Is There More to Long Memory in Fixed-Income Excess Returns and Volatility than Structural Instability?
AbstractUnlike equity returns, many fixed-income return and volatility measures appear to display considerable long memory. Connolly and G½ner (working paper, 1999) show this holds particularly strongly for shorter-maturity Treasury securities in the U.S. They show that fixed-income return and volatility series for other G-7 countries also display long memory. In a number of recent papers, Granger has argued that long memory in returns may only reflect infrequent structural breaks. He finds the case for long memory in volatility much stronger. Parke (Review of Economics and Statistics, 2000) develops a model that generates long memory through a type of structural shift. In this paper, we show that the extent of long memory depends crucially on whether gross or excess returns are under consideration and we provide a simple demonstration of why this distinction is so important. We also carefully explore the impact of structural instability on tests for long memory using a version of the supLM test developed by Andrews. Briefly, we find that evidence of long memory in both gross and excess returns is very considerably weakened after accounting for structural shifts. By contrast, we find that long memory in excess return volatility appears to exist even after controlling for structural shifts. Finally, our estimates of the long memory parameter for excess return volatility series shift from the nonstationary to the stationary range once we account for structural shifts. As a part of the analysis, we also compare the performance of different estimators of long memory volatility model parameters. We conclude the paper with some discussion of the implications of long memory in excess return volatility for asset pricing tests and risk management.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 223.
Date of creation: 01 Apr 2001
Date of revision:
Contact details of provider:
Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
More information through EDIRC
long memory; structural instability; fixed-income returns; fixed-income volatility;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2001-05-02 (All new papers)
- NEP-FIN-2001-05-02 (Finance)
- NEP-FMK-2001-05-02 (Financial Markets)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.