I have a model specifying a cointegration relationship on a number of transaction-level timeseries.
I would like to specify entry and exit points for trades where these points ideally would be just before the turning points of the time series (bottoms for exit and tops for entry). The issue I am having is that the timeseries itself are very short -- usually around 1600 observations/seconds. Thus the usual +- 1/2 standard deviation entry points do not work because I do not know the standard deviation reliably before the window of opportunity is over.
I see a number of solutions but perhaps there's better ones in the literature?
- Rolling standard deviation: very unreliable at the beginning, and losing out on trading opportunities before having reliable results
- Rolling quantile: same problem like above
- Fixed level entry/exit points: could be very wrong since the series vary in magnitude
- High watermark entry/exit points
Here are some example series. You might notice the distortions at the beginning of the series, this is because I'm removing a quadratic trend.