Do Trading Volume and Downside Trading Volume Help Forecast the Downside Risk?
Zhifang He 1, Chuangxia Huang 2 3 * , Xu Gong 4, Xiaoguang Yang 3, Fenghua Wen 5
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1 School of Business, Jiangnan University, Wuxi, CHINA2 School of Economics and management, Changsha University of Science and Technology, Changsha, CHINA3 Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, CHINA4 School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Xiamen, CHINA5 School of Business, Central South University, Changsha, CHINA* Corresponding Author

This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".

Abstract

This paper uses the downside realized semi variance to measure the downside risk and then the HAR-DR, HAR-DR-V and HAR-DR-DV models on the basis of the HAR-RV model are built. Finally, by comparing the three models’ prediction ability for downside risk in the stock spot market and futures market, we test whether the trading volume and downside trading volume of the two markets can be used to predict the downside risk. And we also study the differences under different samples and different models. The results indicate that trading volume and downside trading volume have different prediction effects for the downside risk in different periods. The trading volume and downside trading volume exhibit much forecasting power in the futures market. However, they show little forecasting power in the spot market.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2017, Volume 13, Issue 12, 8367-8382

https://doi.org/10.12973/ejmste/78634

Publication date: 25 Nov 2017

Article Views: 2292

Article Downloads: 820

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