Hacker News Reader

Comment by socratees | Hacker News Reader

The conclusion of the article: Automated Trading could be dangerous to the market as such and should be closely monitored. They appear disturbingly similar to the hedge funds of the old days. Besides, quant-finance big shots like consider automated trading based on algorithms risky.

Correct me if I'm wrong.

View on HN

Actually, I think this argument (posed by the journalist) was woolly. Given that the high speed trading firms seem to stay market neutral (each trade is adequately hedged) and unwind their trades within hours or days, their inherent risk is less than that of massive pension funds withdrawing their capital as we saw in the 07/08 crash.

As was said in the article, these guys are really just providing liquidity for smaller traders (i.e. you and me) who want to be able to move on a security in small chunks without having to pay for an expensive broker.

That said, there is a crash-scenario if the traditional (i.e. non high-speed) platforms are triggered via stop loss mechanisms to offload lots of stock fast. But again, this shouldn't happen if they do two things:

First: look at the source of the trade. If it's one of the high speed firms, they should just ignore the trade unless it moves with a velocity of say 25% more than the high speed stuff - i.e. if it's dropping by 1.25% of the price per minute rather than 1%, then it should consider selling. (or, for a more general formula - sell if total_velocity - highspeed_velocity = x/s)

Secondly, take wider market movements into consideration - if the entire sector is falling, it's probably not an issue with the security, so there's really no point in getting out at that point - it should recover.*

The one technique revealed in that article which i found interesting - pinging to find the edges of the applicable range trade- guessing the probable worst case purchase by offering and withdrawing stock to see if it's jumped on. I could imagine this getting banned, along with the 'who's trading soon' information.

* of course, this depends on the time period the stock is willing to be held for - if the goal is day trading, then you're not going to want to stick around.

I work in this area, and the market risk you allude to here is not the one that scares me. The scary one is what I like to call algorithm or system risk. The 2003 Corinthian Colleges incident mentioned on page 3 of the article is a good example, but I've seen much worse. I once saw a major bank take literally a billion dollars of risk on in approximately 10 seconds due a bug in their algorithm (most likely a new release of a modified program) that interacted with a poorly implemented exchange interface. Some of their counterparties let them out of the trades and some didn't. Releasing new software can be a hair raising experience due to the poor quality of testing systems provided by the exchanges, the speed at which money losing trades can happen, and the vast complexity of the environment faced by the software.

I wonder how long / how hard it'd take to implement a shadow exchange to test new algos and systems... Like, perhaps new code needs to be certified in a full test environment before being deployed to the live market?

Seems like something along those lines would adequately deal with the uncertainty risk here.

I think one of the problems comes from the fact that big players affect the game. So if say, Citi launches a new algorithm that does some new crazy thing, which turns out to trigger random issues or unexpected responses in other algorithms -- such a thing could make lots of people other than citi a pile of money. Are those people really going to want Citi to test it too well?

Another, real concern with such a shadow market, where say everyone is running their algorithms (to prevent the above scenario), is that i could test "a buggy version" and find holes and odd behaviors of my competetors for free, since it is all play money.

Most exchanges have their own API for direct access. Although there is some standardization around the FIX protocol, the fastest access is still usually through the direct API, so while you may have a single backend system that processes incoming data and generates orders, you still usually need to code a separate interface for each exchange that you connect to, and the systems provided by the exchanges to help you test your interface tend to be less than robust.

Your last two sentences are a bit vague. When are the "old days"? 30 or 40 years ago, or pre 2007/8 financial crisis? Automated trading is risky; but then all trading is risky. Do you mean as opposed to another type of trading?

@andrew1, In the first sentence I referred to the 2000-2008 hedge fund trading. The second sentence is from the article - it said high speed algorithmic trading could lead to smaller version of the 1987 crash.

Oh I see, my apologies, I thought that the first sentence was the summary, and the second two were your thoughts on it.

From what I remember from Greenspan's "Age of Turbulence," he mentioned that he was pleasantly surprised that the markets were able to absorb much of the shock that happened on 9/11. I believe he attributed much of that to flexibility in the markets, which is probably related to the liquidity and efficiency that are provided by, for example, high-volume traders. Greenspan argues for deregulation of such activities since they make the markets so much more flexible, and able to withstand sudden shocks such as 9/11.

Of course, much of that was before the fall '08 crisis, so I don't know how he'd respond to that :)

Reply on news.ycombinator.com