Hi, my name is Erich and I am new to this forum.
I am a mathematician working in the field of data mining / statistics.
In recent years I have developed a new data mining algorithm which
in many ways is better than the standard text book algorithms like
neural networks, univariate decision trees, at least so I think.
The algorithm was not developed primarily with trade in mind.
One of my test problems I constructed with Yahoo trade data.
I did not really expect great results because I believed that
stock movements on the small scale are mostly Brownian motions and
hence can not really be predicted. But to my surprise I found that that is not true.
In the model the movement of the Dax-Index on a day is predicted using
movement key data from previous days of the Dax, Nikkei, Dow Jones
and HangSeng.
I am now looking for a partner with access to historical intraday data.
I could show him/her the results that I get so far with the Yahoo data using
a screen-sharing session on the internet. I am open to all kinds of collaborations.
Best regards, Erich
I am a mathematician working in the field of data mining / statistics.
In recent years I have developed a new data mining algorithm which
in many ways is better than the standard text book algorithms like
neural networks, univariate decision trees, at least so I think.
The algorithm was not developed primarily with trade in mind.
One of my test problems I constructed with Yahoo trade data.
I did not really expect great results because I believed that
stock movements on the small scale are mostly Brownian motions and
hence can not really be predicted. But to my surprise I found that that is not true.
In the model the movement of the Dax-Index on a day is predicted using
movement key data from previous days of the Dax, Nikkei, Dow Jones
and HangSeng.
I am now looking for a partner with access to historical intraday data.
I could show him/her the results that I get so far with the Yahoo data using
a screen-sharing session on the internet. I am open to all kinds of collaborations.
Best regards, Erich