{"concept_id":"ALTSS-PERF-026","slug":"quartile-ranking","canonical_name":"Quartile Ranking","aliases":[],"kind":"term","authority":"industry","facets":["PRF"],"domains":["PERFORMANCE"],"display_title":"Quartile Ranking","search_aliases":["what does top quartile mean","top quartile private equity","quartile ranking funds","how are fund quartiles calculated","first quartile fund","top decile fund"],"one_sentence_definition":"Quartile ranking is the classification of a fund into one of four bands of its peer group, cut at the 25th, 50th and 75th percentiles of one performance metric; a top-quartile fund is at or above the 75th percentile.","plain_english":"Rank all comparable funds from best to worst on one measure, such as net IRR, [TVPI](/glossary/tvpi) or [DPI](/glossary/dpi), and cut the list into quarters. The cut-off points are the quartile boundaries. Which quarter a fund lands in depends on which funds are in the list, which metric is used, the measurement date and the way the boundaries are calculated, so the same fund can accurately be described as top quartile in one comparison and second quartile in another.","parent_concepts":[],"child_concepts":[],"related_concepts":["peer-group","benchmark-universe","vintage-year","performance-dispersion","performance-persistence","survivorship-bias","net-irr","tvpi","benchmark"],"comparison_concepts":[],"not_the_same_as":[{"slug":"performance-dispersion","distinction":"Dispersion measures how far apart the quartile boundaries are; quartile ranking places one fund within that spread."},{"slug":"public-market-equivalent","distinction":"PME compares a fund with a public index on its own cash flows; quartiles compare it with other private funds."}],"formula_ids":["F-PERF-026-percentile-boundary-linear-interpolation"],"worked_examples":[{"title":"Illustrative peer group of ten funds (same strategy and vintage)","paragraphs":["Net IRRs: 21.0%, 18.0%, 16.5%, 15.0%, 14.0%, 12.5%, 11.0%, 8.0%, 6.0%, −2.0%. Corresponding TVPIs: 2.10x, 1.75x, 1.60x, 1.95x, 1.55x, 1.70x, 1.50x, 1.40x, 1.30x, 0.90x.","| Boundary | IRR, inclusive method | IRR, exclusive method | TVPI, inclusive | TVPI, exclusive |\n|---|---|---|---|---|\n| Upper quartile (75th) | 16.1% | 16.9% | 1.74x | 1.80x |\n| Median | 13.3% | 13.3% | 1.58x | 1.58x |\n| Lower quartile (25th) | 8.8% | 7.5% | 1.43x | 1.38x |","Under the inclusive method the upper-quartile boundary for IRR is **16.1%**, so the fund with a 16.5% IRR is top quartile."],"calc":{"fn":"quartile","inputs":{"values":[0.21,0.18,0.165,0.15,0.14,0.125,0.11,0.08,0.06,-0.02],"method":"inclusive","value":0.165},"expected":{"upper_quartile":0.16125,"median":0.1325,"lower_quartile":0.0875,"quartile_rank":1},"tol":0.0005}},{"title":"The same peer group, exclusive method","paragraphs":["The exclusive method places the IRR upper-quartile boundary at **16.9%**. The 16.5% fund falls to the second quartile, with no change in its performance."],"calc":{"fn":"quartile","inputs":{"values":[0.21,0.18,0.165,0.15,0.14,0.125,0.11,0.08,0.06,-0.02],"method":"exclusive","value":0.165},"expected":{"upper_quartile":0.16875,"median":0.1325,"lower_quartile":0.075,"quartile_rank":2},"tol":0.0005}},{"title":"The same peer group ranked on TVPI","paragraphs":["On TVPI the inclusive upper-quartile boundary is **1.74x** (1.80x under the exclusive method). The 16.5% IRR fund, at 1.60x, is second quartile by TVPI under both methods, while the fund with a 15.0% IRR and a 1.95x TVPI moves from the second quartile by IRR to the top quartile by TVPI. Speed and size of returns rank the same funds differently."],"calc":{"fn":"quartile","inputs":{"values":[2.1,1.75,1.6,1.95,1.55,1.7,1.5,1.4,1.3,0.9],"method":"inclusive","value":1.6},"expected":{"upper_quartile":1.7375,"median":1.575,"lower_quartile":1.425,"quartile_rank":2},"tol":0.0005}}],"sections":[{"heading":"How quartiles are built","paragraphs":["Four choices define a quartile ranking: the [peer group](/glossary/peer-group) (strategy, geography, size, [vintage year](/glossary/vintage-year) and the vintage rule), the metric (net IRR, net TVPI, DPI or a public market equivalent (PME)), the measurement date, and the method for computing the boundaries. In private-markets usage the first quartile is the best-performing quarter. The peer group is drawn from a [benchmark universe](/glossary/benchmark-universe), a dataset with its own sources, coverage and biases."]},{"heading":"Why a fund's quartile is not a fixed fact","paragraphs":["Change any of the four choices and the ranking can move. Datasets contain different funds; vintage rules put the same fund in adjacent years; IRR and TVPI rank funds differently because one rewards speed and the other magnitude; and interim rankings change as NAVs are replaced by exit values. Rankings of young funds are especially unstable because they rest on NAVs and on the [J-curve](/glossary/j-curve). Korteweg and Sorensen (2017) find that private equity performance is persistent but noisy, which makes it difficult for investors to identify the funds with top-quartile expected future performance."]},{"heading":"Reading a \"top-quartile\" claim","paragraphs":["Because many datasets, vintage rules, metrics and dates are available, a large share of managers can each cite a top-quartile ranking somewhere. A claim is meaningful only with its specification: which dataset and as of when, which peer group and vintage rule, which metric (net or gross), and which boundary method. LPs ask for the fund's position against more than one dataset and on more than one metric, and look at percentile rank rather than just the quartile label. No quartile boundary values are stated on this page because they depend entirely on those choices."]},{"heading":"How LPs use quartile rankings","paragraphs":["Quartiles are a screening and monitoring tool: comparing a manager's prior funds with vintage peers, tracking how a commitment's ranking evolves, and studying [performance persistence](/glossary/performance-persistence) across a manager's successive funds. They describe position relative to private peers, not value added over a public alternative, so LPs pair them with a [public market equivalent](/glossary/public-market-equivalent). The width between quartile boundaries is itself informative; see [performance dispersion](/glossary/performance-dispersion)."]}],"classification_rules":[],"calculation_rules":[],"common_mistakes":["Quoting \"top quartile\" without naming the dataset, vintage, metric and measurement date.","Ranking a gross IRR against net-IRR quartiles.","Treating an interim quartile in years 2 to 4 as evidence of final performance.","Comparing a fund with a vintage cohort built on a different vintage rule.","Assuming the boundaries are the same across datasets."],"edge_cases":["With small peer groups, one fund entering or leaving the dataset can move the boundaries by several percentage points.","A fund exactly on a boundary may be classified differently by inclusive and exclusive methods.","Funds that stop reporting drop out of later rankings, which can lift the remaining distribution (see survivorship bias)."],"external_standard_mappings":[],"source_ids":["SRC-ACAD-KORTEWEG-SORENSEN-2017"],"citations":[{"source_id":"SRC-ACAD-KORTEWEG-SORENSEN-2017","pinpoint":"Abstract (Vol. 124(3), pp. 535–562)","supports":"Performance is persistent but noisy, making it difficult to identify funds with top-quartile expected future performance","source":{"source_id":"SRC-ACAD-KORTEWEG-SORENSEN-2017","title":"Skill and Luck in Private Equity Performance","authors":"Arthur Korteweg; Morten Sorensen","publisher":"Journal of Financial Economics","document_type":"paper","url":"https://doi.org/10.1016/j.jfineco.2017.03.006","doi":"10.1016/j.jfineco.2017.03.006","year":2017,"publication_date":"Vol. 124(3), pp. 535-562","jurisdiction":"intl","status":"Published (paywalled)","last_verified":"2026-10-01"}}],"faq":[{"q":"What does top quartile mean in private equity?","a":"The fund's result on a stated metric is at or above the 75th percentile of a stated peer group of the same strategy and vintage, as of a stated date. Without those specifications the label has no fixed meaning."},{"q":"How can more than a quarter of managers be top quartile?","a":"Each can be top quartile in a different comparison: another dataset, vintage rule, metric or measurement date. Ask which comparison was used."}],"seo":{},"first_published":null,"last_reviewed":"2026-10-01","last_modified":"2026-10-01","content_version":"2.0.0","url":"https://altss.com/glossary/quartile-ranking","json_url":"https://altss.com/reference/concepts/quartile-ranking.json","title":"Quartile Ranking","formulas":[{"formula_id":"F-PERF-026-percentile-boundary-linear-interpolation","concept_id":"ALTSS-PERF-026","label":"Percentile boundary (linear interpolation)","plain":"Q_p = x_(k) + (h − k) × (x_(k+1) − x_(k)), with h = (n − 1) × p and k = floor(h)","latex":"Q_p=x_{(k)}+(h-k)\\left(x_{(k+1)}-x_{(k)}\\right),\\qquad h=(n-1)p,\\; k=\\lfloor h\\rfloor","variables":[{"symbol":"x_{(k)}","meaning":"the k-th value when the peer group's results are sorted from lowest to highest (k = 0 for the lowest)"},{"symbol":"n","meaning":"number of funds in the peer group"},{"symbol":"p","meaning":"percentile: 0.25 (lower-quartile boundary), 0.50 (median), 0.75 (upper-quartile boundary)"}],"convention_note":"This is the \"inclusive\" linear method used by many spreadsheet and statistics packages. The \"exclusive\" method uses h = (n + 1)p − 1; nearest-rank methods use no interpolation. Each dataset applies its own rule, and with small peer groups the choice moves the boundaries materially."}],"sources":[{"source_id":"SRC-ACAD-KORTEWEG-SORENSEN-2017","title":"Skill and Luck in Private Equity Performance","authors":"Arthur Korteweg; Morten Sorensen","publisher":"Journal of Financial Economics","document_type":"paper","url":"https://doi.org/10.1016/j.jfineco.2017.03.006","doi":"10.1016/j.jfineco.2017.03.006","year":2017,"publication_date":"Vol. 124(3), pp. 535-562","jurisdiction":"intl","status":"Published (paywalled)","last_verified":"2026-10-01"}]}