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~isPartOf:"Applied economics letters"
~source:"econis"
~subject:"Artificial intelligence"
~subject:"Estimation theory"
~subject:"Volatility"
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Monte, Enric
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Applied economics letters
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Predicting money laundering sanctions using machine learning algorithms and artificial neural networks
Lokanan, Mark E.
- In:
Applied economics letters
31
(
2024
)
12
,
pp. 1112-1118
Persistent link: https://www.econbiz.de/10014558696
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2
Analysis of investors' prediction potential using Holt Winters model and artificial neural networks
Dungore, Parizad Phiroze
- In:
Applied economics letters
29
(
2022
)
21
,
pp. 2032-2039
Persistent link: https://www.econbiz.de/10013552916
Saved in:
3
Improving econometric prediction by machine learning
Cerulli, Giovanni
- In:
Applied economics letters
28
(
2021
)
16
,
pp. 1419-1425
Persistent link: https://www.econbiz.de/10012609694
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4
How words matter : machine learning & movie success
Nemzer, Louis R.
;
Neymotin, Florence
- In:
Applied economics letters
27
(
2020
)
15
,
pp. 1272-1276
Persistent link: https://www.econbiz.de/10012267121
Saved in:
5
Can machine learning on economic data better forecast the unemployment rate?
Kreiner, Aaron
;
Duca, John V.
- In:
Applied economics letters
27
(
2020
)
17
,
pp. 1434-1437
Persistent link: https://www.econbiz.de/10012313923
Saved in:
6
Combination forecasts of tourism demand with machine learning models
Claveria, Oscar
;
Monte, Enric
;
Torra, Salvador
- In:
Applied economics letters
23
(
2016
)
4/6
,
pp. 428-431
Persistent link: https://www.econbiz.de/10011430763
Saved in:
7
On the approximation of production functions : a comparison of artificial neural networks frontiers and efficiency techniques
Santin, Daniel
- In:
Applied economics letters
15
(
2008
)
7/9
,
pp. 597-600
Persistent link: https://www.econbiz.de/10003741371
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