Tactical asset allocators and global macro traders routinely monitor macroeconomic indicators to assess the current and prospective state of economic growth. The rationale behind this practice is that, by gauging the economic landscape, they can also make informed predictions about the financial markets. Consequently, investors seek to position themselves more defensively or aggressively based on the prevailing economic conditions.
Systematic investors also frequently employ macroeconomic indicators to generate signals for tactical market positioning. There exists a multitude of approaches for crafting trading signals grounded in economic indicators. Some investors rely on composite recession signals, which we have previously discussed here. Additionally, certain investors adopt an economic trend methodology, capitalizing on the persistent influence of new information on asset prices by aligning their positions with trends in macroeconomic fundamentals, as highlighted in an intriguing paper by AQR available here.
In this article, we leverage the concept of an economic trend to formulate a systematic trading model that positions itself between the S&P 500 index and a risk-off asset such as T-bills or Treasuries. To this end, we utilize five leading macroeconomic indicators. It's important to note that there are numerous macroeconomic series that could potentially serve as the basis for constructing trading signals, making the selection of macroeconomic indicators somewhat arbitrary.
In this post, we focus on a select few indicators, primarily chosen due to their extended historical data availability dating back to 1960, their frequent monitoring by investors, and, in most cases (with one exception), their composite nature. A composite indicator is fashioned by aggregating individual indicators into a unified index, guided by an underlying model that captures the multidimensional concept it seeks to measure. The constituents of a composite indicator are often referred to as components or component indicators.
To construct our models, we used the following data sources:
Our Systematic Composite Leading Indicator Model is constructed based on five distinct sub-models. Each of these sub-models employs a specific macroeconomic signal derived from the aforementioned data. The following macro trading signals are computed:
The rules for the five sub-models are crafted based on the aforementioned macro-signals. For illustrative purposes, we occasionally incorporate a trend/momentum overlay onto an economic signal. It's crucial to recognize that negative economic signals may suggest a weaker economic environment, but this doesn't necessarily translate to a negative market (price) environment. The S&P 500 index, for instance, could still perform well despite a strongly negative economic signal. To address this, we sometimes employ price trend filters, meaning that a model only shifts to a risk-off position when both the economic signal AND the trend/momentum signal are negative.
Another critical aspect is the selection of the risk-off asset. These assets are expected to perform reasonably well during challenging market conditions. Commonly used risk-off assets include Treasuries, T-bills, gold, the US dollar, managed futures, and high-quality investment-grade corporate bonds. This choice can have a significant impact, as is evident, for example, in the current market environment. For instance, if an economic signal turns negative, and an investor switches to Treasuries while long-term rates continue to rise, the chosen risk-off asset may suffer. In such cases, T-bills or gold might prove to be more prudent alternatives. In this context, we primarily focus on T-bills and Treasuries as they are the most prevalent risk-off assets. The decision between the two can be determined through momentum analysis, where the investor selects the risk-off asset with the most favorable current momentum.
For the sake of true comparative analysis, it may initially appear more appealing to maintain consistency across all models by using a standardized trend overlay. However, we also aim to emphasize the advantages of strategy diversification between sub-models. Since we cannot predict if a trend-overlay will perform better in the future, it may be advisable to apply a trend overlay to only a select few models. Strategy diversification has the potential to yield more favorable long-term results. The same can be said about signal diversification. For example, there are dozens of ways to measure trend and/or momentum. Since, it is hard to predict which trend parameter will work best, it could be advisable to use different measures of trend between sub-models. Next, we illustrate a couple of variations so that the reader can better comprehend the subtleties involved in designing systematic models.
We offer an overview of the outcomes derived from the five sub-models. For clarity and illustration, we occasionally draw comparisons with the S&P 500 index and a more stringent 60/40 portfolio. Additionally, the ultimate Composite Leading Indicator Model is assessed against a 60/40 portfolio for reference.
Approximately 70% of the countries within our sample exhibit positive economic momentum, as indicated by the red line chart below. Given that the global economic momentum signal surpasses the 50% threshold, the strategy is presently allocated to the S&P 500 index.
The strategy has delivered a commendable performance relative to the S&P 500, showcasing superior returns and reduced risk. Notably, drawdowns have been considerably more contained in comparison to the S&P 500 index. Moreover, the strategy exhibited resilience during the turbulent past two years. While the strategy outperformed across the entire dataset, it's important to acknowledge that there were periods of underperformance extending beyond a decade. Nevertheless, even during these phases, drawdowns and volatility remained comparatively restrained.
The current two-month rate of change for the US OECD indicator is in positive territory. Consequently, the strategy is presently allocated to the S&P 500 index.
The strategy has surpassed the S&P 500 benchmark in both risk-adjusted returns and overall returns. It effectively sidestepped substantial drawdowns during critical periods, such as the recessions in the 1970s and the 2000s. Moreover, it exhibited resilience over the past two years and managed to steer clear of the market turmoil experienced in 2022.
The current six-month change in the US leading index, as depicted in the red line chart below, registers below 0%, indicating a negative economic momentum. Nevertheless, there are signs of an economic momentum recovery, with the one-month change now in positive territory. Consequently, the strategy is currently allocated to the S&P 500 index.
The sub-strategy consistently outperforms our S&P 500 benchmark, both in terms of returns and risk-adjusted performance. While it experienced comparatively higher drawdowns in comparison to the preceding two models, this was offset by achieving superior returns. It's noteworthy that the strategy hasn't outpaced the S&P 500 benchmark in terms of pure returns since 2008, but it has excelled in preserving capital by avoiding the significant crash of that year, resulting in a more favorable risk-reward profile.
However, the strategy did encounter some challenges, albeit to a lesser extent than the S&P 500, during the bear market of 2000-2003, which was primarily a consequence of the technology bubble's burst. Economic indicators often face difficulty in promptly detecting such events, as the technology crash commenced before the actual economic downturn.
Approximately 80% of the yield curve is currently exhibiting an inverted trading pattern, surpassing the 20% threshold, indicating a risk-off environment. In such conditions, the model has the option to allocate funds to either Treasuries or T-Bills, guided by momentum. Given that the momentum score favors T-Bills, the strategy is presently invested in T-Bills.
For illustrative purposes, we are now comparing the model with a more stringent benchmark, the 60/40 allocation (60% equity, 40% treasuries). This benchmark provides a heightened emphasis on risk-adjusted performance. While the sub-model outperforms both in terms of returns and risk-adjusted returns, there are several noteworthy considerations:
The primary concern here revolves around the duration of the signal. Inverted yield curves often serve as a precursor to a looming recession, but they occasionally revert to positive territory just as the recession becomes apparent to all, leading the Federal Reserve to initiate rate cuts. Consequently, the strategy at times switches back to the S&P 500 during the initial stages of a recession, as observed in 2008. This period coincides with the market's most challenging phase. In a forthcoming blog post, we may consider an adjustment to the model by introducing a lag in the signal to account for this economic phenomenon. To maintain the integrity of our models and avoid the introduction of hindsight, we are currently presenting the results in accordance with the logical rules outlined previously.
An invaluable lesson investors can draw from this model, is to exercise continued vigilance during the initial six months following the restoration to a positive interest rate curve.
The present 3-month rolling average of the United States unemployment rate stands at 3.63%, in comparison to the 12-month low of 3.4%. Given that the spread between the two figures falls below 0.5%, the Sahm-rule indicator does not signal a recession, and the strategy is presently maintaining full investment exposure in the S&P 500 index.
Once more, we subject this model to a more rigorous evaluation by comparing it with the 60/40 benchmark. While the sub-strategy exhibited superior performance over the entire data set, several noteworthy considerations emerge:
The composite model allocates 20% of the capital to each of its constituent models, with monthly rebalancing. It is compared against a stringent 60/40 portfolio. The current portfolio allocation, based on the composite model's signals, is 80% invested in the S&P 500 index and 20% in T-bills, guided by the following sub-models:
In our assessment of performance, the following observations are made:
Overall, we are content with the outcomes of this initial model driven by economic reasoning. Patient investors may derive benefits from monitoring critical leading economic indicators and aligning their portfolios accordingly. Nonetheless, it is essential to maintain vigilance and a measure of humility when interpreting these results for the future.
It's important to note that this model primarily relies on macro factors as decision signals. We believe a comprehensive systematic portfolio should encompass strategies based on various factors and signals. In this context, this composite model could function as a sub-strategy within a well-diversified portfolio.
In hindsight, this model holds potential for improvement, but we have presented these results based on available data and our original methodology: