trading Archives - Ravi Desai

Next steps

I would love to be able to get a running forward-testing system going for the pleasance project. This would involve downloading the latest financial information, then training pleasance on it, and applying the trained neural-net on the latest information, and making a prediction. Then do this all over again every week. Provide a running statistic […]

Analysis of magnitude of changes

I’ve been told to look into the magnitude of changes in the market. I’ve done that while sorting them into 2 categories; by the accuracy of the directional prediction. The following box-plots show the results. You will see that there are outliers for both groups, but the number of outliers for the wrong-prediction group are […]

New performance measures for pleasance

This post is a recap of the pleasance system. I’ve just finished checking the pleasance system on the EURUSD and GBPJPY trading pairs. This is in addition to the GBPUSD that I usually work with. I had found a logical error in the nn-for-ga.lisp file, and it has now been fixed. It made no difference […]

Lucifer is out

The ‘lucifer’ project is out. Its available at its Github page. It should be a good basis for most of the trading simulations that I have planned. The next step is to create a seperate project with all the trading system simulators on them. That should be fun. I’ll find enough ideas on the forums.

Musings – 20120106

In the last few weeks I’ve been trying to think about how to make a system that has a way to finding out robust trade parameters. I recently just got a paper and pen and started thinking about it freely and noting everything down. Perhaps its time I break out the ‘Thinkertoys’ book again. This […]


> Its the end of the year. I’m not where I wanted to be at the end of the year. On the other hand, I’m in a better place than I was at the beginning. Progress in small steps. State of the program. I’ve put the program up on under a GPLv3 license. This […]

>Success, failure, and giving up.

> So I hit an interesting place a little more than a month ago. My program worked. But it didn’t give results that were terrible helpful. Talk about an anti-climax. First, the good part. The good part is that the GA+NN combination works wonders. I had it crunching through 50 different chromosomes for about 30 […]

>Big updates to the system

>With the reading of the Yu, Wang & Lai book (Foreign-exchange-rate forecasting with artificial neural networks), I decided to implement a Genetic Algorithm (GA) to figure out which indicators are actually useful for predicting the future price. This involved further refactoring of the code. Genetic algorithms A GA works by sampling and scoring different possible […]

>Neural nets

> Finally, a discovery After months of reading through articles online and searching for books in the public library, I finally hit upon a book that explains neural nets to me in a manner that I understand and can implement. It explained things to me in a clear manner, and I finally got it. This […]

>Better statistics

>I’ve broken apart the time frames that I’m studying, and so I now have a better idea of the sort and variety of results I can expect from the random-entry system. First I divided the data into 2 parts, and then I divided it into 6. For both studies, I performed the same simulation and […]