@inbook{a08ae4f87ebd4eb492d3dba15716164e,
title = "Hedging market and credit risk in corporate bond portfolios",
abstract = "The European market for corporate bonds has grown significantly over the last two decades to become a preferable financing channel for large corporations in the local and Eurobond markets. The 2008 credit crisis has, however, dramatically changed corporations funding opportunities with similar effects on borrowing policies of sovereigns as well. Accordingly institutional and individual investors have progressively reduced the share of credit risky instruments in their portfolios. This chapter investigates the potential of multistage stochastic programming to provide the desired market and credit risk control for such portfolios over the recent, unprecedented financial turmoil. We consider a Eurobond portfolio, traded in the secondary market, subject to interest and credit risk and analyse whether a jump-to-default risk model and a dynamic control policy would have reduced the impact of severe market shocks on the portfolios during the crisis, to limit the systemic impact of investment strategies. The methodology is shown to provide an effective alternative to popular hedging techniques based on credit derivatives at a time in which such markets became extremely illiquid during the Fall of 2008.",
keywords = "Bond portfolio optimization, Credit risk, Multistage stochastic programming",
author = "Patrizia Beraldi and Giorgio Consigli and {de Simone}, Francesco and Gaetano Iaquinta and Antonio Violi",
note = "Funding Information: The authors acknowledge the support given by the research grant PRIN2007 “Optimization of stochastic dynamic systems with applications to finance,” no. 20073BZ5A5, sci.resp. G. Consigli. Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC 2011.",
year = "2011",
doi = "10.1007/978-1-4419-9586-5_4",
language = "British English",
series = "International Series in Operations Research and Management Science",
pages = "73--98",
booktitle = "International Series in Operations Research and Management Science",
}