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~isPartOf:"Applied economics"
~isPartOf:"Computational economics"
~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"International journal of forecasting"
~person:"Burns, Kelly"
~person:"Chen, Yi-Ting"
~person:"Gkonkas, Periklēs"
~person:"Nikolopoulos, Konstantinos"
~person:"Rubaszek, Michał"
~subject:"Bankinsolvenz"
~subject:"Nationaleinkommen"
~subject:"Prognoseverfahren"
~subject:"VAR-Modell"
~subject:"World"
~subject:"Zeitreihenanalyse"
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Indian Economic Outlook 2008-0...
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Bankinsolvenz
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Burns, Kelly
Chen, Yi-Ting
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Nikolopoulos, Konstantinos
Rubaszek, Michał
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15
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12
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10
Moosa, Imad A.
10
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5
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4
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3
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3
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3
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3
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3
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3
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3
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3
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3
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3
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2
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Bas, Eren
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Applied economics
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Discussion paper / Tinbergen Institute
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3
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2
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2
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ECONIS (ZBW)
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1
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:
2
Gold against the machine
Plakandaras, Vasilios
;
Gkonkas, Periklēs
; …
- In:
Computational economics
57
(
2021
)
1
,
pp. 5-28
Persistent link: https://www.econbiz.de/10012486908
Saved in:
3
Forecasting
bank failures and stress testing : a machine learning approach
Gkonkas, Periklēs
;
Papadimitriou, Theophilos
; …
- In:
International journal of forecasting
34
(
2018
)
3
,
pp. 440-455
Persistent link: https://www.econbiz.de/10012031002
Saved in:
4
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:
5
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:
6
Tales from tails : on the empirical distributions of
forecasting
errors and their implication to risk
Spiliotis, Evangelos
;
Nikolopoulos, Konstantinos
; …
- In:
International journal of forecasting
35
(
2019
)
2
,
pp. 687-698
Persistent link: https://www.econbiz.de/10012300716
Saved in:
7
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:
8
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:
9
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:
10
Yield curve and recession
forecasting
in a Machine Learning framework
Gkonkas, Periklēs
;
Papadimitriou, Theophilos
; …
- In:
Computational economics
45
(
2015
)
4
,
pp. 635-645
Persistent link: https://www.econbiz.de/10011440977
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