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Essays on the Informational Content of Implied Correlation and Observation-Driven Models

Sun, Xiaohang (2023) Essays on the Informational Content of Implied Correlation and Observation-Driven Models. Doctor of Philosophy (PhD) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.103371) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:103371)

Language: English

Restricted to Repository staff only until October 2024.

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This thesis examines the application and comparison of a set of widely adopted parametric and non-parametric approaches in forecasting the realisation of risk measures, such as volatility. In Chapter 2, implied correlation is extracted from options and is utilised to predict realised correlation after decomposition and re-grouping. I also attempt to forecast market return using the re-organized signal. Starting from Chapter 3, I focus on parametric models, more specifically, the observation-driven models represented by GARCH and score-driven models (GAS). The observation-driven models are extensively constructed upon assumptions on innovation terms. Their predictive power concerning realised volatility is evaluated and compared. In addition, the performance of GAS and GARCH models is also compared to implied volatility comprehensively. In Chapter 4, I propose to construct GAS models with shifted Gamma (SG-GAS) and shifted negative Gamma (SNG-GAS) innovations for option pricing. Corresponding GARCH models and the Black-Scholes model are built as benchmarks for comparison. It appears that both GAS models outperform the other models. The superiority of SG-GAS and SNG-GAS is mainly driven by their ability to price out-of-the-money options accurately.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Voukelatos, Nikolaos
Thesis advisor: Oberoi, Jaideep
DOI/Identification number: 10.22024/UniKent/01.02.103371
Uncontrolled keywords: Option-implied correlation, Empirical Mode Decomposition, Realised correlation forecasting, Market return forecasting, The distribution of asset return, Observation-driven models, Volatility forecasting, Option pricing
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Funders: University of Kent (
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 20 Oct 2023 17:10 UTC
Last Modified: 23 Oct 2023 15:06 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Sun, Xiaohang.

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