stochosc
Stochastic oscillator
Description
calculates the stochastic oscillator.percentKnD
= stochosc(Data
)
adds optional name-value pair arguments. percentKnD
= stochosc(___,Name,Value
)
Examples
Load the file SimulatedStock.mat
, which provides a timetable (TMW
) for financial data for TMW stock.
load SimulatedStock.mat oscillator = stochosc(TMW,'NumPeriodsD',7,'NumPeriodsK',10,'Type','exponential'); plot(oscillator.Time,oscillator.FastPercentK,oscillator.Time,oscillator.FastPercentD) title('Stochastic Oscillator for TMW')
Input Arguments
Data with high, low, open, close information, specified as a matrix,
table, or timetable. For matrix input, Data
is an
M
-by-3
matrix of high, low, and
closing prices stored in the corresponding columns, respectively. Timetables
and tables with M
rows must contain variables named
'High'
, 'Low'
, and
'Close'
(case insensitive).
Data Types: double
| table
| timetable
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose
Name
in quotes.
Example: percentKnD =
stochosc(TMW,'NumPeriodsD',10,'NumPeriodsK',3,'Type','exponential')
Period difference for PercentK, specified as the comma-separated pair
consisting of 'NumPeriodsK'
and a scalar positive
integer.
Data Types: double
Length of moving average in periods for PercentD, specified as the
comma-separated pair consisting of 'NumPeriodsD'
and
a scalar positive integer.
Data Types: double
Moving average method for PercentD calculation, specified as the
comma-separated pair consisting of 'Type'
and a
character vector with a value of:
'exponential'
– Exponential moving average is a weighted moving average. Exponential moving averages reduce the lag by applying more weight to recent prices. For example, a 10 period exponential moving average weights the most recent price by 18.18%.'triangular'
– Triangular moving average is a double-smoothing of the data. The first simple moving average is calculated and then a second simple moving average is calculated on the first moving average with the same window size.
Data Types: char
Output Arguments
PercentK and PercentD, returned with the same number of rows
(M
) and type (matrix, table, or timetable) as the
input Data
.
More About
The stochastic oscillator is a momentum indicator used in technical analysis to measure the level of a security's closing price relative to its price range over a specific period.
The stochastic oscillator calculates the Fast PercentK (F%K), Fast PercentD (F%D), Slow PercentK (S%K), and Slow PercentD (S%D) from the series of high, low, and closing stock prices.
By default, the stochastic oscillator is based on 10-period difference for PercentK and a 3-period exponential moving average for PercentD.
The the stochastic oscillator is primarily used to identify overbought or oversold conditions in the market, helping traders make informed decisions about buying or selling assets.
References
[1] Achelis, S. B. Technical Analysis from A to Z. Second Edition. McGraw-Hill, 1995, pp. 268–271.
Version History
Introduced before R2006afints
object support for the Data
input
argument is removed.
The Data
input accepts negative prices.
MATLAB Command
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