Goldman Traced The History Of S&P Divergences – Here’s What They Found…


Well, the “convergence/divergence” market debate has officially gone mainstream.

On Monday, the Wall Street Journal ran a piece called “U.S. Stocks Widen Lead Over Rest of the World“, which essentially rehashes the whole “divergence” story for anyone who is inexplicably inclined to waiting around on WSJ to pick up on last month’s market narrative.

The last couple of weeks have seemingly played into the convergence theme, with some folks suggesting that a commodities rally, a pullback in the dollar and the resurgence of the global reflation story could help ex-U.S. assets catch up to their U.S. counterparts.

The caveats are myriad. Arguably, nothing has really changed for EM, other than policymakers demonstrating their willingness to hike rates in step with the Fed. The vulnerabilities (e.g., external funding needs, questions about central bank independence in certain locales, the threat of U.S. sanctions and the possibility that trade frictions dent global growth) remain.

That suggests that if the convergence trade is viable, it’s more a tactical call than a fundamental story, although I suppose one could argue that depending on the market, valuations are now compelling compared to the U.S.

In any event, Goldman is out with a sweeping new piece that documents the history of U.S.-EM divergences and it’s worth highlighting a couple of excerpts and visuals here.

First, the bank notes that divergences between the S&P and other assets are either anomalous or reasonably frequent, depending on how far back in history you want to go.

“The 2003-2010 period (both on the way up and way down in risk prices) was very coordinated in that the S&P 500 rarely moved away from EM and EAFE (non-US DM), commodity prices, and EM credit/FX (measured by the EMBI/GBI-EM)”, the bank writes, before noting that “going further back, to the 1980s and 1990s, there are many more episodes of divergence between the S&P 500 and other assets.” That speaks to rising cross-asset correlations, by the way. Here’s a visual:

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