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Zero lag data smoothers

By John Ehlers

No causal filter can ever predict the future. As a matter of fact, the laws of nature demand that filters all must have lag. However, if we assume steady state conditions – that is, no new disturbing events – there are techniques we can use to reduce the lag of these filters to nearly zero. It turns out that such filters are useful for technical analysts to smooth data, and perhaps create some fast-acting indicators. This is possible because the steady state assumptions are almost satisfied in the short run. These techniques are not applicable to longer moving averages because steady state conditions do not continue over a long time span. There are superior techniques for creating longer term averages, such as nonlinear filters1 or by removing undesired cycling components from a composite price waveform.



  • jaguar1637 2248 days ago

    Yes, you 're right

    The causality removes a little bit of accurency, but this is the price to pay.

    This is the first time you can fetch the inverse of the Hodrick Prescott on forex. so enjoy !