Eugene, so once the optimal parameter has been found through optimization, it 
is 
manually added as the last parameter in 

addParam(FAST_ERROR, 0, 20, 1, 0); statement. Is that correct?



________________________________
From: Astor <[email protected]>
To: [email protected]
Sent: Tue, November 30, 2010 7:48:51 AM
Subject: Re: [JBookTrader] Re: Status of Kalman filter?


>The first three values, "min", "max", and "step" are used by the optimizers. 
>The 
>last value is the actual parameter value used when the strategy is >running in 
>the back testing, forward testing, and trading modes
 
The optimizer searches prameter space throughout the range between "min" and 
"max" in increment specified by "step" and finds the parameter value that 
maximizes some utility function. That is very clear and intuitive.
 
But, once the optimal parameter is found, why are you using that last, 
pre-specified "value" parameter for back testing, etc, instead of the newly 
found optimal parameter value? Sorry if I am being dense here. I am just 
confused.

 



________________________________
From: Eugene Kononov <[email protected]>
To: [email protected]
Sent: Tue, November 30, 2010 6:41:08 AM
Subject: Re: [JBookTrader] Re: Status of Kalman filter



In the constructor in TensionKalman, it has
> super(fastNoise, fastNoise); 
>should it not be:
>super(fastNoise, slowNoise); ?
>
Yes, that was a typo.


>addParam(FAST_ERROR, 0, 20, 1, 0);

>has 0 as the last parameter. I understand the significance
>of the first four parameters for a search algorithm.
> I am not sure what the last 
>parameter, value, signifies within the optimization algorithm context. 

The first three values, "min", "max", and "step" are used by the optimizers. 
The 
last value is the actual parameter value used when the strategy is running in 
the back testing, forward testing, and trading modes.



>The other area where the problem may lie is in the optimization step.
> I would expect the measurement_noise values to be somewhere between
> 0 and 1. For fast_error it may be 0.01 and for slow_error perhaps ten times 
>that, 0.1.

I didn't realize the error should scale between 0 and 1. I've made 
modifications 
in the attached version to reflect it.



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