Analyzing Hedging Strategies for Fixed Income Portfolios: A Bayesian Approach for Model Selection

41 Pages Posted: 26 Apr 2014 Last revised: 25 Jan 2016

See all articles by Wolfgang Bessler

Wolfgang Bessler

University of Hamburg

Alexander Leonhardt

University of Giessen

Dominik Wolff

Deka Investment GmbH; Technical University of Darmstadt; Frankfurt University of Applied Sciences

Date Written: November 9, 2015

Abstract

During the recent European sovereign debt crisis, returns on EMU government bond portfoli-os experienced substantial volatility clustering, leptokurtosis and skewed returns as well as correlation spikes. Asset managers invested in European government bonds had to derive new hedging strategies to deal with changing return properties and higher levels of uncertainty. In this environment, conditional time series approaches such as GARCH models might be better suited to achieve a superior hedging performance relative to unconditional hedging approaches such as OLS. The aim of this study is to test innovative hedging strategies for EMU bond portfolios for non-crisis and crisis periods. We analyze single and composite hedges with the German Bund and the Italian BTP futures contracts and evaluate the hedging effectiveness in an out-of-sample setting. The empirical analysis includes OLS, constant conditional correlation (CCC), and dynamic conditional correlation (DCC) multivariate GARCH models. We also introduce a Bayesian composite hedging strategy, attempting to combine the strengths of OLS and GARCH models, thereby endogenizing the dilemma of selecting the best estimation model. Our empirical results demonstrate that the Bayesian composite hedging strategy achieves the highest hedging effectiveness and compares particularly favorable to OLS during the recent sovereign debt crisis. However, capturing these benefits requires low transactions cost and efficiently functioning futures markets.

Keywords: Sovereign Debt Crisis, Bond Portfolio Management, Interest Rate Fu-tures, MGARCH, Bayesian composite hedging, Hedge Ratio, Hedging Effectiveness

JEL Classification: C52, G11, G19

Suggested Citation

Bessler, Wolfgang and Leonhardt, Alexander and Wolff, Dominik and Wolff, Dominik, Analyzing Hedging Strategies for Fixed Income Portfolios: A Bayesian Approach for Model Selection (November 9, 2015). International Review of Financial Analysis, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2429344 or http://dx.doi.org/10.2139/ssrn.2429344

Wolfgang Bessler (Contact Author)

University of Hamburg ( email )

Allende-Platz 1
Hamburg, 20146
Germany

Alexander Leonhardt

University of Giessen ( email )

Goethestra├če 58
Giessen, 35390
Germany

Dominik Wolff

Deka Investment GmbH ( email )

Mainzer Landstrasse 16
Frankfurt am Main, 60325
Germany

Technical University of Darmstadt

Hochschulstra├če 1
S1|02 40
Darmstadt, Hessen D-64289
Germany

Frankfurt University of Applied Sciences ( email )

Nibelungenplatz 1
Frankfurt / Main, 60318
Germany

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