Advancing volatility prediction: Exploring directional forecasts, measures of volatility, and asset allocation strategies
|
PDF
(6MB)
Xiaodu Xie Thesis.pdf. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. |
Description
This thesis addresses the challenge of forecasting financial asset volatility, a crucial factor in asset pricing and risk management. It applies a mix of conventional and novel statistical methods to improve volatility predictions. It encompasses the accuracy of directional forecasts, the reliability of realized volatility measures, the efficacy of various asset allocation strategies based on volatility timing, and the effectiveness of range-based models in low-frequency scenarios. The findings of this thesis hold practical relevance for market practitioners, and provide insightful solutions for asset pricing and risk management.
Impact and interest:
Citation counts are sourced monthly from Scopus and Web of Science® citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads:
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
| ID Code: | 246410 |
|---|---|
| Item Type: | QUT Thesis (PhD) |
| Supervisor: | Clements, Adam & Thiele, Stephen |
| Keywords: | HAR, Realised volatility, Volatility directions, Investment portfolio, Volatility timing, Realised weights, Volatility, Financial econometrics, Machine learning, Forecasting |
| DOI: | 10.5204/thesis.eprints.246410 |
| Pure ID: | 157748702 |
| Divisions: | Current > QUT Faculties and Divisions > Faculty of Business & Law Current > Schools > School of Economics & Finance |
| Institution: | Queensland University of Technology |
| Deposited On: | 26 Feb 2024 06:15 |
| Last Modified: | 26 Feb 2024 06:15 |
Export: EndNote | Dublin Core | BibTeX
Repository Staff Only: item control page
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)