Re: Proof that neural nets work

Bill Reid wrote:

Since you are posting this on a stock newsgroup, are you implying
that stock prices can be predicted by linear, albeit "complicated"
trig functions? If we could devine what these functions are, similar
to "attractor reconstruction" in chaos theory, could we then just throw
the nueral net away and use the functions to predict the market?

William, in my first response I hadn't read your question carefully
enough. It is a precise question and deserves a precise answer.

The pictures at http://www.goldengem.co.uk/description.html#proof show
the result of putting some related math functions (not linearly
related) into a neural network, then asking the network to predict each
one into the future.

The functions are chosen not to be useful, but to be hard to predict.
Things like cubing the sin of i, then adding a number, then taking the
cosine of that!

The point is, no one could predict even one function, but since the
four functions entered are related to each other (but not linearly) the
neural network was able to figure out and predict all of them
perfectly.

What does that prove? Not that neural networks can predict the stock
market. It proves this particular one does what neural networks can do
best: when there is a relation between graphs, it will find it, and use
that to its advantage to predict one into the future.

This is very different from linear algebra, or linear regression. The
relation between these functions is very complicated and indirect. Only
a neural network could do this.

Now, a net like Stock100 that just runs automatically cannot really do
anything useful. You have to have human cognition first, to imagine a
relation between various tickers and volumes. Then, a neural net can
tell you whether that relationship is real, and quantifiable.

That works in GoldenGem because, when you set sensitivity to zero, the
net is blinded to the blue curve (the present day stock values) and
only sees the red curve (the historical prices and volumes). So if the
green curve it produces is matching the blue curve, this means, it HAS
found a mathematical relationship.

We are not expert investors, we are providing a mathematical service
here. To check that we have not made any mistakes,we can use GoldenGem
to predict very complicated mathematical functions. We ourselves are
not using it in the stock market, and we do not know how.

It is very clear if we entered too many stocks, or entered just all of
the, it would get a fit, but for the wrong reasons (essentially because
with enough input data there will be enough random connections for it
to find a fit). But if a person has an idea that a connection might
exist, that certain share activity might predict certain other, the way
to make that rigoruos, and quantify it, and get a prediction based on
that would be defniitely to use a neural net. And I can certainly
promise that GoldenGem would be the one to use.

.

Relevant Pages

  • Bill Reids post
    ... related) into a neural network, then asking the network to predict each ... Not that neural networks can predict the stock ... This is very different from linear algebra, ... green curve it produces is matching the blue curve, this means, it HAS ...
    (misc.invest.stocks)
  • Re: Proof that neural nets work
    ... reason for asking about that. ... your neural network to see what happens... ... SINGLE stock and future prices. ... One of the big neural net sites mentions the lottery, ...
    (misc.invest.stocks)
  • Re: New record for spec fp peak on x86
    ... a clocked-up version of the same old core. ... vindicated because it ended up being linear. ... a few years of great stock picks means that you're a good stock ... established Hennessy and Patterson performance equations. ...
    (comp.arch)