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Momentum Strategies

LOUIS K. C. CHAN, NARASIMHAN JEGADEESH, JOSEF LAKONISHOK

The Journal of Finance · 1996 · 1262 citations

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Momentum Strategies


Source: Chan, Jegadeesh & Lakonishok (1996) · The Journal of Finance · DOI: 10.1111/j.1540-6261.1996.tb05222.x


TL;DR


Past returns and past earnings surprises each independently predict future return drift, and neither subsumes the other. Market, size, and book-to-market don't explain the drifts, and high-momentum stocks do not subsequently reverse — pointing to gradual underreaction to information. The strongest signal (a six-month return sort) shows a top-minus-bottom decile drift of ~1.74% per month, and analysts' forecasts respond sluggishly to past news, especially for past losers.


What anomaly it documents


  • Predictor: prior 6–12 month returns and prior earnings surprise (SUE / analyst revisions).
  • Direction: positive — past winners and positive-surprise firms keep outperforming.
  • Shape: ~1.74%/mo top-minus-bottom for the strongest sort; additive across price and earnings momentum; no short-horizon reversal.
  • OSAP predictors: momentum (Mom6m/Mom12m) and earnings-surprise signals.

  • How to construct it


  • Sorting variable: past return, standardized unexpected earnings (SUE), and analyst forecast revisions.
  • Universe: NYSE/AMEX/Nasdaq stocks (1977–1993).
  • Portfolio formation: independent sorts on each momentum measure.
  • Long / short: long high-momentum / positive-surprise, short low.
  • Weighting: equal-weighted deciles.
  • Rebalancing: monthly, 6-month holding.

  • Evidence and replication


    PeriodNotesSource
    1977–1993price & earnings momentum both significant and additive; best sort ~1.74%/mothis paper
    OOS (post-1996)momentum and PEAD persist; episodic crashespost-publication
    OSAPmomentum + earnings-surprise predictors positiveChen & Zimmermann 2022

    Why it might work


  • Underreaction: investors and analysts respond sluggishly to news, so prices adjust gradually.
  • Separate channels: price and earnings momentum carry partly distinct information.

  • Limitations and risks


  • Momentum crashes: severe, infrequent drawdowns at rebounds.
  • High turnover: monthly rebalancing is costly net of frictions.
  • Crowding: heavily exploited since publication.

  • Key references


  • Chan, L. K. C., Jegadeesh, N. & Lakonishok, J. (1996) — Momentum Strategies — Journal of Finance — DOI: 10.1111/j.1540-6261.1996.tb05222.x
  • Jegadeesh, N. & Titman, S. (1993) — Returns to Buying Winners and Selling Losers — JF


  • Provenance: verified/generated from the paper's full text.

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    Wiki last updated: June 27, 2026