Goldman: Here’s How Falling Liquidity Drives Up Volatility, By The Numbers

On Friday, we drew your attention to a CNBC interview with Jim Chanos that found Jim fretting over market “fragility”.

Specifically, Chanos expressed concern over how susceptible equities appear to be to sharp drawdowns when yields rise.

In their recap of the interview, CNBC attempted to navigate the choppy waters around explaining the February and October equity routs and considering the source, they did a decent job. Essentially, they put the blame on rapidly rising 10-year yields prior to both selloffs. Here’s what we said on Friday:

It’s true that the February and October equity routs played out following bond selloffs and that clearly suggested that this is a market that cannot stomach rapidly rising yields. Indeed, a flip in the equity-rates correlation in and around those selloffs didn’t bode well for balanced portfolios and risk parity.

That said, the acute moves that transpired on February 5 and October 10 were the direct result of modern market structure gone awry. In both cases (and give me some rope here — enough to hang myself probably) rapidly rising yields flipped the stock-bond correlation and ultimately, systematic selling collided with option hedging effects and evaporating electronic liquidity (i.e., an acute lack of market depth) to catalyze harrowing selloffs.

We dug up some charts from Goldman’s Rocky Fishman as a way of reminding you about deteriorating market depth and then proceeded to quickly recap a recent Goldman note that looked at tail event risk in credit.

Read more

As Chanos Warns On ‘Fragility’, Goldman Tells You Where The Tail Risks Are

Fast forward to Tuesday and there have been two egregious selloffs since we published that post. One on Friday and one on Monday. In other words, stocks have been falling ever since that post was published and we gently suggested during Monday’s rout that poor liquidity probably didn’t do much to help the situation when Jeff Gundlach decided to drop a series of tape bombs about “bear markets” around lunchtime.

Well, on Tuesday, Goldman is out with a new note on liquidity and it is timely. The overarching point is that liquidity (or a lack thereof) now has a ton of explanatory value when it comes to modeling volatility.

The bank begins by noting that their economic models aren’t doing the best job when it comes to predicting vol. Specifically, the bank says that because its economists see growth and employment sticking at above average levels next year, it’s not surprising that the bank’s baseline estimates for vol. come in below average levels of volatility dating back to 2000.

The problem, Goldman writes, is that “the model implicitly assumes that all information needed to forecast volatility is incorporated in these economic variables and assumes that all other drivers of volatility vary with those indicators through time.” Clearly, that is not a safe assumption and the bank goes on to explain why.

“Simple proxies of liquidity have been valuable leading indicators of volatility [and] we find that adding liquidity factors to the model boost the R-sqrd in 2018 from 5% to 45% in 2018”, the bank writes, before coming to the only conclusion that’s possible there which is that “liquidity factors such as Top-of-book depth, single stock liquidity and market volumes are increasingly important for predicting volatility.”

Liquidity

(Goldman)

Goldman goes on to quantify how poor liquidity amplifies volatility above and beyond what economic models would dictate.

“In contrast to the 13.4 volatility implied by our economic model of volatility, the latest liquidity conditions suggest volatility of 19.1 over the next month”, the bank says, adding that “high recent volatility, low volumes and market depth far below history all contribute to an above average volatility expectation.”

Volatility2

(Goldman)

In case it isn’t clear enough, this is almost all down to deteriorating top-of-book depth and, to a lesser degree, to falling single stock liquidity.

“SPX Futures top-of-book depth is down 70% year-over-year while single stock liquidity is down 42% year-over-year”, Goldman says, before noting that “the high explanatory power of the combined regressions show that market depth and overall liquidity measures embed information that has been recently valuable for predicting volatility even after adjusting for realized volatility and volumes.”

Liquidity3

(Goldman)

So, there you go: more evidence (in this case mathematical proof or some semblance thereof) that lack of market depth/low liquidity are contributing to higher volatility.

Notably, Goldman doesn’t attribute the dearth of liquidity in the current environment to passive investing or algos, but rather to a “general risk aversion among professional investors”. We’ll get to that later.

For now, just note that the bank’s Rocky Fishman (mentioned above) and JPMorgan’s Marko Kolanovic have of course been warning about this all year long and one wonders how many more lunchtime swoons and anomalous futures crashes we’re going to have to see before the wider investing community gets the message that something isn’t right here.


 

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One thought on “Goldman: Here’s How Falling Liquidity Drives Up Volatility, By The Numbers

  1. This is common also with Dax. Implied daily range from option prices is almost always underestimating realized range. I model by my own such a range, and saw that realized volatility is a better estimator.

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