When the market starts with an opening gap, a unique psychology becomes dominant in the mind of the traders. This psychology is most effective right at the open.but it fades out gradually by time. After the market opens other factors such as news and the chaos of trading kicks in more and more and it should wear off the initial "gap psychology". This is probably a general statement and applies to any kind of shock to any kind of stable system and it is a principle beyond market context. For example if a person is shocked by a good or bad news, the more time is passed, the effect of that shock is diminished.

Based on the above principle if my probability numbers are real, they should reflect the above behavior of response to a shock .

Therefore, if I can study the effect of time on net profit and show that there is an inverse relation between the two, this is an indication of the reliability of the advantage of the probability numbers based on opening gaps. This is specially the case, if the decline is gradual and without any bumps. This is very important data and it is beneficial to understand it even if you are not a gap trader. Here is the result of one study: This study is based on 12 years of data.

Minutes | PCT Resolved | PF |

10 | 24% | 10.58 |

15 | 40% | 3.48 |

20 | 47% | 2.76 |

30 | 57% | 2.16 |

40 | 67% | 1.68 |

50 | 72% | 1.65 |

60 | 76% | 1.62 |

70 | 79% | 1.55 |

80 | 82% | 1.51 |

100 | 84% | 1.49 |

120 | 87% | 1.43 |

150 | 89% | 1.40 |

PCT Resolved = PCT of the trades that either hit the target for profit or hit the stop and resulted in loss.

PF = Profit factor = Total Win $ divided by Total Loss $.

This is an amazing result. 24% of all trades are completed in the first 10 minutes with more than 10 times winning than losing. As the time passes, more and more trades come to end but less and less are profitable. By noon 89% of trades are completed with profits only 1.4 times the losses. Here is a chart of PF VS Time:

(Please note the minute axis is not quite linear but that does not change the idea that I am trying to cross.)

This graph strongly supports the significance of the probability numbers I come up with everyday. If the numbers were random or result of optimization and curve fitting, this graph would not have been completely downward. It would have had ups and downs. I am very amazed by this result and I hope you realize its significance.

I also took a different approach verifying the above result. In this approach I calculated the correlation between the time passed and the profit made. I found out that there is a statistically significant negative correlation. That means as the time passes, the profits are less (confirming the first approach). "

**statistically significant**" is defined as the state that the amount of evidence exceeds the "

**significance level"**at which point we can say it is unlikely that the event was random. In this approach I found out that the [negative] correlation between time passed and profit starts at a level below the "

**significance level"**at the open. It increases to a maximum of almost double the

**"**

**significance level"**after 40 minutes and then drops for the rest of the day. The profit factor for the trades that complete after 40 minutes and before noon is only 1.03 which is almost break even. The profit factor for the afternoon is 0.66, a huge money looser. So I pick that 40 minutes area (granularity is 5 minutes) as the time that the Gap statistics is starting to loose its advantage. This is the point that I will start to look to see if there is any other reason to stay in the trade or to get out. Otherwise its going to be a close to a 50/50 gambling trade soon.

Having that afternoon profit factor of 0.66 is tempting me to have another study to find out how much of this disadvantage comes from the morning actions vs afternoon actions. If the afternoon actions can be brought to spotlight, it may be possible to come up with a strategy to trade the reverse of morning gap in the afternoon.