Do stocks with high volatility consistently have the lowest returns and vice-versa? A StarMine report examines the low volatility anomaly in different geographic regions using 20 years of data.
- The StarMine Quantitative Research team investigates the low volatility anomaly by studying stock returns and the Sharpe Ratio in the U.S and other regions.
- Stocks with the highest volatility typically have the lowest returns and vice-versa, with Canada and developed Asia presenting the strongest volatility-to-returns relationship.
- The research helps to explore the idea of using volatility as a factor in future StarMine stock selection models.
The observation that high beta assets tend to compensate investors less than is predicted by the Capital Asset Pricing Model has been tested in several studies going back several decades.
The studies have typically shown that the relationship between historical volatility and returns is either flat or inverted. This is generally referred to as the ‘low volatility anomaly’.
A new report by the StarMine Research team investigates this anomaly by leveraging Refinitiv data and evaluating results up to recent time periods.
Download the report: How volatility performs in the long term
The study of stock returns and the Sharpe Ratio in the United States and other geographic regions covered different volatility portfolios for the period of 31 July, 1999 to 31 July, 2019.
Low volatility portfolios
They observed that the stocks with the highest volatility typically have the lowest returns and vice-versa.
For large capitalization U.S. stocks, this relationship nearly disappeared in recent years. But it remains in mid- and small-cap stocks, as well as in other markets, with Canada and developed Asia presenting the strongest and emerging markets the weakest forms of it.
The StarMine Research team found that the lowest volatility portfolio is the one with the highest risk-adjusted returns, as measured by the Sharpe Ratio. Similar results are found when using both equal and market capitalization weights, as well as when using different definitions of volatility.
StarMine stock selection
The motivation for this research is to explore the idea of using volatility as a factor in future StarMine stock selection models. In the research note, the StarMine Quantitative Research team seeks merely to describe findings on the behavior of portfolios formed that have been based on trailing volatility.
Download the report: How volatility performs in the long term
The analysis does not seek to defend nor debunk the low volatility anomaly in a multi-factor analysis.
This work is a springboard to future StarMine research on that topic, and meanwhile they hope that their findings will be of use to investors who themselves are interested in the volatility factor.
