Volume SMA 9 / 20 / 50This is real time volume average lines having option to select period of volume lines . it not only provides volume with respect to price action but also we can find out real picture of price action pressure. use it with ADX and MACD wisely . only volume spike is not confirmation some times fake breakout , so wait for confirmation and participate at breakout confirmation.
Educational
SuperTrend AI + PVSRA Full DashboardOPERATIONAL MANUAL: SuperTrend AI + PVSRA (4H Timeframe)
1. CORE STRATEGY OVERVIEW
The 4H timeframe is the "Institutional Standard." This strategy combines K-Means AI Clustering for trend detection with PVSRA (Price, Volume, Spread, Range Analysis) to identify bank maneuvers.
The goal is to enter trades only when AI trend, Institutional Volume, and Moving Average momentum align perfectly.
2. OPTIMAL 4H CONFIGURATION
AI Performance Memory: 15 to 20 (Provides trend stability against 4H noise).
Factor Range: 1.5 - 5.0 (Allows AI to scale during massive BTC/Crypto cycles).
PVSRA Climax Factor: 2.7 (The filter for significant institutional intervention).
SMA 200 (Institutional): Always active; serves as the ultimate "Bull/Bear" boundary.
3. ENTRY PROTOCOLS: "SUPER CONFLUENCE"
Entries are strictly executed upon the appearance of the SUPER CONFLUENCE label.
A. LONG SETUP (BUY)
AI Trend: The AI Trailing Stop line must be Teal (Bullish).
PVSRA Volume: A Green (Climax) or Blue (Rising) candle must be present.
The Trigger: A "SUPER CONFLUENCE BUY" tag appears (signaling a SMA 20 / AI Line crossover).
Confirmation: Higher probability if the Dashboard shows "Trend 200: ABOVE".
B. SHORT SETUP (SELL)
AI Trend: The AI Trailing Stop line must be Magenta/Red (Bearish).
PVSRA Volume: A Purple (Climax) or Orange (Rising) candle must be present.
The Trigger: A "SUPER CONFLUENCE SELL" tag appears.
Confirmation: Higher probability if the Dashboard shows "Trend 200: BELOW".
4. RISK & TRADE MANAGEMENT
ACTION 4H TIME-BASED RULE
Stop Loss Place SL behind the most recent PVSRA Climax candle wick or the AI Line.
Take Profit 1 Exit 50% at the nearest S/R Level (Red/Blue rectangles) or 1:1.5 RR.
Trailing Stop Trail the Dynamic SMA 20. Exit if the SMA 20 changes color against you.
Exit Signal Immediate exit if a Climax volume of the opposite color appears at a key level
for Me the best settings but You experiment and find yours;
ATR lenght AI :10
Factor range min 2 max 5
Step 1
Perfor.Mem.10
Source : Best
Volume Period 10
Climax 2.5
Multiplier Rising 1.5
Thank you all and happy trading
Micro Futures Risk Calculator (Minimal)risk calculator based off of stop distance. to keep risk consistent for consistent growth
Adaptive For LoopThe Adaptive For Loop is a new advanced trend following tool that can avoid false signals while keeping a high speed.
Benefits
- Good speed
- Low noise
- High Performance on INDEX:BTCUSD
- Plotting for clear visualization of trend and values.
The Idea
Before I tried using a For Loop on a singular piece of source - but every source was noisy in different parts and was not really that good.
So I got an idea: How about I make a for loop on all of them (open, high, low, close) and filter them to get the best out of all worlds?
How it works
Calculate the For Loop for open, high, low, close -> a For Loop compares the current value to past values and scores it accordingly.
After calculating them, it picks the one with the highest absolute value. This means only the for loop with the highest strength gets applied. This filters noise and provides users with high speed even in the environments that do not support it.
Enjoy Gs!
Trap longs - Hamza Naveed// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
//@version=5
indicator("Trap Longs - Hamza Naveed", max_labels_count = 500, overlay = false, format = format.volume)
g1 = '📊 Net Positions '
g2 = '📈 Moving Averages (VWMA/EMA) '
g3 = '⚙️ Additional Settings '
g4 = '🎚️ Profile '
g5 = '🖥️ Statistics '
g6 = '⚖️ Divergences'
// User inputs - General settings
dtype = input.string('Net Positions', 'Type', options = )
disp = input.string('Candles', 'Display as', options = )
cumu = input.string('Full Data', 'Cumulation', options = )
denom = input.string('Quote Currency', 'Quoted in', options = )
// User inputs - Data Source Settings
binance = input.bool(true, 'Binance USDT.P', inline = 'src')
binance2 = input.bool(true, 'Binance USD.P', inline = 'src')
binance3 = input.bool(true, 'Binance BUSD.P', inline = 'src2')
bitmex = input.bool(true, 'BitMEX USD.P', inline = 'src2')
bitmex2 = input.bool(true, 'BitMEX USDT.P ', inline = 'src3')
kraken = input.bool(true, 'Kraken USD.P', inline = 'src3')
// User inputs - Net Positions
showL = input.bool(true, 'NET LONGS ►', group = g1, inline='l')
showS = input.bool(false, 'NET SHORTS ►', group = g1, inline='s')
showD = input.bool(false, 'NET DELTA ►', group = g1, inline='d')
showR = input.bool(false, 'NET RATIO ►', group = g1, inline='r')
pcolL = input.color(#a5d6a7, '', group = g1, inline = 'l')
ncolL = input.color(#f77c80, '', group = g1, inline = 'l')
lcolL = input.color(#a5d6a7, '━', group = g1, inline = 'l')
pcolS = input.color(#a5d6a7, '', group = g1, inline = 's')
ncolS = input.color(#f77c80, '', group = g1, inline = 's')
lcolS = input.color(#faa1a4, '━', group = g1, inline = 's')
pcolD = input.color(#a5d6a7, '', group = g1, inline = 'd')
ncolD = input.color(#f77c80, '', group = g1, inline = 'd')
lcolD = input.color(#90bff9, '━', group = g1, inline = 'd')
pcolR = input.color(#a5d6a7, '', group = g1, inline = 'r')
ncolR = input.color(#f77c80, '', group = g1, inline = 'r')
lcolR = input.color(#f9d690, '━', group = g1, inline = 'r')
// User inputs - Net Positions EMAs
mat = input.string('VWMA', 'Type', options= , group=g2)
emaL = input.bool(false, 'LONGS ', group=g2, inline='emal')
emaS = input.bool(false, 'SHORTS ', group=g2, inline='emas')
emaD = input.bool(false, 'DELTA ',group=g2, inline='emad')
emaR = input.bool(false, 'RATIO ',group=g2, inline='emar')
emaLl = input.int(100, '', group=g2, inline='emal')
emaSl = input.int(100, '', group=g2, inline='emas')
emaDl = input.int(100, '', group=g2, inline='emad')
emaRl = input.int(100, '', group=g2, inline='emar')
emaLc = input.color(color.rgb(165, 214, 167, 60), '', group=g2, inline='emal')
emaSc = input.color(color.rgb(250, 161, 164, 60), '', group=g2, inline='emas')
emaDc = input.color(color.rgb(144, 191, 249, 60), '', group=g2, inline='emad')
emaRc = input.color(color.rgb(249, 214, 144, 60), '', group=g2, inline='emar')
// User inputs - Additional settings
volhm = input.bool(false, 'Volume HM', group=g3, inline='vol')
volc2 = input.color(color.rgb(49, 121, 245),'', group=g3, inline = 'vol')
offs = input.int (10, 'Label Offset', group=g3)
length = input.int (14, 'Position RSI Length', group=g3)
vlbl = input.bool(true, 'Value Labels', group=g3, inline='lv')
nlbl = input.bool(true, 'Data Labels', group=g3, inline='lv')
wick = input.bool(false, 'Show Candle Wicks', group=g3)
// User inputs - Profile settings
prof = input.bool (false, 'Generate a profile', group=g4)
profsrc = input.string('Net Longs', 'Profile Data', options = , group=g4)
vapct = input.float (70, 'Value Area %', minval = 5, maxval = 95, group = g4)
ori = input.string("Left", 'Position', options = , group = g4)
profSize = input.int (2, 'Node Size', minval = 1, group = g4)
rows = input.int (40, 'Rows', minval = 6, maxval = 500, step = 25, group = g4) - 1
vancol = input.color (color.new(color.blue, 75), 'Node Colors ', group = g4, inline = 'nc')
nvancol = input.color (color.new(color.gray, 75), '━', group = g4, inline = 'nc')
poc = input.bool (false, 'POC', group = g4, inline = 'POC'),
poccol = input.color (color.new(color.red, 50), ' ', group = g4, inline = "POC")
val = input.bool (false, 'VA', group = g4, inline = "VA")
vafill = input.color (color.new(color.blue, 95), ' ', group = g4, inline = 'VA')
// User inputs - Statistics
stats = input.bool(false, 'Show Stats', group = g5)
chg_b = input.int(50, 'Bars Back', group = g5)
tablevpos = input.string('Horizontal', 'Orientation', options= , group = g5)
tablepos = input.string('Bottom Center', 'Position', options= , group = g5)
stat_oi = input.bool(true, 'OI ━', group = g5, inline = 'oi')
stat_nl = input.bool(true, 'NL ━', group = g5, inline = 'nl')
stat_ns = input.bool(true, 'NS ━', group = g5, inline = 'ns')
stat_nd = input.bool(true, 'ND ━', group = g5, inline = 'nd')
stat_oi_c = input.bool(true, 'OI Change ━', group = g5, inline = 'oi')
stat_nl_c = input.bool(true, 'NL Change ━', group = g5, inline = 'nl')
stat_ns_c = input.bool(true, 'NS Change ━', group = g5, inline = 'ns')
stat_nd_c = input.bool(true, 'ND Change ━', group = g5, inline = 'nd')
stat_oi_r = input.bool(true, 'OI RSI', group = g5, inline = 'oi')
stat_nl_r = input.bool(true, 'NL RSI', group = g5, inline = 'nl')
stat_ns_r = input.bool(true, 'NS RSI', group = g5, inline = 'ns')
stat_nd_r = input.bool(true, 'ND RSI', group = g5, inline = 'nd')
// User inputs - Divergence Finder
showdiv = input.bool(false, 'Divergence finder', group = g6)
divsrc = input.string('Net Longs', 'Source', options = , group=g6)
pivotDistance = input.int(5, 'Maximum Distance', minval=0, group=g6)
leftPivot = input.int(8, 'Lookback Bars Left', minval=1, group=g6)
rightPivot = input.int(8, 'Lookback Bars Right', minval=1, group=g6)
pHH_npLH = input.bool(true, 'Price HH + Data LH', group = g6, inline='div1')
pLH_npHH = input.bool(true, 'Price LH + Data HH', group = g6, inline='div2')
pLL_npHL = input.bool(true, 'Price LL + Data HL ', group = g6, inline='div3')
pHL_npLL = input.bool(true, 'Price HL + Data LL ', group = g6, inline='div4')
pHH_npLHcol = input.color(color.red, '', group = g6, inline='div1')
pLH_npHHcol = input.color(color.red, '', group = g6, inline='div2')
pLL_npHLcol = input.color(color.green, '', group = g6, inline='div3')
pHL_npLLcol = input.color(color.green, '', group = g6, inline='div4')
// Getting OI data
mex = syminfo.basecurrency=='BTC' ? 'XBT' : string(syminfo.basecurrency)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'BUSD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('KRAKEN' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
deltaOI = (binance ? nz(oid1,0) : 0) + (binance2 ? nz(oid2,0)/close : 0) + (binance3 ? nz(oid3,0) : 0) + (bitmex ? nz(oid4,0)/close : 0) + (bitmex2 ? nz(oid5,0)/close : 0) + (kraken ? nz(oid6,0)/close : 0)
OI = (binance ? nz(oi1,0) : 0) + (binance2 ? nz(oi2,0)/close : 0) + (binance3 ? nz(oi3,0) : 0) + (bitmex ? nz(oi4,0)/close : 0) + (bitmex2 ? nz(oi5,0)/close : 0) + (kraken ? nz(oi6,0)/close : 0)
// Conditions for positions entering and exiting
priceUP = close>open
priceDOWN = close0
oiDOWN = deltaOI<0
newlongs = oiUP and priceUP
rektlongs = oiDOWN and priceDOWN
newshorts = oiUP and priceDOWN
rektshorts = oiDOWN and priceUP
// Visible range
vrc = cumu=='Visible Range' ? time > chart.left_visible_bar_time and time <= chart.right_visible_bar_time : true
// Cumulation of positions entering and exiting
longs_entering = ta.cum(newlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
longs_exiting = ta.cum(rektlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_entering = ta.cum(newshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_exiting = ta.cum(rektshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
// Output data
net_longs = longs_entering - math.abs(longs_exiting)
net_shorts = shorts_entering - math.abs(shorts_exiting)
net_delta = net_longs - net_shorts
net_ratio = net_longs / net_shorts
// Calculating Relative Strength
longs_strength = ta.rsi(net_longs, length)
shorts_strength = ta.rsi(net_shorts, length)
delta_strength = ta.rsi(net_delta, length)
ratio_strength = ta.rsi(net_ratio, length)
oi_strength = ta.rsi(OI, length)
// Calculating candle OHLC
src = dtype=='Net Positions' ? net_longs : longs_strength
OpenL = wick ? ta.sma(src , 2) : src
HighL = ta.highest(src, 1)
LowL = ta.lowest(src, 1)
CloseL = wick ? ta.sma(src, 2) : src
src2 = dtype=='Net Positions' ? net_shorts : shorts_strength
OpenS = wick ? ta.sma(src2 , 2) : src2
HighS = ta.highest(src2, 1)
LowS = ta.lowest(src2, 1)
CloseS = wick ? ta.sma(src2, 2) : src2
src3 = dtype=='Net Positions' ? net_delta : delta_strength
OpenD = wick ? ta.sma(src3 , 2) : src3
HighD = ta.highest(src3, 1)
LowD = ta.lowest(src3, 1)
CloseD = wick ? ta.sma(src3, 2) : src3
src4 = dtype=='Net Positions' ? net_ratio : ratio_strength
OpenR = wick ? ta.sma(src4 , 2) : src4
HighR = ta.highest(src4, 1)
LowR = ta.lowest(src4, 1)
CloseR = wick ? ta.sma(src4, 2) : src4
// Calculating EMAs
Lema = mat=='EMA' ? ta.ema(src, emaLl) : ta.vwma(src, emaLl)
Sema = mat=='EMA' ? ta.ema(src2, emaSl) : ta.vwma(src2, emaSl)
Dema = mat=='EMA' ? ta.ema(src3, emaDl) : ta.vwma(src3, emaDl)
Rema = mat=='EMA' ? ta.ema(src4, emaRl) : ta.vwma(src4, emaRl)
// Conditions
lcondL = showL and (disp=='Line' or disp=='Columns'), ccondL = showL and disp=='Candles'
lcondS = showS and (disp=='Line' or disp=='Columns'), ccondS = showS and disp=='Candles'
lcondD = showD and (disp=='Line' or disp=='Columns'), ccondD = showD and disp=='Candles'
lcondR = showR and (disp=='Line' or disp=='Columns'), ccondR = showR and disp=='Candles'
// Plotting Lines
plot(lcondL ? src : na, title="Net Longs", color=disp=='Line' ? lcolL : (net_longs >0 ? pcolL : ncolL), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondS ? src2 : na, title="Net Shorts", color=disp=='Line' ? lcolS : (net_shorts >0 ? pcolS : ncolS), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondD ? src3 : na, title="Net Shorts", color=disp=='Line' ? lcolD : (net_delta >0 ? pcolD : ncolD), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondR ? src4 : na, title="Net Ratio", color=disp=='Line' ? lcolR : (net_ratio >0 ? pcolR : ncolR), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
// Plotting Candles
plotcandle(ccondL ? OpenL : na, ccondL ? HighL : na, ccondL ? LowL : na, ccondL ? CloseL : na, "Longs", CloseL>OpenL ? pcolL : ncolL, CloseL>OpenL ? pcolL : ncolL, false, bordercolor = CloseL>OpenL ? pcolL : ncolL)
plotcandle(ccondS ? OpenS : na, ccondS ? HighS : na, ccondS ? LowS : na, ccondS ? CloseS : na, "Shorts", CloseS>OpenS ? pcolS : ncolS, CloseS>OpenS ? pcolS : ncolS, false, bordercolor = CloseS>OpenS ? pcolS : ncolS)
plotcandle(ccondD ? OpenD : na, ccondD ? HighD : na, ccondD ? LowD : na, ccondD ? CloseD : na, "Delta", CloseD>OpenD ? pcolD : ncolD, CloseD>OpenD ? pcolD : ncolD, false, bordercolor = CloseD>OpenD ? pcolD : ncolD)
plotcandle(ccondR ? OpenR : na, ccondR ? HighR : na, ccondR ? LowR : na, ccondR ? CloseR : na, "Ratio", CloseR>OpenR ? pcolR : ncolR, CloseR>OpenR ? pcolR : ncolR, false, bordercolor = CloseR>OpenR ? pcolR : ncolR)
// Plotting EMAs
plot(emaL ? Lema : na, color=emaLc, editable = false)
plot(emaS ? Sema : na, color=emaSc, editable = false)
plot(emaD ? Dema : na, color=emaDc, editable = false)
plot(emaR ? Rema : na, color=emaRc, editable = false)
// Plotting Relative Strength
plot(dtype=='Position RSI' ? 100 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 100')
plot(dtype=='Position RSI' ? 70 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 70')
plot(dtype=='Position RSI' ? 50 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 50')
plot(dtype=='Position RSI' ? 30 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 30')
plot(dtype=='Position RSI' ? 0 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 0')
// Volume Heatmap
vol = volume
volmax = ta.highest(volume, 50)
col = color.from_gradient(volume, 0, volmax, chart.bg_color, volc2)
plotshape(time>chart.left_visible_bar_time and volhm, style=shape.square, size=size.normal,location = location.bottom, color=col, editable = false)
// Labels
if vlbl and disp=='Candles'
vLlabel = showL ? label.new(bar_index, CloseL>OpenL ? HighL : LowL, newlongs or rektlongs ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseL>OpenL ? label.style_label_down : label.style_label_up) : na
vSlabel = showS ? label.new(bar_index, CloseS>OpenS ? HighS : LowS, newshorts or rektshorts ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseS>OpenS ? label.style_label_down : label.style_label_up) : na
vDlabel = showD ? label.new(bar_index, CloseD>OpenD ? HighD : LowD, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseD>OpenD ? label.style_label_down : label.style_label_up) : na
vRlabel = showR ? label.new(bar_index, CloseR>OpenR ? HighR : LowR, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseR>OpenR ? label.style_label_down : label.style_label_up) : na
if nlbl and disp!='Columns'
Llabel = showL ? label.new(bar_index+offs, src, 'NET LONGS', size = size.tiny, color=lcolL, textcolor = color.black, style = label.style_label_left) : na
Slabel = showS ? label.new(bar_index+offs, src2, 'NET SHORTS', size = size.tiny, color=lcolS, textcolor = color.black, style = label.style_label_left) : na
Dlabel = showD ? label.new(bar_index+offs, src3, 'NET DELTA', size = size.tiny, color=lcolD, textcolor = color.black, style = label.style_label_left) : na
Rlabel = showR ? label.new(bar_index+offs, src4, 'NET RATIO', size = size.tiny, color=lcolR, textcolor = color.black, style = label.style_label_left) : na
label.delete(Llabel )
label.delete(Slabel )
label.delete(Dlabel )
label.delete(Rlabel )
// Generating a profile - Code from @KioseffTrading's "Profile Any Indicator" script (used with their permission)
srcp = profsrc=='Net Longs' ? src : profsrc=='Net Shorts' ? src2 : profsrc=='Net Delta' ? src3 : src4
var int timeArray = array.new_int()
var float dist = array.new_float()
var int x2 = array.new_int(rows + 1, 5)
var vh = matrix.new(1, 1)
array.unshift(timeArray, math.round(time))
if prof and time >= chart.left_visible_bar_time and time <= chart.right_visible_bar_time
matrix.add_col(vh)
matrix.set(vh, 0, matrix.columns(vh) - 1, srcp)
if prof and barstate.islast
= switch ori
"Left" =>
=>
calc = (matrix.max(vh) - matrix.min(vh)) / (rows + 1)
for i = 0 to rows
array.push(dist, matrix.min(vh) + (i * calc))
for i = 1 to matrix.columns(vh) - 1
for x = 0 to array.size(dist) - 1
if matrix.get(vh, 0, i) >= matrix.get(vh, 0, i - 1)
if array.get(dist, x) >= matrix.get(vh, 0, i - 1) and array.get(dist, x) <= matrix.get(vh, 0, i)
array.set(x2, x, array.get(x2, x) + profSize)
else
if array.get(dist, x) >= matrix.get(vh, 0, i) and array.get(dist, x) <= matrix.get(vh, 0, i - 1)
array.set(x2, x, array.get(x2, x) + profSize)
boc = array.new_box()
for i = 1 to rows
right = array.get(timeArray, n + array.get(x2, i))
if ori == "Left"
switch math.sign(n - array.get(x2, i))
-1 => right := chart.right_visible_bar_time
=> right := array.get(timeArray, n - array.get(x2, i))
array.push(boc, box.new(pos, array.get(dist, i - 1),
right, array.get(dist, i), xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
if i == rows
array.push(boc, box.new(pos, array.get(dist, array.size(dist) - 1),
right, array.get(dist, array.size(dist) - 1) + calc, xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
array.shift(x2), nx = array.indexof(x2, array.max(x2))
nz = nx - 1, nz2 = 0, nz3 = 0, nz4 = 0
for i = 0 to array.size(x2) - 1
if nz > -1 and nx <= array.size(x2) - 1
switch array.get(x2, nx) >= array.get(x2, nz)
true => nz2 += array.get(x2, nx), nx += 1
=> nz2 += array.get(x2, nz), nz -= 1
else if nz <= -1
nz2 += array.get(x2, nx), nx += 1
else if nx >= array.size(x2)
nz2 += array.get(x2, nz), nz -= 1
if nz2 >= array.sum(x2) * (vapct / 100)
nz3 := nx <= array.size(x2) - 1 ? nx : array.size(x2) - 1, nz4 := nz <= -1 ? 0 : nz
break
for i = nz3 to nz4
box.set_border_color(array.get(boc, i), vancol)
box.set_bgcolor(array.get(boc, i), vancol)
if poc
var pocL = line(na)
y = math.avg(box.get_top(array.get(boc, array.indexof(x2, array.max(x2)))), box.get_bottom(array.get(boc, array.indexof(x2, array.max(x2)))))
if na(pocL)
pocL := line.new(chart.left_visible_bar_time, y, chart.right_visible_bar_time, y, xloc = xloc.bar_time, color = poccol, width = 1)
else
line.set_xy1(pocL, chart.left_visible_bar_time, y)
line.set_xy2(pocL, chart.right_visible_bar_time, y)
if val
var vaup = line(na), var vadn = line(na)
ydn = box.get_bottom(array.get(boc, nz3)), yup = box.get_top(array.get(boc, nz4))
if na(vaup)
vadn := line.new(chart.left_visible_bar_time, ydn, chart.right_visible_bar_time, ydn, xloc = xloc.bar_time, color = vancol, width = 1)
vaup := line.new(chart.left_visible_bar_time, yup, chart.right_visible_bar_time, yup, xloc = xloc.bar_time, color = vancol, width = 1)
else
line.set_xy1(vadn, chart.left_visible_bar_time, ydn), line.set_xy2(vadn, chart.right_visible_bar_time, ydn)
line.set_xy1(vaup, chart.left_visible_bar_time, yup), line.set_xy2(vaup, chart.right_visible_bar_time, yup)
linefill.new(vadn, vaup, vafill)
//Generating tables for Stats
switchpos(tablepos) =>
switch tablepos
'Top Left' => position.top_left
'Top Center' => position.top_center
'Top Right' => position.top_right
'Bottom Left' => position.bottom_left
'Bottom Center' => position.bottom_center
'Bottom right' => position.bottom_right
dataTable = table.new(switchpos(tablepos), columns=15, rows=15, bgcolor=color.rgb(120, 123, 134, 56))
fill_rows(cond, txt, c, r) =>
if cond
table.cell(table_id=dataTable, column = tablevpos=='Horizontal' ? c : 0, row = tablevpos=='Horizontal' ? 0 : r, text = txt, height=0, text_color=color.white, text_halign=text.align_center, text_valign= text.align_center)
if barstate.islast and stats and dtype!='Position RSI'
txt = ' •𝗢𝗜: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI : OI*close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt2 = ' •𝗡𝗟: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt3 = ' •𝗡𝗦: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt4 = ' •𝗡𝗗: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt5 = ' •𝗢𝗜𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI-OI : (OI-OI ) * close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt6 = ' •𝗡𝗟𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs - net_longs , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt7 = ' •𝗡𝗦𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts - net_shorts , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt8 = ' •𝗡𝗗𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta - net_delta , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt9 = ' •𝗢𝗜 𝗥𝗦𝗜: ' + str.tostring(math.round(oi_strength,1))
txt10 = ' •𝗡𝗟 𝗥𝗦𝗜: ' + str.tostring(math.round(longs_strength,1))
txt11 = ' •𝗡𝗦 𝗥𝗦𝗜: ' + str.tostring(math.round(shorts_strength, 1))
txt12 = ' •𝗡𝗗 𝗥𝗦𝗜: ' + str.tostring(math.round(delta_strength, 1))
fill_rows(stat_oi, txt, 0, 0)
fill_rows(stat_nl, txt2, 1, 1)
fill_rows(stat_ns, txt3, 2, 2)
fill_rows(stat_nd, txt4, 3, 3)
fill_rows(stat_oi_c, txt5, 4, 4)
fill_rows(stat_nl_c, txt6, 5, 5)
fill_rows(stat_ns_c, txt7, 6, 6)
fill_rows(stat_nd_c, txt8, 7, 7)
fill_rows(stat_oi_r, txt9, 8, 8)
fill_rows(stat_nl_r, txt10, 9, 9)
fill_rows(stat_ns_r, txt11, 10, 10)
fill_rows(stat_nd_r, txt12, 11, 11)
// Divergence Finder
switchdivsrc(divsrc) =>
switch divsrc
'Net Longs' => src
'Net Shorts' => src2
'Net Delta' => src3
'Net Ratio' => src4
np = switchdivsrc(divsrc)
var priceHigh = array.new_float(0), var priceLow = array.new_float(0)
var priceHighIndex = array.new_int (0), var priceLowIndex = array.new_int (0)
var npHigh = array.new_float(0), var npLow = array.new_float(0)
var npHighIndex = array.new_int (0), var npLowIndex = array.new_int (0)
var priceHighTrend = 0, var priceLowTrend = 0
var npHighTrend = 0, var npLowTrend = 0
bool closeRecentHighs = false, bool closeOldHighs = false
bool closeHighs = false, bool closeRecentLows = false
bool closeOldLows = false, bool closeLows = false
curPriceHigh = ta.pivothigh(close, leftPivot, rightPivot)
curPriceLow = ta.pivotlow (close, leftPivot, rightPivot)
curnpHigh = ta.pivothigh(np, leftPivot, rightPivot)
curnpLow = ta.pivotlow (np, leftPivot, rightPivot)
if not na(curPriceHigh)
array.push(priceHigh, curPriceHigh)
array.push(priceHighIndex, bar_index-rightPivot)
if not na(curPriceLow)
array.push(priceLow, curPriceLow)
array.push(priceLowIndex, bar_index-rightPivot)
if not na(curnpHigh)
array.push(npHigh, curnpHigh)
array.push(npHighIndex, bar_index-rightPivot)
if not na(curnpLow)
array.push(npLow, curnpLow)
array.push(npLowIndex, bar_index-rightPivot)
if showdiv
if array.size(priceHigh) >= 2 and not na(curPriceHigh)
if array.get(priceHigh, array.size(priceHigh)-1) >= array.get(priceHigh, array.size(priceHigh)-2)
priceHighTrend := 1
else
priceHighTrend := -1
if array.size(priceLow) >= 2 and not na(curPriceLow)
if array.get(priceLow, array.size(priceLow)-1) >= array.get(priceLow, array.size(priceLow)-2)
priceLowTrend := 1
else
priceLowTrend := -1
if array.size(npHigh) >= 2 and not na(curnpHigh)
if array.get(npHigh, array.size(npHigh)-1) >= array.get(npHigh, array.size(npHigh)-2)
npHighTrend := 1
else
npHighTrend := -1
if array.size(npLow) >= 2 and not na(curnpLow)
if array.get(npLow, array.size(npLow)-1) >= array.get(npLow, array.size(npLow)-2)
npLowTrend := 1
else
npLowTrend := -1
if array.size(priceHighIndex) >= 2 and array.size(npHighIndex) >=2
closeRecentHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-1) - array.get(npHighIndex, array.size(npHighIndex)-1)) <= pivotDistance
closeOldHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-2) - array.get(npHighIndex, array.size(npHighIndex)-2)) <= pivotDistance
closeHighs := closeRecentHighs and closeOldHighs
if array.size(priceLowIndex) >= 2 and array.size(npLowIndex) >=2
closeRecentLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-1) - array.get(npLowIndex, array.size(npLowIndex)-1)) <= pivotDistance
closeOldLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-2) - array.get(npLowIndex, array.size(npLowIndex)-2)) <= pivotDistance
closeLows := closeRecentLows and closeOldLows
bool uptrendExhuastion = closeHighs and priceHighTrend > 0 and npHighTrend < 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool uptrendAbsorption = closeHighs and priceHighTrend < 0 and npHighTrend > 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool downtrendExhuastion = closeLows and priceLowTrend < 0 and npLowTrend > 0 and (not na(curnpLow) or not na(curPriceLow))
bool downtrendAbsorption = closeLows and priceLowTrend > 0 and npLowTrend < 0 and (not na(curnpLow) or not na(curPriceLow))
drawDiv(time1, price1, time2, price2, type) =>
dcol = type == 'Uptrend Exhuastion' ? pHH_npLHcol : type == 'Uptrend Absorption' ? pLH_npHHcol : type == 'Downtrend Exhaustion' ? pLL_npHLcol : type == 'Downtrend Absorption' ? pHL_npLLcol : na
line.new(x1=time1, y1=price1, x2=time2, y2=price2, color=dcol, width=1)
if uptrendAbsorption or uptrendExhuastion and showdiv
highTime1 = array.get(npHighIndex, array.size(npHighIndex)-1)
highPrice1 = array.get(npHigh, array.size(npHigh)-1)
highTime2 = array.get(npHighIndex, array.size(npHighIndex)-2)
highPrice2 = array.get(npHigh, array.size(npHigh)-2)
if uptrendExhuastion and pHH_npLH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Exhuastion')
if uptrendAbsorption and pLH_npHH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Absorption')
if downtrendAbsorption or downtrendExhuastion and showdiv
lowTime1 = array.get(npLowIndex, array.size(npLowIndex)-1)
lowPrice1 = array.get(npLow, array.size(npLow)-1)
lowTime2 = array.get(npLowIndex, array.size(npLowIndex)-2)
lowPrice2 = array.get(npLow, array.size(npLow)-2)
if downtrendExhuastion and pLL_npHL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Exhuastion')
if downtrendAbsorption and pHL_npLL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Absorption')
Gaps-Trendlines-CHOCH-BOS By @crypto_alphabitBINANCE:BTCUSDT
This indicator includes .....
1) Fair value gaps ...
* Bullish gaps
* Bearish gaps
* Automatically removed when the gaps filled
* Gaps color can be changed from setting
2) Recent Trend lines
* Higher trend lines ( from high to high)
* Lower trend lines ( from low to low )
* Higher trend lines breakout ( Bullish Breakout)
* Lower trend lines breakout ( bearish Breakout)
* Coloring breakout candle
* Colors can be changed from setting
* Swing lookback can be changed from setting
* Alert for Bullish Breakout
* Alert for Bearish Breakout
3) COCH & BOS
* Bullish Change of character
* Bearish change of character
* Bullish break of structure
* Bearish break of structure
* Swing lookback can be changed from setting
* Keeping specific number of last drawings
* keeping and removing exact ( CHOCH or BOS) can be managed from setting
* Colors can be changed from setting
* Alert for Bullish CHOCH
* Alert for Bearish CHOCH
* Alert for Bullish BOS
* Alert for Bearish BOS
Thank you for reading .... by @Crypto_alphabit
Range Breakout Statistics [Honestcowboy]⯁ Overview
The Range Breakout Statistics uses a very simple system to detect ranges/consolidating markets. The principle is simple, it looks for areas where the slope of a moving average is flat compared to past values. If the moving average is flat for X amount of bars that's a range and it will draw a box.
The statistics part of the script is a bit more complicated. The aim of this script is to expand analysis of trading signals in a different way than a regular backtest. It also highlights the polyline tool, one of my favorite drawing tools on the tradingview platform.
⯁ Statistics Methods
The script has 2 different modes of analyzing a trading signals strength/robustness. It will do that for 2 signals native to the script.
Upper breakout: first price breakout at top of box, before max bars (100 bars by default)
Lower breakout: first price breakout at bottom of box, before max bars
The analysis methods themselves are straightforward and it should be possible for tradingview community to expand this type of analysis to other trading signals. This script is a demo for this analysis, yet some might still find the native signals helpful in their trading, that's why the script includes alerts for the 2 native signals. I've also added a setting to disable any data gathering, which makes script run faster if you want to automate it.
For both of the analysis methods it uses the same data, just with different calculations and drawing methods. The data set is all past price action reactions to the signals saved in a matrix. Below a chart for explaining this visually.
⯁ Method 1: Averages Projection
The idea behind this is that just showing all price action that happened after signal does not give actionable insights. It's more a spaghetti jumble mess of price action lines. So instead the script averages the data out using 3 different approaches, all selectable in the settings menu.
Geometric Average: useful as it accurately reflects compound returns over time, smoothing out the impact of large gains or losses. Accounts for volatility drift.
Arithmetic Average: a standard average calculation, can be misleading in trading due to volatility drift. It is the most basic form of averaging so I included it.
Median: useful as any big volatility huge moves after a signal does not really impact the mean as it's just the middle value of all values.
These averages are the 2 lines you will find in the middle of the projection. Having a clear difference between a lower break average and upper break average price reaction can signal significance of the trading signal instead of pure chaos.
Outside of this I also included calculations for the maximum and minimum values in the dataset. This is useful for seeing price reactions range to the signal, showing extreme losses or wins are possible. For this range I also included 2 matrices of highs and lows data. This makes it possible to draw a band between the range based on closing price and the one using high/low data.
Below is a visualisation of how the averages data is shown on chart.
⯁ Method 2: Equity Simulation
This method will feel closer to home for traders as it more closely resembles a backtest. It does not include any commissions however and also is just a visualisation of price reaction to a signal. This method will simulate what would happen if you would buy at the breakout point and hold the trade for X amount of bars. With 0 being sell at same bar close. To test robustness I've given the option to visualise Equity simulation not just for 1 simulation but a bunch of simulations.
On default settings it will draw the simulations for 0 bars holding all the way to 10 bars holding. The idea behind it is to check how stable the effect is, to have further confirmation of the significance of the signal. If price simulation line moves up on average for 0 bars all the way to 10 bars holding time that means the signal is steady.
Below is a visualisation of the Equity Simulation.
⯁ Signal filtering
For the boxes themselves where breakouts come from I've included a simple filter based on the size of the box in ATR or %. This will filter out all the boxes that are larger top to bottom than the ATR or % value you setup.
⯁ Coloring of Script
The script includes 5 color themes. There are no color settings or other visual settings in the script, the script themes are simple and always have colors that work well together. Equity simulation uses a gradient based on lightness to color the different lines so it's easier to differentiate them while still upper breaks having a different color than lower breaks.
This script is not created to be used in conjunction with other scripts, it will force you into a background color that matches the theme. It's purpose is a research tool for systematic trading, to analyse signals in more depth.
Metaverse color theme:
⯁ Conclusion
I hope this script will help traders get a deeper understanding of how different assets react to their assets. It should be possible to convert this script into other signals if you know how to code on the platform. It is my intention to make more publications that include this type of analysis. It is especially useful when dealing with signals that do not happen often enough, so a regular backtest is not enough to test their significance.
TDPOWERSYS vs Market-Cap Weighted Peersfor QIC - UnCut Diamonds team..
to compare one company vs its peers bundled as basket.
editable..
EMA + PDH/PDL 2 Days [Scalping-Algo]🎯 Overview
A clean, focused scalping indicator designed for 2-minute and 4-minute stock charts. Combines trend-following EMAs with key daily support/resistance zones to identify high-probability scalp entries.
🛠️ What's Included
ComponentDescription🟡 EMA 13Fast momentum line🟣 EMA 48Medium trend filter🔴 EMA 200Major trend direction🔵 PDH/PDLPrevious day high & low zones🟠 PDH-2/PDL-22 days ago high & low zones
⏰ Session Filter
Only displays levels during regular trading hours (9:30 AM - 4:00 PM EST) to keep your chart clean during pre/post market.
📊 How to Use for Scalping
✅ Long Setup (2m/4m chart)
Price above EMA 200 (bullish bias)
Price pulls back to PDH/PDL zone or EMA 48
EMA 13 crosses above EMA 48
Enter on bounce from zone
Target: next resistance zone or 1:2 R/R
❌ Short Setup (2m/4m chart)
Price below EMA 200 (bearish bias)
Price rallies into PDH/PDL zone or EMA 48
EMA 13 crosses below EMA 48
Enter on rejection from zone
Target: next support zone or 1:2 R/R
💡 Pro Tips
TipWhy🔥 Trade the first hourMost volume & volatility🎯 Zone confluenceBest setups when PDH/PDL aligns with EMAs⚡ Quick exitsScalping = small gains, don't overstay🚫 Avoid chopSkip trades when price is stuck between zones📉 Respect EMA 200Don't long below it, don't short above it
🔵 Zone Colors Explained
Blue zones → Yesterday's high/low (stronger levels)
Orange zones → 2 days ago high/low (secondary levels)
Zone thickness → 20 ticks buffer for natural price noise
⚙️ Best Settings
TimeframeBest For2 minuteQuick scalps, 5-15 cent targets4 minuteSlightly larger moves, less noise
📌 Recommended Pairs
Works best on liquid stocks with tight spreads:
SPY, QQQ, AAPL, TSLA, AMD, NVDA, META, AMZN
⚠️ Risk Management
RuleSuggestion🛑 Stop lossBelow/above the zone (tight)🎯 Take profit1:2 or 1:3 risk/reward minimum📏 Position sizeMax 1-2% account risk per trade
🚀 Quick Start
Add indicator to 2m or 4m chart
Wait for price to reach a colored zone
Confirm trend direction with EMA 200
Look for EMA 13/48 alignment
Enter with tight stop, scale out at targets
SMA Cross + Adaptive Q MA + AMA Channel
📘 OPERATIONAL MANUAL: Adaptive Trend & SR Breakout SystemThis system combines non-parametric regression, volatility channels, and automated price action structures to identify high-probability entries.
1. Core IndicatorsAdaptive Q (KAMA): The primary trend line.
Green = Bullish;
Red = Bearish.
AMA Channel: An ATR-based envelope ($1.5 \times ATR$) that defines the "Value Area".
SMA 50 Filter: Global trend filter. Trade Long only above; Short only below.
SR Zones: Automatic boxes marking historical Support
(Blue/Green) and Resistance (Red).Shutterstock
2. Entry Rules
🟢 LONG SETUP:Price is above SMA 50.Large Lime Triangle appears (Channel Cross).Adaptive Q line is Green.Best entry: Price bounces off a Support Box.
🔴 SHORT SETUP:Price is below SMA 50.Large Red Triangle appears (Channel Cross).Adaptive Q line is Red.Best entry: Price rejects a Resistance Box.
3. Risk Management
Stop Loss: Set at $1.5 \times ATR$ or behind the nearest SR Box.
Take Profit: Target the next opposite SR Zone or exit if the Adaptive Q changes color.
4. LegendLarge Triangles: High-conviction volatility signals.
Small Triangles: Standard SMA Cross (early warning).
Red/Green Boxes: Supply and Demand zones for structural confirmation.
Aggro-15min Pro V4.2 [SMA200 + Vortex] (v6 Ready)🚀 Aggro-15min Pro
Aggro-15min Pro is a professional-grade algorithmic strategy optimized for the 15-minute timeframe. It combines structural trend analysis with aggressive momentum tracking to capture high-probability swings while filtering out market noise.
🛠️ How the Strategy Works
1. Structural Trend (The "Guardrail")
200 SMA: The strategy identifies the primary market direction. It only buys above the 200 SMA and only sells below it, ensuring you stay on the side of institutional flow.
2. Execution Trigger (The "Signal")
EMA Cross (9/50): A crossover of the 9-period Fast EMA and 50-period Slow EMA triggers the entry, identifying a confirmed shift in medium-term momentum.
3. Momentum Engine (The "Vortex")
Vortex Indicator (VI): Validates the "thrust" behind the move.
Dynamic Exit: Includes a "Vortex Reverse" logic that closes trades early if the directional energy fades, preserving capital before a full reversal occurs.
4. Risk & Volatility
ADX Filter: Prevents entries during low-volatility "sideways" periods.
ATR Risk Management: Uses the Average True Range to set dynamic Stop Loss and Take Profit levels that adapt to current market volatility.
-
-
# 📂 STRATEGY PACKAGE: AGGRO-15MIN PRO
**Version:** 4.2 (Pine Script v6 Ready)
**Asset Class:** Crypto, Forex, Indices
**Timeframe:** 15 Minutes
---
## 📘 1. OPERATIONS MANUAL (English)
### 🟢 Strategy Overview
Aggro-15min Pro is a momentum-based trend-following system. It uses a "Triple-Filter" logic to ensure that trades are only taken when long-term trend, medium-term momentum, and short-term volatility are perfectly aligned.
### 🟢 Technical Indicators Setup
* **Structural Filter:** 200-period Simple Moving Average (SMA).
* **Trigger Engine:** 9-period & 50-period Exponential Moving Averages (EMA).
* **Momentum Engine:** 14-period Vortex Indicator (VI).
* **Strength Filter:** 14-period Average Directional Index (ADX).
* **Volatility/Exits:** 14-period Average True Range (ATR).
### 🟢 Entry Checklist
#### LONG Position:
1. **Trend:** Price is **ABOVE** the 200 SMA.
2. **Trigger:** 9 EMA crosses **ABOVE** the 50 EMA.
3. **Vortex:** VIP (Positive) is **ABOVE** VIM (Negative).
4. **Strength:** ADX is **ABOVE** 20.
#### SHORT Position:
1. **Trend:** Price is **BELOW** the 200 SMA.
2. **Trigger:** 9 EMA crosses **BELOW** the 50 EMA.
3. **Vortex:** VIM (Negative) is **ABOVE** VIP (Positive).
4. **Strength:** ADX is **ABOVE** 20.
### 🟢 Exit Management
* **Take Profit (TP):** $3.0 \times ATR$ (Risk/Reward 1:2).
* **Stop Loss (SL):** $1.5 \times ATR$.
* **Dynamic Exit:** If the Vortex lines cross in the opposite direction (e.g., VIM > VIP during a Long), the strategy closes the position immediately to lock in profits or minimize loss.
---
Price Compression Scanner (Chartink Logic)Breakout above range high → BUY
🔹 Breakdown below range low → SELL
🔹 Best with volume expansion
🔹 Works well for swing trades & momentum breakouts
Highs
Highest High of last 10 days (ending 1 day agos) < Highest High of previous 10 days
Highest High of last 10 days < Highest High of earlier 10 days
➡️ Lower highs (falling resistance)
Lows
3. Lowest Low of last 10 days > Lowest Low of previous 10 days
4. Lowest Low of last 10 days > Lowest Low of earlier 10 days
Closed Source Strategy TesterAllows you to test an indicator that is closed source (you don't have access to the code). You will need to understand the exposed data elements of the indicator you are testing. This strategy is only looking for a buy, sell, exit long, or exit short to be signals that change from 0 to 1. The stop loss/take profit, if used, are expected to be price values.
I encourage you to copy this code and modify it to your needs for specific indicators.
RSI PVSRA PRO Edition# 📑 MASTER OPERATING MANUAL: Full Institutional Ecosystem (v3.0)
**Integrated Suite:** PVSRA Dashboard + SR Boxes + Order Spikes + CVD-100 + RSI PRO
---
## 1. SYSTEM HIERARCHY
This ecosystem provides a 360-degree view of the market, eliminating subjective interpretation:
1. **Bias (Dashboard):** Global market direction (Sentiment).
2. **Context (SR Boxes):** Institutional supply and demand zones (The "Where").
3. **Internal Force (CVD-100):** Aggressive money flow (The "Fuel").
4. **Momentum & Divergence (RSI PRO):** Speedometer and early-warning system for reversals.
---
## 2. COMPONENT DICTIONARY
### **A. RSI PRO (Divergences & Confluence)**
* **Bullish Divergence (Green Label):** Price makes a Lower Low, but RSI makes a Higher Low. Indicates hidden institutional accumulation.
* **Bearish Divergence (Red Label):** Price makes a Higher High, but RSI makes a Lower High. Indicates institutional distribution (unloading).
* **Safety Thresholds:** * *Safe Buy Zone (< 65):* Prevents buying into overextended markets.
* *Safe Sell Zone (> 35):* Prevents selling at absolute bottoms.
### **B. CVD-100 (Aggressive Pressure)**
* **Above 80:** Buyer exhaustion. **Below 20:** Seller exhaustion.
* **Slope:** A Lime color indicates buyers are hitting the Ask; Red indicates sellers are hitting the Bid.
### **C. PVSRA & Spikes (The Trigger)**
* **Climax Candles (Green/Magenta):** Marks the peak of professional activity.
* **Triangles (▲/▼):** Statistical confirmation of a massive order execution.
---
## 3. INTEGRATED TRADING STRATEGIES
### **Strategy A: The "Golden Pocket" Reversal (High Accuracy)**
1. **Zone:** Price enters a **Teal SR Box** (Support).
2. **Momentum:** **RSI PRO** displays a **Bullish Divergence** (Green Label).
3. **Volume:** A **Magenta Climax Candle** (PVSRA) appears.
4. **Flow:** **CVD-100** crosses above the 20 level.
5. **Trigger:** A **Buy Spike (▲)** or a **Diamond (◆)** appears.
* *Target:* Next Red Box or Dashed Recovery Line.
### **Strategy B: Momentum Breakout (Trend Following)**
1. **Bias:** Dashboard shows "STRONG BUY" + Price above SMA 200.
2. **RSI Filter:** RSI is below 65 (not yet in extreme overbought territory).
3. **Action:** Price breaks through a **Red SR Box** (Resistance) with force.
4. **Confirmation:** **CVD-100** is Lime (Buying pressure) + **RSI SMA** points upward.
* *Entry:* Close of the breakout candle.
---
## 4. ULTIMATE CONFLUENCE CHECKLIST (MANDATORY)
| Priority | Indicator | Trade Requirement |
| :--- | :--- | :--- |
| **1. Bias** | Dashboard | Must be "STRONG" in the trade direction |
| **2. Context**| SR Boxes | Price must be near a Box (Teal/Red) |
| **3. Momentum**| RSI PRO | Presence of Divergence OR RSI within thresholds (65/35) |
| **4. Internal** | CVD-100 | Slope must be aligned with the trade direction |
| **5. Trigger** | Spike Det. | Presence of Triangle (▲/▼) or Diamond (◆) |
---
## 5. RECOMMENDED TECHNICAL SETTINGS
| Indicator | Parameter | Suggested Value |
| :--- | :--- | :--- |
| **RSI PRO** | Length | 14 |
| **RSI PRO** | Confluence | 65 (Max Buy) / 35 (Min Sell) |
| **CVD-100** | Normalization| 50 (Stochastic Mode) |
| **PVSRA** | Climax Factor | 2.7 |
---
## 6. PRO TIPS & RISK MANAGEMENT
* ⚠️ **The Divergence Rule:** An RSI divergence occurring inside an **SR Box** is 3x more powerful than a divergence in a vacuum.
* ⚠️ **RSI + CVD Synergy:** If the RSI shows a bullish divergence AND the CVD-100 is rising from the 20 level, you have identified a massive institutional "floor."
* ⚠️ **Smoothing MA:** If the yellow RSI line is flat, the market is ranging. Wait for a clear slope before acting.
---
*Document created for Quantitative Trading Operations*
CVD Normalizzato (0-100)# 📑 MASTER OPERATING MANUAL: Institutional Order Flow Ecosystem (v2.0)
**Integrated Suite:** PVSRA Dashboard PRO + SR High Volume Boxes + Massive Order Spike Detector + CVD-100
---
## 1. SYSTEM HIERARCHY
This trading ecosystem is designed to decode "Smart Money" footprints. It filters retail noise to identify where institutional participants are placing massive orders.
1. **Bias (Dashboard):** Determines the overall market direction (Sentiment).
2. **Context (SR Boxes):** Identifies the price "Battlefields" (Supply & Demand).
3. **Internal Force (CVD-100):** Reveals aggressive buying/selling pressure (Market Delta).
4. **Trigger (PVSRA & Spikes):** Signals the exact moment of execution.
---
## 2. COMPONENT DICTIONARY
### A. CVD-100 (The Internal Engine)
*Reveals the aggressive pressure of buyers/sellers.*
- **Values > 80:** Aggressive buyers are dominant (Extreme Overbought).
- **Values < 20:** Aggressive sellers are dominant (Extreme Oversold).
- **Green Slope:** Aggressive buyers are increasing pressure.
- **Red Slope:** Aggressive sellers are increasing pressure.
### B. PVSRA Candles (Market Climax)
- 🟢 **Bright Green:** Bull Climax (Highest institutional activity).
- 🟣 **Magenta:** Bear Climax (Panic selling or Institutional offloading).
- 🔵 **Blue/Red:** Rising volume (Professional participation).
### C. SR Boxes & Spikes (The Execution Zones)
- **Teal/Red Boxes:** Areas where significant volume was stored.
- **Triangles (▲/▼):** "Massive Order Spike". Confirms statistical anomaly.
- **Diamonds (◆):** Confirms a level (Box) is successfully holding the price.
---
## 3. INTEGRATED STRATEGIES
### **Strategy A: Institutional Trend Follower**
- **Bias:** Dashboard shows "STRONG BUY" + Price is above SMA 200.
- **Setup:** Price breaks above a **Red Box** (Resistance).
- **Confirmation:** **CVD-100** is sloping up (Green) and a **Massive Buy Spike** (▲) appears.
- **Entry:** On the close of the breakout candle.
### **Strategy B: The Climax Reversal (The Sniper)**
- **Bias:** Price reaches a **Teal Box** (Support) after an extended drop.
- **Setup:** **CVD-100** is below 20 (Deep Oversold/Exhaustion).
- **Trigger:** A **Magenta Climax Candle** (PVSRA) appears, followed immediately by a **Green Diamond (◆)**.
- **Entry:** Long when price breaks the high of the Climax candle.
---
## 4. THE ULTIMATE CONFLUENCE CHECKLIST
| Priority | Confirmation | Indicator Tool |
| :--- | :--- | :--- |
| **1. Bias** | Is the Dashboard "STRONG" in the trade direction? | PVSRA Dashboard |
| **2. Level** | Is the price at/inside a Teal or Red Box? | SR Boxes |
| **3. Volume** | Is the candle Climax or Rising color? | PVSRA Candles |
| **4. Delta** | Is CVD-100 aligned with your direction? | CVD-100 |
| **5. Trigger**| Has a Triangle (Spike) or Diamond (Hold) appeared? | Spike Detector |
---
## 5. TECHNICAL CONFIGURATION
| Setting | Value | Goal |
| :--- | :--- | :--- |
| **PVSRA Climax Factor** | 2.7 | Filter for institutional impact only. |
| **Spike Multiplier** | 4.0 | Isolate statistical extreme volume. |
| **CVD Normalization** | 50 (Stoch) | Standardize delta for clear overbought/sold. |
| **SMA Bias** | 200 | Institutional trend filter. |
---
## 6. PRO TIPS & RISK NOTES
- ⚠️ **Divergence:** If Price makes a new high but **CVD-100** makes a lower high, the trend is exhausted. Prepare for a reversal.
- ⚠️ **News Filter:** High-impact news causes "Spikes" but invalidates "Boxes". Wait 15 mins for the market to stabilize.
- ⚠️ **Absorption:** A Climax candle with a tiny body inside a Box is "Absorption". Institutions are soaking up orders. Wait for the box breakout.
---
*Created for: Professional Trading Operations*
PVSRA Dashboard PRO [Customized]# 📘 OPERATING MANUAL: Institutional Volume Suite (v1.0)
**Integrated Systems:** PVSRA Dashboard PRO + SR High Volume Boxes + Massive Order Spike Detector
---
## 1. SYSTEM PHILOSOPHY
This ecosystem tracks **Institutional Order Flow**. The core principle is that "Smart Money" leaves undeniable footprints through abnormal volume (Spikes) and specific price zones (High Volume Boxes). The system filters retail noise to identify where "Whales" are accumulating or distributing positions.
---
## 2. VISUAL DICTIONARY & SIGNALS
### A. PVSRA & Candles (Institutional Sentiment)
| Candle Color | Signal Type | Operational Meaning |
| :--- | :--- | :--- |
| 🟢 **Bright Green** | **Bull Climax** | Maximum Volume. Strong institutional buying or "Blow-off top". |
| 🟣 **Magenta** | **Bear Climax** | Maximum Volume. Strong institutional selling or "Selling climax". |
| 🔵 **Blue** | **Bull Rising** | Above-average volume. Professional buying interest. |
| 🔴 **Red/Orange** | **Bear Rising** | Above-average volume. Professional selling interest. |
| ⚪ **Grey** | **Normal** | Retail volume. Low institutional participation. |
### B. SR Boxes & Spike Detector (The Triggers)
* **Teal Boxes:** High Volume Support (Demand Zone).
* **Red Boxes:** High Volume Resistance (Supply Zone).
* **Triangles (▲/▼):** "Massive Order Spike". Statistical confirmation of heavy entry.
* **Diamonds (◆):** Real-time confirmation that a level (Box) is "Holding."
---
## 3. THE PRO DASHBOARD (Confluence Matrix)
Always consult the top-right dashboard before executing a trade:
1. **Momentum (9/20):** Short-term direction (Green Cloud = Long, Red = Short).
2. **Trend (20/50):** Health of the intermediate trend.
3. **Inst. Trend (200):** The master filter. Above SMA 200, look for Longs only; below, Shorts only.
4. **Delta Pressure:** Shows if the actual money flow is positive (BUY) or negative (SELL).
5. **CONFLUENCE PRO:** The final verdict. "STRONG BUY/SELL" means all parameters are aligned.
---
## 4. OPERATIONAL PROTOCOL (STRATEGY)
### **Phase 1: Zone Identification**
Identify where the price is relative to the **High Volume Boxes**.
- *Long Setup:* Price enters a Teal Box or tests a dashed "Support-Flip" line.
- *Short Setup:* Price enters a Red Box or tests a dashed "Resistance-Flip" line.
### **Phase 2: The Trigger (Action)**
Wait for the coordinated appearance of signals:
1. **PVSRA Color:** The candle must turn Climax (Green/Magenta).
2. **Order Spike:** The Triangle confirmation must appear.
3. **Level Confirmation:** The Diamond (◆) appears, indicating a bounce/rejection from the zone.
### **Phase 3: Execution**
- **ENTRY:** Enter when the Dashboard shows "STRONG BUY/SELL" coinciding with Phase 2 signals.
- **STOP LOSS:** Placed behind the opposite limit of the Box or the Climax candle wick.
- **TAKE PROFIT:** Use the **Dashed Recovery Lines** or the opposite High Volume Box.
---
## 5. RECOMMENDED TECHNICAL CONFIGURATION
| Parameter | Value | Notes |
| :--- | :--- | :--- |
| **PVSRA Climax** | 2.7 | Captures only the most significant institutional moves. |
| **Spike Multiplier** | 4.0 | Filters out statistical noise. |
| **Inst. SMA** | 200 | Blue (
Support and Resistance (High Volume Boxes) [ChartPrime]# 📑 OPERATING MANUAL: Institutional Volume & SR Protocol (v1.0)
## 1. SCOPE AND CORE LOGIC
This trading suite is designed to track **Institutional Order Flow**. By combining statistical volume anomalies (Spikes) with price zones of high participation (Boxes), the system identifies where "Smart Money" is entering the market and which price levels they are likely to defend.
---
## 2. COMPONENT OVERVIEW
### **A. Massive Order Spike Detector**
Identifies momentum and exhaustion through volume standard deviation ($σ$).
* **Green/Red Triangles:** Indicate a volume event exceeding **4x** the historical average.
* **Key Use:** Acts as a **trigger** for entry.
### **B. SR High Volume Boxes**
Maps the areas where high-volume pivots occurred.
* **Teal Boxes:** High-volume Support (Buying zones).
* **Red Boxes:** High-volume Resistance (Selling zones).
* **Diamonds (◆):** Real-time confirmation that a level is "Holding."
* **Dashed Boxes:** Indicate a level has been broken and may now "flip" polarity (Support becomes Resistance).
---
## 3. SIGNAL INTERPRETATION TABLE
| Signal Type | Visual | Market Context | Action |
| :--- | :--- | :--- | :--- |
| **Buy Spike** | 🟢 Triangle | Breakout or Trend Continuation | Confirm with Support Box |
| **Sell Spike** | 🔴 Triangle | Breakdown or Trend Exhaustion | Confirm with Resistance Box |
| **Support Hold**| 🟢 Diamond | Price successfully bounced off a Teal zone | Look for Long entry |
| **Resist. Hold**| 🟠 Diamond | Price successfully rejected from a Red zone | Look for Short entry |
| **SR Break** | 🏷️ Label | A major volume zone has been breached | Wait for Retest of dashed box |
---
## 4. OPERATIONAL WORKFLOW (THE STRATEGY)
### **Step 1: Zone Identification**
Observe the **SR High Volume Boxes** to see where the "battlefields" are.
* *Neutral:* Price is between boxes.
* *Action:* Price enters a Teal (Support) or Red (Resistance) box.
### **Step 2: The Trigger (The Spike)**
Wait for the **Massive Order Spike** to appear as the price interacts with a box:
* **The Aggressive Break:** A Spike occurs *as the price breaks through* a box. This validates a strong momentum trade.
* **The Rejection:** A Spike occurs *at the edge of a box* followed by a Diamond (◆). This validates a high-probability reversal.
### **Step 3: Confirmation (The Retest)**
If a box is broken (e.g., "Break Res"), wait for the price to return to the **Dashed Box**. If a "Hold" signal (Diamond) appears on the retest, the setup is high-conviction.
---
## 5. TECHNICAL CONFIGURATION
| Parameter | Recommended Value | Purpose |
| :--- | :--- | :--- |
| **Spike Multiplier** | 4.0 - 5.0 | Filters out noise; captures only major moves. |
| **Lookback Period** | 20 | Balances between minor and major SR levels. |
| **Box Width** | 1.0 - 1.5 | Adjust based on ATR (Volatility) of the asset. |
| **Alert Type** | Once Per Bar Close | Ensures signals are confirmed by the candle close. |
---
## 6. RISK MANAGEMENT & BEST PRACTICES
1. **News Filter:** Avoid trading 5 minutes before/after high-impact news (CPI, FOMC). Spikes are guaranteed but direction is unpredictable.
Support and Resistance (High Volume Boxes) [ChartPrime]# 📘 OPERATING MANUAL: Massive Order Spike Detector (v1.0)
## 1. PURPOSE OF THE TOOL
The **Massive Order Spike Detector** is a quantitative analysis tool designed to isolate volume anomalies. By utilizing **Standard Deviation (σ)**, it identifies the exact moments when order flow exceeds statistical norms, signaling institutional intervention ("Smart Money"), high-frequency trading (HFT) activity, or market climax events.
---
## 2. TECHNICAL SPECIFICATIONS & INPUTS
The indicator calculates the ratio between current volume and its historical volatility to define "extreme" participation.
### **Configuration Settings**
* **Volume Spike Multiplier (x σ):** *Default: **4.0***
* *Function:* Sets the sensitivity threshold. A value of 4.0 triggers a signal only if the current volume is 4 times the standard deviation of the lookback period.
* **StDev Lookback Length:** *Default: **200***
* *Function:* Defines the sample size (number of bars) used to establish the "baseline" or "normal" volume.
---
## 3. SIGNAL INTERPRETATION PROTOCOL
The indicator generates real-time visual signals on the price chart:
| Signal | Graphic Icon | Technical Condition | Market Sentiment |
| :--- | :--- | :--- | :--- |
| **Massive Buy Spike** | 🟢 Lime Triangle (Below) | Vol ≥ 4σ + Close > Open | Extreme buying pressure. Potential accumulation or aggressive breakout. |
| **Massive Sell Spike** | 🔴 Red Triangle (Above) | Vol ≥ 4σ + Close < Open | Extreme selling pressure. Potential distribution or panic selling. |
---
## 4. OPERATIONAL PROCEDURES (STRATEGIES)
### **A. Breakout Validation (Trend Following)**
* **Context:** Price is testing a key Support/Resistance or a consolidation zone.
* **Trigger:** A Spike appears (Lime for Long / Red for Short) as the level is breached.
* **Execution:** The signal confirms that institutional volume is backing the move. High probability of trend continuation.
### **B. Exhaustion Climax (Mean Reversion)**
* **Context:** Price is in an extended trend (overbought/oversold).
* **Trigger:** A Spike appears in the direction of the trend, but the candle features a long wick (rejection) or a small body.
* **Execution:** This indicates a "Blow-off Top" or "Selling Climax." Traders should look to take profits or prepare for a reversal once market structure shifts.
---
## 5. ALERT MANAGEMENT
To ensure no institutional moves are missed, follow this setup for TradingView notifications:
1. Open the **"Create Alert"** panel in TradingView.
2. Select **"Massive Order Spike Detector"** as the condition.
3. Set frequency to: **"Once Per Bar Close"** (to prevent false triggers during mid-candle volatility).
4. The automated message includes the **Normalized Volume** value to gauge the magnitude of the spike.
---
## 6. RISK WARNINGS & BEST PRACTICES
⚠️ **Macro Events:** During high-impact news (e.g., NFP, CPI), spikes are common but highly volatile. Use wider stop losses or avoid entry during the first 5 minutes.
⚠️ **Low Liquidity Assets:** On "thin" charts, a 4.0 multiplier may trigger too often. Increase the multiplier to **6.0+** for better accuracy.
⚠️ **Confluence:** Never trade a spike in isolation. Always align signals with Price Action (Support/Resistance) or Trend Filters (e.g., 200 EMA).
Gold Pullback Precision ProGold Pullback Precision Pro
EMA slope + pullback strategy designed for gold scalping. Combines trend confirmation (slopes) with precise entries (pullbacks), filtered by HTF direction, volume, and RSI. Shows clear BUY/SELL signals with comprehensive dashboard.
EMA Slope + Pullback Pro IndicatorEMA Slope + Pullback Pro Indicator
Core: EMA trend analysis with automated pullback detection.
Key Features:
3-EMA Slope System (9,20,50) with trend signals
Smart Pullback Monitor with visual alerts
Complete Data Table showing all metrics
Multi-Filter System (timeframe + volume)
What It Does:
Shows EMA trends and strength
Detects price pullbacks to EMA levels
Gives entry signals at EMA support/resistance
Filters signals with higher timeframe trend
Visual:
EMA lines on chart
Pullback zones (colored)
Entry arrows
Data table with live metrics
For: Trend + pullback traders wanting automated EMA analysis.
