Forecasting the direction of daily changes in the India VIX index using deep learning

被引:0
|
作者
Prasad, Akhilesh [1 ]
Bakhshi, Priti [2 ]
Guha, Debashis [2 ]
机构
[1] Krea Univ, IFMR Grad Sch Business, Sri City, Andhra Prades, India
[2] SP Jain Sch Global Management, Mumbai, Maharashtra, India
关键词
Volatility; VIX; LSTM; GRU; RNN; CNN; Conv1D; STOCK; EQUILIBRIUM;
D O I
10.1016/j.iimb.2023.05.002
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The VIX index is an indicator of the market's perception of risk, and an accurate fore-cast of the movements in VIX can be very useful for investment risk management. So, the aim of this study is to predict the day-to-day movement of the India VIX using six deep learning archi-tectures. All six architectures performed well and achieved a higher level of accuracy with minor differences than in previous studies. The findings of the study are of great relevance for assessing short-term risk as well as long-term strategies for hedgers, risk-averse investors, volatility trad-ers, investors, and financial researchers.& COPY; 2023 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/)
引用
收藏
页码:149 / 163
页数:15
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