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~isPartOf:"Applied economics"
~isPartOf:"Computational economics"
~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"International journal of forecasting"
~isPartOf:"Tinbergen Institute Discussion Paper"
~person:"Allen, David E."
~person:"Burns, Kelly"
~person:"Chen, Yi-Ting"
~person:"Gooijer, Jan G. de"
~person:"Rubaszek, Michał"
~subject:"Estimation"
~subject:"Nationaleinkommen"
~subject:"Prognoseverfahren"
~subject:"VAR-Modell"
~subject:"World"
~subject:"Zeitreihenanalyse"
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Allen, David E.
Burns, Kelly
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Gooijer, Jan G. de
Rubaszek, Michał
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13
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1
Realized Volatility Risk
Allen, David E.
;
McAleer, Michael
;
Scharth, Marcel
-
2013
of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which
forecasting
…
Persistent link: https://www.econbiz.de/10010326350
Saved in:
2
Forecasting
crude oil prices with DSGE models
Rubaszek, Michał
- In:
International journal of forecasting
37
(
2021
)
2
,
pp. 531-546
Persistent link: https://www.econbiz.de/10012792850
Saved in:
3
Machine learning with parallel neural networks for analyzing and
forecasting
electricity demand
Chen, Yi-Ting
;
Sun, Edward W.
;
Lin, Yi-Bing
- In:
Computational economics
56
(
2020
)
2
,
pp. 569-597
Persistent link: https://www.econbiz.de/10012272048
Saved in:
4
Does the foreign sector help forecast domestic variables in DSGE models?
Kolasa, Marcin
;
Rubaszek, Michał
- In:
International journal of forecasting
34
(
2018
)
4
,
pp. 809-821
Persistent link: https://www.econbiz.de/10012031114
Saved in:
5
Semiparametric quantile averaging in the presence of high-dimensional predictors
Gooijer, Jan G. de
;
Zerom Godefay, Dawit
- In:
International journal of forecasting
35
(
2019
)
3
,
pp. 891-909
Persistent link: https://www.econbiz.de/10012305189
Saved in:
6
Demystifying the Meese-Rogoff puzzle : structural breaks or measures of
forecasting
accuracy?
Burns, Kelly
;
Moosa, Imad A.
- In:
Applied economics
49
(
2017
)
48
,
pp. 4897-4910
Persistent link: https://www.econbiz.de/10011844813
Saved in:
7
The random walk as a
forecasting
benchmark : drift or no drift?
Moosa, Imad A.
;
Burns, Kelly
- In:
Applied economics
48
(
2016
)
43/45
,
pp. 4131-4142
Persistent link: https://www.econbiz.de/10011639995
Saved in:
8
Jump detection and noise separation by a singular wavelet method for predictive analytics of high-frequency data
Chen, Yi-Ting
;
Lai, Wan-Ni
;
Sun, Edward W.
- In:
Computational economics
54
(
2019
)
2
,
pp. 809-844
Persistent link: https://www.econbiz.de/10012134380
Saved in:
9
Asymmetries in conditional mean and variance : modelling stock returns by asMA-asQGARCH
Brännäs, Kurt
;
Gooijer, Jan G. de
-
2000
variancefunctions. In a genuine out-of-sample
forecasting
experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean
forecasting
as well as in terms of risk …
forecasting
. …
Persistent link: https://www.econbiz.de/10011303289
Saved in:
10
Error correction modelling and dynamic specifications as a conduit to outperforming the random walk in exchange rate
forecasting
Moosa, Imad A.
;
Burns, Kelly
- In:
Applied economics
46
(
2014
)
25/27
,
pp. 3107-3118
Persistent link: https://www.econbiz.de/10010418113
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