[Elite Algo Modded]// ALERT READY ON TELEGRAM ==> t.me
//@version=5
indicator(" ", overlay=true, max_lines_count=500, max_labels_count=500, max_boxes_count=350)
// FUNCTIONS
// Close to Close Volatility
f_coc(x, period, sqrtAnnual) =>
mean = ta.sma(x, period)
s = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(s, math.pow(x - mean, 2))
sqrtAnnual * math.sqrt(array.sum(s) / (period - 1))
//
// Parkinson Volatility
f_park(period, sqrtAnnual) =>
var LOG2 = math.log(2)
powLogHighLow = math.pow(math.log(high / low), 2)
sqrtAnnual * math.sqrt(1.0 / period * math.sum(1.0 / (4.0 * LOG2) * powLogHighLow, period))
// Garman Klass Volatility
f_gk(period, sqrtAnnual) =>
var LOG2 = math.log(2)
var SQRT_1_PERIOD = math.sqrt(1 / period)
powLogHighLow = math.pow(math.log(high / low), 2)
powLogCloseOpen = math.pow(math.log(close / open), 2)
tmp = 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) * powLogCloseOpen
sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD
// Rogers Satchell Volatility
f_rsv(period, sqrtAnnual) =>
tmp = math.log(high / close) * math.log(high / open) + math.log(low / close) * math.log(low / open)
sqrtAnnual * math.sqrt(math.sum(tmp, period) / period)
// Garman Klass Yang Zhang Extension Volatility
f_gkyz(period, sqrtAnnual) =>
var LOG2 = math.log(2)
var SQRT_1_PERIOD = math.sqrt(1 / period)
powLogHighLow = math.pow(math.log(high / low), 2)
powLogCloseOpen = math.pow(math.log(close / open), 2)
lastClose = nz(close , close)
powLogOpenClose1 = math.pow(math.log(open / lastClose), 2)
tmp = powLogOpenClose1 + 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) * powLogCloseOpen
sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD
// Yang Zhang Volatility
f_yz(a, period, sqrtAnnual) =>
o = math.log(open) - math.log(nz(close , close))
u = math.log(high) - math.log(open)
d = math.log(low) - math.log(open)
c = math.log(close) - math.log(open)
nMinusOne = period - 1
avgo = ta.sma(o, period)
avgc = ta.sma(c, period)
so = array.new_float(0)
sc = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(so, math.pow(o - avgo, 2))
array.push(sc, math.pow(c - avgc, 2))
sumo = array.sum(so)
sumc = array.sum(sc)
Vo = sumo / nMinusOne
Vc = sumc / nMinusOne
Vrs = math.sum(u * (u - c) + d * (d - c), period) / period
k = (a - 1.0) / (a + (period + 1.0) / nMinusOne)
sqrtAnnual * math.sqrt(Vo + k * Vc + (1.0 - k) * Vrs)
// Exponentially Weighted Volatility
f_ewma(source, period, sqrtAnnual) =>
var lambda = (period - 1) / (period + 1)
squared = math.pow(source, 2)
float v = na
v := lambda * nz(v , squared) + (1.0 - lambda) * squared
sqrtAnnual * math.sqrt(v)
// Mean Absolute Deviation (Adjusted)
f_mad(source, period, sqrtAnnual) =>
var SQRT_HALF_PI = math.sqrt(math.asin(1))
mean = ta.sma(source, period)
S = array.new_float(0)
for i = 0 to period - 1 by 1
array.push(S, math.abs(source - mean))
sumS = array.sum(S)
sqrtAnnual * (sumS / period) * SQRT_HALF_PI
// Median Absolute Deviation
f_mead(source, period, sqrtAnnual) =>
median = ta.percentile_nearest_rank(source, period, 50)
E = 0.0
for i = 0 to period - 1 by 1
E += math.abs(source - median)
E
sqrtAnnual * math.sqrt(2) * (E / period)
//Rescale Function
f_rescale(_src, _size) =>
math.max(0, math.min(_size, int(_src / 100 * _size)))
// label Panel Function
_label(T, color_PnL) =>
label PnL_Label = na
label.delete(PnL_Label )
PnL_Label := label.new(time, 0, text=T, color=color_PnL, textcolor=color.white, size=size.normal, style=label.style_label_left, xloc=xloc.bar_time, textalign=text.align_left)
label.set_x(PnL_Label, label.get_x(PnL_Label) + math.round(ta.change(time) * 3))
// Round Function
Round(src, digits) =>
p = math.pow(10, digits)
math.round(math.abs(src) * p) / p * math.sign(src)
//Options for Inputs
ON = 'On'
OFF = 'Off'
CTC = 'Close to Close'
PKS = 'Parkinson'
GK = 'Garman Klass'
RS = 'Rogers Satchell'
GKYZ = 'Garman Klass Yang Zhang Extension'
YZ = 'Yang Zhang'
EWMA = 'EWMA'
MAD = 'Mean Absolute Deviation'
MAAD = 'Median Absolute Deviation'
L = 'Line'
SL = 'StepLine'
Ar = 'Area'
CL = 'Columns'
// Settings
H = EWMA
period = 10
Annual = 365
a = 1.34
Plen = 365
Pco = ON
sma = ON
malen = 55
bsg = OFF
stl = CL
lT = 3
i_invert = OFF
bg = OFF
sp = OFF
// bgcolor(bg ? color.new(#000000, 20) : na, title='Dark Background', transp=90)
var sqrtAnnual = math.sqrt(Annual) * 100
logr = math.log(close / close )
// Historical Volatiity Models
Hv = if H == CTC
f_coc(logr, period, sqrtAnnual)
else if H == PKS
f_park(period, sqrtAnnual)
else if H == RS
f_rsv(period, sqrtAnnual)
else if H == GK
f_gk(period, sqrtAnnual)
else if H == GKYZ
f_gkyz(period, sqrtAnnual)
else if H == EWMA
f_ewma(logr, period, sqrtAnnual)
else if H == YZ
f_yz(a, period, sqrtAnnual)
else if H == MAD
f_mad(logr, period, sqrtAnnual)
else
// H == "Median Absolute Deviation"
f_mead(logr, period, sqrtAnnual)
pstyle = stl == L ? plot.style_linebr : stl == SL ? plot.style_stepline : stl == Ar ? plot.style_area : stl == CL ? plot.style_columns : plot.style_line
//Hv Stats
avgHV = ta.sma(Hv, malen)
HVP = ta.percentrank(Hv, Plen)
NearZero = HVP < 1.5 ? 1 : 0
HV50 = ta.percentile_nearest_rank(Hv, Plen, 50)
// // Text Functions
// texthv() =>
// ' HV: ' + str.tostring(Round(Hv, 2))
// textphv() =>
// 'HV 50áµ—Ê° Percentile: ' + str.tostring(Round(HV50, 2))
// texthvp() =>
// 'HV Percentile: ' + str.tostring(Round(HVP, 2)) + 'áµ—Ê°'
// // Coloring
// var c_ = array.new_color(na)
// if barstate.isfirst
// array.push(c_, #0effff)
// array.push(c_, #00fdf6)
// array.push(c_, #00fbee)
// array.push(c_, #00f9e4)
// array.push(c_, #00f6db)
// array.push(c_, #00f4d1)
// array.push(c_, #13f1c6)
// array.push(c_, #24efbc)
// array.push(c_, #31ecb1)
// array.push(c_, #3ce9a6)
// array.push(c_, #47e69b)
// array.push(c_, #51e390)
// array.push(c_, #5adf85)
// array.push(c_, #62dc7a)
// array.push(c_, #6ad96e)
// array.push(c_, #72d563)
// array.push(c_, #7ad157)
// array.push(c_, #81cd4b)
// array.push(c_, #88ca3f)
// array.push(c_, #8fc532)
// array.push(c_, #96c123)
// array.push(c_, #9cbd0e)
// array.push(c_, #a3b800)
// array.push(c_, #a9b300)
// array.push(c_, #b0ae00)
// array.push(c_, #b6a900)
// array.push(c_, #bca300)
// array.push(c_, #c29e00)
// array.push(c_, #c29e00)
// array.push(c_, #c89800)
// array.push(c_, #ce9100)
// array.push(c_, #d48b00)
// array.push(c_, #da8400)
// array.push(c_, #df7c00)
// array.push(c_, #e57400)
// array.push(c_, #ea6c00)
// array.push(c_, #ef6200)
// array.push(c_, #f35800)
// array.push(c_, #f74c00)
// array.push(c_, #fb3e00)
// array.push(c_, #ff2d00)
// if i_invert
// array.reverse(c_)
// var sizeOf = array.size(c_) - 1
// colorHV = Pco ? array.get(c_, f_rescale(HVP, sizeOf)) : color.aqua
// Plots
// plot(Hv, 'HV', color=colorHV, linewidth=lT, style=plot.style_line)
// plot(sma ? avgHV : na, 'sma', color=color.new(#FFFFFF, 25), linewidth=2)
//bgcolor(Hv > avgHV ? color.lime : na)
// if sp
// _label(H + texthv() + ' ' + textphv() + ' ' + texthvp() + ' ', #000000c0)
// col2 = HVP >= 1 ? color.yellow : HVP <= 1 and HVP >= 0.5 ? color.orange : HVP <= 0.5 ? #8D0000 : color.silver
// // bgcolor(bsg and NearZero ? col2 : na, transp=50)
//Custrom MAS
maa = avgHV / 100 * 140
mab = avgHV / 100 * 180
mac = avgHV / 100 * 240
mad = avgHV / 100 * 60
mae = avgHV / 100 * 20
// Auto Sensivity Volatility Band Settings
float volatility = 0.0
if Hv < maa and Hv > avgHV // ilk band ust
volatility := 3.15
else if Hv < mab and Hv > maa // ikinci band ust
volatility := 3.5
else if Hv < mac and Hv > mab // ucuncu band ust
volatility := 3.6
else if Hv > mac // volatilite en ust degerde
volatility := 4
else if Hv < maa and Hv > mad // altdaki ilk band
volatility := 3
else if Hv < mad and Hv > mae // altdaki ikinci band
volatility := 2.85
else if Hv < mae // volatilite butun bandlarin anltinda
volatility := 3
//plot(volatility,color = color.red)
// plot(maa, 'maa', color=color.new(color.aqua, 25))
// plot(mab, 'mab', color=color.new(color.aqua, 25))
// plot(mac, 'mac', color=color.new(color.aqua, 25))
// plot(mad, 'mad', color=color.new(color.aqua, 25))
// plot(mae, 'mae', color=color.new(color.aqua, 25))
//-------------- Elite Algo v22 | elitesignals.com -----------------//
// Get user input
enableDashboard = input(true, "Enable Dashboard", group="DASHBOARD SETTINGS")
locationDashboard = input.string("Middle right", "Location", , group="DASHBOARD SETTINGS")
sizeDashboard = input.string("Tiny", "Size", , group="DASHBOARD SETTINGS")
colorBackground = input(#2A2E39, "Bg color", group="DASHBOARD SETTINGS")
colorFrame = input(#2A2E39, "Frame color", group="DASHBOARD SETTINGS")
colorBorder = input(#363A45, "Border color", group="DASHBOARD SETTINGS")
showSignals = input(true, "Show signals", group="BUY AND SELL SIGNALS SETTINGS")
strategy = input.string("Normal", "Strategy", , group="BUY AND SELL SIGNALS SETTINGS")
sensitivity11 = input.float(defval=1.8, title="Sensitivity", minval=1, maxval=20, group = 'Signals')
sensitivity = sensitivity11
auto_button = input.bool(defval = true , title = "Auto Sensitivity", group = 'Signals')
consSignalsFilter = input(false, "Consolidation signals filter", group="BUY AND SELL SIGNALS SETTINGS")
smartSignalsOnly = input(false, "Smart signals only", group="BUY AND SELL SIGNALS SETTINGS")
candleColors = input(false, "Candle colors", group="BUY AND SELL SIGNALS SETTINGS")
momentumCandles = input(false, "Momentum candles", group="BUY AND SELL SIGNALS SETTINGS")
highVolSignals = input(false, "High volume signals only", group="BUY AND SELL SIGNALS SETTINGS")
enableTrailingSL = input(false, "Enable trailing stop-loss", group="RISK MANAGEMENT SETTINGS")
usePercSL = input(false, "% Trailing sl", inline="2", group="RISK MANAGEMENT SETTINGS")
percTrailingSL = input.float(1, "", 0, step=0.1, inline="2", group="RISK MANAGEMENT SETTINGS")
enableSwings = input(false, "Enable Swing High's & Swing's Low's", inline="3", group="RISK MANAGEMENT SETTINGS")
periodSwings = input.int(10, "", 2, inline="3", group="RISK MANAGEMENT SETTINGS")
enableTpSlAreas = input(false, "Enable take profit/stop-loss areas", group="RISK MANAGEMENT SETTINGS")
useTP1 = input(true, "", inline="4", group="RISK MANAGEMENT SETTINGS")
multTP1 = input.float(1, "TP 1", 0, inline="4", group="RISK MANAGEMENT SETTINGS")
useTP2 = input(true, "", inline="5", group="RISK MANAGEMENT SETTINGS")
multTP2 = input.float(2, "TP 2", 0, inline="5", group="RISK MANAGEMENT SETTINGS")
useTP3 = input(true, "", inline="6", group="RISK MANAGEMENT SETTINGS")
multTP3 = input.float(3, "TP 3", 0, inline="6", group="RISK MANAGEMENT SETTINGS")
tpLabels = input(true, "Take profit labels", group="RISK MANAGEMENT SETTINGS")
showTrendCloud = input(true, "Show Trend cloud", group="TREND CLOUD SETTINGS")
periodTrendCloud = input.string("New", "Trend cloud period", , group="TREND CLOUD SETTINGS")
signalsTrendCloud = input(false, "Trend only signals", group="TREND CLOUD SETTINGS")
fastTrendCloud = input(false, "Fast trend cloud", group="TREND CLOUD SETTINGS")
fastTrendCloudLen = input.int(55, "Fast trend cloud", 2, group="TREND CLOUD SETTINGS")
enableAutoTrend = input(false, "Enable Auto Trendlines", group="AUTO TRENDLINES SETTINGS")
srcTrendChannel = input(close, "Trend channel source", group="AUTO TRENDLINES SETTINGS")
lenTrendChannel = input.int(200, "Trend channel loopback", 2, group="AUTO TRENDLINES SETTINGS")
enableSR = input(false, "Enable support and resistance", group="AUTO SUPPORT AND RESISTANCE SETTINGS")
lineSrStyle = input.string("Dashed", "Line Style", , group="AUTO SUPPORT AND RESISTANCE SETTINGS")
lineSrWidth = input.int(2, "Line Width", 1, 4, group="AUTO SUPPORT AND RESISTANCE SETTINGS")
showCons = input(false, "Consolidation Zones", group="CONSOLIDATION ZONES")
lbPeriod = input.int(10, "Loopback Period", 2, 50, group="CONSOLIDATION ZONES")
lenCons = input.int(5, "Min Consolidation Length", 2, 20, group="CONSOLIDATION ZONES")
paintCons = input(true, "Paint Consolidation Area", group="CONSOLIDATION ZONES")
colorZone = input(color.new(color.blue, 70), "Zone Color", group="CONSOLIDATION ZONES")
box_ob = input.bool(false, "Toggle Order Block", group="ORDER BLOCK")
box_hide_gray = input.bool(false, "Hide gray boxes", group="ORDER BLOCK")
bos_type = input.string("High and Low", "MSB trigger", , group="ORDER BLOCK")
box_sv = input.bool(true, "Plot demand boxes", group="ORDER BLOCK")
box_test_delay = input.int(3, "Delay to count test of demand box", 1, group="ORDER BLOCK")
box_fill_delay = input.int(3, "Delay to count fill of demand box", 1, group="ORDER BLOCK")
box_test_sv = input.bool(true, "Dim tested demand boxes", group="ORDER BLOCK")
box_stop_sv = input.bool(true, "Stop plotting filled demand boxes", group="ORDER BLOCK")
eliteVP = input(false, "Elite volume profile", group="ELITE VOLUME PROFILE")
colorBorderVP = input(color.new(color.black, 80), "Border color", group="ELITE VOLUME PROFILE")
colorBuyVP = input(#7F1623, "Buy volume", group="ELITE VOLUME PROFILE")
colorSellVP = input(#00DD00, "Sell volume", group="ELITE VOLUME PROFILE")
offset = input.int(2, "Offset", 2, 20, group="ELITE VOLUME PROFILE")
lookback = input.int(100, "Lookback", 14, 10000, group="ELITE VOLUME PROFILE")
levelNum = input.int(100, "Number of levels", 10, 1000, group="ELITE VOLUME PROFILE")
levelWidth = input.int(50, "Level width", 2, 100, group="ELITE VOLUME PROFILE")
if auto_button == false
sensitivity
else if auto_button == true
sensitivity := volatility
// Functions
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1. / 60 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
atr(len) =>
tr = ta.tr
atr = 0.0
atr := nz(atr + (tr - atr ) / len, tr)
supertrend(src, factor, len) =>
atr = ta.atr(len)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or close < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or close > prevUpperBand ? upperBand : prevUpperBand
int direction = na
float superTrend = na
prevSuperTrend = superTrend
if prevSuperTrend == prevUpperBand
direction := close > upperBand ? 1 : -1
else
direction := close < lowerBand ? -1 : 1
superTrend := direction == 1 ? lowerBand : direction == -1 ? upperBand : na
dchannel(len)=>
hh = ta.highest(len)
ll = ta.lowest (len)
trend = 0
trend := close > hh ? 1 : close < ll ? -1 : nz(trend )
trendScalper(show, len1, len2, len3, colorBull, colorBear, colorBarBull, colorBarBear) =>
avgOC = math.avg(open, close)
ha_o = 0.0, ha_o := na(ha_o ) ? avgOC : (ha_o + ohlc4 ) / 2
ema1 = ta.ema(ha_o, len1), ema2 = ta.ema(ha_o, len2), ema3 = ta.ema(ha_o, len3)
ris1 = ema1 > ema1 , ris2 = ema2 > ema2 , ris3 = ema3 > ema3
fal1 = ema1 < ema1 , fal2 = ema2 < ema2 , fal3 = ema3 < ema3
colorEma1 = ris1 ? colorBull : fal1 ? colorBear : na, colorEma2 = ris2 ? colorBull : fal2 ? colorBear : na, colorEma3 = ris3 ? colorBull : fal3 ? colorBear : na
fillEma1 = avgOC > ema1 ? colorBull : avgOC < ema1 ? colorBear : na, fillEma2 = ema1 > ema2 ? colorBull : ema1 < ema2 ? colorBear : na, fillEma3 = ema2 > ema3 ? colorBull : ema2 < ema3 ? colorBear : na
colorBar = close < ema1 and close < ema2 ? colorBarBear : colorBarBull
candlesMom() =>
= ta.macd(close, 12, 26, 9)
(macd > 0 and macd > macd ) or (macd < 0 and macd < macd )
trailingSL(buy, sell, factor, len, usePerc, perc) =>
atr = atr(len)
upperBand = high + (usePerc ? high * (perc / 100) : factor * atr)
lowerBand = low - (usePerc ? low * (perc / 100) : factor * atr)
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or buy ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or sell ? upperBand : prevUpperBand
int direction = na
float stop = na
prevSuperTrend = stop
if prevSuperTrend == prevUpperBand
direction := buy ? 1 : -1
else
direction := sell ? -1 : 1
stop := direction == 1 ? lowerBand : direction == -1 ? upperBand : na
add_to_zz(zz, val, bi) =>
array.unshift(zz, bi)
array.unshift(zz, val)
if array.size(zz) > 12
array.pop(zz)
update_zz(zz, val, bi, dir) =>
if array.size(zz) == 0
add_to_zz(zz, val, bi)
else
if dir == 1 and val > array.get(zz, 0) or dir == -1 and val < array.get(zz, 0)
array.set(zz, 0, val)
array.set(zz, 1, bi)
0
float ph = ta.pivothigh(high, 10, 10)
float pl = ta.pivotlow (low , 10, 10)
LSRstyle = lineSrStyle == "Dashed" ? line.style_dashed : lineSrStyle == "Solid" ? line.style_solid : line.style_dotted
prdhighest = ta.highest(300)
prdlowest = ta.lowest (300)
cwidth = (prdhighest - prdlowest) * 10 / 100
var pivotvals = array.new_float(0)
if ph or pl
array.unshift(pivotvals, ph ? ph : pl)
if array.size(pivotvals) > 20
array.pop(pivotvals)
get_sr_vals(ind) =>
float lo = array.get(pivotvals, ind)
float hi = lo
int numpp = 0
for y = 0 to array.size(pivotvals) - 1 by 1
float cpp = array.get(pivotvals, y)
float wdth = cpp <= lo ? hi - cpp : cpp - lo
if wdth <= cwidth
lo := cpp <= lo ? cpp : lo
hi := cpp > lo ? cpp : hi
numpp += 1
numpp
var sr_up_level = array.new_float(0)
var sr_dn_level = array.new_float(0)
sr_strength = array.new_float(0)
find_loc(strength) =>
ret = array.size(sr_strength)
for i = ret > 0 ? array.size(sr_strength) - 1 : na to 0 by 1
if strength <= array.get(sr_strength, i)
break
ret := i
ret
ret
check_sr(hi, lo, strength) =>
ret = true
for i = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1
if array.get(sr_up_level, i) >= lo and array.get(sr_up_level, i) <= hi or array.get(sr_dn_level, i) >= lo and array.get(sr_dn_level, i) <= hi
if strength >= array.get(sr_strength, i)
array.remove(sr_strength, i)
array.remove(sr_up_level, i)
array.remove(sr_dn_level, i)
ret
else
ret := false
ret
break
ret
// Get components
rsi = ta.rsi(close, 14)
vosc = ta.obv - ta.ema(ta.obv, 20)
bs = ta.ema(nz(math.abs((open - close) / (high - low) * 100)), 3)
ema = ta.ema(close, 200)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes()
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes()
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10)
securityNoRep(sym, res, src) =>
bool bull = na
bull := equal_tf(res) ? src : bull
bull := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull := array.pop(bull_array)
array.clear(bull_array)
bull
TF1Bull = securityNoRep(syminfo.tickerid, "1" , emaBull)
TF3Bull = securityNoRep(syminfo.tickerid, "3" , emaBull)
TF5Bull = securityNoRep(syminfo.tickerid, "5" , emaBull)
TF10Bull = securityNoRep(syminfo.tickerid, "10" , emaBull)
TF15Bull = securityNoRep(syminfo.tickerid, "15" , emaBull)
TF30Bull = securityNoRep(syminfo.tickerid, "30" , emaBull)
TF60Bull = securityNoRep(syminfo.tickerid, "60" , emaBull)
TF120Bull = securityNoRep(syminfo.tickerid, "120" , emaBull)
TF240Bull = securityNoRep(syminfo.tickerid, "240" , emaBull)
TF720Bull = securityNoRep(syminfo.tickerid, "720" , emaBull)
TFDBull = securityNoRep(syminfo.tickerid, "1440", emaBull)
ema150 = ta.ema(close, 150)
ema250 = ta.ema(close, 250)
hma55 = ta.hma(close, 55 )
= ta.macd(close, 12, 26, 9)
supertrend = supertrend(ohlc4, sensitivity, 10)
maintrend = dchannel(30)
confBull = (ta.crossover (close, supertrend) or (ta.crossover (close, supertrend) and maintrend < 0)) and macd > 0 and macd > macd and ema150 > ema250 and hma55 > hma55 and maintrend > 0
confBear = (ta.crossunder(close, supertrend) or (ta.crossunder(close, supertrend) and maintrend > 0)) and macd < 0 and macd < macd and ema150 < ema250 and hma55 < hma55 and maintrend < 0
trendcloud = supertrend(ohlc4, periodTrendCloud == "Long term" ? 7 : 4, 10)
hma = fastTrendCloud ? ta.hma(close, fastTrendCloudLen) : na
none = close > 0
= ta.dmi(14, 14)
consFilter = adx > 20
smartFilter = ta.ema(close, 200)
volFilter = (ta.ema(volume, 25) - ta.ema(volume, 26)) / ta.ema(volume, 26) > 0
trendFilter = trendcloud
bull = (strategy == "Normal" ? ta.crossover (close, supertrend) : confBull and not confBull ) and strategy != "Trend scalper" and (smartSignalsOnly ? close > smartFilter : none) and (consSignalsFilter ? consFilter : none) and (highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud == "New" ? ema150 > ema250 : close > trendFilter) : none)
bear = (strategy == "Normal" ? ta.crossunder(close, supertrend) : confBear and not confBear ) and strategy != "Trend scalper" and (smartSignalsOnly ? close < smartFilter : none) and (consSignalsFilter ? consFilter : none) and (highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud == "New" ? ema150 < ema250 : close < trendFilter) : none)
countBull = ta.barssince(bull)
countBear = ta.barssince(bear)
trigger = nz(countBull, bar_index) < nz(countBear, bar_index) ? 1 : 0
= trendScalper(strategy == "Trend scalper" ? true : false, 5, 9, 21, color.green, color.red, #00DD00, #DD0000)
trailingStop = trailingSL(bull, bear, 2.2, 14, usePercSL, percTrailingSL)
float _ph = ta.highestbars(high, periodSwings) == 0 ? high : na
float _pl = ta.lowestbars (low, periodSwings) == 0 ? low : na
var _dir = 0, dir_ = _pl and na(_ph) ? -1 : _dir, _dir := _ph and na(_pl) ? 1 : dir_, dirChg = ta.change(_dir)
var zz = array.new_float(0), zzOld = array.copy(zz)
float zzLive = _ph or _pl ? (dirChg ? add_to_zz(zz, _dir == 1 ? _ph : _pl, bar_index) : update_zz(zz, _dir == 1 ? _ph : _pl, bar_index, _dir)) : na
aA = ta.wma(srcTrendChannel, lenTrendChannel), b = ta.sma(srcTrendChannel, lenTrendChannel)
A = 4 * b - 3 * aA, B = 3 * aA - 2 * b
m = (A - B) / (lenTrendChannel - 1)
d = 0., for i = 0 to lenTrendChannel - 1 by 1
l = B + m * i
d += math.pow(srcTrendChannel - l, 2)
rmse = math.sqrt(d / (lenTrendChannel - 1)) * 2
float hb_ = ta.highestbars(lbPeriod) == 0 ? high : na
float lb_ = ta.lowestbars (lbPeriod) == 0 ? low : na
var int dir = 0
float zz_ = na
float pp = na
var int consCnt = 0
var float condHi = na
var float condLo = na
float H_ = ta.highest(lenCons)
float L_ = ta.lowest (lenCons)
var line lineUp = na
var line lineDn = na
bool breakUp = false
bool breakDn = false
var float pvh1_price = array.new_float(1000, na)
var int pvh1_time = array.new_int (1000, na)
var float pvl1_price = array.new_float(1000, na)
var int pvl1_time = array.new_int (1000, na)
var float pvh2_price = array.new_float(1000, na)
var int pvh2_time = array.new_int (1000, na)
var float pvl2_price = array.new_float(1000, na)
var int pvl2_time = array.new_int (1000, na)
var float htcmrll_price = na
var int htcmrll_time = na
var float ltcmrhh_price = na
var int ltcmrhh_time = na
var box long_boxes = array.new_box()
var box short_boxes = array.new_box()
var float temp_pv_0 = na
var float temp_pv_1 = na
var float temp_pv_2 = na
bool pvh = high < high and high > high
bool pvl = low > low and low < low
int pv1_time = bar_index
float pv1_high = high
float pv1_low = low
float trigger_high = bos_type == "High and Low" ? high : math.max(open, close)
float trigger_low = bos_type == "High and Low" ? low : math.min(open, close)
rangeHigh = ta.highest(high, lookback)
rangeLow = ta.lowest(low, lookback)
rangeHeight = rangeHigh - rangeLow
histogramHeight = rangeHeight / levelNum
histogramLowList = array.new_float(levelNum, na)
histogramHighList = array.new_float(levelNum, na)
histogramBuyVolumeList = array.new_float(levelNum, 0.0)
histogramSellVolumeList = array.new_float(levelNum, 0.0)
var buyBars = array.new_box(365, na)
for i = 0 to 364
box.delete(array.get(buyBars, i))
var sellBars = array.new_box(365, na)
for i = 0 to 364
box.delete(array.get(sellBars, i))
// Colors
green = #00DD00, green50 = color.new(green, 50), green20 = color.new(green, 80)
red = #DD0000, red50 = color.new(red, 50), red20 = color.new(red, 80)
silver = #B2B5BE, silver50 = color.new(silver, 50), silver20 = color.new(silver, 80)
// Plots
atrBand = usePercSL ? (trigger ? low : high) * (percTrailingSL / 100) : ta.atr(14) * 2.2
atrStop = trigger ? low - atrBand : high + atrBand
lastTrade(src) => ta.valuewhen(bull or bear, src, 0)
entry_y = lastTrade(close)
stop_y = lastTrade(atrStop)
tp1_y = (entry_y-lastTrade(atrStop))*multTP1 + entry_y
tp2_y = (entry_y-lastTrade(atrStop))*multTP2 + entry_y
tp3_y = (entry_y-lastTrade(atrStop))*multTP3 + entry_y
labelTpSl(cond, y, txt, color) =>
label labelTpSl = enableTpSlAreas and cond ? label.new(bar_index + 1, y, txt, xloc.bar_index, yloc.price, color, label.style_label_left, color.white, size.normal) : na
label.delete(labelTpSl )
labelTpSl(none, entry_y, "Entry : " + str.tostring(math.round_to_mintick(entry_y)), color.orange)
labelTpSl(none, stop_y , "Stop loss : " + str.tostring(math.round_to_mintick(atrStop)), color.red)
labelTpSl(useTP1 and multTP1 != 0, tp1_y, "TP 1 : " + str.tostring(math.round_to_mintick(tp1_y)), color.green)
labelTpSl(useTP2 and multTP2 != 0, tp2_y, "TP 2 : " + str.tostring(math.round_to_mintick(tp2_y)), color.green)
labelTpSl(useTP3 and multTP3 != 0, tp3_y, "TP 3 : " + str.tostring(math.round_to_mintick(tp3_y)), color.green)
lineTpSl(cond, y, color, style) =>
line lineTpSl = enableTpSlAreas and cond ? line.new(bar_index - (trigger ? countBull : countBear), y, bar_index + 1, y, xloc.bar_index, extend.none, color, style) : na
line.delete(lineTpSl )
lineTpSl(none, entry_y, color.orange, line.style_dashed)
lineTpSl(none, stop_y , color.red , line.style_solid )
lineTpSl(useTP1 and multTP1 != 0, tp1_y, color.green, line.style_dotted)
lineTpSl(useTP2 and multTP2 != 0, tp2_y, color.green, line.style_dotted)
lineTpSl(useTP3 and multTP3 != 0, tp3_y, color.green, line.style_dotted)
var dashboard_loc = locationDashboard == "Top right" ? position.top_right : locationDashboard == "Top left" ? position.top_left : locationDashboard == "Middle right" ? position.middle_right : locationDashboard == "Middle left" ? position.middle_left : locationDashboard == "Bottom right" ? position.bottom_right : position.bottom_left
var dashboard_size = sizeDashboard == "Tiny" ? size.tiny : sizeDashboard == "Small" ? size.small : size.normal
var dashboard = table.new(dashboard_loc, 2, 20, colorBackground, colorFrame, 3, colorBorder, 3)
dashboard_cell(column, row, txt) => table.cell(dashboard, column, row, txt, 0, 0, color.white, text_size=dashboard_size)
dashboard_cell_bg(column, row, col) => table.cell_set_bgcolor(dashboard, column, row, col)
if barstate.islast and enableDashboard
dashboard_cell(0, 0 , "Current strategy")
dashboard_cell(0, 1 , "Current sensitivity")
dashboard_cell(0, 2 , "Current Position")
dashboard_cell(0, 3 , "Current trend")
dashboard_cell(0, 4 , "Trend strength")
dashboard_cell(0, 5 , "Volume")
dashboard_cell(0, 6 , "Volatility")
dashboard_cell(0, 7 , "Momentum")
dashboard_cell(0, 8 , "Timeframe trends📊"), table.merge_cells(dashboard, 0, 8, 1, 8)
dashboard_cell(0, 9 , "1 min")
dashboard_cell(0, 10, "3 min")
dashboard_cell(0, 11, "5 min")
dashboard_cell(0, 12, "10 min")
dashboard_cell(0, 13, "15 min")
dashboard_cell(0, 14, "30 min")
dashboard_cell(0, 15, "1 Hour")
dashboard_cell(0, 16, "2 Hour")
dashboard_cell(0, 17, "4 Hour")
dashboard_cell(0, 18, "12 Hour")
dashboard_cell(0, 19, "Daily")
dashboard_cell(1, 0 , strategy)
dashboard_cell(1, 1 , str.tostring(sensitivity))
dashboard_cell(1, 2 , strategy != "Trend scalper" ? (trigger ? "Buy" : "Sell") : ""), dashboard_cell_bg(1, 2, strategy != "Trend scalper" ? (trigger ? color.green : color.red) : colorBackground)
dashboard_cell(1, 3 , emaBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 3, emaBull ? color.green : color.red)
dashboard_cell(1, 4 , str.tostring(bs, "0.0") + " %")
dashboard_cell(1, 5 , vosc > 0 ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 5, vosc > 0 ? color.green : color.red)
dashboard_cell(1, 6 , adx > 20 ? "Trending 🚀" : "Ranging ⚠️"), dashboard_cell_bg(1, 6, adx > 20 ? color.green : color.orange)
dashboard_cell(1, 7 , rsi > 50 ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 7, rsi > 50 ? color.green : color.red)
dashboard_cell(1, 9 , TF1Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 9 , TF1Bull ? color.green : color.red)
dashboard_cell(1, 10, TF3Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 10, TF3Bull ? color.green : color.red)
dashboard_cell(1, 11, TF5Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 11, TF5Bull ? color.green : color.red)
dashboard_cell(1, 12, TF10Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 12, TF10Bull ? color.green : color.red)
dashboard_cell(1, 13, TF15Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 13, TF15Bull ? color.green : color.red)
dashboard_cell(1, 14, TF30Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 14, TF30Bull ? color.green : color.red)
dashboard_cell(1, 15, TF60Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 15, TF60Bull ? color.green : color.red)
dashboard_cell(1, 16, TF120Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 16, TF120Bull ? color.green : color.red)
dashboard_cell(1, 17, TF240Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 17, TF240Bull ? color.green : color.red)
dashboard_cell(1, 18, TF720Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 18, TF720Bull ? color.green : color.red)
dashboard_cell(1, 19, TFDBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 19, TFDBull ? color.green : color.red)
l(css, k) =>
line lr = enableAutoTrend ? line.new(bar_index - lenTrendChannel + 1, A + k, bar_index, B + k, extend=extend.right, color=css) : na
line.delete(lr )
l(color.blue, rmse), l(color.blue, 0), l(color.blue, -rmse)
//
//======================================
Candlestick analysis
Fear and Greed Trading Strategy By EquityPath (Dev Hunainmq)Description:
🚀 **Fear and Greed Trading Strategy for TradingView** 🚀
Take your trading to the next level with this innovative and automated **Fear and Greed Index-based strategy**. 🎯 This strategy leverages the powerful **emotional drivers of the market**—fear and greed—to help you make smarter, data-driven trading decisions. Designed for traders of all experience levels, this tool provides seamless buy and sell signals to capitalize on market sentiment.
🔴 **Fear Zone:** Automatically triggers a sell when the market sentiment shifts toward extreme fear, signaling potential downturns.
🟢 **Greed Zone:** Automatically triggers a buy when the market sentiment trends toward extreme greed, signaling potential growth opportunities.
---
### **Features:**
✅ **Dynamic Buy and Sell Signals:** Executes trades automatically based on sentiment thresholds.
✅ **Position Management:** Trades a fixed quantity (e.g., 100 shares) for simplicity and risk control.
✅ **Threshold Customization:** Adjust fear and greed levels (default: 25 for fear, 75 for greed) to suit your trading style.
✅ **Visual Cues:** Clear labels and visual plots of the Fear and Greed Index on the chart for easy interpretation.
✅ **Fully Automated Execution:** Hands-free trading when connected to a supported broker in TradingView.
---
### **Who Is This Strategy For?**
📈 Crypto Traders
📈 Stock Traders
📈 Forex Traders
📈 Anyone looking to incorporate **market psychology** into their trading!
With sleek design and powerful automation, this strategy ensures you stay ahead of the market by aligning your trades with the ebb and flow of investor sentiment. Whether you're a beginner or an experienced trader, this strategy simplifies the process and enhances your edge. 💡
---
### Hashtags:
#TradingStrategy #FearAndGreedIndex #MarketSentiment #TradingAutomation #AlgorithmicTrading #CryptoTrading #StockMarket #ForexTrading #TechnicalAnalysis #SmartTrading #TradingTools #EmotionalTrading #GreedZone #FearZone #TradingSuccess #PineScript
Support and Resistance with Buy/Sell Signals**Support and Resistance with Buy/Sell Signals**
Support and resistance are key concepts in technical analysis used to identify price levels at which an asset tends to reverse or pause in its trend. These levels are pivotal for traders to anticipate potential entry (buy) or exit (sell) opportunities.
### **Support**
Support is a price level where a downward trend tends to pause or reverse due to an increase in buying interest. It acts as a "floor" for the price. Traders consider this level as an area to look for **buy signals**.
#### **Buy Signals near Support**:
1. **Bounce Confirmation**: When the price touches the support level and rebounds upward, confirming the strength of the support.
2. **Bullish Candlestick Patterns**: Patterns like hammers or engulfing candles forming at support levels suggest buying opportunities.
3. **Volume Increase**: A spike in trading volume at the support level often reinforces the likelihood of a reversal.
---
### **Resistance**
Resistance is a price level where an upward trend tends to pause or reverse due to an increase in selling pressure. It acts as a "ceiling" for the price. Traders consider this level as an area to look for **sell signals**.
#### **Sell Signals near Resistance**:
1. **Price Rejection**: When the price reaches the resistance level and fails to break above it, moving downward instead.
2. **Bearish Candlestick Patterns**: Patterns like shooting stars or bearish engulfing candles at resistance levels signal selling opportunities.
3. **Divergences**: If the price forms higher highs near resistance while an indicator (e.g., RSI) shows lower highs, it suggests weakening momentum.
---
### **Dynamic Indicators for Support and Resistance**
1. **Moving Averages**: Commonly used as dynamic support/resistance, especially the 50, 100, and 200-period moving averages.
2. **Fibonacci Retracements**: Highlight potential support and resistance levels based on mathematical ratios.
3. **Pivot Points**: Daily, weekly, or monthly pivot levels offer reliable zones for support and resistance.
---
### **Combining Buy/Sell Signals with Indicators**
To enhance accuracy, traders combine support and resistance levels with additional indicators such as:
- **RSI (Relative Strength Index)**: To confirm overbought (sell) or oversold (buy) conditions.
- **MACD (Moving Average Convergence Divergence)**: For momentum and trend reversals at key levels.
- **Volume Analysis**: To validate the strength of price movements near support or resistance.
By using support and resistance levels with these signals, traders can develop a structured approach to identifying high-probability trade setups.
Sood 2025// © AdibXmos
//@version=5
indicator('Sood Indicator V2 ', overlay=true, max_labels_count=500)
show_tp_sl = input.bool(true, 'Display TP & SL', group='Techical', tooltip='Display the exact TP & SL price levels for BUY & SELL signals.')
rrr = input.string('1:2', 'Risk to Reward Ratio', group='Techical', options= , tooltip='Set a risk to reward ratio (RRR).')
tp_sl_multi = input.float(1, 'TP & SL Multiplier', 1, group='Techical', tooltip='Multiplies both TP and SL by a chosen index. Higher - higher risk.')
tp_sl_prec = input.int(2, 'TP & SL Precision', 0, group='Techical')
candle_stability_index_param = 0.5
rsi_index_param = 70
candle_delta_length_param = 4
disable_repeating_signals_param = input.bool(true, 'Disable Repeating Signals', group='Techical', tooltip='Removes repeating signals. Useful for removing clusters of signals and general clarity.')
GREEN = color.rgb(29, 255, 40)
RED = color.rgb(255, 0, 0)
TRANSPARENT = color.rgb(0, 0, 0, 100)
label_size = input.string('huge', 'Label Size', options= , group='Cosmetic')
label_style = input.string('text bubble', 'Label Style', , group='Cosmetic')
buy_label_color = input(GREEN, 'BUY Label Color', inline='Highlight', group='Cosmetic')
sell_label_color = input(RED, 'SELL Label Color', inline='Highlight', group='Cosmetic')
label_text_color = input(color.white, 'Label Text Color', inline='Highlight', group='Cosmetic')
stable_candle = math.abs(close - open) / ta.tr > candle_stability_index_param
rsi = ta.rsi(close, 14)
atr = ta.atr(14)
bullish_engulfing = close < open and close > open and close > open
rsi_below = rsi < rsi_index_param
decrease_over = close < close
var last_signal = ''
var tp = 0.
var sl = 0.
bull_state = bullish_engulfing and stable_candle and rsi_below and decrease_over and barstate.isconfirmed
bull = bull_state and (disable_repeating_signals_param ? (last_signal != 'buy' ? true : na) : true)
bearish_engulfing = close > open and close < open and close < open
rsi_above = rsi > 100 - rsi_index_param
increase_over = close > close
bear_state = bearish_engulfing and stable_candle and rsi_above and increase_over and barstate.isconfirmed
bear = bear_state and (disable_repeating_signals_param ? (last_signal != 'sell' ? true : na) : true)
round_up(number, decimals) =>
factor = math.pow(10, decimals)
math.ceil(number * factor) / factor
if bull
last_signal := 'buy'
dist = atr * tp_sl_multi
tp_dist = rrr == '2:3' ? dist / 2 * 3 : rrr == '1:2' ? dist * 2 : rrr == '1:4' ? dist * 4 : dist
tp := round_up(close + tp_dist, tp_sl_prec)
sl := round_up(close - dist, tp_sl_prec)
if label_style == 'text bubble'
label.new(bar_index, low, 'BUY', color=buy_label_color, style=label.style_label_up, textcolor=label_text_color, size=label_size)
else if label_style == 'triangle'
label.new(bar_index, low, 'BUY', yloc=yloc.belowbar, color=buy_label_color, style=label.style_triangleup, textcolor=TRANSPARENT, size=label_size)
else if label_style == 'arrow'
label.new(bar_index, low, 'BUY', yloc=yloc.belowbar, color=buy_label_color, style=label.style_arrowup, textcolor=TRANSPARENT, size=label_size)
label.new(show_tp_sl ? bar_index : na, low, 'TP: ' + str.tostring(tp) + ' SL: ' + str.tostring(sl), yloc=yloc.price, color=color.gray, style=label.style_label_down, textcolor=label_text_color)
if bear
last_signal := 'sell'
dist = atr * tp_sl_multi
tp_dist = rrr == '2:3' ? dist / 2 * 3 : rrr == '1:2' ? dist * 2 : rrr == '1:4' ? dist * 4 : dist
tp := round_up(close - tp_dist, tp_sl_prec)
sl := round_up(close + dist, tp_sl_prec)
if label_style == 'text bubble'
label.new(bear ? bar_index : na, high, 'SELL', color=sell_label_color, style=label.style_label_down, textcolor=label_text_color, size=label_size)
else if label_style == 'triangle'
label.new(bear ? bar_index : na, high, 'SELL', yloc=yloc.abovebar, color=sell_label_color, style=label.style_triangledown, textcolor=TRANSPARENT, size=label_size)
else if label_style == 'arrow'
label.new(bear ? bar_index : na, high, 'SELL', yloc=yloc.abovebar, color=sell_label_color, style=label.style_arrowdown, textcolor=TRANSPARENT, size=label_size)
label.new(show_tp_sl ? bar_index : na, low, 'TP: ' + str.tostring(tp) + ' SL: ' + str.tostring(sl), yloc=yloc.price, color=color.gray, style=label.style_label_up, textcolor=label_text_color)
alertcondition(bull or bear, 'BUY & SELL Signals', 'New signal!')
alertcondition(bull, 'BUY Signals (Only)', 'New signal: BUY')
alertcondition(bear, 'SELL Signals (Only)', 'New signal: SELL')
Volume Footprint POC for Every CandleCalculating and plotting the Point of Control (POC) for every candle on a volume footprint chart can provide valuable insights for traders. Here are some interpretations and uses of this information:
1. Identify Key Price Levels
Highest Traded Volume: The POC represents the price level with the highest traded volume for each candle. This level often acts as a significant support or resistance level.
Confluence Zones: When multiple POCs align at similar price levels over several candles, it indicates strong support or resistance zones.
2. Gauge Market Sentiment
Buyer and Seller Activity: High volume at certain price levels can indicate where buyers and sellers are most active. A rising POC suggests stronger buying activity, while a falling POC suggests stronger selling activity.
Volume Profile: Analyzing the volume profile helps in understanding the distribution of traded volume across different price levels, providing insights into market sentiment and potential reversals.
3. Spot Trends and Reversals
Trend Continuation: Consistent upward or downward shifts in POC levels can indicate a trend continuation. Traders can use this information to stay in trending positions.
Reversal Signals: A sudden change in the POC direction may signal a potential reversal. This can be used to take profits or enter new positions.
4. Intraday Trading Strategies
Short-Term Trading: Intraday traders can use the POC to make informed decisions on entry and exit points. For example, buying near the POC during an uptrend or selling near the POC during a downtrend.
Scalping Opportunities: High-frequency traders can use shifts in the POC to scalp small profits from price movements around these key levels.
5. Volume-Based Indicators
Confirmation of Other Indicators: The POC can be used in conjunction with other technical indicators (e.g., moving averages, RSI) to confirm signals and improve trading accuracy.
Support and Resistance: Combining the POC with traditional support and resistance levels can provide a more comprehensive view of the market dynamics.
In summary, the Point of Control (POC) is a valuable tool for traders to understand market behavior, identify key levels, and make more informed trading decisions. If you have specific questions or need further details on how to use this information in your trading strategy, feel free to ask! 😊
Multi-Timeframe Trend and Market StructureThis indicator can be used to write on your graph the trend direction on 15m, 1h, 4h , daily timeframes
Pure Shadow Check with Rangeyou can set the trading range and set shadow percentage if the candle back and close in the trading range you can buy or sell in momentum trend
DF - Pivot S/R Lines**DF - Pivot S/R Lines**
**Description:**
The "DF - Pivot S/R Lines" indicator dynamically identifies key support and resistance levels using advanced pivot detection algorithms. It calculates pivot points over a configurable timeframe (e.g., 60-minute, daily) and uses factors such as price proximity, touch counts, and expiration periods to determine significant levels.
**Key Features:**
- **Customizable Timeframe:** Select the timeframe for pivot calculations to suit your trading strategy.
- **Configurable Parameters:** Adjust sensitivity with inputs for left/right bars, minimum touches, line proximity percentage, and expiration days.
- **Dynamic Level Drawing:** Automatically draws support/resistance lines on the chart when conditions are met.
- **Alert Notifications:** Generates alerts when the price nears a key pivot level, helping you catch potential reversal or breakout opportunities.
- **Pivot Expiration:** Pivots older than a specified number of days are removed, keeping the chart relevant and uncluttered.
**Usage:**
Once added to your TradingView chart, the indicator will plot dynamic support and resistance lines based on historical price action. Users can adjust input parameters to fine-tune the sensitivity and timeframe of the pivot detection. Alerts notify traders when the price approaches these key levels, facilitating timely decision-making.
This tool is ideal for traders looking to identify and react to critical support and resistance zones using a robust pivot analysis.
Jaakko's Keltner StrategyA version of the Keltner Channel's strategy. Only taking long entries because they perform better. No shorts adviced. Performs very well on cryptos and stocks, where is more volatility included. Beats buy and hold strategy in 70% of US stocks in 30 minutes interval.
Fear and Greed Trading Strategy by EquithPath (Dev Hunainmq)Description:
🚀 **Fear and Greed Trading Strategy for TradingView** 🚀
Take your trading to the next level with this innovative and automated **Fear and Greed Index-based strategy**. 🎯 This strategy leverages the powerful **emotional drivers of the market**—fear and greed—to help you make smarter, data-driven trading decisions. Designed for traders of all experience levels, this tool provides seamless buy and sell signals to capitalize on market sentiment.
🔴 **Fear Zone:** Automatically triggers a sell when the market sentiment shifts toward extreme fear, signaling potential downturns.
🟢 **Greed Zone:** Automatically triggers a buy when the market sentiment trends toward extreme greed, signaling potential growth opportunities.
---
### **Features:**
✅ **Dynamic Buy and Sell Signals:** Executes trades automatically based on sentiment thresholds.
✅ **Position Management:** Trades a fixed quantity (e.g., 100 shares) for simplicity and risk control.
✅ **Threshold Customization:** Adjust fear and greed levels (default: 25 for fear, 75 for greed) to suit your trading style.
✅ **Visual Cues:** Clear labels and visual plots of the Fear and Greed Index on the chart for easy interpretation.
✅ **Fully Automated Execution:** Hands-free trading when connected to a supported broker in TradingView.
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### **Who Is This Strategy For?**
📈 Crypto Traders
📈 Stock Traders
📈 Forex Traders
📈 Anyone looking to incorporate **market psychology** into their trading!
With sleek design and powerful automation, this strategy ensures you stay ahead of the market by aligning your trades with the ebb and flow of investor sentiment. Whether you're a beginner or an experienced trader, this strategy simplifies the process and enhances your edge. 💡
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### Hashtags:
#TradingStrategy #FearAndGreedIndex #MarketSentiment #TradingAutomation #AlgorithmicTrading #CryptoTrading #StockMarket #ForexTrading #TechnicalAnalysis #SmartTrading #TradingTools #EmotionalTrading #GreedZone #FearZone #TradingSuccess #PineScript
NK-Heikin-ashi entry with defined Target and SL//Buy - Green heikin-ashi (with no lower shadow) is formed above vwap and Target at 50 pts and sqr off at cost.Exit at 15:01 if not //closed by then.
//Sell - Red heikin-ashi (with no upper shadow) is formed below vwap and Target at 50 pts and sqr off at cost.Exit at 15:01 if not //closed by then.
// need to update the code for trailing SL and fine tuning of Target for ATR Or ATR/2 or 40 pts for Nifty, etc..
Price Action Indicator with ATRPrice Action Indicator with ATR. This using engulfing candles as a signal to get in the market
Arif MumcuMum Kalıplarını Tanımlar:
Yükseliş Yutan Mum (Bullish Engulfing): Önceki mum düşüş, sonraki mum yükseliş ve sonraki mum öncekini tamamen "yutar".
Düşüş Yutan Mum (Bearish Engulfing): Önceki mum yükseliş, sonraki mum düşüş ve sonraki mum öncekini tamamen "yutar".
Çekiç (Hammer): Küçük gövde, uzun alt gölge, düşük seviyede oluşur (yükseliş sinyali).
Ters Çekiç (Inverted Hammer): Küçük gövde, uzun üst gölge, düşük seviyede oluşur (yükseliş sinyali).
Al-Sat Sinyalleri Üretir:
Al Sinyali: Yükseliş yutan mum veya çekiç oluştuğunda.
Sat Sinyali: Düşüş yutan mum oluştuğunda.
Grafik Üzerinde Gösterir:
Kapanış fiyatını çizerek, al-sat sinyallerini yeşil (al) ve kırmızı (sat) işaretlerle gösterir.
Micropullback Detector w/ Stop Buy & Exits (1 min)**Micropullback Trading Strategy**
This strategy is designed for day traders on the 1-minute chart, identifying high-probability pullback entries within an upward trend. It starts with detecting a **large green candle** with **high relative volume** (based on a volume SMA and ATR filter) as the wave initiation point. The pullback phase follows, requiring shallow retracements (less than 50% of the move) with controlled volume (red candle volume below the largest green candle) and no more than 3 consecutive red candles. An **entry signal** is triggered when a green candle breaks above the high of the previous candle during the pullback.
Risk management includes a **stop-loss** set slightly (2 ticks) below the lowest point of the pullback and a **take-profit** at a 1:2 risk-to-reward ratio. The strategy dynamically tracks wave metrics such as start price, highest price, and largest green volume to ensure accurate pullback validation. Visual markers include blue diamonds for large green candles and green arrows for entry signals.
Leveraging 1-minute charts, the strategy provides granular insights and real-time alerts for timely execution. It’s perfect for intraday momentum traders looking for precise entries and disciplined risk management.
4 Bar FractalThis indicator is a simple yet powerful tool that tracks potential trend reversals by checking whether the closing price of the last candle in a four-candle sequence finishes above or below the highs or lows of both the immediately preceding candle and the first candle in that sequence. If the closing price breaks above those prior highs, a green triangle appears above the chart to indicate bullish momentum; if it breaks below those lows, a red triangle appears below the chart to signal bearish momentum. Not only is it beneficial for scalping or other short-term trading, but it also works well for swing trades and longer-term trends, making it one of the most effective indicators for catching significant market shifts. However, to avoid false breakouts, it is advisable to confirm signals with volume or additional trend indicators and to maintain disciplined risk management.
Improved Combined Trading StrategiesThis script is a comprehensive Pine Script strategy designed for TradingView that combines multiple trading strategies and indicators into one
Vwap and Super Trend by Trade Partners//@version=5
indicator(title='Vwap and Super Trend by Trade Partners', shorttitle='Suresh', overlay=true)
ha_t = syminfo.ticker
// Credits goes to Options scalping
// === VWAP ===
_isVWAP = input(true, '─────── Enable VWAP ─────')
src = input(title='Source', defval=hlc3)
t = time('D')
start = na(t ) or t > t
sumSrc = src * volume
sumVol = volume
sumSrc := start ? sumSrc : sumSrc + sumSrc
sumVol := start ? sumVol : sumVol + sumVol
// You can use built-in vwap() function instead.
plot(_isVWAP ? sumSrc / sumVol : na, title='VWAP', color=color.new(color.red, 0), linewidth=2)
// === SuperTrend ===
_isSuperTrend = input(true, '─────── Enable SuperTrend ─────')
Factor = input.int(2, minval=1, maxval=100)
Pd = input.int(10, minval=1, maxval=100)
Up = hl2 - Factor * ta.atr(Pd)
Dn = hl2 + Factor * ta.atr(Pd)
Trend = 0.0
TrendUp = 0.0
TrendDown = 0.0
TrendUp := close > TrendUp ? math.max(Up, TrendUp ) : Up
TrendDown := close < TrendDown ? math.min(Dn, TrendDown ) : Dn
Trend := close > TrendDown ? 1 : close < TrendUp ? -1 : nz(Trend , 1)
Tsl = Trend == 1 ? TrendUp : TrendDown
linecolor = Trend == 1 ? color.green : color.red
plot(_isSuperTrend ? Tsl : na, color=linecolor, style=plot.style_line, linewidth=2, title='SuperTrend', transp=1)
// === Parabolic SAR ===
_isPSAR = input(true, '──── Enable Parabolic SAR ─────')
start1 = input(0.02)
increment = input(0.02)
maximum = input(0.2)
out = ta.sar(start1, increment, maximum)
plot(_isPSAR ? out : na, title='PSAR', style=plot.style_cross, color=color.new(color.black, 0))
// === 20 VWMA ===
_isVWMA = input(true, '──── Enable 20 VWMA ─────')
plot(_isVWMA ? ta.vwma(close, 20) : na, title='VWMA', style=plot.style_line, color=color.new(color.blue, 0))
// === Strong Volume ===
ShowHighVolume = input(true, '──── Enable High Volume Indicator ─────')
Averageval = input.int(title='Average Volume: (in K)', defval=50, minval=1)
Averageval *= 1000
varstrong = ShowHighVolume ? volume > Averageval : false
plotshape(varstrong, style=shape.square, location=location.bottom, color=color.new(color.blue, 0))
Micropullback (10s trigger 1min setup)**Micropullback Trading Strategy**
This strategy is designed for day traders on the 1-minute chart, identifying high-probability pullback entries within an upward trend. It starts with detecting a **large green candle** with **high relative volume** (based on a volume SMA and ATR filter) as the wave initiation point. The pullback phase follows, requiring shallow retracements (less than 50% of the move) with controlled volume (red candle volume below the largest green candle) and no more than 3 consecutive red candles. An **entry signal** is triggered when a green candle breaks above the high of the previous candle during the pullback.
Risk management includes a **stop-loss** set slightly (2 ticks) below the lowest point of the pullback and a **take-profit** at a 1:2 risk-to-reward ratio. The strategy dynamically tracks wave metrics such as start price, highest price, and largest green volume to ensure accurate pullback validation. Visual markers include blue diamonds for large green candles and green arrows for entry signals.
Leveraging partial 1-minute data on 10-second charts, the strategy provides granular insights and real-time alerts for timely execution. It’s perfect for intraday momentum traders looking for precise entries and disciplined risk management.
EMA Crossover Strategy//@version=5
strategy("EMA Crossover Strategy", overlay=true)
// Define the length of EMAs
ema50Length = 50
ema200Length = 200
// Calculate the EMAs
ema50 = ta.ema(close, ema50Length)
ema200 = ta.ema(close, ema200Length)
// Plot the EMAs on the chart
plot(ema50, title="50 EMA", color=color.green, linewidth=2)
plot(ema200, title="200 EMA", color=color.red, linewidth=2)
// Define the crossover condition
longCondition = ta.crossover(ema50, ema200)
shortCondition = ta.crossunder(ema50, ema200)
// Generate alerts
alertcondition(longCondition, title="Buy Signal", message="50 EMA is above 200 EMA - Buy")
alertcondition(shortCondition, title="Sell Signal", message="50 EMA is below 200 EMA - Sell")
// Execute trades based on the conditions
if (longCondition)
strategy.entry("Buy", strategy.long)
if (shortCondition)
strategy.close("Buy")
