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To the best of our knowledge, the application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon.
Numerical methods for the pricing of Swing options: a stochastic control approach
Christophe Barrera-Esteve, Florent Bergeret, Charles H Dossal, Emmanuel GOBET, Asma Meziou, Rémi Munos, and Damien Reboul-Salze · 2006
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Optimization of injection/withdrawal schedules for natural gas storage facilities
Alan Holland · 2007
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Alexander Boogert and Cyriel De Jong · 2008
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Natural gas storage valuation via least squares monte carlo and support vector regression
Alexander M Malyscheff and Theodore B Trafalis · 2017
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Natural gas storage valuation and optimization under time-inhomogeneous exponential lévy processes
Nemat Safarov and Colin Atkinson · 2017
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Gas storage valuation and hedging: A quantification of model risk
Patrick Hénaff, Ismail Laachir, and Francesco Russo · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Deep hedging
Hans Buehler, Lukas Gonon, Josef Teichmann, and Ben Wood · 2019
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Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications, 2020
Achref Bachouch, Côme Huré, Nicolas Langrené, and Huyen Pham · 2020
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Pricing commodity swing options, 2020
Roberto Daluiso, Emanuele Nastasi, Andrea Pallavicini, and Giulio Sartorelli · 2020
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