market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …

market capitalization, the increasing volatility of the virtual currencies raise various concerns. One of the major concerns … cryptocurrencies returns. This can be attributed to the presence of asymmetric volatility clusters. This study has significant …

does not require the specification and estimation of the economic agent’s information flows or the identification and … estimation of the structural parameters and the noninvertible roots. Moreover, the proposed test statistic uses all lags in the …

outperforms the other models in model estimation and daily out-of-sample volatility forecasting of the two indices. This study is … for forecasting the volatility of both the TASI and the TIPISI in the context of petrochemical industries, as this model …

-frequency data, in line with IT developments, enables the use of more information to estimate not only the variance (volatility), but … estimation method is applied to DAX intraday prices, which balances between the bias and the variance of the realized moments … the fast-time-time scale sampling frequency is held fixed. The realized kernel density estimation enriches the literature …

market was shown to react to news unequally. Volatility spikes sharply when unexpected adverse news reaches the market while …

leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that … volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …We propose a methodology to include night volatility estimates in the day volatility modeling problem with high …