Forecasting the term structure of volatility of crude oil price changes

Ercan Balaban, Shan Lu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
8 Downloads (Pure)

Abstract

This is a pioneering effort to test the comparative performance of two competing models for out-of-sample forecasting the term structure of volatility of crude oil price changes employing both symmetric and asymmetric evaluation criteria. Under symmetric error statistics, our empirical model using the estimated growth factor of volatility through time is overall superior, and it beats in most cases the benchmark model of the square-root-of-time (View the MathML source) for holding periods between one and 250 days. Under asymmetric error statistics, if over-prediction (under-prediction) of volatility is undesirable, the empirical (benchmark) model is consistently superior. Relative performance of the empirical model is much higher for holding periods up to fifty days.
Original languageEnglish
Pages (from-to)116-118
Number of pages3
JournalEconomics Letters
Volume141
Early online date22 Feb 2016
DOIs
Publication statusPublished - Apr 2016

Keywords

  • volatility term structure
  • square-root-of-time rule
  • forecasting
  • forecast evaluation
  • oil prices

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