The environmental literature lacks the use of volatility based models for environmental stochastic processes. To overcome this deficiency, we use EGARCH, IGARCH, TGARCH, GJR-GARCH, NGARCH, AVGARCH and APARCH models for functional relationships of the pathogen indicators time series for recreational activates at beaches. We use generalized error, Student’s t, exponential, normal and normal inver...

In this paper we estimate the skewness of unconditional distribution energy returns and test its statistical significance. We compare performance traditional robust tests for with those based on implied in a TGARCH model Gram-Charlier (TGARCH-GC) innovations. also analyze implications TGARCH-GC tail risk through evaluation Value-at-Risk (VaR) expected shortfall (ES) accuracy. Our results show t...

Smart grid is the main development goal of future power grid while the short-term load forecasting is the significant premise of making management, power supply and trading plan in market circumstance. The forecasting accuracy directly determined the safety and economy of electric system. Support Vector Machines (SVM), as the new machine learning method, has applied successfully to short-termed...

The Chinese stock market has been established for more than 20 years. Although it is not as mature as the highly developed western securities markets, it has a huge influence on the global economy. It is significant to study the risks of the Chinese stock market, especially the risk of stock indexes. Affected by the economic globalization today, more and more financial derivatives and financial...

Methods: Using daily exchange rates for 7 years (January 1, 2008, to April 30, 2015), this study attempted to model dynamics following generalized autoregressive conditional heteroscedastic (GARCH), asymmetric power ARCH (APARCH), exponential generalized autoregressive conditional heteroscedstic (EGARCH), threshold generalized autoregressive conditional heteroscedstic (TGARCH), and integrated g...