Datasets¶

scikit-portfolio contains a small number of datasets, mostly used for testing and demonstration purpose. Once loaded they are cached in the home directory under the .skportfolio hidden folder, similarly to what is done with seaborn.

Technological stock prices¶

This small dataset contains almost five years of adjusted closing prices of technological stocks: Apple (AAPL), Microsoft (MSFT), Tesla (TSLA), Amazon (AMZN) and Microstrategy (MSTR). The data have been obtained through the excellent Python package yfinance

Simulated normal returns¶

These simulated returns are obtained from the Matlab financial toolbox, with random seed set to 42.

rng(42)
m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0; 
    0.00408 0.0289 0.0204 0.0119;
    0.00192 0.0204 0.0576 0.0336;
    0 0.0119 0.0336 0.1225 ];
m = m/12;
C = C/12;

AssetScenarios = mvnrnd(m, C, 20000);

This tool is very useful for testing against commercial implementations of various portfolio optimization methods, see for example the tests in efficient MAD

SP500 prices¶

SP500 index price

NASDAQ100 prices¶

NASDAQ100 prices