Below you will find pages that utilize the taxonomy term “Genetic Algorithms”
I downloaded and started to fool around with another genetic algorithm addin for Excel. This one is called xlbit and is created by Xlpert. What I like about it is that it has a better interface than Gentik Solver, but its not free. It allows you do max and min for target cells, add constraints (a big plus), and lets you choose between three genetic algorithms: Elitism, Roulette, and Tournament. It even creates a new worksheet with results and graph for your average and overall fitness.
I believe that we are fast approaching a bottom based on my market timing model and simulations.Â I know I've said that before but these levels of panic can't sustain themselves for long without some sort of capitulation.Â Below is a superimposed weekly chart (from 1990 through last week) of the my market timing indicator relative to the S&P500.
It's a pretty good indication that some sort of top (not necessarily thee top) was made if a rapid rate of change in the indicator occurs while simultaneously making a new high.
The one nice thing about Genetic Algorithmic stock market models is that they evolve with new market data. The bad thing about them is that they're a pain in the ass to create.Â My current GA model is surprisingly simple and works in conjunction with my S&P500 Volatility Timing Model.
Although its highly secret, what I can tell you is that I use the Genetik Solver Excel Addin.Â I specifically use it because its free and integrates with MS Excel.
Yes you read that right, I'm working on a new set of RapidMiner tutorial posts (I'm bagging the videos for now). I hope to share with my readers two new tutorials over the coming weeks/months and I expect to post the first installment this week.
The first tutorial will be about using RapidMiner's Evolutionary Weighting and Genetic Algorithms to build a Market Timing Model. This tutorial will follow the same methodology I used to build my S&P500 Market Timing Model.
Ugly posted a great article from the New Scientist magazine that discusses how scientists are using Genetic and Evolutionary algorithms to solve all kinds of problems. The article highlights a few uses for these algorithms such as finding the optimal hull shape for boats or determining the best design for cochlear implants. Still though, why should you even bother using Genetic and Evolutionary algorithms in the first place? The reason why is because these algorithms use an evolutionary approach to selecting the “best fit” input variables.