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When dealing with trade data, for example from TAQ, a common problem is that of determining whether a trade was a buy or a sell. The most commonly used classifier is the Lee-Ready algorithm (Inferring trade direction from intraday data, 1991). Unfortunately, this method is known to be inaccurate: Lee and Radhakrishna (Inferring investor behaviour: evidence from TORQ data, 2000) report that Lee-Ready incorrectly classifies 24% of the trades inside the spread.

How to improve on Lee-Ready's recipie? What are the best algorithms for trade classification?

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On every trade there is both a buyer and a seller. When you talk of a buy or sell do you mean which side was the aggressor? ( removed liquidity). In the case of intraspread prints even that gets pretty blurry since you have to consider internalizers and pay for order flow models.... – PabTorre Sep 28 '13 at 5:28
Have a look at the VPIN papers for their method. – user2763361 Oct 2 '13 at 14:12

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