Role of the Global Volatility Indices in Predicting the Volatility Index of the Indian Economy

被引:1
|
作者
Prasad, Akhilesh [1 ]
Bakhshi, Priti [2 ]
机构
[1] Krea Univ, IFMR Grad Sch Business, Sri City 517646, India
[2] SP Jain Sch Global Management, Mumbai 400070, India
关键词
VIX; machine learning; feature importance; stock market risk; fear index; STOCK-MARKET; CLASSIFICATION; PERFORMANCE; OPTIONS; VIX;
D O I
10.3390/risks10120223
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Movements in the volatility index of the Indian economy are influenced by global volatility indices (fear index). This study evaluates the influence of various global implied volatility indices in forecasting the day-to-day binary movements in the implied volatility index of India, denoted by the symbol 'India VIX'. Historical daily data from 18 September, 2009, to 2 December, 2021, was acquired, and the target labels were created from changes in the India VIX. A set of classifiers, consisting of Logistic Regression, Random Forest and Extreme Gradient Boosting (XG Boost), were applied to rank the feature variables according to their importance. This study revealed that India's VIX was impacted most by the previous day's changes in the closing value of the US implied volatility indices, except for the Chicago Board Options Exchange (CBOE) Eurocurrency volatility index. Additionally, the Eurozone implied volatility index was also important. However, the implied volatility indices of Australian Hang Seng and Japan were the least important. This study's outcomes help Indian traders in creating a watch list of important volatility indices.
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页数:18
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