arXiv research

Reverse sensitivity analysis for risk models under various stresses.

Generative model uses DDPMs for risk-neutral derivative pricing.

A new test evaluates risk estimation accuracy using probability integral transform.

A new formula reveals symmetries between mean excess and ES functions.

In electricity markets, it is sensible to use a two-factor model with mean reversion for spot prices. One of the factors is an Ornstein-Uhlenbeck (OU) process driven by a Brownian motion and accounts for the small variations. The other factor is an OU process driven by a pure jump Lévy process and models the characteri…

We study time reversal, last passage time, and $h$-transform of linear diffusions. For general diffusions with killing, we obtain the probability density of the last passage time to an arbitrary level and analyze the distribution of the time left until killing after the last passage time. With these tools, we develop a…

In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such markets in the case of European options. A precise characterization of the hedging cost, the replication cost caused by th…

The quest for diversification has led to an increasing number of complex funds with a high number of strategies and non-linear payoffs. The new generation of Alternative Risk Premia (ARP) funds are an example that has been very popular in recent years. For complex funds like these, a Reverse Stress Test (RST) is regard…

Companies try to maximize their profits by recovering returned products of highly uncertain quality and quantity. In this paper, a reverse logistics network for an Original Equipment Manufacturer (OEM) is presented. Returned products are selected for remanufacturing or scrapping, based on their quality and proportional…

We consider a system of diffusion processes that interact through their empirical mean and have a stabilizing force acting on each of them, corresponding to a bistable potential. There are three parameters that characterize the system: the strength of the intrinsic stabilization, the strength of the external random per…

NSGLD improves SGLD for non-convex optimization problems.

Quantum MC simulations generate financial risk distributions efficiently.

Mitigates DeFi liquidations with reversible call options.

Optimizes trading returns using Hurst exponent and Q-learning.

Reverses simplification of risk measurement, focusing on portfolio covariance.

Modeling informed trading with risk-averse market makers.

Study finds physical momentum portfolios in Indian stock market yield higher returns than benchmarks.

Proposes a reverse stress testing framework for dynamic models.

We give a complete algorithm and source code for constructing what we refer to as heterotic risk models (for equities), which combine: i) granularity of an industry classification; ii) diagonality of the principal component factor covariance matrix for any sub-cluster of stocks; and iii) dramatic reduction of the facto…

The paper analyzes statistical arbitrage using a factor model of equity returns.

New method learns distribution shifts caused by predictive models in social computing.

Develops a method for reverse stress testing in multivariate scenarios.

We found that factors decay over time, with momentum fitting best.

In this article, we look at the effect of volatility clustering on the risk indifference price of options described by Sircar and Sturm in their paper (Sircar, R., & Sturm, S. (2012). From smile asymptotics to market risk measures. Mathematical Finance. Advance online publication. doi:10.1111/mafi.12015). The indiffere…

We propose a dynamic mean field model for `systemic risk' in large financial systems, which we derive from a system of interacting diffusions on the positive half-line with an absorbing boundary at the origin. These diffusions represent the distances-to-default of financial institutions and absorption at zero correspon…

Study shows climate change can cause a 'run on fossil fuels' affecting prices and production.

Develops a method for stress testing correlations of financial portfolios.

New tontine model with transaction costs for retirees.

Optimal trend-following strategy uses simple EMA, avoiding complex cherry-picked signals.

A new method decomposes subjective risk into epistemic and aleatoric uncertainties.

Reinsurance can help life insurers maintain higher capital guarantees without losing utility.

Classifies reversible and strongly reversible elements in quaternionic groups.

The paper classifies reversible and strongly reversible elements in Hermitian isometry groups.

A model-free method analyzes trading strategies using excursion paths.

New study shows diversification can increase risk for heavy-tailed losses.

This paper classifies reversible and strongly reversible elements in affine groups.

New neural net learns time-reversible symplectic dynamics.

The paper calculates optimal trading turnover in terms of asset liquidity and alpha autocorrelation.

A new trading strategy using reinforcement learning for statistical arbitrage.

In this paper we provide an alternative framework to tackle the first-best Principal-Agent problem under CARA utilities. This framework leads to both a proof of existence and uniqueness of the solution to the Risk-Sharing problem under very general assumptions on the underlying contract space. Our analysis relies on an…

Algebraic method reveals criterion for quaternionic Möbius group reversibility.

Recent studies have shown that online portfolio selection strategies that exploit the mean reversion property can achieve excess return from equity markets. This paper empirically investigates the performance of state-of-the-art mean reversion strategies on real market data. The aims of the study are twofold. The first…

A Finsler space is said to be geodesically reversible if each oriented geodesic can be reparametrized as a geodesic with the reverse orientation. A reversible Finsler space is geodesically reversible, but the converse need not be true. In this note, building on recent work of LeBrun and Mason, it is shown that a geodes…

In risk management it is desirable to grasp the essential statistical features of a time series representing a risk factor. This tutorial aims to introduce a number of different stochastic processes that can help in grasping the essential features of risk factors describing different asset classes or behaviors. This pa…

BayesMR estimates causal effects and directionality from genetic data.

Sharp stability results for reverse isoperimetric inequalities in 2D.

Investing in cryptocurrencies can improve portfolio risk-return profile, especially with diversification strategies.

Let $G$ be a group. An element $g$ in $G$ is called reversible if it is conjugate to $g^{-1}$ within $G$, and called strongly reversible if it is conjugate to its inverse by an order two element of $G$. Let $\textbf{H}_{\mathbb H}^n$ be the $n$-dimensional quaternionic hyperbolic space. Let $\mathrm{PSp}(n,1)$ be the i…