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Related papers: Delta Hedging without the Black-Scholes Formula

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We consider a non-stochastic online learning approach to price financial options by modeling the market dynamic as a repeated game between the nature (adversary) and the investor. We demonstrate that such framework yields analogous…

Data Structures and Algorithms · Computer Science 2014-06-25 Henry Lam , Zhenming Liu

The paper proposes a different method of solving a simplified version of the Black-Scholes equation. This paper will discuss the importance of the Black-Scholes equation and its applications in finance.

Pricing of Securities · Quantitative Finance 2016-12-30 Binur Yermukanova , Laila Zhexembay , Natanael Karjanto

The author presents alternatives to the Black-Scholes european call option pricing model by incorporating different transaction cost structures in the replicating strategy. In particular, an exponentially decreasing structure is proposed…

Risk Management · Quantitative Finance 2021-12-21 F. G. Bellora , G. Mazzei , M. Maurette

We investigate the problem of pricing and hedging derivatives of Electricity Futures contract when the underlying asset is not available. We propose to use a cross hedging strategy based on the Futures contract covering the larger delivery…

Pricing of Securities · Quantitative Finance 2014-02-03 Adrien Nguyen Huu , Nadia Oudjane

We solve the superhedging problem for European options in an illiquid extension of the Black-Scholes model, in which transactions have transient price impact and the costs and the strategies for hedging are affected by physical or cash…

Pricing of Securities · Quantitative Finance 2023-06-13 Dirk Becherer , Todor Bilarev

In this paper we present a locally one-dimensional (LOD) splitting method to solve numerically the two-dimensional Black-Scholes equation, arising in the Hull & White model for pricing European options with stochastic volatility,…

Numerical Analysis · Mathematics 2015-07-20 T. Chernogorova , R. Valkov

This paper introduces a novel methodology for the pricing and management of share buyback contracts, overcoming the limitations of traditional optimal control methods, which frequently encounter difficulties with high-dimensional state…

Pricing of Securities · Quantitative Finance 2024-07-15 Bastien Baldacci , Philippe Bergault , Olivier Guéant

We consider the hedging error of a derivative due to discrete trading in the presence of a drift in the dynamics of the underlying asset. We suppose that the trader wishes to find rebalancing times for the hedging portfolio which enable him…

Probability · Mathematics 2014-07-18 Jiatu Cai , Masaaki Fukasawa , Mathieu Rosenbaum , Peter Tankov

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 investigate a nonlinear generalization of the Black-Scholes equation for pricing American style call options in which the volatility term may depend on the underlying asset price and the Gamma of the option. We propose a…

Computational Finance · Quantitative Finance 2018-06-14 Maria do Rosario Grossinho , Yaser Faghan Kord , Daniel Sevcovic

Newton's method is the most widespread high-order method, demanding the gradient and the Hessian of the objective function. However, one of the main disadvantages of Newtons method is its lack of global convergence and high iteration cost.…

We propose a novel Black-Scholes model under which the stock price processes are modeled by stochastic differential equations driven by sub-diffusions. The new framework can capture the less financial activity phenomenon during the bear…

Probability · Mathematics 2025-11-14 Shuaiqi Zhang , Zhen-Qing Chen

The problem of stock hedging is reconsidered in this paper, where a put option is chosen from a set of available put options to hedge the market risk of a stock. A formula is proposed to determine the probability that the potential loss…

Risk Management · Quantitative Finance 2011-10-04 Guanghui Huang , Jing Xu , Wenting Xing

Hedging in the presence of transaction costs leads to complex optimization problems. These problems typically lack closed-form solutions, and their implementation relies on numerical methods that provide hedging strategies for specific…

Risk Management · Quantitative Finance 2013-05-30 Terje Lensberg , Klaus Reiner Schenk-Hoppé

We consider the jump-diffusion risky asset model and study its conditional prediction laws. Next, we explain the conditional least square hedging strategy and calculate its closed form for the jump-diffusion model, considering the…

Mathematical Finance · Quantitative Finance 2024-08-21 Hamidreza Maleki Almani , Foad Shokrollahi , Tommi Sottinen

Hedging strategies in bond markets are computed by martingale representation and the Clark-Ocone formula under the choice of a suitable of numeraire, in a model driven by the dynamics of bond prices. Applications are given to the hedging of…

Pricing of Securities · Quantitative Finance 2013-04-24 Nicolas Privault , Timothy Robin Teng

This paper develops a novel analytically tractable Neumann series of Bessel functions representation for pricing (and hedging) European-style double barrier knock-out options, which can be applied to the whole class of one-dimensional…

Computational Finance · Quantitative Finance 2017-12-25 Igor V. Kravchenko , Vladislav V. Kravchenko , Sergii M. Torba , José Carlos Dias

We apply Gauge Theory of Arbitrage (GTA) {hep-th/9710148} to derivative pricing. We show how the standard results of Black-Scholes analysis appear from GTA and derive correction to the Black-Scholes equation due to a virtual arbitrage and…

High Energy Physics - Theory · Physics 2009-02-20 Kirill Ilinski , Gleb Kalinin

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

Epistemic uncertainty quantification is a crucial part of drawing credible conclusions from predictive models, whether concerned about the prediction at a given point or any downstream evaluation that uses the model as input. When the…

Machine Learning · Statistics 2022-11-15 Nathan Kallus , James McInerney