Equity Trading Fundamentals: How Fast, How Small, How Soon, and How Easy?
Trade Size is Shrinking, but the Queues are lengthening…
So far we have focused on typical intertrade durations, but this is only one measure of the speed of trading. More sophisticated measures also take into account orderbook queue dynamics; in other words, how many times you would expect an order to be placed, or cancelled, on the order book. We measure simply how frequently the bid/ask queues change, over a typical trading day, for our set of exchanges. The order cancellations or submissions we count occur only on the most competitive bid and ask levels. High numbers of changes are a strong indication of significant systematic, or algorithmic trading activity. It is here, in particular, that US trading really distinguishes itself from the rest of the world; specifically, trading on NASDAQ. In Figure 3, we look at a near current picture of number of trades, and the number of bid/ask changes, during October 2008.
Algorithms jostle for precedence in the bid/ask queues, particularly in their passive cycles. During these, they try to execute parts of their original quantity without resorting to a market order. This results in longer natural queue lengths, but does not fully explain the extraordinary number of changes evident on NASDAQ. We attribute at least some of this to other active systematic trading systems, perhaps designed to capture spread.
Ease of Trading over the Credit Crunch
Algorithms which target VWAP typically have a number of hard decisions to make. One of these, is when to transition from passive behaviour to more active behaviour. Optimal passive behaviour ensures good order placement in the bid, or offer queues. In a liquid market where there is some appetite for risk, passive cycles make executions easy and cheap. In less liquid, risk-averse markets, active behaviour is necessary to execute target quantities of shares: the bid-offer spread need to be crossed, and this pushes up the cost of the average execution.
The typical bid-offer spread that must be crossed at different periods of time varies widely. We show how it has varied over the credit crunch period in figure 4. We choose to focus only on this period to minimize the effect of tick size reductions which complicate earlier pictures of spread evolution. Some events in the history of the credit crunch are clearly visible in the typical bid/offer spread of liquid names, trading on the exchanges considered. Bear Stearns hedge funds’ bail-out is clearly visible in the NYSE spread history. Massive credit events like Lehman Brothers’ bankruptcy have a longer lasting effect on spreads.
Throughout the contortions, one trend has held steady: the trend towards faster, and – mostly – smaller and more fractured executions. It has held steady in all markets, through high volume panics, as automation suffuses equity trading more broadly each year.
To end on an optimistic note, if one views bid-offer spread as a risk indicator, then the risk aversion of the market has moved steadily downwards since March of this year. Perhaps new algorithms to deal with volatile spreads will emerge just as the volatility is decreasing. Whatever, it seems certain that algorithms will continue to evolve to the limits imposed by trading costs, and lack of alpha forecasts.