tag:blogger.com,1999:blog-107568321062020427.post8801750100777513886..comments2023-09-19T00:48:06.643-07:00Comments on Intelligent Trading: Practical Implementation of Neural Network based Time Series (Stock) Prediction - PART 3Intelligent Tradinghttp://www.blogger.com/profile/17765336450326139518noreply@blogger.comBlogger3125tag:blogger.com,1999:blog-107568321062020427.post-16815907020696068442010-05-17T19:07:12.587-07:002010-05-17T19:07:12.587-07:00I understand your comments and examples, but my po...I understand your comments and examples, but my point was that the 'cherry picked' examples are based on data with inherent cycles, hence the ability of the algorithm to produce goo results. Take away the deterministic elements, then this type of algoroithm is not as effective as such examples portray to be.adam coxnoreply@blogger.comtag:blogger.com,1999:blog-107568321062020427.post-24056154155571153682010-05-14T18:32:56.371-07:002010-05-14T18:32:56.371-07:00Thanks for the comment Adam,
Although this is tru...Thanks for the comment Adam,<br /><br />Although this is true, the data need not necessarily be cyclic. And I agree that is a problem with cherry picked type examples. However, as I illustrated with a true financial series (part 4?), the data need not necessarily be cyclic so much as it needs to be bounded and stationary. For a neural net (you can take a smoothed aperiodic set of data, and it will still learn pretty well given enough training information.Intelligent Tradinghttps://www.blogger.com/profile/17765336450326139518noreply@blogger.comtag:blogger.com,1999:blog-107568321062020427.post-85455073020978766512010-05-14T14:49:44.616-07:002010-05-14T14:49:44.616-07:00Problem with this type of example, and one which e...Problem with this type of example, and one which even Matlab promotes in its documentation is that the data is cyclic. Real time series data, particularly financial time series are random walks with heteroskedasticity.adam coxhttp://www.primeconsulting.co.nznoreply@blogger.com