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Here is what is going on:
- The Optimizer modeling continues. We are running money through the model as previously reported and are pleased with the results.
- There is now an Optimizer 2.0 that has gone through the modeling process and is also running money. Model 2.0 is constructed to provide additional lift during prolonged bull markets via changes we made to the component weighting structure within the model, while still providing all the downside protection inherent to the Optimizer.
- We have also developed the Optimizer-S that was mentioned in an earlier Update. That modeling went very well and provided even more lift during prolonged bull markets while maintaining all the advantages of the downstroke protection. We also reduced the exposure to certain industries within the Optimizer-S as a means of reducing what we discern as risks related to those industries even though they historically provided benefit.
- The Optimizer-S outperforms the Optimizer 2.0. We think the Optimizer-S should be considered as entailing more risk because of the added exposure to upside factors and the removal of the industries that historically offered value. The S gave an annualized rate of return of 17.68 from 12/31/94 to 12/31/2019. The S&P gave an annualized rate of return of 10.22 during that same period. Changing the period from 3/1/2009 to 12/31/2019, the S did 19.00 while the S&P did 17.06. The market bottomed in 3/2009. A fee of 1.5 was charged on the Optimizer in both situations and no fee charged on the S&P 500.
- We think the Optimizer 2.0 and the Optimizer-S are going to prove themselves very worthwhile equity investment vehicles given the rise that we see ahead and the ongoing probability of a 2022-23 general economic recession with a probable outsized downturn in the equities market.
Thank you for your continued interest.
Here is what is going on:
- We have been working on adding a “super cyclicals” component to the ITR Equity Optimizer Model™. The intent is to enable the model to perform better than the current iteration during prolonged bull markets without losing the defensive capabilities inherent to the model.
- The results are encouraging. Our internal analysis indicates that we can add 100+ basis points to our CAGR over the last 10 years and 200+ bps over the last 24 years. The numbers will be appreciable even after “drag” for taxes and transaction costs are taken into consideration.
- Our next step is to decide on which iteration to move forward with and provide it to Bellwether Wealth for independent modeling. Bellwether Wealth runs the modeling through Morningstar.
- The Morningstar tests will provide monthly, annual, 3-year, 5-year, and 10-year, etc. comps to the benchmark. We are looking forward to seeing those ASAP.
- The live testing continues. Results are as we expected, with the funds in the model performing as anticipated. We are putting additional accounts under the model to broaden the performance testing.
The next update will come once we have the Morningstar backtesting results completed.
Thank you for your continued interest.
- Live dollar testing began October 4, 2019. From its inception October 4 through October 29, the Optimizer is +65 bps versus the S&P 500 Total Return Index. The Optimizer Model return is 3.60% while the S&P 500 is 2.95%.
- We have had numerous meeting with different segments of the financial industry: P/E, VC, Wealth Management firms, and retailers. We’ve garnered a lot of great ideas. The feedback on the Optimizer is positive and supportive.
- Our Model currently provides for three “positions” that vary from Aggressive, to Defensive, to Very Defensive. We are starting to define what would constitute “Very Aggressive” and, if it would benefit performance, how it would fit into the model.
- We think a future iteration of the Optimizer will look at being able to incorporate into the model slicing the equity platform into small cap, mid cap, large cap, etc.; there are enough differences in performance that this could prove to be worthwhile.
- Another future version may include loading in certain “base” or “mainstay” equities to more aggressively pursue upside alpha during bull markets
Our next update will be at the December 2019 webinar Alan and I will be doing. In addition to an Optimizer update, the webinar will look at the financial markets/trends, how close we are to our system of leading indicators signaling we are a “go” for the recovery in 2020, a look at how the election might impact some aspects of the forecast and how it won’t impact other aspects at all. The purpose is to get you thinking ahead of the competition so you can make the key decisions to thrive while they are wondering what is going on.
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.
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.
- 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.