Stocks daily data for comparing performance metrics applied to ML algorithms

Published: 24 September 2021| Version 1 | DOI: 10.17632/nbwhzctrjp.1
Contributor:
Jean Dessain

Description

SQL database (accessed with SQlite3 in Python) Daily OHLCV of DJIU, CACA40, BEL20, AEX and FTSE for testing main performance metrics and D-ratio with AI models predicting asset returns. 1. Daily returns are computed as target variable 2. Various AI models (MLP, LSTM, ResNet, XGB, PPO,...) have been tested for their ability to predict returns 3. Dozens of performance metrics usually applied in the literature have been assessed to identify the best performing algorithms: MSE, RMSE, MAE, MAPE,... , Accuracy, F1, precision, recall, R, R², Matthews correlation coefficient, Cohen's kappa, Sharpe, Sortino, Calmar,... 4. A new metric "D-ratio" has been tested

Files

Institutions

IESEG School of Management

Categories

Machine Learning Algorithm, Performance Measurement, Time Series Forecasting, Deep Learning, Empirical Finance

License