scholarly journals Out-of-Sample Comparison of Copula Specifications in Multivariate Density Forecasts

2008 ◽  
Author(s):  
Cees G. H. Diks ◽  
Valentyn Panchenko ◽  
Dick J. C. van Dijk
Keyword(s):  
Out Of Sample ◽  
Density Forecasts ◽  
Multivariate Density

scholarly journals Out-of-sample comparison of copula specifications in multivariate density forecasts

2010 ◽  
Vol 34 (9) ◽  
pp. 1596-1609 ◽  
Author(s):  
Cees Diks ◽  
Valentyn Panchenko ◽  
Dick van Dijk
Keyword(s):  
Out Of Sample ◽  
Density Forecasts ◽  
Multivariate Density

Comparing the accuracy of multivariate density forecasts in selected regions of the copula support

2014 ◽  
Vol 48 ◽  
pp. 79-94 ◽  
Author(s):  
Cees Diks ◽  
Valentyn Panchenko ◽  
Oleg Sokolinskiy ◽  
Dick van Dijk
Keyword(s):  
Density Forecasts ◽  
Multivariate Density

scholarly journals Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts

2018 ◽  
Author(s):  
Jonas Dovern ◽  
Hans Manner
Keyword(s):  
Density Forecasts ◽  
Multivariate Density ◽  
Order Invariant

scholarly journals Oil-price density forecasts of US GDP

2016 ◽  
Vol 20 (4) ◽  
Author(s):  
Francesco Ravazzolo ◽  
Philip Rothman
Keyword(s):  
Stochastic Volatility ◽  
Great Recession ◽  
Oil Prices ◽  
Oil Price ◽  
Risk Indicator ◽  
The Great Recession ◽  
Sample Density ◽  
Density Forecasting ◽  
Out Of Sample ◽  
Density Forecasts

AbstractWe carry out a pseudo out-of-sample density forecasting study for US GDP with an autoregressive benchmark and alternatives to the benchmark that include both oil prices and stochastic volatility. The alternatives to the benchmark produce superior density forecasts. This comparative density performance appears to be driven more by stochastic volatility than by oil prices, and it primarily occurs outside of the great recession. We use our density forecasts to compute a recession risk indicator around the great recession. The alternative model with the real price of oil generates the earliest strong signal of a recession; but it surprisingly indicates reduced recession immediately after the Lehman Brothers bankruptcy. Use of the “net oil-price increase” nonlinear transformation of oil prices does lead to warnings of highly elevated risk during the Great Recession.

scholarly journals Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support

2013 ◽  
Author(s):  
Cees G. H. Diks ◽  
V. Panchenko ◽  
Dick J. C. van Dijk
Keyword(s):  
Density Forecasts ◽  
Multivariate Density

scholarly journals A Trading-Based Evaluation of Density Forecasts in a Real-Time Electricity Market

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2658 ◽  
Author(s):  
Derek W. Bunn ◽  
Angelica Gianfreda ◽  
Stefan Kermer
Keyword(s):  
Electricity Market ◽  
Mean Value ◽  
Linear Functions ◽  
Forecast Errors ◽  
Density Forecast ◽  
Out Of Sample ◽  
Density Forecasts ◽  
T Distribution ◽  
Intraday Market

This paper applies a multi-factor, stochastic latent moment model to predicting the imbalance volumes in the Austrian zone of the German/Austrian electricity market. This provides a density forecast whose shape is determined by the flexible skew-t distribution, the first three moments of which are estimated as linear functions of lagged imbalance and forecast errors for load, wind and solar production. The evaluation of this density predictor is compared to an expected value obtained from OLS regression model, using the same regressors, through an out-of-sample backtest of a flexible generator seeking to optimize its imbalance positions on the intraday market. This research contributes to forecasting methodology and imbalance prediction, and most significantly it provides a case study in the evaluation of density forecasts through decision-making performance. The main finding is that the use of the density forecasts substantially increased trading profitability and reduced risk compared to the more conventional use of mean value regressions.

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