We designed our public dual momentum model, GEM, to be simple and easy to use by do-it-yourself investors. GEM exists to help protect smaller investors from horrendous drawdowns while allowing them to earn better than market returns over the long run.
But dual momentum works best when it incorporates multiple trend determinants. There is a synergistic effect from doing so. Most investors do not give enough importance to price trend. Greyserman & Kaminsky show that simple trend following has outperformed buy-and-hold and reduced downside excursions back to the beginnings of every market. No other investment factor can say that.
Using all available investment tools, we created proprietary models to achieve high and consistent returns. Our models are the culmination of a lifetime of investment research and experience. Three of our four proprietary models use a channel breakout approach that we validated on 100 years of data in this research study, giving us high confidence in this approach. Richard Dennis taught something similar to this to his “turtle traders.” Jack Dreyfus became a billionaire using channel breakouts of stocks, making new highs. Most of our models also incorporate mean reversion as a complement to trend following.
All our models use daily data and are highly adaptive to market conditions. They are based on rigorous, academic-quality research with extensive out-of-sample validation on at least 100 years of data. This contrasts with many other trading models that overfit limited amounts of data.
We spend considerable time on due diligence to find the best ETFs for our models. Most investment approaches do not spend enough time on portfolio construction. Thoughtful portfolio structuring is an essential part of our optimal investing process.
Our models work in many different markets. We chose which ones to use so that their combinations create balanced portfolios responsive to different market conditions. Multiple models with low to moderate correlation are the best way to reduce model estimation error and uncertainty. Optimal combinations of models can enhance expected returns while reducing downside exposure.
We license our proprietary model signals to substantial private and institutional investors and selected investment advisors who understand and appreciate what we do.
Most trading models exit to a safe harbor asset when not in their risk-on positions. Our models are unique in switching to other assets or models with positive trends before they seek a safe harbor. This model layering captures additional profit and helps reduce whipsaw losses. Here are our current proprietary models.
BEAST holds intermediate investment-grade U.S. or non-U.S. bond ETFs when their trends are positive. Otherwise, BEAST holds Treasury bill equivalent ETFs. BEAST also has occasional short-term trades in emerging stock ETFs to exploit mean reversion and the turn-of-the-month effect.
GLTR applies trend following to gold ETFs. Gold is often mean-reverting and challenging to trade, but our trend strategy handles it well. GLTR holds the BEAST bond positions when not in gold. Even without trend following, gold has outperformed the S&P 500 over the past 25 years.
BADASS applies our trend model to the BLOK ETF, representing blockchain technology, and to a spot Bitcoin ETF. This combination gives better risk-adjusted results than either alone. When not in these positions, BADASS holds the GLTR or SMURF positions. BADASS is our most profitable model.
SMURF is a stock and bond model that combines mean reversion with trend and seasonality. It buys large-cap growth stock ETFs when their trends are positive. SMURF exits when trends are no longer positive or on abnormal strength. When not in growth stock ETFs, SMURF holds the BEAST bond positions. Here are the results of our SMURF, BEAST, and GLTR models since 2008.
SMURF combines mean reversion with trend and has the highest reward-to-risk ratio of all our models. It spends 69% of its time in large-cap growth ETFs and 31% of its time in BEAST bonds. BEAST has had a higher return with much less volatility and drawdown than the S&P 500. 70/30 is 70% SMURF and 30% BEAST for even more conservative investors.
S&P500 | SMURF | BEAST | GLTR | 70/30 | |
CAGR | 10.2 | 26.3 | 11.1 | 16.4 | 23.4 |
STD DEV | 17.9 | 17.6 | 10.1 | 13.3 | 14.5 |
SHARPE | 0.63 | 1.41 | 1.10 | 1.21 | 1.43 |
UPI | 1.08 | 10.91 | 5.60 | 4.08 | 12.58 |
MAX DD | -49.0 | -10.5 | -7.0 | -12.3 | -8.3 |
AVG DD | -6.0 | -1.3 | -1.2 | -2.9 | -0.9 |
W% MOS | 68 | 73 | 58 | 59 | 75 |
Results do not guarantee future success nor represent returns that any investor attained. You cannot invest directly in our models. CAGR is the compound annual growth rate. Drawdowns are on a month-end basis. UPI is the Ulcer Performance Index, which divides return by the Ulcer Index. The Ulcer Index measures the depth and duration of drawdowns from earlier highs.
Here are the results of some high reward-to-risk portfolios that include digital assets.
Here are the BADASS results and some attractive SMURF, BADASS, and GLTR allocations in that order. Because of our models’ risk controls, we can use digital assets more aggressively than buy-and-hold investors. We also reduce portfolio risk by combining models with modest correlations. Combining models with low and high volatilities and returns with modest correlations creates the desirable “barbell effect.”
BADASS | SMURF | GLTR | BEAST | S&P500 | 45/30/25 | 40/35/25 | 45/35/20 | |
CAGR | 65.5 | 29.6 | 18.6 | 10.5 | 11.7 | 37.1 | 38.7 | 39.3 |
STD DEV | 31.4 | 13.9 | 11.8 | 8.3 | 18.0 | 13.9 | 14.8 | 15.0 |
SHARPE | 1.72 | 1.96 | 1.51 | 1.24 | 0.71 | 2.37 | 2.31 | 2.31 |
UPI | 15.81 | 14.51 | 6.29 | 5.22 | 1.73 | 26.94 | 26.59 | 26.77 |
MAX DD | -12.9 | -7.2 | -11.0 | -6.2 | -23.8 | -5.7 | -6.0 | -6.2 |
AVG DD | -2.5 | -1.0 | -1.8 | -1.3 | -4.8 | -0.6 | -0.6 | -0.6 |
W%MOS | 67 | 75 | 66 | 56 | 62 | 78 | 77 | 77 |
Results do not guarantee future success and do not represent returns that any investor attained. You cannot invest directly in our models. CAGR is the compound annual growth rate. Drawdowns are on a month-end basis. UPI is the Ulcer Performance Index which divides return by the Ulcer Index. The Ulcer Index measures the depth and duration of drawdowns from earlier highs. Please see the Disclaimer page for additional information.
