A Financial Optimization Approach to Quantitative Analysis of Long Term Government Debt Management in Sweden
Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
The Swedish National Debt Office (SNDO) is the Swedish Government’s financial administration. It has several tasks and the main one is to manage the central government’s debt in a way that minimizes the cost with due regard to risk. The debt management problem is to choose currency composition and maturity profile - a problem made difficult because of the many stochastic factors involved.
The SNDO has created a simulation model to quantitatively analyze different aspects of this problem by evaluating a set of static strategies in a great number of simulated futures. This approach has a number of drawbacks, which might be handled by using a financial optimization approach based on Stochastic Programming.
The objective of this master’s thesis is thus to apply financial optimization on the Swedish government’s strategic debt management problem, using the SNDO’s simulation model to generate scenarios, and to evaluate this approach against a set of static strategies in fictitious future macroeconomic developments.
In this report we describe how the SNDO’s simulation model is used along with a clustering algorithm to form future scenarios, which are then used by an optimization model to find an optimal decision regarding the debt management problem.
Results of the evaluations show that our optimization approach is expected to have a lower average annual real cost, but with somewhat higher risk, than a set of static comparison strategies in a simulated future. These evaluation results are based on a risk preference set by ourselves, since the government has not expressed its risk preference quantitatively. We also conclude that financial optimization is applicable on the government debt management problem, although some work remains before the method can be incorporated into the strategic work of the SNDO.
Place, publisher, year, edition, pages
Matematiska institutionen , 2003. , 120 p.
Mathematical optimization, systems theory, Financial Optimization, Stochastic Programming, Government Debt, Debt Portfolio Management, Treasury Bond, Treasury Bill, Macroeconomic Simulation, Stochastic Process, Autoregressive Process, Markov Chain, K-Means Clustering, Scenario Tree
IdentifiersURN: urn:nbn:se:liu:diva-2223ISRN: LITH-MAT-EX--03/16--SEOAI: oai:DiVA.org:liu-2223DiVA: diva2:19553
Subject / course
UppsokPhysics, Chemistry, Mathematics