How to Backtest Trading Algorithms and Portfolio Metrics with Python and QuantStats

Опубликовано: 07 Декабрь 2022
на канале: Matt Macarty

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‪@MattMacarty‬
#python #quant #backtesting #trading #quantstats #datascience

How to Backtest Trading Strategies and Algorithms, Generate Portfolio Metrics with Quantstats

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In this video, we'll be discussing Python Quantstats, a powerful tool for quantitative traders and investors. We'll be covering how to generate comprehensive portfolio metrics and back test trading algorithms in Python.

Quantstats allows you to easily measure your portfolio's performance and identify potential areas of improvement. By understanding your portfolio's performance in detail, you can make informed investment decisions. With Quantstats, you'll be able to generate powerful trading algorithms and improve your trading skills!

Learn how to:

Build a trading algorithm using Python NumPy and Pandas
Backtest your strategies to assess historical performance and risk.
Output key portfolio metrics like Sharpe ratio, Sortino ratio, and maximum drawdown.
Generate visualizations of your results

In this tutorial, you'll discover:

Essential Python libraries: NumPy & Pandas.
The QuantStats library: A comprehensive tool for backtesting and performance analysis.
Step-by-step guidance: From data preparation to result interpretation.
Real-world examples: To solidify your understanding.

Timestamps
==========
0:00 Intro
2:05 Stats Module Overview
6:55 Plots Module Overview
12:20 Reports Module Overview

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