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Spearman Correlation🔗 Spearman Correlation – Ranked Relationship Tracker Overview: This indicator calculates and plots the Spearman Rank Correlation Coefficient between the current chart’s asset and a custom comparison ticker (the example shown is BTC vs the OTHERS market cap for crypto). Unlike Pearson correlation, which measures linear relationships, Spearman correlation captures monotonic (ranked) relationships—making it better suited for analysing assets that move in sync but not necessarily in a linear fashion. 🧠 What It Does: Computes ranked correlation between two assets over a user-defined lookback period Smooths the correlation curve for better readability Visually shades the background by correlation strength and direction: 🟩 Strong Positive (+0.5 to +1) 🟨 Weak Positive (+0.1 to +0.5) ⬜ No Correlation (–0.1 to +0.1) 🟧 Weak Negative (–0.5 to –0.1) 🟥 Strong Negative (–1 to –0.5) ⚙️ User Inputs: Lookback Period: Number of bars used to calculate correlation Comparison Ticker: Choose any asset to compare against Shading Toggles: Customize which correlation zones are highlighted 📈 Use Cases: Identify evolving relationships between assets (e.g., BTC vs DXY, ETH vs SPX) Spot when assets become inversely correlated or lose correlation entirely Track regime shifts where traditional relationships break down or re-align Use alongside trend or momentum strategies to add a cross-asset confirmation layer 🔍 Interpreting the Correlation: +1 → Perfect positive (ranks match exactly) +0.5 to +1 → Strong positive relationship +0.1 to +0.5 → Weak but positive relationship –0.1 to +0.1 → Essentially uncorrelated –0.5 to –0.1 → Weak negative correlation –1 to –0.5 → Strong inverse relationship –1 → Perfect negative (rankings are completely opposite) 🧪 Technical Notes: Calculation uses ranked returns to better reflect monotonic relationships Smoothed with a simple moving average (SMA) for stability Arrays are managed internally to maintain performance and adaptability This script is ideal for traders seeking deeper insight into cross-asset dynamics, portfolio hedging, or timing divergence-based strategies.
อินดิเคเตอร์ Pine Script®
โดย aussiemcbull
Directional Comparisons - Two Tickers📊 Directional Comparisons – Two Tickers Overview: This tool allows you to visually and statistically compare the directional behaviour of any two assets on any chart timeframe. It identifies and color-codes each bar based on how both the current asset and your chosen comparison asset performed in that period (e.g., both up, both down, diverging). A statistical summary table dynamically updates in the corner of your chart, tracking the probability and streak performance of each condition. 🛠 How It Works: Each candle is analysed and color-coded based on the relationship between the current chart's asset and a comparison asset of your choice: ✅ Green – Both tickers closed higher (bullish alignment) 🔻 Red – Both tickers closed lower (bearish alignment) 🔷 Blue – Current ticker up, comparison ticker down (positive divergence) 🟧 Orange – Current ticker down, comparison ticker up (negative divergence) You can toggle each colour condition on/off independently. 📈 Statistical Table (Top Right): For the candles in the visible chart range, the indicator displays: The frequency (probability) of each condition Longest, shortest, and average streaks for each condition Average % change for both the current and comparison asset under each scenario All stats auto-update as you zoom or scroll through the chart. 🔧 User Inputs: Comparison Ticker: Choose any ticker symbol to compare against the current chart Toggle Conditions: Enable or disable individual directional conditions (color-coded) ✅ Use Cases: Spot high-probability alignment zones between two assets (e.g., BTC vs ETH, SPX vs VIX) Identify divergence opportunities for trading signals Analyse historical relationships and co-movements between assets Perform correlation streak studies directly on the chart 🔍 Notes: The script works across all timeframes (1min to monthly). Stats only consider visible bars on your chart for responsiveness. Ideal for pair traders, macro analysts, or anyone interested in cross-asset relationships.
อินดิเคเตอร์ Pine Script®
โดย aussiemcbull
Crypto Session Range 📄 INDICATOR DESCRIPTION (ENGLISH) Crypto Session Range (Custom Timezone) is a lightweight and accurate session-based indicator designed specifically for cryptocurrency markets (24/7). This indicator allows traders to define custom trading time windows using any global timezone, solving common issues found in traditional session indicators that are built for stock markets. 🔹 Key Features Custom timezone support (e.g. America/Puerto_Rico, America/New_York, UTC) Up to 3 configurable trading sessions Visual background highlighting during active sessions Automatic High & Low range tracking for each session Optional range extension after the session ends Works on all crypto pairs and timeframes 🔹 Who Is This For? Crypto traders who want precise session control Day traders, scalpers, and session-based strategies Traders who operate during specific market windows (London / NY / custom) 🔹 Notes This indicator is not restricted to exchange trading hours and is fully compatible with 24/7 markets like crypto, unlike many default session tools.
อินดิเคเตอร์ Pine Script®
โดย YanzaCrypto
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')
อินดิเคเตอร์ Pine Script®
โดย nomanahmad6041
Adaptive Log Trend Zones + Retest SignalsAdaptive Log Trend Zones + Retest Signals Adaptive Log Trend Zones is a trend-following overlay built to identify high-probability breakout retests in strong market conditions. It combines logarithmic regression , volatility-adaptive behavior , and ATR-based trend zones to help traders stay aligned with dominant momentum while avoiding chop. 🔹 Core Features Logarithmic Regression Midline Uses linear regression on log price to better handle exponential market moves Produces smoother, more realistic trend structure on higher timeframes Volatility-Adaptive Lookback Automatically expands or contracts the regression length based on ATR volatility Reacts faster in high volatility, smoother in consolidation Dynamic Trend Zones Upper and lower bands are ATR-adjusted and trend-colored Optional future projection for visual trend guidance Breakout → Retest Signal Logic Detects clean breakouts beyond the trend zone Waits for a controlled pullback (retest) before signaling Signals only trigger when trend strength is confirmed Trend Quality Filter Internal regime detection filters out low-quality, sideways conditions Uses slope strength and volatility compression to validate entries 🔹 Signals BUY : Bullish breakout followed by a valid retest in a trending regime SELL : Bearish breakout followed by a valid retest in a trending regime Signals are designed for trend continuation , not mean reversion. 🔹 Best Use Cases Crypto, Forex, and Index markets Higher timeframes (15m+ recommended) Trend continuation and pullback strategies ⚠️ Notes This indicator is not a standalone trading system . Always use proper risk management and confirm signals with structure, volume, or higher-timeframe context. Designed for traders who prefer structure, patience, and momentum alignment.
อินดิเคเตอร์ Pine Script®
โดย Cryptobingbong
Triple EMA + Stochastic/ADX# Triple EMA + Stochastic/ADX Breakout Indicator A professional TradingView indicator designed for trend-following and momentum breakout trading. This system uses a hierarchical confirmation process to ensure high-probability entries and robust trend maintenance. ## 🚀 Core Trading Logic: "The Setup Cycle" This indicator operates on a **Cycle-Based Logic** rather than simple crossovers. A trade cycle is defined as: 1. **The Setup (Priming)**: A Stochastic crossover (K > D for Long, D > K for Short) initiates a "Setup Mode." This is marked by a small dot (Blue for Long, Orange for Short). 2. **The Confirmation (Trend)**: The systems checks for hierarchical EMA alignment (Fast > Medium > Slow for Longs). 3. **The Trigger (Breakout)**: Once the Setup is active and EMAs are aligned, every **Price Breakout** above the previous high (X-period) triggers a continuous **BUY/SELL mark**. 4. **The Exit (Take Profit/Stop)**: The cycle and trade only end when the Fast EMA crosses back over the Medium EMA (EMA 9/21 crossover). --- ## 🛠 Features ### 1. Triple EMA System * **Hierarchical Alignment**: Requires Fast > Medium > Slow (9, 21, 50 by default) for a confirmed trend direction. * **Dynamic Trend Background**: Chart background changes color when a full EMA trend is established. ### 2. Dual Filter System (Stochastic & ADX) * **Stochastic Setup**: Uses smoothed %K and %D to identify the start of momentum cycles. * **ADX Filter**: Provides a trend-strength baseline. Default threshold is set to 20 to filter out choppy markets. ### 3. Price Breakout Confirmation * Requires price to break above/below the previous High/Low of the last X bars (default 10). * Allows for **continuous entries** within a single trend cycle. ### 4. Robust Exit Strategy * **EMA Crossover Exit**: The primary exit method. Triggers an "EXIT" flag when the trend momentum shifts. * **ATR Trailing Stop**: A secondary volatility-based stop that moves with the price. Can be set as the absolute exit or used for visual reference. ### 5. Mean Reversion Mode (Optional) * Identifies overextended price action (percent deviation from EMA2). * Signals potential "bounce" or "rejection" trades against the trend. --- ## 📊 Dashboard & Visuals * **🟢 BUY / 🔴 SELL**: Trend continuation breakout signals. * **🟠 EXIT / 🟣 EXIT**: Trend reversal/exit signals. * **🔵/🟠 Small Dots**: Setup priming moments. * **Real-time Dashboard**: Displays current Setup Status, EMA Alignment, Breakout status, ADX strength, and calculated Stop levels. --- ## ⚙️ How to Customize | Parameter | Recommended Use | | :--- | :--- | | **Breakout Lookback** | Lower (3-5) for aggressive scalping, Higher (10-20) for conservative trends. | | **Filter Mode** | Choose "Stochastic" for momentum or "ADX" for trend strength preference. | | **ATR Multiplier** | Reduce (1.5) for tighter stops, Increase (3.0) for wider trend following. | | **Exit ONLY on EMA** | Enable to stay in trades longer; Disable to exit immediately on ATR stop hits. | --- ## 📥 Installation 1. Open your **Pine Editor** in TradingView. 2. Create a new "Indicator." 3. Copy the code from `Triple_EMA_Stochastic_ADX.pine`. 4. Click **Save** and **Add to Chart**. --- *Developed for Dhan/MCX/Futures and general Asset Trading.*
อินดิเคเตอร์ Pine Script®
โดย trade_crush
GOLD TERTIUM MGC 1mThis indicator is a visual tool for TradingView designed to help you read trend structure using EMAs and highlight potential long and short entries on the MGC 1‑minute chart, while filtering pullbacks and avoiding trades when the 200 EMA is flat. ​ It calculates five EMAs (32, 50, 110, 200, 250) and plots them in different colors so you can clearly see the moving‑average stack and overall direction. The main trend is defined by the 200 EMA: bullish when price and the fast EMAs (32 and 50) are above it with a positive slope, and bearish when they are below it with a negative slope; if the 200 EMA is almost flat, signals are blocked to reduce trading in choppy markets. ​ Entry logic looks for a pullback into the 32–50 EMA zone on the previous candle, then requires a trend‑aligned candle to trigger a signal: long when the trend is up, the previous bar retested the EMA zone, and the current bar closes above EMA 32 with a bullish body; short when the trend is down, there was a valid retest, the current bar closes below EMA 32 with a bearish body and EMA 32 is below EMA 50. On the chart, you will see colored EMAs plus green “L” triangles under bars for potential long entries and red “S” triangles above bars for potential short entries, which are meant as visual cues rather than automatic trade instructions
อินดิเคเตอร์ Pine Script®
โดย bkfeuer326
Pulsar Heatmap CVD/OBV [by Oberlunar]Pulsar Heatmap CVD/OBV is a flow/price-consensus dashboard that turns OBV, CVD and their combination blend into a compact “heatmap + bias/signal” view, with optional main-chart candle coloring and HUD overlays. What it shows The panel is split into 3 horizontal lanes (OBV / CVD / COMBO). Each lane is further split into two halves: Flow half: the normalized OBV/CVD/COMBO component (either per-bar Delta or Cumulative series). PriceΔ half: the normalized divergence between price and the lane (price unit − flow unit), highlighting when price moves with or against the flow proxy. Colors use intensity-based transparency so you can quickly spot pressure, compression, and disagreement between lanes. Core engines Normalization: Z-Score→tanh, Z-Score→clamp, MinMax, or None (unit range ≈ ). Bias engine (6 halves): builds a directional BIAS from the six components (OBV/CVD/COMBO × Flow/PriceΔ), with optional hysteresis to reduce flicker. Signal engine: triggers LONG/SHORT only on full alignment (all 6 halves agree), with confirm-bars and optional sticky behavior. ROC/Acceleration layers: optional impulse context (ROC + ACC) to gate signals and/or boost bias strength when momentum is supportive. AST filter: a strict directional filter combining volatility regime, BB expansion/contraction, MTF RSI prior and Kalman-smoothed evidence. When AST is directional, it can block opposite signals to enforce coherence. Visual tools Bias/Signal bands: top/bottom bands render BIAS strength and SIGNAL state; yellow highlights indicate disagreement/blocked states. Candle colouring (main chart): optionally colours chart candles from LaneScore / Bias / Signal / Bias+Signal (uses overlay drawing where supported). Signal labels: optional LONG/SHORT markers (with “better price than last shown” logic). Triangle HUD: right-side geometric HUD summarising OBV/CVD/COMBO consensus + disagreement cues. Timed Exhaustion / Absorption table: compact state machine that flags momentum exhaustion and absorption-like conditions using tight range + ROC/ACC behaviour. How to use Start with Lane data = Delta for faster microstructure timing; switch to Cumulative for macro context. Choose a normalisation that fits your symbol’s volatility (ZScore→tanh is usually stable). Read BIAS as the current dominant direction/strength; treat SIGNAL as the strict “all lanes aligned” confirmation. If you want stricter coherence, keep the AST filter enabled (it is integrated by design and blocks opposite-direction signals when directional). Setup 1 — Long Signal (Clean Alignment + Impulse) In this example, Pulsar Heatmap transitions into a clear long setup when the system prints a LONG SIGNAL. The key idea is simple: the indicator does not enter on “bias” alone. It waits for full alignment across the internal lanes, optionally reinforced by the ROC/Acceleration impulse layer, and only then does it confirm a signal on a closed bar (Safe Mode) Setup 2 — Short Signal After Compression (Absorption → Release) In this screenshot, the short trade idea is not coming from “red candles” alone, but from a very specific sequence: the heatmap shows a shift into bearish alignment, the system prints a SHORT SIGNAL, and the timed module confirms that the market was in a tight range while sell pressure started to dominate. Setup 3 — Neutral State (Stand-By Zone, No Trade Yet) In the following screenshot, Pulsar Heatmap is doing something very important: it is clearly saying NEUTRAL 0%. Even if, visually, price could “look” like it might resume upward, the indicator is not providing a directional edge yet. If you are already short, treat DISAGREE as a signal to take profit, tighten the stop, or scale out. Setup 4 — When similar conditions return Setup 4 — Impulse + Exhaustion conditions In this screenshot, you’re basically seeing a “timing warning” configuration. Price prints a sharp bearish extension, but Pulsar Heatmap is not presenting it as a clean continuation setup: the center read is NEUTRAL 0%, while the timed engine shows both Absorption = SHORT and Exhaustion = SHORT. That combination often means: the downside pressure was real, but the move is already in a late/fragile phase (good for managing an existing short, not for opening a new one). This tool uses available volume data from your data provider and approximates flow via OBV/CVD-style logic; results can differ across symbols/brokers and sessions. This script is for educational/analytical purposes and is not financial advice. by Oberlunar 👁️ ⭐
อินดิเคเตอร์ Pine Script®
โดย oberlunar_tr
2
EDUVEST Lorentzian ClassificationEDUVEST Lorentzian Classification - Machine Learning Signal Detection ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ ORIGINALITY This indicator enhances the original Lorentzian Classification concept by jdehorty with EduVest's visual modifications and alert system integration. The core innovation is using Lorentzian distance instead of Euclidean distance for k-NN classification, providing more robust pattern recognition in financial markets. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ WHAT IT DOES - Generates BUY/SELL signals using machine learning classification - Displays kernel regression estimate for trend visualization - Shows prediction values on each bar - Provides trade statistics (Win Rate, W/L Ratio) - Includes multiple filter options (Volatility, Regime, ADX, EMA, SMA) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ HOW IT WORKS 【Lorentzian Distance Calculation】 Unlike Euclidean distance, Lorentzian distance uses logarithmic transformation: d = Σ log(1 + |xi - yi|) This provides: - Better handling of outliers - More stable distance measurements - Reduced sensitivity to extreme values 【Feature Engineering】 The classifier uses up to 5 configurable features: - RSI (Relative Strength Index) - WT (WaveTrend) - CCI (Commodity Channel Index) - ADX (Average Directional Index) Each feature is normalized using the n_rsi, n_wt, n_cci, or n_adx functions. 【k-Nearest Neighbors Classification】 1. Calculate Lorentzian distance between current bar and historical bars 2. Find k nearest neighbors (default: 8) 3. Sum predictions from neighbors 4. Generate signal based on prediction sum (>0 = Long, <0 = Short) 【Kernel Regression】 Uses Rational Quadratic kernel for smooth trend estimation: - Lookback Window: 8 - Relative Weighting: 8 - Regression Level: 25 【Filters】 - Volatility Filter: Filters signals during extreme volatility - Regime Filter: Identifies market regime using threshold - ADX Filter: Confirms trend strength - EMA/SMA Filter: Trend direction confirmation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ HOW TO USE 【Recommended Settings】 - Timeframe: 15M, 1H, 4H, Daily - Neighbors Count: 8 (default) - Feature Count: 5 for comprehensive analysis 【Signal Interpretation】 - Green BUY label: Long entry signal - Red SELL label: Short entry signal - Bar colors: Green (bullish) / Red (bearish) prediction strength 【Trade Statistics Panel】 - Winrate: Historical win percentage - Trades: Total (Wins|Losses) - WL Ratio: Win/Loss ratio - Early Signal Flips: Premature signal changes 【Filter Recommendations】 - Enable Volatility Filter for ranging markets - Enable Regime Filter for trend confirmation - Use EMA Filter (200) for higher timeframes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ CREDITS Original Lorentzian Classification concept and MLExtensions library by jdehorty. Enhanced with visual modifications and alert integration by EduVest. License: Mozilla Public License 2.0
อินดิเคเตอร์ Pine Script®
โดย EduVest_doro
The Island RSI MasteryComplete Breakdown of the Indicator. Let me walk you through every component of this trading indicator to help you fully understand its logic and application. Overall PurposeThis indicator combines momentum analysis (RSI) with volume-based price levels to identify high-probability trading opportunities. It answers three key questions: When is momentum shifting? (RSI crossovers). Where are institutional zones? (High-volume S/R levels). Is a breakout confirmed? (Price closing beyond key levels).
อินดิเคเตอร์ Pine Script®
โดย SergioAdams85
First 15 min of Each Hour First 15 Minutes of Each Hour – Background Highlighter This indicator visually highlights the first 15 minutes of every hour by coloring the chart background. It is designed to help traders quickly identify key intraday time windows often associated with increased volatility, session opens, or strategy-specific execution periods. The highlight automatically repeats every hour and adapts to the chart’s timeframe and timezone. It works best on intraday charts (1m, 3m, 5m, 15m), where precise time-based structure is important. Key Features: Automatically marks minutes 00–14 of every hour Clean, non-intrusive background shading Fully customizable color and transparency No future bar repainting Ideal for scalping, session-based, and time-window strategies Use Cases: Identifying opening volatility each hour Time-based entries and confirmations Liquidity sweep or breakout models Algo execution timing visualization This indicator does not generate trade signals. It is a visual time-management tool intended to improve clarity and discipline in intraday trading.
อินดิเคเตอร์ Pine Script®
โดย millersetterpuppies
DEMA MACD BUY signal confirmationDEMA MACD – Trend Continuation Signals Okay I made this script and wrote this description using AI. I was inspired by the HAP MACD indicator so I made signal confirmation indicator based on that. This indicator is a momentum-based signal tool built around a DEMA MACD model. It is designed to help identify potential continuation entries within an existing trend. Important notes This indicator works best in clear uptrend conditions. It is not suitable for consolidation or downtrend markets. Higher timeframes (Daily / Weekly) generally provide more reliable signals than lower timeframes. Signals BUY Indicates a potential entry in the direction of the current trend. SELL Indicates an exit from the previous BUY. This is not a short or sell-to-open signal. Usage Use this tool as a confirmation, not as a standalone decision maker. Always consider overall market context and basic price structure. Risk management is essential. This indicator is shared for educational purposes and reflects one possible approach to trend continuation trading.
อินดิเคเตอร์ Pine Script®
โดย bilguut
2
First Candle com TargetsThis Pine Script implements a "First Candle of the Day" breakout strategy with targets: Strategy Logic: Identifies the first hourly candle of each trading day Calculates the high, low, and range (distance) of that candle Draws four horizontal levels on the chart: High level (red solid line) Low level (green solid line) Buy target (blue dashed): High + Daily Range Sell target (purple dashed): Low - Daily Range Generates signals when price breaks above/below these levels: BUY signal: When price closes ABOVE the Buy target (High + Range) SELL signal: When price closes BELOW the Sell target (Low - Range) Visualizes all levels with labels showing exact price values Key Features: Uses 1-hour timeframe Lines extend 500 bars forward from the first candle Automatic cleanup and update of levels each new day Includes alert conditions for automated trading notifications Marks the first candle of each day with a blue label Trading Approach: Breakout long when price exceeds the first candle's high by its full daily range Breakout short when price falls below the first candle's low by its full daily range The strategy assumes the first candle's range establishes intraday volatility boundaries
อินดิเคเตอร์ Pine Script®
โดย itasouza