Hi all:
I continue with my explanation of Level2 system implementation. All this dates are not real, its an aproximate.
Imagine we have a data base around 6000 1h bars that it is 1 year ago or 250 trading days.
Now you think that there is an average of two RB daily. Then we have 500 RB at period time.
Normally when a RB is formed price hit limits range several times until range is broken.
Now the question is to determine the average number of times that price touch this limits at every 1h RB and build a percentage classification of this dates. For example.
Price touch 1 time limits and then breakout……… 5% of 1h RB.
Price touch 2 times limits and then breakout…… 5% 1h RB.
Price touch 3 times limits and then breakout……. 10% 1h RB.
Price touch 4 times limits and then breakout……. 20% 1h RB.
Price touch 5 times limits and then breakout…… 35% 1h RB.
Price touch 6 times limits and then breakout….. 30% 1h RB.
Price touch 7 times or more limits and then breakout……. 5% 1h RB.
With this classification we can elaborate a system that enter buy and sell orders when price hit range limits at consonance with percentage data base.
If we can find a percentage range thats give us a matematic success probability we can enter buy and sell orders to capture profit when price is ranging leaving open the last order to capture trend.
Think in it please. I continue.
Regards.
I continue with my explanation of Level2 system implementation. All this dates are not real, its an aproximate.
Imagine we have a data base around 6000 1h bars that it is 1 year ago or 250 trading days.
Now you think that there is an average of two RB daily. Then we have 500 RB at period time.
Normally when a RB is formed price hit limits range several times until range is broken.
Now the question is to determine the average number of times that price touch this limits at every 1h RB and build a percentage classification of this dates. For example.
Price touch 1 time limits and then breakout……… 5% of 1h RB.
Price touch 2 times limits and then breakout…… 5% 1h RB.
Price touch 3 times limits and then breakout……. 10% 1h RB.
Price touch 4 times limits and then breakout……. 20% 1h RB.
Price touch 5 times limits and then breakout…… 35% 1h RB.
Price touch 6 times limits and then breakout….. 30% 1h RB.
Price touch 7 times or more limits and then breakout……. 5% 1h RB.
With this classification we can elaborate a system that enter buy and sell orders when price hit range limits at consonance with percentage data base.
If we can find a percentage range thats give us a matematic success probability we can enter buy and sell orders to capture profit when price is ranging leaving open the last order to capture trend.
Think in it please. I continue.
Regards.
That which you give to others, life will return it in spades