Plain old diversification may still be an investor’s best bet at equity outperformance, says a study.
No strategy consistently beats equally weighted stock portfolios in terms of mean excess return, Sharpe ratio, or turnover, according to research by Horizon Investments.
“These results add to the mounting evidence of the poor performance of portfolio optimization techniques,” said Mike Dickson, Horizon’s director of structured financial solutions. “Practical optimization techniques are inferior to naive diversification when forming portfolios of individual stocks.”
For the study, Dickson compared the performance of 15 portfolio construction techniques using individual stock data from July 1963 to December 2013. Techniques evaluated included mean-variance strategies, such as volatility timing and reward-to-risk timing, as well as parametric portfolio choice techniques.
He found that “naive diversification”—holding asset weights equal—routinely had one of the largest mean returns, best Sharpe ratios, and smallest measures of turnover, or trading costs.
Many of the mean-variance extensions performed well when tested in a simulation experiment, reducing estimation risk and turnover. However, when the strategies were applied to actual stock data, the improvements in performance were “not large enough to consistently top naive diversification.”
“These techniques are incapable of outperforming naive diversification using actual stock data,” he argued.
Parametric portfolio choice frameworks similarly failed to outperform plain vanilla equal-weighting.
“These results should serve as a warning to investors when attempting to optimize over a portfolio of stocks,” Dickson wrote. “Simply put, naive diversification is hard to beat.”
Read the full report, “Naive Diversification Isn’t So Naive After All.”
Related: When is Diversification a Bad Idea?