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Author: search.filters.author.Bal, Debi PrasadSubject: search.filters.subject.COVID-19

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    Sector wise nonlinear causality between stock market volatility and COVID 19 pandemic: Evidence from India
    (Asian Economics Letters, 2021) Bal, Debi Prasad
    This paper examines the linear and nonlinear relationship between daily confirmed COVID-19 cases and sectoral stock market volatility in India. The linear Granger causality test reveals bidirectional causality. Further, we observe that bidirectional nonlinear Granger causality exists between stock market volatility and COVID-19. This implies that the historical and lagged information can have a significant role in predicting COVID-19 cases and the stock market.
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    Is Public Debt Sustainable in Indian States? An Empirical Insight
    (Springer, 2024-07) Bal, Debi Prasad
    This paper measures the public debt sustainability of twenty-eight Indian states during 2012–2013 and 2020–2021, including the first year of the COVID-19 pandemic. The study uses Domar’s stability test and panel vector autoregressive (PVAR) model in a generalized method of moments (GMM) approach by segregating the Indian states into three regions. The Domar’s stability conditions find that there is no violation throughout all the regions of India. The major findings from the PVAR result show that the response of public debt to the gross state-domestic production ratio and the gross primary deficit is negative due to the positive shock of the level of economic growth for the southeastern region. On the other hand, we observed a positive response to public debt for the northwest and northeast regions due to the shock of economic growth. Our findings suggest that while the public debt is sustainable in the southeast region, it is unsustainable in the northwest and northeast regions. The findings emphasize various steps and initiatives of state governments toward fiscal discipline for public sustainability in the long run.
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    Sectoral Nonlinear Causality Between Stock Market Volatility and the COVID-19 Pandemic: Evidence From India
    (Asian Economics Letters, 2021) Bal, Debi Prasad
    This paper examines the linear and nonlinear relationship between daily confirmed COVID-19 cases and sectoral stock market volatility in India. The linear Granger causality test reveals bidirectional causality. Further, we observe that bidirectional nonlinear Granger causality exists between stock market volatility and COVID-19. This implies that the historical and lagged information can have a significant role in predicting COVID-19 cases and the stock market.
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    Characteristics of 2020 stock market crash: The COVID-19 induced extreme event
    (AIP, 2021-04) Bal, Debi Prasad
    A sudden fall of stock prices happens during a pandemic due to the panic sell-off by the investors. Such a sell-off may continue for more than a day, leading to a significant crash in the stock price or, more specifically, an extreme event (EE). In this paper, Hilbert–Huang transformation and a structural break analysis (SBA) have been applied to identify and characterize an EE in the stock market due to the COVID-19 pandemic. The Hilbert spectrum shows a maximum energy concentration at the time of an EE, and hence, it is useful to identify such an event. The EE’s significant energy concentration is more than four times the standard deviation above the mean energy of the normal fluctuation of stock prices. A statistical significance test for the intrinsic mode functions is applied, and the test found that the signal is not noisy. The degree of nonstationarity test shows that the indices and stock prices are nonstationary. We identify the time of influence of the EE on the stock price by using SBA. Furthermore, we have identified the time scale (τ) of the shock and recovery of the stock price during the EE using the intrinsic mode function obtained from the empirical mode decomposition technique. The quality stocks with V-shape recovery during the COVID-19 pandemic have definite τ of shock and recovery, whereas the stressed stocks with L-shape recovery have no definite τ. The identification of τ of shock and recovery during an EE will help investors to differentiate between quality and stressed stocks. These studies will help investors to make appropriate investment decisions