Predictive analytics is the process of using statistics and modelling to determine future performance based on current and past historical data. What if I told you that you could program a computer to read thousands of gigabytes of data about stock market information and find correlations between asset prices. It would then trade based on this information and make you money. Seems a little bit too good to be true doesn't it? Well...Thats because it is, and its more complicated than that. A lot of these execution systems deal with computing complex bayesian probability (that continually update themselves) at breakneck speed.
One distinction to make is that these predictive analytics systems are slightly different from what algorithms do. A key difference is in its ability to learn to evolve from its experience, a form of artificial intelligence. They take in what are called factors, essentially data types that vary over time and can be correlated to execution, like volatility, size of orders, spread, time of day, news etc... There are hundreds of these types of factors and past analysis yields which ones of them offer the greatest predictive power of stock prices. Those particular factors are tracked by the predictive analytics system and determine likely price movements in the form of buy/sell recommendations.
Rumours among the professional finance community claim that these systems are already forming a new paradigm of trading for both professional traders and retail traders alike. More and more specialised firms are offering these services to the community for increasingly cheap costs (some even for as cheap as a few hundred bucks a month). Only time will tell whether or not these analytics are here to stay. I, for one, say adapt or die.
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