This is a summary of links featured on Quantocracy on Sunday, 10/23/2016. To see our most recent links, visit the Quant Mashup. Read on readers!
Evolving Neural Networks through Augmenting Topologies Part 4 of 4 [Gekko Quant]This post explores applying NEAT to trading the S&P. The learned strategy significantly out performs buying and holding both in and out of sample. Features: A key part of any machine learning problem is defining the features and ensuring that theyre normalised in some fashion. The features will be rolling percentiles of the following economic data, a rolling percentile takes the last n data
Flexing VBA For Quants (And Everyone Else) [TrendXplorer]Would it not be great to have the models for Protective Asset Allocation (PAA) and Global Protective Momentum (GPM) in Excel, so you can run your own backtests without AmiBroker? And not being limited to a pre-defined universe? Actually, now you can. Based on a foundation by InvestExel, Denis Bergemann from Germany collaborated with me in developing an Excel spreadsheet that allows you to select