Input variables are multiplied by adjustable weights, summed and passed to threshold detectors called nodes. These nodes, like neurons in the brain, fire when the sum of their inputs exceeds some value. This procedure continues, with the weights continuously adjusted, until the last layer of nodes produces the desired forecast. Additional nodes or more complex functions must cause the historical errors to fall by more than the complexity penalty. Building from these fundamental improvements, MQE's sophisticated functionality should improve real-time forecasts in the hands of an experienced user.
Documentation is professional and complete, and extensive online help also is available.
Raw data can be read from an Ascii file, Excel spreadsheet or several popular database programs. Unfortunately, common futures formats such as CSI, MetaStock or Technical Tools cannot be read directly. Having to use other programs to export the data into an Ascii file before importing it into MQE is an inconvenient step. Once imported, MQE can transform the raw data to input into a network. 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.