Proof that application of GARCH technique offers potential for profitability. Forecasting is an underestimated field of … forecasting methods in context of supply chains and demonstrated financial profitability from use of the GARCH technique. It … advanced forecasting tools for decision support in supply chain scenarios and provide preliminary simulation results from their …

This paper examines the forecasting performance of GARCH’s models used with agricultural commodities data. We compare … different possible sources of forecasting improvement, using various statistical distributions and models. We have chosen to … containing a genuine stock index also. The implied goal is to find out if the GARCH models are more fitted for stock indices than …

. The data covers the period of 2005-2009. To effectively forecast the volatility in the exchange rates, a GARCH model is … forecasting can be made at least for the next day given the high degree of volatility in the crisis period. The paper also reveals …

econometric problem of volatility forecasting for a portfolio of a number of selected returns. The discussion complicates given … difficult. As a solution to such problems, I have justified the superiority of one autoregressive heteroskedastic model (PC-GARCH …M) in order to evidentiate advantages of this model. They may be summarized as it follows: PC-GARCH • Minimizes …

This article examines the volatility forecasting abilities of three approaches: GARCH-type model that uses carbon … document that GARCH-type models perform better than an implied volatility and the k-nearest neighbor model. This result …

-Switching Autoregressive (MSAR) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors in each regime to cope with … including a GARCH specification for density forecasts. …