Trading Strategies Backtesting With Python – Jaro Algo

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What you'll learn

• How to install and set up Python and related libraries used in financial data analysis
• Get financial data for Forex, Stocks and more from different sources
• Essentials of Algorithmic trading and Technical analysis
• Build, backtest and analyse all kinds of different trading strategies and ideas
• How to create from scratch strategy development platform with Python
• Visualisation of data and results of strategy backtest
• Understanding of strategy backtest results as CAGR, Accuracy and much more

Requirements

• Basic Python knowledge (I explain each step so you can understand what I am doing)
• Basic trading knowledge

Description

Learn how to backtest most of the strategies for Forex and Stock trading. You will build strategy backtest platform from scratch and modify it for different strategies so you can backtest your or others ideas to see if there is any value in them. You will also be taught how to analyse backtest results and visualise important metrics. I will be adding more strategies and better ways to backtest and implement ideas in future lectures.

Who this course is for:

• Anyone interested in trading, who wants to backtest trading ideas with few lines of code

Course content
16 sections • 72 lectures • 9h 56m total length

• Introduction
• Getting Started v Financial data and visualisation
• Algorithmic Trading
• Strategy 1 – Moving average crossover
• Strategy 2 – Short term breakout with RSI
• Strategy 3 – Inside bar
• Strategy 4 – Long bar with small wicks
• Strategy 5 – Long bar with small wicks + SL to breakeven
• Strategy 6 – Bollinger bands mean cross
• Strategy 7 – London breakout
• Strategy 8 – Momentum counter
• Strategy 9 – Peak breakout
• Strategy 10 – Martingale system
• Market profile project with FXCM API
• Thank you

Get Trading Strategies Backtesting With Python – Jaro Algo, Only Price $37

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Trading foreign exchange, cryptocurrencies, and algorithmic assets on margin carries a high level of risk and may not be suitable for all investors. Past performance of any trading system or quantitative blueprint does not guarantee future results.<br><br><b>Asset Classification:</b>