Saturday, June 30, 2018

trends - Data Synchronization


I'm working on market trends. I have daily prices for 33 assets from different markets. I was wondering if there is a way to cancel the effects of different opening/closing times.


I have been told that a moving average over four days would be enough; I think a weekly moving average should improve many thing. As I observe a 50-day moving average to observe market trends, I don't really see the point in doing this first moving average.


Is there any literature about this topic? Are there simple solutions to cancel the effects of markets desynchronization?



Answer



Effects of non-contemporaneous trading (i.e. different closing times) for risk management are covered in this article (preprint,link to journal).


The conclusion is that a moving average process in the sense of time-series analysis can handle the resulting cross-autocorrelation. This means that in each time-step you have lagged correlations (e.g. Japan today to US yesterday) but only for lag $1$.


In case you want to use e.g. the Hodrick-Prescott-filter in a Kalman filter setting for fitting a trend, this model approach could improve the picture (I can not tell from experience but as an idea ...). For hints on the HP-filter you can start here.


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