1. Introduction and motivation
Liquidity is a complex concept. In general, liquidity
often defined as the ability of markets to absorb large transactions without
much effect on prices. Nowadays, research in liquidity is important for empirical
asset pricing, market efficiency, and corporate finance literature. Especially,
in market microstructure, liquidity plays a central role in the functioning of
A number of studies have proposed liquidity
measures derived from intraday data, which we called “high-frequency data”.
However, intraday data are not available in many countries. Even if the data is
available, estimation of liquidity required high performance of computer and computational
intensive process. Recently, Johann and Theissen (2017) perform comprehensive
comparative analysis of low-frequency measures of liquidity by using US data.
They identified high quality proxies for liquidity based on daily data. Hence,
this study will use the low-frequency proxies to explore liquidity in emerging
market of Thailand.
The aim of this study is to provide empirical
evidence about liquidity in Thai equity market in several perspectives, both cross-sectional
determinants of liquidity and time-series variation in liquidity analysis. This
study contributes to market microstructure literature in several ways. First,
this study provides empirical evidence on liquidity in stock exchange of
Thailand, before and after crisis. Second, this paper is the first study investigating
low-frequency liquidity measurements in developing market of Thailand.
The remainder of the
paper is organized as follows. In Section 2, reviews the literature on liquidity
and discusses evidence on low-frequency measures. Section 3, describe data structure and methodology for this study.
Section 4, present the results. Last section, discuss the results and further
2. Liquidity measures and literature review
The literature has used
an extensive set of measures and proxies to estimate the liquidity on the stock
market. The two most widely-used measures in liquidity are spread and price
impact. Brennan and Subrahmanyam (1996) suggest that spread
and price impact represent the fixed and variable components of the trading
cost, respectively. For low-frequency measures of liquidity, Johann and Theissen (2017) present
some low-frequency measures has high correlation with the benchmark measure. In
this study, the data that available are daily close price, high price, low price,
and traded volume. Due to data availability, I selected VoV Sigma, Amihud
(2002) illiquidity ratio, and VoV daily which represent liquidity of spread and
price impact. Moreover, the study of Johann and Theissen (2017) also show that
these set of low-frequency measures have performed well along with the