Summary:
The Administrative Measures for the Operation and Management of Publicly Offered Securities Investment Funds, implemented in August 2014, require the leverage of fixed-income funds to be below 140% but give no explicit requirement for the leverage of equity funds. In practice, equity funds barely invest on margin and even set aside a high proportion of cash reserves (Simutin, 2014; Boguth and Simutin, 2018). This self-imposed zero-leverage constraint is implicit and motivates funds to indirectly gain leverage by holding high beta stocks when funding conditions deteriorate. Based on this intuition, this paper uses actively managed equity-oriented open-end funds from 2003 to 2019 to explore the implications of the aggregate mutual fund beta. We aggregate all actively managed equity funds in China to a hypothetical large fund and calculate the value-weighted average market beta of its aggregate A-share holdings. Following Brunnermeier and Pedersen (2009), we conjecture that a priced liquidity risk factor drives the dynamic of the aggregate mutual fund beta. The time series of the aggregate mutual fund beta contains useful information on the tightness of implicit leverage constraints for Chinese mutual funds and reflects the liquidity condition in the stock market. Furthermore, we investigate whether loadings on changes in the aggregate mutual fund beta predict returns in the cross-section. We find that exposure to the monthly change in the aggregate mutual fund beta unconditionally fails to predict returns at the firm and fund levels. In contrast, such exposure negatively predicts stock and fund returns following periods of low sentiment or low liquidity. The negative price of the change in the tightness of implicit leverage constraints is consistent with the notion that an asset that pays off when implicit leverage constraints are tighter provides capital when the capital is most valuable. As a result, the strong performance of stocks and funds with low exposure to implicit leverage constraints following periods of low sentiment or low liquidity can be rationalized as compensation for liquidity risk. However, short-sale constraints prohibit the positive relationship between leverage tightness exposure and stock returns after periods of high sentiment. By exploiting the staggered implementation of pilot marginable stocks in China, our study compares the cross-sectional pricing power of changes in implicit leverage constraints among pilot and non-pilot stocks. We find that the distorted risk-return relationship is more pronounced among stocks that are ineligible for margin trading. This confirms our conjecture regarding conditional pricing, namely, that in high-sentiment regimes, short-selling constraints lead to active leverage constraints and thus affect the pricing kernel.Next, recent papers document that funds oriented toward small-and medium-cap stocks exhibit a stronger liquidity preference in deteriorating funding conditions (Li et al., 2015; Zhang et al., 2017). We construct the fund-beta-based implicit leverage constraint using funds investing in small-and medium-sized stocks and document that this aggregate beta measure captures the dynamics of funding liquidity in a more timely manner. This study extends the literature in two ways. First, we propose a measure for implicit leverage constraints. Different from developed markets, retail investors have long been important market participants in the A-share market. Meanwhile, the recent emergence of high-frequency trading, together with retail investors' noisy trading, may invalidate turnover as an effective proxy for market funding conditions (Baker and Wurgler, 2007). The proposed aggregate risk-taking measure of mutual funds can be used as a market-based forward-looking signal of market illiquidity. Second, we explore the interaction between implicit and explicit leverage constraints. We show that the distorted risk-return relationship between leverage tightness exposure and stock returns is more pronounced among stocks that are ineligible for margin trading, especially after periods of high sentiment. These findings provide direct evidence of the conditional pricing of liquidity risk. However, semi-annual snapshots of fund holdings fail to capture the daily trading activities of active funds, thus contaminating our liquidity measure. We mitigate this concern by dropping funds with a high probability of window dressing, and our main findings remain unchanged. In addition, it is possible that other forces overlap with our sentiment channel; for example, the timing ability of fund managers and investor inflows/outflows may affect the aggregate fund beta. Furthermore, it is relevant to investigate whether mutual fund herding during high-sentiment periods affects price efficiency. We leave these questions for future research.
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