We tested the efficacy of the model back to 1991 using an industry-standard drag on earnings to account for transaction costs and taxes. The testing was done outside of ITR. The results were favorable to the Optimizer Model.
We ran additional analysis using the testing results and determined that we successfully avoided negative returns over any given 5-year period (the S&P 500 experienced negative 5-year returns five times in the test period). The Optimizer model minimized weak return periods, and essentially was on par with the best periods in the specified bands.
| # 5 Year Periods, Negative Annual Return |
0 |
5 |
| # 5 Year Periods, 0% to 5% Annual Return |
2 |
4 |
| # 5 Year Periods, 5% to 10% Annual Return |
8 |
2 |
| # 5 Year Periods, 10% to 20% Annual Return |
10 |
9 |
| # 5 Year Periods, 20%+ Annual Return |
3 |
3 |
Twice the Optimizer Model yielded 5-year annual return results slightly more than 5 percentage points lower than the S&P 500. Overall, the S&P 500 provided a better return in 9 of the 23 years we tested.
We are going to investigate those periods where the buy-hold strategy outperformed our model to determine what the causal factors/relationships were in those instances, specifically looking for some consistency in the factors.
Beyond that, we are going to test an additional idea or two to further optimize the model, but we are approaching the point of diminishing returns.
Best regards,
Brian Beaulieu
CEO
We tested the data using an outside source to verify results. We also put an industry-standard drag on earnings to account for transaction costs and taxes. Since the benchmark is a buy and hold strategy, a similar drag was not placed on the benchmark. With the drag taken into consideration, the Equity Optimizer model outperformed the benchmark CAGR over the 12-year test period by 370 bps.
What’s next:
- We are going to conduct further back testing to encompass an even broader array of market forces to further test the ability of our model to work under varying circumstances. We all know the admonition that prior results are not a guarantee of future performance, but we can be more confident about the model’s advantages with further back testing because of the varying forces at work in the past and conceivably in the future.
- We are also going to tinker with the model to determine if we can improve upon its performance during certain periods where we think the model perhaps could have provided more alpha.
- ITR Economics and Clark Bellin of Bellwether Wealth will be investing money to begin “live” testing of the model and create additional data points.
Best regards,
Brian Beaulieu
CEO
