Abstract
Understanding of volatility term structure is highly relevant both for market agents and policymakers. As traditional methodologies often bring results contradicting situation on the markets, we revisit volatility term structure modeling in univariate case.
In this paper we benefi t from extensive high-frequency dataset of US Treasury futures prices allowing us to empirically inspect the behaviour of the respective realized volatility term structure. We believe that the discovered properties justify the application of multi-factor modeling techniques primarily developed for yield curves.
Finally we develop the comprehensive methodology fitting empirical data efficiently by term structure decomposition using Nelson-Siegel class of models.