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Can Shorts Predict Returns? A Global Perspective

Review of Financial Studies 2022 35(5), 2428-2463
Using multiple short-sale measures, we examine the predictive power of short sales for future stock returns in 38 countries from July 2006 to December 2014. We find that the days-to-cover ratio and the utilization ratio measures have the most robust predictive power for future stock returns in the global capital market. Our results display significant cross-country and cross-firm differences in the predictive power of alternative short-sale measures. The predictive power of shorts is stronger in countries with nonprohibitive short sale regulations and for stocks with relatively low liquidity, high shorting fees, and low price efficiency.

Retail Trading and Return Predictability in China

Journal of Financial and Quantitative Analysis 2025 60(1), 68-104
Using comprehensive account-level data, we separate Chinese retail investors into 5 groups and document strong heterogeneity in trading dynamics and performances. Retail investors with smaller account sizes cannot predict future returns correctly, display daily momentum patterns, fail to process public news, and show overconfidence and gambling preferences, while retail investors with larger account balances predict future returns correctly, display contrarian patterns, and incorporate public news in trading. Using performance measures established in previous literature, we find that smaller retail investors suffer from poor stock selection abilities and trading costs, while large retail investors’ stock selection abilities are offset by trading costs.

When do short sellers trade? Evidence from intraday data and implications for informed trading models

Journal of Financial Economics 2025 172, 104148
Using 2015–2019 intraday short sale data from CBOE, we show that shorting flows near the open, middle, and close all negatively predict future returns, but the shorting flows near the open and middle have stronger predictive power than shorting flows near the close. We relate our findings to three informed trading models with different predictions on the timing of the trades. The long term predictive power of shorting flows near the open and midday is consistent with Kyle’s (1985) model of steady trading; the intraday variation in shorting flows’ predictive power is more consistent with Holden and Subrahmanyam’s (1992) aggressive trading model, in the sense that predictive power of shorting flows is stronger when there is greater urgency to trade at open and when the securities lending market is more competitive; and the liquidity timing hypothesis from Collin-Dufresne and Fos (2016) is also supported by the finding that opening shorting flows increase for firms with better liquidity conditions.

Tracking Retail Investor Activity

Journal of Finance 2021 76(5), 2249-2305
We provide an easy method to identify marketable retail purchases and sales using recent, publicly available U.S. equity transactions data. Individual stocks with net buying by retail investors outperform stocks with negative imbalances by approximately 10 bps over the following week. Less than half of the predictive power of marketable retail order imbalance is attributable to order flow persistence, while the rest cannot be explained by contrarian trading (proxy for liquidity provision) or public news sentiment. There is suggestive, but only suggestive, evidence that retail marketable orders might contain firm‐level information that is not yet incorporated into prices.