Quote from Jerry030:
Not really.
The software application looks at history, be it market prices time series, pervious acoustic signals from geological formations that have produced oil or failed to produce it or previously intercepted voice patterns of known terrorist suspect then identifies patterns and relationships that are currently unknown and unseen by a human reviewer and learns them. If they hold up on unseen data not subject to the same learning and discovery process and on future unknown data (works in the real world), then it's of value as something unknown has been discovered and verified.
Attached is an example of predictive analytics applied to FOREX.
Goal: trend detection.
Data Structure: modified Landmark
Analytic tool: neural network
Market: Forex EUR/JPY hourly bars
Training Set 24,000 bars
Stable out of Sample Performance: about 4,000 bars
Retraining time: about a week.
As you can see it doesnât catch the exact trend turn point but it does get signals bars sooner than conventional linear rule systems, which havce to wait for the price to move as they arenât pedictive.
The other drawback is as you mentioned in non-linear/asymmetric systems about 55% of the time there is nothing to detect as the market is chaotic or at least the analytics process could not learn a pattern structure. So sometimes it doesn't trade for a few days.
Jerry