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Can Machine Learning Techniques Be Used To Predict Market Direction? The 1,000,000 Model Test.

During the 1990′s the advent of Neural Networks unleashed a torrent of research on their applications in financial markets, accompanied by some rather extravagant claims about their predicative abilities.  Sadly, much of the research proved to be sub-standard and the results illusionary, following which the topic was largely relegated to the bleachers, at least in the field of financial market research.

With the advent of new machine learning techniques such as Random Forests, Support Vector Machines and Nearest Neighbor Classification, there has been a resurgence of interest in non-linear modeling techniques and a flood of new research, a fair amount of it supportive of their potential for forecasting financial markets.  Once again, however,  doubts about the quality of some of the research bring the results into question.

Against this background I and my co-researcher Dan Rico set out to address the question of whether these new techniques really do have predicative power, more specifically the ability to forecast market direction.  Using some excellent MatLab toolboxes and a new software package, an Excel Addin called 11Ants, that makes large scale testing of multiple models a snap, we examined over 1, 000, 000 models and model-ensembles, covering just about every available non-linear technique.  The data set for our study comprised daily prices for a selection of US equity securities, together with a large selection of technical indicators for which some other researchers have claimed explanatory power.


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2001-06-13 12:10:13 by datamouse

An article in Rolling Stone (October 20, 1994) by Adam Miller called J. Philippe Rushton a 'professor of hate,' someone who 'takes money from an organization with a terrible past' (the Pioneer Fund, a foundation said to have an orientation toward eugenics). He is accused of being 'obsessed with intelligence and genetics' to the point of having 'racist' attitudes by Jeffrey Rosen and Charles Lane in The New Republic symposium on IQ (October 31, 1994). They single out Rushton for linking ethnocentricism to genetic factors; this in turn subjects him to the broad brush of being, along with Richard J. Herrnstein and Charles Murray, 'Neo-Nazis' Newsweek (October 24, 1994). In The Chronicle of Higher Education (October 26, 1994) critiquing Herrnstein and Murray's The Bell Curve it is clear...

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Neural networks, machine learning and artificial intelligence approaches have helped YouTube discover—without human intervention—what cats are and have helped paleontologists speed up the fossil hunt. Because they can analyze vast swaths of data, ...

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