Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 7, Issue 2


Published
on

July 15, 2022


Pages

1861-1870


DOI

Article

A Study on the Application of Quantile Regression Equation in Forecasting Financial Value at Risk in Financial Markets


Authors

Lin Chen Affiliation:
Department of Economic Management, Science and Technology College Gannan Normal University, Ganzhou, China
and Ibrahim Hatamleh Affiliation:
College of Administrative Sciences, Applied Science University, Bahrain


Abstract

With the development of the times and the progress of science and technology, the financial market is constantly reformed and China’s financial industry is gradually modernized. However, China’s economy has been in the stage of rough growth for a long time, which has led to low efficiency in the allocation of financial resources and unreasonable use of funds, and this has seriously restricted the whole social production activities and the stability and sustainable and healthy development of the national economy, so the prevention and control of financial risks is particularly important.Therefore, how to identify and measure the risks in China’s financial industry and manage and invest them in a reasonable way is a very serious issue facing China’s financial institutions today. On the other hand, due to the continuous development and innovation of the financial market, China’s financial industry has been gradually reformed. However, due to the imperfection of China’s economic system and related laws and regulations, some non-performing assets and irregularities in the operation of domestic financial institutions have emerged, and instability in the financial market has also emerged. These phenomena make China’s financial industry face huge financial risks in the process of development.


Keywords

Quantile regression equation, Financial market risk, Financial value forecasting, 15B99


Citation

Chen, L. & Hatamleh, I. (2022). A study on the application of quantile regression equation in forecasting financial value at risk in financial markets. Applied Mathematics and Nonlinear Sciences, 7(2), 1861–1870. https://doi.org/10.2478/amns.2022.2.0174

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