Nonparametric Estimation of Time Series Volatility Model Estimation

Author

Teng Tu, Washington University in St. LouisFollow

Date of Award

Spring 5-2018

Author's School

Graduate School of Arts and Sciences

Author's Department

Mathematics

Degree Name

Master of Arts (AM/MA)

Degree Type

Thesis

Abstract

In this article we consider two estimation methods of a non-parametric volatility model with autoregressive error of order two. The first estimation method based on the two- lag difference. To get a better result, we consider the second approach based on the general quadratic forms. For illustration, we provided several data sets from different simulation models to support the procedures of both two methods, and prove that the second approach can make a better estimation.

Language

English (en)

Chair and Committee

José E. Figueroa-López

Committee Members

Jimin Ding Nan Lin

Comments

Permanent URL: https://doi.org/10.7936/K7C828RB

Recommended Citation

Tu, Teng, "Nonparametric Estimation of Time Series Volatility Model Estimation" (2018). Arts & Sciences Electronic Theses and Dissertations. 1496.
https://openscholarship.wustl.edu/art_sci_etds/1496