Drawdown Analysis Is Also Valuable For Economic Indicators

Calculating the history of drawdown (DD) for assets is common in the investment community, but the risk metric also provides useful information for analyzing economic data. In particular, monitoring peak-to-trough declines can offer relatively reliable estimates for turning points and estimating the probability that a decline is set to end or that a new downturn has started.

In contrast with DDs in financial markets, economic DDs tend to be smoother and suffer less noise. More importantly, the start of a rebound following a trough is often more persistent vs. comparable results in the stock market.

Some of this is a function of data frequency. Many key economic indicators are published monthly vs. the tick-by-tick numbers available for stocks, bonds and other financial assets. But even accounting for this difference shows that some economic data sets have a habit of tenacious recoveries after reaching a bottom, and vice versa following a peak. That’s a valuable feature for developing real-time estimates of trend changes in the business cycle.

As an example, consider DD for US private payrolls. Most of the declines exhibit a recurring feature: once a drawdown’s depth eases following a decline, the recovery persists. As a result, the first DD data point that posts a lesser shade of red is a reasonably reliable first estimate that the decline has hit bottom and a recovery has started for the indicator.

For private payrolls, the previous trough was April 2020. In that month, private payrolls posted a 16.5% drawdown, followed by a slightly lesser 13.9% drawdown in May. Once the May data was available (in early June), there was a case for estimating that a recovery in payrolls had started.

That’s obvious now, but in the depths of the pandemic such thinking was a radical thought. But studying the history of DD for economic indicators suggests that these turning points are valuable real time estimates of major shifts in economic trends.

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Disclosures: None.

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