OPEN-SOURCE SCRIPT
Moving Covariance
Co-variance is a representation of the average percent data points deviate from there mean. A standard calculation of Co-variance uses One standard Deviation. Using the empirical rule, we can assume that about 68.26% of Data points lie in this range.
The advantage to plotting co variance as a time series is that it will show you how volatility of a trailing period changes. Therefore trend lines and other methods of analysis such as Fibonacci retracements could be applied in order to generate volatility targets.
For the purpose of this indicator I have the mean using a vwma derived from vwap. This makes this measurement of co-variance more sensitive to changes in volume, likewise are more representative a change in volatility, thus giving this indicator a "leading aspect".
The advantage to plotting co variance as a time series is that it will show you how volatility of a trailing period changes. Therefore trend lines and other methods of analysis such as Fibonacci retracements could be applied in order to generate volatility targets.
For the purpose of this indicator I have the mean using a vwma derived from vwap. This makes this measurement of co-variance more sensitive to changes in volume, likewise are more representative a change in volatility, thus giving this indicator a "leading aspect".
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