Sand and fat fingers May 8, 2010 at 10:52 am
I attended a meeting last week at which a doctrinaire free markets economist was praising the benefits of a market in markets. The theory was that lots of different markets in the same asset would somehow give better liquidity, cheaper trading and hence better price transparency. What tosh.
No, what we see instead is that a diversity of markets produces poor liquidity, gappy markets, and just occasionally, near disaster. That seems to have happened on the 6th of May, when a market fall erased a trillion dollars in value in what Bloomberg dubs a ‘flash crash’. The WSJ account is here. It seems that a ‘fat finger’ trade, i.e. a mistaken transaction where perhaps a trader executed billions rather than the intended millions set off the wave. What happened then, it seems, is that waves of automated trading intensified the problem. Some of the smaller dark pools – alternative markets – were overwhelmed by the orders placed and became disorderly.
As Rajiv Sethi says, this is a recipe for disaster: computer-driven trading executed in milliseconds, poor liquidity, and no automatic trading stops make for instability.
The Bloomberg article above then says
One SEC memo, according to people who saw it, discusses a theory raised yesterday by NYSE Euronext spokesman Ray Pellecchia, who said sudden price moves in multiple stocks reached so-called liquidity replenishment points. That prompted the exchange to slow trading in those shares as it tried to ensure an orderly market. Such incidences allow other exchanges to ignore NYSE price quotes.
Trades sent to electronic networks then fueled the drop, said Larry Leibowitz, chief operating officer of NYSE Euronext. While the first half of the Dow Jones Industrial Average’s 998.5-point plunge probably reflected normal trading, the decline snowballed as orders went to venues lacking liquidity to match them, he said in an interview yesterday…
NYSE competitors such as Nasdaq OMX Group Inc. don’t use liquidity replenishment points. The SEC and CFTC in their joint statement raised concerns that the plunge may have been caused by exchanges not adhering to uniform practices.
“We are scrutinizing the extent to which disparate trading conventions and rules across markets may have contributed to the spike in volatility,” the regulators said.
No wonder. It is time to end this market in markets, and to throw some sand in the cogs of the algos. If every trade executed in the same, say, five second interval got the same price, instability would be greatly reduced, yet ordinary investors would not notice the effect. And if every trade were executed on the NYSE, or at least using the same market conventions, then officials could actually stop everything when things get out of hand.
A very readable and plausible account from a sell side analyst is here. I’m going to quote it at length as it deserves the widest possible dissemination:
I’ve got 28 pages in front of me of P&G prints [individual trades in Procter and Gamble] that occurred between $39 and $50 per share and between 2:46 p.m. and 2:51 p.m. At 36 prints per page, that means P&G traded over one thousand times at those “crazy” and “surely erroneous” levels. I’m sorry, but that isn’t an error, THAT IS WHAT WE LIKE TO CALL TRADING. So what happened here? Three things:
- Sellers probably had orders in algorithms – percentage-of-volume strategies most likely, maybe VWAP – and could not cancel, could not “get an out.” These sellers could be really “quanty” types, or high freqs, or they could be vanilla buy side accounts. It really doesn’t matter. The issue here is that the trader did not anticipate such a sharp price move and did not put a limit on the order. The fact that the technology may have failed does not mean the trader deserves a do-over, it means that the trader and the broker who provided the algorithm need to decide whether any losses should be split.
- Sell stop orders were triggered which forced market sell orders into an already well offered market.
- While the market was well offered, it was not well bid. Liquidity disappeared. For example, in P&G, 200 shares traded at $44.10 at 2:51:04 in the afternoon and one second later, at 2:51:05, three hundred shares traded at $47.08. That’s a three dollar jump in one second. Bids disappeared, spreads blew out, and no one was trading except a handful of orphaned algo orders, stop sell orders, and maybe a few opportunists who had loaded up the order book with low ball bids (“just in case”). High frequency accounts and electronic market makers were, by all accounts, nowhere to be found.
It boils down to this: this episode exposed structural flaws in how a trade is implemented (think orphaned algo orders) and it exposed the danger of leaving market making up to a network of entities with no mandate to ensure the smooth and orderly functioning of the market (think of the electronic market makers and high freqs who can pull bids instantaneously as opposed to a specialist on the floor who has a clearly defined mandate to provide liquidity).