What drives short rate dynamics? A functional gradient descent approach
Journal
Computational Economics
ISSN
0927-7099
ISSN-Digital
1572-9974
Type
journal article
Date Issued
2012-03
Author(s)
Abstract
Functional gradient descent, a recent technique coming from computational statistics, is applied to the estimation of the conditional moments of the short rate process with the goal of finding the main drivers of the drift and volatility dynamics. Functional gradient descent can improve the accuracy of some reasonable starting estimates obtained using classical short rate models introduced in the literature. It exploits the predictive information of an enlarged set of variables, including yields at other maturities, time, and macroeconomic indicators. Fitting this methodology to the time series of monthly US 3-month Treasury bill rates, we find that the drift dynamics react mostly in a non-linear way to changes in macroeconomic variables, whereas volatility dynamics are subjected to time-dependent regime-switches. Finally we show the superior performance of the final predictions obtained by applying functional gradient descent in a forecasting exercise.
Language
English
Keywords
Functional gradient descent
Short rate process
Macroeconomic variables
Time-varying drift and volatility dynamics.
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Refereed
Yes
Publisher
Springer
Publisher place
US
Volume
39
Number
3
Start page
315
End page
335
Pages
21
Subject(s)
Eprints ID
207833