A Neural-Network Approach to the Modeling of the Impact of Market Volatility on Investment

Advances in Mathematical Finance and Applications

مقاله 10، دوره 5، شماره 4، دی 2020، صفحه 569-581   

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2020.674953

نویسندگان

Mohammad Azim Khodayari¹؛ Ahmad Yaghobnezhad²؛ Khalili Eraghi Khalili Eraghi³

¹Department of financial management Science and Research branch, Islamic Azad University, Tehran, Iran

²Department of Economic And Accounting, Islamic Azad University of Central Tehran Branch, Tehran, Iran

³Department of Economic And Management Science and Research branch, Islamic Azad University, Tehran, Iran

چکیده

In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted to improve forecasting models employing a variety of techniques. In this paper, we extend the field of expert systems, forecasting, and model by applying an Artificial Neural Network. ANN model is applied to forecast market volatility. The results show an overall improvement in forecasting using the neural network as compared to linear regression method.

کلیدواژه‌ها

Market volatility؛ Investment؛ Neural Network

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