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.
Dual representations for robust risk measures and uncertainty sets.
In this paper, the dual Orlicz curvature measure is proposed and its basic properties are provided. A variational formula for the dual Orlicz-quermassintegral is established in order to give a geometric interpretation of the dual Orlicz curvature measure. Based on the established variational formula, a solution to the …
The equivalence between multiportfolio time consistency of a dynamic multivariate risk measure and a supermartingale property is proven. Furthermore, the dual variables under which this set-valued supermartingale is a martingale are characterized as the worst-case dual variables in the dual representation of the risk m…
Derives stability for curvature measure near constant density, proving dual Minkowski problem solutions.
Researchers prove uniqueness and continuity of solution to L_p dual Minkowski problem.
We establish dual representations for systemic risk measures based on acceptance sets in a general setting. We deal with systemic risk measures of both "first allocate, then aggregate" and "first aggregate, then allocate" type. In both cases, we provide a detailed analysis of the corresponding systemic acceptance sets …
This paper solves the dual Minkowski problem for q-torsional rigidity.
The general volume of a star body, a notion that includes the usual volume, the th dual volumes, and many previous types of dual mixed volumes, is introduced. A corresponding new general dual Orlicz curvature measure is defined that specializes to the -dual curvature measures introduced recently by Lutwak, Ya…
Solves a generalized dual Minkowski problem for specific values of q.
The dual Minkowski problem for even data asks what are the necessary and sufficient conditions on an even prescribed measure on the unit sphere for it to be the -th dual curvature measure of an origin-symmetric convex body in . A full solution to this is given when . The necessary and suffic…
The Gauss Image Measure uniquely identifies dual convex bodies up to dilation.
Investigates set-valued risk measures for processes and vectors, proving equivalence and providing new dual representations.
Study dual representations for quasiconvex systemic risk measures.
Unified Minkowski problem discussed for (p,q)-mixed quermassintegrals.
New method solves a generalized Minkowski problem using a curvature flow.
Study anisotropic inverse Gauss curvature flows and solve dual Orlicz Minkowski problems.
Study systemic risk measures adjusted to financial markets.
Researchers develop multi-utility representations for incomplete preferences linked to risk measures.
The paper analyzes the observability of relative pose estimation using dual quaternions.
Extends portfolio optimization with two quasiconvex risk measures.
Optimal hedging framework with variational preferences under convex risk measures.
Develops risk measures on Lipschitz spaces for financial positions.
New financial model revises risk measure under NA condition.
We present a general framework for measuring the liquidity risk. The theoretical framework defines a class of risk measures that incorporate the liquidity risk into the standard risk measures. We consider a one-period risk measurement model. The liquidity risk is defined as the risk that a given security or a portfolio…
New characterization of geodesic currents via curve functionals.
Paper estimates diameter for Minkowski problem solutions.
The local kinematic formulas on complex space forms induce the structure of a commutative algebra on the space of dual unitarily invariant curvature measures. Building on the recent results from integral geometry in complex space forms, we describe this algebra structure explicitly as a…
The general dual volume $\dveV(K)$ and the general dual Orlicz curvature measure $\deV(K, \cdot)$ were recently introduced for functions $G: (0, \infty)\times \sphere\rightarrow (0, \infty)$ and convex bodies in containing the origin in their interiors. We extend $\dveV(K)$ and $\deV(K, \cdot)$ to more gener…
Paper solves a new Minkowski problem for a specific type of rigidity.
Paper solves a geometric problem involving mixtures of area and curvature measures.
In this paper we present results on scalar risk measures in markets with transaction costs. Such risk measures are defined as the minimal capital requirements in the cash asset. First, some results are provided on the dual representation of such risk measures, with particular emphasis given on the space of dual variabl…
Measuring comodules are defined and shown to provide a useful generalization of the set of maps between modules with a broad range of applications. Three applications are described. Connections on bundles are described in terms of measuring comodules, enabling curvature to be defined under general algebraic circumstanc…
Set risk measures extend traditional risk measures to handle sets of positions.
Algorithm optimizes constrained reinforcement learning with dual variables.
The Lebesgue property (order-continuity) of a monotone convex function on a solid vector space of measurable functions is characterized in terms of (1) the weak inf-compactness of the conjugate function on the order-continuous dual space, (2) the attainment of the supremum in the dual representation by order-continuous…
Develops risk measures for markets with constraints and costs.
This paper shows how to calculate risk measures for sums of two counter-monotonic risks.
Dual-CLVSA predicts financial markets using both trading data and sentiment measurements.
In this paper we propose the notion of dynamic deviation measure, as a dynamic time-consistent extension of the (static) notion of deviation measure. To achieve time-consistency we require that a dynamic deviation measures satisfies a generalised conditional variance formula. We show that, under a domination condition,…
The framework of this paper is that of risk measuring under uncertainty, which is when no reference probability measure is given. To every regular convex risk measure on , we associate a unique equivalence class of probability measures on Borel sets, characterizing the riskless non positive elements of $…
We study the heat equation on time-dependent metric measure spaces (as well as the dual and the adjoint heat equation) and prove existence, uniqueness and regularity. Of particular interest are properties which characterize the underlying space as a super Ricci flow as previously introduced by the second author. Our ma…
The dual problem of optimal transportation in Lorentz-Finsler geometry is studied. It is shown that in general no solution exists even in the presence of an optimal coupling. Under natural assumptions dual solutions are established. It is further shown that the existence of a dual solution implies that the optimal tran…
We prove that higher moment maps on area measures of a euclidean vector space are injective, while the kernel of the centroid map equals the image of the first variation map. Based on this, we introduce the space of smooth dual area measures on a finite-dimensional euclidean vector space and prove that it admits a natu…
Estimates dimensions of maximal simplices for rational and irrational trees in Outer space.
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…
In our previous paper, "A Unified Approach to Systemic Risk Measures via Acceptance Set" (\textit{Mathematical Finance, 2018}), we have introduced a general class of systemic risk measures that allow for random allocations to individual banks before aggregation of their risks. In the present paper, we prove the dual re…
Dual representation and properties of expectile-based expected shortfall studied.
The financial crisis showed the importance of measuring, allocating and regulating systemic risk. Recently, the systemic risk measures that can be decomposed into an aggregation function and a scalar measure of risk, received a lot of attention. In this framework, capital allocations are added after aggregation and can…