Quantitative Trading with Python | Python Libraries for Quantitative Trading | Backtesting Strategy

Welcome to our comprehensive guide on Quantitative Trading with Python! In this video, we delve into the fascinating intersection of mathematics, statistics, and financial markets, showcasing how Python serves as a powerful tool for developing and executing trading strategies.

What You'll Learn:

Introduction to Quantitative Trading: Understand the core principles and why Python is the preferred language in this field.

Market Data Analysis: Discover how to analyze historical and real-time data to identify lucrative trading opportunities.

Backtesting Strategies: Learn how to evaluate your trading strategies with past data to ensure their effectiveness.

Risk Management Techniques: Explore methods to control exposure to losses, including the use of stop-loss orders and portfolio allocation.

Algorithmic Execution: Understand how to automate trade orders using set rules and optimize your trading process.

Machine Learning in Trading: Get introduced to advanced AI techniques for predictive modeling and algorithm development.

Steps to Build Your Own Trading Strategy:

Data Collection: Acquire historical market data from sources like Yahoo Finance and Binance API.

Data Pre-processing: Clean and prepare your data using Python libraries like Pandas.

Feature Engineering: Calculate indicators, such as moving averages, that will inform your trading decisions.

Strategy Development: Create a trading strategy, for instance, a simple moving average crossover.

Backtesting: Rigorously test the strategy to ensure it performs well against historical data.

Risk Management: Understand metrics like maximum drawdown and sharp ratio to measure performance accurately.

Automating Trades: Use APIs to implement automated trading strategies effectively.

Advanced Topics Covered:

Machine learning models for predicting price movements.

Deep learning techniques for time series forecasting.

Reinforcement learning for developing AI trading agents.

Resources for Further Learning:

"Quantitative Trading" by Ernest Chan

"Advances in Financial Machine Learning" by Marcos Lopez de Prado

"Algorithmic Trading" by Ernie Chan

Thank you for watching! If you’re passionate about trading and looking to enhance your skills with Python, don't forget to like, comment, and subscribe for more insightful content!

Video Tags:-

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