基于RSI的EA，Pine转mq5

任务编号：125557 悬赏任务20H币 悬赏任务 : 按雇主需求进行任务后提交稿件，被采纳后即获得佣金。

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雇主发布需求24.10.05 雇主托管佣金24.10.05 投稿者投稿 雇主开始选稿 任务完成24.10.15

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任务需求:

不需要实现指标和图表物件，只需要实现下单功能，实现EA。

//@version=5



const int maxDistanceToLastBar = 5000

const int labelCooldown = 8

const int KDELimit = 300



strategy("RSI短线", shorttitle = "RSI短线",overlay = true, max_labels_count = 500)



rsiLengthInput = input.int(14, minval = 1, title="RSI Length", group="RSI Settings")

rsiSourceInput = input.source(close, "Source", group="RSI Settings")



highPivotLen = input.int(21,  "High Pivot Length", minval = 1, group = "Pivots", display = display.none)

lowPivotLen = input.int(21, "Low Pivot Length", minval = 1, group = "Pivots", display = display.none)



activationThresholdStr = input.string("Medium", "Activation Threshold", options = ["High", "Medium", "Low"], group = "KDE", tooltip = "Determines the amount of arrows shown. Higher options will result in more arrows being rendered.")

string KDEKernel = input.string("Gaussian", "Kernel", options=['Uniform', 'Gaussian', 'Sigmoid'], group = "KDE", tooltip = "The kernel function for KDE calculation. Gaussian is a commonly used kernel and is based on normal distribution.")

float KDEBandwidth = input.float(2.71828, "Bandwidth", group = "KDE", tooltip = "This setting sets the smoothness of the KDE function output.")

int KDEStep = input.int(100, "Nº Bins", minval = 1, group = "KDE", tooltip = "The number of elements the KDE Probability array will have. Higher settings will result in greater precision.")

activationThreshold = (activationThresholdStr == "High" ? 0.4 : activationThresholdStr == "Medium" ? 0.25 : 0.15)

probMode = "Sum"

minPadding =  false



bearishColor = input.color(#f23646, "High Pivots", group = "Style", inline = "col", display = display.none)

neutralColor = input.color(color.gray, "Neutral", group = "Style", inline = "col", display = display.none)

bullishColor = input.color(#089981, "Low Pivots", group = "Style", inline = "col", display = display.none)

RSILabelsEnabled = input.bool(true, "RSI Labels", group = "Style")

KDELabelsEnabled = input.bool(true, "KDE Labels", group = "Style")



rsi = ta.rsi(rsiSourceInput, rsiLengthInput)





//#region KDE

gaussian (float distance, float bandwidth = 1.0) => 1.0 / math.sqrt(2.0 * math.pi) * math.pow(math.e, -0.5 * math.pow(distance / bandwidth, 2.0))

uniform (float distance, float bandwidth = 1.0) => (math.abs(distance) > bandwidth) ? 0.0 : 0.5

sigmoid (float distance, float bandwidth = 1.0) => 2.0 / math.pi * (1.0 / (math.pow(math.e, (distance / bandwidth)) + math.pow(math.e, -(distance / bandwidth))))



kde (array<float> arr, string kernel, float bandwidth, int steps) =>

    arrSize = arr.size()

    arrRange = arr.range()

    arrMin = arr.min() - (minPadding ? (arrRange / 2.0) : 0)

    stepCount = arrRange / steps

    

    densityRange = array.new<float>(steps * 2)

    for i = 0 to (steps * 2) - 1

        densityRange.set(i, arrMin + i * stepCount)

    

    xArr = array.new<float>()

    yArr = array.new<float>()

    for i = 0 to densityRange.size() - 1

        float temp = 0

        for j = 0 to arr.size() - 1

            temp += gaussian(densityRange.get(i) - arr.get(j), 1.0 / bandwidth)



        

        xArr.push(densityRange.get(i))

        yArr.push(1.0 / arrSize * temp)

    [xArr, yArr]

//#endregion



//#region Pivots



prefixSum (array<float> arr, int l, int r) =>

    arr.get(r) - (l == 0 ? 0 : arr.get(l - 1))



float MidKDEHigh = na

float MidKDELow = na



var array<float> KDEHighX = na

var array<float> KDEHighY = na

var array<float> KDEHighYSum = array.new<float>()



var array<float> KDELowX = na

var array<float> KDELowY = na

var array<float> KDELowYSum = array.new<float>()



highPivot = ta.pivothigh(highPivotLen, highPivotLen)

lowPivot = ta.pivotlow(lowPivotLen, lowPivotLen)



var highPivotRSIs = array.new<float>()

var lowPivotRSIs = array.new<float>()



if not na(highPivot) 

    if highPivotRSIs.size() > KDELimit

        highPivotRSIs.remove(0)

    highPivotRSIs.push(rsi[highPivotLen])



    [KDEHighX1, KDEHighY1] = kde(highPivotRSIs, KDEKernel, KDEBandwidth, KDEStep)

    KDEHighX := KDEHighX1

    KDEHighY := KDEHighY1

    

    KDEHighYSum.clear()

    temp = 0.0

    for i = 0 to KDEHighY.size() - 1

        temp += KDEHighY.get(i)

        KDEHighYSum.push(temp)



    MidKDEHigh := array.get(KDEHighX, array.indexof(KDEHighY, array.max(KDEHighY)))



if not na(lowPivot)

    if lowPivotRSIs.size() > KDELimit

        lowPivotRSIs.remove(0)

    lowPivotRSIs.push(rsi[lowPivotLen])



    [KDELowX1, KDELowY1] = kde(lowPivotRSIs, KDEKernel, KDEBandwidth, KDEStep)

    KDELowX := KDELowX1

    KDELowY := KDELowY1



    KDELowYSum.clear()

    temp = 0.0

    for i = 0 to KDELowY.size() - 1

        temp += KDELowY.get(i)

        KDELowYSum.push(temp)



    MidKDELow := array.get(KDELowX, array.indexof(KDELowY, array.max(KDELowY)))

//#endregion





float lowProb = na

float maxLowProb = na

float highProb = na

float maxHighProb = na



if last_bar_index - maxDistanceToLastBar < bar_index

    if highPivotRSIs.size() > 0

        highXIndexL = array.binary_search_leftmost(KDEHighX, rsi)

        highXIndexR = math.min(array.binary_search_rightmost(KDEHighX, rsi), KDEHighX.size() - 1)

        nearestIndex = (math.abs(rsi - KDEHighX.get(highXIndexL)) < math.abs(rsi - KDEHighX.get(highXIndexR))) ? highXIndexL : highXIndexR

        highProb := prefixSum(KDEHighYSum, 0, nearestIndex)

    

    if lowPivotRSIs.size() > 0

        lowXIndexL = array.binary_search_leftmost(KDELowX, rsi)

        lowXIndexR = math.min(array.binary_search_rightmost(KDELowX, rsi), KDELowX.size() - 1)

        nearestIndex = (math.abs(rsi - KDELowX.get(lowXIndexL)) < math.abs(rsi - KDELowX.get(lowXIndexR))) ? lowXIndexL : lowXIndexR

        lowProb := prefixSum(KDELowYSum, nearestIndex, KDELowYSum.size() - 1)





//#region Draw Pivots

color curColor = na

if (not na(KDELowY)) and (not na(KDEHighY))

    if lowProb > KDELowY.sum() * (1.0 - activationThreshold)

        curColor := bullishColor

    else if highProb > KDEHighY.sum() * (1.0 - activationThreshold)

        curColor := bearishColor





long = na(curColor) and curColor[1] == bullishColor and barstate.isconfirmed

short = na(curColor) and curColor[1] == bearishColor and barstate.isconfirmed





if long

    strategy.entry("Long", strategy.long)

if short

    strategy.entry("Short", strategy.short)    

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