Growth enterprise market in Hong Kong: efficiency evolution and long memory in return and volatility

Nguyen, Trang;Chaiechi, Taha;Eagle, Lynne;Low, David

Abstract

Purpose: Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market. The purpose of this paper is to examine the evolving efficiency and dual long memory in the GEM. This paper also explores the joint impacts of thin trading, structural breaks and inflation on the dual long memory. Design/methodology/approach: State-space GARCH-M model, Kalman filter estimation, factor-adjustment techniques and fractionally integrated models: ARFIMA–FIGARCH, ARFIMA–FIAPARCH and ARFIMA–HYGARCH are adopted for the empirical analysis. Findings: The results indicate that the GEM is still weak-form inefficient but shows a tendency towards efficiency over time except during the global financial crisis. There also exists a stationary long-memory property in the market return and volatility; however, these long-memory properties weaken in magnitude and/or statistical significance when the joint impacts of the three aforementioned factors were taken into account. Research limitations/implications: A forecasts of the hedging model that capture dual long memory could provide investors further insights into risk management of investments in the GEM. Practical implications: The findings of this study are relevant to market authorities in improving the GEM market efficiency and investors in modelling hedging strategies for the GEM. Originality/value: This study is the first to investigate the evolving efficiency and dual long memory in an SME stock market, and the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

Journal

Journal of Asian Business and Economic Studies

Publication Name

N/A

Volume

ISBN/ISSN

2515-964X

Edition

N/A

Issue

Pages Count

Location

N/A

Publisher

Emerald

Publisher Url

N/A

Publisher Location

N/A

Publish Date

N/A

Url

N/A

Date

N/A

EISSN

N/A

DOI

10.1108/JABES-01-2019-0009