Forecasting Sugar Price Fluctuation In Malaysia Using Geometric Brownian Motion Modelling
Keywords:Brownian motion, Drift value, MAPE, MSE, Volatility, Performance metric
A mathematical model known as Geometric Brownian motion has proven to be an effective tool that can be deployed to forecast the price of goods in the future due to the presence of random terms, which represent the stochastic or random fluctuation of prices over a given period of time. The success of this model revolves around the estimation of its governing parameters. To efficiently predict the price of goods, using the Geometric Brownian Motion model (GBM), one needs to determine the value of returns and use the calculated returns to estimate the value of drift as well as volatility. This research used the value of volatility and drift terms obtained from real data of sugar in the months under review. The method has shown to be very reliable in capturing the intelligent trend in the price of sugar in Malaysia. The model was able to stimulate the pattern of the predicted price that shares a great resemblance to the actual price of sugar. The result obtained is very encouraging and places this study with a good note now that the country is just returning to normalcy from the pandemic that has crippled the economies of most developing nations in the world. We used the model to predict the price of sugar for a period of 20 months and the result of our prediction as well as the graph of the predicted prices confirmed the practicability of the model. The obtained values of MAPE and MSE, two of the popular performance metrics, also justified the effectiveness of the GBM in capturing the trend in the data. This model can be classified as a good model that can be deployed to forecast the price of goods that exhibit high volatility.
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Copyright (c) 2023 Abdulwaheed Adebayo Salaudeen, Saratha Sathasivam, Majid Khan Majahar Ali, Nurwahdatul Elya Abd Wahab
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