Experiment 4

The next experiment in the series took place from 5/22 through 6/10.  The results of Experiment 3 were inconclusive, and this experiment set out to investigate additional capabilities of the EAs.

Up until now we were placing trades at a constant 0.1 lot size.  For Experiment 4 we used the EA’s predicted standard deviation envelopes to determine the lot size.  In order to accomplish this, we held the bet amount at a constant $100.  This means that when the SL (set at 1 SD) is larger, the lot size will be smaller and on the flip size, we’ll bet larger lots for a smaller SL.  This results in larger bets as the EAs have more confidence in a move.

We’re also increasing the PN entry trigger to 0.3 to try and reduce false entries.  In addition, we’re increasing the limit of open orders to 5,000, to be closed either by TP, SL or change of bias.  Other than that, the EAs are set up consistent with Experiment 3 as shown:

Where:

Mode A is the original operational mode previously studied.  The entry trigger is PN=0.3, and statistics are segregated by session and day of the week in addition to indicator states
Mode B is the same as A, but there is no day of week segregation.  Only the session data is kept separate
Mode C uses no segregation between day of week or session.  The only data bins are those defined by the indicator states.

Results:

 

The experiment results were statistically significant, and they indicate that the most profitable system based on the Q-metric measure was the MACD-A as previously defined.

In addition, the following scatterplot indicates that the most profitable results were obtained with the MACD-A system operating at a PN =[4.5,5.5]

This is further explored in the following analysis of average trade return versus opening PN:

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One Response to Experiment 4

  1. Pingback: Now broadcasting on Myfxbook « GatorNuke's Lab

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