Some time ago I blogged about my Cauchy Schwarz inequality inspired matching algorithm and some tests of it here and here. More recently I have come across a nice paper about developing and back testing systematic trading strategies here, courtesy of the quantnews.com aggregating site, and being motivated by the exhortation in said paper to conduct hypothesis driven development and separate evaluation of each component of a strategy, I have decided to perform some more tests of the matching algorithm.
The above mentioned tests were of the Effect size of differences in means between random matches of price and algorithm matched prices for 5 bars following a test point, with the test statistic being the Cauchy-Schwarz value itself. This was intended to be a test of the similarity of the evolution of price after any particular test point. However, a more pertinent test is whether this similarity can be exploited for profit, and doubly so since I intend the matching algorithm to select training examples for my machine learning development of a trading system. If there is no potential to extract profit from the basic selection of matched training examples, it would be naive to expect any machine learning algorithm to somehow magic such profit from these same examples.
The first (set) of test(s) I have in mind is a simple Monte Carlo Permutation test, which will be the subject of my next post.
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