Investigating the Asymmetric Effect and Moon Cycle of Vietnam Stock Index Returns: An Approach Based on Extended GARCH Models

The study focuses on investigating the asymmetry and moon cycle effects of the Vietnam stock index (VN-Index) return series by estimating extended GARCH models. The data used are the daily closing prices of the VN-Index traded on the Vietnam stock market on the HoSE from 2000 to 2024, with a total of 1129 trading days. The results show that the VN-Index possesses significant characteristics of time variation and clustering, which are characteristic of the ARCH and GARCH effects of financial time series. The estimation of the GARCH(1,1) model confirms the existence of variance clustering on the return series of the VN-Index. Estimation of TARCH (1, 1) and EGARCH (1, 1) models confirms the existence of asymmetric effect of the VN-Index's return series: negative news has a stronger impact than positive news on the future volatility of asset prices. Estimation of IGARCH (1,1) model confirms the influence of the moon cycle on stock returns (specifically, the influence of the full moon phase in the 1-day cycle, and the influence of the new moon phase in the 2-day cycle). From this quantitative result, the Vietnamese stock market should strengthen the system construction, reduce excessive intervention of the Vietnamese government and support the rational investment philosophy.

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Publication Details

Journal
Journal of Applied Statistics and Data Science.
Published
2026-10-28
DOI
https://doi.org/10.21776/ub.jasds.2026.003.02.4
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Investigating the Asymmetric Effect and Moon Cycle of Vietnam Stock Index Returns: An Approach Based on Extended GARCH Models

Phạm Thị Phương Thảo, Duy Phung, Hoang Nam Quyen, Nguyễn Hữu Thịnh et al.
Journal of Applied Statistics and Data Science.
Financial Risk and Volatility Modeling
article

Investigating the Asymmetric Effect and Moon Cycle of Vietnam Stock Index Returns: An Approach Based on Extended GARCH Models

Phạm Thị Phương Thảo, Duy Phung, Hoang Nam Quyen, Nguyễn Hữu Thịnh, Nguyen Viet Ha, Thi Quynh Anh Bui
article en

Abstract

The study focuses on investigating the asymmetry and moon cycle effects of the Vietnam stock index (VN-Index) return series by estimating extended GARCH models. The data used are the daily closing prices of the VN-Index traded on the Vietnam stock market on the HoSE from 2000 to 2024, with a total of 1129 trading days. The results show that the VN-Index possesses significant characteristics of time variation and clustering, which are characteristic of the ARCH and GARCH effects of financial time series. The estimation of the GARCH(1,1) model confirms the existence of variance clustering on the return series of the VN-Index. Estimation of TARCH (1, 1) and EGARCH (1, 1) models confirms the existence of asymmetric effect of the VN-Index's return series: negative news has a stronger impact than positive news on the future volatility of asset prices. Estimation of IGARCH (1,1) model confirms the influence of the moon cycle on stock returns (specifically, the influence of the full moon phase in the 1-day cycle, and the influence of the new moon phase in the 2-day cycle). From this quantitative result, the Vietnamese stock market should strengthen the system construction, reduce excessive intervention of the Vietnamese government and support the rational investment philosophy.

Journal of Applied Statistics and Data Science.Vol. 3(2)
Foreign Trade University (VN)
Openalex Percentile: Top 9%
Financial Risk and Volatility Modeling
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Investigating the Asymmetric Effect and Moon Cycle of Vietnam Stock Index Returns: An Approach Based on Extended GARCH Models — Phạm Thị Phương Thảo, Duy Phung, et al. · Journal of Applied Statistics and Data Science. (2026) | TGRS Research Map | TGRS