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Algorithmic trading from A to Z using Python
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[Image: d952492b1d715d329462a1376e255914.jpg]
Algorithmic trading from A to Z using Python
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 79 lectures (6h 17m) | Size: 2.6 GB

Technical analysis, Machine Learning, Price Action, Backtest, MetaTrader 5 live trading.

What you'll learn
?Create an algorithmic trading strategy from A to Z (data import to live trading)
?Put any algorithm in live trading using MetaTrader 5 and Python
?Data Cleaning using Pandas
?️Guided tour thought the main algorithmic trading strategy (Technical Analysis, Price action, Machine Learning)
?Manage financial data using Numpy, Pandas and Matplotlib
?Python programming for algorithmic trading
?Create scaling, intraday and swing trading strategies
? Import stock price from Yahoo Finance and from your broker

Requirements
Nothing

Description
Do you want to create algorithmic trading strategies?

You already have some trading knowledge and you want to learn about quantitative trading/finance?

You are simply a curious person who wants to get into this subject to monetize and diversify your knowledge?

If you answer at least one of these questions, I welcome you to this course. All the applications of the course will be done using Python. However, for beginners in Python, don't panic! There is a FREE python crash course included to master Python.

In this course, you will learn how to use technical analysis, price action, machine learning to create robust strategies. You will perform quantitative analysis to find patterns in the data. Once you will have many profitable strategies, we will learn how to perform vectorized backtesting. Then you will apply portfolio techniques to reduce the drawdown and maximize your returns.

You will learn and understand quantitative analysis used by portfolio managers and professional traders

Modeling: Technical analysis (Moving average, RSI), price action (Support, resistance) and Machine Learning (Linear regression).

Backtesting: Do a backtest properly without error and minimize the computation time (Vectorized Backtesting).

Portfolio management: Combine strategies properly (Strategies portfolio).

Why this course and not another?

This is not a programming course nor a trading course or a machine learning course. It is a course in which statistics, programming and financial theory are used for trading.

This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to finance.

You can ask questions or read our quantitative finance articles simply by registering on our free Discord forum.

Without forgetting that the course is satisfied or refunded for 30 days. Don't miss an opportunity to improve your knowledge of this fascinating subject.

Who this course is for
Everyone who wants to learn algorithmic trading

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