Search results

We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.

The purpose of this study is to examine the performances of liquidity factors in the stock market cycle. It aims to investigate whether the contribution of liquidity factors changes with stock market trends.

Six liquidity proxies and two-factor construction methods are compared in this study. The spanning regression method was applied to examine the contribution of liquidity factors to the asset pricing model, while the Fama and MacBeth regression method was used for examining the pricing power of liquidity factors.

The result shows that liquidity factors are accretive to models explaining returns in bull markets but not accretive to models in bear markets. The most appropriate method of constructing liquidity factors in the Japanese stock market has also been clarified.

In the Japanese stock market, there has never been a comprehensive test of the role of the liquidity risk factor in different market trends using the long-run data. This study helps with identifying the importance of liquidity pricing risk in different market trends. It also fills the gaps by comparing liquidity factors that are constructed through different methods and proxies and provides evidence for further confirming the correct asset pricing model in the future.

This paper investigates the style timing and liquidity style timing vis-à-vis the market, size, value and momentum factors of the actively managed Indian equity mutual funds.

We examine the style timing of the funds using the augmented Carhart four-factor model by incorporating timing measures (Treynor and Mazuy; Henriksson and Merton). Based on this, the study explores the four-factor liquidity and volatility style timing exhibited by fund managers. The sample is from April 2000 to March 2018 and spans the volatile 2008 subprime economic crises. The sample comprised 182 actively managed equity funds from various sizes and was considered to be a well-diversified sample.

The results of our study provide strong evidence of market liquidity timing in India. No other style timing skills are observed in our analysis. Our results also imply that the fund managers might misidentify size timing as market timing if integrated liquidity timing measures are not employed, leading to false conclusions.

The findings of our study imply that the fund managers might misidentify size timing as market timing if integrated liquidity timing measures are not employed, leading to false conclusions.

This study, to our knowledge, is the first attempt to investigate the portfolio-based style timing in the Indian context.

Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors.

Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities.

The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns.

The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets.

This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

The purpose of this paper in this context is to examine the impact of asset liquidity on real estate equity returns, after taking well-documented systematic risk factors into account. Due to their unique characteristics, real estate equities constitute an inherently low degree of underlying asset liquidity.

Following the Fama-French time-series regression approach, the authors extend the conventional asset pricing model by a real estate-specific asset liquidity factor (ALF), using a sample of 244 real estate equities.

The results, based on monthly data for the period 1999-2012, reveal that asset liquidity is a relevant pricing factor which contributes to explaining return variations in real estate equity markets. Accordingly, investors expect a risk premium from listed real estate companies with a low degree of asset liquidity, which is especially the case for companies facing financial constraints and during economic downturns. Furthermore, an investment strategy exploiting differences in the underlying asset liquidity yields considerable average excess returns of upto 8.04 per cent p.a.

Considering the findings presented in this paper, asset liquidity should receive special attention from investors, as well as from the management boards of listed real estate companies. While investors who ignore the magnitude of asset liquidity may systematically misprice real estate equities, management can influence the firm’s cost of capital by adjusting the underlying asset liquidity.

This is the first study to examine the role of an ALF in a real estate asset pricing framework.

The risk-return relationship of real estate equities is of particular interest for investors, practitioners and researchers. The purpose of this paper is to examine, in an asset pricing framework, whether the systematic risk factors play a significantly different role in explaining the returns of listed real estate companies, compared to general equities.

Running the difference test of the Fama-French three-factor and the liquidity-augmented asset pricing model, the authors analyze the effect of the systematic risk factors related to market, size, BE/ME and liquidity in a time-series setting over the period July 1992 to June 2012. By applying the propensity score matching (PSM) algorithm, the authors bypass the “curse of dimensionality” of traditional matching techniques and identify a comparable control sample of general equities, in terms of the relevant firm characteristics of size, BE/ME and liquidity.

The empirical results indicate that European real estate equity returns load significantly differently on the size, value and liquidity factor, while the influence of the market factor seems to be equivalent. In addition, the authors find an economically and statistically significant underperformance of European real estate equities, after accounting for the diverging role of systematic risk factors. Running the conditional time-series regression, the authors further reveal that these findings are predominately caused by the divergent risk-return behavior of real estate equities in economic downturns.

Due to the diverging role of the systematic risk factors in pricing real estate equities, the authors provide evidence of potential diversification benefits for investors and portfolio managers.

This is the first real estate asset pricing study to dissect the unique risk-return relationship of real estate equities by employing propensity score matching.

The purpose of this paper is to estimate the effects of liquidity on corporate bond spreads.

Using a systematic liquidity factor extracted from the yield spreads between on- and off-the-run Treasury issues as a state variable, the authors jointly estimate the default and liquidity spreads from corporate bond prices.

The authors find that the liquidity factor is strongly related to conventional liquidity measures such as bid-ask spread, volume, order imbalance, and depth. Empirical evidence shows that the liquidity component of corporate bond yield spreads is sizable and increases with maturity and credit risk. On average the liquidity spread accounts for about 25 percent of the spread for investment-grade bonds and one-third of the spread for speculative-grade bonds.

The results show that a significant part of corporate bond spreads are due to liquidity, which implies that it is not necessary for credit risk to explain the entire corporate bond spread.

The results show that returns from investments in corporate bonds represent compensations for bearing both credit and liquidity risks.

It is a novel approach to extract a liquidity factor from on- and off-the-run Treasury issues and use it to disentangle liquidity and credit spreads for corporate bonds.

This study aims to investigate the relationship between return and liquidity risk and the impact of the prospect theory value (PTV) as a moderator variable on this relationship.

The statistical population of this study is the companies listed on the Tehran Stock Exchange during the years 2006–2019. In this research, the portfolio construction method and alpha analysis of the factor models and the cross-sectional regression of Fama and Macbeth have been used to analyze the data.

The results obtained through the portfolio construction method and the cross-sectional regression of Fama and Macbeth show that there is no significant relationship between return and Amihud (2002) criterion (ILLIQ) as liquidity risk. The PTV also does not affect this relationship, but there is a positive and significant relationship between returns and the turnover ratio (TOR) as liquidity risk. In other words, the lower the TOR (higher liquidity risk), the lower the return. On the other hand, the results showed that the PTV affects this relationship.

To the best of the authors’ knowledge, this study is the first to examine the effect of the PTV on the relationship between return and liquidity risk. It is expected that the results of this study can help investors explain returns better through a deeper understanding of the behavior of investors and their decision-making methods. In other words, by examining the PTV as a proxy for behavioral dimension, we can understand that the relationship between return and liquidity risk can be affected by other dimensions like PTV, so when evaluating risk and return, other influential factors should also be considered.

The purpose of this paper is to investigate whether liquidity risk (i.e. the returns’ vulnerability to the unexpected changes in overall market liquidity) is a priced risk factor in China. Moreover, it investigates the potential role of a stock’s information quality in reducing its liquidity risk during the period of post-non-tradable shares reforms in China.

The authors collect data of all the A-share issuing firms listed either on the Shanghai Stock Exchange or Shenzhen Stock Exchange during the period 2006–2016. The authors perform two-stage cross-sectional regression testing. First, the authors perform firm-specific time-series regressions of excess returns over Fama–French’s three-factor model and a liquidity factor. Second, to test whether firm-specific liquidity risk is a priced risk factor, the authors apply Fama and MacBeth’s regressions.

Firm-level asset pricing tests provide substantial evidence for market pricing of liquidity risk in China. The authors find a significant negative association between information quality and liquidity risk. The authors also find that the reduction in liquidity risk induced by better information quality is substantial enough to reduce required returns. These findings are robust to alternative measures of liquidity risk and information quality.

The study underscores that a policy initiative to enhance the information environment can significantly reduce the market volatility in China.

To the best of authors’ knowledge, this is the first study that considers the Shanghai Stock Exchange as well as Shenzhen Stock Exchange to investigate market pricing of liquidity risk in China.

The purpose of this paper is to test whether the 2007 identification of commonality in liquidity by Galariotis and Giouvris for the UK is robust to different methodological approaches; to find whether commonality is priced; and to identify how changes in trading regimes, hence liquidity provision, affect the relationship between commonality and excess returns.

The paper builds on the 2001 methodology of Huberman and Halka. In addition it extracts common factors using principal component analysis to test the effect of commonality on excess returns.

The findings of this paper confirm the presence of a systematic time‐varying component in UK spreads (under a different approach) even after controlling for well‐known spread determining variables.

The paper provides original evidence on the presence and the effect of systematic liquidity on asset pricing in the UK, showing that it is sensitive to the nature of trading regimes. It is concluded that in order‐driven regimes the effect of commonality on asset pricing is reduced, hence policy makers should consider this when deciding on trading systems