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I am curious to know if there have been studies on when selling occurs and if any useful patterns exist. I am particularly interested in the behavior of sellers when they are under water on their purchase since while an asset may theoretically be unbounded on the profit side, they can only lose 100% of purchase which might make the loss side easier to study.

Is there data/research indicating some kind of curve? E.G. x% sell when down 10%, y% sell when down 30%, z% ride it into oblivion.

I am not sure if this kind of research would be the province of behavioral finance studies based on small group experiments or if market data (e.g. brokerage house records, clearing house data, etc.) has been made available to some group to study.

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up vote 2 down vote accepted

Barber and Odean are pretty famous for doing exactly this type of research on individual investors. Now, individual investors are obviously not representative of market participants, so if you are looking for a generally applicable answer to your question, or for an answer specific to institutions, this is not it.

An example of their research is The Behavior of Mutual Fund Investors.

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I highly doubt there are useful studies around. Think about it, the answers of such data sets must be highly skewed simply because there are price takers in the market that are extremely secretive about profits and losses. You will only get one side of the story and it most likely skews the results by quite a bit.

Also, keep in mind many institutions do not cut positions themselves to stop out of trades but they put on hedges. The most recent trading error at JPM is a good example. Would they have cleaned up their CDS portfolio and traded out of their Series 9 positions they may have easily lost twice as much as is currently estimated. On the other side the book cleaning at SocGen was done as badly as could after Kerviel's trading blunders for the precise reason that they sold all positions as quickly as they could instead of first putting on broad market hedges for risk mitigation purposes.

In summary, I do not believe you will get anything useful to work with by looking at such studies. Useful I mean in the context of making money in the market or setting up profitable trading strategies. If you want to just write an academic paper then go ahead, but there are enough out there who write a lot and even get Nobel prizes but could not generate 10% annual returns in actual markets.

I would probably look at the issue at hand by investigating individual stock time series. There are inflection points that can be isolated. Look at statistically significant price jumps or large continuous moves in volume at the open or nearby market closes absent any company specific news releases/ratings changes/up/downgrades and also in isolation, meaning, times the stock moved in volume while sector indicies or broad market indicies did not correlate. Thats how I would look at it.

Why am I saying all that? Simple: Because there is a reason why many top ex-bank traders truly struggle right now to generate returns that keep AUM at stable levels. Such traders had a lot of information at their disposal inside the banks where they saw all the money flow of large institutional players. Prop bank trading was the biggest cash cow of the past couple decades in financial services and it will soon be entirely gone (until the pendulum starts to swing back ;-)

Edit: You may also want to look at pure OTC instruments that are not available to the masses. If you have access to swaptions pricing data this will give you a taste of how institutional players cut positions at times. Also, another idea could be to look at fx markets. Those guys at bank and broker desks are not the most iq blessed chaps out there in the trading world and as a result often openly share and disseminate information where they see stop loss levels lying around. Often you need to take it with a big grain of salt but there is definitely channels out there that provide very accurate levels and this is what you may want to focus and zero in on.

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