Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.06168

Model Risk Analysis for Entropic Hedging Strategies

Paul McCloud
View original source ↗Read source document ↗Export metadata ↓

Abstract

Entropic risk optimisation is a general framework for pricing and hedging financial derivatives in incomplete markets that can be used to decompose P&L into market and model risk contributions. When the prices are quadratic Gaussian, the coupled equations for price and hedge ratios are solved in closed form. This enables comprehensive analysis of trading P&L, with a decomposition of the model value-at-risk into convexity, dimension and funding contributions that are attributed in the explanation of realised P&L. The equations of the quadratic Gaussian model are directly applicable when the underlying prices follow Gaussian processes, such as fractional Ornstein-Uhlenbeck processes. The model also provides simple parametric expressions for hedge ratios that can be used for regressions in deep hedging.

Explore related subjects

q-fin.MF

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Paul McCloud. 2026-10-05. Model Risk Analysis for Entropic Hedging Strategies. https://arxiv.org/abs/2610.06168

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Retirement Planning with Minimum Guarantees for Both Beneficiaries and Fund Managers

This article studies a retirement planning problem from a new perspective in which a retiree delegates an initial lump sum to a professional fund manager. The fund is managed dynamically to deliver lifelong benefits while satisfying a guarantee that, at all times, wealth remains above a prescribed solvency level and the benefit rate remains above a minimum level. We formulate this problem as a continuous-time stochastic control model, in which the controls are the benefit rate and the portfolio allocation, and the objective incorporates general utility functions over benefits, management fees, and terminal bequest. Conventional approaches such as standard viscosity solution and martingale methods are not immediately applicable here due to the simultaneous influence of (i) the control variable nature of the benefit rate; (ii) the guarantee constraints; and (iii) the running wealth-dependent utility. We develop a new approach that deals directly with the associated fully nonlinear Hamilton-Jacobi-Bellman equation and establish the unique existence of a classical solution. One particular trick for resolving this equation is to apply an intricate transform that diverts the former to a semilinear auxiliary equation. A major contribution is to establish the existence of the solution to the auxiliary equation and characterize its precise growth, derivative, and boundary behavior. These results are crucial for establishing the verification theorems and deriving the optimal strategy. Besides, numerical experiments indicate that guarantee constraints induce more conservative policies, particularly at low wealth levels, while providing effective downside protection for both wealth and benefits. The associated well-being loss relative to the unconstrained framework remains small, suggesting that incorporating guarantees into retirement products is practically appealing.

q-fin.MF↗
arXiv2026

Buying at Support: The Entry Problem under Multi-Skew Brownian Motion

We study when to buy a share that will later be sold optimally, when the price follows a geometric multi-skew Brownian motion whose skew levels model support and resistance. The reward for buying is the exit premium of the liquidation problem solved in a companion paper. This premium is strictly $r$-subharmonic inside the exit continuation region, so buying is optimal only at levels where the price is pushed upward, and the entry problem reduces to a finite one whose value is an upper concave hull of finitely many points. With one support and one resistance, the optimal rule is to buy exactly at the support, in every exit regime, with an explicit value.

q-fin.MF↗
arXiv2026

Low-rank and graphon limits for dynamic threshold distress contagion in heterogeneous financial networks

The transmission of financial distress depends on the structure of exposures, the distribution of institutional buffers, and the duration of stress. We develop a dynamic model in which losses flow through weighted directed networks while counterparties are distressed, with recovery and repeated threshold crossings incorporated into the same system. A representation with \(K\) exposure factors closes the \(N\)-institution dynamics through \(K\) feedback coordinates, preserving heterogeneous sender and receiver roles. For bounded Lipschitz losses, Wasserstein stability and aligned \(L^1\) kernel estimates connect finite populations, factor models, and directed-kernel limits, with separate bounds for sampling and exposure approximation. For the hard threshold, every bounded nonnegative kernel admits a greatest cumulative-distress solution selected by vanishing positive-side regularization. The mass of institutions near the threshold governs stability: an Osgood condition along one reference path yields uniqueness, quantitative perturbation bounds, and convergence under sampled latent labels. Rank-one examples establish sharpness among uniqueness criteria based on threshold-layer mass, and a branchwise condition verifies the regularity directly from the initial profile and kernel. Numerical experiments examine how network structure and threshold concentration affect the dynamics. An application to disclosed EBA sovereign holdings constructs common-exposure factors and quantifies sensitivity to portfolio perturbations.

q-fin.MF↗