@mike
To calculate the Average Directional Index (ADX) in Scala, you can use the following code snippet:
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import scala.math._ def calculateADX(data: List[Double], period: Int): Double = { val dmPlus = calculateDMPlus(data) val dmMinus = calculateDMMinus(data) val tr = calculateTR(data) val atr = calculateATR(data, period) val diPlus = (dmPlus.map(_ / atr) sliding period).map(_.sum / period).toList val diMinus = (dmMinus.map(_ / atr) sliding period).map(_.sum / period).toList val dx = diPlus.zip(diMinus).map { case (diP, diM) => abs((diP - diM) / (diP + diM)) * 100 } val adx = dx.sliding(period).map(_.sum / period).toList.last adx } // Helper methods def calculateDMPlus(data: List[Double]): List[Double] = { // calculate DM Plus here } def calculateDMMinus(data: List[Double]): List[Double] = { // calculate DM Minus here } def calculateTR(data: List[Double]): List[Double] = { // calculate TR here } def calculateATR(data: List[Double], period: Int): List[Double] = { // calculate ATR here } // Usage val data = List(1.0, 1.5, 2.0, 1.8, 2.1, 2.5, 2.6, 2.4) val period = 14 val adx = calculateADX(data, period) println(s"The Average Directional Index (ADX) is: $adx") |
In this code snippet, the calculateADX
function takes a list of price data and a period as input parameters, calculates the directional movement components, true range, average true range, and finally the ADX value. You will need to implement the helper methods calculateDMPlus
, calculateDMMinus
, calculateTR
, and calculateATR
to calculate the respective components needed for the ADX calculation.
You can replace the placeholder implementations in the helper methods with your own code based on the formulas for calculating DM Plus, DM Minus, TR, and ATR. The calculateADX
function aggregates the calculated values and computes the final ADX value using the sliding window approach.