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Modeling and forecasting volatility of financial data using Geometric Brownian Motion

Khamis, Azme and Abd Sukor, Muhammad Akram and Nor, Maria Elena and Mohd Razali, Siti Noor Asyikin and Mohd Salleh, Rohayu (2017) Modeling and forecasting volatility of financial data using Geometric Brownian Motion. International Journal of Advanced Research in Science, Engineering and Technology, 4 (9). pp. 4599-4605. ISSN 23500328

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Abstract

This study presents modeling and forecasting volatility of financial data in Bursa Malaysia using Geometric Brownian Motion. Stock market is the main platform for investors to participate and own some of their shares in a certain company. The changes of share prices on daily basis make the stock market more volatile and very difficult to predict because of economic factors of the country. From the Geometric Brownian Motion simulation, most of the graph will heading toward a direction with some deviation. The simulation is including the random walk from Wiener Process or Brownian Motion, which is the stochastic process for random behavior of share prices in stock market. Hundreds of simulation is done for generating the forecast value and it is selected based on the value of drift rate and volatility rate with the statistical test of forecast accuracy. For the prediction value distribution and interval, the Geometric Brownian Motion generating function is defined to produce the final value of commodity.

Item Type: Article
Uncontrolled Keywords: Modelling; forecasting; random walk; Wiener process; Geometric Brownian Motion
Subjects: Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 30 Apr 2019 01:07
Last Modified: 30 Apr 2019 01:07
URI: http://eprints.uthm.edu.my/id/eprint/10984
Statistic Details: View Download Statistic

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