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

Sadhna Bagchi et al.

Acta Universitatis Bohemiae Meridionalis2025https://doi.org/10.32725/acta.2024.013article
ABDC C
Weight
0.50

What the paper says

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.

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https://doi.org/https://doi.org/10.32725/acta.2024.013

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@article{sadhna2025,
  title        = {{Comprehensive Analysis of Volatility Spillover and Investment Efficiency of Stocks of Electrical Vehicles}},
  author       = {Sadhna Bagchi et al.},
  journal      = {Acta Universitatis Bohemiae Meridionalis},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.32725/acta.2024.013},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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