Monte Carlo Resampling of Equity Curves Using N-Bar Segments (paper)
Very readable paper on MC resampling techniques. Classic MC techniques tend to generate smoother equity curves with shallower drawdowns than actual live results, as they “chop up” returns too finely, thereby reducing the impact of correlation during Black Swan events. The paper presents a simple method which attempts to preserve these correlations (click on title to view paper).
Global Optimization Algorithms: Theory and Application (e-book)
Well written e-book on various optimization strategies using bio-inspired/evolutionary techniques (click title).
Clever Algorithms: Nature-Inspired Programming Recipes
A nice overview of Bio-Inspired algorithms, including Genetic Algorithms, Genetic Programming, Simulated Annealing, Neural Networks, Particle Swarms, Ant Colonies, Artificial Immune Systems, etc (click on title for article).
Data Mining Bias: The Risk of Picking an Inferior Rule
A quick study on how to avoid every algo trader’s worst enemy (or at least one of them): the dreaded Data Mining Bias (click title for article).
Bootstrapping: White’s Reality Check
Interesting article on WRC (click title):
“Prior to WRC, bootstrapping could be used to generate the sampling distribution to test the significance of a single rule. White’s innovation, for which he was granted a patent, allows the bootstrap to be applied to the best rule found by data mining. Specifically, WRC permits the data miner to develop the sampling distribution for the best of N-rules, where N is the number of rules tested, under the assumption that all of the rules have expected returns of zero. In other words, WRC generates the sampling distribution to test the null hypothesis that all the rules examined during data mining have expected returns of zero.”