# Optimal Transport for Risk Management and scenario Generation (OTRiMaGe)

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · New York University (NY) · $299,057

## Abstract

This project aims at contributing to the mathematical foundations of risk management in finance and robust generative models. The first major focus is the design of dynamic stochastic models subject to domain and/or distribution constraints. Such models will play a key role for a robust representation of the underlying uncertainties and will allow for a better generation of risk scenarios thus improving the back testing abilities of financial risk management. The second key component addresses model risk and hedging by developing sensitivity analysis tools in the context of distributionally robust optimization. This project contributes new mathematical methods for optimizing systems of interacting agents which plays a crucial role in the analysis of financial risks.
 
More specifically, the project investigates ergodic optimal semimartingale transport problems to model multidimensional stochastic processes under both domain (support) and distributional constraints. These results can be applied to diffusion-based generative methods in artificial intelligence and are expected to outperform standard score-based procedures. A second major part addresses model risk assessment and hedging through the so-called distributional robust optimization. This involves defining model deviations within small Wasserstein balls around a reference martingale model--a novel concept for quantifying and mitigating model risk. When volatility surface calibration gives access to marginals, the proje

## Key facts

- **NSF award ID:** 2508581
- **Awardee organization:** New York University (NY)
- **SAM.gov UEI:** NX9PXMKW5KW8
- **PI:** Nizar Touzi
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Machine Learning Theory
- **Estimated total:** $299,057
- **Funds obligated:** $299,057
- **Transaction type:** Standard Grant
- **Period:** 09/01/2025 → 08/31/2027

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2508581

## Citation

> US National Science Foundation, Award 2508581, Optimal Transport for Risk Management and scenario Generation (OTRiMaGe). Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2508581. Licensed CC0.

---

*[NSF Awards dataset](/datasets/nsf-awards) · CC0 1.0*