I'd like to thank DownRiverTrader for this idea.Unfortunately his thread is limited only to people that have TradeStation and are interested only in the EURUSD pair.
He also was unable (or unwilling?) to explain how the TradeStation study works exactly so I tried to figure it out on my own so that I can replicate it in Excel.
I decided to share my findings with all of you, in the hope that some of you who know more than me about maths and statistics can contribute.
I have limited knowledge of statistics, all of it due to a 4 month college course and I'm pretty sure I forgot most of it.However, with the things I still remember and with some freshing up by flipping through some statistics books, I was able to come up with this:
Price Distribution Analysis is about determining support and resistance levels in price.In it's scope, it is somewhat similar to MarketProfile, but does not account for volume.
If you know at least some basic data about MarketProfile, you know it's based on the normal distribution curve also known as the Bell Curve, because, well, it looks like the profile of a bell.
For the bell curve, approximatively 70% (I believe 68% in reality) of the values fall within 1 standard deviation away from the average ( mean - 1 standard deviation for the left half of the curve area, mean + 1 standard deviation for the right half of the curve area).
However, in real trading, normal distributions of prices rarely occur.Most of the times, price distributions are skewed to the left or right, which is actually a very good thing because we can see where most of the trading has taken place.
This is effectively because of what the price distributions represent: they are probability distributions.
Here's how to put all of this together:
Let's assume we have a specific price interval we want to analyze.For the purpose of this example, like DownRightTrader I will also use the current month and the EURUSD pair.
If we know the peak of the distribution curve, the value at which most of the trading has taken place, we can then accurately predict where 68% and 95% of the future closing prices for the EURUSD pair will be:
by calculating first the standard deviation of the whole price range, the mean of the price range, then subtracting 1 standard deviation from the mean and adding 1 std dev to the mean to get the 2 values delimiting the 68% probability area, and subtracting 2 std dev from the mean and adding 2 std dev to the mean to get the 2 values delimiting the 95% area.
This can be applied to any time interval, not just for a whole month.
I've attached the Excel spreadhsheet I used and you will find more specific explanations inside of it.
I also have to mention that you will need 1 minute data for the whole month.I got mine from the Alpari databank.
Hopefully I managed to explain things correctly.Please correct me if necessary or contribute to the spreadsheet if you have any ideas.
I'm sure there are a lot of things that can be improved.It does not come with all the bells and whistles of Tradestation but it very usable, even in it's current state.
edit: forgot to say that in this case, in the spreadsheet i used, the peak value of the curve represents the mode and is different than the mean(average), why exactly the 68% and 95% intervals are calculated in relation to the mean and not the actual peak - the mode, is something i haven't managed to understand yet; maybe the mean is used only for a normal distribution and in this case, since we do not have a normal distribution we should use the mode instead for our probabilistic calculations
hopefully someone with more knowledge than me can confirm or infirm this.
He also was unable (or unwilling?) to explain how the TradeStation study works exactly so I tried to figure it out on my own so that I can replicate it in Excel.
I decided to share my findings with all of you, in the hope that some of you who know more than me about maths and statistics can contribute.
I have limited knowledge of statistics, all of it due to a 4 month college course and I'm pretty sure I forgot most of it.However, with the things I still remember and with some freshing up by flipping through some statistics books, I was able to come up with this:
Price Distribution Analysis is about determining support and resistance levels in price.In it's scope, it is somewhat similar to MarketProfile, but does not account for volume.
If you know at least some basic data about MarketProfile, you know it's based on the normal distribution curve also known as the Bell Curve, because, well, it looks like the profile of a bell.
For the bell curve, approximatively 70% (I believe 68% in reality) of the values fall within 1 standard deviation away from the average ( mean - 1 standard deviation for the left half of the curve area, mean + 1 standard deviation for the right half of the curve area).
However, in real trading, normal distributions of prices rarely occur.Most of the times, price distributions are skewed to the left or right, which is actually a very good thing because we can see where most of the trading has taken place.
This is effectively because of what the price distributions represent: they are probability distributions.
Here's how to put all of this together:
Let's assume we have a specific price interval we want to analyze.For the purpose of this example, like DownRightTrader I will also use the current month and the EURUSD pair.
If we know the peak of the distribution curve, the value at which most of the trading has taken place, we can then accurately predict where 68% and 95% of the future closing prices for the EURUSD pair will be:
by calculating first the standard deviation of the whole price range, the mean of the price range, then subtracting 1 standard deviation from the mean and adding 1 std dev to the mean to get the 2 values delimiting the 68% probability area, and subtracting 2 std dev from the mean and adding 2 std dev to the mean to get the 2 values delimiting the 95% area.
This can be applied to any time interval, not just for a whole month.
I've attached the Excel spreadhsheet I used and you will find more specific explanations inside of it.
I also have to mention that you will need 1 minute data for the whole month.I got mine from the Alpari databank.
Hopefully I managed to explain things correctly.Please correct me if necessary or contribute to the spreadsheet if you have any ideas.
I'm sure there are a lot of things that can be improved.It does not come with all the bells and whistles of Tradestation but it very usable, even in it's current state.
edit: forgot to say that in this case, in the spreadsheet i used, the peak value of the curve represents the mode and is different than the mean(average), why exactly the 68% and 95% intervals are calculated in relation to the mean and not the actual peak - the mode, is something i haven't managed to understand yet; maybe the mean is used only for a normal distribution and in this case, since we do not have a normal distribution we should use the mode instead for our probabilistic calculations
hopefully someone with more knowledge than me can confirm or infirm this.
Attached File(s)
pricedistribution.xls
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