Gideon Saar

Individual Investor Trading and Stock Returns

This paper investigates the dynamic relation between net individual investor trading and short-horizon returns for a large cross-section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk-averse individuals provide liquidity to meet institutional demand for immediacy.

Individual Investor Trading and Return Patterns Around Earnings Announcements

This paper documents evidence consistent with informed trading by individual investors around earnings announcements using a unique dataset of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose the abnormal returns into a component that is attributed to risk-averse liquidity provision and a component that is attributed to private information or skill, and show that about half of the abnormal returns in the three months following the event can be attributed to private information. We also examine the behavior of individuals after the earnings announcement and find that they trade in the opposite direction to both pre-event returns (i.e., exhibit “contrarian�? behavior) and the earnings surprise (i.e., exhibit “news-contrarian�? behavior). The latter behavior, which could be consistent with profit-taking, has the potential to slow down the adjustment of prices to earnings news and contribute to the post-earnings announcement drift.

Relative Tick Size and the Trading Environment

This paper examines how the relative tick size influences market liquidity and the biodiversity of trader interactions. Using unique NYSE order-level data, we find that a larger relative tick size benefits High-Frequency Trading (HFT) firms that make markets on the NYSE: they leave orders in the book longer, trade more aggressively, and have higher profit margins. The effects of a larger relative tick size on the market are more complex. In a one-tick spread environment, a larger relative tick size results in greater depth and more volume; in a multi-tick environment, the opposite outcome prevails. The negative impact on depth and volume in the multi-tick environment is consistent with greater adverse selection coming from increased undercutting of limit orders by informed HFT market makers. Our work suggests why a one-size-fits-all spread policy is unlikely to be optimal, and we propose an alternative policy.