Statistical Methods in Finance 2016

Abstract

Time Series of Functional Data with application to Yield Curves

by Rituparna Sen

We develop time series analysis of functional data observed discretely, treating the whole curve as a random realization from a distribution on functions that evolve over time. The method consists of principal components analysis of functional data and subsequently modeling the principal component scores as vector ARMA process. We justify the method by showing that an underlying ARMAH structure of the curves leads to a VARMA structure on the principal component scores. We derive asymptotic properties of the estimators, fits and forecast. For term structures of interest rates, this provides a unified framework for studying the time and maturity components of interest rates under one set-up with few parametric assumptions. We apply the method to the yield curves of USA and India. We compare our forecasts to the parametric model of Diebold and Li (2006). In another application we study the dependence of long term interest rate on the short term interest rate using functional regression.

---

---