Maximum Sharpe vs. minimum volatility

Introduction to Portfolio Analysis in Python

Charlotte Werger

Data Scientist

Remember the Efficient Frontier?

$$ Graph of the efficient frontier

Chart of options in PyPortfolioOpt

Maximum Sharpe portfolio: the highest Sharpe ratio on the EF

from pypfopt.efficient_frontier import EfficientFrontier

# Calculate the Efficient Frontier with mu and S
ef = EfficientFrontier(mu, Sigma)
raw_weights = ef.max_sharpe()

# Get interpretable weights 
cleaned_weights = ef.clean_weights()

{'GOOG': 0.01269,'AAPL': 0.09202,'FB': 0.19856,
 'BABA': 0.09642,'AMZN': 0.07158,'GE': 0.02456,...}

# Get performance numbers
ef.portfolio_performance(verbose=True)

Expected annual return: 33.0%
Annual volatility: 21.7%
Sharpe Ratio: 1.43

Minimum volatility portfolio: the lowest level of risk on the EF

# Calculate the Efficient Frontier with mu and S
ef = EfficientFrontier(mu, Sigma)

raw_weights = ef.min_volatility()

# Get interpretable weights and performance numbers
cleaned_weights = ef.clean_weights()

{'GOOG': 0.05664, 'AAPL': 0.087, 'FB': 0.1591,
'BABA': 0.09784, 'AMZN': 0.06986, 'GE': 0.0123,...}

ef.portfolio_performance(verbose=True)

Expected annual return: 17.4%
Annual volatility: 13.2%
Sharpe Ratio: 1.28

Graph of efficient frontier with minimum volatility and maximum Sharpe portfolio indicated

Graph of efficient frontier with minimum volatility and maximum Sharpe portfolio indicated

Introduction to Portfolio Analysis in Python