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Accurate option pricing is essential for effective trading and risk management in financial markets, yet it remains challenging due to market volatility and the limitations of traditional models like Black-Scholes. In this paper, we…

Computational Engineering, Finance, and Science · Computer Science 2025-06-09 Feliks Bańka , Jarosław A. Chudziak

The field of portfolio selection is an active research topic, which combines elements and methodologies from various fields, such as optimization, decision analysis, risk management, data science, forecasting, etc. The modeling and…

Portfolio Management · Quantitative Finance 2020-10-28 A. Georgantas

Non-equilibrium phenomena occur not only in physical world, but also in finance. In this work, stochastic relaxational dynamics (together with path integrals) is applied to option pricing theory. A recently proposed model (by Ilinski et…

Statistical Mechanics · Physics 2009-10-31 Matthias Otto

Recorded option pricing datasets are not always freely available. Additionally, these datasets often contain numerous prices which are either higher or lower than can reasonably be expected. Various reasons for these unexpected observations…

Computational Finance · Quantitative Finance 2025-01-22 Jaco Visagie

The problem of identifying the most discriminating features when performing supervised learning has been extensively investigated. In particular, several methods for variable selection in model-based classification have been proposed.…

Applications · Statistics 2020-12-16 Andrea Cappozzo , Francesca Greselin , Thomas Brendan Murphy

Option price data are used as inputs for model calibration, risk-neutral density estimation and many other financial applications. The presence of arbitrage in option price data can lead to poor performance or even failure of these tasks,…

Pricing of Securities · Quantitative Finance 2021-08-24 Samuel N. Cohen , Christoph Reisinger , Sheng Wang

In classic robust optimization, it is assumed that a set of possible parameter realizations, the uncertainty set, is modeled in a previous step and part of the input. As recent work has shown, finding the most suitable uncertainty set is in…

Optimization and Control · Mathematics 2016-10-18 André Chassein , Marc Goerigk

We propose a probabilistic framework for pricing derivatives, which acknowledges that information and beliefs are subjective. Market prices can be translated into implied probabilities. In particular, futures imply returns for these implied…

Pricing of Securities · Quantitative Finance 2010-01-12 Ulrich Kirchner

We study the upper and lower bounds for prices of European and American style options with the possibility of an external termination, meaning that the contract may be terminated at some random time. Under the assumption that the underlying…

Mathematical Finance · Quantitative Finance 2022-12-27 Libo Li , Ruyi Liu , Marek Rutkowski

We construct a statistical indicator for the detection of short-term asset price bubbles based on the information content of bid and ask market quotes for plain vanilla put and call options. Our construction makes use of the martingale…

Pricing of Securities · Quantitative Finance 2018-07-17 Petteri Piiroinen , Lassi Roininen , Tobias Schoden , Martin Simon

One of the shortcomings of the Black and Scholes model on option pricing is the assumption that trading of the underlying asset does not affect the price of that asset. This assumption can be fulfilled only in perfectly liquid markets.…

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

We introduce a local volatility model for the valuation of options on commodity futures by using European vanilla option prices. The corresponding calibration problem is addressed within an online framework, allowing the use of multiple…

Computational Finance · Quantitative Finance 2016-02-16 Vinicius Albani , Uri M. Ascher , Jorge P. Zubelli

This paper explores the application of Machine Learning techniques for pricing high-dimensional options within the framework of the Uncertain Volatility Model (UVM). The UVM is a robust framework that accounts for the inherent…

Computational Finance · Quantitative Finance 2025-06-06 Ludovic Goudenege , Andrea Molent , Antonino Zanette

The inflated beta regression model is widely used for modeling continuous proportions with values at the boundaries. Maximum likelihood estimation for these models is well-known for its sensitivity to outliers, which can severely distort…

Methodology · Statistics 2026-05-15 Francisco Felipe Queiroz , Silvia Lopes de Paula Ferrari

Unbiased and consistent variance estimators generally do not exist for design-based treatment effect estimators because experimenters never observe more than one potential outcome for any unit. The problem is exacerbated by interference and…

Methodology · Statistics 2024-07-04 Christopher Harshaw , Joel A. Middleton , Fredrik Sävje

In robust decision-making under non-Bayesian uncertainty, different robust optimization criteria, such as maximin performance, minimax regret, and maximin ratio, have been proposed. In many problems, all three criteria are well-motivated…

Optimization and Control · Mathematics 2024-03-20 Jerry Anunrojwong , Santiago R. Balseiro , Omar Besbes

Estimating and optimizing Mutual Information (MI) is core to many problems in machine learning; however, bounding MI in high dimensions is challenging. To establish tractable and scalable objectives, recent work has turned to variational…

Machine Learning · Computer Science 2019-05-17 Ben Poole , Sherjil Ozair , Aaron van den Oord , Alexander A. Alemi , George Tucker

Perpetual American options are financial instruments that can be readily exercised and do not mature. In this paper we study in detail the problem of pricing this kind of derivatives, for the most popular flavour, within a framework in…

Pricing of Securities · Quantitative Finance 2009-07-09 Miquel Montero

We propose a method to bound the expectation of the supremum of the price process in stochastic volatility models. It can be applied, for example, to the rough Bergomi model, avoiding the need to discuss finiteness of higher moments. Our…

Probability · Mathematics 2026-03-20 Stefan Gerhold , Julian Pachschwöll , Johannes Ruf

We solve a min-max problem in a robust exploratory mean-variance problem with drift uncertainty in this paper. It is verified that robust investors choose the Sharpe ratio with minimal $L^2$ norm in an admissible set. A reinforcement…

Optimization and Control · Mathematics 2021-08-10 Chenchen Mou , Weiwei Zhang , Chao Zhou