Hi Mashume, can you help me to thinkscript the computation of the third central moment in the skewed distribution I am not educated in statistics, so I needed to read a few articles in Wikipedia. plus Jerry Perl article Trading with Market Statistics on Traders Laboratory. I had tried the formula (skew = vwap - vpoc /sd) but this may be better.

CM3 = sum(PROBi * (Pi - VWAP)^3),

where

i is going through all prices in range (i.e. all rows in Volume Distribution Function)

CM3 ... the 3rd Central Moment

PROBi = Vi / V ... ith price probability (Volume per ith price / Total Volume)

Pi ... ith price in the Vol. Dist. function

Then the Skew would be calculated as

Skew = CM3 / SD^3

I point of view is if we know the prediction of the price for the next hour and the skew, that will be a better edge trading the instrument. If the prediction is up and the skew is above vwap ( positive) then we has a bullish bias ....

Sorry my English is not very good looking ..........

As per Jerry Perl the distribution function itself tells you the trend bias and strength based on the strength of the skewThe VWAP/VPOC relationship determines the type of distribution (skewed/symmetric). Ignoring for the moment that as price moves around and volume trades that the VWAP and VPOC change and the distribution will probably change. Let's just say we were pretty sure that the type of distribution was not going to change for the next hour( Algorithmic Prediction). I think the distribution function itself tells you the trend bias and strength based on the strength of the skew, if Algorithmic Prediction is Up and the distribution had positive skew, you would go long every time the price action dropped below the VPOC and vice versa for negative skew. Similarly for no skew distribution, always trade toward the VWAP. This is the classical reversion to the mean theory.

CM3 = sum(PROBi * (Pi - VWAP)^3),

where

i is going through all prices in range (i.e. all rows in Volume Distribution Function)

CM3 ... the 3rd Central Moment

PROBi = Vi / V ... ith price probability (Volume per ith price / Total Volume)

Pi ... ith price in the Vol. Dist. function

Then the Skew would be calculated as

Skew = CM3 / SD^3

I point of view is if we know the prediction of the price for the next hour and the skew, that will be a better edge trading the instrument. If the prediction is up and the skew is above vwap ( positive) then we has a bullish bias ....

Sorry my English is not very good looking ..........

As per Jerry Perl the distribution function itself tells you the trend bias and strength based on the strength of the skewThe VWAP/VPOC relationship determines the type of distribution (skewed/symmetric). Ignoring for the moment that as price moves around and volume trades that the VWAP and VPOC change and the distribution will probably change. Let's just say we were pretty sure that the type of distribution was not going to change for the next hour( Algorithmic Prediction). I think the distribution function itself tells you the trend bias and strength based on the strength of the skew, if Algorithmic Prediction is Up and the distribution had positive skew, you would go long every time the price action dropped below the VPOC and vice versa for negative skew. Similarly for no skew distribution, always trade toward the VWAP. This is the classical reversion to the mean theory.

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