forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

We examined volatility spillover effects from five prominent global stock markets to India's stock market during the … and compare the results pre-and-post COVID-19. Results show that previous period news and volatility feeds the next period …'s volatility significantly and the volatility is found to be persistent. The analysis also shows that during the pre-COVID period …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

The volatility clustering observed in financial market data implies that large net yield shocks increase the … probability of a higher future volatility during the price formation. Starting from the ARCH models which were suggested by Engle …