It has been established in the literature that volatility of stock returns exhibits complex properties of not only … volatility clustering, but also long memory, regime change, and substantial outliers during turbulent and calm periods. Hence …, this paper seeks to analyze volatility spillover, co-movements, independence and contagion in the Chinese, Japanese …

-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively … intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock … performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts and …

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility … clustering and asymmetry characterize the logarithmic realized volatility of both indices. ARFIMAX model with time … superior next trading day's realized volatility forecasts …

Predicting the one-step-ahead volatility is of great importance in measuring and managing investment risk more … accurately. Taking into consideration the main characteristics of the conditional volatility of asset returns, I estimate an … leptokurtic conditional distribution of innovations, produces the most accurate one-day-ahead volatility forecasts. The study …

such as the realized volatility and squared overnight returns, are confronted with those from ARFIMA realized volatility …

decades in the mean and volatility dynamics, including the underlying volatility persistence and volatility spillovers … existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and …

We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and … for modeling the ISE-100 return volatility. The t-distribution seems to characterize the distribution of the heavy tailed … model to the historical ISE-100 return data indicates that the return volatility reacts to bad news 24% more than they react …

dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …