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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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9 results for “riskmetrics”

Partial comonotonicity and distortion riskmetricsq-fin.RM

New concept of partial comonotonicity connects riskmetrics and dependence.

problem Understanding and quantifying risk metrics under partial comonotonicity.

method Developed a new notion of partial comonotonicity and established its connection to distortion riskmetrics.

result Partial comonotonicity uniquely characterizes a class of distortion riskmetrics through additivity.

partial comonotonicity distortion riskmetrics additivity dependence structures

2025-06-09abs ↗pdf ↗

Optimizing distortion riskmetrics with distributional uncertaintymath.OC

Optimizes riskmetrics with uncertainty, making complex problems simpler.

problem Optimizing riskmetrics with distributional uncertainty.

method Unifying result converting non-convex optimization to convex, using closedness under concentration.

result Great tractability achieved through unifying equivalence result.

riskmetrics uncertainty optimization distortion closedness

2020-11-10abs ↗pdf ↗

Evaluating the RiskMetrics Methodology in Measuring Volatility and Value-at-Risk in Financial Marketscond-mat.stat-mech

We analyze the performance of RiskMetrics, a widely used methodology for measuring market risk. Based on the assumption of normally distributed returns, the RiskMetrics model completely ignores the presence of fat tails in the distribution function, which is an important feature of financial data. Nevertheless, it was …

2001-03-05abs ↗pdf ↗

A Noise-Robust Elicit-to-Optimize Framework for Distortion Riskmetrics via Inverse Reinforcement Learningcs.LG

Framework uses IRL and RL to elicit and optimize risk preferences robustly to noise.

problem Eliciting and optimizing risk preferences in noisy environments.

method Adaptive Bayesian IRL for elicitation, model-free RL for optimization, using quantile networks.

result Framework achieves convergence rate of

O(\exp(-cm+O(\sqrt{m\log m})))

Inverse Reinforcement Learning Reinforcement Learning Risk Metrics Distortion Risk Elicitation

2026-07-15abs ↗pdf ↗

Analyzing distortion riskmetrics and weighted entropy for unimodal and symmetric distributions under partial information constraintsq-fin.RM

The paper calculates bounds for risk metrics and entropies under partial information constraints.

problem Analyzing risk metrics and entropies for unimodal, symmetric distributions with limited information.

method Develops lower and upper bounds for worst-case distortion riskmetrics and weighted entropy for unimodal, symmetric distributions with known mean and variance.

result Sharp upper bounds for distortion riskmetrics and weighted entropy for symmetric distributions.

risk metrics entropy unimodal distributions partial information worst-case analysis

2025-04-28abs ↗pdf ↗

Risk sharing, measuring variability, and distortion riskmetricsq-fin.RM

The paper addresses risk sharing and variability measures among agents with general risk preferences.

problem Risk sharing and variability measures among agents with general risk preferences.

method Characterizes Pareto-optimal allocations using Gini deviation, mean-median deviation, and inter-quantile difference as variability measures.

result Optimal allocations are not comonotonic and feature a mixture of pairwise counter-monotonic structures.

Risk sharing Distortion riskmetrics Pareto-optimal allocations General risk preferences Inter-quantile difference

2023-02-08abs ↗pdf ↗

Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithmsstat.ML

Paper introduces risk-sensitive bandits with optimal arm mixtures.

problem Designing algorithms for risk-sensitive multi-armed bandits.

method Formalizes risk-sensitive bandits framework, identifies optimal arm mixtures, designs regret-efficient algorithms.

result Regret-efficient algorithms track optimal arm mixtures or solitary arms.

bandits risk-sensitive arm mixtures regret algorithms

2025-03-11abs ↗pdf ↗

Worst-cases of distortion riskmetrics and weighted entropy with partial informationq-fin.RM

The paper analyzes worst-case distortion risk metrics and weighted entropy under partial information.

problem Analyzing worst-case distortion risk metrics and weighted entropy with limited information.

method General distributions, partial information (mean and variance), various entropies and risk measures.

result Provides worst-case results for distortion risk metrics and weighted entropy.

distortion risk metrics weighted entropy partial information worst-case analysis risk measures

2024-05-29abs ↗pdf ↗

Risk measures with non-Gaussian fluctuationsphysics.soc-ph

Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modeling the power-law tails of the returns distribution in terms of a Student- $t$ (or Tsallis) distribution. Non-Gau…

2006-07-27abs ↗pdf ↗