"Let's say that there is a buyer willing to buy 100,000 shares of BRCM with a limit price of $26.40. That is, the buyer will accept any price up to $26.40.
But the market at this particular moment in time is at $26.10, or thirty cents lower.
So the computers, having detected via their "flash orders" (which ought to be illegal) that there is a desire for Broadcom shares, start to issue tiny (typically 100 share lots) "immediate or cancel" orders - IOCs - to sell at $26.20. If that order is "eaten" the computer then issues an order at $26.25, then $26.30, then $26.35, then $26.40. When it tries $26.45 it gets no bite and the order is immediately canceled.
Now the flush of supply comes at, big coincidence, $26.39, and the claim is made that the market has become "more efficient."
Nonsense; there was no "real seller" at any of these prices! This pattern of offering was intended to do one and only one thing - manipulate the market by discovering what is supposed to be a hidden piece of information - the other side's limit price!" [emphasis in original]
Some of the firms even use facial recognition software to determine whether the speakers believe what they're saying. My friends joke about how Cramer is a goldmine for their algorithms but that the profitable trades rarely match up with his advice.
This is really sad. My father has been a floor trader for nearly 30 years and everyone who loves the business bemoans the computerized trading that goes on. There's no ACTION on the floor anymore. It's just boring button pushing and screen watching. Specialists can't work orders the way they used to, and most traders are at the mercy of their machines. It's killing the NYSE for one, and besides, it's just not FUN to trade anymore. When I used to go to work with my dad as a kid, it would be insane on the floor; people yelling, running around, working their orders. … So many people have lost their jobs because of these idiotic trading programs.
There's some hyperbole there, but it's not as threatening as it sounds. No, they haven't invented strong AI, but it's easy to develop NLP algorithms that are non-deterministic in practice. In my NLP class we wrote spam filters that used Bayesian filtering, trained on known-good/known-bad datasets. After training, you could see the spam score the algorithm assigned to a piece of mail, but there was no way to say exactly why it assigned that score except to say "that's the current shape of the neural net".
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