Why Attributing Price Moves to a Single Market Participant Is Difficult
Summary
The document considers whether minute-level data for large NYSE stocks can reveal if a price move came from one participant or from many smaller orders. Its central lesson is that reliable attribution is difficult because a large trader may conceal activity through intermediaries, venues, or aliases, and may use tactics such as patience, refreshing displayed size, or trading against their intended direction to reduce market impact.
The responses suggest that order-book or ladder observations may offer clues, while recognizing that these are speculative. Identifying execution patterns would require knowledge of participants' algorithms, and observed moves may trigger other algorithms, making even abrupt errors hard to distinguish from ordinary market responses. The discussion offers no tested detection method or empirical evidence that minute bars can identify a specific trader. Broker insight is mentioned as a possible source of certainty, underscoring the limits of inference from public market data alone.
Key ideas
- Price moves in minute-level data are difficult to attribute confidently to one participant.
- Large traders may hide activity through intermediaries, multiple identities, or patient execution.
- Order-book patterns may provide clues, but the document describes them as speculative.
- Recognizing execution schemes requires knowledge of other participants' algorithms.
- Market reactions can make abrupt mistakes difficult to distinguish from algorithmic feedback.
Tags
Full text
# How to determine if one player moved a price # How to determine if one player moved a price I'm trying to understand what caused certain price movements (aren't we all!) in per-minute data for major NYSE stocks. In particular, I'd like to determine whether a given price movement of X% in either direction was due to a single entity making a large trade (maybe their order-splitting algorithms leave traces, or maybe they skipped that and had to buy/sell in a hurry) versus an aggregation of many small orders. What is the best way to approach this analysis? ## Answer by rajah9 (score 3, accepted) https://quant.stackexchange.com/a/975 This could be very difficult to determine in practice, because the axe (who controls the supply and demand) wants to hide his tracks. Also consider the axe's aliases. I mention this because you would need to take into account the axe disguising his trades through another market maker (for example, Goldman trading through ARCA, or even showing sales between himself and his conferderate). If it is the player's task to accumulate or distribute a lot of stock, his job will be to do so with as small a change in stock price as is possible. He may achieve this through a number of different methods, including head fakes (selling a small quantity when his direction is to accumulate), patience (accumulating over several days or weeks) or refreshing his bid size. ## Answer by SRKX (score 4) https://quant.stackexchange.com/a/967 If you look at the ladder, you might have some insight, but it's mainly speculation. The only way to be really "sure" in my opinion would be to have some insight from a broker. Otherwise, what I'd try to look for is to recognize execution schemes, but again you have to know the algorithms of all the participants in order to determine "who" it was. In my opinion, even "fat fingers" are difficult to detect, because I think the algos are reacting to the move in the market (probably using some kind of momentum) and kicking in as well.
Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.