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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

The Constant Elasticity of Variance (CEV) model is mathematically presented and then used in a Credit-Equity hybrid framework. Next, we propose extensions to the CEV model with default: firstly by adding a stochastic volatility diffusion…

Probability · Mathematics 2007-05-23 Marc Atlan , Boris Leblanc

We derive integral tests for the existence and absence of arbitrage in a financial market with one risky asset which is either modeled as stochastic exponential of an Ito process or a positive diffusion with Markov switching. In particular,…

Mathematical Finance · Quantitative Finance 2020-02-13 David Criens

We derive the Black-Scholes-Merton dual equation, which has exactly the same form as the Black-Scholes-Merton equation. The novel and general equation works for options with a payoff of homogeneous of degree one, including European,…

Pricing of Securities · Quantitative Finance 2024-05-20 Shuxin Guo , Qiang Liu

In this paper we study the quality of model-free valuation approaches for financial derivatives by systematically evaluating the difference between model-free super-hedging strategies and the realized payoff of financial derivatives using…

Pricing of Securities · Quantitative Finance 2026-02-18 Zixing Chen , Yihan Qi , Shanlan Que , Julian Sester , Xiao Zhang

We study the construction of arbitrage-free option price surfaces from noisy bid-ask quotes across strike and maturity. Our starting point is a Chebyshev representation of the call price surface on a warped log-moneyness/maturity rectangle,…

Mathematical Finance · Quantitative Finance 2025-12-02 Robert Jenkinson Alvarez

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

New simulation approaches to evaluating path-dependent options without matrix inversion issues nor Euler bias are evaluated. They employ three main contributions: Stochastic approximation replaces regression in the LSM algorithm; Explicit…

Pricing of Securities · Quantitative Finance 2018-04-13 Michael A. Kouritzin

In this study we prove the existence of statistical arbitrage opportunities in the Black-Scholes framework by considering trading strategies that consists of borrowing from the risk free rate and taking a long position in the stock until it…

Mathematical Finance · Quantitative Finance 2014-09-02 Ahmet Goncu

This paper presents a new model for options pricing. The Black-Scholes-Merton (BSM) model plays an important role in financial options pricing. However, the BSM model assumes that the risk-free interest rate, volatility, and equity premium…

Mathematical Finance · Quantitative Finance 2024-08-29 Nicole Hao , Echo Li , Diep Luong-Le

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

In this paper, we consider the pricing and hedging of a financial derivative for an insider trader, in a model-independent setting. In particular, we suppose that the insider wants to act in a way which is independent of any modelling…

Mathematical Finance · Quantitative Finance 2020-06-25 Beatrice Acciaio , Alexander M. G. Cox , Martin Huesmann

This note develops an arbitrage theory for a discrete-time market model without the assumption of the existence of a num\'eraire asset. Fundamental theorems of asset pricing are stated and proven in this context. The distinction between the…

Mathematical Finance · Quantitative Finance 2015-07-07 Michael R. Tehranchi

We consider option hedging in a model where the underlying follows an exponential L\'evy process. We derive approximations to the variance-optimal and to some suboptimal strategies as well as to their mean squared hedging errors. The…

Computational Finance · Quantitative Finance 2017-07-25 Aleš Černý , Stephan Denkl , Jan Kallsen

In this paper, we provide a model-independent extension of the paradigm of dynamic hedging of derivative claims. We relate model-independent replication strategies to local martingales having a closed form which we can characterise via…

Mathematical Finance · Quantitative Finance 2018-10-09 Tigran Atoyan

Proof that under simple assumptions, such as constraints of Put-Call Parity, the probability measure for the valuation of a European option has the mean derived from the forward price which can, but does not have to be the risk-neutral one,…

Mathematical Finance · Quantitative Finance 2016-09-05 Nassim N. Taleb

We explore the role that random arbitrage opportunities play in hedging financial derivatives. We extend the asymptotic pricing theory presented by Fedotov and Panayides [Stochastic arbitrage return and its implication for option pricing,…

Other Condensed Matter · Physics 2009-11-11 Stephanos Panayides

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

In the current literature, the analytical tractability of discrete time option pricing models is guaranteed only for rather specific types of models and pricing kernels. We propose a very general and fully analytical option pricing…

Pricing of Securities · Quantitative Finance 2014-04-15 Adam Aleksander Majewski , Giacomo Bormetti , Fulvio Corsi

Building systems that autonomously create temporal abstractions from data is a key challenge in scaling learning and planning in reinforcement learning. One popular approach for addressing this challenge is the options framework (Sutton et…

Machine Learning · Computer Science 2020-01-01 Matthew Riemer , Miao Liu , Gerald Tesauro