Relative Volume Breakout Context

indicator("Relative Volume Breakout Context", shorttitle="RV Breakout", overlay=false, max_labels_count=100)

string GROUP_SESSION = "Exchange session model"
string GROUP_BASELINE = "Same-position volume baseline"
string GROUP_BREAKOUT = "Breakout context"
string GROUP_VISUALS = "Visual system"

sessionStartHour = input.int(9, "Session start hour", minval=0, maxval=23, group=GROUP_SESSION, tooltip="Hour in the symbol exchange timezone.")
sessionStartMinute = input.int(30, "Session start minute", minval=0, maxval=59, group=GROUP_SESSION, tooltip="Minute in the symbol exchange timezone.")
sessionLength = input.int(390, "Session length (minutes)", minval=30, maxval=1440, group=GROUP_SESSION)

memorySessions = input.int(30, "Baseline memory (sessions)", minval=5, maxval=120, group=GROUP_BASELINE, tooltip="Controls the exponential memory of each same-position volume baseline.")
minimumSamples = input.int(10, "Minimum prior samples", minval=3, maxval=60, group=GROUP_BASELINE)
dispersionFloorPct = input.float(10.0, "Dispersion floor (% of mean)", minval=1.0, maxval=100.0, step=1.0, group=GROUP_BASELINE, tooltip="Prevents a nearly constant volume history from producing unstable Z scores.")
volumeZThreshold = input.float(1.5, "Breakout volume Z threshold", minval=0.25, maxval=5.0, step=0.05, group=GROUP_BASELINE)
decayZThreshold = input.float(0.0, "Post-breakout decay Z threshold", minval=-3.0, maxval=3.0, step=0.1, group=GROUP_BASELINE)

breakoutLength = input.int(30, "Prior price range bars", minval=5, maxval=300, group=GROUP_BREAKOUT)
atrLength = input.int(14, "ATR length", minval=2, maxval=100, group=GROUP_BREAKOUT)
minimumBreakAtr = input.float(0.10, "Minimum close beyond range (ATR)", minval=0.0, maxval=3.0, step=0.05, group=GROUP_BREAKOUT)
trackingBars = input.int(12, "Event tracking bars", minval=2, maxval=100, group=GROUP_BREAKOUT)

showScorePane = input.bool(true, "Show context score", group=GROUP_VISUALS)
showVolumeZ = input.bool(true, "Show relative-volume Z score", group=GROUP_VISUALS)
showCandidateRails = input.bool(true, "Show prior breakout rails", group=GROUP_VISUALS)
showStateWash = input.bool(true, "Show tracked-state wash", group=GROUP_VISUALS)
showEventLabels = input.bool(true, "Show confirmed event labels", group=GROUP_VISUALS)
showDashboard = input.bool(true, "Show context dashboard", group=GROUP_VISUALS)
maximumLabels = input.int(30, "Maximum event labels", minval=5, maxval=100, group=GROUP_VISUALS)

bullColor = input.color(color.rgb(16, 185, 129), "Bullish acceptance", group=GROUP_VISUALS)
bearColor = input.color(color.rgb(239, 92, 118), "Bearish acceptance", group=GROUP_VISUALS)
decayColor = input.color(color.rgb(245, 158, 11), "Participation decay", group=GROUP_VISUALS)
volumeColor = input.color(color.rgb(56, 189, 248), "Relative volume", group=GROUP_VISUALS)
neutralColor = input.color(color.rgb(148, 163, 184), "Neutral / warming", group=GROUP_VISUALS)

int MAX_SESSION_SLOTS = 1440
var array<int> slotCounts = array.new_int(MAX_SESSION_SLOTS, 0)
var array<float> slotMeans = array.new_float(MAX_SESSION_SLOTS, 0.0)
var array<float> slotVariances = array.new_float(MAX_SESSION_SLOTS, 0.0)
var array<label> eventLabels = array.new<label>()

f_clamp(float value, float lower, float upper) =>
    math.min(math.max(value, lower), upper)

f_update_slot(int index, float observation) =>
    int oldCount = array.get(slotCounts, index)
    float oldMean = array.get(slotMeans, index)
    float oldVariance = array.get(slotVariances, index)
    float alpha = oldCount < memorySessions ? 1.0 / float(oldCount + 1) : 2.0 / float(memorySessions + 1)
    float delta = observation - oldMean
    float nextMean = oldCount == 0 ? observation : oldMean + alpha * delta
    float nextVariance = oldCount == 0 ? 0.0 : (1.0 - alpha) * (oldVariance + alpha * delta * delta)
    array.set(slotCounts, index, math.min(oldCount + 1, 1000000))
    array.set(slotMeans, index, nextMean)
    array.set(slotVariances, index, math.max(nextVariance, 0.0))

f_push_label(label eventLabel) =>
    array.push(eventLabels, eventLabel)
    if array.size(eventLabels) > maximumLabels
        label.delete(array.shift(eventLabels))

float chartMinutes = float(timeframe.in_seconds()) / 60.0
bool validTimeframe = timeframe.isintraday and chartMinutes >= 1.0 and chartMinutes <= 30.0 and math.abs(chartMinutes - math.round(chartMinutes)) < 0.001
int minuteOfDay = hour(time, syminfo.timezone) * 60 + minute(time, syminfo.timezone)
int sessionStartMinuteOfDay = sessionStartHour * 60 + sessionStartMinute
int elapsedMinute = (minuteOfDay - sessionStartMinuteOfDay + 1440) % 1440
bool inSession = validTimeframe and elapsedMinute < sessionLength
int slotIndex = inSession ? int(math.floor(float(elapsedMinute) / chartMinutes)) : na
bool validSlot = inSession and slotIndex >= 0 and slotIndex < MAX_SESSION_SLOTS
bool volumeValid = validSlot and not na(volume) and volume >= 0.0

int slotSamples = validSlot ? array.get(slotCounts, slotIndex) : 0
float expectedVolume = validSlot and slotSamples > 0 ? array.get(slotMeans, slotIndex) : na
float rawDispersion = validSlot and slotSamples > 1 ? math.sqrt(array.get(slotVariances, slotIndex)) : na
float dispersionFloor = not na(expectedVolume) ? expectedVolume * dispersionFloorPct * 0.01 : na
float effectiveDispersion = not na(rawDispersion) and not na(dispersionFloor) ? math.max(rawDispersion, dispersionFloor) : na
bool baselineReady = volumeValid and slotSamples >= minimumSamples and expectedVolume > 0.0 and effectiveDispersion > 0.0
float volumeZ = baselineReady ? f_clamp((volume - expectedVolume) / effectiveDispersion, -5.0, 5.0) : na
float relativeVolume = baselineReady ? volume / expectedVolume : na
float reliability = baselineReady ? f_clamp(float(slotSamples) / float(minimumSamples * 2), 0.0, 1.0) : 0.0

float upperRail = ta.highest(high, breakoutLength)[1]
float lowerRail = ta.lowest(low, breakoutLength)[1]
float atr = ta.atr(atrLength)
bool priceReady = not na(upperRail) and not na(lowerRail) and not na(atr) and atr > 0.0
bool bullOutside = priceReady and close > upperRail
bool bearOutside = priceReady and close < lowerRail
bool freshBullBreak = bullOutside and close[1] <= upperRail
bool freshBearBreak = bearOutside and close[1] >= lowerRail
float bullDistanceAtr = bullOutside ? (close - upperRail) / atr : 0.0
float bearDistanceAtr = bearOutside ? (lowerRail - close) / atr : 0.0
float signedBreakDistanceAtr = bullOutside ? bullDistanceAtr : bearOutside ? -bearDistanceAtr : 0.0

float volumeComponent = baselineReady ? f_clamp(math.max(volumeZ, 0.0) / math.max(volumeZThreshold, 0.01), 0.0, 2.0) * 50.0 : 0.0
float distanceComponent = f_clamp(math.abs(signedBreakDistanceAtr) / math.max(minimumBreakAtr, 0.05), 0.0, 2.0) * 50.0
float jointMagnitude = math.sqrt(volumeComponent * distanceComponent) * reliability
float contextScore = bullOutside ? jointMagnitude : bearOutside ? -jointMagnitude : 0.0

var int activeDirection = 0
var int eventAge = 0
var float eventRail = na
var float eventFrontier = na
var bool decayLatched = false

bool confirmedBullEvent = barstate.isconfirmed and activeDirection == 0 and baselineReady and freshBullBreak and bullDistanceAtr >= minimumBreakAtr and volumeZ >= volumeZThreshold
bool confirmedBearEvent = barstate.isconfirmed and activeDirection == 0 and baselineReady and freshBearBreak and bearDistanceAtr >= minimumBreakAtr and volumeZ >= volumeZThreshold
bool confirmedBreakoutEvent = confirmedBullEvent or confirmedBearEvent
bool confirmedDecayEvent = false
bool confirmedInvalidation = false

if barstate.isconfirmed
    if confirmedBreakoutEvent
        activeDirection := confirmedBullEvent ? 1 : -1
        eventAge := 0
        eventRail := confirmedBullEvent ? upperRail : lowerRail
        even

Показано первые 50% кода (символов: 13478)