Neural networks are processing devices (algorithms) that are loosely modeled after the neuronal structure of the human cerebral cortex but on a much smaller scale. Most neural networks contain some form of ‘learning rule’ which modifies the weights of its internal connections according to the input patterns that it is presented with. In a sense, neural networks learn by example as do their biological counterparts.
But neural networks can’t learn until you throw enough data at them. They need large quantities of information to consider and attempt to classify. Most people already know that the neurons that do the computation in our brain are not organized like the linear processes of computer semiconductors. Rather, in the brain each neuron is nominally its own self-contained actor, and it’s wired to most or all of the neurons that physically surround it in highly complex and somewhat unpredictable ways.
What this means is that for a digital computer to achieve an ordered result, it needs one over-arching program to direct it and tell each semiconductor just what to do to contribute toward the overall goal. A brain, on the other hand, unifies billions of tiny, exceedingly simple units that can each have their own programming and make decisions without the need for an outside authority.
We use computer servers to run a simulation of a bunch of heavily interconnected little mini-programs which stand in for the neurons of our simulated neural network. Data enters the network and has some operation performed on it by the first “neuron,” that operation being determined by how the neuron happens to be programmed to react to data with those specific attributes. It’s then passed on to the next neuron, which is chosen in a similar way, so that another operation can be chosen and performed.
There are a finite number of “layers” of these computational neurons, and after moving through them all, an output is produced. Using market data in this fashion, the outputs our network produces are the relative Buy and Sell zones that occur as a security creates pivot points in its trading pattern.