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Information Journal Paper

Title

Comparison of the Forecasting of Financial Markets Volatility Using the Regression Model and Neural Network Model

Pages

  223-240

Abstract

 Volatility as an effective factor in determining Investment risk can play an important role in decision making of investors. An appropriate estimate of Market Volatility in an Investment period is an important starting point in Investment risk control. Volatility plays a key role in financial markets, so it needs to be recognized and calculated, and plans to manage Market Volatility that affect investors ' decision. Due to the importance of Market Volatility, the main objective of this research is to compare two methods before Market Volatility. The results of this research show that the combination of artificial Neural Network and financial ratios are capable to predict the volatility of capital Market Volatility and according to the total error of the model presented using Neural Network in this research has better performance in the forecasting of capital Market Volatility than linear regression.

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    APA: Copy

    Khodayari, Mohammad Azim, YaghobNejad, Ahmad, & KHALILI ARAGHI, MARYAM. (2020). Comparison of the Forecasting of Financial Markets Volatility Using the Regression Model and Neural Network Model. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), 14(52 ), 223-240. SID. https://sid.ir/paper/369799/en

    Vancouver: Copy

    Khodayari Mohammad Azim, YaghobNejad Ahmad, KHALILI ARAGHI MARYAM. Comparison of the Forecasting of Financial Markets Volatility Using the Regression Model and Neural Network Model. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT)[Internet]. 2020;14(52 ):223-240. Available from: https://sid.ir/paper/369799/en

    IEEE: Copy

    Mohammad Azim Khodayari, Ahmad YaghobNejad, and MARYAM KHALILI ARAGHI, “Comparison of the Forecasting of Financial Markets Volatility Using the Regression Model and Neural Network Model,” JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), vol. 14, no. 52 , pp. 223–240, 2020, [Online]. Available: https://sid.ir/paper/369799/en

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