Overview

Original Research

FORECASTING FUTURE STOCK RETURN IN INFORMATIONALLY INEFFICIENT MARKETS

ABDULMALIKI ARUNA KILANGE 1, KUBE ANANDA 2, and PHILIP NGARE 3.

Vol 18, No 07 ( 2023 )   |  DOI: 10.17605/OSF.IO/G73QN   |   Author Affiliation: Ph.D Student, Department of Mathematics, Pan African University Institute of Basic Sciences, Technology and Innovation, Nairobi, Kenya. Assistant Lecturer, Department of Mathematics and Statistics, University of Dodoma, Dodoma, Tanzania 1; Lecturer, Department of Mathematics and Actuarial Sciences, Kenyatta University, Nairobi, Kenya 2; Professor, School of Mathematics, University of Nairobi, Nairobi, Kenya 3.   |   Licensing: CC 4.0   |   Pg no: 2122-2128   |   Published on: 31-07-2023

Abstract

As a characteristic of informationally inefficient economies, asymmetric information has frequently led to distorted financial markets. By using stochastic optimization techniques, we constructed a model that addresses the problem of mispricing financial instruments in markets that do not conform to the traditional Markowitz portfolio optimization. The model does not suffer from adverse observations and is hence insensitive to sudden changes in the model parameters. We propose forecasting future stock market returns using the model constructed under informationally inefficient markets. Using data from BofA Merrill Lynch, we estimated an optimal forecasting model for this work. The sample period is from December 1998 to November 2017, and the forecast period starts 14 years after the beginning of the sample. We conclude that there is substantial predictability in stock market returns, as with our constructed model, an investor could have timed the market and gained up to 6.11% over the course of five years.

Keywords

Inefficient Market; Log Return; Return Predictability; Information Asymmetry.