Modeling volatility changes in the 10-year Treasury

Guillermo Covarrubias, Bradley T. Ewing, Scott E. Hein, Mark A. Thompson

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


This paper examines the daily volatility of changes in the 10-year Treasury note utilizing the iterated cumulative sums of squares algorithm [C. Inclan, G. Tiao, Use of cumulative sums of squares for retrospective detection of changes of variance, J. Am. Stat. Assoc. 89 (1994) 913-923]. The ICSS algorithm can detect regime shifts in the volatility of the interest rate changes. A general model allows for endogenously determined changes in variance while the more restrictive model forces the variance to follow the same process throughout the sample period. A comparison of the out-of-sample volatility forecasting performance of two competing models is made using asymmetric error measures. The asymmetric error statistics penalize models for under- or over-predicting volatility. The results shed light on the importance of ignoring volatility regime shifts when performing out-of-sample forecasts. The findings are important to financial market participants who require accurate forecasts of future volatility in order to implement and evaluate asset performance.

Original languageEnglish
Pages (from-to)737-744
Number of pages8
JournalPhysica A: Statistical Mechanics and its Applications
Issue number2
StatePublished - Sep 15 2006


  • Asymmetric forecast evaluation
  • Forecasting
  • Interest rate
  • Regime shifts
  • Volatility


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