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  • Home>Research & Insights>Gray Matters>Less-Liquid Holdings Mean More-Solid Results

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    Less-Liquid Holdings Mean More-Solid Results

    The liquidity investment style is present in mutual funds and leads to dramatic differences in performance. 

    James X. Xiong and Thomas Idzorek and Roger Ibbotson, Ph.D., 10/19/2012

    This article originally appeared in the October/November 2012 issue of MorningstarAdvisor magazine.  To subscribe, please call 1-800-384-4000. 

    It is well known that less-liquid investments tend to outperform more-liquid investments. The same holds true within the universe of publicly traded stocks. The generally accepted rationale for a liquidity premium is that all else equal, investors prefer greater liquidity; thus, in order to induce investors to hold less-liquid assets, they must have the expectation (but not the guarantee) of a return premium.

    Recent literature indicates that the liquidity investment style—the process of investing in less-liquid stocks within the liquid universe of publicly traded stocks—produces risk adjusted returns that rival or exceed those of the three best-known market anomalies: size, value, and momentum (see Carhart, 1997). For example, Amihud and Mendelson (1986) used the quoted bid-ask spread as a measure of liquidity and tested the relationship between stock returns and liquidity during the period of 1961 –1980. They found evidence consistent with the notion of a liquidity premium. Datar, Naik, and Radcliffe (1998) used the turnover rate (number of shares traded as a fraction of the number of shares outstanding) as a proxy for liquidity and found that stock returns were strongly negatively related to their turnover rates, confirming the notion that less liquid stocks provided higher average returns. Overall, the results supported the relationship between less liquidity and higher stock returns.

    While stock-level liquidity has been explored by academics as an important “risk factor” and as an ongoing concern for portfolios that need immediate liquidity, it is only recently that it has been explored as an investment style similar to how an investor might prefer funds with a small-cap or value bias. To that end, and perhaps most importantly for our purposes, using monthly data for the largest 3,500 U.S. stocks by capitalization, starting in 1972, Ibbotson, Chen, and Hu (2012) sorted stocks into equally weighted quartiles based on liquidity. The results clearly showed that annually rebalanced composites of relatively less-liquid stocks significantly outperformed composites of more-liquid stocks after controlling for size, valuation, and momentum. Ibbotson et al. attempted to distinguish between risk factors and an investment style, ultimately characterizing liquidity as the missing style.1

    Despite these powerful stock-level liquidity findings, we are practically unaware of any mutual fund managers who actively seek less-liquid stocks. Might this emerging investment style and risk factor be present and economically significant among mutual funds? If so, methods of constructing portfolios of less-liquid stocks might be beneficial for not only creating mutual funds but also for selecting mutual funds that are more likely to outperform their peers.

    Data and Methodology
    Combining data from Morningstar’s individual stock database with Morningstar’s mutual fund holding database, we built composites of mutual funds based on the weighted average liquidity of the individual stocks held by the mutual funds. Morningstar’s U.S. open-end equity mutual fund universe contains 5,198 funds (including funds now defunct).

    There are a number of measures of liquidity for an individual stock. For simplicity and consistency, we focused on the basic stock level “turnover” measure used in Ibbotson, Chen, and Hu (2012): average daily shares traded over the past year divided by the number of shares outstanding. No attempt was made to adjust the number of shares outstanding for free-float.

    Armed with each mutual fund’s weighted average stock level liquidity within any given category, we rank-ordered the mutual funds based on their weighted average liquidity and used this information to form monthly rebalanced, equally weighted composites (in our case, quintiles) of mutual funds with similar-weighted average stock-level liquidity scores. Funds with the lowest weighted average liquidity were assigned to the “L1” quintile and funds with the highest weighted average liquidity were assigned to the “L5” quintile. The constituent mutual funds in the composite evolve each month, as the weighted average stock level liquidity of the mutual funds evolves.