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On a security by security basis, I want to be able to quantify the level of HFT activity (and later institutional & retail activity). Is it higher than it normally is? How much so?

What would you say is the best way to measure? Number of quotes? # of quotes relative to volume? Relative to # of trades? Spread volatility? Reversals after block prints?

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how is HFT not institutional trading? – phil Feb 25 '11 at 14:33
referring to long only institutional investors, the funds that hold positions as opposed to prop desks. – tdelet Feb 25 '11 at 14:42

You won't know who made the trade, so you'll need to look at the quotes. Specifically, you should look to see if there are a lot of cancellations in the full order book. That will tell you if there's higher "churn" for a particular stock since HTFs often have low fill ratios (<1% for some shops). But you'll need to control for volatility since wild market swings in general will cause market makers to pull their quotes.

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A simple way to do this with the TAQ database (Nasdaq trade and quote) is to measure the amount of time between a quote update and a trade inside that quote. The shorter that time, the higher probability HFT is present.

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A trade always happens at the most recently updated inside price. Lag won't differentiate between an asset manager and a prop shop. – chrisaycock Feb 25 '11 at 16:41
@chrisaycock: i should have have been clearer. choose the trade time and sales as your basis, and see how long it takes the quote to catch up to the trades(TAQ, or NBBO, or other). Most HFT, in equities, is based on the lag between RegNMS feed, and the exchange/colo feed. – glyphard Feb 25 '11 at 16:49
Interesting. I suppose there are two differing situations: there can be high frequency "interest" that doesn't lead to a lot of actual executions (which would be characterized by a lot of quotes, cancels and relatively few executions. Then there is actual HF "trading" where we'll see the higher number of quotes, a lot of cancels AND a lot of executions. Presumably we'd also see the avg execution size drop. Clearly the best measurement will need to take into account the different HFT strategies. – tdelet Feb 25 '11 at 19:43
@user483: here's a good source to get a handle on the order cancellations that chrisacock talks about and the quote lagging that I referred to: nanex.net/FlashCrash/CCircleDay.html – glyphard Feb 26 '11 at 16:05

You might find the paper "Low-Latency Trading" by Hasbrouck and Saar useful. In it they discuss the episodic nature of some high-frequency flow and construct some useful measures of this flow.

Generally, I would think some model that relates the cancel rate with the quote rate is most useful.

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