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~isPartOf:"Applied economics"
~isPartOf:"Quantitative finance"
~subject:"Börsenkurs"
~subject:"Derivat"
~subject:"Prognoseverfahren"
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Search: subject_exact:"Neuronale Netze"
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Börsenkurs
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Funahashi, Hideharu
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Applied economics
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International journal of forecasting
68
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Journal of risk and financial management : JRFM
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European journal of operational research : EJOR
20
Decision analytics journal
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International journal of production research
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Technological forecasting & social change : an international journal
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Advances in business and management forecasting
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Applications of artificial intelligence in finance and economics
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Finanzmarktanalyse und -prognose mit innovativen quantitativen Verfahren : Ergebnisse des 5. Karlsruher Ökonometrie-Workshops
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1
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:
2
Reliability study of stock index forecasting in volatile and trending cities using public sentiment : based on word2Vec and LSTM models
Ma, Yuanyuan
;
Liu, Chenglong
;
Zhang, Jie Tian
;
Liu, Yanze
- In:
Applied economics
55
(
2023
)
43
,
pp. 5013-5032
Persistent link: https://www.econbiz.de/10014334940
Saved in:
3
SABR equipped with AI wings
Funahashi, Hideharu
- In:
Quantitative finance
23
(
2023
)
2
,
pp. 229-249
Persistent link: https://www.econbiz.de/10014232624
Saved in:
4
Integrating prediction in mean-variance portfolio optimization
Butler, Andrew
;
Kwon, Roy H.
- In:
Quantitative finance
23
(
2023
)
3
,
pp. 429-452
Persistent link: https://www.econbiz.de/10014232664
Saved in:
5
Deep learning volatility : a deep neural network perspective on pricing and calibration in (rough) volatility models
Horvath, Blanka Nora
;
Muguruza, Aitor
;
Tomas, Mehdi
- In:
Quantitative finance
21
(
2021
)
1
,
pp. 11-27
Persistent link: https://www.econbiz.de/10012424629
Saved in:
6
Deep learning-based least squares forward-backward stochastic differential equation solver for high-dimensional derivative pricing
Liang, Jian
;
Xu, Zhe
;
Li, Peter
- In:
Quantitative finance
21
(
2021
)
8
,
pp. 1309-1323
Persistent link: https://www.econbiz.de/10012608649
Saved in:
7
Artificial neural network for option pricing with and without asymptotic correction
Funahashi, Hideharu
- In:
Quantitative finance
21
(
2021
)
4
,
pp. 575-592
Persistent link: https://www.econbiz.de/10012483840
Saved in:
8
A neural network enhanced volatility component model
Zhai, Jia
;
Cao, Yi
;
Liu, Xiaoquan
- In:
Quantitative finance
20
(
2020
)
5
,
pp. 783-797
Persistent link: https://www.econbiz.de/10012262620
Saved in:
9
Bayesian regularized artificial neural networks for the estimation of the probability of default
Sariev, Eduard
;
Germano, Guido
- In:
Quantitative finance
20
(
2020
)
2
,
pp. 311-328
Persistent link: https://www.econbiz.de/10012194868
Saved in:
10
Encoding of high-frequency order information and prediction of short-term stock price by deep learning
Tashiro, Daigo
;
Matsushima, Hiroyasu
;
Izumi, Kiyoshi
; …
- In:
Quantitative finance
19
(
2019
)
9
,
pp. 1499-1506
Persistent link: https://www.econbiz.de/10012194801
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