Issue 68 (#71)

* Adding rolling moving average (RMA) indicator.

* Adding RMA to index.

* Changing RSI to use RMA indicator.

Fixes #68.

README.md

@@ -29,6 +29,7 @@ The following list of indicators are currently supported by this package:
 - [Parabolic SAR](trend_indicators.md#parabolic-sar)
 - [Qstick](trend_indicators.md#qstick)
 - [Random Index (KDJ)](trend_indicators.md#random-index-kdj)
+- [Rolling Moving Average (RMA)](trend_indicators.md#rolling-moving-average-rma)
 - [Simple Moving Average (SMA)](trend_indicators.md#simple-moving-average-sma)
 - [Since Change](trend_indicators.md#since-change)
 - [Triple Exponential Moving Average (TEMA)](trend_indicators.md#triple-exponential-moving-average-tema)

momentum_indicators.go

@@ -90,8 +90,8 @@ func Rsi(closing []float64) ([]float64, []float64) {
 		}
 	}
 
-	meanGains := Sma(14, gains)
-	meanLosses := Sma(14, losses)
+	meanGains := Rma(14, gains)
+	meanLosses := Rma(14, losses)
 
 	rsi := make([]float64, len(closing))
 	rs := make([]float64, len(closing))

trend_indicators.go

@@ -390,6 +390,32 @@ func DefaultKdj(high, low, closing []float64) ([]float64, []float64, []float64)
 	return Kdj(9, 3, 3, high, low, closing)
 }
 
+// Rolling Moving Average (RMA).
+//
+// R[0] to R[p-1] is SMA(values)
+// R[p] and after is R[i] = ((R[i-1]*(p-1)) + v[i]) / p
+//
+// Returns r.
+func Rma(period int, values []float64) []float64 {
+	result := make([]float64, len(values))
+	sum := float64(0)
+
+	for i, value := range values {
+		count := i + 1
+
+		if i < period {
+			sum += value
+		} else {
+			sum = (result[i-1] * float64(period-1)) + value
+			count = period
+		}
+
+		result[i] = sum / float64(count)
+	}
+
+	return result
+}
+
 // Simple Moving Average (SMA).
 func Sma(period int, values []float64) []float64 {
 	result := make([]float64, len(values))

trend_indicators.md

@@ -17,6 +17,7 @@ Trend indicators measure the direction and strength of a trend.
 - [Parabolic SAR](#parabolic-sar)
 - [Qstick](trend_indicator.md#qstick)
 - [Random Index (KDJ)](#random-index-kdj)
+- [Rolling Moving Average (RMA)](#rolling-moving-average-rma)
 - [Simple Moving Average (SMA)](#simple-moving-average-sma)
 - [Since Change](#since-change)
 - [Triple Exponential Moving Average (TEMA)](#triple-exponential-moving-average-tema)
@@ -242,6 +243,19 @@ By default, _rPeriod_ of 9, _kPeriod_ of 3, and _dPeriod_ of 3 are used. The [De
 k, d, j := indicator.DefaultKdj(high, low, closing)
 ```
 
+#### Rolling Moving Average (RMA)
+
+The [Rma](https://pkg.go.dev/github.com/cinar/indicator#Rma) function calculates the rolling moving average for a given period.
+
+```
+R[0] to R[p-1] is SMA(values)
+R[p] and after is R[i] = ((R[i-1]*(p-1)) + v[i]) / p
+```
+
+```Golang
+result := indicator.Rma(2, []float64{2, 4, 6, 8, 10, 12})
+```
+
 #### Simple Moving Average (SMA)
 
 The [Sma](https://pkg.go.dev/github.com/cinar/indicator#Sma) function calculates the simple moving average for a given period.

trend_indicators_test.go

@@ -175,6 +175,43 @@ func TestKdj(t *testing.T) {
 	testEquals(t, roundDigitsAll(j, 2), expectedJ)
 }
 
+func TestRma(t *testing.T) {
+	values := []float64{
+		0,
+		0.00005,
+		0.000017,
+		0.000262,
+		0.000107,
+		0,
+		0,
+		0.000597,
+		0,
+		0,
+		0.000059,
+		0.000198,
+		0.000073,
+		0,
+		0.000006,
+		0,
+		0.000077,
+		0.000032,
+		0.000112,
+	}
+
+	expected := []float64{
+		0.00009735714286,
+		0.00009083163265,
+		0.00008434365889,
+		0.00008381911183,
+		0.0000801177467,
+		0.00008239505051,
+	}
+	period := 14
+
+	actual := Rma(period, values)
+	testEquals(t, roundDigitsAll(actual[len(actual)-6:], 14), expected)
+}
+
 func TestSma(t *testing.T) {
 	values := []float64{2, 4, 6, 8, 10}
 	expected := []float64{2, 3, 5, 7, 9}