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Geometric Brownian Motion with Ito's lemma approach to evaluate market fluctuations: A case study on Colombo Stock Exchange

R. M. Kapila Tharanga Rathnayaka · D. M. K. N. Seneviratna

26 citations0/0 files storedInternational Conference on Behavioral, Economic, and Socio-Cultural Computing

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Stochastic processes and financial applications

Abstract

The data forecasting in economical time series provides a significant guidance for making decisions in the financial markets today. It can be widely applied for solving economic problems with uncertainty and instability patterns. Forecasting high volatile fluctuations with instability behavioral patterns make complicated problems in stock markets around the world today. The main focus of this study is to develop a forecasting model based on Geometric Brownian Motion approach for estimating share price indices in short-term investments in the Colombo Stock Exchange (CSE), Sri Lanka. Furthermore, traditional ARIMA approach was used to compare the predictions. The results reveal that, the new proposed model is more significant for investors in making their investment decisions wisely.

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References

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