package indicator import ( "math" "git.qtrade.icu/lychiyu/qbtrade/pkg/datatype/floats" "git.qtrade.icu/lychiyu/qbtrade/pkg/types" ) // Refer: Commodity Channel Index // Refer URL: http://www.andrewshamlet.net/2017/07/08/python-tutorial-cci // with modification of ddof=0 to let standard deviation to be divided by N instead of N-1 // // CCI = (Typical Price - n-period SMA of TP) / (Constant x Mean Deviation) // // Typical Price (TP) = (High + Low + Close)/3 // // Constant = .015 // // The Commodity Channel Index (CCI) is a technical analysis indicator that is used to identify potential overbought or oversold conditions // in a security's price. It was originally developed for use in commodity markets, but can be applied to any security that has a sufficient // amount of price data. The CCI is calculated by taking the difference between the security's typical price (the average of its high, low, and // closing prices) and its moving average, and then dividing the result by the mean absolute deviation of the typical price. This resulting value // is then plotted as a line on the price chart, with values above +100 indicating overbought conditions and values below -100 indicating // oversold conditions. The CCI can be used by traders to identify potential entry and exit points for trades, or to confirm other technical // analysis signals. //go:generate callbackgen -type CCI type CCI struct { types.SeriesBase types.IntervalWindow Input floats.Slice TypicalPrice floats.Slice MA floats.Slice Values floats.Slice UpdateCallbacks []func(value float64) } func (inc *CCI) Update(value float64) { if len(inc.TypicalPrice) == 0 { inc.SeriesBase.Series = inc inc.TypicalPrice.Push(value) inc.Input.Push(value) return } else if len(inc.TypicalPrice) > MaxNumOfEWMA { inc.TypicalPrice = inc.TypicalPrice[MaxNumOfEWMATruncateSize-1:] inc.Input = inc.Input[MaxNumOfEWMATruncateSize-1:] } inc.Input.Push(value) tp := inc.TypicalPrice.Last(0) - inc.Input.Last(inc.Window) + value inc.TypicalPrice.Push(tp) if len(inc.Input) < inc.Window { return } ma := tp / float64(inc.Window) inc.MA.Push(ma) if len(inc.MA) > MaxNumOfEWMA { inc.MA = inc.MA[MaxNumOfEWMATruncateSize-1:] } md := 0. for i := 0; i < inc.Window; i++ { diff := inc.Input.Last(i) - ma md += diff * diff } md = math.Sqrt(md / float64(inc.Window)) cci := (value - ma) / (0.015 * md) inc.Values.Push(cci) if len(inc.Values) > MaxNumOfEWMA { inc.Values = inc.Values[MaxNumOfEWMATruncateSize-1:] } } func (inc *CCI) Last(i int) float64 { return inc.Values.Last(i) } func (inc *CCI) Index(i int) float64 { return inc.Last(i) } func (inc *CCI) Length() int { return len(inc.Values) } var _ types.SeriesExtend = &CCI{} func (inc *CCI) PushK(k types.KLine) { inc.Update(k.High.Add(k.Low).Add(k.Close).Div(three).Float64()) } func (inc *CCI) CalculateAndUpdate(allKLines []types.KLine) { if inc.TypicalPrice.Length() == 0 { for _, k := range allKLines { inc.PushK(k) inc.EmitUpdate(inc.Last(0)) } } else { k := allKLines[len(allKLines)-1] inc.PushK(k) inc.EmitUpdate(inc.Last(0)) } }