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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

An optimal control problem is considered for a stochastic differential equation containing a state-dependent regime switching, with a recursive cost functional. Due to the non-exponential discounting in the cost functional, the problem is…

Optimization and Control · Mathematics 2017-12-29 Hongwei Mei , Jiongmin Yong

We propose the deep parametric PDE method to solve high-dimensional parametric partial differential equations. A single neural network approximates the solution of a whole family of PDEs after being trained without the need of sample…

Computational Finance · Quantitative Finance 2020-12-14 Kathrin Glau , Linus Wunderlich

Statistical arbitrage exploits temporal price differences between similar assets. We develop a unifying conceptual framework for statistical arbitrage and a novel data driven solution. First, we construct arbitrage portfolios of similar…

Machine Learning · Computer Science 2022-10-11 Jorge Guijarro-Ordonez , Markus Pelger , Greg Zanotti

Continuous time financial market models are often motivated as scaling limits of discrete time models. The objective of this paper is to establish such a connection for a robust framework. More specifically, we consider discrete time models…

Probability · Mathematics 2024-10-17 David Criens

Since the introduction of the Black-Scholes model stochastic processes have played an increasingly important role in mathematical finance. In many cases prices, volatility and other quantities can be modeled using stochastic ordinary…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Yin Mei Wong , Joshua Wilkie

The analysis of Temporal Difference (TD) learning in the average-reward setting faces notable theoretical difficulties because the Bellman operator is not contractive with respect to any norm. This complicates standard analyses of…

Machine Learning · Computer Science 2026-05-05 Haoxing Tian , Zaiwei Chen , Ioannis Ch. Paschalidis , Alex Olshevsky

Under a Bayesian framework, we formulate the fully sequential sampling and selection decision in statistical ranking and selection as a stochastic control problem, and derive the associated Bellman equation. Using value function…

Machine Learning · Computer Science 2017-10-10 Yijie Peng , Edwin K. P. Chong , Chun-Hung Chen , Michael C. Fu

In the paper, the martingales and super-martingales relative to a regular set of measures are systematically studied. The notion of local regular super-martingale relative to a set of equivalent measures is introduced and the necessary and…

Statistical Finance · Quantitative Finance 2018-10-23 N. S. Gonchar

We consider a general path-dependent version of the hedging problem with price impact of Bouchard et al. (2019), in which a dual formulation for the super-hedging price is obtained by means of PDE arguments, in a Markovian setting and under…

Probability · Mathematics 2020-01-09 Bruno Bouchard , Xiaolu Tan

The determination of acceptability prices of contingent claims requires the choice of a stochastic model for the underlying asset price dynamics. Given this model, optimal bid and ask prices can be found by stochastic optimization. However,…

Pricing of Securities · Quantitative Finance 2019-01-31 Martin Glanzer , Georg Ch. Pflug , Alois Pichler

When sales of a product are affected by randomness in demand, retailers can use dynamic pricing strategies to maximise their profits. In this article the pricing problem is formulated as a stochastic optimal control problem, where the…

Optimization and Control · Mathematics 2017-10-17 Asbjørn N. Riseth , Jeff N. Dewynne , Chris L. Farmer

We investigate discrete-time mean-variance portfolio selection problems viewed as a Markov decision process. We transform the problems into a new model with deterministic transition function for which the Bellman optimality equation holds.…

Optimization and Control · Mathematics 2025-09-23 Nicole Bäuerle , Anna Jaśkiewicz

A standing assumption in the literature on proportional transaction costs is efficient friction. Together with robust no free lunch with vanishing risk, it rules out strategies of infinite variation, as they usually appear in frictionless…

Mathematical Finance · Quantitative Finance 2023-06-21 Christoph Kühn , Alexander Molitor

Option pricing is an integral part of modern financial risk management. The well-known Black and Scholes (1973) formula is commonly used for this purpose. This paper is an attempt to extend their work to a situation in which the…

Pricing of Securities · Quantitative Finance 2013-04-18 Youssef El-Khatib , Abdulnasser Hatemi-J

In a model free discrete time financial market, we prove the superhedging duality theorem, where trading is allowed with dynamic and semi-static strategies. We also show that the initial cost of the cheapest portfolio that dominates a…

Mathematical Finance · Quantitative Finance 2016-05-03 Matteo Burzoni , Marco Frittelli , Marco Maggis

Duality for robust hedging with proportional transaction costs of path dependent European options is obtained in a discrete time financial market with one risky asset. Investor's portfolio consists of a dynamically traded stock and a static…

Portfolio Management · Quantitative Finance 2013-08-30 Yan Dolinsky , H. Mete Soner

When stochastic control problems do not possess separability and/or monotonicity, the dynamic programming pioneered by Bellman in 1950s fails to work as a time-decomposition solution method. Such cases have posted a great challenge to the…

Optimization and Control · Mathematics 2020-10-20 Xin Huang , Duan Li , Daniel Zhuoyu Long

We analyse derivative securities whose value is NOT a deterministic function of an underlying which means presence of a basis risk at any time. The key object of our analysis is conditional probability distribution at a given underlying…

Probability · Mathematics 2008-12-10 S. Esipov , I. Vaysburd

Neural marked temporal point processes have been a valuable addition to the existing toolbox of statistical parametric models for continuous-time event data. These models are useful for sequences where each event is associated with a single…

Machine Learning · Computer Science 2024-03-20 Yuxin Chang , Alex Boyd , Padhraic Smyth
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