The Real Edge Needs Distributional Skills
| Money Management
We need trends to survive. Both in life and trading.
But how to identify trends?
Below you can find my
trend indicator (yellow columns) which is quantifying the importance of
a trend component in a time series, i.e. the statistical significance of persistence.
The indicator is calculated with a VBA function (Microsoft Visual Basic for Applications) in Microsoft Excel.
The trend indicator is based on advanced statistics applied over different time frames, and can range from 0 for no importance to 1 if the series is pure trend.
- In sideways markets the mentioned trend statistic is erratic and inconsistent (as a result R squared is low).
- In trending markets the trend statistic is stable and consistent (as a result R squared is high).
|sideways market (stay out)||trending market (get in)|
We should have a method to distinguish between
- random drifts and trends
- noise and trends
- random events/fluctuations/trends and significant events/fluctuations/trends
- random variation and "true" variation
- deterministic trend and stochastic trend processes
- coincidence and significance
R squared (also often referred to as R², correlation, or coefficient of determination) is a goodness-of-fit parameter which measures how perfectly a curve resembles a straight line with no jiggles.
The higher the R squared, the smoother the curve and so the better/desirable the fit.
Rsquared can range from 0 for no importance (erratic) to 1 if the series is pure trend (stable).
A R2 value of about .33 indicates that 33% of the variance in the stock return can be explained by the data model.
The rest of the stock's variance is due to factors other than the data model.
Beware: R2 is a descriptive measure only for the goodness-of-fit, it is no measure for the quality of the estimation.
So this is a statistical method to identify trending and nontrending (mean reverting) financial time series.
All rights reserved.