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Hello Everyone,

I'm looking to build an algorithm that can put up big buy or sell orders but doesn't execute them.

Is this possible? Can anyone make this?

Kindest regards,


5 responses

Hi Sander,

When you say "put up" do you mean put an order in the market? You cannot "show" an order in the market without risk of execution.

However, if you were showing any order, but particularly a large one, that you didn't intend to execute then this would undoubtedly qualify as market manipulation.


Hi Maureen,

Thank you for your reply.

The idea behind this is that I sometimes trade in products with very little liquidity. Some big banks hold the responsibility of making the market but as soon as you throw in an order of 50k they pull their bid and ask prices.

So I was wondering if there is a way to find out if the bid and ask are 'real'.

I guess you are right and it will probably be seen as market manipulation.

I can make some suggestions on how you might be able to find liquidity in thinly traded stocks but much of it would be "off market" so not algorithm-able (such as calling around brokers for a block).

If the stock is very thin - nothing traded most days - you might try sitting your (real) block order at the top of the book each day and waiting. If a genuine cross comes in, they will show at mid price and expect you to meet them there. There are already algos around which grab at certain prices.

I just found this article Tweeting Found To Improve The Liquidity Of Small Cap Companies which a smart coder might be able to convert to an algo


The study you cited is interesting. How would you want an algo to trade on the twitter data? I can imagine calculating some kind of indexed score for a company's twitter handle - number of tweets per day is a simple example, or a rolling average over the last 7 days. Would such a measure be for comparison to other companies, or would changes in the level mean something for a particular company?

thanks for the article,


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Hi Fawce,

I don't think that I gave it that much thought when I posted the link. i just think that smalls caps have been long neglected as far as algos are concerned and their volumes have suffered as a result.

In this particular instance the investor already has a list of stocks that he wishes to buy or sell, he is merely seeking liquidity. Twitter could offer a signal against a list of small cap holdings that now is a good time for liquidity. His holding for a sale or desired holding for a buy can be stated as a ratio of "days to liquidation" figure (based on one third of a days average volume).

The spike in volume is self-referencing for a particular company but the AR(MA) model would need to be general since the tail and frequency of events in this sector would make it impractical to produce models for each company. So, for a days average volume of x in a given company, n tweets might correspond to an mx volume spike on that day (although I doubt the relationship is linear). If this mx value exceeded the "days to liquidation" ratio then order goes to market as volume weighted order or similar.

However, there is a qualitative conundrum: does the investor still want to trade given the flurry of news...