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This paper introduces a relative model risk measure of a product priced with a given model, with respect to another reference model for which the market is assumed to be driven. This measure allows comparing products valued with different…

Risk Management · Quantitative Finance 2015-03-19 Alberto Elices , Eduard Giménez

We introduce an additive stochastic mortality model which allows joint modelling and forecasting of underlying death causes. Parameter families for mortality trends can be chosen freely. As model settings become high dimensional, Markov…

Risk Management · Quantitative Finance 2017-05-02 Jonas Hirz , Uwe Schmock , Pavel V. Shevchenko

Through the Bayesian lens of data assimilation, uncertainty on model parameters is traditionally quantified through the posterior covariance matrix. However, in modern settings involving high-dimensional and computationally expensive…

Computation · Statistics 2023-11-16 Michael Stanley , Mikael Kuusela , Brendan Byrne , Junjie Liu

Valuation adjustments, collectively named XVA, play an important role in modern derivatives pricing to take into account additional price components such as counterparty and funding risk premia. They are an exotic price component carrying a…

Pricing of Securities · Quantitative Finance 2025-03-06 Lorenzo Silotto , Marco Scaringi , Marco Bianchetti

Recent years have seen an increased level of interest in pricing equity options under a stochastic volatility model such as the Heston model. Often, simulating a Heston model is difficult, as a standard finite difference scheme may lead to…

Computational Finance · Quantitative Finance 2011-11-28 Ian Iscoe , Asif Lakhany

Cr\'epey, Frikha, and Louzi (2025) introduced a multilevel stochastic approximation scheme to compute the value-at-risk of a financial loss that is only simulatable by Monte Carlo. The best complexity of the scheme is in…

Risk Management · Quantitative Finance 2026-04-14 Stéphane Crépey , Noufel Frikha , Azar Louzi , Jonathan Spence

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the…

Computational Finance · Quantitative Finance 2014-08-15 Tetsuya Takaishi

This paper adresses the general issue of estimating the sensitivity of the expectation of a random variable with respect to a parameter characterizing its evolution. In finance for example, the sensitivities of the price of a contingent…

Computational Finance · Quantitative Finance 2009-09-15 Romuald Elie

We present a new volatility model, simple to implement, that includes a leverage effect whose return-volatility correlation function fits to empirical observations. This model is able to capture both the "retarded effect" induced by the…

Statistical Finance · Quantitative Finance 2020-01-03 Sebastien Valeyre , Denis Grebenkov , Sofiane Aboura , Qian Liu

This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma…

Portfolio Management · Quantitative Finance 2011-11-08 Yang Li , Traian A Pirvu

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of…

Statistical Mechanics · Physics 2008-12-02 T. Di Matteo , T. Aste , M. M. Dacorogna

In this paper, we study the computation of sensitivities with respect to spot of path dependent financial derivatives by means of path weighting. We propose explicit path weighting formula and variance reduction adjustment in order to…

Probability · Mathematics 2024-11-21 Liu Xuan , Gauthier Michel

This paper proposes a Monte Carlo technique for pricing the forward yield to maturity, when the volatility of the zero-coupon bond is known. We make the assumption of deterministic default intensity (Hazard Rate Function). We make no…

Computational Finance · Quantitative Finance 2012-04-23 Didier Kouokap Youmbi

The rough Bergomi (rBergomi) model, introduced recently in [5], is a promising rough volatility model in quantitative finance. It is a parsimonious model depending on only three parameters, and yet remarkably fits with empirical implied…

Computational Finance · Quantitative Finance 2020-07-13 Christian Bayer , Chiheb Ben Hammouda , Raul Tempone

Reliability analysis is a sub-field of uncertainty quantification that assesses the probability of a system performing as intended under various uncertainties. Traditionally, this analysis relies on deterministic models, where experiments…

Computation · Statistics 2026-05-19 Anderson V. Pires , Maliki Moustapha , Stefano Marelli , Bruno Sudret

The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the…

Pricing of Securities · Quantitative Finance 2014-09-19 José Da Fonseca , Claude Martini

We propose a method for extending a given asset pricing formula to account for two additional sources of risk: the risk associated with future changes in market--calibrated parameters and the remaining risk associated with idiosyncratic…

Disordered Systems and Neural Networks · Physics 2008-12-02 T. R. Hurd

This paper explores the effectiveness of high-frequency options trading strategies enhanced by advanced portfolio optimization techniques, investigating their ability to consistently generate positive returns compared to traditional long or…

Trading and Market Microstructure · Quantitative Finance 2024-08-19 Sid Bhatia

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic…

This paper considers the pricing of equity-linked life insurance contracts with death and survival benefits in a general model with multiple stochastic risk factors: interest rate, equity, volatility, unsystematic and systematic mortality.…

Pricing of Securities · Quantitative Finance 2021-11-03 Karim Barigou , Lukasz Delong
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