For example, if the raw data is a daily price series, you can create a new series of price changes over any number of days. Or you can create a series of price ratios, recent volatility, trigonometric functions of price, etc. Excel's functions and data manipulation capabilities also are available. Training Training the model is nearly automatic. MQE systematically tests thousands of possible network connections, functions and parameters to find the combination that minimizes the forecast error.
Advanced options allow even more complex networks to be tested.
For example, you can tell MQE to build a second network that uses the forecast error from the first network as an input. The results MQE provides a series of reports detailing the best network and how well it works. You can view the network's structure, and under Windows NT you can click on a node to display its mathematical function. This table includes the average error, correlation between the predicted and actual output and other statistical measures. Graphical reports show histograms of error distribution, predicted vs. actual output and error vs. predicted output.