Assessing point forecast accuracy by stochastic loss distance

Francis X. Diebold, Minchul Shin

Research output: Contribution to journalArticlepeer-review


We explore the evaluation (ranking) of point forecasts by a "stochastic loss distance" (SLD) criterion, under which we prefer forecasts with loss distributions F(L(e)) "close" to the unit step function at 0. We show that, surprisingly, ranking by SLD corresponds to ranking by expected loss.

Original languageEnglish (US)
Pages (from-to)37-38
Number of pages2
JournalEconomics Letters
StatePublished - May 1 2015


  • Absolute-error loss
  • Expected loss
  • Forecast evaluation
  • Forecast ranking
  • Quadratic loss
  • Squared-error loss

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics


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