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

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