It took longer than usual, but the priced-for-perfection bull run has taken a body blow in recent weeks. That’s good news for investors with relatively long time horizons since lower prices equate with higher expected returns. Meantime, with the benefit of hindsight, let’s consider how a pair of econometric tools have fared for monitoring bubble risk and bull/bear market regimes. The question before the house: Have these metrics provided any value for managing risk in an effort to cut through the noise and anticipate trouble based solely on the hard data? As a preview, I’ll argue “yes,” but with caveats.

Several years ago I reviewed the potential for using a rolling 36-month ADF test to quantify the state of bubble risk for the US stock market (here’s the 2014 article). Soon after I analyzed an econometric measure for objectively estimating if equities were in a bear or bull regime via a statistical framework known as a Hidden Markov model (HMM). Although the historical results on both fronts looked encouraging for anticipating critical turning points in the market, the out-of-sample data would ultimately decide if these tools were useful in the real world.

In the years since I published those two pieces, I’ve periodically looked at how the models have stood the test of time. Last November, for example, I noted that the elevated readings for bubble risk appeared to suffer false warnings. Despite the warning, the S&P was still rising, and with an unusually low level of volatility.

Several months later, however, it’s reasonable to wonder if the recent round of high bubble risk readings were accurate after all? The warnings were early, but one could argue that the probability was high that a sharp correction was lurking. The only question: What would be the catalyst and when? Recent events appear to have solved the mystery.

The future’s still unclear, of course, but the market’s slide in recent weeks suggests that the ADF metric offered useful perspective for estimating bubble risk in real time. The caveat with bubbles, however, is that the market can remain irrational for longer than you can stay solvent. As a timing mechanism, even a perfect bubble-risk model is going to stumble. Rather, the way to think of about dramatically elevated market conditions is to take reasonable precautions by methodically dialing down portfolio risk over the duration of what can be an extended bubble period.

Meantime, here’s how the bubble estimate stacks up at the moment. The main takeaway: this threat has deflated dramatically of late in the wake of the S&P’s latest tumble.

Bubble risk is no longer a clear and present danger, but has the market slipped into a bear market regime? In a word, no, at least not yet, based on an HMM reading of current market conditions through yesterday’s close (Mar. 1) for the S&P 500.

The days ahead could tell us otherwise. No one knows if the market will stabilize, rally, or continue to drop like a stone. Whatever unfolds, I expect that the HMM data will provide a relatively clear and objective signal on whether a new edition of regime shift has arrived.

Overall, history offers support for including the ADF and HMM frameworks in your risk-management toolkit. No, they’re not perfect, which means that looking at market risk through several prisms, using a variety of techniques, is still necessary. But as big-picture tools for profiling the market, these two models have performed well enough in the out-of-sample tests to keep them in our analytical arsenal.