The main objective of this paper is to develop a practical approach to Argentina's sovereign risk management. Through Contingent Claim Analysis (CCA), Gape, Gray, Lim and Xiao (2008)[1] developed a sovereign risk framework whereby we can construct a marked to market sovereign balance sheet and obtain a set of credit risk indicators that can help policy-makers: set thresholds for foreign reserves, design risk mitigation strategies and select best policy options. The main contribution is that instead of using a conventional index such as GBI-EM 1 in order to estimate the volatility of domestic currency liabilities, we use 24 sovereign domestic currency bonds to construct an interest rate covariance matrix. That is, an interest rate sensitive sovereign portfolio, whose risk factor variations 2 are represented by a vector of the portfolio PV01 (present value of a basis point change) with respect to each interest rate of the zero-coupon yield curve. Since zero-coupon rates are rarely directly observable, we must estimate them from market data. In this paper we implemented a widely-used parametric term structure estimation method called Nelson and Siegel. For Argentina we generated two yield curves, i.e., sets of fixed maturity interest rates determined by Badlar and CER.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.