Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023)

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Volatility Analysis of Hong Kong Stock Hang Seng Index Based on GARCH Model

Authors
YiFan Lai1, *
1School of Mathematics and Statistics, Southwest University, Chongqing, 400715, PR China
*Corresponding author. Email: 1779437091@qq.com
Corresponding Author
YiFan Lai
Available Online 29 October 2023.
DOI
10.2991/978-94-6463-270-5_11How to use a DOI?
Keywords
Stock volatility; GARCH model; EGARCH model; APARCH model; TGARCH model
Abstract

Financial time series models are one of the commonly used methods to conduct stock market analysis and have good forecasting effects. In this paper, we use the monthly return data of Hong Kong stock Hang Seng Index as the research sample and calculate the volatility of low-frequency data based on high-frequency data returns as a basis for comparative exploration of the optimal model applicable to fitting the volatility forecasts of Hong Kong stocks to provide reference for stock investors. After the normality test, ADF test, white noise test, and ARCH effect test, it was determined that the log return series of the sample had conditional heteroskedasticity and was suitable for constructing a GARCH model. The GARCH model, EGARCH model, APARCH model, and TGARCH model are established respectively; furthermore, this paper also forecasts the future volatility scenario and calculates the estimates of actual volatility using high-frequency data, and after comparison, it is determined that the APARCH model has the best accuracy in estimating volatility for the sample data.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023)
Series
Atlantis Highlights in Economics, Business and Management
Publication Date
29 October 2023
ISBN
10.2991/978-94-6463-270-5_11
ISSN
2667-1271
DOI
10.2991/978-94-6463-270-5_11How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - YiFan Lai
PY  - 2023
DA  - 2023/10/29
TI  - Volatility Analysis of Hong Kong Stock Hang Seng Index Based on GARCH Model
BT  - Proceedings of the 3rd International Conference on Internet Finance and Digital Economy (ICIFDE 2023)
PB  - Atlantis Press
SP  - 92
EP  - 104
SN  - 2667-1271
UR  - https://doi.org/10.2991/978-94-6463-270-5_11
DO  - 10.2991/978-94-6463-270-5_11
ID  - Lai2023
ER  -