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~isPartOf:"Applied economics letters"
~isPartOf:"Computational economics"
~isPartOf:"Quantitative finance"
~subject:"Prognoseverfahren"
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Search: subject_exact:"Neuronale Netze"
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Prognoseverfahren
Neural networks
103
Neuronale Netze
103
Forecasting model
57
Theorie
57
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57
Artificial intelligence
18
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18
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Bas, Eren
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Applied economics letters
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International journal of forecasting
74
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25
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24
Decision analytics journal
22
European journal of operational research : EJOR
22
International journal of production research
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Energy economics
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Tourism economics : the business and finance of tourism and recreation
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Applications of artificial intelligence in finance and economics
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European research studies
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Finanzmarktanalyse und -prognose mit innovativen quantitativen Verfahren : Ergebnisse des 5. Karlsruher Ökonometrie-Workshops
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ECONIS (ZBW)
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Forecasting cryptocurrencies' price with the financial stress index : a graph neural network prediction strategy
Yin, Wei
;
Chen, Ziling
;
Luo, Xinxin
;
Kirkulak-Uludag, Berna
- In:
Applied economics letters
31
(
2024
)
7
,
pp. 630-639
Persistent link: https://www.econbiz.de/10014557817
Saved in:
2
A new neural network approach for predicting the volatility of stock market
Koo, Eunho
;
Kim, Geonwoo
- In:
Computational economics
61
(
2023
)
4
,
pp. 1665-1679
Persistent link: https://www.econbiz.de/10014327101
Saved in:
3
A generative model of a limit order book using recurrent neural networks
Hultin, Hanna
;
Hult, Henrik
;
Proutiere, Alexandre
; …
- In:
Quantitative finance
23
(
2023
)
6
,
pp. 931-958
Persistent link: https://www.econbiz.de/10014304400
Saved in:
4
Bayesian estimation of economic simulation models using neural networks
Platt, Donovan
- In:
Computational economics
59
(
2022
)
2
,
pp. 599-650
Persistent link: https://www.econbiz.de/10013169024
Saved in:
5
Feature selection and hyperparameters optimization employing a hybrid model based on genetic algorithm and artifcial neural network : forecasting dividend payout ratio
Konak, Fatih
;
Bülbül, Mehmet Akif
;
Türkoǧlu, Diler
- In:
Computational economics
63
(
2024
)
4
,
pp. 1673-1693
Persistent link: https://www.econbiz.de/10014549172
Saved in:
6
GARCHNet: Value‑at‑risk forecasting with GARCH models based on neural networks
Buczynski, Mateusz
;
Chlebus, Marcin
- In:
Computational economics
63
(
2024
)
5
,
pp. 1949-1979
Persistent link: https://www.econbiz.de/10014550845
Saved in:
7
Physics-informed convolutional transformer for predicting volatility surface
Kim, Soohan
;
Yun, Seok-Bae
;
Bae, Hyeong-Ohk
;
Lee, Muhyun
; …
- In:
Quantitative finance
24
(
2024
)
2
,
pp. 203-220
Persistent link: https://www.econbiz.de/10014551964
Saved in:
8
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
Saved in:
9
Statistical evaluation of deep learning models for stock return forecasting
Yilmaz, Firat Melih
;
Yildiztepe, Engin
- In:
Computational economics
63
(
2024
)
1
,
pp. 221-244
Persistent link: https://www.econbiz.de/10014472083
Saved in:
10
Predicting natural gas prices based on a novel hybrid model with variational mode decomposition
Lu, Qin
;
Liao, Jingwen
;
Chen, Kechi
;
Liang, Yanhui
;
Lin, Yu
- In:
Computational economics
63
(
2024
)
2
,
pp. 639-678
Persistent link: https://www.econbiz.de/10014472537
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