What Caused The Q4 Stock Market Crash? Let’s Ask The News Team!

What was the proximate cause of the December insanity across markets?

It’s a question that vexes market participants and answering it has become a veritable obsession for analysts, pundits, reporters and a certain “very stable” U.S. president.

We’ve certainly spent our fair share of time trying to “solve” the mystery in these pages. From where we’re sitting (i.e., on a literal island) it was some combination of Jerome Powell’s “plain English“, Donald Trump’s “plain insanity” and a “plain” dearth of liquidity/market depth which served to exacerbate price swings amid an exodus of retail money from mutual funds and a last minute pension rebalance bid which, you’ll recall, was all that stood between a terrible situation (i.e., the worst December for U.S. equities since the Great Depression) and an outright catastrophe (i.e., some kind of ~30% monthly plunge that ended with Trump sending in the U.S. military to lockdown the NYSE).

(Goldman)

Well, as it turns out, BofAML has devised a way to quantify the contributions of various factors to the Q4 drawdown. Spoiler alert: it’s a “news-based” approach, which means there’s a problem right off the bat – namely that it cannot, by definition, account for the media’s role in acting as an accelerant.

In a piece dated Wednesday that carries the extremely unfortunate title “Who let the bears out?”, the bank begins by noting that “since markets peaked on September 20, there have been 47 days out of 74 total trading days when the S&P 500 moved by at least 0.5% in either direction.” That compares to just 51 such days out of the 251 trading days in 2017.

(Bloomberg) 

Ok, so here’s how the bank’s news-based approach works and please, try to contain your laughter because they are serious about it and until you spend the time to develop your own better model, you can’t really judge, ok?! Ok. To wit:

We have been maintaining a proprietary dataset that allows us to do an event-study analysis of the drivers of the US equity market. We focus on days when the S&P 500 moved by at least 0.5% in either direction

We then used the Bloomberg daily market wrap reports to identify the cause of the move in equities. For each news category, we created a dummy variable that equals 1 if the Bloomberg report cites that news category as the reason for the equity-market move. The dummy variable equals 0 on all other days. If more than one story is reported to have driven the markets on one of the days in the sample, each story is apportioned equal credit

There you go. We’re going by Bloomberg’s daily market wraps and before you chastise that, do ask yourself how many times you’ve relied on the very same daily wraps to get a sense of what’s going on and also note that those pieces are infinitely more reliable than any blog you’re going to read (well, save this one, naturally).

So what does this model tell us about what’s driven equity declines? Well, starting with the trade war, BofAML notes that “trade protectionism has been the most important headwind to US equities since the start of last year, taking 4.4% off the S&P 500.” Amusingly, this model suggests that were it not for trade fears, the S&P actually would have finished in positive territory in 2018.

(BofAML)

As for the Fed, BofAML’s approach naturally suggests that “the negative effect on markets was concentrated around the December meeting.” Of course anybody not using this news-based approach would tell you that the Fed’s deleterious impact actually dates from October 3 (“long way from neutral”), but for the purposes of this study, BofAML attributes ~6.4% of the nearly 10% selloff during the six trading days from December 17 to 24 to the Fed.

The macro data is the biggest drag since the September 20 peak, according to this model, shaving 3.8% off the S&P. BofAML says that through September, upbeat economic data (i.e., “surprises”) juiced U.S. equities by 6%. “Towards the end of the year, however, investors started to worry about the slowdown in the housing market”, they continue, before flagging the conflicting signals from last week’s ISM manufacturing print and the jobs report and proclaiming that “one thing is clear: as the Fed has become more data dependent, so too have the markets.”

The bank goes on to attribute 3.5% of the Q4 decline to oil and 2.9% to “international news”, where that primarily means dour-sounding reports about the Chinese economic deceleration, Brexit headlines and, of course, the Italian budget drama.

Finally, BofAML runs a similar analysis for a variety of other asset classes and “finds similar results for most [with] the same five categories responsible for overall financial tightening.” Here’s a summary:

(BofAML)

All in all, BofAML thinks there are just “too many balls in the air”. “The implication for the outlook is that the data and policy mix needed to support the markets is not trivial”, the bank muses.

Right. And as far as the analysis itself is concerned, we would reiterate that the media itself (and especially social media and the blogosphere) are exacerbating volatility by creating a highly efficient echo chamber, which is then scanned by algos for market-moving information. When combined with illiquid markets, you end up with months like December.