This paper explores whether firms manage their earnings after stock splits to meet the raised expectations from the market due to the positive signal sent by the splits. We first document that post-split drift mainly exists in the first three months and is positively associated with post-split standardized unexpected earnings (SUE). However, the higher post-split SUE of split firms is associated with higher discretionary accruals and abnormally lower R&D expenses. This result is consistent with our hypothesis that split firms overstate their post-split earnings by manipulating accruals and reducing R&D spending. Moreover, post-split abnormal returns increase with discretionary accruals and R&D reduction for about six months and tend to reverse over longer horizons, especially for firms with negative pre-split SUE. Overall, our results indicate that the post-split drift is a short-term phenomenon and partly attributable to the earnings management after the splits.

We hypothesize that cognitive limitation may be manifested in a disproportionately large volume of limit orders submitted at round-number prices if investors use these numbers as cognitive shortcuts. Using detailed limit order data in the Taiwan Futures Exchange, we find that investors with lower cognitive abilities, defined as higher limit order submission ratios at round numbers, suffer greater losses in their round-numbered and non-round-numbered limit orders, market orders, and round-trip trades. The positive correlation between cognitive ability and investment performance is monotonic and robust across futures and options markets. In addition, past trading experience helps mitigate cognitive limitation.

We provide a psychological explanation for the delayed price response to news about economically linked firms. We show that the return predictability of economically linked firms depends on the nearness to the 52-week high stock price. The interaction between news about economically linked firms and the nearness to the 52-week high can partially explain the underreaction to news about customers, geographic neighbors, industry peers, or foreign industries. We also find that analysts react to news about economically linked firms but the 52-week high effect reduces such reactions, providing direct evidence that the 52-week high affects the belief-updating process.

We propose that firms use stock splits as a means of attracting attention and inducing information production to correct price distortion caused by investors’ 52-week high anchoring bias. Our analysis shows that firms are more likely to split stocks when their prices are near 52-week highs, especially if they are highly profitable and undervalued. After splits, undervaluation gradually disappears. Moreover, these splits are associated with a slower market reaction and a more positive post-split drift, consistent with the notion that investors’ anchoring bias hinders price adjustment, leading to a gradual price correction. In addition, the likelihood of such splits increases with CEO wealth-performance sensitivity, and investment-price sensitivity increases following splits. Our evidence suggests that firms utilize stock splits to correct mispricing induced by investors’ 52-week high anchoring bias.

This article provides the first comprehensive evidence that the return extrapolation behavior of investors leads to biases in the expectations of volatility. Lower past returns are associated with higher expectations of volatility when using the physical, risk-neutral, and survey measures to estimate volatility expectations. Consistent with the return extrapolation framework, recent past returns have a larger impact than distant past returns on volatility expectations. Biases in volatility expectations are i) distinct from extrapolating past realized volatility, ii) asymmetrically induced by recent past negative returns, and iii) lead investors to pay more to insure against the perceived higher expected volatility.

In this article, we use volatility surface data from options contracts to document a strong, robust, and positive cross-sectional relation between risk-neutral skewness (RNS) and subsequent stock returns. The differential return between high- and low-RNS stocks amounts to 0.17% per week. Preannouncement RNS is positively related to earnings announcement returns, and the positive RNS–return relation is more pronounced for other nonscheduled news releases. This suggests that it is informed trading that drives the positive relation between RNS and subsequent stock returns. We also find that RNS contains incremental information beyond trading signals captured by option-implied volatility and volume.

This study examines the informational content of options trading on acquirer announcement returns. We show that implied volatility spread predicts positively on the cumulative abnormal return (CAR), and implied volatility skew predicts negatively on the CAR. The predictability is much stronger around actual merger and acquisition (M&A) announcement days, as compared with pseudo-event days. The prediction is weaker if pre-M&A stock price has incorporated part of the information, but stronger if the acquirer’s options trading is more liquid. Finally, we find that a higher relative trading volume of options to stock predicts higher absolute CARs. The relation also exists among the target firms.

We develop a new methodology to estimate abnormal performance and risk exposure of nontraded assets from cash flows. Our methodology extends the standard internal rate of return approach to a dynamic setting. The small-sample properties are validated using a simulation study. We apply the method to a sample of 958 private equity funds. For venture capital funds, we find a high market beta and underperformance before and after fees. For buyout funds, we find a relatively low market beta and no evidence for outperformance. We find that self-reported net asset values significantly overstate fund values for mature and inactive funds.

We use data on signed option volume to study which components of option volume predict stock returns and resolve the seemingly inconsistent results in the literature. We find no evidence that trades related to synthetic short positions in the underlying stocks contain more information than trades related to synthetic long positions. Purchases of calls that open new positions are the strongest predictor of returns, followed by call sales that close out existing purchased call positions. Overall, our results indicate that the role of options in providing embedded leverage is the most important channel why option trading predicts stock returns.

We hypothesize that high stock price levels impede informed trading on the stocks and reduce price informativeness. This is because uninformed trading is needed to facilitate informed trading, and high stock prices may impose budget constraints on uninformed investors. Indeed, we find, for high-price firms, (i) options to stock trading volume (O/S), an informed trading measure in options market, is higher, (ii) price informativeness about future earnings is lower, and (iii) investment sensitivity to price is lower. We also find these patterns reverse after stock splits, suggesting that firms can use splits to improve informed trading and enhance price informativeness.