Alexey Burnakov

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Machine learning in trading: theory, models, practice and algo-trading

Good afternoon, everyone, I know that there are machine learning and statistics enthusiasts on the forum. I propose to discuss in this topic (without holivars), share and enrich our own knowledge bank in this interesting field. For beginners and not only there is a good theoretical resource in

293

Thoughts on the random

Good afternoon! I'm writing this and wondering how not to offend anyone or provoke a flood. I hope to be constructive, and, I'm just asking (not proving, not refuting, just wanting a dialogue). If you take a series of quotes for many years and create on their basis a file of zeros and ones: zero if

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Neuro-forecasting of financial series (based on one article)

Good afternoon! Subj: http://etd.ohiolink.edu/send-pdf.cgi/Lakshminarayanan%20Sriram.pdf?ohiou1127333497&dl=y In this article, the researcher achieved a daily closing price prediction accuracy of around 94% for exchange-traded instruments. His test sample size was: 158 days. He built a predictive

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Dependency statistics in quotes (information theory, correlation and other feature selection methods)

Good afternoon! I decided to slightly develop the topic touched upon by Alexey (Mathemat) in one of the forum threads. I tried to search for dependencies in the quotes of one financial instrument using statistical methods. To begin with, I took the Dow Jones Industrial index, daily data, and

SOM: cooking methods

Good afternoon! I've been approaching the use of self-organizing maps in Forex for a long time now. I decided to make an experiment: I have taken daily bars from 2001 till the end of March 2011, built input vectors for a neural network with size 40 and trained SOM with size 7 by 7 neurons, thus