Is the U.S. energy independence and Security Act of 2022 associated with stock market volatility?

This study investigates the influence of the U.S. Energy Independence and Security Act (EISA) of 2022 on stock market volatility. Considering potential policy impacts on market dynamics, it employs a mean-reverting jump-diffusion model for volatility analysis, supported by rigorous hypothesis testing to validate empirical findings. For investor sentiment analysis, a pre-trained model (BERT-base-multilingual-uncased) is used to assess sentiment, with logistic regression and Bidirectional LSTM utilized for sentiment prediction. Contrary to conventional findings, logistic regression outperforms Bidirectional LSTM for the small dataset. Overall, the study estimates show no statistically noteworthy difference in volatility before and after implementing the EISA of 2022. This study provides valuable insights for navigating financial decisions within the intricate landscape of energy markets.

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Institutions

Publication Details

Journal
Utilities Policy
Published
2024-08-16
DOI
https://doi.org/10.1016/j.jup.2024.101813
Citations
5
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
5.65

Funders

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article

Is the U.S. energy independence and Security Act of 2022 associated with stock market volatility?

Parthajit Kayal, Moinak Maiti, Hiridik Rajendran
5 citations
Utilities Policy
Market Dynamics and Volatility
5.65
article

Is the U.S. energy independence and Security Act of 2022 associated with stock market volatility?

Parthajit Kayal, Moinak Maiti, Hiridik Rajendran
article en
5 citations

Abstract

This study investigates the influence of the U.S. Energy Independence and Security Act (EISA) of 2022 on stock market volatility. Considering potential policy impacts on market dynamics, it employs a mean-reverting jump-diffusion model for volatility analysis, supported by rigorous hypothesis testing to validate empirical findings. For investor sentiment analysis, a pre-trained model (BERT-base-multilingual-uncased) is used to assess sentiment, with logistic regression and Bidirectional LSTM utilized for sentiment prediction. Contrary to conventional findings, logistic regression outperforms Bidirectional LSTM for the small dataset. Overall, the study estimates show no statistically noteworthy difference in volatility before and after implementing the EISA of 2022. This study provides valuable insights for navigating financial decisions within the intricate landscape of energy markets.

Utilities PolicyVol. 90
University of the Witwatersrand (ZA)
University of the Witwatersrand, Johannesburg
Openalex Percentile: Top 4%
Market Dynamics and Volatility
5.65
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