Following my previous post “New Tools at the Horizon“, one question was twirling in my mind: why the stock market is forecastable, but the forecasts are not affordable?
The forecastability of the market is an evidence, because if it were not – being it just a random walk – there would not be the possibility to have an output from the neural networks that manage the forecast process. For a neural network to work, there must be some sort of structure inside tha data that can be used to produce the forecast/diagnosis.
And this hidden structure is present indeed inside the market data, otherwise r.Virgeel would be totally blind and dumb. This is a sample chart of a blind network: not structure is evaluated and the output is just an array of zero values.
The fact that we humans do not recognize any structure in the data is irrelevant.
So we have a (hidden) structure, the neural tools recognize it, but the output ranges from nicely precise to totally incorrect, without having the possibility to know how much the result is matching the real future movement of the price.
Now, I begin to see the light.
The price of a financial instrument is the result of an ask/bid process, where a multitude of actors (I’m considering liquid markets with a wide audience) buy and sell that instruments under the suggestion of a personal forecast that the price of that instrument will rise or fall in the future. Every partecipant to this activity actually does a personal forecast every time he/she executes an order. So, the resulting price is the sum of all the collective forecasts and, at the end of the day, this collective forecasting process generates the push that contribute to move the trend.
[revec2t text="Every partecipant to the market activity actually does a personal forecast every time he/she executes an order."]
In other words, every attempt to forecast the market is a process of forecasting a collective forecast activity, a meta-forecast: no surprise that somewhere in the process one or more dimensions are lost and the result is probably something similar to a shadow, that let you recognize the original shape under certain conditions and totally mistify the original shape under other conditions. When you project a multidimensional event in a field that reduces the dimensions (think to a 3d object projected onto a plane) you lose a significant portion of information and you may generate a lot of ambuguity.
Now, the forecasting process is just a minor side activity of r.Virgeel, even if it is the most appealing and mind-storming: r.Virgeel is mostly a diagnostic tool that reads current data and find historical patterns that match the best market position available, with a significant success.