Python Trading Strategies | Create Trading Strategies And Backtest | Portfolio Management Techniques

Check out this comprehensive tutorial on Python Trading Strategies and Portfolio Management Techniques. In this step-by-step guide, you'll learn how to create trading strategies and backtest your own trading strategies using technical indicators. We'll cover everything from the strategy development process to portfolio management techniques.

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Join us as we walk you through the entire process using Quantra Blueshift, a free-to-use backtesting platform by QuantInsti. Starting with an introduction and outlining today's session, we'll dive into topics such as the Strategy Spectrum, Systematic Strategy Design Cycle, Systematic Strategy Development, and even provide a short primer on Python.

Discover the workflow on Blueshift and get started with strategy development. Learn how to incorporate technical indicators into your strategies, and follow along as we build a simple yet effective trading strategy. We'll also delve into evaluating the performance of your strategies and managing your strategy portfolio.

▶️ How to Become an Algo Trader:    • Learning Algo Trading with EPAT | Alg...  
▶️ Portfolio Optimization Techniques | Explained:    • Portfolio Optimization Techniques | E...  
▶️ Algorithmic Trading Course:    • Full Algorithmic Trading Python Course  

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Chapters:
0:00 Introduction
3:26 Outline of Today's Session
4:46 The Strategy Spectrum
6:25 Systematic Strategy Design Cycle
8:33 Systematic Strategy Development
12:07 A Very Short Primer on Python
24:28 Work-Flow on Blueshift
26:04 Blueshift Environment
30:34 Getting Started with Development
44:09 Getting Technical with Indicators
48:30 A Simple Strategy
54:29 Performance of Strategies
55:46 Managing Strategy Portfolio
58:12 Committee of Experts

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