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Systemic risk is the risk that a company- or industry-level risk could trigger a huge collapse of another or even the whole institution. Various systemic risk measures have been proposed in the literature to quantify the domino and…

Risk Management · Quantitative Finance 2024-05-14 Tong Pu , Yifei Zhang , Yiying Zhang

This paper investigates the state estimation problem for a class of complex networks, in which the dynamics of each node is subject to Gaussian noise, system uncertainties and nonlinearities. Based on a regularized least-squares approach,…

Systems and Control · Electrical Eng. & Systems 2021-03-16 Peihu Duan , Qishao Wang , Zhisheng Duan , Guanrong Chen

Portfolio optimization in real-world financial markets is notoriously difficult due to non-stationarity, noisy data, and high transaction costs. Standard predict-then-optimize methods first forecast returns and then solve for weights,…

Portfolio Management · Quantitative Finance 2026-05-29 Rahul Fernandes , Travis Desell

We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints, possibly corrupted by noise. Based on duality of convex programming, we present a novel…

Optimization and Control · Mathematics 2019-10-22 Tobias Sutter , David Sutter , Peyman Mohajerin Esfahani , John Lygeros

We study a discrete-time multi-period portfolio optimization problem under an explicit constraint on the Deviation Conditional Value-at-Risk (DCVaR), defined as the excess of Conditional Value-at-Risk over expected terminal wealth. The…

Portfolio Management · Quantitative Finance 2026-04-17 Jérôme Lelong , Véronique Maume-Deschamps , William Thevenot

This paper examines the usefulness of high frequency data in estimating the covariance matrix for portfolio choice when the portfolio size is large. A computationally convenient nonlinear shrinkage estimator for the integrated covariance…

Statistics Theory · Mathematics 2016-11-22 Cheng Liu , Ningning Xia , Jun Yu

Censored quantile regression (CQR) has become a valuable tool to study the heterogeneous association between a possibly censored outcome and a set of covariates, yet computation and statistical inference for CQR have remained a challenge…

Statistics Theory · Mathematics 2022-10-25 Xuming He , Xiaoou Pan , Kean Ming Tan , Wen-Xin Zhou

A positive correlation between exposure and counterparty credit risk gives rise to the so-called Wrong-Way Risk (WWR). Even after a decade of the financial crisis, addressing WWR in both sound and tractable ways remains challenging.…

Risk Management · Quantitative Finance 2021-07-15 Ashish Kumar , Laszlo Markus , Norbert Hari

Expected Shortfall (ES, also known as CVaR) is the most important coherent risk measure in finance, insurance, risk management, and engineering. Recently, Wang and Zitikis (2021) put forward four economic axioms for portfolio risk…

Mathematical Finance · Quantitative Finance 2022-04-05 Xia Han , Bin Wang , Ruodu Wang , Qinyu Wu

The subject of the present article is the study of correlations between large insurance companies and their contribution to systemic risk in the insurance sector. Our main goal is to analyze the conditional structure of the correlation on…

General Economics · Economics 2019-05-10 Anna Denkowska , Stanisław Wanat

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

The conditional value-at-risk (CVaR) is a useful risk measure in fields such as machine learning, finance, insurance, energy, etc. When measuring very extreme risk, the commonly used CVaR estimation method of sample averaging does not work…

Methodology · Statistics 2021-03-10 Dylan Troop , Frédéric Godin , Jia Yuan Yu

We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. (2021) with the pointwise two-stage calibration of Bayer et al. (2018) and Liu et al.…

Pricing of Securities · Quantitative Finance 2024-01-15 Fabio Baschetti , Giacomo Bormetti , Pietro Rossi

Covariate imbalance between treatment groups makes it difficult to compare cumulative incidence curves in competing risk analyses. In this paper we discuss different methods to estimate adjusted cumulative incidence curves including inverse…

This paper has two main goals: (a) establish several statistical properties---consistency, asymptotic distributions, and convergence rates---of stationary solutions and values of a class of coupled nonconvex and nonsmoothempirical risk…

Statistics Theory · Mathematics 2019-10-08 Zhengling Qi , Ying Cui , Yufeng Liu , Jong-Shi Pang

Optimization under uncertainty and risk is indispensable in many practical situations. Our paper addresses stability of optimization problems using composite risk functionals which are subjected to measure perturbations. Our main focus is…

Optimization and Control · Mathematics 2022-01-06 Darinka Dentcheva , Yang Lin , Spiridon Penev

We propose a dependence-aware predictive modeling framework for multivariate risks stemmed from an insurance contract with bundling features - an important type of policy increasingly offered by major insurance companies. The bundling…

Methodology · Statistics 2023-10-17 Peng Shi , Zifeng Zhao

A key driver of Credit Value Adjustment (CVA) is the possible dependency between exposure and counterparty credit risk, known as Wrong-Way Risk (WWR). At this time, addressing WWR in a both sound and tractable way remains challenging:…

Mathematical Finance · Quantitative Finance 2016-11-10 Damiano Brigo , Frédéric Vrins

Focusing on stochastic programming (SP) with covariate information, this paper proposes an empirical risk minimization (ERM) method embedded within a nonconvex piecewise affine decision rule (PADR), which aims to learn the direct mapping…

Optimization and Control · Mathematics 2025-09-29 Yiyang Zhang , Junyi Liu , Xiaobo Zhao

We consider the problem of minimizing the sum of two convex functions: one is smooth and given by a gradient oracle, and the other is separable over blocks of coordinates and has a simple known structure over each block. We develop an…

Optimization and Control · Mathematics 2014-07-07 Qihang Lin , Zhaosong Lu , Lin Xiao