Return value of the SAR parabolic indicator.
Syntax:
|
1 |
SAR[At,St,Lim] |
Calculation :
SAR points are calculated from both prices and time.
The parameters are the initial acceleration factor (typically 0.02), the addition factor (typ. 0.02) and the acceleration factor limit (typ. 0.2).
Return value of the smoothed SAR parabolic indicator.
Syntax:
|
1 |
SARatdmf[At,St,Lim] |
Example:
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1 2 3 4 5 6 7 8 9 |
i1 = SARatdmf[0.02,0.02,0.2] if(close[1]>i1[1] AND close<i1) THEN signal = -1 ELSE signal = 0 ENDIF RETURN signal |
SenkouSpanA
ProRealTime v11Returns the SenkouSpanA value (component of the “ichimoku kinko hyo” indicator), part of the cloud.
Syntax:
|
1 |
SenkouSpanA[9,26,52] |
SenkouSpanA is an average of the Tenkan and Kijun line projected 26 periods forward, in the form of extension. It is therefore traced beyond the current price.
SenkouSpanB ProRealTime v11Returns the SenkouSpanB value (component of the “ichimoku kinko hyo” indicator), part of the cloud.
Syntax:
|
1 |
SenkouSpanB[9,26,52] |
SenkouSpanB is an average of the highest and the lowest of the last 52 periods, projected 26 periods forward, in the form of extension. It is therefore drawn beyond the current price.
Return the value of the Stochastic Momentum Index Indicator for the selected price.
Syntax:
|
1 |
SMI[N,SS,DS)(price) |
This indicator represents the position of the close relative to the median point whereas the traditionnal stochastic represents the position of the close relative to the highest and lowest points. We use a double smoothing with an exponential moving average so that the signals are more consistent.
The SMI also gives good divergence signals.
SmoothedRepulse ProRealTime v11Returns the Smoothed Repulse indicator value.
Syntax:
|
1 |
SmoothedRepulse[period](price) |
Where:
Return value of the smoothed stochastic oscillator for the selected price. Also known as the slow stochastic.
Syntax:
|
1 |
SmoothedStochastic[N,K](price) |
Calculation :
The calculation of the %D is similar to the stochastic rapid but with the smoothing the signals are more regular.
%D(y) = 100 * (H(y)/B(y))
with :
H(y) : sum of C – PH(n) on X days ago
B(y) : sum of PH(n) – PB(n) on X days ago
C days : today’s close
PB(n) day : lowest on n period
PH(n) : Highest on n period
n : period
Statistical function “standard deviation” of a time series N of selected price.
Syntax:
|
1 |
STD[N](price) |
Calculation :
STD = SQUAREROOT[(summation(from d = 1 to n)(Close-Moving average on n days)²]
Statistical function “standard error” of time series of N periods for the selected price.
Syntax:
|
1 |
STE[N](price) |
Interpretation :
This indicator allows us to know if prices are close to the linear regression line or not. The closer they are, the more the trend is reliable.
On the other hand, the further away they are the less reliable is the trend.
This indicator is often used in relation to R² so as to interpret trend reversales more easily.
We can observe that when the two indicators start from opposite levels and converge, there is usually a change of trend taking place – either a new phase of consolidation and/or possibly a phase of reversal.
Example:
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1 2 3 4 |
myseries = range statisticalerror = STE[10](myseries) RETURN statisticalerror |
Return value of the Stochastic oscillator %K line over N periods of the selected price serie.
Syntax:
|
1 |
Stochastic[N,K](price1,price2,price3) |
Calculation :
The first parameter is the number of days used to calculate %K, the second is the number of days to be considered for the moving average of %K (generally 1 for Fast Stochastic and 3 or 5 for Slow Stochastic), the third is the number of days to be considered for the moving average of %D.
“price1”, “price2” and “price3” are optional. By default the stochastic will be calculated with Close on the High/Low scale (same as the internal platform indicator). But you can adjust it with any other price or data series (e.g. Stochastic[N,K](close,close,close) or Stochastic[N,K](var1,var2,var3) )
