Sharp Declin in S&P 500 on Monday
This much is clear: the sharp decline in the S&P 500 yesterday (April 2) confirms that the downside bias in the first three months of the year has spilled over into the second quarter.
It’s also obvious that the latest market stumble has inspired a new round of warnings from analysts.
CNBC, for example, reports that “Monday’s broad-based sell-off pushed stocks below important technical levels, signaling more pain ahead for the market.”
Some analysts say that the S&P 500’s (NYSEARCA:SPY) close below its 200-day moving average yesterday for the first time in nearly two years marks a grim sign for a momentum-based outlook of equity prices generally. Perhaps, but market history shows that not every close below the 200-day average marks a sustained fall in subsequent weeks and months. The previous dip below that trend line, in June 2016, was brief and turned out to be a great buying opportunity, for instance. That alone doesn’t mean that a repeat performance is fate this time, but it’s a reminder that a slide below the 200-day average by itself can be noise.
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A more troubling sign from a momentum perspective would be if we see the S&P’s 50-day average fall below the 200-day average. For the moment, however, that dark shift isn’t on the immediate horizon.
Meantime, consider how the S&P’s current drawdown stacks up. After Monday’s selling, the market has fallen 10.1% from its previous peak. That’s a dramatic slide in the context of the past two years, but it’s middling based on the S&P’s history since 1960.
Tactical traders with a short-term horizons may find reason to be anxious these days, but investors with a relatively longer outlook might wonder if a genuine regime shift has arrived for equities. One way to answer that question is with a quantitative process that looks at market history through the lens of a Hidden Markov model (HMM). For some background, see these posts here and here. The short explanation for HMM is that this econometric filter analyzes market history for statistical guidance on estimating if a regime shift has taken place. In other words, are we in a bear market?
No, according to the latest HMM reading. For clarity, note that the HMM parameters I’m using are designed to minimize noise, which potentially comes at the expense of timely signals. As such, the HMM design focuses on monthly averages of the S&P based on 12-month changes. The latest data point is Monday’s close, which for the moment represents the average prices for April. Only if the stock market falls significantly lower would this version of the HMM model signal that a bear market has started.
Keep in mind, too, that the broad macro trend remains encouraging. The preliminary economic profile for the US in February continued to reflect healthy momentum and this week’s issue of the US Business Cycle Risk Report confirmed that the numbers overall continued to skew positive, based on data published through the end of March.
That doesn’t mean that stocks can’t fall further. But until or if the economic trend flashes a warning sign, there’s room for debate about whether the great bull market of recent vintage is history. Stocks can certainly suffer when the economy’s expanding, but such a slide usually requires some event that’s unrelated to the economy proper. The leading suspect on that front at the moment: the rising threat of a trade war. If you’re looking for a reason to worry, this is at the top of the list.
At least one investment strategist, however, advises that this risk is still low. “I think we’re going to see a lot of extreme targeting of tariffs” in the next few years, predicts Scott Wren, a senior global equity strategist at Wells Fargo Investment Institute. “The volume of trade between [the US and China] is obviously huge and what the tariffs are actually on is pretty small, so I don’t think we’re going to see a big escalation.”
But take that with a grain of salt. Deciding if a trade war will sink the economy is all about assessing political risk at this stage. The crucial question: Will cooler heads prevail? For insight, econometrics has little to say. Monitoring a certain Twitter feed, on the other hand, may offer a hint of things to come.