Quote from slacker:
Ok, this looks like a vendor spam with 3 new posters who just happen to be interested in the same product at the same time and happen to visit this site at the same time.
But hey, up late and bored so here goes.
This looks like a genetic algorithm that is designed to produce a better backfit of data. It would be interesting to see how the backfitted results of Dakota would compare to backfitted results of a simple one-dimension backfit of system on WealthLab or Metastock.
I personally like Genetic Algorithms. I especially like to watch them 'learn'. The Dakota program looks like it is only using bots with very few number of parameters that can be optimized. At then end of the run the results would not be much different than if you ran the same type of backtesting several times using Metastock's optimizer.
Dakota 'might' be interesting if you could run bots on several markets at the same time. Or on a single market using different time frames. It doesn't do either.
Dakota may make it easier to provide a backfitted results with a few clicks of the mouse. However, anyone want to tell me how they were surprised with the optimized parameters that were the result of one of the runs? Is this approach good enough so there is some 'discovery' of a new combination of parameters that were not considered without this swarm approach. I don't think so....
It looks way overpriced, and is targeted toward new users who do not yet understand how easy it is to produce a backfitted equity curve on any market. You do not need 'swarm', GA or Neural nets to produce these screens or these results.
But hey, just my opinion.
Welcome to ET guys!
I was a BioComp user for over a decade but abandoned it some years ago for serious trading. It's probably no better or worse than other tools like NeuroShell that are marketed to traders who have little in the way of data mining skills or training, which isnât saying much.
A few years ago I challenged the CEO of BioComp to a "Pepsi Challenge" in terms of trading results. The challenge was take a standard price data set with the same dependant and independent variables and run it through BioComp and see what the results are in terms of trading performance. The same set would be run through NeuroShell and similar competitive systems. Carl declined saying he was much to busy to allow or support a comparative evaluation of his product.
I see he now has some time to post here. What about it Carl, how about a standard objective evaluation of your products performance?
I'd be happy to supply the data set and we can get some of the old participants from the Yahoo Neural Network group to act as judges.
For anyone wanting my suggestion of software applications: forget the stuff promoted to traders. If the folks who create it and market it could make money trading it, they would. They can't so the sell it, which is a major undertaking with customer support, marketing plans, ad buys, time posting to newsgroups under various identities, etc.
Instead get the best general purpose data mining application you can afford. That is the kind of systems used by major corporations for credit card fraud detection, oil exploration and similar mission critical applications. This stuff actually works on complex problems.
Jerry030