A new study offers encouraging results for a strategy of monitoring the business cycle as a tool for enhancing investment returns (or at least limiting losses). “Over the period 1970-2015, investment returns were enhanced by merely knowing concurrently whether the economy was in a state of expansion or contraction, and making the most basic asset allocation decision of whether to be in stocks or bonds,” write a trio of professors in a recent paper (“Does it Pay to Forecast the Business Cycle? A U.S. Update and an International Perspective”).
The results aren’t terribly surprising. As the authors note, probing the potential for using the economy’s ebb and flow as a signal for adjusting equity allocations has been studied previously. A 1991 article in The Journal of Portfolio Managment (“Does it pay stock investors to forecast the business cycle”) by Professor Jeremy Siegel, for instance, found that “stock returns can be significantly enhanced by successfully forecasting business cycle turning points.”
The new paper, written by James A. Conover at the University of North Texas and two co-authors, updates the analysis through 2015 and expands the focus to foreign markets/economies to supplement the US-based results. The main takeaway:
In the United States, an annual excess return of 2.01% was earned by investing in stocks during expansions and in bonds during contractions. In eight foreign markets, the average annual excess return from the same strategy was 1.74%.
The authors also note that “forecasting business cycle troughs is more important than business cycle peaks” and “even investors who invested one month after the cycle turns could still earn excess returns.”
There are caveats, of course, starting with the simple-but-always-relevant warning that backtested strategies tend to degrade in the out-of-sample results. Nonetheless, the new study highlights a fundamental fact: risk premia fluctuate, sometimes dramatically, and a key (arguably dominant) reason is bound up with the business cycle. We must manage expectations in terms of what this insight can provide, but neither can we afford to ignore this fundamental fact.
A buy-and-hold investor with the discipline to sit tight through economic recessions will probably earn comparable if not superior results vs. a dynamic strategy. But such investors are a small minority, even among institutions. The reality is that economic contractions will motivate a high degree of trading, often at the worst possible time. The lesson is that developing a risk-management framework for money management to factor in business cycle risk – before a recession strikes – is critical, if only to limit the damage that’s likely to unfold for strategies that are naively built on the notion that any rough spots won’t affect the master plan.
Momentum-based risk strategies have become a popular solution in recent years, and rightly so. A huge volume of academic and empirical research tells us that an intelligent use of moving averages and other performance metrics can be valuable tools for managing risk and minimizing drawdowns that routinely weigh on markets and portfolio strategies.
But nothing’s perfect. The limits of relying solely on price-momentum analytics was on full display during the 12 months through Aug. 2016. During that year, the US stock market was unusually volatile, dispensing a number of momentum-based warnings that implied that an extended bear market and recession were looming. In fact, it turned out to be a short-lived market correction sans an economic downturn.
In sum, it was useful during that rocky 12-month period to maintain perspective by monitoring US economic conditions – through an objective, econometric lens across a diversified set of indicators — a focus that would have consistently told you that the economy never slipped over to the dark side.
For example, in the April 2016 review of macro conditions I noted that “the evidence is still weak for arguing that a new downturn started.” A number of analysts were arguing otherwise, but the numbers — in aggregate — didn’t agree. In fact, the vintage history of the Economic Trend and Momentum indices never reached the tipping points that mark the start of new downturns. The macro profile, in other words, was a sober antidote to Mr. Market’s volatility.
To be sure, a robust methodology for estimating recession risk can be quite useful. As I discussed here, the real-time signals of the Chicago Fed National Activity Index (3-month average) dispensed valuable warnings in the early innings of the last two NBER-defined downturns for limiting US equity market losses. Even better, history suggests that we can build an econometric-based model to anticipate the Chicago Fed index by a few weeks.
The point is that using market-based analytics in concert with a robust profile of the macro trend is considerably more reliable than using one or the other in isolation. This critical insight is too often lost on money managers who subscribe to the notion that economic analysis offers little relevance for portfolio design and management.
In fact, “knowledge of the macroeconomy still represents an important input into asset allocation decisions,” Professor Conover and his co-authors advise.
The main caveat is that trying to analyze the macro trend through conventional methods – cherry-picking indicators and relying on media reports – is destined for failure. Ditto for trying to predict economic activity. A more reliable method is analyzing the macro profile based on published data via a broad set of indicators and business-cycle benchmarks. The future is always uncertain, but the recent past is relatively clear. As history reminds, that small edge can be a powerful tool for managing portfolio risk.