Stochastic.go

/*
Copyright 2018 www.gokhankocak.com gokhan.kocak@mail.ru

The MIT License
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"),
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WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/

/*
    Implements Stochastic Technical Analysis
    Stochastic Slow
*/

package stoploss

import(
  "math"
)

type Stochastic struct {
  DataSet Series
  DebugMode bool
}

func (DataSet Series) NewStochastic() *Stochastic {
  st := new(Stochastic)
  st.DataSet = DataSet
  return st
}

/*
%K = (Current Close - Lowest Low)/(Highest High - Lowest Low) * 100
%D = 3-day SMA of %K

Lowest Low = lowest low for the look-back period
Highest High = highest high for the look-back period
%K is multiplied by 100 to move the decimal point two places
*/

// https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/slow-stochastic
// 0 1 2 3 4 5 6 7 8 9 10 11 12
// Period = 5
// PeriodK = 3
// PeriodD = 2

func (st *Stochastic) Slow( Period int, PeriodK int, PeriodD int ) (float64, float64) {

	var Highest float64
	var Lowest float64
	var MaxKD int
	var Kpercents Series
	var Dpercent float64

  LastIndex := len(st.DataSet) - 1
	//log.Printf("StochasticSlow: LastIndex %d Period %d PeriodK %d PeriodD %d\n", LastIndex, Period, PeriodK, PeriodD)

	MaxKD = int(math.Max(float64(PeriodK), float64(PeriodD)))

	if LastIndex - Period - MaxKD - 1 < 0 { return math.NaN(), math.NaN() }
	if Period < PeriodK || Period < PeriodD { return math.NaN(), math.NaN() }

	Kpercents = make(Series, MaxKD)

	for c := 0; c < MaxKD; c++ {

		Start := LastIndex - Period - MaxKD + 2 + c
		Highest = math.SmallestNonzeroFloat64
		Lowest  = math.MaxFloat64

		for _, d := range st.DataSet[Start:Start + Period] {

			//log.Printf("StochasticSlow: c %d Start %d k %d\n", c, Start, k)

			Highest = math.Max(Highest, d.High)
			Lowest  = math.Min(Lowest, d.Low)
		}

		Kpercents[c].Close = 100.0 * (st.DataSet[Start + Period - 1].Close - Lowest) / (Highest - Lowest)
	}

	//log.Printf("StochasticSlow: Kpercents %v\n", Kpercents)

	Dpercent = Kpercents.NewMovingAverage().SMA(PeriodD)

	return Kpercents[len(Kpercents) - 1].Close, Dpercent
}