A general approach for modeling the volatility process in continuous-time is based on the convolution of a kernel with a non-decreasing Lévy process, which is non-negative if the kernel is non-negative. Within the framework of Continuous-time Auto-Regressive Moving-Average (CARMA) processes, we derive a necessary condition for the kernel to be non-negative, and propose a numerical method for ch...

Recently, there are much works on developing models suitable for analyzing the volatility of a discrete-time process. Within the framework of Auto-Regressive Moving-Average (ARMA) processes, we derive a necessary and sufficient condition for the kernel to be non-negative. This condition is in terms of the generating function of the ARMA kernel which has a simple form. We discuss some useful con...

This paper anticipates trends in the digital economy during a COVID-19 epidemic worldwide. The United States and China are considered world’s largest economies have attempted to transition fully over last few years. Therefore, this used auto-regressive integrated moving average (ARIMA) model gross domestic product (GDP) for USA period 1960-2019. As we arrive at peak of pandemic, one most squeez...

In the prognosis of radar transmitter degradation malfunction, there are some restrictions, such as fact that it is difficult to obtain fault samples and monitoring data cannot reach threshold. For these a novel data-driven prognostic method proposed predict in which dynamic updated-auto-regressive integrated moving average be used subsequent time-step microwave measurement historical data, mul...

The massive spread of COVID-19 has disrupted trading activities worldwide plunging the economy a nation; particularly, trade-dependent nations are severely affected by restriction in exports and imports. This paper aims to evaluate implications on trade New Zealand exploratory data analysis ARIMA modeling. Based comprehensive strategy prediction, were processed notice impact pandemic sales. (Au...

In this paper, modeling of doubly fed induction generator (DFIG) based wind energy conversion system (WECS) and speed controller are presented. The System Identification Toolbox MatLab is used to develop the linear model WECS by considering as input output. Two models, namely Auto Regressive with eXogenous Input (ARX) Auto-Regressive Moving Average (ARMAX), estimated. We ARX221 structure best f...

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...