What Business is Wall Street In?

i'm about to make a nuanced, technical argument, and i don't know if it's correct. if you understand it, your feedback is appreciated.

so, i believe information asymmetry is possible. i believe that many good ideas are in such a relationship with the world that the people who have them have an asymmetric advantage over those who don't: that possession of the idea equals wealth, as long as you are attempting to execute. (wealth in the net-present-value sense, not liquidity sense.)

this gives you the interesting situation that you can be walking along the road and, if you are the right person and respond properly, you can immediately in a bolt out of the blue become richer by the net-present-value of the idea you are just struck with: provided it is one of those asymmetric ones and you proceed to execute on it.

now. now, for the larger ideas (like Google), the net-present-value was in the millions. but if the people doing it had actually had millions of liquidity, they would not have been coding: they would have hired a coder.

so please assume p, where p is "a person with a net-present-value of $n million is currently coding something which will make money and then allow him to hire coders. assume that with probability 1 he will succeed."

as he is coding, before he actually has succeeded, what business is he in under p?

i would say he is in the information-arbitrage business. he is coding at $0/hour against the net-present-value of the idea he has. it seems to me kind of an arbitrage thing.

this is assuming p, which means that this is an assymetric condition where with probability 1 he pays off. obviously it becomes more complex as we get into probabilities other than 1 - but is this a fair conclusion about the startup hacker?

that he is arbitraging information asymmetry?

as i mentioned at the start of this comment, this is a technical argument and i'm not sure of its validity. any feedback is appreciated.

if you hate my assumptions (specifically, p) i still would appreciate to go with them as well as any other thoughts you may have, which you can address separately.

In order to make money on a trade, the share price needs to move. So you've got algorithms whose attributes manage things like how much of an actual order is exposed to the market at one time, or how much they adjust your bid or ask as the order progresses. I've got some algo documentation whose algo "Watch Out For" notes warn "may be too aggressive and cause impact" and "must watch out for order size that adversely impacts market". But maybe you're a trader that decides you want to be "too aggressive" with your trade and now you've moved the market because you've used an algorithm in a way it wasn't intended to be used, and your employer's risk controls didn't care or didn't catch what you were doing until it's too late. Net effect is that your trade may sway the overall market in a way that moved that company, or that company's sector, or maybe the whole market depending on what impact your trade had.

And all of that assumes the algorithms behave in a way that they're expected to. I like this example from Amazon's pricing algorithms: http://www.pcmag.com/article2/0,2817,2384102,00.asp but you could apply the same concerns to pricing matters of the stock market where the unintended consequences of poorly-conceived strategies have a destabilizing effect on pricing.

HFT allows all of this happen so much faster than could have ever been done manually. And when high frequency trading is being done by entities with enormous balance sheets, and an increased tolerance for risk due to assurances by the government that they'll be bailed out should they make a bad bet, it's got the potential to destabilize the entire market.

I agree that the system is not perfect because, lets face it, computers are not always that reliable. However, this is a problem that solves itself. If an algorithm goes haywire and drives the market down temporarily, that computer stands to lose a whole lot of money so there is tons on incentives to fix or retire that particular machine.

Otherwise it would be easy to make a very profitable algorithm on the back of the machines that create flash crashes by detecting those crashes and buying tons of shares when they are discounted in order to sell them back when prices returns to rational levels. By buying on the crash this algorithm would push the price up thus reducing the price swing.

"Otherwise the HFT spots it (and they usually do) and then front runs all of the trades, just skimming pennies off. What use are they ?"

So when BigMutualFund decides they want to buy 50 Million Shares of MegaCorp they try to disguise their order so that the share price of MegaCorp doesn't go up to much as they make their buy. That's absolutely right.

You're also absolutely right that HFTs have made it harder to disguise this action. The HFTs "see" what's going on and start buying shares of MegaCorp at a higher price and then selling them to BigMutualFund. So BigMutualFund makes a bit less money.

So where does BigMutualFund's go? To the HFTs? NO! The HFTs aren't changing the spread width, so they aren't making more money.

You know who makes more money? The current shareholders of MegaCorp who decide that they want to sell! And that's great! Whatever information it was that made BigMutualFund think that now was the time to buy gets communicated to the market faster (in terms of the share price) because of the great work the HFTs are doing.

More efficiency for all!

> it's got the potential to destabilize the entire market.

No, it really doesn't. There's not a boogey man hiding under your bed just waiting to get you.

You know what would happen if a bunch of computer algorithms went crazy and mispriced a bunch of stocks? The guys running that code would get taken for a bath(1). If a bunch of computers went crazy today and started selling shares of GOOG for $20 then the humans would start buying like crazy and the share price would correct.

1. http://en.wikipedia.org/wiki/Knight_Capital_Group#2012_stock...