I have published the usual monthly update and in the post I have included a significant minority report. One subscriber was surprised by the existence of a “minority report” and asked how does it work. It is an interesting question, that I cannot reply exhaustively,  without revealing some well-kept secret about the building of the model. But, I can try to explain.

Like any software tool, r.Virgeel’s code is plenty of variables. One of my long term efforts has always been to try to reduce the parameters of the model to the minimum, to avoid any possibility of over-optimize the networks. Neural networks have their ability to generalize, inducing replies out of sample, inside their realm of comfort.

Finally, I arrived in the latest versions of the model, to just one variable. The one and only that affects the model sensitiveness. Let’s call it sensibility. Low sensibility produces more volatile analysis and indicators; higher sensibility produces results more stable, day by day. If sensibility goes too high, r.Virgeel gets stuck for long periods, inside a sort of trance. There is an interval of best response.

I’m interested in a reactive and adaptive response, so I usually select a value of sensitiveness inside the well-tested range and change it only occasionally. And I also get a look to the forecasts generated with different sensitiveness and if I find a particularly persistent minority report I share it with the subscribers, to warn of any possible incoming event.

Also, consider that, to work, neural networks must be trained. Training means that experience is transferred into the network and what sorts out is that very similar conditions are trained for opposite outputs. It is not an error or a limit, it is inevitable: every market is an alive entity and r.Virgeel brews its reports from a huge correlation matrix between dozens of markets. Altogether, it’s gigantic. Bifurcations are inevitable, are part of the alive thing. Bifurcations and minority reports are different aspects of the same datascape. I’m working on this aspect, but it a long way. Anyway, bifurcations have reduced their aggressiveness and really interesting minority reports are rare.

If you come from technical analysis, you are used to consider the price bars as your primary source and you are used to self refer your data to generate some significance. Inside the model, the SPX is absent from the correlation matrix, being placed on the learning side. Yes, it’s different. The whole configuration of dozens of other markets generates the SPX  inside the brain of r.Virgeel – by the way, the most relevant markets are the biggest, not surprisingly. The process is known as “pattern recognition”: find where some similar data is in the archive and learn from it to process the current moment. Once the model works, and it has been real-time tested since 2013, you, me, we are not requested to do much. Through the indicators, r.Virgeel gives a variety of different reading of the present status of the market, designed to be in reciprocal confirmation.

The use of the output we get from r.Virgeel is up to each one of us. I’m sure everyone uses it differently, with different time horizons. The a.i. tools offer a huge potential to enhance many trading styles. At the moment I’m testing the intraday use the FastTrack indicator and the results are really nice. The FastTrack levels on the intraday chart help me to have an immediate frame and it works from 4h to 5mins. You do not have to use r.Virgeel in a specific way: find how it fits your plans.

A final word about the jargon: I understand that sometimes you may be confused by technical terms, but I must use them to try to be clear. Artificial intelligence has a plethora of dialects and terminology, it’s exploding just now and I’m sure that in the next future many concepts will be of public domain.