Logarithmic returns |
| Written by Mikhail Kopytine | |
| Saturday, 12 April 2008 11:46 | |
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For a price time series p(t), discrete with a time increment dt, a logarithmic return variable is x(t|dt) = log(p(t)/p(t-dt)) where dt is the time increment separating adjacent points in the time series. This variable has several advantages. It is additive: the return of the entire series is the sum of the returns comprising the series: x(tn|tn-t1) = x(t2|dt) + ... + x(tn|dt), dt = (tn-t1)/(n-1) Non-negativity of the price is "built in" -- especially useful when simulating artificial time series. When used in the correlation analysis, logarithmic returns (as do ordinary returns p(t)/p(t-dt)) eliminate one trivial source of non-stationarity of the correlation functions which is the possible long time-scale trend in the time dependence of the price. Long-term absolute level of the price is almost irrelevant to a forex trader, what matters is relative movements. Finally, the moments of the logarithmic returns may converge better than they would for the ordinary returns -- although, notably, Mandelbrot |
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| Last Updated ( Saturday, 25 October 2008 17:06 ) |