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1
A machine learning approach for flagging incomplete bid-rigging cartels
Wallimann, Hannes
;
Imhof, David
;
Huber, Martin
- In:
Computational economics
62
(
2023
)
4
,
pp. 1669-1720
Persistent link: https://www.econbiz.de/10014437552
Saved in:
2
Unit roots in macroeconomic time series : a comparison of classical, Bayesian and machine learning approaches
Ahmad, Yamin
;
Check, Adam
;
Lo, Ming Chien
- In:
Computational economics
63
(
2024
)
6
,
pp. 2139-2173
Persistent link: https://www.econbiz.de/10014636725
Saved in:
3
Comparing out-of-sample performance of machine learning methods to forecast U.S. GDP growth
Chu, Ba
;
Qureshi, Shafiullah
- In:
Computational economics
62
(
2023
)
4
,
pp. 1567-1609
Persistent link: https://www.econbiz.de/10014437505
Saved in:
4
Economic policy uncertainty index meets ensemble learning
Lolić, Ivana
;
Sorić, Petar
;
Logarušić, Marija
- In:
Computational economics
60
(
2022
)
2
,
pp. 401-437
Persistent link: https://www.econbiz.de/10013380776
Saved in:
5
Forecasting of real GDP growth using machine learning models : gradient boosting and
random
forest
approach
Yoon, Jaehyun
- In:
Computational economics
57
(
2021
)
1
,
pp. 247-265
Persistent link: https://www.econbiz.de/10012486898
Saved in:
6
An intelligent system for insider trading identification in Chinese security market
Deng, Shangkun
;
Wang, Chenguang
;
Fu, Zhe
;
Wang, Mingyue
- In:
Computational economics
57
(
2021
)
2
,
pp. 593-616
Persistent link: https://www.econbiz.de/10012486935
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