Winners Vs. Losers
Cornell, Hsu and Nanigian also examined the counterintuitive “loser strategy,” which follows the same procedure but invests in products that rank in the bottom decile of benchmark-adjusted returns.
The winner-strategy bucket would generally consist of fund managers that investment consultants would recommend to their pension clients. Managers in the loser-strategy bucket would generally be put on a “watch list” and actively replaced in client portfolios by managers on the recommended list.
Finally, they also compared the investment performance produced by an unorthodox strategy of investing in products that underperformed their benchmarks by more than 1% per year, as well as the even more extreme case of investing in products that underperformed their benchmarks by more than 3% per year.
These portfolios provide insight into the impact of the common manager firing heuristic. Their sample excluded funds that did not have at least $1 billion in AUM and also those that ranked in the top decile of expense ratio (research shows that expensive mutual funds tend to be persistent underperformers because of costs). Their study covers the period 1994 through 2015.
Following is a summary of their findings:
- The average benchmark-adjusted return for the median strategy beats that of the winner strategy by 1.32 percentage points per year (-1.07% versus -2.39%), and the loser strategy outperforms the median strategy by 0.96 percentage points per year (the loser strategy had a benchmark-adjusted return of -0.11). Thus, the loser strategy outperformed the winner strategy by 2.28 percentage points per year.
- In addition to benchmark-adjusted returns, the median strategy outperforms the winner strategy across all other performance metrics commonly employed in academic studies, while the loser strategy outperforms the median strategy.
- The Sharpe ratio of the median strategy is 0.42 versus 0.25 for the winner strategy, while the loser strategy produced a Sharpe ratio of 0.48. Thus, investors would have nearly doubled their mean-variance efficiency by switching from chasing winners to investing in loser funds.
- The CAPM alpha generated by the median strategy beats that of the winner strategy by a statistically significant 2.76 percentage points per year (-0.85% versus -3.61%) and its Carhart four-factor (market beta, size, value and momentum) alpha beats that of the winner strategy by a statistically significant 1.03 percentage points a year (-2.16% versus -3.19%). The loser strategy managed to do even better, producing a CAPM alpha of just -0.11 and a Carhart four-factor alpha of -0.17, though neither was statistically significant.
Cornell, Hsu and Nanigian found very similar results when examining the performance of the extreme loser portfolios.
They write: “At the 3% threshold, the fired funds outperform the kept funds by over 1 percentage point per year based on benchmark-adjusted return, raw return, CAPM alpha, and Carhart four-factor model alpha. The Sharpe ratios indicate that the fired funds also exhibit greater mean-variance efficiency than their counterparts. The results are largely similar when we use a 1% threshold in place of the 3% threshold. Once again, the fired funds outperform the kept funds across all performance metrics.”
For example, they found the funds that underperformed by more than 1% (fired managers) produced four-factor alphas of -0.69%, which compares favorably to the -1.88% alpha of funds that did not underperform by more than 1% (managers who were retained). For funds that underperformed by more than 3%, the four-factor alpha was -0.48% versus -1.64% for those that did not underperform by more than 3%.
As a test of robustness, Cornell, Hsu and Nanigian found similar results using a two-year evaluation period instead of three years. They also found similar results when they eliminated the $1 billion AUM requirement, and when they looked at only institutional share classes (which have lower costs).
They even found the same results when looking at funds by benchmark performance decile (in general, moving from the funds in the best-performing deciles to the worst, performance became worse on both a raw and risk-adjusted basis).
Such outcomes help to explain the often-reported “performance gap”—the finding that, on average, performance-chasing behavior can cause investors to underperform the very funds in which they invest.