Transaction costs, liquidity risk, and the CCAPM

Liu, Weimin; Luo, Di; Zhao, Huainan

doi:10.1016/j.jbankfin.2015.11.011

Cited by 12 publications

(13 citation statements)

References 65 publications

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“…Acharya & Pedersen (2005) provide supporting evidence of liquidity risk being a priced risk factor employing three liquidity betas that capture different forms of liquidity risk. Further replications and enhancements of the Acharya & Pedersen (2005) model subsequently emerge (see, for example, He & Kryzanowski, 2006;Liu, 2006;Lee, 2011;Vu et al, 2015;Liu et al, 2016). Liu (2006) employs a two factor CAPM for the US that includes liquidity, finding that his model better explains the cross-section of stock returns as compared to the standard CAPM or the three-factor model (Fama & French, 1993…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Grillini

Özkan

Sharma

et al. 2019

International Review of Financial Analysis

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This paper investigates time-varying characteristics of illiquidity and the pricing of its risk using a liquidity-adjusted capital asset pricing model (L-CAPM). Collecting data from a pool of Eurozone countries between 1990 and 2018, we employ Markov switching models to assess the degree of persistence of illiquidity shocks. Contrary to prior research, which largely makes use of autoregressive (AR) processes, we provide strong evidence that illiquidity is time-varying and the persistence of shocks determines two distinct regimes characterised by high and low illiquidity. We assess pricing of illiquidity risk by developing and empirically testing a conditional L-CAPM model, where different regimes constitute priced risk factors for the cross-section of stock returns. We extend previous unconditional versions of L-CAPM models and we show that the various channels through which illiquidity affects asset returns and price of risks are time-varying. We find strong support for our conditional L-CAPM and our results are robust to alternative specifications and estimation techniques. These findings have important implications for portfolio management practices and are relevant to portfolio and risk managers and regulatory institutions.

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Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Grillini

Özkan

Sharma

et al. 2019

International Review of Financial Analysis

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“…Our final filter uses the dollar volume of stock traded in the previous month as a proxy for transaction costs. Dollar volume has been shown to affect the relative spread (Stoll ), is a major determinant of liquidity (Brennan and Subrahmanyam ), has been used in tests of the impact of illiquidity and transaction costs on required returns (Brennan, Chordia, and Subrahmanyam ; Liu, Luo, and Zhao ), or as a means of controlling for firm‐specific liquidity (Brockman and Chung ) and is available on a monthly basis for all of our sample countries. The dollar volume filter may also assist in controlling for transaction cost effects, while having a less severe impact on variation in AQ.…”

Section: Resultsmentioning

confidence: 99%

Accruals Quality, Stock Return Seasonality, and the Cost of Equity Capital: International Evidence

Zhang

Wilson

2018

Contemporary Accting Res

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Mashruwala and Mashruwala (2011) argue that inconsistent earlier findings regarding whether accruals quality (AQ) is priced in equity markets (Core, Guay, and Verdi 2008; Kim and Qi 2010) may be explained by seasonality in returns deriving from tax‐loss selling. Finding no evidence of annual AQ premia for U.S. firms, Mashruwala and Mashruwala report that significant monthly premia concentrate in January, with the remainder of the year demonstrating negative or insignificant returns to AQ and attribute this strong seasonality to tax‐loss selling by investors, rather than information risk. However, the end of the tax year for U.S. investors coincides with the calendar year and the financial year for the majority of firms, which may suggest alternative explanations for seasonal variation in returns. We extend Mashruwala and Mashruwala's study, using an international sample including countries where incentives for tax‐loss selling exist, but in which the standard tax and financial years differ (Japan and the United Kingdom), and where the tax and financial years conclude in a month other than December (Australia), as well as employing a longer U.S. sample. We find some evidence of an AQ premium in the United States, which although dominated by January returns, remains significant annually. However, these findings are sensitive to the inclusion of low price stocks and the choice of asset pricing test. In Japan, the United Kingdom, and Australia we document consistent evidence that an AQ premium exists on average throughout the year, and in samples excluding the first month of the tax year. The sensitivity of our U.S. results to the January period may reflect the conflation of numerous seasonal influences on returns, not all of which necessarily reflect mispricing.

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“…Dreyer (2012) shows that both transaction costs and liquidity premium can explain at least part of the so-called Equity Premium Paradox (Mehra and Prescott, 1985). In line with this, Liu et al (2016) use a liquidity-adjusted consumption-based asset-pricing model (CCAPM) alongside different measures of transaction costs and show that the model outperforms the original CCAPM by explaining a larger fraction of the variation in cross-sectional returns.…”

Section: Introductionmentioning

confidence: 84%

“…To answer these questions, we follow Liu et al (2016) and modify the traditional CCAPM by incorporating the effects of liquidity risk and transaction costs in both the Iranian and Turkish stock markets. The stocks of the latter country are used as the “control group.” To the best of our knowledge, this study is the first to explicitly calculate transaction costs for Iranian stocks.…”

Section: Introductionmentioning

confidence: 99%

Liquidity risk, transaction costs and financial closedness: lessons from the Iranian and Turkish stock markets

Alizadeh

Tash‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Dreyer

2021

RAF

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Purpose This paper aims to study the impact of liquidity risk and transaction costs on stock pricing in Iran, a closed market operating under a financial embargo and compare the results with those of an important neighboring market, namely, Turkey. Design/methodology/approach This study follows Liu et al. (2016) and incorporates liquidity risk and transaction costs into the traditional consumption-based asset-pricing model (CCAPM) from 2009 to 2017. Effective transaction costs are estimated a la Hasbrouck (2009) and liquidity risk according to eight different criteria. Findings According to the results, both liquidity risk and transaction costs are higher in Iran, possibly due to the financial embargo. Thus, relative to Turkey, this paper should expect a higher increase in the CCAPM pricing performance in Iran when accounting for these two variables. The results are in line with this expectation and indicate that adjusting the CCAPM significantly increases its pricing performance in both countries, but relatively more in Iran. Originality/value This study compares liquidity risk and transaction costs in an economy under the extreme case of a financial embargo to an open yet in other important aspects similar economy from the same region.

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Transaction costs, liquidity risk, and the CCAPM

Cited by 12 publications

References 65 publications

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model

Accruals Quality, Stock Return Seasonality, and the Cost of Equity Capital: International Evidence

Liquidity risk, transaction costs and financial closedness: lessons from the Iranian and Turkish stock markets

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