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Found 8 papers, 1 papers with code
Macroscopic Market Making
We propose the macroscopic market making model \`a la Avellaneda-Stoikov, using continuous processes for orders instead of discrete point processes.
Simultaneous upper and lower bounds of American option prices with hedging via neural networks
In this paper, we introduce two methods to solve the American-style option pricing problem and its dual form at the same time using neural networks.
Superhedging duality for multi-action options under model uncertainty with information delay
We consider the superhedging price of an exotic option under nondominated model uncertainty in discrete time in which the option buyer chooses some action from an (uncountable) action space at each time step.
Optimal transport for model calibration
We provide a survey of recent results on model calibration by Optimal Transport.
On Stochastic Partial Differential Equations and their applications to Derivative Pricing through a conditional Feynman-Kac formula
In a multi-dimensional diffusion framework, the price of a financial derivative can be expressed as an iterated conditional expectation, where the inner conditional expectation conditions on the future of an auxiliary process that enters into the dynamics for the spot.
Joint Modelling and Calibration of SPX and VIX by Optimal Transport
This paper addresses the joint calibration problem of SPX options and VIX options or futures.
Valuation of contingent claims with short selling bans under an equal-risk pricing framework
This paper studies the valuation of European contingent claims with short selling bans under the equal risk pricing (ERP) framework proposed in Guo and Zhu (2017) where analytical pricing formulae were derived in the case of monotonic payoffs under risk-neutral measures.
Calibration of Local-Stochastic Volatility Models by Optimal Transport
In this paper, we study a semi-martingale optimal transport problem and its application to the calibration of Local-Stochastic Volatility (LSV) models.
