Limit Order Cancellations, Spoofing, and Market Quality
Summary
The document asks whether predicting limit order cancellations has academic or practical value, including for exchange surveillance, spoofing detection, and high-frequency trading. The response emphasizes that spoofing is difficult to define and prove: an order may be canceled for legitimate reasons, and intent to manipulate is hard to infer from the order alone. Exchange orders are treated as firm commitments while displayed, though motives remain ambiguous.
An anecdotal example describes a reduction in tick size for Short Sterling futures that was followed by lower liquidity and greater visible price impact, then reversed. The response says it cannot determine whether spoofing caused the change, and suggests exchanges may use participant and behavioral statistics to assess market functioning. This is an opinion-based discussion with no predictive model, formal evidence, or cited studies, so it motivates surveillance research without establishing how accurately cancellations can identify manipulation.
Key ideas
- A canceled order alone does not reveal whether the trader intended manipulation.
- Spoofing is difficult to define, detect, and prove from order behavior.
- Exchanges have an interest in monitoring behaviors that may affect orderly markets.
- The tick-size anecdote links a market design change with reduced liquidity, but does not prove spoofing caused it.
- Cancellation prediction could be useful for surveillance, though the document offers no tested method.
Tags
Full text
# Limit order book cancellations # Limit order book cancellations Is there any practical and academic interest in predicting which orders in a limit order book will be canceled? From a policy point of view are people interested in detecting potential spoofing within the market? or would the SEC or similar be interested in detecting anomalies with canceled limited orders? i.e. is there interest academically if somebody were to develop a model to detect which orders are likely to be canceled? From a practitioners point of view are HFT firms interested in detecting if the sell side of an order book is overinflated with potential orders which will be canceled. I know spoofing is illegal but does it still happen? Are there any papers out there trying to detect spoofing or canceled orders? I am more interested in this from an academic point but its also interesting to me from a practitioners point also. ## Answer by Attack68 (score 5) https://quant.stackexchange.com/a/42458 This is somewhat of an opinion based response with some factual anecdotes at the end. Spoofing is a very difficult concept to define, identify and prove. In voice brokered markets where transactions are executed with levels of discretion, spoofing can be more readily identified by people refusing to commit to trades with insufficient reasons of cancellation. On exchanges one cannot refuse to trade if a transaction has been electronically registered, so the notion of bidding/offering a price represents a commitment at that point in time. Whether there is a desire or not to physically transact is subjective and can easily be argued, and whether the intent of the price order is to manipulate the market is also very difficult to characterise. Neither of those necessarily come without calculated risks and cost to the dealer. It is my own personal opinion that where a market exists that only allows firm prices to be shown and for any other participant to respond to those prices everything is fair. In practical terms the organisers of the exchange have an interest in maintaining and orderly and stable market. Around 2011/2012 I think Short Sterling futures (3M LIBOR futures in GBP) decreased their bid/offer tick size on the exchange from 1bp to 0.5bp. Liquidity, as a result dropped (the number of participants happy to market make a reduced spread fell) and the ability to visibly impact the market by trying to transact sizeable quantities increased. Whether this was characterised by spoofers trying to manipulate Short Sterling in order to profit in other instruments, or by large dealers unable to execute similar volumes to before it is unclear (probably both). But the result was a worse market characterised in terms of anecdotal volumes and volatility. The exchange reversed the change. Whilst I cannot attest to the notion of spoofing directly it seems there must be some level of statistics, particularly user data from an exchange point of view that characterises certain type of behaviours that are either conductive to the overall functioning of a market, or are not.
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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.