{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:44:08Z","timestamp":1792759448721,"version":"4.5.0"},"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>Tracking error is routinely related to benchmark volatility, and the relation is found to be strong. We show that two standard construction choices make much of it arithmetic. The first is aggregation: averaging the tracking errors of N funds diversifies nothing and delivers a quantity 1.74 times the tracking error of the aggregated portfolio, which is what the diversification argument implies. The second is the estimation window: when tracking error and volatility are both standard deviations computed on overlapping windows, they co-move by construction. On 377 weeks of European fund data the estimated elasticity falls from 0.421 to 0.184 to 0.027 as the overlap is removed, and volatility measured inside the estimation window explains 92 per cent of the variation while volatility from the preceding non-overlapping window adds nothing. We propose normalised replication risk, tracking error per unit of market volatility; the unit exponent it imposes is not rejected, the elasticity estimated in levels being 1.04 with an interval of 0.77 to 1.31. We illustrate the correction on the entry into force of MiFID, where the uncorrected series produces a mean shift at the regulatory date with a t-statistic of 6.05 while the corrected one places the break in December 2008 and distinguishes no candidate date from a randomly chosen one, at any normalising exponent between zero and 1.6.<\/jats:p>","DOI":"10.2139\/ssrn.7651238","type":"posted-content","created":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:03:57Z","timestamp":1792757037000},"source":"Crossref","is-referenced-by-count":0,"title":["The Systematic Tracking Error: Two Measurement Biases in the Estimation of Replication Risk"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8224-3596","authenticated-orcid":true,"given":"Cheikh","family":"Niang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alois","family":"Kanyinda Kansanda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T12:03:57Z","timestamp":1792757037000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7651238"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7651238","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}