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model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility … volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for …
Persistent link: https://www.econbiz.de/10010256409
This chapter summarizes recent literature on asymptotic inference about forecasts. Both analytical and simulation based methods are discussed. The emphasis is on techniques applicable when the number of competing models is small. Techniques applicable when a large number of models is compared to...
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implications arise from the dependence of forecast performance on nuisance parameters. Depending on these nuisance parameters … distortion in inference in such models is reviewed. Finally, forecast evaluation for these problems is discussed. …
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A fast method is developed for value-at-risk and expected shortfall prediction for univariate asset return time series exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral t innovations. While the method involves the use...
Persistent link: https://www.econbiz.de/10010429763
need for macroeconomic forecasters to account for sudden and deep recessions, periods of higher macroeconomic volatility … Factor Model (MS-DFM) by incorporating two new features: switches in volatility and time-variation in trend GDP growth. First …, we show that volatility switches largely improve the detection of business cycle turning points in the low-volatility …
Persistent link: https://www.econbiz.de/10012227436
The topic of this chapter is forecasting with nonlinear models. First, a number of well-known nonlinear models are introduced and their properties discussed. These include the smooth transition regression model, the switching regression model whose univariate counterpart is called threshold...
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