Al Sat Sistemi Time Series Forecast System Test

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Time Series Forecast Formula

· To: metastock@xxxxxxxxxxxxx
· Subject: Time Series Forecast Formula
· From: Robert Lambert <lambertb1@xxxxxxxxx>
· Date: Tue, 11 May 1999 07:07:39 -0700 (PDT)
· Reply-To: metastock@xxxxxxxxxxxxx
· Sender: owner-metastock@xxxxxxxxxxxxx

All:

I would like to know if the following formula (taken from Equis website) is actually the formula for the Time Series Forecast, or a modified formula which is simply using the Time Series Forecast as part of it’s computation.

I’m asking because I’d like to setup a Time Series Forecast of an indicator as a crossover trigger, rather than use a moving average. So, if I plug an indicator into the below referenced formula ( in place of the close value), will this particular formula actually give me the Time Series Forecast of the indicator, or will it give me something
modified?

Thanks in advance for feedback.

The End Point Moving Average was introduced in the October 95 issue of Technical Analysis of Stocks & Commodities in the article "The End Point Moving Average", by Patrick E. Lafferty. The exact formula for the End Point Moving average is as follows:

( 14 * Sum( Cum( 1 ) * C,14 ) - Sum( Cum( 1 ),14) * Sum( C,14) ) / (14
* Sum( Pwr( Cum( 1 ),2),14 ) - Pwr( Sum( Cum( 1 ),14 ),2 ) ) * Cum( 1 )
+ (Mov(C,14,S) - Mov( Cum( 1 ),14,S) * (14 * Sum( Cum( 1 ) * C,14) -
Sum( Cum( 1 ),14 ) * Sum( C,14) ) / (14 * Sum( Pwr( Cum( 1 ),2 ),14) -
Pwr( Sum( Cum( 1 ),14 ),2 ) ) )

The above formula plots the last value of a linear regression line of the previous 14 periods. The Time Series Forecast takes this value and the slope of the regression line to forecast the next day and then plots this forecasted price as today's value.


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Re: Time Series Forecast Formula

· To: <metastock@xxxxxxxxxxxxx>
· Subject: Re: Time Series Forecast Formula
· From: "Steve Karnish" <kernish@xxxxxxxxxxxx>
· Date: Tue, 11 May 1999 08:55:02 -0700
· Reply-To: metastock@xxxxxxxxxxxxx
· Sender: owner-metastock@xxxxxxxxxxxxx

Robert,

I can't answer your question, but here's a nice optimizer that uses TSF:​

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Time Series Forecast System Test

Enter long:
Cross(opt1,((CLOSE-Ref(TSF(C,opt3),-1))/CLOSE*100))
Close long:
Cross(((CLOSE-Ref(TSF(C,opt3),-1))/CLOSE*100),opt2)
Enter short:
Cross(((CLOSE-Ref(TSF(C,opt3),-1))/CLOSE*100),opt2)
Close short:
Cross(opt1,((CLOSE-Ref(TSF(C,opt3),-1))/CLOSE*100))

opt 1: -2 to 0 (with .1 step)
opt 2: zero to +2 (with .1 step)
opt 3: 2 to 8 (with 1 step)
Org. !!
opt 1: zero to -2 (with .1 step)​