NOTE: This column was originally published on the Saporta Report Thought Leadership website on May 22, 2018. Visit https://leadership.saportareport.com/higher-education/ for more insight about a range of topics from top researchers and scholars at Georgia State. New columns are published weekly.
By Scott Murray, Assistant Professor of Finance
If you invest in high-risk stocks, you should expect, on average and in the long run, higher returns than if you invest in low-risk stocks, right?
That’s what financial economic theory tells us, but when we looked at data on stock returns from 1963-2012, we found that portfolios containing high-risk stocks generate about the same return as portfolios containing low-risk stocks.
Why the discrepancy? An article recently published in the Journal of Financial and Quantitative Analysis titled “A Lottery Demand-Based Explanation of the Beta Anomaly” that I co-authored with Turan G. Bali, Stephen J. Brown and Yi Tang investigates why the history of stock returns diverges so dramatically from what economists may expect.
As you probably know, price of stock is determined by demand. The higher a stock’s demand, the higher the price. The amount of risk a stock bears, also known as its “beta”, determines the return investors can expect. Stocks with higher risk levels should, in theory, result in higher returns for investors.
What we found is that high-risk stocks also tend to be stocks that are lottery-like in nature, meaning that they have the possibility of experiencing a very large increase in price at any point in time. Certain investors are attracted to these lottery stocks, and this attraction generates demand which pushes the price of these stocks too high. The high price means that, if you buy the stock today, you are probably overpaying for the stock and it will produce relatively low returns in the future. Thus, by buying high-risk stocks, investors are coincidentally also purchasing lottery-like stocks, which tend to be overpriced today and thus generate low future profits.
In our paper’s main analysis, we redesigned the portfolios in our data set to make sure that the high-risk portfolio has the same proportion of lottery stocks as the low-risk portfolio.
By doing so, we ensured that both portfolios are equally subjected to the price impact of demand by lottery investors. Our results show that when the portfolios are constructed in this manner, the performance of the portfolios is in line with what is predicted by economic theory.
So what does all this mean for investors? It’s a basic caveat every investor must understand. They must be cautious when investing in high-risk stocks and expecting high returns. When looking for high returns, investors need to assemble a diverse portfolio that is not overly exposed to lottery-like stocks.
Because timing in the stock market is everything, one aspect of our research that warrants further examination is when investors identify lottery-like stocks and when they decide to buy and sell them.
Department of Finance
Scott Murray’s research focuses on empirical asset pricing, including identifying and explaining patterns in security returns, with an emphasis on the stock and stock option markets.