trade-strategy 0.1.3

A Python package for analyzing investment portfolios, including using quantitative methods like the efficient frontier for calculations an optimal asset allocation strategy.

trade_strategy

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Table of Contents

• Installation
• How to Run example.py
• License

Installation

pip install trade-strategy

How to Run

To use the risk_return function, you can use the following Python code:

from trade_strategy import risk_return

tickers = ["AAPL", "MSFT", "GOOG"]
start_date = '2013-03-07'
end_date = '2025-04-05'

risk_return(tickers, start_date, end_date)

• Assets: ["AAPL", "MSFT", "GOOG"]
• Start Date: 2013-03-07
• End Date: 2025-04-05

Expected Output

The script will output the lowest risk, highest returns, and highest Sharpe ratio allocations for the specified tickers and date range.

Lowest risk Allocation
Returns                    0.248073
Risk                       0.234054
Sharpe Ratio               1.059898
Weights         [0.347, 0.352, 0.3]
Name: 69, dtype: object
['AAPL', 'MSFT', 'GOOG']

Highest Returns Allocation
Returns                      0.268417
Risk                         0.262248
Sharpe Ratio                 1.023524
Weights         [0.003, 0.986, 0.011]
Name: 116, dtype: object
['AAPL', 'MSFT', 'GOOG']

Highest Sharpe Allocation
Returns                      0.258282
Risk                         0.238805
Sharpe Ratio                 1.081562
Weights         [0.301, 0.588, 0.111]
Name: 128, dtype: object
['AAPL', 'MSFT', 'GOOG']

License

trade-strategy is distributed under the terms of the MIT license.