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Surrender poses one of the major risks to life insurance and a sound modeling of its true probability has direct implication on the risk capital demanded by the Solvency II directive. We add to the existing literature by performing…

Risk Management · Quantitative Finance 2021-08-30 Mark Kiermayer

Measures of concordance have been widely used in insurance and risk management to summarize non-linear dependence among risks modeled by random variables, which Pearson's correlation coefficient cannot capture. However, popular measures of…

Statistics Theory · Mathematics 2019-03-19 Marius Hofert , Takaaki Koike

Least squares Monte Carlo methods are a popular numerical approximation method for solving stochastic control problems. Based on dynamic programming, their key feature is the approximation of the conditional expectation of future rewards by…

Optimization and Control · Mathematics 2022-03-28 Christian Bayer , Denis Belomestny , Paul Hager , Paolo Pigato , John Schoenmakers , Vladimir Spokoiny

This article proposes omnibus portmanteau tests for contrasting adequacy of time series models. The test statistics are based on combining the autocorrelation function of the conditional residuals, the autocorrelation function of the…

Methodology · Statistics 2024-02-02 Esam Mahdi

The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management…

Risk Management · Quantitative Finance 2024-06-03 Fernando Acebes , José Manuel González-Varona , Adolfo López-Paredes , Javier Pajares

Equivalent characterizations of multiportfolio time consistency are deduced for closed convex and coherent set-valued risk measures on $L^p(\Omega,\mathcal F, P; R^d)$ with image space in the power set of $L^p(\Omega,\mathcal F_t,P;R^d)$.…

Risk Management · Quantitative Finance 2017-01-27 Zachary Feinstein , Birgit Rudloff

Accurately and efficiently estimating system performance under uncertainty is paramount in power system planning and operation. Monte Carlo simulation is often used for this purpose, but convergence may be slow, especially when detailed…

Computation · Statistics 2020-10-23 Simon Tindemans , Goran Strbac

The underlying stochastic nature of the requirements for the Solvency II regulations has introduced significant challenges if the required calculations are to be performed correctly, without resorting to excessive approximations, within…

Computational Finance · Quantitative Finance 2014-06-30 Mark Tucker , J. Mark Bull

We are concerned with the market-consistent valuation of lifelong health insurance products, which are subject to adjustments derived from the actuarial equivalence principle and driven by (medical) inflation. Such products are…

Mathematical Finance · Quantitative Finance 2026-04-30 Simon Hochgerner , Jonas Ingmanns , Nicole Kastanek

Computing risk measures of a financial portfolio comprising thousands of derivatives is a challenging problem because (a) it involves a nested expectation requiring multiple evaluations of the loss of the financial portfolio for different…

Mathematical Finance · Quantitative Finance 2023-01-10 Michael B. Giles , Abdul-Lateef Haji-Ali

We propose a highly efficient and accurate methodology for generating synthetic financial market data using a diffusion model approach. The synthetic data produced by our methodology align closely with observed market data in several key…

Computational Finance · Quantitative Finance 2025-02-04 Andrew Lesniewski , Giulio Trigila

Expanding on techniques of concentration of measure, we develop a quantitative framework for modeling liquidity risk using convex risk measures. The fundamental objects of study are curves of the form $(\rho(\lambda X))_{\lambda \ge 0}$,…

Risk Management · Quantitative Finance 2015-10-28 Daniel Lacker

In the framework of Embedded Value new standards, namely the MCEV norms, the latest principles published in June 2008 address the issue of market and underwriting risks measurement by using stochastic models of projection and valorization.…

Risk Management · Quantitative Finance 2010-01-13 Jean-Paul Félix , Frédéric Planchet

We study the feature-scaled version of the Monte Carlo algorithm with linear function approximation. This algorithm converges to a scale-invariant solution, which is not unduly affected by states having feature vectors with large norms. The…

Machine Learning · Computer Science 2022-05-31 Rahul Madhavan , Hemanta Makwana

We introduce \textsc{CAT}, a framework designed to evaluate and visualize the \emph{interplay} of \emph{accuracy} and \emph{response consistency} of Large Language Models (LLMs) under controllable input variations, using multiple-choice…

Computation and Language · Computer Science 2026-01-01 Paulo Cavalin , Cassia Sanctos , Marcelo Grave , Claudio Pinhanez , Yago Primerano

An algorithm is proposed that enables the imposition of shape constraints on regression curves, without requiring the constraints to be written as closed-form expressions, nor assuming the functional form of the loss function. This…

Methodology · Statistics 2019-04-08 Kenyon Ng , Berwin A. Turlach , Kevin Murray

Solvency II Directive 2009/138/EC requires an insurance and reinsurance undertakings assessment of a Solvency Capital Requirement by means of the so-called "Standard Formula" or by means of partial or full internal models. Focusing on the…

Risk Management · Quantitative Finance 2018-01-30 Fabio Baione , Paolo De Angelis , Ivan Granito

The paper provides a stochastic model useful for assessing the capital requirement for demographic risk. The model extends to the market consistent context classical methodologies developed in a local accounting framework. In particular we…

Risk Management · Quantitative Finance 2022-01-12 Gian Paolo Clemente , Francesco Della Corte , Nino Savelli

The European insurance sector will soon be faced with the application of Solvency 2 regulation norms. It will create a real change in risk management practices. The ORSA approach of the second pillar makes the capital allocation an…

Risk Management · Quantitative Finance 2015-06-15 Véronique Maume-Deschamps , Didier Rullière , Khalil Said

Quasi-Monte Carlo (QMC) method is a useful numerical tool for pricing and hedging of complex financial derivatives. These problems are usually of high dimensionality and discontinuities. The two factors may significantly deteriorate the…

Numerical Analysis · Mathematics 2019-02-27 Zhijian He , Xiaoqun Wang