financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms …

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …

financial index price forecasting. …

The topic of this chapter is forecasting with nonlinear models. First, a number of well-known nonlinear models are … linear model. There exist relatively large studies in which the forecasting performance of nonlinear models is compared with …

explain risk premium. Investigating whether these factors are useful in forecasting stock returns remains active research in …

This paper analyses inflation forecasting power of artificial neural networks with alternative univariate time series … models for Turkey. The forecasting accuracy of the models is compared in terms of both static and dynamic forecasts for the …, provide better one-step ahead forecasting performance. However, unobserved components model turns out to be the best performer …

returns plays an important role for volatility forecasting. Additionally, models utilizing a logarithmic transformation of the … an easy-to-use and accurate tool for realized variance forecasting, whose performance may potentially be further improved …