This rapid propagation of the Novel Coronavirus Disease (COVID-19) has caused global healthcare system to break down. The infectious disease originated from East Asia and spread world. unprecedented pandemic further damages economy. It seems highly probable that COVID-19 recession changes stock market volatility. Therefore, this study resorts Generalized Autoregressive Conditional Heteroscedast...

Tourism forecasting has garnered considerable interest. However, integrating tourism with volatility is significantly less typical. This study investigates the performance of both single models and their combinations for demand. The seasonal autoregressive integrated moving average (SARIMA) model used to construct mean equation, three models, namely generalized conditional heteroscedasticity (G...

Background: The study aimed to evaluate the interval between first drug use and regular injection and factors associated with transition from first injection into premature regular injection among people who inject drugs (PWIDs).Methods: In a multicenter cross-sectional study, we recruited 400 PWIDs using snowball sampling. Age of first drug use, age of initiation of regular injection, and demo...

High-dimensional time series data exist in numerous areas such as finance, genomics, healthcare, and neuroscience. An unavoidable aspect of all such datasets is missing data, and dealing with this issue has been an important focus in statistics, control, and machine learning. In this work, we consider a high-dimensional estimation problem where a dynamical system, governed by a stable vector au...

The American lumber market has gone through various demand and supply shocks for 40 years, and has been particularly shaped by harvesting restrictions in the Pacific Northwest. Linkage of lumber markets has considerably changed since then, with the most observable alteration in price fluctuation. In this study, the degree of spatial price linkage between the South and Pacific Northwest markets ...

This paper develops a smooth transition GARCH model with an asymmetric transition function, which allows for an asymmetric response of volatility to the size and sign of shocks, and an asymmetric transition dynamics for positive and negative shocks. We apply our model to the empirical financial data: the NASDAQ index and the individual stock IBM daily returns. The empirical evidence shows that ...

This paper discusses methods for reducing the bias of consistent estimators that are biased in nite samples. These methods are available whenever the bias function, which relates the bias of the parameter estimates to the values of the parameters, can be estimated by computer simulation or by some other method. If so, bias can be reduced by one full order in the sample size and, in some cases t...

A challenge for the efficient operation of power systems and wind farms is the occurrence of wind power ramps, which are sudden large changes in the power output from a wind farm. This paper considers the probabilistic forecasting of a ramp event, defined as exceedance beyond a specified threshold. We directly model the exceedance probability using autoregressive logit models fitted to the chan...

In this study, we investigate the validity of purchasing power parity (PPP) proposition for 34 European and selected global countries. For purpose, propose a new unit root test cross-sectionally dependent heterogeneous panels that allows gradual structural breaks symmetric nonlinear adjustment toward equilibrium level. The alternative hypothesis stationary is obtained by due to exponential smoo...

We consider time series described by Markov chains that alternate periodically between different transition distributions, with conditional constraints involving unknown parameters. We obtain variance bounds and characterize efficient estimators for these parameters. Efficient estimators can be obtained as solutions of randomly weighted martingale estimating equations. Our model includes altern...