• Corpus ID: 251105216

Classical and deep pricing for Path-dependent options in non-linear generalized affine models

@inproceedings{Geuchen2022ClassicalAD,
  title={Classical and deep pricing for Path-dependent options in non-linear generalized affine models},
  author={Benedikt Geuchen and Katharina Oberpriller and Thorsten Schmidt},
  year={2022}
}
. In this work we consider one-dimensional generalized affine processes under the paradigm of Knightian uncertainty (so-called non-linear generalized affine models). This extends and generalizes previous results in Fadina et al. (2019) and L¨utkebohmert et al. (2022). In particular, we study the case when the payoff is allowed to depend on the path, like it is the case for barrier options or Asian options. To this end, we develop the path-dependent setting for the value function relying on… 

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SHOWING 1-10 OF 39 REFERENCES

Affine processes under parameter uncertainty

We develop a one-dimensional notion of affine processes under parameter uncertainty, which we call nonlinear affine processes. This is done as follows: given a set Θ of parameters for the process, we

Robust deep hedging

We study pricing and hedging under parameter uncertainty for a class of Markov processes which we call generalized affine processes and which includes the Black–Scholes model as well as the constant

Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations

This work proposes a new method for solving high-dimensional fully nonlinear second-order PDEs and shows the efficiency and the accuracy of the method in the cases of a 100-dimensional Black–Scholes–Barenblatt equation, a100-dimensional Hamilton–Jacobi–Bellman equation, and a nonlinear expectation of a 200-dimensional G-Brownian motion.

Efficient Asian option pricing under regime switching jump diffusions and stochastic volatility models

Utilizing frame duality and a FFT-based implementation of density projection we develop a novel and efficient transform method to price Asian options for very general asset dynamics, including regime

Comparison of semimartingales and Lévy processes

In this paper, we derive comparison results for terminal values of d-dimensional special semimartingales and also for finite-dimensional distributions of multivariate Levy processes. The comparison

Reduced-form setting under model uncertainty with non-linear affine intensities

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NON-LINEAR CONTINUOUS SEMIMARTINGALES

. In this paper we study a family of non-linear (conditional) expectations that can be understood as a continuous semimartingale with uncertain local characteristics. Here, the differential

PRICING ASIAN OPTIONS FOR JUMP DIFFUSION

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A THEORETICAL FRAMEWORK FOR THE PRICING OF CONTINGENT CLAIMS IN THE PRESENCE OF MODEL UNCERTAINTY

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Functional Ito calculus and stochastic integral representation of martingales

We develop a non-anticipative calculus for functionals of a continuous semimartingale, using an extension of the Ito formula to path-dependent functionals which possess certain directional