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subject:"Börsenkurs"
type:"book"
~isPartOf:"Discussion paper / Humboldt-Universität zu Berlin, Sonderforschungsbereich 373 Quantifikation und Simulation Ökonomischer Prozesse"
~isPartOf:"Working paper / Department of Econometrics and Business Statistics, Monash University"
~subject:"Bootstrap-Verfahren"
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Börsenkurs
Bootstrap-Verfahren
Estimation theory
252
Schätztheorie
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Theorie
99
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Time series analysis
83
Zeitreihenanalyse
83
Nichtparametrisches Verfahren
66
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Gao, Jiti
5
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Grose, Simone D.
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Linton, Oliver
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Litvinova, Svetlana
2
Liu, Fei
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Silvapulle, Mervyn J.
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1
Benkwitz, Alexander
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Bunke, Olaf
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Cai, Biqing
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1
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1
Hyndman, Rob J.
1
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1
Kim, Jae H.
1
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1
Lukas, Manuel
1
Lütkepohl, Helmut
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1
Naik, Narayan Y.
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Rao, J. N. K.
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Silvapulle, Paramsothy
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Discussion paper / Humboldt-Universität zu Berlin, Sonderforschungsbereich 373 Quantifikation und Simulation Ökonomischer Prozesse
Working paper / Department of Econometrics and Business Statistics, Monash University
CEMMAP working papers / Centre for Microdata Methods and Practice
32
Discussion paper / Tinbergen Institute
17
CREATES research paper
15
Cowles Foundation discussion paper
14
Queen's Economics Department working paper
14
Working paper
11
Working paper series
11
Cambridge working papers in economics
10
Discussion papers of interdisciplinary research project 373
10
SFB 649 discussion paper
10
Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund
9
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8
NBER working paper series
8
Cowles Foundation Discussion Paper
7
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6
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6
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6
CORE discussion paper : DP
5
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5
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5
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5
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5
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Discussion paper / Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München
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Discussion paper in financial economics : FE
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Discussion papers / Deutsches Institut für Wirtschaftsforschung
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ECONIS (ZBW)
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Estimation and inference for three-dimensional panel data models
Feng, Guohua
;
Gao, Jiti
;
Liu, Fei
;
Peng, Bin
-
2024
Persistent link: https://www.econbiz.de/10014584601
Saved in:
2
Estimation and inference for three-dimensional panel data models
Feng, Guohua
;
Gao, Jiti
;
Liu, Fei
;
Peng, Bin
-
2023
Persistent link: https://www.econbiz.de/10014452624
Saved in:
3
High-frequency jump tests : which test should we use?
Maneesoonthorn, Worapree
;
Martin, Gael M.
;
Forbes, …
-
2020
-
(Revised working paper 17/18)
Persistent link: https://www.econbiz.de/10012606872
Saved in:
4
Consistency of full-sample bootstrap for estimating high-quantile, tail probability, and tail index
Litvinova, Svetlana
;
Silvapulle, Mervyn J.
-
2020
Persistent link: https://www.econbiz.de/10012607652
Saved in:
5
Bagging weak predictors
Hillebrand, Eric
;
Lukas, Manuel
;
Wei, Wei
-
2020
Persistent link: https://www.econbiz.de/10012607673
Saved in:
6
Nonparametric predictive regressions for stock return prediction
Cheng, Tingting
;
Gao, Jiti
;
Linton, Oliver
-
2019
Persistent link: https://www.econbiz.de/10012592220
Saved in:
7
Bootstrapping tail statistics: tail quantile process, Hill estimator, and confidence intervals for highquantiles of heavy tailed distributions
Litvinova, Svetlana
;
Silvapulle, Mervyn J.
-
2018
Persistent link: https://www.econbiz.de/10012583470
Saved in:
8
Exponent of cross-sectional dependence for residuals
Bailey, Natalia
;
Kapetanios, George
;
Pesaran, M. Hashem
-
2018
Persistent link: https://www.econbiz.de/10012583496
Saved in:
9
Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction
Cheng, Tingting
;
Gao, Jiti
;
Linton, Oliver
-
2017
Persistent link: https://www.econbiz.de/10011782226
Saved in:
10
A simple nonlinear predictive model for stock returns
Cai, Biqing
;
Gao, Jiti
-
2017
Persistent link: https://www.econbiz.de/10011782256
Saved in:
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