DataSplit

Splits the simulation in a training period (given in percent) and a following test period. F.i. when set at 60, the training period has a length of 60% and the test period has a length of 40%. This works with or without WFO and ensures that the test always uses out-of-sample data.

Typical range:

50..90 (default = 0 = no separate training / test period).

Type:

int

DataSkip

Gives the number of bars to skip with the SKIP1...SKIP3 flags (default: number of bars corresponding to one week).

Type:

int 

DataHorizon

Prevents trading for the given number of bars at the begin of a WFO test phase (default: 0). This avoids test bias by future-peeking training f.i. with a machine learning algorithm. If training uses prices from up to 5 bars in the future, set DataHorizon to 5.

Type:

int

DataSlope

Applies a moving weight factor to the trade results in the training period. F.i. at DataSlope = 2 the last trades have twice the weight than the first trades. This generates parameters that are better fitted to the most recent part of the price curve, and thus takes care of slow market changes.

Typical range:

1..3 (default = 1 = equal weight for all trades)

Type:

var
 

Remarks:

Example:

function run()
{
  DataSlope = 2;
  DataSplit = 80;
  NumWFOCycles = -10; // anchored WFO
  ...
}

See also:

Mode, WFO

 

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