{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:45:45Z","timestamp":1792046745817,"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:\/\/www.uspto.gov\/ip-policy\/copyright-policy\/copyright-basics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Early detection of systematic market stress remains a central challenge in quantitative finance, as traditional risk models often rely on lagging indicators that fail to capture sudden cross-asset panic. This paper introduces a cross-asset machine learning model classifying trading days into three distinct states (Low, Normal, and High Stress) using short-term momentum velocity, rolling volatility across equities, and fixed income. Using historical data from 2011 to 2025, we evaluate a non-linear Random Forest classifier against a linear Logistic Regression baseline across a strict chronological test\/train split. The Random Forest Model achieved an out-of-sample accuracy of 59.21%, outperforming the Logistic Regression baseline by 18.52 percentage points. Our feature importance results demonstrate that equity momentum velocity acts as a critical leading indicator of market distress offering quantitative risk managers an earlier warning system before liquidity shock spreads to slower moving assets.<\/jats:p>","DOI":"10.2139\/ssrn.7607360","type":"posted-content","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:12:08Z","timestamp":1792044728000},"source":"Crossref","is-referenced-by-count":0,"title":["Predicting Financial Market Stress Regimes Using Multi-Asset Machine Learning"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4145-8478","authenticated-orcid":true,"given":"Dylan","family":"Phillips","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daanish","family":"Khurram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Avend","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:12:08Z","timestamp":1792044728000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7607360"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7607360","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}