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In this paper we introduce efficient Monte Carlo estimators for the valuation of high-dimensional derivatives and their sensitivities (''Greeks''). These estimators are based on an analytical, usually approximative representation of the…

Computational Finance · Quantitative Finance 2008-12-10 Joerg Kampen , Anastasia Kolodko , John Schoenmakers

This study introduces computation of option sensitivities (Greeks) using the Malliavin calculus under the assumption that the underlying asset and interest rate both evolve from a stochastic volatility model and a stochastic interest rate…

Pricing of Securities · Quantitative Finance 2018-06-18 Bilgi Yilmaz

We present a unified framework for computing CVA sensitivities, hedging the CVA, and assessing CVA risk, using probabilistic machine learning meant as refined regression tools on simulated data, validatable by low-cost companion Monte Carlo…

Computational Finance · Quantitative Finance 2024-07-29 Stéphane Crépey , Botao Li , Hoang Nguyen , Bouazza Saadeddine

We study the use of the multilevel Monte Carlo technique in the context of the calculation of Greeks. The pathwise sensitivity analysis differentiates the path evolution and reduces the payoff's smoothness. This leads to new challenges: the…

Computational Finance · Quantitative Finance 2011-02-08 Sylvestre Burgos , M. B. Giles

The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is…

Computational Finance · Quantitative Finance 2014-08-06 Tetsuya Takaishi

We investigate the use of Antithetic Variables, Control Variates and Importance Sampling to reduce the statistical errors of option sensitivities calculated with the Likelihood Ratio Method in Monte Carlo. We show how Antithetic Variables…

Data Analysis, Statistics and Probability · Physics 2008-08-24 Luca Capriotti

Quasi Monte Carlo (QMC) and Global Sensitivity Analysis (GSA) techniques are applied for pricing and hedging representative financial instruments of increasing complexity. We compare standard Monte Carlo (MC) vs QMC results using Sobol' low…

Computational Finance · Quantitative Finance 2026-02-17 Stefano Scoleri , Marco Bianchetti , Sergei Kucherenko

Variable Annuity (VA) products expose insurance companies to considerable risk because of the guarantees they provide to buyers of these products. Managing and hedging these risks requires insurers to find the value of key risk metrics for…

Computational Finance · Quantitative Finance 2017-01-17 Seyed Amir Hejazi , Kenneth R. Jackson , Guojun Gan

Valuation of Credit Valuation Adjustment (CVA) has become an important field as its calculation is required in Basel III, issued in 2010, in the wake of the credit crisis. Exposure, which is defined as the potential future loss of a default…

Computational Finance · Quantitative Finance 2014-12-12 Q. Feng , C. W. Oosterlee

Conditional Monte Carlo (CMC) has been widely used for sensitivity estimation with discontinuous integrands as a standard simulation technique. A major limitation of using CMC in this context is that finding conditioning variables to ensure…

Probability · Mathematics 2016-03-22 Guiyun Feng , Guangwu Liu

We discuss the pricing and hedging of volatility options in some rough volatility models. First, we develop efficient Monte Carlo methods and asymptotic approximations for computing option prices and hedge ratios in models where…

Pricing of Securities · Quantitative Finance 2019-01-31 Blanka Horvath , Antoine Jacquier , Peter Tankov

High precision analytical approximation is proposed for variance-covariance based risk allocation in a portfolio of risky assets. A general case of a single-period multi-factor Merton-type model with stochastic recovery is considered. The…

Risk Management · Quantitative Finance 2009-09-28 Mikhail Voropaev

The valuation of over-the-counter derivatives is subject to a series of valuation adjustments known as xVA, which pose additional risks for financial institutions. Associated risk measures, such as the value-at-risk of an underlying…

Computational Finance · Quantitative Finance 2024-05-24 Michael B. Giles , Abdul-Lateef Haji-Ali , Jonathan Spence

We consider the problem of forecasting debt recovery from large portfolios of non-performing unsecured consumer loans under management. The state of the art in industry is to use stochastic processes to approximately model payment behaviour…

Computation · Statistics 2022-10-26 Sam Baynes , Simon Cotter , Paul Russell , Edmund Ryan , Timothy Waite

Using Malliavin calculus techniques, we obtain formulas for computing Greeks under different rough Volterra stochastic volatility models. Due to the fact that underlying prices are not always square integrable, we extend the classical…

Mathematical Finance · Quantitative Finance 2025-07-08 Mishari Al-Foraih , Òscar Burés , Jan Pospíšil , Josep Vives

This paper investigates the valuation of variable annuity contracts with an early surrender option under non-Markovian models. Moreover, policyholders are provided with guaranteed minimum maturity and death benefits to protect against the…

Computational Finance · Quantitative Finance 2026-04-23 Wenyuan Li , Haoqi Lyu

Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo…

General Economics · Economics 2020-11-17 Seyed Mohammad Sina Seyfi , Azin Sharifi , Hamidreza Arian

The computation of Greeks is a fundamental task for risk managing of financial instruments. The standard approach to their numerical evaluation is via finite differences. Most exotic derivatives are priced via Monte Carlo simulation: in…

Computational Finance · Quantitative Finance 2021-06-24 Andrea Maran , Andrea Pallavicini , Stefano Scoleri

Engineering risk is concerned with the likelihood of failure and the scenarios when it occurs. The sensitivity of failure probability to change in system parameters is relevant to risk-informed decision making. Computing sensitivity is at…

Methodology · Statistics 2025-12-19 Siu-Kui Au , Zi-Jun Cao

The aim of this paper is to describe a new an integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous methodologies.…

Risk Management · Quantitative Finance 2024-06-06 Fernando Acebes , M Pereda , David Poza , Javier Pajares , Jose M Galan
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