Abstract
Geopolitical tensions between nations play a crucial role in triggering volatility and affecting the investors’ behavior in stock markets. This empirical work attempts to detect the traces of herding and bubble embedded in the Indian stock indices of CNX Nifty 50 and CNX Nifty 100 (both in High-Frequency Trading domains) during the latest events of geopolitical tensions escalated between India-China and India-Pakistan. An event window approach is employed to capture the impact of these events on herding behavior and information uncertainty in the considered stock indices. Multifractal Detrended Fluctuation Analysis (MFDFA) is applied to compute the Hurst value in all the trading days of the event window. The results of both indices exhibit conclusive evidence of herding and bubble formation during the overall period of geopolitical tensions between India-China and India-Pakistan. However, the degree of herding in the stock indices intensifies to a profound pattern when the tensions between India and China escalated into deadly violent clashes, and also during the heightened tensions between India and Pakistan that eventually ended up in airstrikes across the boundaries. The overall level of information uncertainty depicted by entropy is within control. The volatility in these stock indices has been confirmed to follow a unidirectional pattern. AcknowledgementsThe authors express their sincere thanks of gratitude to Dr. Bikramaditya Ghosh (Professor, Department of Finance and Analytics, RV Institute of Management, Bangalore, India) for his instrumental role in encouraging and motivating them to accomplish this research task. The authors also extend their sincere thanks to Dr. Manu K.S. (Assistant Professor, School of business and management, CHRIST (Deemed to be university), Bangalore, India) for his continued support throughout this empirical investigation.
Highlights
When there is a menace to normal associations between regions and nations, this is generally referred to as geopolitical tensions
Milos et al (2020) conductto the use of the Hurst exponent measure and its ed a comparative investigation on the detection applications to examine a variety of phenomena of multifractality in seven CEE stock markets in financial markets, this study further focuses on of the EU using the Multifractal Detrended Fluctuation Analysis (MFDFA) method
The results suggest that the geopolitical tensions escalated with China was relatively riskier to the Indian markets and its participants than those heightened tensions with Pakistan
Summary
When there is a menace to normal associations between regions and nations, this is generally referred to as geopolitical tensions. When the market volatility is unidirectional and persistent in large parts of the series, it is said to exhibit a profound pattern of the mindless following This mindless following in financial terms is referred to as herding behavior. Herding is said to occur in financial markets when investors are challenged with unpredictability, uncertainty and extreme market volatility (Naresh et al, 2019) Events such as ‘geopolitical tensions’ between nations are bounded by market volatility and accompanied by the uncertainty of all kinds. Such extreme events are said to disturb the normal market behavior as they pose a huge challenge to the investors in assessing the direction of the market volatility and making a rational investment decision. A comparative investigation of market behavior using herding during those days of geopolitical tensions by employing robust econophysics tool of ‘Hurst Exponent’ cobbled with an event window approach makes this study unique
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