Realised variance forecasting under Box-Cox transformations

Research output: Contribution to journalArticle (Academic Journal)peer-review

7 Citations (Scopus)
266 Downloads (Pure)


This paper assesses the benefits of modeling Box-Cox transformed realised variance data. In particular, it examines the quality of realised variance forecasts with and without this transformation applied in an out-of-sample forecasting competition. Using various realised variance measures, data transformations, volatility models and assessment methods, and controlling for data mining issues, the results indicate that data transformations can be economically and statistically significant. Moreover, the quartic root transformation appears to be the most effective in this regard. The conditions under which the use of transformed data is effective are identified.
Original languageEnglish
Pages (from-to)770-785
Number of pages16
JournalInternational Journal of Forecasting
Issue number4
Early online date13 Jun 2017
Publication statusPublished - Oct 2017

Structured keywords

  • AF Financial Markets


  • Realised variance
  • Box-Cox transformation
  • Forecasting competitions
  • Loss function
  • Reality check


Dive into the research topics of 'Realised variance forecasting under Box-Cox transformations'. Together they form a unique fingerprint.

Cite this