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Comprehensive Analysis of Volatility Spillover and Investment Efficiency of Stocks of Electrical Vehicles

Author

Listed:
  • Sadhna Bagchi

    (AAFT University of Media and Arts, Raipur, Chhattisgarh)

  • Shradha Gupta

    (O.P. Jindal University, Raigarh, Chhattisgarh)

  • Debasis Mohanty

    (O.P. Jindal University, Raigarh, Chhattisgarh)

Abstract

Electric Vehicles (EVs) have garnered substantial attention and adoption. Global governmental bodies are increasingly enforcing regulations aimed at curtailing carbon emissions and fostering the uptake of EVs, thus fostering an optimistic outlook for the EV industry. This scholarly discourse endeavors to scrutinize the ramifications of stock market dynamics on the Indian EV sector. Leveraging data from the Bombay Stock Exchange (BSE), comprising 1485 observations spanning from 2017 to 2023, this investigation employs Dynamic Conditional Correlation (DCC) methodologies to explore the phenomenon of volatility spillover from the Indian stock market to the Indian EV market. Given the propensity of price fluctuations to exert influence on both demand and supply dynamics within the EV market, a discernible escalation in volatility is observed. Thus, it becomes imperative to ascertain the extent to which volatility permeates from one market segment (equity) to another (EVs). Insights gleaned from this study are poised to furnish risk-averse investors with strategic directives for diversifying their portfolios, specifically by channeling investments from the equity market to the EV sector in the short term.

Suggested Citation

  • Sadhna Bagchi & Shradha Gupta & Debasis Mohanty, 2024. "Comprehensive Analysis of Volatility Spillover and Investment Efficiency of Stocks of Electrical Vehicles," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 27(3), pages 67-80.
    • Handle: RePEc:boh:actaub:v:27:y:2024:i:3:p:67-80
    DOI: 10.32725/acta.2024.013
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    1. Zhengde Xiong & Lijun Han, 2015. "Volatility spillover effect between financial markets: evidence since the reform of the RMB exchange rate mechanism," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-12, December.
    2. Jagjeevan Kanoujiya & Shailesh Rastogi & Venkata Mrudula Bhimavarapu, 2022. "Competition and distress in banks in India: An application of panel data," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2122177-212, December.
    3. David S. Rapson & Erich Muehlegger, 2023. "The Economics of Electric Vehicles," Review of Environmental Economics and Policy, University of Chicago Press, vol. 17(2), pages 274-294.
    4. Park, Jungwook & Ratti, Ronald A., 2008. "Oil price shocks and stock markets in the U.S. and 13 European countries," Energy Economics, Elsevier, vol. 30(5), pages 2587-2608, September.
    5. Xenia Raufeisen & Linda Wulf & Sören Köcher & Ulya Faupel & Hartmut H. Holzmüller, 2019. "Spillover effects in marketing: integrating core research domains," AMS Review, Springer;Academy of Marketing Science, vol. 9(3), pages 249-267, December.
    6. Xie He & Tetsuya Takiguchi & Tadahiro Nakajima & Shigeyuki Hamori, 2020. "Spillover effects between energies, gold, and stock: the United States versus China," Energy & Environment, , vol. 31(8), pages 1416-1447, December.
    7. Anil Khurana & V. V. Ravi Kumar & Manish Sidhpuria, 2020. "A Study on the Adoption of Electric Vehicles in India: The Mediating Role of Attitude," Vision, , vol. 24(1), pages 23-34, March.
    8. Satyaban Sahoo & Sanjay Kumar, 2024. "Volatility spillover among the sectors of emerging and developed markets: a hedging perspective," Cogent Economics & Finance, Taylor & Francis Journals, vol. 12(1), pages 2316048-231, December.
    9. Shailesh Rastogi & Jagjeevan Kanoujiya & Satyendra Pratap Singh & Adesh Doifode & Neha Parashar & Pracheta Tejasmayee, 2023. "Fossil Fuel-Based versus Electric Vehicles: A Volatility Spillover Perspective Regarding the Environment," JRFM, MDPI, vol. 16(12), pages 1-16, November.
    10. Liu, Zhiqiang, 2008. "Foreign direct investment and technology spillovers: Theory and evidence," Journal of Development Economics, Elsevier, vol. 85(1-2), pages 176-193, February.
    11. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    Electrical Vehicle; BSE; DCC; Spillover effect;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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