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Applied mathematical finance
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A family of maximum entropy densities matching call option prices
Neri, Cassio
;
Schneider, Lorenz
- In:
Applied mathematical finance
20
(
2013
)
5/6
,
pp. 548-577
Persistent link: https://www.econbiz.de/10010235560
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Deep reinforcement learning for market making in corporate bonds : beating the curse of dimensionality
Guéant, Olivier
;
Manziuk, Iuliia
- In:
Applied mathematical finance
26
(
2019
)
5
,
pp. 387-452
Persistent link: https://www.econbiz.de/10012210413
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3
Double Deep Q-Learning for optimal execution
Ning, Brian
;
Lin, Franco Ho Ting
;
Jaimungal, Sebastian
- In:
Applied mathematical finance
28
(
2021
)
4
,
pp. 361-380
Persistent link: https://www.econbiz.de/10013411703
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4
Policy gradient learning methods for stochastic control with exit time and applications to share repurchase pricing
Hamdouche, Mohamed
;
Henry-Labordere, Pierre
;
Pham, Huyên
- In:
Applied mathematical finance
29
(
2022
)
6
,
pp. 439-456
Persistent link: https://www.econbiz.de/10014390280
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5
Deep Q-learning for Nash equilibria : Nash-DQN
Casgrain, Philippe
;
Ning, Brian
;
Jaimungal, Sebastian
- In:
Applied mathematical finance
29
(
2022
)
1
,
pp. 62-78
Persistent link: https://www.econbiz.de/10013554784
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6
Robust risk-aware option hedging
Wu, David
;
Jaimungal, Sebastian
- In:
Applied mathematical finance
30
(
2023
)
3
,
pp. 153-174
Persistent link: https://www.econbiz.de/10015051231
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