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To focus on new and emerging areas of research and education, Centres of Excellence have been established within the Institute. These ‘virtual' centres draw on resources from its stakeholders, and interact with them to enhance core competencies

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Faculty members at IIMB generate knowledge through cutting-edge research in all functional areas of management that would benefit public and private sector companies, and government and society in general.

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IIMB Management Review

Journal of Indian Institute of Management Bangalore

IIM Bangalore offers Degree-Granting Programmes, a Diploma Programme, Certificate Programmes and Executive Education Programmes and specialised courses in areas such as entrepreneurship and public policy.

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About IIMB

The Indian Institute of Management Bangalore (IIMB) believes in building leaders through holistic, transformative and innovative education

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PANDEMICS AND CRYPTOCOINS

The hedge and safe haven advantage of cryptocoins during the periods clouded by uncertainties has been keenly contested in the literature. However, most of the extant studies that either validated or contradicted the hedge or safe haven potential do not adequately capture the vulnerability, or otherwise, of cryptocoins to uncertainties due to pandemics. This study examines the effect of pandemic-induced uncertainty on three top- traded cryptocoins (Bitcoin, Ethereum and Ripple) over the period  August 7, 2015 to June 27, 2020. The study differs from extant studies in terms of the measure of uncertainties associated with pandemics and the choice of methodology. First, it utilises two new datasets on uncertainty due to pandemics: Equity Market Volatility in Infectious Disease Index (EMV-IDI) developed by Baker, Bloom, Davis, and Terry (2020), which captures all the pandemics including COVID-19; and Global Fear Index (GFI) by Salisu and Akanni (2020), which is a complementary dataset on COVID-19 that has been developed using a different approach. Second, it employs the Westerlund and Narayan (2012, 2015) predictive model, which simultaneously incorporates salient data features (persistence, endogeneity, and conditional heteroscedasticity) within a single model framework, to examine the predictability of pandemic-induced uncertainty for returns on cryptocoins and assesses our predictive model’s forecast performance in comparison with a benchmark historical average model, under the full sample, pre-COVID-19, and post-COVID-19 periods. A rolling window estimation is adopted to account for time-dependent parameters due to structural shifts. We also examine the role of asymmetry in the uncertainty index, and the sensitivity of our results to pandemic-induced uncertainty proxies. Cryptocoins act as a hedge against uncertainty due to pandemics, albeit with reduced hedging effectiveness in the COVID-19 period. Accounting for asymmetry improves predictability and model forecast performance. Our results may be sensitive to the choice of measure of pandemic-induced uncertainty.