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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,115 @@ | ||
| // Copyright (c) 2021-2023 Onur Cinar. | ||
| // The source code is provided under GNU AGPLv3 License. | ||
| // https://github.com/cinar/indicator | ||
|
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| package trend | ||
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| import "github.com/cinar/indicator/helper" | ||
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| const ( | ||
| // DefaultKdjMinMaxPeriod is the default period for moving min | ||
| // of low, and moving max of high. | ||
| DefaultKdjMinMaxPeriod = 9 | ||
|
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| // DefaultKdjSma1Period is the default period for SMA of RSV. | ||
| DefaultKdjSma1Period = 3 | ||
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| // DefaultKdjSma2Period is the default period for SMA of K. | ||
| DefaultKdjSma2Period = 3 | ||
| ) | ||
|
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| // Kdj represents the configuration parameters for calculating the | ||
| // KDJ, also known as the Random Index. KDJ is calculated similar | ||
| // to the Stochastic Oscillator with the difference of having the | ||
| // J line. It is used to analyze the trend and entry points. | ||
| // | ||
| // The K and D lines show if the asset is overbought when they | ||
| // crosses above 80%, and oversold when they crosses below | ||
| // 20%. The J line represents the divergence. | ||
| // | ||
| // RSV = ((Closing - Min(Low, rPeriod)) | ||
| // / (Max(High, rPeriod) - Min(Low, rPeriod))) * 100 | ||
| // | ||
| // K = Sma(RSV, kPeriod) | ||
| // D = Sma(K, dPeriod) | ||
| // J = (3 * K) - (2 * D) | ||
| // | ||
| // Example: | ||
| // | ||
| // kdj := NewKdj[float64]() | ||
| // values := kdj.Compute(highs, lows, closings) | ||
| type Kdj[T helper.Number] struct { | ||
| // MovingMax is the highest high. | ||
| MovingMax *MovingMax[T] | ||
|
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| // MovingMin is the lowest low. | ||
| MovingMin *MovingMin[T] | ||
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| // Sma1 is the SMA of RSV. | ||
| Sma1 *Sma[T] | ||
|
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| // Sma2 is the SMA of K. | ||
| Sma2 *Sma[T] | ||
| } | ||
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| // NewKdj function initializes a new Kdj instance with the default parameters | ||
| func NewKdj[T helper.Number]() *Kdj[T] { | ||
| kdj := &Kdj[T]{ | ||
| MovingMax: NewMovingMax[T](), | ||
| MovingMin: NewMovingMin[T](), | ||
| Sma1: NewSma[T](), | ||
| Sma2: NewSma[T](), | ||
| } | ||
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| kdj.MovingMax.Period = DefaultKdjMinMaxPeriod | ||
| kdj.MovingMin.Period = DefaultKdjMinMaxPeriod | ||
| kdj.Sma1.Period = DefaultKdjSma1Period | ||
| kdj.Sma2.Period = DefaultKdjSma2Period | ||
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| return kdj | ||
| } | ||
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| // Compute function takes a channel of numbers and computes the KDJ | ||
| // over the specified period. Returns K, D, J. | ||
| func (kdj *Kdj[T]) Compute(high, low, closing <-chan T) (<-chan T, <-chan T, <-chan T) { | ||
| highest := kdj.MovingMax.Compute(high) | ||
| lowests := helper.Duplicate( | ||
| kdj.MovingMin.Compute(low), | ||
| 2, | ||
| ) | ||
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| closing = helper.Skip(closing, kdj.MovingMax.Period-1) | ||
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| rsv := helper.MultiplyBy( | ||
| helper.Divide( | ||
| helper.Subtract(closing, lowests[0]), | ||
| helper.Subtract(highest, lowests[1]), | ||
| ), | ||
| 100, | ||
| ) | ||
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| ks := helper.Duplicate( | ||
| kdj.Sma1.Compute(rsv), | ||
| 3, | ||
| ) | ||
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| ds := helper.Duplicate( | ||
| kdj.Sma2.Compute(ks[0]), | ||
| 2, | ||
| ) | ||
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| ks[1] = helper.Skip(ks[1], kdj.Sma2.Period-1) | ||
| ks[2] = helper.Skip(ks[2], kdj.Sma2.Period-1) | ||
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| j := helper.Subtract( | ||
| helper.MultiplyBy(ks[1], 3), | ||
| helper.MultiplyBy(ds[0], 2), | ||
| ) | ||
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| return ks[2], ds[1], j | ||
| } | ||
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| // IdlePeriod is the initial period that KDJ won't yield any results. | ||
| func (kdj *Kdj[T]) IdlePeriod() int { | ||
| return kdj.MovingMax.Period + kdj.Sma1.Period + kdj.Sma2.Period - 3 | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| // Copyright (c) 2021-2023 Onur Cinar. | ||
| // The source code is provided under GNU AGPLv3 License. | ||
| // https://github.com/cinar/indicator | ||
|
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| package trend_test | ||
|
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| import ( | ||
| "testing" | ||
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| "github.com/cinar/indicator/helper" | ||
| "github.com/cinar/indicator/trend" | ||
| ) | ||
|
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| func TestKdj(t *testing.T) { | ||
| type Data struct { | ||
| High float64 | ||
| Low float64 | ||
| Close float64 | ||
| K float64 | ||
| D float64 | ||
| J float64 | ||
| } | ||
|
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| input, err := helper.ReadFromCsvFile[Data]("testdata/kdj.csv", true) | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
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| inputs := helper.Duplicate(input, 6) | ||
| high := helper.Map(inputs[0], func(d *Data) float64 { return d.High }) | ||
| low := helper.Map(inputs[1], func(d *Data) float64 { return d.Low }) | ||
| closing := helper.Map(inputs[2], func(d *Data) float64 { return d.Close }) | ||
| expectedK := helper.Map(inputs[3], func(d *Data) float64 { return d.K }) | ||
| expectedD := helper.Map(inputs[4], func(d *Data) float64 { return d.D }) | ||
| expectedJ := helper.Map(inputs[5], func(d *Data) float64 { return d.J }) | ||
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| kdj := trend.NewKdj[float64]() | ||
| actualK, actualD, actualJ := kdj.Compute(high, low, closing) | ||
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| actualK = helper.RoundDigits(actualK, 2) | ||
| actualK = helper.Shift(actualK, kdj.IdlePeriod(), 0) | ||
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| actualD = helper.RoundDigits(actualD, 2) | ||
| actualD = helper.Shift(actualD, kdj.IdlePeriod(), 0) | ||
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| actualJ = helper.RoundDigits(actualJ, 2) | ||
| actualJ = helper.Shift(actualJ, kdj.IdlePeriod(), 0) | ||
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| err = helper.CheckEquals(actualK, expectedK, actualD, expectedD, actualJ, expectedJ) | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
| } |
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