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Stochastic indicator (#300)
# Describe Request Stochastic indicator is added. # Change Type New indicator. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added a new Stochastic indicator to the trend indicators collection with configurable period settings and dual output values (%K and %D). * **Documentation** * Updated README with comprehensive documentation for the new Stochastic indicator and its configuration options. * **Tests** * Added unit tests for the Stochastic indicator with validation against test data. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
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‎README.md‎

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@@ -48,6 +48,7 @@ The following list of indicators are currently supported by this package:
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- [Moving Sum](trend/README.md#type-movingsum)
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- Parabolic SAR
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- [Random Index (KDJ)](trend/README.md#type-kdj)
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- [Stochastic](trend/README.md#type-stochastic)
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- [Rolling Moving Average (RMA)](trend/README.md#type-rma)
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- [Simple Moving Average (SMA)](trend/README.md#type-sma)
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- [Since Change](helper/README.md#func-since)

‎trend/README.md‎

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- [func \(s \*Smma\[T\]\) Compute\(c \<\-chan T\) \<\-chan T](<#Smma[T].Compute>)
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- [func \(s \*Smma\[T\]\) IdlePeriod\(\) int](<#Smma[T].IdlePeriod>)
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- [func \(s \*Smma\[T\]\) String\(\) string](<#Smma[T].String>)
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- [type Stochastic](<#Stochastic>)
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- [func NewStochastic\[T helper.Number\]\(\) \*Stochastic\[T\]](<#NewStochastic>)
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- [func NewStochasticWithPeriod\[T helper.Number\]\(period int\) \*Stochastic\[T\]](<#NewStochasticWithPeriod>)
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- [func \(s \*Stochastic\[T\]\) Compute\(values \<\-chan T\) \(\<\-chan T, \<\-chan T\)](<#Stochastic[T].Compute>)
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- [func \(s \*Stochastic\[T\]\) IdlePeriod\(\) int](<#Stochastic[T].IdlePeriod>)
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- [type Tema](<#Tema>)
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- [func NewTema\[T helper.Number\]\(\) \*Tema\[T\]](<#NewTema>)
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- [func \(t \*Tema\[T\]\) Compute\(c \<\-chan T\) \<\-chan T](<#Tema[T].Compute>)
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)
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```
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<a name="DefaultStochasticPeriod"></a>
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```go
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const (
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// DefaultStochasticPeriod is the default period for the Stochastic indicator.
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DefaultStochasticPeriod = 10
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// DefaultStochasticSmaPeriod is the default period for the SMA of %K.
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DefaultStochasticSmaPeriod = 3
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)
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```
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<a name="DefaultTsiFirstSmoothingPeriod"></a>
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```go
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String is the string representation of the SMMA.
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<a name="Stochastic"></a>
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## type [Stochastic](<https://github.com/cinar/indicator/blob/master/trend/stochastic.go#L30-L36>)
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Stochastic represents the configuration parameters for calculating the Stochastic indicator on a single input series. This is different from the Stochastic Oscillator which operates on high, low, and close. This generic version is useful for applying stochastic calculation to any series, such as MACD values in the Schaff Trend Cycle \(STC\).
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```
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K = (Value - Min(Value, period)) / (Max(Value, period) - Min(Value, period)) * 100
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D = SMA(K, dPeriod)
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```
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Example:
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```
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s := trend.NewStochastic[float64]()
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k, d := s.Compute(values)
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```
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```go
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type Stochastic[T helper.Number] struct {
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// Period is the period for the min/max calculation.
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Period int
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// Sma is the SMA instance for %D calculation.
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Sma *Sma[T]
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}
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```
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<a name="NewStochastic"></a>
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### func [NewStochastic](<https://github.com/cinar/indicator/blob/master/trend/stochastic.go#L39>)
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```go
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func NewStochastic[T helper.Number]() *Stochastic[T]
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```
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NewStochastic function initializes a new Stochastic instance with the default parameters.
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<a name="NewStochasticWithPeriod"></a>
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### func [NewStochasticWithPeriod](<https://github.com/cinar/indicator/blob/master/trend/stochastic.go#L44>)
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```go
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func NewStochasticWithPeriod[T helper.Number](period int) *Stochastic[T]
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```
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NewStochasticWithPeriod function initializes a new Stochastic instance with the given period.
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<a name="Stochastic[T].Compute"></a>
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### func \(\*Stochastic\[T\]\) [Compute](<https://github.com/cinar/indicator/blob/master/trend/stochastic.go#L53>)
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```go
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func (s *Stochastic[T]) Compute(values <-chan T) (<-chan T, <-chan T)
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```
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Compute function takes a channel of numbers and computes the Stochastic indicator. Returns %K and %D.
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<a name="Stochastic[T].IdlePeriod"></a>
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### func \(\*Stochastic\[T\]\) [IdlePeriod](<https://github.com/cinar/indicator/blob/master/trend/stochastic.go#L87>)
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```go
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func (s *Stochastic[T]) IdlePeriod() int
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```
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IdlePeriod is the initial period that Stochastic won't yield any results.
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<a name="Tema"></a>
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## type [Tema](<https://github.com/cinar/indicator/blob/master/trend/tema.go#L18-L22>)
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‎trend/stochastic.go‎

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// Copyright (c) 2021-2026 Onur Cinar.
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// The source code is provided under GNU AGPLv3 License.
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// https://github.com/cinar/indicator
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package trend
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import "github.com/cinar/indicator/v2/helper"
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const (
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// DefaultStochasticPeriod is the default period for the Stochastic indicator.
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DefaultStochasticPeriod = 10
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// DefaultStochasticSmaPeriod is the default period for the SMA of %K.
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DefaultStochasticSmaPeriod = 3
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)
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// Stochastic represents the configuration parameters for calculating
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// the Stochastic indicator on a single input series. This is different
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// from the Stochastic Oscillator which operates on high, low, and close.
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// This generic version is useful for applying stochastic calculation to
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// any series, such as MACD values in the Schaff Trend Cycle (STC).
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//
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// K = (Value - Min(Value, period)) / (Max(Value, period) - Min(Value, period)) * 100
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// D = SMA(K, dPeriod)
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//
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// Example:
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//
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// s := trend.NewStochastic[float64]()
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// k, d := s.Compute(values)
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type Stochastic[T helper.Number] struct {
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// Period is the period for the min/max calculation.
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Period int
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// Sma is the SMA instance for %D calculation.
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Sma *Sma[T]
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}
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// NewStochastic function initializes a new Stochastic instance with the default parameters.
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func NewStochastic[T helper.Number]() *Stochastic[T] {
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return NewStochasticWithPeriod[T](DefaultStochasticPeriod)
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}
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// NewStochasticWithPeriod function initializes a new Stochastic instance with the given period.
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func NewStochasticWithPeriod[T helper.Number](period int) *Stochastic[T] {
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return &Stochastic[T]{
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Period: period,
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Sma: NewSmaWithPeriod[T](DefaultStochasticSmaPeriod),
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}
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}
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// Compute function takes a channel of numbers and computes the Stochastic indicator.
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// Returns %K and %D.
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func (s *Stochastic[T]) Compute(values <-chan T) (<-chan T, <-chan T) {
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movingMin := NewMovingMinWithPeriod[T](s.Period)
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movingMax := NewMovingMaxWithPeriod[T](s.Period)
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values = helper.Buffered(values, s.Period)
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inputs := helper.Duplicate(values, 3)
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lowestSplice := helper.Duplicate(
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movingMin.Compute(inputs[0]),
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2,
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)
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highest := movingMax.Compute(inputs[1])
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skipped := helper.Skip(inputs[2], movingMin.IdlePeriod())
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kSplice := helper.Duplicate(
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helper.MultiplyBy(
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helper.Divide(
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helper.Subtract(skipped, lowestSplice[0]),
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helper.Subtract(highest, lowestSplice[1]),
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),
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100,
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),
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2,
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)
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d := s.Sma.Compute(kSplice[0])
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kSplice[1] = helper.Skip(kSplice[1], s.Sma.IdlePeriod())
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return kSplice[1], d
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}
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// IdlePeriod is the initial period that Stochastic won't yield any results.
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func (s *Stochastic[T]) IdlePeriod() int {
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return s.Period + s.Sma.Period - 2
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}

‎trend/stochastic_test.go‎

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// Copyright (c) 2021-2026 Onur Cinar.
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// The source code is provided under GNU AGPLv3 License.
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// https://github.com/cinar/indicator
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package trend_test
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import (
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"testing"
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"github.com/cinar/indicator/v2/helper"
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"github.com/cinar/indicator/v2/trend"
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)
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func TestStochastic(t *testing.T) {
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type Data struct {
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Value float64
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K float64
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D float64
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}
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input, err := helper.ReadFromCsvFile[Data]("testdata/stochastic.csv")
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if err != nil {
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t.Fatal(err)
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}
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inputs := helper.Duplicate(input, 3)
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values := helper.Map(inputs[0], func(d *Data) float64 { return d.Value })
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expectedK := helper.Map(inputs[1], func(d *Data) float64 { return d.K })
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expectedD := helper.Map(inputs[2], func(d *Data) float64 { return d.D })
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s := trend.NewStochastic[float64]()
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actualK, actualD := s.Compute(values)
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actualK = helper.RoundDigits(actualK, 2)
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actualD = helper.RoundDigits(actualD, 2)
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expectedK = helper.Skip(expectedK, s.IdlePeriod())
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expectedD = helper.Skip(expectedD, s.IdlePeriod())
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err = helper.CheckEquals(actualK, expectedK, actualD, expectedD)
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if err != nil {
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t.Fatal(err)
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}
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}

‎trend/testdata/stochastic.csv‎

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Value,K,D
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111.00,100.00,100.00
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109.00,75.00,91.67
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112.00,100.00,91.67
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113.00,100.00,91.67
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115.00,100.00,100.00
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114.00,87.50,95.83
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116.00,100.00,95.83
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118.00,100.00,95.83
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117.00,88.89,96.30
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119.00,100.00,96.30
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120.00,100.00,96.30
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118.00,75.00,91.67
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121.00,100.00,91.67
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122.00,100.00,91.67
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120.00,75.00,91.67
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123.00,100.00,91.67
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125.00,100.00,91.67
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124.00,87.50,95.83
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126.00,100.00,95.83

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