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This paper was presented and written for two seminars: a national UK University Risk Conference and a Risk Management industry workshop. The target audience is therefore a cross section of Academics and industry professionals. The current…

Risk Management · Quantitative Finance 2009-04-07 Sovan Mitra

Risk-sensitive reinforcement learning (RL) has become a popular tool for controlling the risk of uncertain outcomes and ensuring reliable performance in highly stochastic sequential decision-making problems. While it has been shown that…

Machine Learning · Computer Science 2026-01-21 Xian Yu , Lei Ying

We introduce new forecast encompassing tests for the risk measure Expected Shortfall (ES). The ES currently receives much attention through its introduction into the Basel III Accords, which stipulate its use as the primary market risk…

Risk Management · Quantitative Finance 2020-08-31 Timo Dimitriadis , Julie Schnaitmann

We revisit mean-risk portfolio selection in a one-period financial market where risk is quantified by a positively homogeneous risk measure $\rho$. We first show that under mild assumptions, the set of optimal portfolios for a fixed return…

Mathematical Finance · Quantitative Finance 2021-07-20 Martin Herdegen , Nazem Khan

Risk measures for random vectors have been considered in multi-asset markets with transaction costs and financial networks in the literature. While the theory of set-valued risk measures provide an axiomatic framework for assigning to a…

Risk Management · Quantitative Finance 2024-07-25 Çağın Ararat , Zachary Feinstein

In this paper we develop a novel methodology for estimation of risk capital allocation. The methodology is rooted in the theory of risk measures. We work within a general, but tractable class of law-invariant coherent risk measures, with a…

Risk Management · Quantitative Finance 2019-11-25 Tomasz R. Bielecki , Igor Cialenco , Marcin Pitera , Thorsten Schmidt

Given measurements from sensors and a set of standard forces, an optimization based approach to identify weakness in structures is introduced. The key novelty lies in letting the load and measurements to be random variables. Subsequently…

Optimization and Control · Mathematics 2023-11-22 Facundo N. Airaudo , Harbir Antil , Rainald Löhner , Umarkhon Rakhimov

We study the single-period portfolio selection problem under Constant Relative Risk-Aversion (CRRA) utility through the information-theoretic lens. Assuming only that the market payoff vector has finite support, we show that the…

Information Theory · Computer Science 2026-05-12 Bo-Yu Yang , Michael Gastpar

We consider a liquidation problem in which a risk-averse trader tries to liquidate a fixed quantity of an asset in the presence of market impact and random price fluctuations. The trader encounters a trade-off between the transaction costs…

Trading and Market Microstructure · Quantitative Finance 2022-01-31 Seungki Min , Ciamac C. Moallemi , Costis Maglaras

Systemic risk measures have been shown to be predictive of financial crises and declines in real activity. Thus, forecasting them is of major importance in finance and economics. In this paper, we propose a new forecasting method for…

Methodology · Statistics 2025-04-23 Yannick Hoga

Wrong-Way Risk (WWR) is an important component in Funding Valuation Adjustment (FVA) modelling. Yet, the standard assumption is independence between market risks and the counterparty defaults and funding costs. This typical industrial…

Computational Finance · Quantitative Finance 2024-06-07 T. van der Zwaard , L. A. Grzelak , C. W. Oosterlee

PAC generalization bounds on the risk, when expressed in terms of the expected loss, are often insufficient to capture imbalances between subgroups in the data. To overcome this limitation, we introduce a new family of risk measures, called…

Machine Learning · Statistics 2026-04-09 Hind Atbir , Farah Cherfaoui , Guillaume Metzler , Emilie Morvant , Paul Viallard

Credit Suisse First Boston (CSFB) launched in 1997 the model CreditRisk+ which aims at calculating the loss distribution of a credit portfolio on the basis of a methodology from actuarial mathematics. Knowing the loss distribution, it is…

Statistical Mechanics · Physics 2008-12-02 Hermann Haaf , Dirk Tasche

We study risk-sensitive RL where the goal is learn a history-dependent policy that optimizes some risk measure of cumulative rewards. We consider a family of risks called the optimized certainty equivalents (OCE), which captures important…

Machine Learning · Computer Science 2025-03-03 Kaiwen Wang , Dawen Liang , Nathan Kallus , Wen Sun

This guide provides a reference for high-probability regret bounds in empirical risk minimization (ERM). The presentation is modular: we begin with intuition and general proof strategies, then state broadly applicable guarantees under…

Machine Learning · Statistics 2026-03-04 Lars van der Laan

We present the conditional value-at-risk (CVaR) in the context of Markov chains and Markov decision processes with reachability and mean-payoff objectives. CVaR quantifies risk by means of the expectation of the worst p-quantile. As such it…

Logic in Computer Science · Computer Science 2018-05-09 Jan Křetínský , Tobias Meggendorfer

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

The diversification quotient (DQ) is recently introduced for quantifying the degree of diversification of a stochastic portfolio model. It has an axiomatic foundation and can be defined through a parametric class of risk measures. Since the…

Risk Management · Quantitative Finance 2023-05-12 Xia Han , Liyuan Lin , Ruodu Wang

In this paper we introduce a novel approach to risk estimation based on nonlinear factor models - the "StressVaR" (SVaR). Developed to evaluate the risk of hedge funds, the SVaR appears to be applicable to a wide range of investments. Its…

Risk Management · Quantitative Finance 2009-11-23 Cyril Coste , Raphael Douady , Ilija I. Zovko

De Finetti's optimal reinsurance is a set of contracts, one for each risk in a portfolio, that caps the retained aggregate variance to a pre-specified level while minimizing total expected loss. The premiums are determined using the…

Optimization and Control · Mathematics 2026-03-03 N. D. Shyamalkumar , Tianrun Wang