1. Introduction and motivationLiquidity is a complex concept. In general, liquidityoften defined as the ability of markets to absorb large transactions withoutmuch effect on prices. Nowadays, research in liquidity is important for empiricalasset pricing, market efficiency, and corporate finance literature.
Especially,in market microstructure, liquidity plays a central role in the functioning offinancial markets. A number of studies have proposed liquiditymeasures derived from intraday data, which we called “high-frequency data”.However, intraday data are not available in many countries. Even if the data isavailable, estimation of liquidity required high performance of computer and computationalintensive process. Recently, Johann and Theissen (2017) perform comprehensivecomparative 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 emergingmarket of Thailand.The aim of this study is to provide empiricalevidence about liquidity in Thai equity market in several perspectives, both cross-sectionaldeterminants of liquidity and time-series variation in liquidity analysis. Thisstudy contributes to market microstructure literature in several ways. First,this study provides empirical evidence on liquidity in stock exchange ofThailand, before and after crisis. Second, this paper is the first study investigatinglow-frequency liquidity measurements in developing market of Thailand.
The remainder of thepaper is organized as follows. In Section 2, reviews the literature on liquidityand 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 furtherenhancement. 2. Liquidity measures and literature reviewThe literature has usedan extensive set of measures and proxies to estimate the liquidity on the stockmarket. The two most widely-used measures in liquidity are spread and priceimpact.
Brennan and Subrahmanyam (1996) suggest that spreadand price impact represent the fixed and variable components of the tradingcost, respectively. For low-frequency measures of liquidity, Johann and Theissen (2017) presentsome low-frequency measures has high correlation with the benchmark measure. Inthis 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 andprice impact.
Moreover, the study of Johann and Theissen (2017) also show thatthese set of low-frequency measures have performed well along with thebenchmark measure.