Skip to main content

Cross- and auto-correlation effects arising from averaging: the case of US interest rates and equity duration

Buy Article:

$47.50 plus tax (Refund Policy)

Most available monthly interest data series consist of monthly averages of daily observations. It is well known that this averaging introduces spurious autocorrelation in the first differences of the series. It is exactly this differenced series that one is interested in when estimating interest rate risk exposures, for example. This paper presents a method to filter this autocorrelation component from the averaged series. In addition, the potential effect of averaging on duration analysis is investigated, namely, when estimating the relationship between interest rates and financial market variables like equity or bond prices or exchange rates. In contrast to interest rates the latter price series are readily available in ultimo monthly form. It is found that combining monthly returns on market variables with changes in averaged interest rates leads to substantial biases in estimated correlations (R2), regression coefficients (durations) and their significance (t-statistics). These theoretical findings are confirmed by an empirical investigation of US interest rates and their relationship with US equities (S&P 500 Index).
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: Erasmus University Rotterdam, POB 1738, NL-3000 DR Rotterdam, The Netherlands e-mail: [email protected]

Publication date: 01 January 2003

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more