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Are Indian sectoral indices oil shock prone? An empirical evaluation

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  • Mishra, Shekhar
  • Mishra, Sibanjan

Abstract

We present the impact of oil shocks on a disaggregate Indian stock market by using 10 sectoral indices for the period from 2010-2019. We use the novel Ready's (2018) oil shock decomposition mechanism. Using the rolling regression and dynamic conditional correlation, we ascertain the time varying properties of different oil shocks on the sectoral returns. To understand the asymmetric effect, we employ the markov switching regression. The results of the study are presented in two sets: One, we observe a structural dynamic shift in the conditional correlation between the oil shocks and sectoral returns across the study period. Also, the markov regime regression confirms that demand shocks have positive effect on all sectors in high and low volatility regime signalling the huge consumption demand in Indian industries. The supply shocks are not significant either in low or high volatility regimes indicating collapse of economic activities in such case. the demand and supply shocks have positive and negative impact on all sectoral indices, respectively. The influence of risk shocks is observed to be negative and statistically significant on all the sectoral equity indices. These results are helpful for investors in devising optimal portfolio with rational risk exposure to different sectors. They would be able to ascertain the optimal market timing for investment and orient their investment strategy towards better industry rotation. The policymakers also be able to formulate better macroeconomic strategies commensurating with the time varying effects of oil price shocks on Indian economy.

Suggested Citation

  • Mishra, Shekhar & Mishra, Sibanjan, 2021. "Are Indian sectoral indices oil shock prone? An empirical evaluation," Resources Policy, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:jrpoli:v:70:y:2021:i:c:s030142072030920x
    DOI: 10.1016/j.resourpol.2020.101889
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    More about this item

    Keywords

    Oil shocks; Sectoral indices; Demand; Supply and risk shocks; Markov switching regression;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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