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This study evaluated volatility spillovers among oil price, volatility index and a pool of the credit default swaps for emerging market economies. A special role was ascribed to the time-varying interdependencies and connectedness from the perspectives of Kazakhstan, an oil exporting country. The result shows that Kazakhstan may be more resistant to the volatility, which originated from the other emerging countries. However, Kazakhstan is more sensitive to the global "fear index barometer" of volatility index and oil price volatility. The results might be appealing for portfolio diversification strategies because Kazakhstan's credit default swaps are in the low oil dependency regime.

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In this paper, we propose six Student's t based compound distributions where the scale parameter is randomized using functional forms of the half normal, Fré chet, Lomax, Burr III, inverse gamma and generalized gamma distributions. For each of the proposed distribution, we give expressions for the probability density function, cumulative distribution function, moments and characteristic function. GARCH models with innovations taken to follow the compound distributions are fitted to the data using the method of maximum likelihood. For the sample data considered, we see that all but two of the proposed distributions perform better than two popular distributions. Finally, we perform a simulation study to examine the accuracy of the best performing model.