Introduction
One of the fundamental strategies in portfolio construction is diversification, a crucial risk management technique. When implemented effectively, diversification can enhance a portfolio’s overall risk profile, often yielding lower risk than that of its individual components. Our application of the Correction Protection Model (CPM) and Sector ETF Asset Flows (SEAF) Model illustrates this concept, enabling us to mitigate some risks through strategic combinations.
Investment Implications
Table 1 below showcases the performance of CPM and SEAF individually over the past five years, with a blended version of the two models in the center column. This table highlights two important metrics: maximum drawdown and the Sharpe Ratio. By integrating CPM into the SEAF models, we achieve a diversification effect, which allows investors to enjoy potential gains while minimizing risks. Although the blended model exhibits a slight decrease in annualized returns—about a 4.5% drop compared to SEAF—it significantly lowers the maximum drawdown from approximately 29% to 18%. This diversification effectively reduces drawdowns to levels even below those of CPM alone.
Another critical metric to consider is the Sharpe ratio, which measures return per unit of risk. The blending of CPM and SEAF maintains a Sharpe ratio comparable to that of SEAF alone, but with roughly 60% less drawdown. While historical returns do not guarantee future performance, analyzing the underlying metrics of our models helps us understand their behavior in various market conditions and their responses to different economic stimuli.
(Editor’s Note: All back-tested hypothetical performance, as indicated in the tables below, does not include the deduction of any fees, commissions, or expenses.)
Table 1
Click tables above and below to enlarge
Using the 50/50 CPM and SEAF blend (referenced in Table 2 below, middle) as a baseline, we can further optimize our portfolio to adjust risk metrics more closely to an investor’s profile and their investment objectives. To illustrate the range, on one end, we have a 90/10 CPM to SEAF portfolio, and on the other, a 10/90 CPM to SEAF portfolio. The 90/10 portfolio demonstrates a lower limit on how maximum drawdown is affected by blending the two models, showing a notable decrease. Conversely, the maximum drawdown in the 10/90 portfolio increases by approximately 9.0% percent compared to the 50/50 model. This situation exemplifies an efficient frontier, aiming to find an optimal balance between maximizing returns and minimizing risk based on one’s risk tolerance. At one extreme, prioritizing SEAF could maximize profits, but it also increases risk and potential drawdowns.
Table 2
Generally, higher returns correlate with higher risks, as there are no risk-free profits in markets (excluding arbitrage opportunities). At the other extreme, a higher allocation to CPM reduces return potential without a corresponding decrease in drawdown, although it does result in a lower standard deviation due to CPM’s nature and less frequent trading. This analysis underscores the importance of aligning investment strategies with personal risk preferences and market volatility tolerance.
We are currently using this model blending strategy to provide our money management clients with more personalized solutions to their investment objectives. Feel free to contact us to discuss implementing similar strategies into your own portfolio.
Disclosure/Disclaimer: The information on this website is provided solely for informational purposes and is not intended to be an offer to sell securities or a solicitation of an offer to buy securities. The strategies employed in managing this and other model portfolios may involve algorithmic techniques such as trend analysis, relative strength, moving averages, various momentum, and related strategies. There is no assurance that these strategies and techniques will yield positive outcomes or prevent losses. Past performance as indicated from historical back-testing is hypothetical in nature and does not involve actual client portfolios, does not consider cash flows or market events, and is not predictive of future performance. The model is managed by contemporaneously recording hypothetical trades. Such trades are not live trades and are not influenced by emotional or subjective reactions to extraneous market, economic, political and related factors. The performance for such model(s) is derived from utilizing a variety of technical trading strategies and techniques. Technical trading models are mathematically driven based upon historical data and trends of domestic and foreign market trading activity, including various industry and sector trading statistics within such markets. Technical trading models utilize mathematical algorithms to attempt to identify when markets are likely to increase or decrease and identify appropriate entry and exit points. The primary risk of technical trading models is that historical trends and past performance cannot predict future trends and there is no assurance that the mathematical algorithms employed are designed properly, new data is accurately incorporated, or the software can accurately predict future market, industry, and sector performance. Asbury Research LLC does not and cannot provide any assurance that an investment in the model portfolios will yield profitable outcomes. The risk of loss trading in financial assets can be substantial, and different types of investment vehicles, including ETFs, involve varying degrees of risk. Therefore, you should carefully consider whether such trading is suitable for you in light of your financial condition. An investor’s personal goals, risk tolerance, income needs, portfolio size, asset allocation and securities preferences, income tax, and estate planning strategy should be reviewed and taken into consideration before committing to a specific investment program. Please consult with your financial advisor to discuss the appropriateness of any strategy prior to investing. All investments involve risk. Principal is subject to loss, and actual returns may be negative. Returns are not guaranteed in any way and may vary widely from year to year.