Do geopolitical tensions instigate mindless following in stock markets? An empirical enquiry into the indices of CNX Nifty HFT

  • 715 Views
  • 257 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

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.

Acknowledgements
The 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.

view full abstract hide full abstract
    • Figure 1. The 5th order Hurst exponent (H) of CNX Nifty 50 on the event day June 16, 2020, i.e., (t = 0)
    • Figure 2. The 5th order Hurst exponent (H) of CNX Nifty 100 on event day June 16, 2020, i.e., (t = 0)
    • Figure 3. Hurst exponent (H) values in the event window for India-China geopolitical tensions event
    • Figure 4. The 5th order Hurst exponent (H) of CNX Nifty 50 on the event day February 26, 2019, i.e., (t = 0)
    • Figure 5. The 5th order Hurst exponent (H) of CNX Nifty 100 on the event day February 26, 2019, i.e., (t = 0)
    • Figure 6. Hurst exponent (H) values in the event window for India-Pakistan geopolitical tensions event
    • Table 1. Range of Hurst values and their respective interpretation
    • Table 2. Illustrating the results of Hurst, Fractal dimension and Entropy for CNX Nifty 50
    • Table 3. Illustrating the results of Hurst, Fractal dimension and Entropy for CNX Nifty 100
    • Table 4. Illustrating the results of Hurst, Fractal dimension and Entropy for CNX Nifty 50
    • Table 5. Illustrating the results of Hurst, Fractal dimension and Entropy for CNX Nifty 100
    • Conceptualization
      Krishna T. A.
    • Data curation
      Krishna T. A., Suresha B.
    • Formal Analysis
      Krishna T. A.
    • Investigation
      Krishna T. A., Suresha B.
    • Methodology
      Krishna T. A.
    • Software
      Krishna T. A.
    • Validation
      Krishna T. A., Suresha B.
    • Visualization
      Krishna T. A., Suresha B.
    • Writing – original draft
      Krishna T. A.
    • Writing – review & editing
      Krishna T. A., Suresha B.