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Related papers: Option pricing models without probability: a rough…

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The objectives of option hedging/trading extend beyond mere protection against downside risks, with a desire to seek gains also driving agent's strategies. In this study, we showcase the potential of robust risk-aware reinforcement learning…

Computational Finance · Quantitative Finance 2023-12-27 David Wu , Sebastian Jaimungal

We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approximations of rough volatility models. The option pricing partial…

Computational Finance · Quantitative Finance 2025-04-04 Antonis Papapantoleon , Jasper Rou

Deep learning for option pricing has emerged as a novel methodology for fast computations with applications in calibration and computation of Greeks. However, many of these approaches do not enforce any no-arbitrage conditions, and the…

Computational Finance · Quantitative Finance 2020-07-22 Marc Chataigner , Stéphane Crépey , Matthew Dixon

Numerous empirical proofs indicate the adequacy of the time discrete auto-regressive stochastic volatility models introduced by Taylor in the description of the log-returns of financial assets. The pricing and hedging of contingent products…

Pricing of Securities · Quantitative Finance 2011-10-31 Joan del Castillo , Juan-Pablo Ortega

We consider the problem of option hedging in a market with proportional transaction costs. Since super-replication is very costly in such markets, we replace perfect hedging with an expected loss constraint. Asymptotic analysis for small…

Portfolio Management · Quantitative Finance 2014-09-12 Bruno Bouchard , Ludovic Moreau , Mete H. Soner

In this work we are concerned with valuing optionalities associated to invest or to delay investment in a project when the available information provided to the manager comes from simulated data of cash flows under historical (or…

Computational Finance · Quantitative Finance 2015-09-14 Edgardo Brigatti , Felipe Macias , Max O. Souza , Jorge P. Zubelli

The quadratic rough Heston model provides a natural way to encode Zumbach effect in the rough volatility paradigm. We apply multi-factor approximation and use deep learning methods to build an efficient calibration procedure for this model.…

Computational Finance · Quantitative Finance 2022-05-31 Mathieu Rosenbaum , Jianfei Zhang

We derive a semi-analytical pricing formula for European VIX call options under the Heston-Hawkes stochastic volatility model introduced in arXiv:2210.15343. This arbitrage-free model incorporates the volatility clustering feature by adding…

Mathematical Finance · Quantitative Finance 2024-06-21 Oriol Zamora Font

Following the foundational work of the Black--Scholes model, extensive research has been developed to price the option by addressing its underlying assumptions and associated pricing biases. This study introduces a novel framework for…

Mathematical Finance · Quantitative Finance 2025-08-21 Tapan Kar , Suprio Bhar , Barun Sarkar , Sesha Meka

Options are contingent claims regarding the value of underlying assets. The Black-Scholes formula provides a road map for pricing these options in a risk-neutral setting, justified by a delta hedging argument in which countervailing…

Mathematical Finance · Quantitative Finance 2026-05-26 Erina Nanyonga , Matt Davison

In this paper the valuation problem of a European call option in presence of both stochastic volatility and transaction costs is considered. In the limit of small transaction costs and fast mean reversion, an asymptotic expression for the…

Pricing of Securities · Quantitative Finance 2012-11-20 R. E. Caflisch , G. Gambino , M. Sammartino , C. Sgarra

We use a path integral approach for solving the stochastic equations underlying the financial markets, and we show the equivalence between the path integral and the usual SDE and PDE methods. We analyze both the one-dimensional and the…

Statistical Mechanics · Physics 2008-12-10 Marco Rosa-Clot , Stefano Taddei

Using tools from spectral analysis, singular and regular perturbation theory, we develop a systematic method for analytically computing the approximate price of a derivative-asset. The payoff of the derivative-asset may be path-dependent.…

Computational Finance · Quantitative Finance 2012-04-09 Matthew Lorig

In this work, we introduce a Monte Carlo method for the dynamic hedging of general European-type contingent claims in a multidimensional Brownian arbitrage-free market. Based on bounded variation martingale approximations for…

Pricing of Securities · Quantitative Finance 2013-08-20 Dorival Leão , Alberto Ohashi , Vinicius Siqueira

An agent-based modelling methodology for the joint price evolution of two stocks is put forward. The method models future multidimensional price trajectories reflecting how a class of agents rebalance their portfolios in an operational way…

Mathematical Finance · Quantitative Finance 2025-03-25 Dario Crisci , Sebastian E. Ferrando , Konrad Gajewski

In this work, I address the issue of forming riskless hedge in the continuous time option pricing model with stochastic stock volatility. I show that it is essential to verify whether the replicating portfolio is self-financing, in order…

Statistical Mechanics · Physics 2008-12-02 D. F. Wang

We study the valuation and hedging problem of European options in a market subject to liquidity shocks. Working within a Markovian regime-switching setting, we model illiquidity as the inability to trade. To isolate the impact of such…

Pricing of Securities · Quantitative Finance 2014-09-10 Michael Ludkovski , Qunying Shen

In this article, we introduce an algorithm called Backward Hedging, designed for hedging European and American options while considering transaction costs. The optimal strategy is determined by minimizing an appropriate loss function, which…

Computational Finance · Quantitative Finance 2023-06-26 Ludovic Goudenège , Andrea Molent , Antonino Zanette

A simple statement and accessible proof of a version of the Fundamental Theorem of Asset Pricing in discrete time is provided. Careful distinction is made between prices and cash flows in order to provide uniform treatment of all…

Mathematical Finance · Quantitative Finance 2019-12-04 Keith A. Lewis

Mathematical modelling is ubiquitous in the financial industry and drives key decision processes. Any given model provides only a crude approximation to reality and the risk of using an inadequate model is hard to detect and quantify. By…

Mathematical Finance · Quantitative Finance 2020-07-09 Patryk Gierjatowicz , Marc Sabate-Vidales , David Šiška , Lukasz Szpruch , Žan Žurič