
A bestiary of algorithmic trading strategies - Anon84
http://scottlocklin.wordpress.com/2009/08/17/a-bestiary-of-algorithmic-trading-strategies/
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slocklin
Bill Gates is only there because he's standing next to a bunch of hooters
models who are obviously there for Warren's ineffable awesomeness. Warren is
the most famous fundamentals trader there is, therefore he belongs in the
picture, even if he isn't well known as a quant. I don't have any pictures of
Richard Grinold next to pretty girls.

Buying a short, selling a long: it's still buying low and selling high if you
do it right.

As for why I'm linked here: I haven't got a whit of a clue. My best guess is
that someone realized I'm a big Lisp nerd.

-Scott

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dvvarf
Fun fact about that picture (if I've identified it correctly): It was taken
for Warren Buffett's annual Christmas card. After the photo was taken, the
Hooters girls all fawned over Bill Gates, leaving Buffett behind.

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christofd
The basics of devising algorithmic strategies come from the field of Market
Microstructure in Finance/Economics.

I took a graduate level course on it (math prof. from Stanford).

I found a decent graduate level course syllabus with all the main literature
and links to literature in it:

[http://pages.stern.nyu.edu/~jhasbrou/Teaching/2006%20Fall%20...](http://pages.stern.nyu.edu/~jhasbrou/Teaching/2006%20Fall%20PhD%20Microstructure/B40.3349%20Word.htm)

One of the main models is the Kyle model: Kyle, Albert S., 1985, Continuous
auctions and insider trading. Econometrica 53, 1315-1336
(<http://www.jstor.org/pss/1913210>)

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tptacek
I'm halfway through Harris _Trading and Exchanges_, recommended at the top of
this article, and it's just a phenomenally awesome book. I brought it up to
the lake for summer reading, it's been that fun to read so far.

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rjett
Book Extract: [http://www-rcf.usc.edu/~lharris/Trading/Book/Book-
extract.pd...](http://www-rcf.usc.edu/~lharris/Trading/Book/Book-extract.pdf)

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cowmoo
Why do algorithmic trading articles pop up frequently on HN?

I understand why people are attracted to it because they think that they can
beat the market by implementing their own stat arb strategy using neural
networks/genetic programming etc. They think that they'll fare out better than
the average day-traders because they have the know-how's to program and the
quantitative skills to formulate the models and the technical skills to
implement the models.

But what people don't realize is that despite of all that, you still can't
beat the street because: speed and volume. All high frequency trading strategy
rely on fast execution speed (get in and get out, most prop shops at
investment banks and hedge funds hold their positions usually for a couple of
seconds, or even less), because due to prevalence of electronic trading, the
inefficiency in the market for arbitrage opportunities exists in the time-
frame of seconds or micro-seconds. In arbitrage, it's no longer a matter of
who can discover the treasure map; it's more like everyone already has the
treasure map, whoever can get to the X mark the spot first wins.

Goldman Sachs/SAC/DE Shaw etc. all "colo" with the market exchanges, meaning
they have their algorithmic trading servers hooked up directly to the same
trading servers of NYSE/Nasdaq/BATS. They might be connected directly to those
market servers in the same server room in NYC/Kansas, or they might be
connected over a dark fiber network in Jersey City. In the matter of seconds a
retail brokerage customer puts out a buy order for GOOG, or even a aspiring
trading-hacker sends out a order over Interactive Broker API, these algo
machines have already piped out thousands of orders and a good percentage of
those orders have already been filled.

Secondly, good algo's require fast real-time information processing of the
quote book, general market condition, real-time calculation of the basket of
related stocks in the stat arb strategy. On an single active stock, there
might be hundreds of bid/ask/trade ticks per minute from a single market
center. Can an individual's machine setup handle real-time analysis of a
basket of stocks and general market condition from multiple market centers?
This issue is so critical and complex that there exists a sub-industry
(Complex Event Processing, CEP) and technology companies (StreamBase) that
created and profit from dealing with this problem for hedge funds and prop
shops.

Finally, usually high frequency algo's are only profitable with high volume
and low transaction cost. Typically, arbitrageurs and liquidity providers make
pennies on the share per trade. But their daily volume are in the tens or
hundreds of millions shares traded; their transaction cost are in the quarters
of pennies or sometimes negative (meaning they are compensated by the
exchanges for providing liquidity). Compare this to a retail consumer account
with $10,000 and trading comission of $5 (ETrade) - $0.01/share (IB).

Still, I know of people who have IB API setup's and profit consistently. But I
wanted to let would-be traders know the competitive disadvantage that they are
up against the big boys before they pour out their life savings in their
neural network futures arbitrage algorithm.

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BrentRitterbeck
That's like saying that the articles on particle physics that pop every once
in a while here shouldn't be posted simply because I don't have the money or
the resources to build my own particle detector. Some people find these things
interesting. It's not for you to judge what others here may find worth
reading.

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dmfdmf
> To make money as a trader, assuming your motivation is to make a profit, you
> need to buy low and sell high.

Not to pic a nit but most traders also sell short, i.e. reverse the order to
make money; (borrow stock) Sell High and Buy Low (return stock). The guy seems
pretty smart so he probably left this out to keep his explanation simple.

Side note; Short selling serves an important function in price formation and
liquidity and is not the primary cause of a stock price to fall. In fact, for
the short seller to make profits there must be an independent cause of the
fall apart from the short seller's actions or they lose money.

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mynameishere
Bill Gates and Buffet are both bad examples because both of them are
essentially managers rather than traders.

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Leon
What's a good book on algorithmic trading?

~~~
known
<http://quantlib.org/index.shtml>

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known
To fix all types of <http://en.wikipedia.org/wiki/Information_asymmetry>
issues in stock markets, every Algorithmic and high-frequency trade should be
regulated via <http://www.sec.gov/answers/form345.htm>

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eru
Why?

~~~
known
<http://en.wikipedia.org/wiki/Information_asymmetry>

