Abstract
The yield curve is a very important financial tool used in investment and policy decisions. Its estimation from market data is essentially a non-linear optimization problem. In this paper, we compare a diversity of non-linear optimization algorithms for estimating yield curves based on actual bond market data and conclude that certain classes of algorithms are more effective due to the nature of the problem.
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