The impact of accounting disclosure on emerging stock market prediction in an unstable socio-political context

Abstract

The paper analyzes the impact of accounting disclosure on the prediction quality of stock market prices. The study also investigates whether a changing socio-political context affects the prediction quality. We focused on the Tunisian case, which has known a political turmoil in January 2011. Our sample includes 48,204 daily stock closing prices of 39 companies listed in Tunis Stock Exchange from 2009 to 2014. We used an Artificial Neural Network (ANN) with a Multi-layer Perceptron topology to predict the time series. The simulations showed that the average annual prediction error of the stock prices is the largest in the period relating to the January 2011 events. Thus, the country socio-political context impacts negatively the prediction quality of the stock market prices. Furthermore, the integration of an accounting variable improves the quality of the stock prices prediction for all the study periods, except the one that corresponds to the events of January 2011. In other words, it appears that accounting disclosure does not improve prices prediction quality in an unstable context.