arXiv subjects

Hirbod Assa

Publications and source records attributed to Hirbod Assa.

8 recordsLinked to original sources

arXiv2026

NatPar: Natural Parametric Modeling

We develop natural parametric (NatPar) insurance as the natural next step from natural-catastrophe (NatCat) modelling: the same hazard-exposure-vulnerability-finance machinery, with a parametric index made contractual in place of indemnity loss adjustment. Our aim is practical - a standard approach inspired by how the catastrophe-insurance industry already operates, not another optimal-contract criterion. This delivers two payoffs. First, it fixes how reporting is formulated: NatPar contracts are reported in the native NatCat language (annual average loss, EP/AEP/OEP curves, return-period levels), complemented with two-sided basis-exceedance diagnostics (BEP+/-) elevated to the central status the EP curve holds for losses - the canonical distributional view of basis risk, not a supplementary number. Second, the same standard shows how the tail is reallocated between insuree and insurer. A frost case study yields the central result: it is about time, not average. Holding a contract AAL-neutral, the bounded payout cannot follow the unbounded exposure tail, so equalising the mean separates over- and under-payment across return periods: the insuree gains at short horizons while the insurer sheds the deep tail past a crossover of several decades. This reverses under tail dependence - when regions reach extremes jointly, bounded payouts stack and the insurer reabsorbs the deep tail.

q-fin.RM↗

arXiv2026

The Epistemic Risk of Risk: A Modal Framework for Quantitative Risk Management

Risk governance is not only about identifying and measuring adverse states of the world. It also asks when an institution is entitled to rely on a risk claim. This paper introduces modal epistemic tools for that second layer of QRM. For a risk proposition $p$, $Kp$ denotes assurance-grade endorsement for certification, audit reliance, board sign-off, or regulatory reporting. By contrast, $Bp$ denotes working commitment: a disciplined action-guiding stance under incomplete assurance. The framework distinguishes object-level risk claims from stances toward them. It develops crisp and fuzzy modal semantics for assurance, working commitment, live possibility, non-exclusion, hesitation, and epistemic inconsistency. The central diagnostics are \[ p\wedge\neg Kp \qquad\text{and}\qquad p\wedge\neg Bp, \] which identify cases in which a risk is present but lacks the relevant stance. Thus QRM should model not only hazards and losses, but also evidential incompleteness, model risk, validation gaps, and failures of escalation. Two governance principles motivate the analysis. The Risk Management Principle says that if $p$ is a risk, then the absence of the relevant stance, $p\wedge\neg Mp$, is itself risk-relevant. The Risk Reach Principle says that real and decision-relevant risks should be reachable by the appropriate stance. Their unrestricted combination creates Moorean and Fitch-style collapse pressure: treating $p\wedge\neg Kp$ or $p\wedge\neg Bp$ as ordinary targets of the same stance whose absence they record undermines the diagnostic. The response is architectural. Object-level risk claims should be separated from meta-level epistemic diagnostics. The latter should be governed through an audit layer that records and controls epistemic gaps. This preserves action and precaution without collapsing risk governance into institutional omniscience.

q-fin.RM↗

arXiv2024

Factor risk measures

This paper introduces and studies factor risk measures. While risk measures only rely on the distribution of a loss random variable, in many cases risk needs to be measured relative to some major factors. In this paper, we introduce a double-argument mapping as a risk measure to assess the risk relative to a vector of factors, called factor risk measure. The factor risk measure only depends on the joint distribution of the risk and the factors. A set of natural axioms are discussed, and particularly distortion, quantile, linear and coherent factor risk measures are introduced and characterized. Moreover, we introduce a large set of concrete factor risk measures and many of them are new to the literature, which are interpreted in the context of regulatory capital requirement. Finally, the distortion factor risk measures are applied in the risk-sharing problem and some numerical examples are presented to show the difference between the Value-at-Risk and the quantile factor risk measures.

q-fin.MF↗

arXiv2022

Calibrating distribution models from PELVE

The Value-at-Risk (VaR) and the Expected Shortfall (ES) are the two most popular risk measures in banking and insurance regulation. To bridge between the two regulatory risk measures, the Probability Equivalent Level of VaR-ES (PELVE) was recently proposed to convert a level of VaR to that of ES. It is straightforward to compute the value of PELVE for a given distribution model. In this paper, we study the converse problem of PELVE calibration, that is, to find a distribution model that yields a given PELVE, which may either be obtained from data or from expert opinion. We discuss separately the cases when one-point, two-point, n-point and curve constraints are given. In the most complicated case of a curve constraint, we convert the calibration problem to that of an advanced differential equation. We apply the model calibration techniques to estimation and simulation for datasets used in insurance. We further study some technical properties of PELVE by offering a few new results on monotonicity and convergence.

q-fin.RM↗

arXiv2015

Optimal risk allocation in a market with non-convex preferences

The aims of this study are twofold. First, we consider an optimal risk allocation problem with non-convex preferences. By establishing an infimal representation for distortion risk measures, we give some necessary and sufficient conditions for the existence of optimal and asymptotic optimal allocations. We will show that, similar to a market with convex preferences, in a non-convex framework with distortion risk measures the boundedness of the optimal risk allocation problem depends only on the preferences. Second, we consider the same optimal allocation problem by adding a further assumption that allocations are co-monotone. We characterize the co-monotone optimal risk allocations within which we prove the "marginal risk allocations" take only the values zero or one. Remarkably, we can separate the role of the market preferences and the total risk in our representation.

q-fin.RM↗

arXiv2014

On Optimal Reinsurance Policy with Distortion Risk Measures and Premiums

In this paper, we consider the problem of optimal reinsurance design, when the risk is measured by a distortion risk measure and the premium is given by a distortion risk premium. First, we show how the optimal reinsurance design for the ceding company, the reinsurance company and the social planner can be formulated in the same way. Second, by introducing the marginal indemnification functions, we characterize the optimal reinsurance contracts. We show that, for an optimal policy, the associated marginal indemnification function only takes the values zero and one. We will see how the roles of the market preferences and premiums and that of the total risk are separated.

q-fin.RM↗

arXiv2008

Convex Risk Measures: Lebesgue Property on one Period and Multi Period Risk Measures and Application in Capital Allocation Problem

In this work we study the Lebesgue property for convex risk measures on the space of bounded càdlàg random processes ($\mathcal{R}^\infty$). Lebesgue property has been defined for one period convex risk measures in \cite{Jo} and earlier had been studied in \cite{De} for coherent risk measures. We introduce and study the Lebesgue property for convex risk measures in the multi period framework. We give presentation of all convex risk measures with Lebesgue property on bounded càdlàg processes. To do that we need to have a complete description of compact sets of $\mathcal{A}^1$. The main mathematical contribution of this paper is the characterization of the compact sets of $\mathcal{A}^p$ (including $\mathcal{A}^1$). At the final part of this paper, we will solve the Capital Allocation Problem when we work with coherent risk measures.

q-fin.RM↗

arXiv2008

Characterization of Compact Subsets of $\mathcal{A}^p$ with Respect to Weak Topology

In this brief article we characterize the relatively compact subsets of $\mathcal{A}^p$ for the topology $σ(\mathcal{A}^p,\mathcal{R}^q)$ (see below), by the weak compact subsets of $L^p$ . The spaces $\mathcal{R}^q$ endowed with the weak topology induced by $\mathcal{A}^p$, was recently employed to create the convex risk theory of random processes. The weak compact sets of $\mathcal{A}^p$ are important to characterize the so-called Lebesgue property of convex risk measures, to give a complete description of the Makcey topology on $\mathcal{R}^q$ and for their use in the optimization theory.

math.PR↗