Using Autocorrelation to Find Trading Signals
Autocorrelation is the variable’s linear correlation with its own lagged values. Insights may be gotten from autocorrelation that help understand the market’s properties. For example, persistent positive autocorrelation generally happens in trending markets while negative autocorrelation generally happens in ranging markets.
The Intuition of the Trading Signals
Correlation is the degree of linear association between two variables. It is a number bounded between -1.00 and 1.00 with the following interpretations:
- A value of 1.00 represents a perfectly positive correlation which means that the two variables move in the same direction all the time.
- A value of 0.70 represents a strong positive correlation which means that the two variables move mostly in the same direction.
- A value of 0.00 represents independent variables with no linear association. They have no relationship and does not necessarily move together.
- A value of -0.70 represents a strong negative correlation which means that the two variables move mostly in the opposite direction,
- A value of -1.00 represents a perfectly negative correlation which means that the two variables move in the opposite direction all the time.
It is worth noting that correlation does not imply causality and therefore we always have to be careful from the results.
Autocorrelation is the correlation of a variable (e.g. price) with its own lagged values from the past. It is generally calculated to understand the market regime. The indicator we are about to create uses autocorrelation and the concept of normality-reversion where high correlations are associated with a return to normality in a cyclical way.
If you plot an autocorrelation chart (of any period), you will notice that it moves from negative to positive territory in a cyclical way which may give some predictive abilities as to when the correlation should reverse.
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