arXiv research

The paper provides a representation for dynamic risk measures and capital allocations.

Efficiently computes optimal policies for Entropic Risk Measures.

This paper introduces new risk measures for evaluating losses with varying time horizons.

New risk measure considers horizon risk and interest rate uncertainty.

Entropic framework models stock and option dynamics.

New risk measures incorporate economic states to assess crude oil derivatives.

New method measures model risk in dynamic settings with uncertain state processes.

Modeling exchange rates and options using entropic dynamics.

Researchers calculated EVaR for various distributions using Lambert function.

New risk measure includes VaR, TVaR, and Entropic Risk Measure.

Using elements from the theory of ergodic backward stochastic differential equations (BSDE), we study the behavior of forward entropic risk measures. We provide their general representation results (via both BSDE and convex duality) and examine their behavior for risk positions of long maturities. We show that forward …

ERTS uses Thompson sampling for Gaussian entropic risk bandits, achieving regret bounds.

The paper mentioned in the title introduces the entropic value at risk. I give some extra comments and using the general theory make a relation with some commonotone risk measures.

Paper proposes risk-averse reinforcement learning algorithms.

Proposes a method to generate counterfactuals for ensemble models using entropic risk measures.

Investment strategy optimizes risk using a specific risk measure.

The paper develops a new approach to conditional risk measures using modular convex analysis.

New method corrects bias in estimating entropic risk for better decision-making.

Paper introduces Lambda EVaR, a new risk measure.

Study risk-sensitive reinforcement learning with entropic risk measures and generative models.

The left tail of the implied volatility skew, coming from quotes on out-of-the-money put options, can be thought to reflect the market's assessment of the risk of a huge drop in stock prices. We analyze how this market information can be integrated into the theoretical framework of convex monetary measures of risk. In …

Dynamic risk measures are defined using BSDEs in a filtration enlargement setting.

New risk measures control subgroup imbalances, improving PAC-Bayesian bounds.

We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. The density process of the optimal measure is characterized using a semimartingale BSDE under general conditions. The EMT is used to reinterpret the conditiona…

We consider insurance derivatives depending on an external physical risk process, for example a temperature in a low dimensional climate model. We assume that this process is correlated with a tradable financial asset. We derive optimal strategies for exponential utility from terminal wealth, determine the indifference…

This work addresses time inconsistency in risk measures and develops a dynamic programming principle for risk minimization problems.

Solves risk-sensitive investment via duality, entropic regularization, and RL.

This work extends entropic optimal transport to non-product reference couplings, focusing on Gaussian cases.

New algorithms reduce risk in reinforcement learning with provable regret bounds.

This paper is devoted to study the optimal portfolio problem. Harry Markowitz's Ph.D. thesis prepared the ground for the mathematical theory of finance. In modern portfolio theory, we typically find asset returns that are modeled by a random variable with an elliptical distribution and the notion of portfolio risk is d…

Study gap-dependent regret bounds for risk-sensitive RL.

Mean-field neural nets approximate functions using a free energy functional and controlled dynamics.

Improved sample complexity for identifying best policies in risk-sensitive reinforcement learning.

Proposes a new derivative concept for nonlinear DRO problems.

Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set minimization problems. The dual relationship between these two classes of multivariate ris…

Generalizes risk sharing models to a continuum of agents.

This paper uses entropy to derive stock price dynamics and option valuation.

A new framework tightens risk measure confidence bounds.

The paper studies risk-sensitive MDPs with recursive risk measures.

Sharp bounds found for various risk measures using generalized FGM copulas.

This work finds mixed equilibria in machine learning problems using measures and simultaneous gradient ascent-descent.

Overview of risk-sensitive Markov decision processes with Optimized Certainty Equivalent.

New bounds for statistical entropic optimal transport with subgaussian measures.

The entropic value-at-risk (EVaR) is a new coherent risk measure, which is an upper bound for both the value-at-risk (VaR) and conditional value-at-risk (CVaR). As important properties, the EVaR is strongly monotone over its domain and strictly monotone over a broad sub-domain including all continuous distributions, wh…

New concept of partial law invariance connects decision theory and financial risk management.

New training method for neural nets using multilevel entropic regularization.

We study the problem of portfolio insurance from the point of view of a fund manager, who guarantees to the investor that the portfolio value at maturity will be above a fixed threshold. If, at maturity, the portfolio value is below the guaranteed level, a third party will refund the investor up to the guarantee. In ex…

Study entropic regularization of Gaussian measures and processes on Hilbert space.