The purpose of this study is to investigate the impacts calendar anomalies specifically on day week effect (DOW) 10 Islamic stock markets’ returns such as Dow Jones Market (DJIM), Saudi Arabia, Malaysia, United Arab Emirates (UAE), Kuwait, Qatar, Turkey, Indonesia, Bahrain, Pakistan—for 20 years from 25 September 2000 24 2020. methods using Generalized AutoRegressive Conditional Heteroskedastic...

E evidence on the distributional characteristics of common stock returns indicates: (1) A powerlaw tail index close to three describes the behavior of the positive tail of the survivor function of returns (pr r > x ∼ x− a reflection of fat tails; (2) general linear and nonlinear dependencies exist in the time series of returns; (3) the time-series return process is characterized by short-run de...

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previous...

This study explores the fractionally integrated (FI) time series analysis in Malaysian stock market. Four proxies of latent volatility, namely the absolute return, squared return and range-based (Parkinson and Garman and Klass) volatilities are selected for the empirical studies. In addition, the well-known FI autoregressive conditional variance (ARCH) type model is also taken into account for ...

The scientific community still struggles to understand the magnitude of worldwide infections and deaths induced by COVID-19, partly ignoring financial consequences. In this paper, using autoregressive fractionally integrated moving average (ARFIMA)—general conditional heteroskedasticity (GARCH) model, we quantify show impact COVID-19 spread in Italy, utilizing data for stock market. Using infor...

98. Nelson DB (1990) Stationarity and persistence in the GARCH(1,1) model. Econom Theory 6:318–334 99. Nelson DB (1991) Conditional heteroskedasticity in asset returns: A new approach. Econometrica 59:347–370 100. Nelson DB, Cao CQ (1992) Inequality constraints in the univariate garchmodel. J Bus Econ Stat 10:229–235 101. Newey WK, Steigerwald DS (1997) Asymptotic bias for quasi maximum likelih...

In this paper we put forward a new method to estimate value at risk (VaR), autoregressive conditional heteroskedastic (ARCH) factor, which combines multivariate analysis with ARCH models. Firstly, from a set of correlated portfolio risk factors, we derive a smaller uncorrelated risk factors set, by applying multivariate analysis. Secondly, we use ARCH schemes to model uncorrelated factors histo...