Virtual digital assets including cryptocurrencies, non-fungible tokens and decentralized financial asset have been initially used as an alternative currency but are currently being purchased as an asset and hedging instruments. Exponentially growing trading volume witnesses the growing inclination of investors towards these assets, and this calls for volatility analysis of these assets. In this reference, the present study assessed and compared the volatility of returns from investment in virtual digital assets, equity and commodity market. Daily closing prices of selected cryptocurrencies, non-fungible tokens and decentralized financial assets, stock indices and commodities have been analysed for the post-covid period. Since returns were observed to be heteroscedastic, autoregressive conditional heteroscedastic models have been used to assess the volatility. The results indicate a low correlation of commodity investment with all other investment opportunities. Also, Tether and Dai have been observed to be negatively correlated with stock market. This indicates the possibility of minimizing risk through portfolio diversification. In terms of average returns, virtual digital assets are discerned to be better options than equity stock or commodity yet the variance scenario of these investment avenues is not very rosy. The volatility parameters reveal that unlike commodity market, virtual digital assets have got a significant impact of external shocks in the short-run. Further, the long run persistency of shocks is observed to be higher for the UK stock market, followed by Ethereum, Tether and Dai. The present analysis is crucial as the decision about its acceptance as legal tender money is still sub-judice in some countries. The results are expected to provide insight to regulatory bodies about these assets.
The recent demonetization announced in India led to a massive flow of deposits in banks, which called for efficient disbursement of available funds. Realizing its implication for the financial sector, researchers explored the possible impact of demonetization on the performance, profitability, and efficiency of Indian banks. However, these studies overlooked the non-performing assets, which are a serious concern for banks and have emerged as an undesirable output of the credit creation process. To fill this research gap, the present study investigates the impact of demonetization on the efficiency of domestic banks with due consideration of such undesirable assets. To get bias-free efficiency estimates, bootstrapped data envelopment analysis has been done. The study period has been divided into two sub-periods viz., pre-demonetization period and post-demonetization period. The results indicate that the efficiency of the majority of banks remains unaffected by demonetization. Only 13 banks have got a significant impact, out of which eight banks exhibited better efficiency while five banks were found to be less efficient during the post-demonetization period. However, these changes have been contributed to bank-specific factors, and demonetization cannot be accounted for the same. The findings are useful to banks, regulators, and policymakers.
Purpose This study aims to analyse whether investment in green and sustainable stocks provide some cushion during current precarious time. To compare the impact of COVID-19 on the volatility of sustainable and market-capitalisation-based stocks, daily returns from Greenex, Carbonex, Large-Cap, Mid-Cap and Small-Cap index have been analysed over a period of six years from 2015 to 2021. Design/methodology/approach At the outset, logarithmic return of all selected indices has been tested for possible unit root and heteroscedastic. On confirmation of stationarity and heteroscedasticity of data, auto-regressive conditional heteroscedastic models have been applied. Thereafter, volatility is modelled through best suitable model as suggested by Akaike and Schwarz information criterions. Findings The findings indicate the positive impact of COVID-19 on the volatility of the indices. Asymmetric power ARCH model indicates highest significant impact of COVID-19 over the volatility of Large-Cap index, whereas exponential GARCH model detected highest significant impact of COVID-19 over the volatility of Mid-Cap Index. Originality/value To the best of the authors’ knowledge, the present study is original in the sense that it aimed at comparing the possible impact of COVID-19 over sustainable and market-capitalisation-based indices.
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