Jan'20
Focus
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Article | Price (₹) | ||
Volatility Dynamics of Cryptocurrencies' Returns: An Econometric Study |
100
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Measuring Financial Risk Tolerance: The Role of Socio-Demographic Factors Under the Influence of Attitude Towards Money |
100
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Fiscal Legislation, Debt Management and Social Spending: A State-Level Analysis in India |
100
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Volatility Dynamics of Cryptocurrencies' Returns: An Econometric Study
The dicey regulatory environment surrounding the cryptocurrency sector has raised the concern of investors and potential investors to study the volatility dynamics of cryptocurrencies' returns in the present scenario. The present treatise is an attempt to study the volatility dynamics of most traded cryptocurrencies, viz., Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin, Stellar, Tether and XRP. The daily closing prices for the period of July 2017 to March 2019 were considered. The data of cryptocurrencies was initially studied for stationarity with the help of Ng-Perron test and Augmented Dickey-Fuller (ADF) test. The data was further studied for ARCH effect with the help of Ljung-Box Q-test and Engle's ARCH test. The results confirmed that all cryptocurrencies' return series are stationary and ARCH effect is present in all series. GARCH family models (GARCH, EGARCH, TARCH and PARCH) were applied to study the volatility dynamics. The results confirm the presence of highly persistent volatility and asymmetry in Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin, Stellar, Tether and XRP return series. The diagnostic checking as per Akaike Information Criterion, Schwarz Information Criterion and Hannan-Quinn Information Criterion confirmed that PARCH model is the best fitted model for these series, except EOS. EGARCH is the best fitted model for EOS. These findings may help in reducing the investors' dilemma with regard to taking investment decision in the cryptocurrency sector.
Measuring Financial Risk Tolerance: The Role of Socio-Demographic Factors Under the Influence of Attitude Towards Money
In this paper, a conceptual model of individual's financial risk tolerance is described. The study, among the first, has incorporated 'attitude towards money' as an interacting variable in predicting the relationship between socio-demographic factors and financial risk tolerance. Using a sample of 219 individual investors, it was determined that the interaction effects significantly predicted the relationship between socio-demographic influences and financial risk tolerance, thereby expanding a new perspective to the literature.
Fiscal Legislation, Debt Management and Social Spending: A State-Level Analysis in India
The implementation of Fiscal Responsibility and Budgetary Management (FRBM) Act led to a conflicting trade-off between fiscal discipline and social sector spending. The scenario was expected to be even worse at the state level, given the imbalance between responsibilities and revenue of the states. This led to a legitimate intellectual apprehension fearing that the states may resort to a deliberate slashing of vital capital and social sector expenditures to maintain fiscal equation. The current study is an addition to the literature along the same line wherein we have tried to highlight the effects of fiscal rule on the fiscal discipline and thereby on social spending in Indian states. A majority of the states were found to have experienced more fiscal impotence in the post-reform period, especially post global melting down of 2008. On average, the states exhibited a conflicting scenario between social spending and fiscal potency, though with some variability between general and special category states. Further, the states are found to rely on deficit financing for their social sector spending mainly. The broad conclusion emerged thereupon was that states in the Indian federation, to maintain their fiscal commitment as mandated by FRBM, have resorted to slashing of social sector spending.