Li, Shengnan and Tsang, Edward PK and O'Hara, John (2022) Measuring relative volatility in high‐frequency data under the directional change approach. Intelligent Systems in Accounting, Finance and Management, 29 (2). pp. 86-102. DOI https://doi.org/10.1002/isaf.1510
Li, Shengnan and Tsang, Edward PK and O'Hara, John (2022) Measuring relative volatility in high‐frequency data under the directional change approach. Intelligent Systems in Accounting, Finance and Management, 29 (2). pp. 86-102. DOI https://doi.org/10.1002/isaf.1510
Li, Shengnan and Tsang, Edward PK and O'Hara, John (2022) Measuring relative volatility in high‐frequency data under the directional change approach. Intelligent Systems in Accounting, Finance and Management, 29 (2). pp. 86-102. DOI https://doi.org/10.1002/isaf.1510
Abstract
We introduce a new approach in measuring relative volatility between two markets based on the directional change (DC) method. DC is a data-driven approach for sampling financial market data such that the data are recorded when the price changes have reached a significant amplitude rather than recording data under a predetermined timescale. Under the DC framework, we propose a new concept of DC micro-market relative volatility to evaluate relative volatility between two markets. Unlike the time-series method, micro-market relative volatility redefines the timescale based on the frequency of the observed DC data between the two markets. We show that it is useful for measuring the relative volatility in micro-market activities (high-frequency data).
Item Type: | Article |
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Uncontrolled Keywords: | directional change; events; high-frequency data in FX markets; relative volatility |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 15 Jun 2022 09:32 |
Last Modified: | 30 Oct 2024 21:22 |
URI: | http://repository.essex.ac.uk/id/eprint/32954 |
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Filename: Intelligent Systems in Accounting Finance and Management - 2022 - Li - Measuring relative volatility in high‐frequency.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0