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The dynamics of macroeconomic variables in Indian stock market: a Bai–Perron approach

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  • Narayan Parab
  • Y. V. Reddy

Abstract

The stock market is dynamic, so also the economic conditions. Structural breaks are unexpected shifts which occur in a time-series data which may deteriorate the results. The study deals this situation using the Bai–Perron test and examines the impact of select macroeconomic variables on stock market returns and thereafter investigates the causal relations. The study evidenced a significant impact of macroeconomic variables on stock market returns, and such impact was found to be varying across structural periods. The results are aimed to contribute significantly to finance literature and assist market participants and research analysts in evaluating Indian stock market.

Suggested Citation

  • Narayan Parab & Y. V. Reddy, 2020. "The dynamics of macroeconomic variables in Indian stock market: a Bai–Perron approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 13(1), pages 89-113, January.
  • Handle: RePEc:taf:macfem:v:13:y:2020:i:1:p:89-113
    DOI: 10.1080/17520843.2019.1641533
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    Cited by:

    1. Mengrui Zhu & Hua Xu & Xingyu Gao & Minggang Wang & André L. M. Vilela & Lixin Tian, 2022. "Identification of Breakpoints in Carbon Market Based on Probability Density Recurrence Network," Energies, MDPI, vol. 15(15), pages 1-18, July.
    2. Prem Vaswani & Padmaja M, 2023. "Asymmetric relationship between macroeconomic uncertainty and stock market performance: a study of the Indian stock market," Economics Bulletin, AccessEcon, vol. 43(4), pages 1887-1895.
    3. Bouzgarrou, Houssam & Ftiti, Zied & Louhichi, Waël & Yousfi, Mohamed, 2023. "What can we learn about the market reaction to macroeconomic surprise? Evidence from the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Muhammad Kamran Khan & Jian‐Zhou Teng & Muhammad Imran Khan & Muhammad Fayaz Khan, 2023. "Stock market reaction to macroeconomic variables: An assessment with dynamic autoregressive distributed lag simulations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2436-2448, July.

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