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This paper is devoted to a study of robust fundamental theorems of asset pricing in discrete time and finite horizon settings. Uncertainty is modelled by a (possibly uncountable) family of price processes on the same probability space. Our…

Mathematical Finance · Quantitative Finance 2024-04-04 Huy N. Chau

Paper is based on "The cost of illiquidity and its effects on hedging", L. C. G. Rogers and Surbjeet Singh, 2010. We generalize its thesis to constant elasticity model, which own previously used Black-Schoels model as a special case. The…

Mathematical Finance · Quantitative Finance 2014-09-23 Krzysztof Turek

An efficient computational algorithm to price financial derivatives is presented. It is based on a path integral formulation of the pricing problem. It is shown how the path integral approach can be worked out in order to obtain fast and…

Statistical Mechanics · Physics 2009-11-07 G. Montagna , O. Nicrosini , N. Moreni

In this paper we introduce a new approach to model-free path-dependent option pricing. We first introduce a general duality result for linear optimisation problems over signed measures introduced in [3] and show how the the problem of…

Pricing of Securities · Quantitative Finance 2015-01-16 Raphael Hauser , Sergey Shahverdyan

In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price European path dependent options on multidimensional assets is obtained and…

Other Condensed Matter · Physics 2008-12-02 G. Bormetti , G. Montagna , N. Moreni , O. Nicrosini

We estimate prices of exotic options in a discrete-time model-free setting when the trader has access to market prices of a rich enough class of exotic and vanilla options. This is achieved by estimating an unobservable quantity called…

Mathematical Finance · Quantitative Finance 2020-02-26 Terry Lyons , Sina Nejad , Imanol Perez Arribas

We develop a robust framework for pricing and hedging of derivative securities in discrete-time financial markets. We consider markets with both dynamically and statically traded assets and make minimal measurability assumptions. We obtain…

Mathematical Finance · Quantitative Finance 2018-02-08 Matteo Burzoni , Marco Frittelli , Zhaoxu Hou , Marco Maggis , Jan Obłój

This work focuses on the dynamic hedging of financial derivatives, where a reinforcement learning algorithm is designed to minimize the variance of the delta hedging process. In contrast to previous research in this area, we apply…

Optimization and Control · Mathematics 2023-06-21 Cong Zheng , Jiafa He , Can Yang

We price and replicate a variety of claims written on the log price $X$ and quadratic variation $[X]$ of a risky asset, modeled as a positive semimartingale, subject to stochastic volatility and jumps. The pricing and hedging formulas do…

Mathematical Finance · Quantitative Finance 2021-07-02 Peter Carr , Roger Lee , Matthew Lorig

In this paper we propose a novel pricing-hedging framework for volatility derivatives which simultaneously takes into account rough volatility and volatility jumps. Our model directly targets the instantaneous variance of a risky asset and…

Pricing of Securities · Quantitative Finance 2021-11-30 Liang Wang , Weixuan Xia

We develop two alternate approaches to arbitrage-free, market-complete, option pricing. The first approach requires no riskless asset. We develop the general framework for this approach and illustrate it with two specific examples. The…

Pricing of Securities · Quantitative Finance 2024-03-27 W. Brent Lindquist , Svetlozar T. Rachev

We discuss the pricing and hedging of volatility options in some rough volatility models. First, we develop efficient Monte Carlo methods and asymptotic approximations for computing option prices and hedge ratios in models where…

Pricing of Securities · Quantitative Finance 2019-01-31 Blanka Horvath , Antoine Jacquier , Peter Tankov

We provide a model-free pricing-hedging duality in continuous time. For a frictionless market consisting of $d$ risky assets with continuous price trajectories, we show that the purely analytic problem of finding the minimal superhedging…

Mathematical Finance · Quantitative Finance 2019-07-29 Daniel Bartl , Michael Kupper , David J. Prömel , Ludovic Tangpi

This paper shows how reinforcement learning can be used to derive optimal hedging strategies for derivatives when there are transaction costs. The paper illustrates the approach by showing the difference between using delta hedging and…

Computational Finance · Quantitative Finance 2021-03-31 Jay Cao , Jacky Chen , John Hull , Zissis Poulos

A common assumption in financial engineering is that the market price for any derivative coincides with an objectively defined risk-neutral price - a plausible assumption only if traders collectively possess objective knowledge about the…

Pricing of Securities · Quantitative Finance 2013-10-08 Kerry W. Fendick

We present a new approach for the pricing of interest rate derivatives which allows a direct computation of option premiums without deriving a (Black-Scholes type) partial differential equation and without explicitly solving the stochastic…

Statistical Mechanics · Physics 2008-12-02 Matthias Otto

We consider a portfolio with call option and the corresponding underlying asset under the standard assumption that stock-market price represents a random variable with lognormal distribution. Minimizing the variance (hedging risk) of the…

Pricing of Securities · Quantitative Finance 2010-04-27 Vladimir Nikulin

In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such markets in the case of European options. A…

Pricing of Securities · Quantitative Finance 2020-03-19 Josselin Garnier , Knut Solna

We investigate pricing-hedging duality for American options in discrete time financial models where some assets are traded dynamically and others, e.g. a family of European options, only statically. In the first part of the paper we…

Optimization and Control · Mathematics 2017-04-11 Anna Aksamit , Shuoqing Deng , Jan Obłój , Xiaolu Tan

In incomplete financial markets, pricing and hedging European options lack a unique no-arbitrage solution due to unhedgeable risks. This paper introduces a constrained deep learning approach to determine option prices and hedging strategies…

Computational Finance · Quantitative Finance 2025-11-27 Nicolas Baradel