, query and calculate various types of candles and historical data, and finally, compute and plot technical indicators. Next, you’ll learn how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. Later chapters will cover backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created. You’ll even understand how to automate trading and find the right strategy for making effective decisions that would otherwise be impossible for human traders. By the end of this book, you’ll be able to use Python libraries to conduct key tasks in the algorithmic trading ecosystem. Note: For demonstration, we're using Zerodha, an Indian Stock Market broker. If you're not an Indian resident, you won't be able to use Zerodha and therefore will not be able to test the examples directly. However, you can take inspiration from the book and apply the concepts across your preferred stock market broker of choice.
Table of Contents (16 chapters)
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Trend indicators – moving average convergence divergence

Moving average convergence divergence (MACD) is a lagging trend indicator. MACD has three components: the MACD line, MACD signal, and MACD histogram. The MACD line helps in identifying trend changes as it signals the start of a new trend direction. Large positive values of the MACD line indicate that the shorter EMA is much larger than the longer EMA. This suggests that there is an overbought condition in the market, which means prices will be going up. Similarly, large negative values of the MACD line indicate that the shorter EMA is much smaller than the longer EMA. This suggests that there is an oversold condition in the market, which means the prices will be going down. When the MACD line crosses above the MACD signal and is positive, a buy signal is generated; and the MACD line crosses below the MACD signal and becomes negative, a sell signal is generated.

The formulae for computing the three components of MACD are given...

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Python Algorithmic Trading Cookbook
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