{"paper":{"title":"Conformal Kelly: Conformal Prediction Intervals as the Scale in Fractional Kelly Position Sizing","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["q-fin.RM"],"primary_cat":"q-fin.PM","authors_text":"Robert Jacob Ryan","submitted_at":"2026-08-02T20:56:06Z","abstract_excerpt":"Conformal prediction has traditionally been used to quantify prediction uncertainty. We put that uncertainty to a second use, combining a 75% conformal interval with fractional Kelly to size portfolio positions: as the range widens we shrink the position, and as it narrows we grow it. On a six-year development window (2016-2021), with trading costs and strict leverage caps, this compounds at 28.5% annualised net log growth with a Sharpe ratio of 1.34 and a 27.7% maximum drawdown, versus 15.9% for holding the S&P 500 and 21-22% for passive portfolios at the same leverage.\n  Our main development"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01494","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2608.01494/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}