PREDICTING LOGARITHMIC STOCK RETURNS BASED ON A NAIVE BAYESIAN CLASSIFIER

UDC 519.213: 5177
DOI: 10.36871/2618-9976.2023.09.004

Authors

Sergei Ya. Krivolapov,
Candidate of physicomathematical science, assistant professor of Department of Mathematics, Financial University under Govenment of Russian Federation, Moscow, Russia

Abstract

The time series of the results of stock quotations of a certain company and the values of logarithmic profitability calculated from them are considered. The forecast of the future value of logarithmic profitability is carried out based on the values of this indicator in previous periods. A Gaussian naive Bayesian classifier is used to calculate the forecast.

Keywords

logarithmic stock returns, Gaussian naive Bayesian classifier, Python language