egutierrez
113c6dfd71
11 funciones puras con implementación real: SMA, EMA, RSI, BollingerBands, VWAP, LogReturn, AnnualizedVolatility, SharpeRatio, MaxDrawdown, NormalizeOHLCV, TickToOHLCV 4 funciones impuras (stubs): FetchOHLCV, StreamTicks, WriteOHLCVToParquet, LoadOHLCVFromDuckDB Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
48 lines
1.1 KiB
Go
48 lines
1.1 KiB
Go
package finance
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// RSI calcula el Relative Strength Index.
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// Usa el metodo de suavizado de Wilder (EMA con alpha = 1/period).
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// Los primeros period elementos del resultado son 0.
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func RSI(data []float64, period int) []float64 {
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n := len(data)
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result := make([]float64, n)
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if period <= 0 || n < period+1 {
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return result
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}
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var gainSum, lossSum float64
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for i := 1; i <= period; i++ {
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change := data[i] - data[i-1]
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if change > 0 {
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gainSum += change
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} else {
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lossSum -= change
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}
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}
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avgGain := gainSum / float64(period)
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avgLoss := lossSum / float64(period)
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if avgLoss == 0 {
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result[period] = 100
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} else {
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rs := avgGain / avgLoss
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result[period] = 100 - 100/(1+rs)
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}
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for i := period + 1; i < n; i++ {
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change := data[i] - data[i-1]
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var gain, loss float64
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if change > 0 {
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gain = change
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} else {
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loss = -change
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}
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avgGain = (avgGain*float64(period-1) + gain) / float64(period)
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avgLoss = (avgLoss*float64(period-1) + loss) / float64(period)
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if avgLoss == 0 {
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result[i] = 100
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} else {
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rs := avgGain / avgLoss
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result[i] = 100 - 100/(1+rs)
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}
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}
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return result
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}
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