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ECONIS (ZBW)
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Early warning system for currency crises using long short-term memory and gated recurrent unit neural networks
Barthélémy, Sylvain
;
Rondeau, Fabien
;
Gautier, Virginie
-
2023
Persistent link: https://www.econbiz.de/10014334456
Saved in:
2
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:
3
Learning a functional control for high-frequency finance
Leal, Laura
;
Lauriere, Mathieu
;
Lehalle, Charles-Albert
- In:
Quantitative finance
22
(
2022
)
11
,
pp. 1973-1987
Persistent link: https://www.econbiz.de/10013490928
Saved in:
4
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:
5
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:
6
A hybrid convolutional neural network with long short-term memory for statistical arbitrage
Eggebrecht, P.
;
Lütkebohmert-Holtz, Eva
- In:
Quantitative finance
23
(
2023
)
4
,
pp. 595-613
Persistent link: https://www.econbiz.de/10014304278
Saved in:
7
Deep weighted Monte Carlo : a hybrid option pricing framework using neural networks
Kunsági-Máté, Sándor
;
Fáth, Gábor
;
Csabai, István
; …
- In:
Quantitative finance
23
(
2023
)
4
,
pp. 615-629
Persistent link: https://www.econbiz.de/10014304287
Saved in:
8
Efficient pricing and hedging of high-dimensional American options using deep recurrent networks
Na, Andrew S.
;
Wan, Justin W. L.
- In:
Quantitative finance
23
(
2023
)
4
,
pp. 631-651
Persistent link: https://www.econbiz.de/10014304288
Saved in:
9
Multi-state health transition modeling using neural networks
Wang, Qiqi
;
Hanewald, Katja
;
Wang, Xiaojun
-
2020
Persistent link: https://www.econbiz.de/10012585604
Saved in:
10
What is the value of the cross-sectional approach to deep reinforcement learning?
Aboussalah, Amine Mohamed
;
Xu, Ziyun
;
Lee, Chi-Guhn
- In:
Quantitative finance
22
(
2022
)
6
,
pp. 1091-1111
Persistent link: https://www.econbiz.de/10013367887
Saved in:
11
An unsupervised deep learning approach to solving partial integro-differential equations
Fu, Weilong
;
Hirsa, Ali
- In:
Quantitative finance
22
(
2022
)
8
,
pp. 1481-1494
Persistent link: https://www.econbiz.de/10013367923
Saved in:
12
Optimal asset allocation for outperforming a stochastic benchmark target
Ni, Chendi
;
Li, Yuying
;
Forsyth, Peter A.
;
Carroll, Ray
- In:
Quantitative finance
22
(
2022
)
9
,
pp. 1595-1626
Persistent link: https://www.econbiz.de/10013367937
Saved in:
13
A deep learning approach to estimating fill probabilities in a limit order book
Maglaras, Costis
;
Moallemi, Ciamac C.
;
Wang, Muye
- In:
Quantitative finance
22
(
2022
)
11
,
pp. 1989-2003
Persistent link: https://www.econbiz.de/10013490915
Saved in:
14
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:
15
Deep neural network framework based on backward stochastic differential equations for pricing and hedging American options in high dimensions
Chen, Yangang
;
Wan, Justin W. L.
- In:
Quantitative finance
21
(
2021
)
1
,
pp. 45-67
Persistent link: https://www.econbiz.de/10012424632
Saved in:
16
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:
17
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:
18
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:
19
Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network
Mulvey, John M.
;
Sun, Yifan
;
Wang, Mengdi
;
Ye, Jing
- In:
Quantitative finance
20
(
2020
)
8
,
pp. 1239-1261
Persistent link: https://www.econbiz.de/10012262660
Saved in:
20
Accelerated share repurchase and other buyback programs : what neural networks can bring
Guéant, Olivier
;
Manziuk, Iuliia
;
Pu, Jiang
- In:
Quantitative finance
20
(
2020
)
8
,
pp. 1389-1404
Persistent link: https://www.econbiz.de/10012262692
Saved in:
21
A neural network approach to understanding implied volatility movements
Cao, Jay
;
Chen, Jacky
;
Hull, John
- In:
Quantitative finance
20
(
2020
)
9
,
pp. 1405-1413
Persistent link: https://www.econbiz.de/10012295608
Saved in:
22
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:
23
Calibrating rough volatility models : a convolutional neural network approach
Stone, Henry
- In:
Quantitative finance
20
(
2020
)
3
,
pp. 379-392
Persistent link: https://www.econbiz.de/10012194872
Saved in:
24
Generative Bayesian neural network model for risk-neutral pricing of American index options
Jang, Huisu
;
Lee, Jaewook
- In:
Quantitative finance
19
(
2019
)
4
,
pp. 587-603
Persistent link: https://www.econbiz.de/10012194699
Saved in:
25
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
Saved in:
26
Learning multi-market microstructure from order book data
Ju, Geonhwan
;
Kim, Kyoung-Kuk
;
Lim, Dong-Young
- In:
Quantitative finance
19
(
2019
)
9
,
pp. 1517-1529
Persistent link: https://www.econbiz.de/10012194803
Saved in:
27
Can machine learning approaches predict corporate bankruptcy? : evidence from a qualitative experimental design
Lahmiri, Salim
;
Bekiros, Stelios
- In:
Quantitative finance
19
(
2019
)
9
,
pp. 1569-1577
Persistent link: https://www.econbiz.de/10012194807
Saved in:
28
Neural network copula portfolio optimization for exchange traded funds
Zhao, Yang
;
Stasinakis, Charalampos
;
Sermpinis, Georgios
; …
- In:
Quantitative finance
18
(
2018
)
5
,
pp. 761-775
Persistent link: https://www.econbiz.de/10011907933
Saved in:
29
Forecasting realized volatility with linear and nonlinear univariate models
McAleer, Michael
;
Medeiros, Marcelo C.
-
2010
Persistent link: https://www.econbiz.de/10008689073
Saved in:
30
Boosting estimation of RBF neural networks for dependent data
Kapetanios, George
(
contributor
); …
-
2007
Persistent link: https://www.econbiz.de/10003428552
Saved in:
31
Testing the martingale difference hypothesis using neural network approximations
Kapetanios, George
(
contributor
); …
-
2007
Persistent link: https://www.econbiz.de/10003475296
Saved in:
32
A test for serial dependence using neural networks
Kapetanios, George
(
contributor
)
-
2007
Persistent link: https://www.econbiz.de/10003564910
Saved in:
33
Testing for neglected nonlinearity in long memory models
Baillie, Richard
(
contributor
); …
-
2005
Persistent link: https://www.econbiz.de/10002808664
Saved in:
34
Testing for neglected nonlinearity in cointegrating relationships
Blake, Andrew P.
(
contributor
); …
-
2004
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001920635
Saved in:
35
Testing for ARCH in the presence of nonlinearity of unknow form in the conditional mean
Blake, Andrew P.
(
contributor
); …
-
2003
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001868024
Saved in:
36
Testing for neglected nonlinearity in long memory models
Kapetanios, George
(
contributor
)
-
2002
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001867128
Saved in:
37
Testing for structural breaks in nonlinear dynamic models using artificial neural network approximations
Kapetanios, George
(
contributor
)
-
2002
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001867146
Saved in:
38
Artificial neural networks versus multivariate statistics : an application from economics
Cooper, John C. B.
-
1998
Persistent link: https://www.econbiz.de/10000683183
Saved in:
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