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The construction of approximate replication strategies for pricing and hedging of derivative contracts in incomplete markets is a key problem of financial engineering.
The pricing of options and corporate liabilities
F. Black and M. Scholes · 1973
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R. C. Merton · 1973
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John C. Cox, Stephen A. Ross, and Mark Rubinstein · 1979
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H. Föllmer and D. Sondermann · 1985
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T.L Lai and Herbert Robbins · 1985
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Phelim Boyle · 1986
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J. Hull and A. White · 1987
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Knut K. Aase · 1988
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S. Hodges and A. Neuberger · 1989
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E.N. Barron and R. Jensen · 1990
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Continuous Time Finance
R.C. Merton · 1990
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Bernard Bensaid, Jean-Philippe Lesne, Henri Pagès, and José Scheinkman · 1992
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Q-learning
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Mark H. A. Davis, Vassilios G. Panas, and Thaleia Zariphopoulou · 1993
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The Black-Scholes option pricing problem in mathematical finance: generalization and extensions for a large class of stochastic processes
Jean-Philippe Bouchaud and Didier Sornette · 1994
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Markov decision processes: discrete stochastic dynamic programming
M.L. Puterman · 1994
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On quadratic cost criteria for option hedging
Manfred Schäl · 1994
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Planning under time constraints in stochastic domains
Thomas Dean, Leslie Pack Kaelbling, Jak Kirman, and Ann Nicholson · 1995
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Dynamic programming and pricing of contingent claims in an incomplete market
Nicole El Karoui and Marie-Claire Quenez · 1995
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Variance-optimal hedging in discrete time
Martin Schweizer · 1995
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Optimal sailing strategies, statistics and operations research program
R. Vanderbei · 1996
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Optimal delta-hedging under transactions costs
Les Clewlow and Stewart Hodges · 1997
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Analysis of temporal-difference learning with function approximation
J. N. Tsitsiklis and B. Van Roy · 1997
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A Survey of Monte Carlo Tree Search Methods
C. B. Browne, E. Powley, D. Whitehouse, S. M. Lucas, P. I. Cowling, P. Rohlfshagen, S. Tavener, D. Perez, S. Samothrakis, and S. Colton · 2012
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Monte Carlo Tree Search for Continuous and Stochastic Sequential Decision Making Problems
Couëtoux Adrien · 2013
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Playing atari with deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller · 2013
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Deep exploration via bootstrapped DQN
I. Osband, C. Blundell, A. Pritzel, and B. Van Roy · 2016
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Deep reinforcement learning with double q-learning
H. Van Hasselt, A. Guez, and D. Silver · 2016
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Thinking fast and slow with deep learning and tree search
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Utility based option pricing with proportional transaction costs and diversification problems: an interior-point optimization approach
Erling D. Andersen and Anders Damgaard · 1999
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Dynamic Asset Pricing Theory: Third Edition
D. Duffie · 2001
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LAO ∗ \ast : A heuristic search algorithm that finds solutions with loops
Eric A. Hansen and Shlomo Zilberstein · 2001
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Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolò Cesa-Bianchi, and Paul Fischer · 2002
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A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
Michael Kearns, Yishay Mansour, and Andrew Y. Ng · 2002
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Thomas Anthony, Zheng Tian, and David Barber · 2017
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Qlbs: Q-learner in the Black-Scholes (-Merton) worlds
I. Halperin · 2017
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Mastering the game of Go without human knowledge
D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, and A. Bolton · 2017
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A general reinforcement learning algorithm that masters Chess, Shogi, and Go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, and Demis Hassabis · 2018
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Reinforcement learning: An introduction
R. S. Sutton and A. G. Barto · 2018
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Deep hedging
H. Buehler, L. Gonon, J. Teichmann, and B. Wood · 2019
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Deep hedging: hedging derivatives under generic market frictions using reinforcement learning
H. Buehler, L. Gonon, J. Teichmann, B. Wood, B. Mohan, and J. Kochems · 2019
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Deep hedging of derivatives using reinforcement learning
J. Cao, J. Chen, J. C. Hull, and Z. Poulos · 2019
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Dynamic replication and hedging: A reinforcement learning approach
P. N. Kolm and G. Ritter · 2019
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Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
L. Bisi, L. Sabbioni, E. Vittori, E. Papini, and M. Restelli · 2020
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Monte carlo tree search in continuous spaces using voronoi optimistic optimization with regret bounds
B. Kim, K. Lee, S. Lim, L. Kaelbling, and T. Lozano-Perez · 2020
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Option Hedging with Risk Averse Reinforcement Learning
E. Vittori, E. Trapletti, and M. Restelli · 2020
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