Demystifying Liquidity Beta Anomaly in India: Behavioral or Rational?

The conventional, risk-based view on liquidity beta is often a dismal story for empirical data. We propose a competing, sentiment-based view on the reversed pricing pattern of liquidity beta in China: High liquidity beta stocks underperform low liquidity beta stocks by 1.17% per month. The striking pattern is robust to different weighting schemes, competing factor models, alternative liquidity measures, and other well-known determinants of cross-sectional returns. Consistent with our new perspective, liquidity beta is a negative return predictor at firm level. Moreover, the return differential between high and low liquidity beta stocks is more dramatic following high market liquidity periods.

Low liquidity beta anomaly in China

Securities liquidity varies over time, which leads to equity return volatility. It implies that the liquidity in the capital markets is a significant source of risk. Therefore, liquidity risk in securities is difficult to diversify and contributes to the systemic market risk. This study aims to analyze the relationship between securities returns and liquidity risk while taking into account the time-varying characteristics of illiquidity on the Colombo Stock Exchange from 2015-2019 and taking into account the effect of liquidity level, using the Generalized Method of Movements (GMM) framework model to assess the persistence of illiquidity securities contributions of the updated version of the Amihud illiquidity (Amihud, 1986) proxy to represent across time market illiquidity and to research the time-series relationship between liquidity and returns. The pricing of liquidity risk and its implications for expected returns are empirically tested using the conditional liquidity adjusted capital asset pricing model (LCAPM), where stock returns are cross-sectionally dependent on market risk and three additional betas (β1, β2 , β3 ) that capture different aspects of illiquidity and its risk. The findings reveal some support for the conditional capital asset pricing model (CAPM), but results are not robust to alternative specifications and estimation techniques. The total effect of liquidity risk is 0.11%, and illiquidity is 2.5% per year. Illiquidity premium depends on the expected transaction cost at the end of the holding period for investors' 2.5%. This makes the overall illiquidity premium of 2.61%. These estimates and the overall importance of liquidity level and liquidity risk depend on the model implied restrictions of a constant market risk premium and a fixed transaction cost. However, LCAPM has constructed conditionally; it can relax these model-implied constraints and estimate different liquidity risk premiums while also allowing transaction costs to be a free parameter. The overall liquidity risk characterized by liquidity betas with a single market risk premium is relatively small and barely significant in the restricted model. Using this unrestricted model, find that the overall illiquidity premium corresponds to 2.61%. The empirical results shed light on these channels' toal and relative economic significance and provide evidence of flight to liquidity.
 
 Keywords: Capital Asset Pricing Model, Liquidity Risk, Liquidity beta, Generalize Method of Movement, Sri Lanka

This paper examines the impact of liquidity and liquidity risk on the cross-section of mutual fund returns. I find that funds with the most illiquid equity holdings outperform those with the most liquid holdings by as much as 4.44 percent annually. While funds with high liquidity beta only marginally outperform those with low liquidity beta, this outperformance is significantly stronger after excluding periods of extreme market illiquidity. A one standard deviation increase in liquidity beta increases annualized fund returns by as much as 2.04 percent. Testing the two liquidity effects jointly reveals that both independently influence fund returns. Overall, I find that the liquidity level and liquidity risk of fund holdings are both important determinants of mutual fund returns.

This paper demonstrates that the ability of fund managers to create value depends on market liquidity conditions, which in turn introduces a liquidity risk exposure (beta) for skilled managers. We document an annual liquidity beta performance spread of 4% in the cross section of mutual funds over the period 1983–2014. Liquidity risk premia explain an insubstantial fraction of this spread; instead, the spread can be attributed to the differential ability of high liquidity beta funds to outperform across high and low market liquidity states, due to a differential rate of either mispricing correction or intensity of informed trading. Tests based on mispricing, proxied by a comprehensive set of 68 anomalies, and tick-by-tick trades, from a large proprietary institutional trading data set, corroborate the contribution of these channels. The results highlight the interaction between informed investors, mispricing, and liquidity beta. The Internet appendix is available at https://doi.org/10.1287/mnsc.2017.2851 . This paper was accepted by Neng Wang, finance.

This paper studies whether stock returns' sensitivities to aggregate liquidity fluctuations and the pricing of liquidity risk vary over time. We find that liquidity betas vary across two distinct states: one with high liquidity betas and the other with low betas. The high liquidity-beta state is short lived and characterized by heavy trade, high volatility, and a wide cross-sectional dispersion in liquidity betas. It also delivers a disproportionately large liquidity risk premium, amounting to more than twice the value premium. Our results are consistent with a model of liquidity risk in which investors face uncertainty about their trading counterparties' preferences.

This paper studies whether stock returns' sensitivities to aggregate liquidity fluctuations and the pricing of liquidity risk vary over time. We find that liquidity betas vary across two distinct states: one with high liquidity betas and the other with low betas. The high liquidity-beta state is short lived and characterized by heavy trade, high volatility, and a wide cross-sectional dispersion in liquidity betas. It also delivers a disproportionately large liquidity risk premium, amounting to more than twice the value premium. Our results are consistent with a model of liquidity risk in which investors face uncertainty about their trading counterparties' preferences.

The purpose of this research is to analyze Beta (systematic risk) as an intervening variable between accounting variables (Dividend Payout Ratio, Assets Growth, Firm Size, Liquidity, Financial Leverage, Earnings Variability and Accounting Beta) and share return of companies listed at the Indonesia Stock Exchange. Data employed in this study was pooled data during the period of 2001 till 2005 which consist of 624 firm-years. The analysis tools used in this research is structural equation model (SEM). The results of this research show that Beta acts as an intervening variable between Dividend Payout Ratio, Firm Size and Financial Leverage and share return. Whiles the other accounting variables (assets growth and earnings variability) have direct effect on the stock return. Evidence in small firms indicates that certain factors have direct influence to investing decision such as firm size, earnings variability and accounting Beta. The test also suggests that Beta affect relation between dividend payout ratio, firm size and leverage and share return. This research finds no support for the role of liquidity and accounting Beta neither directly to return no intervened by Beta. The whole result is consistent with the proposition that Beta has important role in investing decision besides accounting information.

Bagi perusahaan yang sangat membutuhkan pendanaan atau modal dengan segera, salah satu cara untuk mendapatkannnya tentu saja melalui listing ke pasar modal. Dimana pasar modal merupakan tempat bertemunya investor yang memiliki kelebihan dana dengan investor yang kekurangan dana. Dana tersebut dapat berupa surat-surat berharga seperti saham, obligasi dan lain sebagainya. Di dalam menanamkan atau menginvestasikan dananya seorang investor selalu melihat kondisi perusahaan yang akan diinvestasikannya, kondisi tersebut dapat berupa kondisi volatilitas harga saham perusahaan atau pergerakan harga saham perusahaan. Volatilitas harga saham menunjukkan pola perubahan harga saham yang menentukan pola return yang diharapkan dari saham. Pola perilaku saham di pasar modal menjadi perhatian bagi para pelaku pasar untuk menentukan waktu yang tepat dalam berinvestasi. Dari volatilitas harga saham tersebut dapat menghasilkan adanya return saham atau keuntungan saham, keuntungan saham tersebut dapat dipengaruhi oleh adanya resiko. Resiko tersebut dapat di ukur dengan menggunakan beta. Beta dapat terdiri dari beta pasar, beta akuntansi dan beta fundamental. Objek penelitian yang peneliti pergunakan dalam penelitian ini adalah saham LQ 45 hal yang mendasari peneliti menggunakan saham LQ 45 salah satunya saham LQ 45 merupakan saham yang paling aktif yang di perdagangkan di pasar bursa atau pasar modal. Hasil penelitian adalah beta pasar , beta akuntansi, dividen pay out ratio, asset growth, leverage, liquidity, asset size, earning variability, dan accounting beta dengan return saham memiliki nilai sebesar 37,8%, Besarnya pengaruh beta pasar, dividen pay out ratio, asset growth, leverage, liquidity, asset size, earning variability, dan accounting beta dengan return saham yang dilakukan secara gabungan sebesar 61,0%. Dividen payout ratio, asset growth, liquidity, sedangkan pengaruh tidak langsung beta pasar terhadap volatilitas harga saham melalui return saham adalag signifikan, pengaruh dividen payout ratio, beta pasar terhadap volatilitas harga saham melalui return saham adalah tidak signifikan, pengaruh asset growth terhadap volatilitas harga saham melalui return saham adalah tidak signifikan, leverage terhadap volatilitas harga saham melalui return saham adalah signifikan, liquidity terhadap volatilitas harga saham melalui return saham adalah tidak signifikan, dan asset size, earning variability, dan accounting beta terhadap volatilitas harga saham melalui return saham adalah signifikan.

I investigate whether the relation between investor sentiment and profitable trading strategies is due to short sale constraints. I find that the average security in these strategies is not hard-to-short. Furthermore, the short leg does not appear to be harder to short or more overvalued than the long leg. However, I find that these strategies are more illiquid and have higher institutional ownership following low sentiment. Additionally, I find that the long leg has a positive liquidity beta, while the short leg has a negative liquidity beta. These results imply that the relation between investor sentiment and profitable trading strategies could be due to illiquidity and institutional trading, rather than short sale constraints.

In the first study of its kind, I find evidence from the application of both time series regressions and time varying techniques, specifically the Kalman Filter, that during the financial crisis there was a significant change in the liquidity of the UK banking sector, which in some cases has not returned to its pre-crisis equilibrium. The ‘break point’ at which the liquidity beta changes trajectory has been identified in each case around the collapse of Lehman Brothers in 2008. The results highlight Standard Chartered’s liquidity position developed in an entirely different fashion – most likely due to their strong Asian, Middle East & African position leading them to ‘weather the liquidity drought’ and increase returns in the crisis period whilst its contemporaries all experienced negative abnormal returns.

Liquidity risk and expected corporate bond returns

We present an empirical study of the pricing effect of liquidity in the credit default swaps (CDS) market. We construct liquidity proxies to capture various facets of CDS liquidity including adverse selection, search frictions, and inventory costs. We show that the liquidity effect on CDS spreads is significant with an estimated liquidity premium on par with those of Treasury bonds and corporate bonds. Our finding of cross-sectional variations in the liquidity effect highlights the structure of the search-based over-the-counter market and the interplay between search friction and adverse selection in CDS trading. Using liquidity betas and volume respectively to measure liquidity risk, we find supporting evidence for liquidity risk being priced beyond liquidity level in the CDS market.

The authors study whether the pricing of systematic factors depends on the investment horizon over which risk is measured. Market beta and Fama–French value beta are priced when risk is measured over intermediate horizons, and liquidity beta is priced over short horizons. Alpha on a long–short portfolio formed on short-horizon liquidity beta increases monotonically as an investor’s horizon (for measuring risk) increases, making those assets more attractive to long-horizon investors. Institutional investors align their portfolios to harvest risk premiums that are important to investors with horizons different from their own.

The Chinese stock market’s liquidity risk premium at medium-size and large companies declined from 2002 to 2016. We find the liquidity risk premium is negative during this period. The negative liquidity risk premium demonstrates that sellers prefer to compensate buyers when stock prices crash. In addition, the portfolio liquidity risk has a structural change after the split-share structure reform. Portfolio liquidity risk diverges from the relevant prehistorical betas, during the split-share structure reform. Similarly, the historical liquidity beta is nonmonotonic with postranking liquidity beta, before the reform. However, the historical liquidity beta is monotonic with postranking beta, after the reform.