Long Memory Characteristics of the Distribution of Treasury Security Yields, Returns, and Volatility
AbstractThe distributions of Treasury security yields, returns, and volatility play critical roles in finance theory, and there are many papers that characterize features of these distributions. Our aim is to extend earlier work on short-term dependence of these by documenting and measuring long-range dependence in debt markets. Our long-memory tests focus on the R/S statistic and a statistic for fractional differencing. We estimate the degree of fractional differencing using semiparametric Gaussian and averaged periodogram estimators and a log periodogram estimator. To help select the optimal spectral bandwidth, we apply various automatic bandwidth results. We apply these tests and estimators to the U.S. Treasury security markets and focus on instances where long memory is for understanding important financial economics issues. We sample weekly holding-period returns on seven Treasury bills and bonds for the 7/62Ü5/96 period and check our results with comparable maturity Treasury bills drawn from the CRSP bond file. Our findings can be grouped into three categories. First, we show that one-week and one-month gross holding-period returns on Treasury Bills display strong evidence of long memory, whereas Treasury Bond holding-period returns do not. Bill returns give results different from those reported for equity markets. Lo shows the equity market reflects significant short-term dependence that biases estimates of long memory; once short-term dependence is eliminated, long-memory evidence disappears. We use Lo's methods but find strong evidence of long memory in Treasury Bill returns. We find short-term dependence produces biased tests for long memory, but LoÍs bias correction eliminates evidence of long memory only for long-maturity Treasury bonds. We find excess returns on bills and bonds show no evidence of long memory, suggesting it to be less relevant to empirical asset pricing studies. Second, short- and long-maturity bond yields strongly appear to be long-memory processes. Comte and Renault show this implies term-structure and bond-pricing models must accommodate long memory in the short-term yield. We show the implications of long memory in the short-rate process for empirical bond pricing. We also show that the term premium clearly displays long-memory properties. What remains unclear is whether this contributes term premium's ability to predict excess returns in conditional asset-pricing models. Third, gross and excess holding-period returns, yields, and yield spreads all display long memory in volatility. This is important because our results imply that GARCH-type conditional volatility models and certain stochastic volatility models are mis-specified. This undermines hypothesis testing in asset-pricing settings where the GARCH-type models are used to calculate robust standard errors.
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 1999 with number 943.
Date of creation: 01 Mar 1999
Date of revision:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Duan, Jin-Chuan & Jacobs, Kris, 2008. "Is long memory necessary? An empirical investigation of nonnegative interest rate processes," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 567-581, June.
- Jin-Chuan Duan & Kris Jacobs, 2001. "Short and Long Memory in Equilibrium Interest Rate Dynamics," CIRANO Working Papers 2001s-22, CIRANO.
- Gil-Alana, Luis A., 2004. "Long memory in the U.S. interest rate," International Review of Financial Analysis, Elsevier, vol. 13(3), pages 265-276.
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.