Assessing stock performance using panel logistic regression: evidence from KSA stock market

Abstract

Assessing stock performance is very important for investors to act in future. KSA stock market is evolving rapidly; so the objective of our paper is to analyze the stock performance using panel logistics regression. Logistic model is a variety of probabilistic statistical classification model. It is also used to predict a binary response from a binary predictor. The model has used the preprocessed data set of closing value, fundamental and technical data of 18 firm listed in KSA stock market. The data set encompassed the trading days from 7th January, 2007 to 18th May, 2015. The method gives us estimation with up to 90.59% accuracy.