Forecasting volatility: Roles of sampling frequency and forecasting horizon

Wing Hong Chan, Xin Cheng, Joseph K W FUNG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This study empirically tests how and to what extent the choice of the sampling frequency, the realized volatility (RV) measure, the forecasting horizon and the time-series model affect the quality of volatility forecasting. Using highly synchronous executable quotes retrieved from an electronic trading platform, the study avoids the influence of various market microstructure factors in measuring RV with high-frequency intraday data and in inferring implied volatility (IV) from option prices. The study shows that excluding non-trading-time volatility produces significant downward bias of RV by as much as 36%. Quality of prediction is significantly affected by the forecasting horizon and RV model, but is largely immune from the choice of sampling frequency. Consistent with prior research, IV outperforms time-series forecasts; however, the information content of historical volatility critically depends on the choice of RV measure.

Original languageEnglish
Pages (from-to)1167-1191
Number of pages25
JournalJournal of Futures Markets
Volume30
Issue number12
DOIs
Publication statusPublished - Dec 2010

Scopus Subject Areas

  • Accounting
  • Business, Management and Accounting(all)
  • Finance
  • Economics and Econometrics

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