A Review on Geometric Brownian Motion for Forecasting the Daily Share Prices in CSE

Abstract

Capital Investments in stock market is the easiest and fastest way for building healthy financial foundation for our future life. As a result, stock markets have become more institutionalized in the past few decades and have been advanced as the main forms of investments for numerous organizations as well as individuals for arranging large investment funds to the general public. Present study mainly focuses an attempt to develop a suitable model based on Geometric Brownian Motion (GBM) to estimate the short-term share price behaviours in the Colombo Stock Exchange (CSE), Sri Lanka based on daily price indices data from January to December, 2013. Furthermore, a time series technique such as ARIMA was used to compare the results.