We construct a "universe" of over 18,000 fundamental signals from financial statements and use a bootstrap approach to evaluate the impact of data mining on fundamental-based anomalies. We find that ...many fundamental signals are significant predictors of cross-sectional stock returns even after accounting for data mining. This predictive ability is more pronounced following high-sentiment periods and among stocks with greater limits to arbitrage. Our evidence suggests that fundamental-based anomalies, including those newly discovered in this study, cannot be attributed to random chance, and they are better explained by mispricing. Our approach is general and we also apply it to past return–based anomalies.
We show that the positive relation between institutional ownership and future stock returns documented in Gompers and Metrick (2001) is driven by short-term institutions. Furthermore, short-term ...institutions' trading forecasts future stock returns. This predictability does not reverse in the long run and is stronger for small and growth stocks. Short-term institutions' trading is also positively related to future earnings surprises. By contrast, long-term institutions' trading does not forecast future returns, nor is it related to future earnings news. Our results are consistent with the view that short-term institutions are better informed and they trade actively to exploit their informational advantage.
Using a large proprietary database of institutional trades, this paper examines the interim (intraquarter) trading skills of institutional investors. We find strong evidence that institutional ...investors earn significant abnormal returns on their trades within the trading quarter and that interim trading performance is persistent. After transactions costs, our estimates suggest that interim trading skills contribute between 20 and 26 basis points per year to the average fund's abnormal performance. Our findings also indicate that any trading skills documented by previous studies that use quarterly data are biased downwards because of their inability to account for interim trades.
Using a comprehensive set of 103 equity strategies, we analyze the value of volatility-managed portfolios for real-time investors. Volatility-managed portfolios do not systematically outperform their ...corresponding unmanaged portfolios in direct comparisons. Consistent with Moreira and Muir (2017), volatility-managed portfolios tend to exhibit significantly positive alphas in spanning regressions. However, the trading strategies implied by these regressions are not implementable in real time, and reasonable out-of-sample versions generally earn lower certainty equivalent returns and Sharpe ratios than do simple investments in the original, unmanaged portfolios. This poor out-of-sample performance for volatility-managed portfolios stems primarily from structural instability in the underlying spanning regressions.
This study examines the impact of block ownership on the firm’s information environment. Previous research shows that stock price efficiency depends on the cost of acquiring private information, as ...well as on the precision of this information. Blockholders have a clear advantage over diffuse, atomistic shareholders in terms of the precision and acquisition cost of their private information. We hypothesize that this informational advantage will manifest itself primarily in the firm-specific component of stock returns. Our empirical findings confirm that blockholders increase the probability of informed trading and idiosyncratic volatility, and decrease the firm’s stock return synchronicity. These results hold for both inside and outside blockholders, but are insignificant for blocks controlled by employee stock ownership plans (ESOPs). Overall, our findings support the contention that ownership structure plays a significant role in shaping the firm’s information environment.
Shorting flows remain a significant predictor of negative future stock returns during 2010–2015, when daily short-sale volume data are published in real time. This predictability decays slowly and ...lasts for a year. Long-term shorting flows are more informative than short-term shorting flows. Indeed, abnormal short-term shorting flows do not predict future returns or anticipate bad news. We find that short sellers exploit prominent anomalies. A comparison with the Regulation SHO data indicates that the predictability is much shorter-term during 2005–2007. Short sellers appear to have shifted from trading on short-term private information to trading on long-term public information that is gradually incorporated into prices.
Behavioral theory predicts that investor overconfidence leads to overpricing because overconfident investors overestimate the quality of their information and underestimate risk. We test this ...prediction by using a measure of investor overconfidence derived from the characteristics and holdings of U.S. equity mutual fund managers. We find that firms with more overconfident investors are relatively overvalued based on the market-to-book ratio and a misvaluation measure. The result is stronger among stocks with greater mutual fund ownership, particularly by active mutual funds. Firms with more overconfident investors also exhibit lower subsequent stock returns, issue more equity, and invest more. Overall, our findings suggest that investor overconfidence is significantly related to firm valuation and corporate decisions.
The Internet appendix is available at
https://doi.org/10.1287/mnsc.2017.2806
.
This paper was accepted by Neng Wang, finance.
Using stock transactions data along with detailed stockholdings for a comprehensive sample of U.S. actively managed equity mutual funds from 1993 to 2002, this paper empirically examines the effect ...of liquidity and investment style on the relation between fund size and fund performance. Consistent with Chen, Hong, Huang, and Kubik (2004), I find a significant inverse relation between fund size and fund performance. Further, this inverse relation is stronger among funds that hold less liquid portfolios. The inverse relation between fund size and fund performance is also more pronounced among growth and high turnover funds that tend to have high demands for immediacy. Overall, this paper's findings suggest that liquidity is an important reason why fund size erodes performance.
Using a large proprietary database of institutional trades, we investigate whether institutional investors drive the turn-of-the-year (TOY) effect. Institutions that engage in window dressing, ...tax-loss selling, or risk shifting will contribute to the TOY effect by selling small, poorly performing stocks at the end of December and/or buying those same stocks at the beginning of January. We find abnormal pension fund selling in small stocks with poor past performance during the final trading days in December, providing some support for the window dressing hypothesis. However, we find little evidence that institutional tax-loss selling or risk-shifting trading strategies contribute to TOY returns. Furthermore, stocks with no institutional trading around the year-end exhibit considerably stronger TOY return patterns than stocks in which institutions trade. Taken together, our results suggest that institutions play a limited role in driving the TOY effect.
Does Idiosyncratic Risk Really Matter? BALI, TURAN G.; CAKICI, NUSRET; YAN, XUEMIN (STERLING) ...
The Journal of finance (New York),
April 2005, Volume:
60, Issue:
2
Journal Article
Peer reviewed
Goyal and Santa-Clara (2003) find a significantly positive relation between the equal-weighted average stock volatility and the value-weighted portfolio returns on the NYSE/AMEX/Nasdaq stocks for the ...period of 1963:08 to 1999:12. We show that this result is driven by small stocks traded on the Nasdaq, and is in part due to a liquidity premium. In addition, their result does not hold for the extended sample of 1963:08 to 2001:12 and for the NYSE/AMEX and NYSE stocks. More importantly, we find no evidence of a significant link between the value-weighted portfolio returns and the median and value-weighted average stock volatility.
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