Portfolio Optimization in Python: Boost Your Financial Performance

Ryan O'Connell, CFA, FRM shows you how to perform portfolio optimization in Python. Have you ever wondered how to calculate the optimal portfolio from a group of risky stocks or securities? Find out here!

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Chapters:
0:00 - Intro to Portfolio Optimization in Python
0:36 - Import Required Libraries
1:52 - Define Securities and Time Range
3:57 - Import Adjusted Close Prices From yFinance
6:48 - Calculate Daily Returns (Lognormal)
8:36 - Calculate the Covariance Matrix
9:57 - Calculate Optimal Weights of the Portfolio
10:07 - Calculate Portfolio Expected Return and Standard Deviation
13:38 - Calculate the Sharpe Ratio
14:56 - Retrieve the Risk Free Rate from the FRED API
16:51 - Set the Initial Weights and Constraints
18:13 - Find the Weights in the Optimal Portfolio
20:44 - Display the Optimal Portfolio Results

Get Free FRED API Key: fred.stlouisfed.org/docs/api/api_key.html

*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC

Alternative Titles:
"Portfolio Optimization Mastery: Enhance Your Investments with Python"
"Python for Portfolio Optimization: Boost Your Financial Performance"
"Discover the Power of Python in Portfolio Optimization"
"Portfolio Optimization Techniques: Unleash Python's Potential"
"Optimal Investment Strategies: Portfolio Optimization with Python"
"Achieve Financial Success through Portfolio Optimization in Python"
"Mastering Portfolio Optimization: Python's Guide to Better Investments"
"Supercharge Your Investments: Portfolio Optimization using Python"
"The Python Advantage: Expert Portfolio Optimization Tips"
"Portfolio Optimization in the Digital Age: Python's Winning Form