Hi all,
I believe the significance of Nuke's method is that it uses a Bayesian conditional probability in predicting whether a bar is going up or going down, based on the 90th percentile LSD SLD:
Let's say you are betting long. If the bar has gone up beyond open+LSD90 then the probability that this bar is an up bar is 90%. That's because you have surpassed 90% of the times that the bar is a downward bar (i.e., most downward bars will have the short distance going upward).
So then once it surpassed open+LSD90 (your limit buy price), you can then impose the SLD90 as your take profit point. That point is guaranteed to be reached 90% of the time IF you are in an up bar.
So the overall rough probability of being in profit is 90% x 90% = about 81%.
Of course there is a chance that once you have surpassed the LSD90, it could swing back down to the open and in fact it can go down to the open - LSD90. That will probably screw up the stats. I believe this is where Nuke goes into tick data to find out how often that happens and perhaps adjusts the limit price upward to reduce that probability. I can see however that you still may retain some statistical edge even with this momentary swing down probability because it is likely rare (I need to check) that such an extreme swing down occurs once you've hit the price open+LSD90.
The trouble comes in when LSD > SLD. That means that the distribution of SDs overlaps the distribution of LDs, which means that you won't be able to discriminate up or down bars based on the LSD or SLD.
This is where I have lost Nuke's logic. He says you can go ahead and move over the SDs that are greater than the SLD to the LD column. I think he explained it once but I still don't understand how that changes the probabilities. He says something like if the bar is so volatile such that the LSD is > than the SLD, then you could have bet either way and made a profit or loss. I believe he might have some idea in here, but I am still not following that logic.
If anyone can explain this logic, I would greatly appreciate it.
I believe the significance of Nuke's method is that it uses a Bayesian conditional probability in predicting whether a bar is going up or going down, based on the 90th percentile LSD SLD:
Let's say you are betting long. If the bar has gone up beyond open+LSD90 then the probability that this bar is an up bar is 90%. That's because you have surpassed 90% of the times that the bar is a downward bar (i.e., most downward bars will have the short distance going upward).
So then once it surpassed open+LSD90 (your limit buy price), you can then impose the SLD90 as your take profit point. That point is guaranteed to be reached 90% of the time IF you are in an up bar.
So the overall rough probability of being in profit is 90% x 90% = about 81%.
Of course there is a chance that once you have surpassed the LSD90, it could swing back down to the open and in fact it can go down to the open - LSD90. That will probably screw up the stats. I believe this is where Nuke goes into tick data to find out how often that happens and perhaps adjusts the limit price upward to reduce that probability. I can see however that you still may retain some statistical edge even with this momentary swing down probability because it is likely rare (I need to check) that such an extreme swing down occurs once you've hit the price open+LSD90.
The trouble comes in when LSD > SLD. That means that the distribution of SDs overlaps the distribution of LDs, which means that you won't be able to discriminate up or down bars based on the LSD or SLD.
This is where I have lost Nuke's logic. He says you can go ahead and move over the SDs that are greater than the SLD to the LD column. I think he explained it once but I still don't understand how that changes the probabilities. He says something like if the bar is so volatile such that the LSD is > than the SLD, then you could have bet either way and made a profit or loss. I believe he might have some idea in here, but I am still not following that logic.
If anyone can explain this logic, I would greatly appreciate it.
