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Related papers: Path weighting sensitivities

200 papers

We develop a Fourier approach to rough path integration, based on the series decomposition of continuous functions in terms of Schauder functions. Our approach is rather elementary, the main ingredient being a simple commutator estimate,…

Probability · Mathematics 2014-10-16 Massimiliano Gubinelli , Peter Imkeller , Nicolas Perkowski

In the paper written by Klibanov et al, it proposes a novel method to calculate implied volatility of a European stock options as a solution to ill-posed inverse problem for the Black-Scholes equation. In addition, it proposes a trading…

Numerical Analysis · Mathematics 2025-01-29 Wanchaloem Wunkaew , Yuqing Liu , Kirill V. Golubnichiy

We present a new methodology for computing sensitivities in evolutionary systems using a model-driven low-rank approximation. To this end, we formulate a variational principle that seeks to minimize the distance between the time derivative…

Optimization and Control · Mathematics 2020-12-29 Michael Donello , Mark Carpenter , Hessam Babaee

We propose a generic calibration framework to both vanilla and no-touch options for a large class of continuous semi-martingale models. The method builds upon the forward partial integro-differential equation (PIDE) derived in Hambly et al.…

Mathematical Finance · Quantitative Finance 2025-11-19 Alan Bain , Matthieu Mariapragassam , Christoph Reisinger

Sensitivity analysis in probabilistic discrete graphical models is usually conducted by varying one probability value at a time and observing how this affects output probabilities of interest. When one probability is varied then others are…

Statistics Theory · Mathematics 2021-01-14 Manuele Leonelli , Eva Riccomagno

In dynamic discrete choice models, some parameters, such as the discount factor, are being fixed instead of being estimated. This paper proposes two sensitivity analysis procedures for dynamic discrete choice models with respect to the…

Econometrics · Economics 2024-08-30 Chun Pong Lau

Inference and prediction of routes have become of interest over the past decade owing to a dramatic increase in package delivery and ride-sharing services. Given the underlying combinatorial structure and the incorporation of probabilities,…

Logic in Computer Science · Computer Science 2023-06-21 Suwei Yang , Victor C. Liang , Kuldeep S. Meel

Uncertainties exist in both physics-based and data-driven models. Variance-based sensitivity analysis characterizes how the variance of a model output is propagated from the model inputs. The Sobol index is one of the most widely used…

Methodology · Statistics 2020-06-09 Zhanlin Liu , Youngjun Choe

In this paper we use convolutional neural networks to find the H\"older exponent of simulated sample paths of the rBergomi model, a recently proposed stock price model used in mathematical finance. We contextualise this as a calibration…

Computational Finance · Quantitative Finance 2019-07-30 Henry Stone

We introduce a new method of proving pathwise uniqueness, and we apply it to the degenerate stochastic differential equation \[dX_t=|X_t|^{\alpha} dW_t,\] where $W_t$ is a one-dimensional Brownian motion and $\alpha\in(0,1/2)$. Weak…

Probability · Mathematics 2009-09-29 Richard F. Bass , Krzysztof Burdzy , Zhen-Qing Chen

Varying coefficient model is often used in statistical modeling since it is more flexible than the parametric model. However, model detection and variable selection of varying coefficient model are poorly understood in mode regression.…

Methodology · Statistics 2020-09-23 Xuejun Ma , Yue Du , Jingli Wang

Parametric path problems arise independently in diverse domains, ranging from transportation to finance, where they are studied under various assumptions. We formulate a general path problem with relaxed assumptions, and describe how this…

Data Structures and Algorithms · Computer Science 2021-06-08 Prerona Chatterjee , Kshitij Gajjar , Jaikumar Radhakrishnan , Girish Varma

In this work we present an analytical model, based on the path-integral formalism of Statistical Mechanics, for pricing options using first-passage time problems involving both fixed and deterministically moving absorbing barriers under…

Mathematical Finance · Quantitative Finance 2018-04-24 Andre Catalao , Rogerio Rosenfeld

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is…

Quantum Physics · Physics 2025-12-08 Amir Kalev , Itay Hen

For a given statistical model, it often happens that it is necessary to intervene the model to reduce the variances of the output variables. In structural equation models, this can be done by changing the values of the path coefficients by…

Methodology · Statistics 2011-08-16 Kentaro Tanaka , Atsushi Yagishita , Masami Miyakawa

A heuristic formula for 5-point approximation of the first derivative of an unknown function whose values are measured with an error at unequally spaced points is proposed. The derivative at a given point is calculated using the effective…

Data Analysis, Statistics and Probability · Physics 2022-09-14 Emmanuil Beygelzimer , Yan Beygelzimer

In this companion to our letter (arXiv:2208.10514), we elaborate the full details of the predicted corrections to the primordial scalar and tensor power spectra that arise from quantum gravity-motivated, natural, covariant ultraviolet…

High Energy Physics - Theory · Physics 2023-06-07 Aidan Chatwin-Davies , Achim Kempf , Petar Simidzija

We develop the path integral formalism for studying cosmological perturbations in multi-field inflation, which is particularly well suited to study quantum theories with gauge symmetries such as diffeomorphism invariance. We formulate the…

High Energy Physics - Theory · Physics 2016-08-24 Jinn-Ouk Gong , Min-Seok Seo , Gary Shiu

The usage of a spot volatility estimate based on a volatility decomposition in a time-changed price-model according to the trading times is investigated. In this model clock-time volatility splits up into the product of tick-time volatility…

Probability · Mathematics 2016-05-10 Rainer Dahlhaus , Sophon Tunyavetchakit

Stochastic differential equation (SDE) models are the foundation for pricing and hedging financial derivatives. The drift and volatility functions in SDE models are typically chosen to be algebraic functions with a small number (less than…

Computational Finance · Quantitative Finance 2024-06-04 Lei Fan , Justin Sirignano