This paper examines two asymmetric stochastic volatility models used to describe the heavy tails and volatility dependencies found in most financial returns. The first is the autoregressive stochastic volatility model with Student’s t-distribution (ARSV-t), and the second is the multifactor stochastic volatility (MFSV) model. In order to estimate these models, the analysis employs the Monte Car...

It is well-established that the …nancial time series display some stylized fatcs such as volatility clustering, high kurtosis, low starting and slow-decaying autocorrelation function and the Talyor e¤ect as well. In order to evaluate volatility models’capacity in capturing such facts, we apply both standard and robust measures of kurtosis and autocorrelation of squares to GARCH, EGARCH and ARSV...

air quality is a topic of crucial importance, because air pollution is one of the most important pollution problems in the world. in particular, predicting or detecting a future extreme air pollution episode or predicting the violation of an air quality standard, is of crucial interest in the field of pollution control. there have been a variety of attempts to reach this purpose both from the p...

For constant monitoring of rotor slot in induction motor, average variation (ARSV) prediction is proposed. The slots expand due to thermal stress and high intensity magnetic flux. flux with created lamination sheet, because stretching curving surface exhibits over current which turn generates heat transfers the into surface. stress-based size never monitored or measured before. In proposed ARSV...

Objectives: The motion of structures the heart is basis for cardiac function. Factors such as low image quality and signal-to-noise ratio create hindrances in adequate valuation left ventricular (LV) systolic diastolic Even cases with poor quality, aorta being a large structure well visualized. One unorthodox approaches to assessment function study aortic root movement. Materials Methods: We st...