The Cycle Dynamics portfolio bridges a gap in investment management between the All Weather approach and trend following systems. A quick review of the All Weather and trend following methodologies reveals the distinctions.
The All Weather system attempts to create a static portfolio that offsets the volatility between different assets as the economic cycle moves through different combinations of rising or falling inflation and growth. Both inflation and growth can rise or fall at different times, which means that at any one time the economic climate can be categorized as being in one of 4 quadrants.
In theory, by analyzing the implications for different assets as the economic cycle moves through the different quadrants a static portfolio can be constructed to create very low volatility by weighting offsetting assets. This is called a risk parity approach. This is calculated to work throughout the 4 quadrants in almost all circumstances. This then enables investors to hold on to all the assets to achieve the long term return from each asset class.
Trend following systems are easier to define as they seek to find trends wherever they occur and to maximize the returns from the trend, while also minimizing or managing the risks.
Cycle Dynamics uses the philosophy of both of these approaches. The construction of the trend following systems is developed with the whole cycle of the 4 quadrants in mind. In effect trend following techniques are used to navigate dynamically through the 4 quadrants. The great benefit of this approach is that not only does this avoid the difficulty of achieving risk parity at all times, it also maximizes the returns at each stage of the cycle.
Furthermore, cycle dynamics is much more adaptable to changes in perceptions of value, and varying economic and policy environments. The choice of assets is far more neutral to the normal economic, value and policy judgments that dominate so many conventional asset management approaches, and far more connected to current market realities.
If markets and economics are complex systems then a socratic humility can be an advantage. It can allow for judgments to be made where they are appropriate, and otherwise left to a process that may well handle the decisions better in a multivariable complex environment. The socratic approach appropriately asks significant questions. In what conditions does any investment manager have an advantage over a well constructed cycle dynamic system?
Cycle dynamics challenges the investment manager to rethink where in the process his added value is best allocated. A well designed system introduces market intelligence to the process. This may have significant advantages over otherwise binary investment choices that may not allow for the complexity, timing and flow that may be inherent in a cycle dynamic complex process.
At the very least it is worth considering what can be achieved from constructing a set of cycle dynamic systems that can be incorporated into the investment process.
I have constructed a more or less complete portfolio solution by incorporating 4 cycle dynamic systems as described below. Each system considers a different cycle focused on either separate asset classes or a combination of asset classes.
Much more complicated is how these four systems themselves interact. While I have not been able to analyze the entire portfolio effect I have been able to analyze all combinations of 2 of the systems when run together. In each case the combined systems improved in all metrics so there does appear to be a further positive portfolio effect derived from the combinations of systems.
The results below show that this approach to portfolio structure can produce results that significantly outperforms the S&P500 with dramatically lower volatility and risk. The outline for this portfolio is given below.
Cycle Dynamic Portfolio
___________________Return/Yield Sharpe Drawdown Worst Best Year
10% less than 3 year bonds 5%
15% Bond Selector 9.5% 1.1 -9.9% 2.5% 18.3%
20% Equity Sector Selector 17.1% 1.2 -9.0% 4.1% 42.2%
20% individual equities, 1% allocation, 25% trailing stop.
10% (discretionary estimate)
10% PHYS 5% (discretionary estimate)
10% Commodity Selector 10.8% 0.8 -16.2% -1.6% 24.6%
15% Asset Selector 21.4% 1.2 -17.6% 7.5% 34.4%
The average portfolio return/yield is 12% p.a..
Here are the comparable numbers for the S&P 500 index.
S&P 500 9.5% 0.4 -55.2% -36.8% 32.3%
All testing periods start at the beginning of 2008 or before, and are current to the present date. Brokerage not included. Based on closing prices. Past performance is no guarantee of future performance.
Every element of the portfolio has lower volatility than the S&P 500. In addition there are significant risk offsets between the different sectors. I would estimate that the Cycle Dynamic Portfolio has around half the volatility of the S&P 500 on average. Only one of the line items above has even a single losing year and that was a minor loss of -1.6%. The portfolio above has a maximum 55% allocation to equities.
The components of the Cycle Dynamic Portfolio is made up of modules that could easily be weighted differently. So this approach forms an ideal basis for constructing a suitable combination of modules appropriate for each investor with significant flexibility. This module approach may therefore provide a very useful approach for investment planning.
All the selectors revert to Treasury Bills under certain conditions. Also many of the equity sectors are based on real estate and commodities. Therefore there is substantial adaptive allocation in this approach. In order to reflect this minimum and maximum allocations to the three main investment sectors are shown below.
___________________ Minimum Maximum
Cash/Bonds 15% 90%
Equities 20% 55%
Real Assets 10% 75%
Overall this portfolio has very low risk. The allocation to equities is modest and risk management tightly controls downside risk. So the remarkably consistent results above show very attractive returns considering the very low level of risk.
There is also significant flexibility to the design of any investment plan. By shifting the weights of the modules, different ranges for the asset allocation can be produced to suit each individual investor.
There are also multiple adjustments that can be introduced to the systems themselves which can also be adjusted or tailored to deal with different investment requirements.
Overall, cycle dynamics brings a great deal of clarity and flexibility to the investment planning process as well as providing impressive results.