Use of geometric Brownian motion to forecast stock market scenario using post covid-19 NEPSE index

Abstract

Stock market is one of the fields where the randomness is prominent factor to be considered. Although many stochastic process deals which the randomness found in nature through the interdisciplinary subject like Econophysics, many of them exhibits cumbersome trends. So, Geometric Brownian motion (GBM) is used to analyze the market scenario of Nepal on the basis of the parameter; NEPSE Index along with the prediction of indices through python programming platform. Python simulation was carried out to check the consistency by implying it to the stable market timeline 2003/2004. And after the verification of the model proposed in the stable market year, the model (GBM) is employed to the unstable timeline; pandemic situation by COVID-19 in 2020. Mapping of Nepal stock market through GBM was found to be consistent with the standard forecasting accuracy making GBM one of the flexible and consistent to predict stock market scenario of Nepal accounting the random nature. BIBECHANA 18 (2) (2021) 50-60