Udemy - Backtesting Crypto Trading Strategies with Python & C + + 2021

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Description

Backtesting Crypto Trading Strategies with Python & C++ 2021



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 54 lectures (8h 15m) | Size: 2.26 GB
Use Python and the Power of C++ for High-Performance Backtesting and Optimization of your Trading Strategies
What you'll learn:
Collect Data from Cryptocurrency Exchanges through their REST API
Store Data using the HDF5 format
Use the Pandas library to calculate Technical Indicators
Backtest various types of strategies and prepare to backtest your own
Link a Python and C++ Program
Use C++ to perform heavy calculations
Use Visual Studio Code and CMake to Create a C++ Library
Avoid common mistakes when backtesting
Optimize your backtesting results with a Genetic Algorithm
Implement the NSGA-2 Algorithm

Requirements
Basic Python knowledge (know what a class/object is, dictionaries, lists, functions, loops, etc.)
Basic knowledge about trading (what candlesticks are, Long/Short...)

Description
Backtest your trading ideas before implementing them in real conditions!
Backtesting is an essential step when elaborating a trading strategy. This course will explain how you can use programming to estimate the potential performance of your strategy and avoid unpleasant surprises in live trading.
By the end of the course, you will be able to build your own backtesting framework and comfortably use all its features.

Collect and store large amounts of market data
Before starting to backtest, you need to have a reliable system that collects, stores and organizes the data. You will learn how to fetch data from any cryptocurrency exchange (Binance, FTX...) and store candlestick data efficiently in a powerful file format: HDF5. Many developers do not yet know about this file format, so you will have the upper hand by learning it!



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Udemy - Backtesting Crypto Trading Strategies with Python & C + + 2021


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2.8 GB
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Udemy - Backtesting Crypto Trading Strategies with Python & C + + 2021


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