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Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data

Author

Listed:
  • Bharat Kumar Meher

    (Department of Commerce, Darshan Sah College, Katihar, Under Purnea University, India)

  • Iqbal Thonse Hawaldar

    (Department of Accounting and Finance, College of Business Administration, Kingdom University, Bahrain,)

  • Mathew Thomas Gil

    (Department of Commerce, Manipal Academy of Higher Education, Karnataka, India)

  • Deebom Zorle Dum

    (Rivers State Universal Basic Education Board, Rivers State, Nigeria)

Abstract

The uprising of the pandemic COVID-19 has paralysed the whole Indian economy, and as a result the Indian stock market is severely affected too. The widely inclusive lockdown articulated on 24th March 2020 by the Prime Minister as a careful step against COVID-19, trailed by ensuing augmentations, has brought about a halt of all financial movement in the country. The objective of the study is to frame different asymmetric price volatility models for Selected Companies under Energy Sector using 1-minute closing price from 15th October 2019 to 15th May 2020 to captivate the leverage effect of the pandemic. The asymmetric terms in the selected asymmetric models are providing sufficient proof that the stock price volatility of three companies out of six under NIFTY Energy i.e., BPCL, Power grid and Indian Oil Corporation are unfavourably influenced by the pandemic. The forecasting graphs for volatility of four companies have been plotted, reveals that there is consistency in the stock price returns of all these four companies but the graph of predicted variance of Indian Oil Corporation reveals that the volatility has been fluctuating drastically with many high peak variances or fluctuations during the two days of forecasted period.

Suggested Citation

  • Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.
    • Handle: RePEc:eco:journ2:2021-06-56
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    References listed on IDEAS

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    Cited by:

    1. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Santosh Kumar & Abhishek Kumar Gupta, 2022. "Modelling Market Indices, Commodity Market Prices and Stock Prices of Energy Sector using VAR with Variance Decomposition Model," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 122-130, July.
    2. Monika Rakos & Janos Szendrak & Laszlo Erdey & Peter Miklos Komives & Veronika Fenyves, 2022. "Analysis of the Economic Situation of Energy Companies in Central and Eastern Europe," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 553-562, July.
    3. Cristi Spulbar & Ramona Birau & Iqbal Thonse Hawaldar & Jatin Trivedi & Anca Ioana Iacob (Troto), 2023. "Measuring Asymmetric Volatility Of Uk, France, And German Stock Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 134-146, February.

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    More about this item

    Keywords

    Asymmetric Volatility; EGARCH; GJR-GARCH; TGARCH; High frequency Data;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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