منابع مشابه
Comparing Univariate and Multivariate Models to Forecast Portfolio Value
Value-at-Risk has become one of the most widely-used financial risk measurement techniques. In this paper, we compare multivariate and univariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models in terms of their respective performance in forecasting portfolio Value-at-Risk (VAR). First, we review a few common VaR models both in a univariate and a multivariate setting. T...
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We explain that revisions to successive density forecasts of the same outcome, as measured by the Kullback-Leibler Information Criterion, need not be unpredictable, unlike those to conditional mean forecasts, even when the forecaster uses information efficiently. However one can still test the efficiency of fixed-event conditional density forecasts, similarly to conditional mean forecasts, by t...
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Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is try...
متن کاملDensity Forecast Combination
In this paper we investigate whether and how far density forecasts sensibly can be combined to produce a “better” pooled density forecast. In so doing we bring together two important but hitherto largely unrelated areas of the forecasting literature in economics, density forecasting and forecast combination. We provide simple Bayesian methods of pooling information across alternative density fo...
متن کاملKp forecast models
[1] Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Langrangian point (L1) and nowcast Kps, Kp forecast models based on neural networks were developed with the focus on improving the forecast for active times. To ...
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ژورنال
عنوان ژورنال: Journal of Forecasting
سال: 2007
ISSN: 0277-6693,1099-131X
DOI: 10.1002/for.1023