Hedging Gnma Mortgage-Backed Securities with T-Note Futures: Dynamic Versus Static Hedging

Posted: 17 Aug 1999

See all articles by Gregory Koutmos

Gregory Koutmos

Fairfield University - Charles F. Dolan School of Business

Andreas Pericli

ALM & Fixed Income Research

Abstract

This article proposes a dynamic hedging model for Government National Association Mortgage-Backed Securities (GNMA MBSs) that is free of the drawbacks associated with the static hedging strategies currently used. The simultaneity bias of the regression approach is dealt with by modeling the joint distribution of price changes of GNMA MBSs and 10-year Treasury-note futures. Error correction (EC) terms from cointegrating relationships are included in the conditional mean equations to preserve the long-term equilibrium relationship of the two markets. The time-varying variance-covariance structure of the two markets is modeled via a version of the bivariate generalized autoregressive conditionally heteroskedastic model (bivariante GARCH), which assures that the time-varying variance-covariance matrix is positive semidefinite for all time periods. This dynamic error-correction GARCH model is estimated using daily data on six different coupon GNMA MBSs. Dynamic cross-hedge ratios are obtained from the time-varying variance-covariance matrix using the 10-year Treasury-note futures contract as the hedging instrument. These ratios are evaluated in terms of both overall risk reduction and expected utility maximization. There is overwhelming evidence that dynamic hedge ratios are superior to static ones even when transaction costs are incorporated into the analysis. This conclusion holds for all six different coupon GNMA MBSs under investigation.

JEL Classification: G13

Suggested Citation

Koutmos, Gregory and Pericli, Andreas, Hedging Gnma Mortgage-Backed Securities with T-Note Futures: Dynamic Versus Static Hedging. Available at SSRN: https://ssrn.com/abstract=171849

Gregory Koutmos

Fairfield University - Charles F. Dolan School of Business ( email )

Dolan School of Business
N. Benson Road
Fairfield, CT 06824
United States
203-254-4000 Ext. 2832 (Phone)

Andreas Pericli (Contact Author)

ALM & Fixed Income Research ( email )

8200 Jones Branch Drive
Mailstop 375
Mclean, VA 22102
United States
703-903-2429 (Phone)
Not available (Fax)

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
1,703
PlumX Metrics