文章基本信息

标题：A Neural-Network Approach to the Modeling of the Impact of Market Volatility on Investment
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作者：Mohammad Azim Khodayari ; Ahmad Yaghobnezhad ; Khalili Eraghi Khalili Eraghi 等
期刊名称：Advances in Mathematical Finance and Applications
印刷版ISSN：2538-5569
电子版ISSN：2645-4610
出版年度：2020
卷号：5
期号：4
页码：1-16
DOI：10.22034/amfa.2020.674953
语种：English
出版社：Islamic Azad University of Arak
摘要：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.