File(s) under permanent embargo

Reason: Restricted by author. A copy can be supplied under Section 51(2) of the Australian Copyright Act 1968 by submitting a document delivery request through your library, or by emailing document.delivery@monash.edu

Modelling and forecasting volatility in Applied Econometrics

thesis
posted on 02.08.2021, 06:34 by armin pourkhanali
Here, I investigate a variety of volatility models with varying parameters. Then compare two new Conditional heteroscedasticity models with varying parameters. In the first proposed model, I allow the parameters, which are attached to the lagged squared error term and lagged conditional variance term in the conditional variance under a GARCH specification, to be time-varying. The second proposed model is to introduce functional parameters into the GARCH process, resulting in a new model called fGARCH, based on the temporal interactions between stock and bond returns. They both demonstrate strong improvement in volatility prediction relative to constant parameter GARCH models.

History

Campus location

Australia

Principal supervisor

Jonathan Macgregor Keith

Additional supervisor 1

Xibin Zhang

Year of Award

2021

Department, School or Centre

Mathematics

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Science

Usage metrics

Exports