

Training Rats as Traders - nav
http://sites.google.com/site/artmarcovici/rat-traders

======
Spyckie
My first thought was, is it April 1st already?

"Since I did not want to make it too complicated, I only used the USD/EUR
future to make the rats experts in this specific market segment, but other
rats can be trained in other markets as well. I trained the rats for about 3
months, starting with 80 Sprague Dawley laboratory rats, 40 males and 40
females with the intention to cross the best of them to genetically create the
best traders through select breeding."

Sounds like a pigeonrank algorithm to me...

~~~
andreyf
Considering the rest of the website, this is probably social commentary, not a
real experiment...

~~~
Alex3917
It's clearly not a real experiment. The social commentary angle is
interesting, although personally I'd tend to lean more toward elaborate hoax.
The only thing I don't understand is why it has so many votes. It's not like
it's at all insightful or illuminating when viewed as a thought experiment, so
people must just be falling for it.

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steveplace
Essentially, he made a more complicated version of a moving average quant
system.

The more interesting part was breeding top-performing rats to see if they are
able to improve their "trading" genetically. You can do this _exact same
thing_ using evolutionary algorithms with trading systems that help you to
adapt to the market.

Quant finance is fun when you're doing it for yourself, not a bank.

~~~
cool-RR
I'm not sure that what you say is right. What makes you think that it's the
same?

~~~
steveplace
He assigned pitches to how fast the market was moving, and trained the rats on
those pitches. The speed of the market can be measured using averages.

~~~
cool-RR
Obviously a positive return cannot be made from moving averages. But how do
you know that the rats don't develop some sort of intuition that can make a
positive return?

~~~
steveplace
First, moving averages do play a role in some (profitable) quant systems.

Second, I never said that the rats couldn't create a positive return, but you
could model the rats behavior quantitatively and develop a system, but that's
just bringing it back full circle.

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nav
Well Keith Chen @ yale showed that capuchin monkeys show the same fundamental
behavior as humans. By the end, they were trading jello beans for sex and
creating their own bubble economy. <http://tinyurl.com/au5hq>

Comment from a buddy of mine Kartik, that I figured I'd share with the thread.

~~~
jibiki
Cool article, maybe you should submit it. There was a similar article some
months ago, but it seems to have gone unnoticed:

<http://news.ycombinator.com/item?id=248613>

The NYT article you cited is way better, although I don't think there's much
that one can say about either of them.

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jibiki
Fascinating. I'm extremely skeptical, of course. The thing that bothers me
most is that they list percentages (perhaps this is the percentage of time
that the rats guess correctly?) rather than $ amounts.

Even if the experiment fails, explaining the fact that the later generations
performed better could lead to some really interesting science.

~~~
Eliezer
Percentages rather than dollars are worthless. There are skewed bets; you can
predict "up" rightly 70% of the time and lose money on the bigger downward 30%
of the movements.

~~~
joeyo
Be that as it may, if the rats cannot do better than a coin toss, what use is
it?

~~~
JabavuAdams
Your response indicates that you did not understand the parent post.

Assume I have some system where I guess right only 25% of the time, but if I
guess right I get $5. If I guess wrong I lose $1. My expected return is (0.25
* 5 - 0.75 * 1) = 0.5, which is 50 cents.

So, I'm doing worse than a coin toss, but still making money.

This is what the parent poster meant by a "skewed bet". The payoff for
guessing "heads" or "tails" is not the same.

You can't just look at the results of the coin toss (correct guess, incorrect
guess). You also have to look at how much you get paid for a correct guess,
and how much you lose for an incorrect guess.

In most real-life situations, the payoff is not symmetric (equal win and loss
amounts). This is why your "if you can't beat a coin-toss" comment is
meaningless (and usually incorrect).

~~~
joeyo
I still don't get it:

A. I guess correctly 25% of the time (via some method) and make money because
of the skewed payoff. (0.25 * 5 - 0.75 * 1) = 0.5

B. I flip a coin and guess correctly 50% of time and make EVEN MORE money
because of the skewed payoff. (0.5 * 5 - 0.5 * 1) = 2

Why should I ever go with option A?

Furthermore if your method lets you guess correctly 25% of the time, why don't
you simply make the opposite trade and now you are guessing correctly 75% of
the time!

Are we are talking about something fundamentally non-binomial? (buy, sell and
do nothing or something even more complicated?)

~~~
JabavuAdams
Ah, ok. If there's a skewed payoff for B, then yes, you're correct. I read
your post to mean that you were not considering the payoff, and only the
probabilities.

As for the rest, what does "opposite trade" mean? For instance, going short
versus going long carries very different risks. It's unlikely that your payoff
would simply be mirrored.

~~~
joeyo

      > I read your post to mean that you were not considering
      > the payoff, and only the probabilities.
    

Ultimately, the payoff is just acting as a constant offset to the break-even
point (assuming the payoff doesn't vary with some other parameter). The skewed
payoff may mean that you only need 25% accuracy to break even or it could mean
that you need 95% accuracy to break even. It doesn't matter. Either way, you
can effectively ignore it and consider, for a given payoff schedule, how your
prediction algorithm will perform.

If we live in a universe where you can under-perform a coin toss and still
make money because of how the bet is skewed, then I can do better by flipping
a coin!

If the bet is skewed the other way, then we will both lose money but my coin
toss will lose less.

Let me restate that: you can completely dissociate your prediction algorithm
from your cost function

    
    
      > As for the rest, what does "opposite trade" mean? For
      > instance, going short versus going long carries very
      > different risks. It's unlikely that your payoff would
      > simply be mirrored.
    

Here my (lack of) knowledge of the various types of financial transactions
that can be made puts me at a disadvantage, but the way the "article"
describes it, the rats were trained to press a green button (long, betting
prices were going to go up) or a red button (short, betting prices were going
to go down).

There are only four outcomes here (as I understand it):

    
    
      * Predict Up, Moves Up
      * Predict Down, Moves down
      * Predict Up, Moves Down
      * Predict Down, Moves Up
    

It's possible that you can better predict upward movements than downward
movements, but lets assume for simplicity that you (or the rats) are equally
bad at both.

If you were able to predict at 25% accuracy, I would take what you told me (up
or down) and flip it-- because you are actually performing at 75% accuracy,
you just don't know it. Then I would make a trade. I don't know what the most
clever trade that could be made based on that knowledge, or what the various
payoffs associated with them are, but as I showed above, it doesn't matter for
the analysis.

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likpok
Issues with this that I see (aside from the obvious lack of statistical rigor)
are that he gives the rats repeated input. Effectively, he is selecting for
the rats who best memorize tracks 1-600.

~~~
mechanical_fish
_aside from the obvious lack of statistical rigor_

I think we've found a very fun story problem for a Statistics 101 class.

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mkelly
I wonder how this compares to using a neural network. I see no comparison to
using other methods to predict the market, though he claims to outperform
humans.

~~~
safetywerd
It is a neural network though, isn't it?

~~~
Rod
Exactly. It just isn't an _Artificial Neural Network_ ;-) After all, though
rats are super disgusting, they were created by Nature.

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cosmo7
Excellent social commentary.

The rather neat dynastic results table at the end show percentages but no
legend; does anyone know what they represent?

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nav
The study is very eye opening to say the least. Results are based off of and
emotion-free instinctive approach to choosing outcomes based on (to a degree)
fundamental investment principles. Pavlov's application to investing. I agree
with the thread, the most fascinating aspect is the generational improvement
throughout the experiment.

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biohacker42
Awesome!

Spoiler alert, predicting a self aware system like the stock market not so
much possible in the long run.

But profiting from the lucky guesses of rodents in the short term - possible
and awesome. (As long as it's not your money on the line.)

~~~
rw
> "predicting a self aware system like the stock market"

Please elaborate on why you think the stock market is self-aware!

~~~
biohacker42
The market makers, those tend to be human beings who buy and sell stocks,
watch the market and continuously adjust their actions based on their
observations of the market.

No elaborate theory here, just stating the oversimplified obvious.

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tichnak
I would say the % means that out of 100 investment decisions, the rats have
been correct at x-percent. I have seen this before and it looks like work in
progress, but maybe more art then science, the man is an artist...

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paraschopra
Isn't it forex, not stocks?

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steveplace
He traded forex and futures, not actual stocks. Headline misleading.

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omarchowdhury
How is the headline misleading? It says 'traders' not 'stock traders'
specifically.

~~~
paraschopra
It got changed later, earlier it was stock traders...

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Allocator2008
A neural network, whether software-based, hardware-based, or wet-ware based
(rat in this case, or human for that matter), can only spot patterns in a
given set of data which are there. No patterns in the data means no
predictability. You can have the coolest, most hyper-intelligent system ever
devised, but that cannot see patterns which do not exist. Of course market
data has patterns (sell on Friday, for instance), but it is always limited.
Generally, I think you could even in principle never get more than 80%
accuracy with any kind of neural network, because of the lack of complete
patterns in market data, whether we are talking about a rat or a human or a
whatever kind of neural network. Which brings me to a second point, since 100%
accuracy or anywhere near that is not possible even in principle, applying
electric shocks to test subjects when they are wrong is simply cruel and
irresponsible.

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alecco
We don't want HN to get hammered, please don't submit this kind of "fluffy"
stuff.

Save HN! :)

