RESEARCH
RESEARCH REPORTS
BREAKOUTS: PUMP UP THE VOLUME
We studied patterns of stock returns, following breakout events from an O’Neil pattern, across our U.S. universe from 1995‒2021. We found generally that breakouts that were accompanied with high volume percentages led to post-event excess returns for up to 63 trading days (or approximately three months) afterward. While all breakouts were followed by positive alpha, breakouts with volume percentage changes in excess of 150% had cumulative alpha of 2.8% on average. These results suggest that breakouts with high volume percentage changes may signal demand from institutional investors that dominate trading volume on U.S exchanges.
Price Gaps: Growing by Leaps and Bounds
This brief examines the performance of gap-ups and gap-downs segmented by style (growth/value) and size (large caps/small caps). Our team found that gaps generate much stronger momentum-like signals for growth stocks than for value stocks for both gap-ups and gap-downs. For gap-downs, they found a stronger bearish momentum effect for large-cap stocks than small-cap stocks.
HOTNESS: HIGH TURNOVER HOT STOCKS EVENTUALLY GO COLD
In this paper, we explore the relationship between levels of speculative trading intensity (Hotness) and excess returns. We perform cross-sectional studies comparing the returns of Hot versus Cold stocks, which we differentiate with our proprietary measure of speculative trading intensity.
GAP-DOWNS: THE BIGGER THEY ARE, THE HARDER THEY FALL
The brief highlights the effect of gap-downs on stock price performance over three subsequent months. The team compares price gap-downs from less than two standard deviations of average daily price move to more than four standard deviations in the U.S. market from January 1995 to September 2020 utilizing William O’Neil + Co.’s proprietary database.
Volatility: Slow and Steady Wins the Race
Previous studies have found evidence of persistent underperformance of high-volatility stocks compared with lower-volatility stocks on a risk-adjusted basis. Consistent with prior studies, our cross-sectional research found that U.S. stocks in the top (highest) volatility quintile significantly underperform those in the bottom (least volatile) quantile such that long-short portfolios constructed on the basis of volatility quintile rankings generate significantly negative returns while remaining market-neutral. These volatility Q5–Q1 portfolios have positive exposure to size (SMB) and negative exposure to value (HML). However, these portfolios are prone to short-term losses during bear markets.