Of Liquidity, Fragility, HFTs And ETFs: One Bank Takes You On A ‘Flash Crash Course’

Late last month, in what amounted to a follow-up to a previous piece, Goldman’s Charles Himmelberg took a closer look at fragility and liquidity provision in the context of modern market structure.

This is an extremely important discussion for all manner of reasons, not the least of which is that the current system (characterized as it is by the presence of HFTs, systematic strats, programmatic trading and the proliferation of passive investing) has never been truly stress tested. The events that transpired on the afternoon of Monday, February 5 and the flash-crashing madness that unfolded on August 24, 2015, certainly seem to suggest that when it is, it will fail (or at the very least not pass with flying colors).

The two dates mentioned above are but two examples of something that happens on a smaller scale all the time.

There have been probably a dozen other acute episodes since 2008 and God only knows how many fleeting instances of “anomalous” price action. All of those events lend credence to the notion that something isn’t quite right, and that the proximate cause of these anomalies (which, by virtue — or maybe, by Virtu is better — of their increasing frequency aren’t really “anomalies” anymore) is likely to be the presence of machines. Here’s a sample:

(Goldman)

Passive investing presents its own set of risks which aren’t well understood and making matters worse, even suggesting that the epochal active-to-passive shift has the potential to cause problems is taboo in polite company. After all, passive investing is what saves retail investors from themselves by discouraging day trading and the fact that passive vehicles come with rock-bottom fees has ostensibly freed Joe E*Trader from the tyranny of high cost active management.

The problem, however, is that these passive flows combined with what Howard Marks has described as a “perpetual motion machine” dynamic, have created a self-feeding loop, encouraged by the post-crisis monetary policy regime which kept volatility anchored and transformed “BTFD” from a derisive meme about retail investors into a viable (indeed, an almost infallible) trading “strategy”.

If that self-feeding dynamic ever slams into reverse, there are questions as to the durability of the mechanisms that underpin it (e.g., Will the ETF model actually crack, as it did on August 24, 2015? And what about credit ETFs? What happens to HY and EM bond funds when the underlying liquidity mismatch is exposed?) There’s more on this in a recent post I wrote for Dealbreaker about smart beta.

The question, in a nutshell, is exactly that posed by Goldman back in March. Namely, this: Are markets themselves a bigger risk than fundamentals?

You can read all about this in the following posts which are of course just two of dozens penned in the short history of this site:

In the first linked post, Goldman talks about the “adverse selection” problem for HFTs, but their analysis doesn’t stop there. They list all manner of other risks, some more pressing than others.

Recently, JPMorgan’s Marko Kolanovic penned the following assessment of modern liquidity provision which is worth a read, if you haven’t already seen it:

Liquidity: Risks of Market “Uberization”

We have noted in the past that a combination of computerized sellers, and computerized market makers poses a threat to equity price stability. As volatility increases, systematic investors have to sell, and at the same time market depth as provided by electronic market makers quickly disappears. For instance, S&P 500 futures market depth dropped over 90% during the February selloff. What is the reason for such a dramatic drop in liquidity? The most important driver is likely the increase of volatility (e.g. VIX), given that many market making algos (as well as business models) were calibrated during the years of low volatility. As these programs don’t have an obligation to make markets and are optimized for profits, they likely adjust quotes and reduce size in order to maximize their own Sharpe ratio. Other factors likely played a role as well: the increase in short-term rates (e.g. LIBOR), increase of exchange margin requirements, index fund outflows, and risk capital being diverted towards cryptocurrency market making. Full electronification of the market making industry has never been tested in a recession environment. Given that financial markets are a critical part of the economy’s infrastructure, perhaps more attention should be paid to the risks posed by the Uberization of financial markets. The analogy between market making and Uberization is as follows: when there are normal market conditions, the amount of liquidity (cars available) is more than needed and market transaction costs (fare) is low, thus benefiting market participants. However, when there is a volatility shock (heavy traffic, weather) liquidity quickly disappears (i.e. fares can surge to unreasonable levels). In the case of a car ride, one can simply ignore such a surge in price, postpone the trip, or fall back to public transport. However with financial markets, certain participants have to transact (e.g. systematic strategies, option hedging, leverage constraints, algos trading headlines). This results in significant intraday volatility and causes damage to investors’ confidence in the market. Human market makers (the analogy of regulated taxi services or public transport) were to a large extent dismantled over the past decade, so there is hardly any alternative liquidity back-up. These risks previously manifested themselves as ‘flash crashes’ in single stocks and indices. However, equally damaging for investor confidence are what we see now as ‘slow moving crashes’ that can last several hours as was the case recently with some large stocks and market segments (e.g. Caterpillar ~11% intraday drop on April 24th).

Well, as you might have noticed, we’ve seen several examples of liquidity vacuums and anomalous activity over the past two weeks. For instance, bid-asks for Italian bonds blew out on May 29…

… and 2Y yields surged the most on record:

As we wrote at the time, “clearly, no one is providing any liquidity here – the market is no-bid.”

“Dealers are start[ing] to pull quotes,” Bloomberg warned, that same morning.

And just last Thursday, as the bottom fell out for the Brazilian real, Treasury yields flash crashed (USTs “flash rallied”):

Here’s what Bloomberg’s Cameron Crise wrote while live-blogging it last week:

Judging by the way my IB chats lit up, that downdraft in Treasury yields generated a lot of excitement. It certainly looks like there was a big stop-out; 10 minute volume in TY futures exceeded that of both month-end and payrolls, with 185k contracts trading during the spike higher in price. There were similar volume spikes in FV and US as well.

And wouldn’t you know it, something strange happened the very next morning, when 10Y yields dove at just after 4:00 a.m., following a headline about Apple suppliers.

“From post-crisis ‘flash crashes’ to the recent illiquid trading in Italian bonds, markets have become familiar with a pattern: Liquidity seems to evaporate as volatility rises, arguably leading to price moves that seem excessive relative to their fundamental catalyst (if there is even one at all),” Goldman’s Allison Nathan writes, in the bank’s latest “Top Of Mind” note, which is all about liquidity, volatility and fragility.

As a reminder, these are basically expansive takes on whatever the market topic du jour happens to be. They combine interviews with Goldman’s own employees and also with outside sources in an effort to provide a balanced and comprehensive assessment on whatever seems to be the most important question on market participants’ minds (hence “Top of Mind”).

There’s a ton to go through in Goldman’s piece, and as usual, doing these TOM notes justice in a blog post is well nigh impossible.

So what we’ll do here is simply show you one visual from the piece which is a fun history of flash crashes and then excerpt a few passages from Nathan’s interview with the above-mentioned Charles Himmelberg.

A “Flash Crash Course”:

Via Goldman

Allison Nathan: You’ve argued that today’s market structure shows signs of fragility. Why?

Charlie Himmelberg: Over the last several years, we’ve seen flash crashes happen in a number of major, liquid markets. It isn’t hard to find examples of price swings that seem excessive relative to the fundamental news that triggered them, if there was even any fundamental news at all. Just last month, two-year Italian government bonds experienced a much bigger price decline than they had at any point during the 2011-2012 crisis when systemic risks to the Euro area were far more acute. And potential “cracks” in the market were also revealed during the VIX spike on February 5th.

I see two main takeaways from such events. First, technical dislocations are risky because they can fuel false fundamental narratives. On February 5th, traders familiar with the VIX could tell that the spike was a technical disruption and nothing more, yet many observers tried to attribute the move to the prior Friday’s slight upside surprise in average hourly earnings data. That narrative didn’t get much traction with market participants, but in a future dislocation under less benign macro conditions, it could, and might thus fuel even larger price declines.

The second point is that when market liquidity evaporates, selling pressure is amplified. And growing frequency of flash crashes during the post-crisis period provides some reason to worry that liquidity may have become less reliable–or more “fragile”–during market stress events. For over-the-counter (OTC) markets, I think it is widely understood that the quality of market liquidity has declined due to the new costs imposed on traditional broker-dealers by the post-crisis regulatory environment. For exchange-traded markets, by contrast, such claims are more controversial. But I see reasons to worry that the rapid growth of liquidity supply from newer market participants like HFTs has a “feast or famine” quality to it. In normal times, machines are more nimble than human traders, and liquidity is great. In distressed periods, by contrast, evidence suggests that HFTs may withdraw liquidity more aggressively than human traders, and the resulting reduction in liquidity can interact with selling pressures in a way that results in outsized price declines.

So that’s the fragility risk that I’ve been trying to explore. It feels particularly relevant in the current environment, where recession risk is low but valuations are high. The biggest risk to markets might therefore be markets themselves.

Allison Nathan: How does this HFT liquidity withdrawal play out, and what evidence is there for it happening?

Charlie Himmelberg: Academic research on flash crashes has demonstrated two things. For one, in many flash crashes, trade-level data show that HFTs pull back from the market. That hasn’t been the case in every flash crash, so I don’t want to over-generalize. But other research shows that HFTs tend to withdraw liquidity when they’re faced with complex fundamental news. The recent political headlines in Italy are a good example. In circumstances like these, HFTs appear to recognize that their algorithms cannot understand or process the information as well as human traders. This puts HFTs at a disadvantage since it exposes them to adverse selection by those better-informed buyers or sellers. In response, it only makes sense for the HFTs to widen out their bid-ask spreads, perhaps dramatically; in some cases they withdraw from the marketplace altogether. And while evidence shows that liquidity typically returns quickly, the logic of adverse selection obviously suggests the risk that it could take longer under conditions less benign than the current expansion.

When HFTs withdraw, it leaves a greater share of liquidity provision up to human traders, which would be fine if there were a deep bench of human traders with spare risk-taking capacity. But as I alluded to earlier, there isn’t. Over the past ten years, a variety of factors–regulatory constraints, low volatility, low returns, advances in technology–have contributed to the so-called “rise of the machines.” As a result, there is simply a smaller base of human traders who can step in when the HFTs pull back. And in the case of traditional broker-dealers, new regulations have put tighter limits on how much risk capital they can deploy when they do.

Allison Nathan: What makes you confident that human traders can understand complex information any better than sophisticated HFT algorithms?

Charlie Himmelberg: Well, I don’t think HFT algorithms are necessarily all that sophisticated; they’re mostly just fast. And under routine circumstances, the evidence suggests that this substitution of “speed for capital” allows machines to supply liquidity more cheaply than humans. But when the markets experience a big negative event and price discovery breaks down, I would argue that traditional market makers are more sophisticated in their ability to determine where prices will settle. They are able to determine when the markets have overshot that level, take principal risk accordingly, and thus stabilize price discovery. By contrast, HFT algorithms can process price and volume, but not value.

Allison Nathan: What about products like ETFs? Could they be a source of market fragility?

Charlie Himmelberg: I take a relatively benign view of ETFs. Some ETF critics question the idea that you can take an illiquid portfolio of underlying assets, put an ETF wrapper on it, and come up with something more liquid. To some, this seems like black magic. But to me, that’s how financial markets have always enhanced liquidity. The same thing happens routinely with corporate capital structures. Take a steel mill. Its underlying assets, the blast furnaces, are highly illiquid. Yet the financial claims on the cash flows from those furnaces, in the form of debt and equity, trade with plenty of liquidity. Similarly, ETFs make it easier for a wider base of investors to trade the stream of cash flows from harder-to-trade portfolios of assets. Now, that’s somewhat disruptive, because in some markets it creates more price discovery than many investors–particularly buy-and-hold investors–are accustomed to. ETFs may also place more demands on market liquidity since that is part of their appeal to end users. But I think the basic product design is sound. In distressed markets the price of an ETF can deviate materially from the price of its underlying assets, but such pricing differentials are self-stabilizing, and I think the net effect of ETFs on market liquidity is additive. All of that said, it’s important to distinguish between the vast majority of “plain vanilla” ETFs from levered or inverse ETFs. The latter make up only a narrow slice of the market, but they have more worrisome features to the extent they can become “forced sellers” in the face of price declines–as happened for certain VIX products in February.