6 papers in the archive (2024–2026), average empirical rigor 4/10, average math complexity 8.1/10. Quadrant mix: Holy Grail ×3, Lab Rats ×3.
Works mostly in Risk Management & Tail Risk, Insurance & Actuarial Risk, Crypto Markets & DeFi.
Frequent co-authors: Tong Pu (3), Yunran Wei (1), Wenjun Jiang (1), Qingqing Zhang (1), Qiqi Li (1), Wei Wang (1).
Scores are our LLM-assisted heuristics (methodology), not peer review or citation counts. Author pages are generated from paper metadata; name variants may split one person across pages. arXiv author page →
Ordered by a blend of empirical rigor (60%) and math complexity (40%).
Conditional risk measures and their associated risk contribution measures are commonly employed in finance and actuarial science for evaluating systemic risk and quantifying the effects of risk interactions. This paper introduces various types of contribution ratio measures based on the MCoVaR, MCoE
We introduce a novel class of systemic risk measures, the Vulnerability Conditional risk measures, which try to capture the “tail risk” of a risky position in scenarios where one or more market participants is experiencing financial distress. Various theoretical properties of Vulnerability Condition
Systemic risk is the risk that a company- or industry-level risk could trigger a huge collapse of another or even the whole institution. Various systemic risk measures have been proposed in the literature to quantify the domino and (relative) spillover effects induced by systemic risks such as the w
This paper investigates two optimal insurance contracting problems under distributional uncertainty from the perspective of a potential policyholder, utilizing a Bregman-Wasserstein (BW) ball to characterize the ambiguity set of loss distributions. Unlike the $p$-Wasserstein distance, BW divergence
In this article, we employ a principal-agent model to analyze optimal contract design in a monopolistic reinsurance market under adverse selection with a continuum of insurer types. Instead of using the classical expected utility framework, we model each insurer’s risk preference through their VaR a
In economic analysis, rational decision-makers often take actions to reduce their risk exposure. These actions include purchasing market insurance and implementing prevention measures to modify the shape of the loss distribution. Under the assumption that the insureds’ actions are fully observed by