Building a Robo-Advisor with Python and Machine Learning

Discover the power of robo-advisors! These automated platforms use algorithms to create and manage personalized investment portfolios, taking the guesswork out of investing. This tutorial will empower you to build your own robo-advisor using Python and the magic of machine learning. We’ll dive deep into the core components, from data acquisition and portfolio optimization to risk management and algorithmic trading.

Photo by Ishant Mishra on Unsplash

Table of Contents

• Data Acquisition and Preprocessing: Learn how to gather, clean and prepare financial data using libraries like yfinance, pandas and scikit-learn.
• Portfolio Optimization Techniques: Explore modern portfolio theory (MPT) and other optimization algorithms to construct efficient portfolios. We’ll even delve into the Black-Litterman model.
• Risk Management and Assessment: Implement risk assessment methods like Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) to understand and mitigate portfolio risk.
• Machine Learning for Investment Predictions: Use machine learning algorithms, including time series analysis and regression, to predict asset returns and boost portfolio performance.
• Backtesting and Performance Evaluation: Build a framework to simulate and evaluate the performance of various…