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subject:"Productivity"
type_genre:"Non-commercial literature"
~isPartOf:"Cambridge working papers in economics"
~subject:"Time series analysis"
~type_genre:"Bibliografie"
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Productivity
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Do consumption-based asset pricing models explain own-history predictability in stock market returns?
Ashby, Michael F.
;
Linton, Oliver
-
2022
Persistent link: https://www.econbiz.de/10013486082
Saved in:
2
Revisiting the great ratios hypothesis
Chudik, Alexander
;
Pesaran, M. Hashem
;
Smith, Ron
-
2022
Persistent link: https://www.econbiz.de/10013263388
Saved in:
3
Estimating time-varying networks for high-dimensional time series
Chen, Jia
;
Li, Degui
;
Li, Yuning
;
Linton, Oliver
-
2022
-
Version: December 13, 2022
Persistent link: https://www.econbiz.de/10013503856
Saved in:
4
Testing and modelling time series with time varying tails
Palumbo, Dario
-
2021
Persistent link: https://www.econbiz.de/10013254110
Saved in:
5
Estimation of common factors for microstructure noise and efficient price in a high-frequency dual factor model
Li, Yu-Ning
;
Chen, Jia
;
Linton, Oliver
-
2021
Persistent link: https://www.econbiz.de/10013259517
Saved in:
6
Conditional heteroskedasticity in the volatility of asset returns
Ding, Yashuang
-
2021
Persistent link: https://www.econbiz.de/10013262866
Saved in:
7
Can alternative data improve the accuracy of dynamic factor model nowcasts? : evidence from the euro area
Cristea, Radu Gabriel
-
2020
Persistent link: https://www.econbiz.de/10013206467
Saved in:
8
The aggregate consequences of default risk : evidence from firm-level data
Besley, Timothy
;
Roland, Isabelle
;
Van Reenen, John
-
2019
Persistent link: https://www.econbiz.de/10012793064
Saved in:
9
A multiple testing approach to the regularisation of large sample correlation matrice
Bailey, Natalia
;
Peseran, Hashem
;
Smith, L. Vanessa
-
2014
Persistent link: https://www.econbiz.de/10010366306
Saved in:
10
Modeling dynamic diurnal patterns in high frequency financial data
Ito, Ryoko
-
2013
Persistent link: https://www.econbiz.de/10009737686
Saved in:
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