The author of this indicator is Veronique Valcu. The z-score (z) for a data
item x measures the distance (in standard deviations StdDev) and direction
of the item from its mean (U):
z = (x-StdDev) / U
A value of zero indicates that the data item x is equal to the mean U, while
positive or negative values show that the data item is above (x>U) or below
(x Values of +2 and -2 show that the data item is two standard deviations
above or below the chosen mean, respectively, and over 95.5% of all data
items are contained within these two horizontal references (see Figure 1).
We substitute x with the closing price C, the mean U with simple moving
average (SMA) of n periods (n), and StdDev with the standard deviation of
closing prices for n periods, the above formula becomes:
Z_score = (C - SMA(n)) / StdDev(C,n)
The z-score indicator is not new, but its use can be seen as a supplement to
Bollinger bands. It offers a simple way to assess the position of the price
vis-a-vis its resistance and support levels expressed by the Bollinger Bands.
In addition, crossings of z-score averages may signal the start or the end of
a tradable trend. Traders may take a step further and look for stronger signals
by identifying common crossing points of z-score, its average, and average of average.
item x measures the distance (in standard deviations StdDev) and direction
of the item from its mean (U):
z = (x-StdDev) / U
A value of zero indicates that the data item x is equal to the mean U, while
positive or negative values show that the data item is above (x>U) or below
(x Values of +2 and -2 show that the data item is two standard deviations
above or below the chosen mean, respectively, and over 95.5% of all data
items are contained within these two horizontal references (see Figure 1).
We substitute x with the closing price C, the mean U with simple moving
average (SMA) of n periods (n), and StdDev with the standard deviation of
closing prices for n periods, the above formula becomes:
Z_score = (C - SMA(n)) / StdDev(C,n)
The z-score indicator is not new, but its use can be seen as a supplement to
Bollinger bands. It offers a simple way to assess the position of the price
vis-a-vis its resistance and support levels expressed by the Bollinger Bands.
In addition, crossings of z-score averages may signal the start or the end of
a tradable trend. Traders may take a step further and look for stronger signals
by identifying common crossing points of z-score, its average, and average of average.
//////////////////////////////////////////////////////////// // Copyright by HPotter v1.0 07/07/2014 // The author of this indicator is Veronique Valcu. The z-score (z) for a data // item x measures the distance (in standard deviations StdDev) and direction // of the item from its mean (U): // z = (x-StdDev) / U // A value of zero indicates that the data item x is equal to the mean U, while // positive or negative values show that the data item is above (x>U) or below // (x Values of +2 and -2 show that the data item is two standard deviations // above or below the chosen mean, respectively, and over 95.5% of all data // items are contained within these two horizontal references (see Figure 1). // We substitute x with the closing price C, the mean U with simple moving // average (SMA) of n periods (n), and StdDev with the standard deviation of // closing prices for n periods, the above formula becomes: // Z_score = (C - SMA(n)) / StdDev(C,n) // The z-score indicator is not new, but its use can be seen as a supplement to // Bollinger bands. It offers a simple way to assess the position of the price // vis-a-vis its resistance and support levels expressed by the Bollinger Bands. // In addition, crossings of z-score averages may signal the start or the end of // a tradable trend. Traders may take a step further and look for stronger signals // by identifying common crossing points of z-score, its average, and average of average. //////////////////////////////////////////////////////////// study(title="Z-Score", shorttitle="Z-Score") Period = input(20, minval=1) hline(0, color=purple, linestyle=line) xStdDev = stdev(close, Period) xMA = sma(close, Period) nRes = (close - xMA) / xStdDev plot(nRes, color=blue, title="Z-Score")