Volatility clustering and asymmetry are considered as an essential element in time series data analysis for portfolio … managers. This study is conducted to analyze the volatility clustering and asymmetry occurrence by employing different GARCH … findings of the study show that volatility clustering increases the asymmetric comportment of daily stock market returns. We …

First Version: 03/11/2015This Version: 04/01/2016We expand the literature of volatility and Value-at-Risk forecasting … of oil price returns by comparing the recently proposed Mixture Memory GARCH (MMGARCH) model to other discrete volatility … MMGARCH and find regimes that differ in volatility level as well as shock persistence. Furthermore, we observe dissimilar …

This paper examines the impact of MIB30 Index Futures on the volatility of the Italian Stock Exchange. The results … suggest that the onset of futures trading may have led to diminished daily volatility. They also suggest that the nature of … the volatility itself has not changed between the pre-futures and post-futures periods although a lower volatility is …

and low prices which may be an important tool for short term traders and incorporated in volatility estimation, Also, the …

The generalized autoregressive conditional heteroscedastic model (GARCH) is used to estimate volatility for Nifty Index … futures on day trades. The purpose is to find out if a contemporaneous or causal relation exists between volatility volume and … according to this study establishes that volume has a stronger impact on volatility compared to open interest. Furthermore, the …

diffusive volatility and squared jump variation. We use this result to develop a new option valuation model in which the … underlying asset price exhibits volatility and jump intensity dynamics. The volatility and jump intensity dynamics in the model … are directly driven by model-free empirical measures of diffusive volatility and jump variation. Because the empirical …