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This paper investigates the pricing of European-style lookback options when the price dynamics of the underlying risky asset are assumed to follow a Markov-modulated Geo-metric Brownian motion; that is, the appreciation rate and the…

Pricing of Securities · Quantitative Finance 2014-07-21 Leunglung Chan , Song-Ping Zhu

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

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

Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under…

Mathematical Finance · Quantitative Finance 2017-03-16 Omar El Euch , Mathieu Rosenbaum

By the classical Martingale Representation Theorem, replication of random vectors can be achieved via stochastic integrals or solutions of stochastic differential equations. We introduce a new approach to replication of random vectors via…

Portfolio Management · Quantitative Finance 2013-08-01 Nikolai Dokuchaev

We study the problem of reconstructing the Faber--Schauder coefficients of a continuous function $f$ from discrete observations of its antiderivative $F$. For instance, this question arises in financial mathematics when estimating the…

Numerical Analysis · Mathematics 2024-10-14 Xiyue Han , Alexander Schied

Motivated by the model- independent pricing of derivatives calibrated to the real market, we consider an optimization problem similar to the optimal Skorokhod embedding problem, where the embedded Brownian motion needs only to reproduce a…

Probability · Mathematics 2017-01-31 Gaoyue Guo

We consider the robust pricing and hedging of American options in a continuous time setting. We assume asset prices are continuous semimartingales, but we allow for general model uncertainty specification via adapted closed convex…

Mathematical Finance · Quantitative Finance 2025-10-08 Ivan Guo , Jan Obłój

This article is the second one in a series on the use of scaling invariance in finance. In the first article (cond-mat/9906048), we introduced a new formalism for the pricing of derivative securities, which focusses on tradable objects…

Condensed Matter · Physics 2007-05-23 Jiri Hoogland , Dimitri Neumann

We consider the pricing of derivatives in a setting with trading restrictions, but without any probabilistic assumptions on the underlying model, in discrete and continuous time. In particular, we assume that European put or call options…

Mathematical Finance · Quantitative Finance 2015-06-09 Alexander M. G. Cox , Zhaoxu Hou , Jan Obloj

In this paper we extend discrete time semi-static trading strategies by also allowing for dynamic trading in a finite amount of options, and we study the consequences for the model-independent super-replication prices of exotic derivatives.…

Mathematical Finance · Quantitative Finance 2021-07-20 Ariel Neufeld , Julian Sester

This paper studies equity basket options -- i.e., multi-dimensional derivatives whose payoffs depend on the value of a weighted sum of the underlying stocks -- and develops a new and innovative approach to ensure consistency between options…

Computational Finance · Quantitative Finance 2022-06-22 Lech A. Grzelak , Juliusz Jablecki , Dariusz Gatarek

This paper examines the applicability of the Skorokhod representation theorem in filtrated probability spaces for the utility maximization problem in the Kabanov conic model of multi-asset markets with proportional transaction costs. A key…

Probability · Mathematics 2025-09-08 Artur Sidorenko

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We…

Computational Finance · Quantitative Finance 2018-02-12 Hans Bühler , Lukas Gonon , Josef Teichmann , Ben Wood

A general method to construct recombinant tree approximations for stochastic volatility models is developed and applied to the Heston model for stock price dynamics. In this application, the resulting approximation is a four tuple Markov…

Computational Finance · Quantitative Finance 2016-08-14 Erdinç Akyıldırım , Yan Dolinsky , H. Mete Soner

We solve the $n$-marginal Skorokhod embedding problem for a continuous local martingale and a sequence of probability measures $\mu_1,...,\mu_n$ which are in convex order and satisfy an additional technical assumption. Our construction is…

Probability · Mathematics 2014-01-07 Jan Obłój , Peter Spoida

The proposed model modifies option pricing formulas for the basic case of log-normal probability distribution providing correspondence to formulated criteria of efficiency and completeness. The model is self-calibrating by historic…

Pricing of Securities · Quantitative Finance 2008-12-02 Pavel Levin

Using microscopic price models based on Hawkes processes, it has been shown that under some no-arbitrage condition, the high degree of endogeneity of markets together with the phenomenon of metaorders splitting generate rough Heston-type…

Statistical Finance · Quantitative Finance 2021-01-20 Aditi Dandapani , Paul Jusselin , Mathieu Rosenbaum

We study an optimal investment/consumption problem in a model capturing market and credit risk dependencies. Stochastic factors drive both the default intensity and the volatility of the stocks in the portfolio. We use the martingale…

Mathematical Finance · Quantitative Finance 2018-06-20 Lijun Bo , Agostino Capponi

The standard Black-Scholes theory of option pricing is extended to cope with underlying return fluctuations described by general probability distributions. A Langevin process and its related Fokker-Planck equation are devised to model the…

Physics and Society · Physics 2009-11-11 L. Moriconi