Proposal on Fund Liquidity, Liquidity Risk and Information

Proposal on fund liquidity, liquidity risk and Information

In this section, we try to systematically discuss several fund liquidity management problems.

Motivation

Fund liquidity is the salient future of fund products and services (Wahal and Wang 2011). Funds position their holdings along a liquidity spectrum (Chordia 1996). Actually, fund liquidity provides us an import perspective to detect fund behavior. Typically, managers need to balance the benefit of a liquidity stock (lower transaction cost) with the cost of holding a liquidity stock (lower expected performance) (Massa and Phalippou 2005; Lynch and Yan 2012).

Stock-level liquidity has been explored by academics as an important explanatory risk factor (Huang 2003; Pástor and Stambaugh 2003; Acharya and Pedersen 2005; Watanabe and Watanabe 2008). However, the existence of a liquidity risk premium in the cross-section of tradable assets does not necessarily imply a similar premium in the cross-section of portfolios of such assets (Dong et al. 2011). Actually, liquidity management has become a particularly important determinant of the cross-section of mutual fund future performance except other fund characteristics, for example, funds follow, career concerns, the trading motivation and so on. (Cohen et al. 2005; Alexander et al. 2007; Daniel et al. 2007; Yan 2008; Lynch and Yan 2012). Heterogeneity in liquidity needs leads to predictability in the performance. The nature of relationship between liquidity and performance reflects the efficiency of mutual fund market (Berk and Green 2004). In addition, a fund’s exposure to liquidity risk may signify the fund manager’s skill/ability to generate abnormal performance (Dong et al. 2011). That motives us to investigate the determinants of liquidity risk, especially the role of information, which is helpful for us to understand the smart money effect and diseconomies of scale (Dong et al. 2011).

Moreover, investor behavior is an endogenous factor that determines liquidity. Short-term convergence traders do not influence the liquidity of specific security, but it generates a liquidity contagion among all securities (Shawky and Tian 2011). It is reasonable to expect liquidity is managed actively by mutual fund managers. We divide liquidity management motive into precautionary motive and speculative motive. And we aim to explore information spillover for fund managers in competition using liquidity as an important medium. In particular, we try to develop risk-adjustment behavior in the tournament (Kempf and Ruenzi 2008) under liquidity constrains.

Contribution

Recent researches provide evidence that liquidity risk of fund holdings has been priced in the market (Lynch and Yan 2012). However, they ignore the role of information on the liquidity risk. Lambert et al. (2007) suggest higher information quality lowers market risk and cost of capital in the traditional capital asset pricing model framework. Ng (2011) finds higher information quality is associated with lower stock liquidity risk because of greater uncertainty and adverse selection. We firstly investigate effects of information quality on the performance of mutual funds that may be helpful to explain smart money effect and diseconomies of scale (Dong et al. 2011).

Second, we try to detect dynamic liquidity and liquidity management process based on private information. Lo et al. (2003) theoretically prove that liquidity is carefully and likely optimally managed. We argue that private information is crucial factor to manage liquidity driven by expected market volatility. We use portfolio approach to emphasize on role of private information on the dynamic liquidity preference hypothesis (Huang 2012).

Third, fund managers actively manipulate prices of stocks they hold (Carhart et al. 2002). These actively manipulation full of information will affect other fund managers’ choice. These funds compete for information about similar assets and dispersion in beliefs tends to place large bet relative to their peers if he is informed managers (Jiang and Sun 2011; Gupta-Mukherjee 2013). We first detect game behavior (Taylor 2003) to emphasize individual manager’s decision using liquidity as medium omitted by previous researchers. Our work may provide another explanation for the career concern theory in the labor market (Scharfstein and Stein 1990). And we address time-varying characteristics of liquidity and liquidity risk adjustments in the competition environment.

In particular, our work is a development of tournament behavior within families (Kempf and Ruenzi 2008). The convex incentive structure within mutual fund families gives rises to adjust risk. However, it is not obvious how managers operate liquidity in this tournament. We provide evidence on the risk adjustment under liquidity constrains and liquidity risk management.

Literature Review

Recent literatures begin to pay more attention on the predictability of liquidity and liquidity risk to the fund performance. Dong et al. (2011) demonstrate that the systematic liquidity-risk exposures of mutual funds can predict their performance in the cross-section. Yan (2008) empirically finds there is stronger inverse relation between size and performance when funds hold less liquid portfolios. This relation is also more pronounced among growth and high turnover funds that tend to have high demands for immediacy. Lynch and Yan (2012) examine the impact of liquidity and liquidity risk on the cross-section of mutual fund returns. Testing the two effects jointly reveals that both independently influence fund returns. Most illiquid equity holdings outperform those with the most liquid holdings by as much as 4.44 percent annually. Similarly, Idzorek et al. (2012) point out mutual funds that hold relatively less liquid stocks from within the liquid universe of publicly traded stocks out-performed mutual funds that hold relatively more liquid stocks by 2.65%. Sadka (2010) demonstrates that liquidity risk is an important determinant in the cross-section of hedge-fund returns.

Considerable evidences show that liquidity is actively managed by fund managers. Huang (2012) examines the relation between expected market volatility and the demand for liquidity in open-end mutual funds. He finds mutual fund managers hold more cash and tilt their holdings more heavily on liquid stocks when expected market volatility is high. Shawky and Tian (2011) find that on average, small-cap mutual fund managers are able to earn an additional1.5% return per year as compensation for providing liquidity creation to the market. Massa and Phalippou (2005) use a large sample of US active equity mutual funds from 1983 to 2001, and show that portfolio liquidity is actively managed and chosen as a function of the multiple liquidity needs.