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SABR equipped with AI wings
Funahashi, Hideharu
- In:
Quantitative finance
23
(
2023
)
2
,
pp. 229-249
Persistent link: https://www.econbiz.de/10014232624
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2
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
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3
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
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4
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
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5
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
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6
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
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7
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
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8
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
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