{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T13:55:14Z","timestamp":1792158914329,"version":"4.4.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":0,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>We couple two sets of simulated market and credit paths by minimizing absolute temporalcorrelation error relative to a prescribed target. Each market path receives exactly one credit path, preserving both empirical distributions of complete scenarios. A perfect-matching test identifies whether a uniform correlation-error tolerance is feasible and determines its smallest attainable value. Further assignments give exact empirical mean-loss and exceedance-probability bounds; quantile bounds follow by binary search over eligible loss thresholds. A synthetic bond-forward credit stress test illustrates the method. The experiments report matching precision, empirical score tails and exposure-grid error, and measure matching and mean-loss computation. The method is independent of the scenario generator and provides a reproducible way to examine dependence assumptions in existing risk engines. Tail measures concern default-probabilityweighted credit scores.<\/jats:p>","DOI":"10.2139\/ssrn.7617059","type":"posted-content","created":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T13:28:22Z","timestamp":1792157302000},"source":"Crossref","is-referenced-by-count":0,"title":["Scenario Matching for Credit Dependence Stress Tests Temporal Correlation Constraints and Empirical Risk Bounds"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-6983-6537","authenticated-orcid":true,"given":"Naoufal","family":"NIFA","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T13:28:22Z","timestamp":1792157302000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7617059"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7617059","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}