Modelıng the volatılıty of stock returns Usıng arma and garch models

Abstract

Financial experts and investors are concerned about the uncertainty of the returns on investment assets caused by the variations in speculative market prices and market risk. Volatility has emerged as a very vital concept in diverse areas in financial theory and practice such as portfolio selection, derivative pricing, and risk management. This study employs stock prices of the Standard and Poor (S&P) 500 from 19th May 1998 to 15th May 2018 in modeling and forecasting stock returns and volatility using ARMA and GARCH models. The experimental results obtained with the suitable ARMA-GARCH model demonstrate the potential of the ARMA-GARCH model to predict stock returns and volatility satisfactorily in the short-run. With the results obtained ARMA-GARCH models can compete reasonably well with emerging forecasting techniques in short-term prediction