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Asian Review of Financial Research Vol.21 No.2 pp.77-114
The Characteristics of the Illiquidity Premium, Measured via Spread
Jaesung James Park* Deputy General Manager, Korea Life Insurance Economic Research Institute
Kyong Shik Eom Korea Securities Research Institute
Key Words : Liquidity,Relative Spread,Illiquidity Premium,Asset Pricing Model,Cross-Sectional Analysis,Time-Series Analysis


We examined how the illiquidity premium affects the portfolio returns for all the stocks listed on the Stock Market Division and the KOSDAQ Market Division of the Korea Exchange (KRX). We used the daily relative spread as a proxy variable for illiquidity which was calculated using the bid-ask spread for each stock at the daily closing session. We estimated the beta using weekly returns for each stock. Our sample period runs 10 years, from April 1996 to March 2006. Our conclusions are as follows. First, using the cross-sectional regressions presented in Fama and Macbeth(1973), we found that the relative spread is a significant and robust characteristic variable in explaining the expected excess return for each portfolio. The explanatory power of the relative spread for the expected excess return was significant for all the regression models. Second, using the time-series regressions presented in Fama and French(1993), the illiquidity risk factor IMV explained the expected portfolio excess return in about 60% of all portfolios. However, in the case of the KRX data, the economic significance of IMV was limited; The single-factor model that used IMV as its sole factor explains the expected portfolio excess return. However, no other meaningful model specification was found when combining or using other explanatory factors like the market risk factor MKT, the size factor SMB or the B/M factor HML. This is in contrast to the case of US markets for which SMB and HML reportedly have their own economic significance when added to a single-factor model that uses MKT. Third, analyzing two market divisions of the KRX separately by multiple regressions, we found that the statistical significances of relative spread in the Stock Market Division was very strong, while the statistical significance in the KOSDAQ Division was weak. In addition, we made a robustness check of cross-sectional and time-series analyses using the beta estimated by using daily returns for each stock and found that the explanatory power of relative spread for the expected excess return for each portfolio became very limited. This suggests that the economic significance of relative spread differs from the stock returns we use to estimate beta.
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