Eugene,
What about Mike's idea of taking the averaging coefficients used to
compute EMA's
and making them a function of volatility , variance, or standard
deviation of the 'value' ?
On 12/1/2010 11:25 AM, nonlinear5 wrote:
By experimentation, I was able to match EMA filters with the Kalman
filters:
http://groups.google.com/group/jbooktrader/web/EMAvsKalman.PNG
In this image,
"price" is 1-second price
"emafast" is the 60-second exponential average of price
"emaslow" is the 600-second exponential average of price
"kalmanfast" is the kalman filter of price with the measurement noise
set to 1
"kalmanslow" is the kalman filter of price with the measurement noise
set to 100
The good news is the EMA and Kalman filters closely match. The bad
news is that the Kalman filter is less intuitive to set up. In
particular, the error 100 works for the price, but to get comparable
smoothing for balance, the error should probably be in the single
digits. By contrast, using the EMA requires setting the period length,
and works regardless of the range of data.
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