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指标和策略

AI - Jack & EgiScopri un approccio innovativo al trading automatizzato su BTCUSD. La nostra strategia sfrutta una logica proprietaria e algoritmi dinamici per identificare in tempo reale le opportunità di ingresso ottimali, bilanciando il potenziale profitto con una gestione del rischio sofisticata tramite livelli adattivi di stop loss e take profit. Progettata per operare in maniera autonoma, questa soluzione offre un supporto completo per il trading intraday, consentendoti di cogliere le opportunità del mercato senza la necessità di interventi manuali costanti. Ideale per trader che cercano un sistema all'avanguardia e pronto a rispondere alle sfide di un mercato in continua evoluzione.
Pine Script™策略
由egidiopalmieri提供
Estrategia: Cruce de EMAs con MACD Explicación Entradas basadas en Cruce de EMAs y MACD: Se utiliza ta.crossover(ema_fast_val, ema_slow_val) para detectar cuando la EMA rápida cruza al alza la EMA lenta. Además, se verifica que el histograma del MACD sea mayor que 0 para confirmar una tendencia alcista. De manera similar, se utiliza ta.crossunder(ema_fast_val, ema_slow_val) y se comprueba que el histograma sea negativo para una señal bajista. Salidas mediante pivotes: Se define la resistencia (máximo en un lookback) y el soporte (mínimo en un lookback) para determinar las salidas, lo que simplifica la toma de ganancias o la salida de la posición. Gestión de Riesgo: Se calcula un nivel de stop loss y take profit basado en el ATR y se muestran mediante etiquetas en el gráfico.
Pine Script™指标
由Niezhm提供
Liquidity crypt //@version=5 indicator(" 💧TFO_LVL_OI_LIQ 💧 ", " 💧TFO_LVL_OI_LIQ 💧", true, max_bars_back=5000, max_lines_count = 500, max_polylines_count = 100, max_labels_count = 500, max_boxes_count = 500) string userSymbol = 'BINANCE' + ":" + string(syminfo.basecurrency) + 'USDT.P' string Formula = str.format("{0}_OI", userSymbol) OI = request.security(Formula, timeframe.period, close) OI_delta = OI - nz(OI ) maLength = input(60, title="MA Length") numOfLines = 500 OI_delta_MA = ta.sma(OI_delta, maLength) OI_delta_abs = math.abs(OI_delta) OI_delta_abs_MA = ta.sma(OI_delta_abs, maLength) h3 = input(3.0, title="Large Liquidation Level") h2 = input(2.0, title="Middle Liquidation Level") h1 = input(1.2, title="Small Liquidation Level") OI_delta_open_h3 = (OI_delta_abs >= OI_delta_abs_MA * h3) and OI_delta > 0 OI_delta_open_h2 = (OI_delta_abs >= OI_delta_abs_MA * h2 and OI_delta_abs < OI_delta_abs_MA * h3) and OI_delta > 0 OI_delta_open_h1 = (OI_delta_abs >= OI_delta_abs_MA * h1 and OI_delta_abs < OI_delta_abs_MA * h2) and OI_delta > 0 kline_price = (open + close + high + low) / 4 showLine = input(true, title="Show lines") showHist = input(true, title="Show histgram") showLocalOnly = input(true, title="Only show local liquidation levels") i_5xColor = input.color(#626367a2, '5x Leverage color', group='5x Leverage') i_10xColor = input.color(#017cff7a, '10x Leverage color', group='10x Leverage') i_25xColor = input.color(#0dff0064, '25x Leverage color', group='25x Leverage') i_50xColor = input.color(#f0a02966, '50x Leverage color', group='50x Leverage') i_100xColor = input.color(color.rgb(218, 55, 101, 44), '100x Leverage color', group='100x Leverage') var h3Array = array.new_line() var h2Array = array.new_line() var h1Array = array.new_line() // histgram barColor = input(color.rgb(0, 55, 254, 4), "Bar Color") numOfBars = input(120, 'Number of bars to lookback') distLastCandle = input(5, 'Histgram distance from last candle') local_high = ta.highest(high, numOfBars) local_low = ta.lowest(low, numOfBars) rangeHigh = local_high * (1 + local_high / local_low / 10) rangeLow = local_low * (1 - local_high / local_low / 10) rangeHeight = rangeHigh - rangeLow numOfHistograms = input(120, 'Number of histograms (<=120)') histogramHeight = rangeHeight / numOfHistograms histogramLowList = array.new_float(numOfHistograms, na) histogramHighList = array.new_float(numOfHistograms, na) histogramData = array.new_float() histogramtargetList = array.new_float(numOfHistograms, 0.0) var Bars = array.new_box(numOfHistograms, na) // Clean up drawings every tick for i=0 to numOfHistograms - 1 box.delete(array.get(Bars, i)) f_drawLine(_x1, _x2, _yValue, _lineColor, _style, _width) => line.new(x1=_x1, y1=_yValue, x2=_x2, y2=_yValue, color=_lineColor, style=_style, width=_width) f_extendArray(_lineArray, _extendLines) => if array.size(_lineArray) > 0 for _i = array.size(_lineArray) - 1 to 0 by 1 x2 = line.get_x2(array.get(_lineArray, _i)) yValue = line.get_y1(array.get(_lineArray, _i)) if _extendLines or bar_index - 1 == x2 - 1 and not(high > yValue and low < yValue) line.set_x2(array.get(_lineArray, _i), bar_index + 1) if bar_index == last_bar_index array.push(histogramData, yValue) f_calculateLeverage100x(_pivotValue, _shortSell) => _shortSell ? _pivotValue * (1 - 0.01) : _pivotValue * (1 + 0.01) f_calculateLeverage50x( _pivotValue, _shortSell) => _shortSell ? _pivotValue * (1 - 0.02) : _pivotValue * (1 + 0.02) f_calculateLeverage25x(_pivotValue, _shortSell) => _shortSell ? _pivotValue * (1 - 0.04) : _pivotValue * (1 + 0.04) f_calculateLeverage10x(_pivotValue, _shortSell) => _shortSell ? _pivotValue * (1 - 0.1) : _pivotValue * (1 + 0.1) f_calculateLeverage5x(_pivotValue, _shortSell) => _shortSell ? _pivotValue * (1 - 0.2) : _pivotValue * (1 + 0.2) float yValue = na int x1 = na int x2 = na line l = na x1 := bar_index x2 := bar_index f_append(Array, l) => if array.size(Array) == numOfLines line.delete(array.shift(Array)) array.push(Array, l) if OI_delta_open_h3 yValue := f_calculateLeverage5x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_5xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage5x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_5xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage10x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_10xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage10x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_10xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage25x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage25x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage50x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage50x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage100x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_solid, 1) f_append(h3Array, l) yValue := f_calculateLeverage100x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_solid, 1) f_append(h3Array, l) if OI_delta_open_h2 yValue := f_calculateLeverage10x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_10xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage10x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_10xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage25x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage25x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage50x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage50x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage100x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_solid, 1) f_append(h2Array, l) yValue := f_calculateLeverage100x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_solid, 1) f_append(h2Array, l) if OI_delta_open_h1 yValue := f_calculateLeverage25x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_dotted, 1) f_append(h1Array, l) yValue := f_calculateLeverage25x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_25xColor, line.style_dotted, 1) f_append(h1Array, l) yValue := f_calculateLeverage50x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_dotted, 1) f_append(h1Array, l) yValue := f_calculateLeverage50x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_50xColor, line.style_dotted, 1) f_append(h1Array, l) yValue := f_calculateLeverage100x(kline_price, true) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_dotted, 1) f_append(h1Array, l) yValue := f_calculateLeverage100x(kline_price, false) l := f_drawLine(x1, x2, yValue, i_100xColor, line.style_dotted, 1) f_append(h1Array, l) f_extendArray(h3Array, false) f_extendArray(h2Array, false) f_extendArray(h1Array, false) // draw hist if barstate.islast and showHist // Define lows and highs of the histograms for i = 0 to numOfHistograms - 1 histogramLow = rangeLow + histogramHeight * i histogramHigh = rangeLow + histogramHeight * (i + 1) array.set(histogramLowList, i, histogramLow) array.set(histogramHighList, i, histogramHigh) for i = 0 to array.size(histogramData) - 1 y = array.get(histogramData, i) for j = 0 to numOfHistograms - 1 histogramLow = array.get(histogramLowList, j) histogramHigh = array.get(histogramHighList, j) if y >= histogramLow and y <= histogramHigh array.set(histogramtargetList, j, array.get(histogramtargetList, j) + 1) for i = 0 to numOfHistograms - 1 histogramLow = array.get(histogramLowList, i) histogramHigh = array.get(histogramHighList, i) histogramtarget = array.get(histogramtargetList, i) histogramWidth = math.floor((histogramtarget + 0.49) * 2) // Draw histograms array.set(Bars, i, box.new(left=bar_index + distLastCandle, top=histogramHigh, right=bar_index + distLastCandle + histogramWidth, bottom=histogramLow, bgcolor=barColor, border_color=barColor)) if barstate.islast and not showLine for i=0 to array.size(h3Array) - 1 line.delete(array.get(h3Array, i)) for i=0 to array.size(h2Array) - 1 line.delete(array.get(h2Array, i)) for i=0 to array.size(h1Array) - 1 line.delete(array.get(h1Array, i)) else if barstate.islast and showLocalOnly for i=0 to array.size(h3Array) - 1 if line.get_y1(array.get(h3Array, i)) < rangeLow or line.get_y1(array.get(h3Array, i)) > rangeHigh line.delete(array.get(h3Array, i)) for i=0 to array.size(h2Array) - 1 if line.get_y1(array.get(h2Array, i)) < rangeLow or line.get_y1(array.get(h2Array, i)) > rangeHigh line.delete(array.get(h2Array, i)) for i=0 to array.size(h1Array) - 1 if line.get_y1(array.get(h1Array, i)) < rangeLow or line.get_y1(array.get(h1Array, i)) > rangeHigh line.delete(array.get(h1Array, i)) // Volume Profile Inputs var g_VP = "Volume Profile" rows = input.int(200, "Rows", tooltip = "The number of price levels/rows that will be used to approximate the cumulative volume profile", group = g_VP) tf = input.timeframe("D", "Profile Timeframe", tooltip = "The aggregate timeframe that the volume profile represents", group = g_VP) ltf = input.timeframe("1", "Resolution Timeframe", tooltip = "The timeframe whose price data will be used to build the volume profile", group = g_VP) extend = input.int(100, "Profile Extend %", 0, 100, tooltip = "How much the volume profile should extend to the next session", group = g_VP) vp_color = input.color(color.new(color.blue, 70), "Profile Color", tooltip = "The color of the volume profile", group = g_VP) // Volume Point of Control Inputs var g_VPOC = "Volume Point of Control" show_vpoc = input.bool(true, "Show VPOC", inline = "VPOC", tooltip = "Whether to show the volume point of control (VPOC), or the level with the largest volume in a given volume profile", group = g_VPOC) vpoc_color = input.color(color.yellow, "", inline = "VPOC", group = g_VPOC) ext_vpoc = input.bool(true, "Extend Last N VPOCs", inline = "EXT", tooltip = "Whether to extend the last N number of VPOCs to the right of the chart", group = g_VPOC) ext_n_vpoc = input.int(5, "", 0, 100, inline = "EXT", group = g_VPOC) vpoc_label_above = input.timeframe("D", "Show Labels Above", tooltip = "With extend last N VPOCs turned on, labels displaying the date of said VPOCs will be shown when the profile timeframe is greater than or equal to this", group = g_VPOC) vpoc_label_size = input.string('Normal', "Label Size", options = , tooltip = "The size of VPOC date labels", group = g_VPOC) vpoc_width = input.int(2, "Line Width", tooltip = "The width of VPOC lines", group = g_VPOC) // High Volume Nodes Inputs var g_HVN = "High Volume Nodes" show_hvn = input.bool(true, "Show Previous HVNs", inline = "HVN", tooltip = "Whether to show high volume nodes (HVNs) from the previous session. Using the previous session's close, HVNs above this price will use the first color, and HVNs below this price will use the second color", group = g_HVN) hvn_color_bull = input.color(color.new(color.teal, 70), "", inline = "HVN", group = g_HVN) hvn_color_bear = input.color(color.new(color.red, 70), "", inline = "HVN", group = g_HVN) hvn_strength = input.int(10, "HVN Strength", tooltip = "HVNs are validated when a given level in the volume profile contains more volume than this many rows both above and below it", group = g_HVN) hvn_type = input.string("Areas", "HVN Type", options = , tooltip = "Whether to display HVNs as levels (lines) or areas (boxes). Levels use a solid line to denote the prior session's VPOC, and dotted lines for all other HVNs", group = g_HVN) hvn_width = input.int(1, "Line Width", tooltip = "The width of HVN lines, if the HVN type is selected as levels", group = g_HVN) // Bubbles AcadAlgo Inputs showBubbles = input.bool(true, "Display Bubbles", group="Bubbles", inline="1") useHeatMap = input.bool(false, "Enable HeatMap", group="Bubbles") showLevels = input.bool(false, "Highlight Significant Levels", group="Volume Levels") levelsCount = input.int(10, "Number of Levels", group="Volume Levels") mainColor = input.color(color.green, "Main Color", group="Colors") heatMapColor1 = input.color(color.new(color.aqua, 50), "HeatMap Color 1", group="Colors") heatMapColor2 = input.color(color.new(color.green, 50), "HeatMap Color 2", group="Colors") heatMapColor3 = input.color(color.new(color.yellow, 50), "HeatMap Color 3", group="Colors") heatMapColor4 = input.color(color.new(color.orange, 30), "HeatMap Color 4", group="Colors") heatMapColor5 = input.color(#d32626, "HeatMap Color 5", group="Colors") calculateInDollars = input.bool(false, "Calculate Volume in Dollars", group="Volume Options") volumeFilterOn = input.bool(true, "Enable Volume Filter", group="Volume Filters") // Toggle button for volume filter minVolumeDollars = input.float(100, "Minimum Volume ($)", minval=1, group="Volume Filters") maxVolumeDollars = input.float(1000000000000, "Maximum Volume ($)", minval=1, group="Volume Filters") // SPL Level Inputs swingSizeR = input.int(10, 'Bars Right-Left', inline='brl') swingSizeL = input.int(15, '-', inline='brl') showBoxes = input.bool(true, 'Show Boxes ', inline='aa') showSwingLines = input.bool(true, 'Show Lines', inline='aa') showBubblesSPL = input.bool(true, 'Show Labels ', inline='bb') showVol = input.bool(false, 'Show Volume', inline='bb') showOId = input.bool(false, 'Show OI Δ   ', inline='cc') extendtilfilled = input.bool(true, 'Extend Until Fill', inline='cc') hidefilled = input.bool(false, 'Hide Filled', group='Conditions') voltresh = input.int(0, 'Volume >', group='Conditions') oitresh = input.int(0, 'OI Δ (abs.) >', group='Conditions') pnoid = input.string('/', 'Only Swings With', options= , group='Conditions') showhighs = input.bool(true, '', inline='sh', group='Appearance') showlows = input.bool(true, '', inline='sl', group='Appearance') sellcol = input.color(#aa2430, 'Lows (Line - Label - Box)', inline='sh', group='Appearance') buycol = input.color(#66bb6a, 'Highs (Line - Label - Box)', inline='sl', group='Appearance') sellcolB = input.color(#aa2430, '', inline='sh', group='Appearance') buycolB = input.color(#66bb6a, '', inline='sl', group='Appearance') sellboxCol = input.color(#80192231, '', inline='sh', group='Appearance') buyboxCol = input.color(#66bb6a31, '', inline='sl', group='Appearance') lineStyle = input.string('Dotted', 'Line Style + Width', , inline='l', group='Appearance') lineWid = input.int(1, '', inline='l', group='Appearance') boxWid = input.float(0.7, 'Box Width + Type ', step=0.1, inline='xx', group='Appearance') boxStyle = input.string('TYPE 1', '', options= , inline='xx', group='Appearance') labelsize = input.string('Size: Tiny', 'Text Style        ', options= , inline='txt', group='Appearance' ) texthalign = input.string('Right','', options= , inline='txt', group='Appearance') lookback = input.bool(false, '', inline='lb') daysBack = input.float(150, 'Lookback (D)               ',inline='lb') binance = input.bool(true, 'Binance USDT.P', inline='src', group='Open Interest') binance2 = input.bool(true, 'Binance USD.P', inline='src', group='Open Interest') binance3 = input.bool(true, 'Binance BUSD.P', inline='src2', group='Open Interest') bitmex = input.bool(true, 'BitMEX USD.P', inline='src2', group='Open Interest') bitmex2 = input.bool(true, 'BitMEX USDT.P ', inline='src3', group='Open Interest') kraken = input.bool(true, 'Kraken USD.P', inline='src3', group='Open Interest') // Calculating inRange, used for lookback in days MSPD = 24 * 60 * 60 * 1000 lastBarDate = timestamp(year(timenow), month(timenow), dayofmonth(timenow), hour(timenow), minute(timenow), second(timenow)) thisBarDate = timestamp(year, month, dayofmonth, hour, minute, second) daysLeft = math.abs(math.floor((lastBarDate - thisBarDate) / MSPD)) inRange = lookback ? (daysLeft < daysBack) : true // Volume Profile Variables var vpoc = array.new_line() var dates = array.new_label() var values = array.new_float() var x_vol = array.new_int() var y_vol = array.new_float() var hvn_lines = array.new_line() var hvn_boxes = array.new_box() var hvn_Ly = array.new_float() var hvn_By = array.new_float() var PLA = array.new() var polyline PL = na var line temp_vpoc = na var int lb_idx = na var int lb_time = na // SPL Level Variables int prevHighIndex= na, int prevLowIndex= na, bool highActive= false, bool lowActive= false, bool h= false, bool lv= false pivHi = ta.pivothigh(high, swingSizeL, swingSizeR) pivLo = ta.pivotlow(low, swingSizeL, swingSizeR) if not na(pivHi) h := true prevHighIndex := bar_index - swingSizeR if not na(pivLo) lv := true prevLowIndex := bar_index - swingSizeR // Getting OI data mex = syminfo.basecurrency == 'BTC' ? 'XBT' : string(syminfo.basecurrency) oid1 = nz(request.security('BINANCE:' + string(syminfo.basecurrency) + 'USDT.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) oid2 = nz(request.security('BINANCE:' + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) oid3 = nz(request.security('BINANCE:' + string(syminfo.basecurrency) + 'BUSD.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) oid4 = nz(request.security('BITMEX:' + mex + 'USD.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) oid5 = nz(request.security('BITMEX:' + mex + 'USDT.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) oid6 = nz(request.security('KRAKEN:' + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, close - close , ignore_invalid_symbol=true), 0) 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) // Volume, OI, box width vol = volume oitreshcond = oitresh > 0 ? math.abs(deltaOI ) > oitresh : true voltreshcond = voltresh > 0 ? vol > voltresh : true oicond = pnoid == 'Positive OI Delta' ? deltaOI > 0 : pnoid == 'Negative OI Delta' ? deltaOI < 0 : true CLEAR = color.rgb(0, 0, 0, 100) boxWid1 = 0.001 * boxWid // Styles boxStyle(x) => switch x 'TYPE 1' => h ? pivHi : lv ? pivLo : na 'TYPE 2' => h ? pivHi * (1 - boxWid1) : lv ? pivLo * (1 + boxWid1) : na lineStyle(x) => switch x 'Solid' => line.style_solid 'Dashed' => line.style_dashed 'Dotted' => line.style_dotted switchtextsize(textsize) => switch textsize 'Size: Normal' => size.normal 'Size: Small' => size.small 'Size: Tiny' => size.tiny 'Size: Auto' => size.auto 'Size: Large' => size.large switchhalign(texthalign) => switch texthalign 'Middle' => text.align_center 'Right' => text.align_right 'Left' => text.align_left // Swing level labels var levelBoxes = array.new_box() var levelLines = array.new_line() if h and inRange and showhighs and oitreshcond and voltreshcond and oicond hBox = box.new(prevHighIndex, pivHi * (1 + boxWid1), bar_index, boxStyle(boxStyle), border_color=na, bgcolor=showBoxes ? sellboxCol : CLEAR, text=(showVol ? str.tostring(vol, format.volume) : na) + ' ' + (showOId ? str.tostring(deltaOI , format.volume) : ''), text_halign=switchhalign(texthalign), text_valign=text.align_center, text_color=chart.fg_color, text_size=switchtextsize(labelsize)) hLine = line.new(prevHighIndex, pivHi, bar_index, pivHi, color=showSwingLines ? sellcol : CLEAR, style=lineStyle(lineStyle), width=lineWid) array.push(levelBoxes, hBox) array.push(levelLines, hLine) if lv and inRange and showlows and oitreshcond and voltreshcond and oicond lBox = box.new(prevLowIndex, pivLo * (1 - boxWid1), bar_index, boxStyle(boxStyle), border_color=na, bgcolor=showBoxes ? buyboxCol : CLEAR, text=(showVol ? str.tostring(vol, format.volume) : na) + ' ' + (showOId ? str.tostring(deltaOI , format.volume) : ''), text_halign=switchhalign(texthalign), text_valign=text.align_center, text_color=chart.fg_color, text_size=switchtextsize(labelsize)) lLine = line.new(prevLowIndex, pivLo, bar_index, pivLo, color=showSwingLines ? buycol : CLEAR, style=lineStyle(lineStyle), width=lineWid) array.push(levelBoxes, lBox) array.push(levelLines, lLine) // Looping over the full array of lines and updating them, and deleting them if they have been touched size = array.size(levelBoxes) if size > 0 for i = 0 to size - 1 j = size - 1 - i box = array.get(levelBoxes, j) line = array.get(levelLines, j) level = line.get_y2(line) filled = (high >= level and low <= level) if filled and extendtilfilled and not hidefilled array.remove(levelLines, j) array.remove(levelBoxes, j) continue box.set_right(box, bar_index + 1) line.set_x2(line, bar_index + 1) if filled and hidefilled array.remove(levelLines, j) array.remove(levelBoxes, j) line.delete(line) box.delete(box) if not filled and not extendtilfilled array.remove(levelLines, j) array.remove(levelBoxes, j) continue // Deleting the oldest lines if array is too big if array.size(levelBoxes) >= 500 int i = 0 while array.size(levelBoxes) >= 500 box = array.get(levelBoxes, i) line = array.get(levelLines, i) box.delete(box) line.delete(line) array.remove(levelBoxes, i) array.remove(levelLines, i) i += 1 // Plotting circle labels for SPL plotshape(showhighs and showBubblesSPL and h and oitreshcond and voltreshcond and oicond ? high : na, style=shape.triangleup, location=location.absolute, offset=-swingSizeR, color=sellcolB, size=size.tiny) plotshape(showlows and showBubblesSPL and lv and oitreshcond and voltreshcond and oicond ? low : na, style=shape.triangledown, location=location.absolute, offset=-swingSizeR, color=buycolB, size=size.tiny) // Calculations for Bubbles AcadAlgo volumeData = volume priceSource = hl2 volumeInDollars = volumeData * close selectedVolume = calculateInDollars ? volumeInDollars : volumeData normalizedVolume = selectedVolume / ta.stdev(selectedVolume, 200) gradientColor = not useHeatMap ? color.from_gradient( normalizedVolume, 0, 8, chart.bg_color == color.white ? color.new(mainColor, 100) : color.rgb(18, 34, 18, 50), mainColor ) : ( normalizedVolume < 1 ? color.from_gradient(normalizedVolume, 0, 1, heatMapColor1, heatMapColor2) : normalizedVolume >= 1 and normalizedVolume < 4 ? color.from_gradient(normalizedVolume, 1, 4, heatMapColor3, heatMapColor4) : normalizedVolume >= 4 ? color.from_gradient(normalizedVolume, 4, 8, heatMapColor4, heatMapColor5) : na ) volumeCondition = volumeFilterOn ? (selectedVolume >= minVolumeDollars and selectedVolume < maxVolumeDollars) : true conditionTiny = volumeCondition and normalizedVolume > 0 and normalizedVolume < 1 and showBubbles conditionSmall = volumeCondition and normalizedVolume >= 1 and normalizedVolume < 2 and showBubbles conditionNormal= volumeCondition and normalizedVolume >= 2 and normalizedVolume < 3 and showBubbles conditionLarge = volumeCondition and normalizedVolume >= 3 and normalizedVolume < 4 and showBubbles conditionHuge = volumeCondition and normalizedVolume >= 4 and showBubbles // Plotting for Bubbles AcadAlgo if conditionHuge and (showLevels or showBubbles) label.new(showBubbles ? bar_index : last_bar_index, priceSource, str.tostring(selectedVolume, format.volume), xloc.bar_index, yloc.price, #00000000, showBubbles ? label.style_label_center : label.style_label_left, chart.fg_color) if conditionHuge and showLevels line.new(bar_index, priceSource, last_bar_index, priceSource, xloc.bar_index, extend.none, gradientColor, width=2) // figure plotshape(conditionTiny ? priceSource : na, "", shape.square, location.absolute, gradientColor, 0, "", na, size=size.tiny) plotshape(conditionSmall ? priceSource : na, "", shape.circle, location.absolute, gradientColor, 0, "", na, size=size.small) plotshape(conditionNormal? priceSource : na, "", shape.circle, location.absolute, gradientColor, 0, "", na, size=size.normal) plotshape(conditionLarge ? priceSource : na, "", shape.square, location.absolute, gradientColor, 0, "", na, size=size.normal) plotshape(conditionHuge ? priceSource : na, "", shape.diamond, location.absolute, gradientColor, 0, "", na, size=size.huge) // Manage the number of lines and labels on the chart a_allLines = line.all if array.size(a_allLines) > levelsCount line.delete(array.shift(a_allLines)) a_allLabels = label.all if array.size(a_allLabels) > levelsCount and not showBubbles label.delete(array.shift(a_allLabels)) // Warning if no Volume data Provided if ta.cum(volume) <= 0 and barstate.islast label.new(bar_index, hl2, "No Volume Data Available Use Another Symbol", style=label.style_label_left, textcolor=chart.fg_color) // Volume Profile Functions get_label_size(x) => result = switch x 'Auto' => size.auto 'Tiny' => size.tiny 'Small' => size.small 'Normal' => size.normal 'Large' => size.large 'Huge' => size.huge get_hvn() => if values.size() > hvn_strength for i = 0 to values.size() - 1 start = values.get(i) valid = true for j = -hvn_strength to hvn_strength k = i + j if k < 0 or k > values.size() - 1 continue else if j != 0 and values.get(k) > start valid := false break if valid idx = values.indexof(start) if idx != -1 y1 = y_vol.get(idx) y2 = y_vol.get(idx) val = y_vol.get(idx) if i < values.size() - 1 for m = i to values.size() - 2 if values.get(m + 1) > values.get(m) y1 := y_vol.get(m) break if i > 0 for m = i to 1 if values.get(m - 1) > values.get(m) y2 := y_vol.get(m) break new_color = close > math.avg(y1, y2) ? hvn_color_bull : hvn_color_bear if hvn_type == "Levels" if hvn_Ly.indexof(val) == -1 hvn_Ly.unshift(val) hvn_lines.unshift(line.new(time, val, time + timeframe.in_seconds(tf)*1000, val, xloc = xloc.bar_time, color = color.new(new_color, 0), style = start == values.max() ? line.style_solid : line.style_dotted, width = hvn_width)) else if hvn_By.indexof(y1) == -1 hvn_By.unshift(y1) hvn_boxes.unshift(box.new(time, y1, time + timeframe.in_seconds(tf)*1000, y2, xloc = xloc.bar_time, bgcolor = new_color, border_color = na)) ltf := timeframe.in_seconds(ltf) <= timeframe.in_seconds() ? ltf : "" = request.security_lower_tf(syminfo.tickerid, ltf, ) if not na(lb_idx) lb = bar_index - lb_idx > 0 ? (bar_index - lb_idx) : 1 y_max = ta.highest(high , lb) y_min = ta.lowest(low , lb) if timeframe.change(tf) or barstate.islast x_vol.clear() y_vol.clear() values.clear() for i = 0 to rows y = y_min + i * (y_max - y_min) / rows x_vol.push(lb_time) y_vol.push(y) values.push(0) for i = bar_index - lb_idx to 1 vol = ltf_V , if vol.size() > 0 for j = 0 to values.size() - 1 temp = y_vol.get(j) for k = 0 to vol.size() - 1 H = ltf_H L = ltf_L V = ltf_V if H.get(k) >= temp and L.get(k) <= temp add = math.floor(V.get(k) / ((H.get(k) - L.get(k)) / (y_max - y_min) / rows)) values.set(j, values.get(j) + add) max_y = y_vol.get(values.indexof(values.max())) sf = values.max() / (time - lb_time) / (extend / 100) for j = 0 to values.size() - 1 set = (lb_time + math.floor(values.get(j) / sf)) x_vol.set(j, set) PLA.clear() PLA.push(chart.point.from_time(lb_time, y_min)) for i = 0 to x_vol.size() - 1 PLA.push(chart.point.from_time(x_vol.get(i), y_vol.get(i))) PLA.push(chart.point.from_time(lb_time, y_max)) PL.delete() if timeframe.change(tf) polyline.new(PLA, curved = false, closed = true, line_color = vp_color, fill_color = vp_color, xloc = xloc.bar_time) temp_vpoc.delete() vpoc.unshift(line.new(lb_time, max_y, time, max_y, xloc = xloc.bar_time, color = show_vpoc ? vpoc_color : na, extend = ext_vpoc ? extend.right : extend.none, width = vpoc_width)) if ext_vpoc and timeframe.in_seconds(tf) >= timeframe.in_seconds(vpoc_label_above) dates.unshift(label.new(bar_index, max_y, str.format("{0,date,short}", time("", session = "0000-0000", timezone = "America/New_York")), textcolor = show_vpoc ? vpoc_color : na, color = na, size = get_label_size(vpoc_label_size))) else PL := polyline.new(PLA, curved = false, closed = true, line_color = vp_color, fill_color = vp_color, xloc = xloc.bar_time) if na(temp_vpoc) temp_vpoc := line.new(lb_time, max_y, time, max_y, xloc = xloc.bar_time, color = show_vpoc ? vpoc_color : na, extend = ext_vpoc ? extend.right : extend.none, width = vpoc_width) temp_vpoc.set_y1(max_y) temp_vpoc.set_y2(max_y) temp_vpoc.set_x2(time) if timeframe.change(tf) lb_idx := bar_index lb_time := time if show_hvn hvn_lines.clear() hvn_boxes.clear() hvn_Ly.clear() hvn_By.clear() get_hvn() if ext_vpoc and vpoc.size() > ext_n_vpoc line.set_extend(vpoc.pop(), extend.none) if timeframe.in_seconds(tf) >= timeframe.in_seconds(vpoc_label_above) label.delete(dates.pop()) if dates.size() > 0 for i = 0 to dates.size() - 1 dates.get(i).set_x(bar_index + 20)
Pine Script™指标
由makcwell88提供
MgboIntroduction: Crafted with TTrades, the Fractal Model empowers traders with a refined approach to Algorithmic Price Delivery. Specifically designed for those aiming to capitalize on expansive moves, this model anticipates momentum shifts, swing formations, orderflow continuations, as well as helping analysts highlight key areas to anticipate price deliveries. Description: > The Fractal Model° is rooted in the cyclical nature of price movements, where price alternates between large and small ranges. Expansion occurs when price moves consistently in one direction with momentum. By combining higher Timeframe closures with the confirmation of the change in state of delivery (CISD) on the lower Timeframe, the model reveals moments when expansion is poised to occur.> Thanks to TTrades' extensive research and years of studying these price behaviours, the Fractal Model° is a powerful, adaptive tool that seamlessly adjusts to any asset, market condition, or Timeframe, translating complex price action insights into an intuitive and responsive system. The TTrades Fractal Model remains stable and non-repainting, offering traders reliable, unchanged levels within the given Time period. This tool is meticulously designed to support analysts focus on price action and dynamically adapt with each new Time period. Key Features: Custom History: Control the depth of your historical view by selecting the number of previous setups you’d like to analyze on your chart, from the current setup only (0) to a history of up to 40 setups. This feature allows you to tailor the chart to your specific charting style, whether you prefer to see past setups or the current view only.>Fractal Timeframe Pairings: This indicator enables users to observe and analyze lower Timeframe (LTF) movements within the structure of a higher Timeframe (HTF) candle. By examining LTF price action inside each HTF candle, analysts can gain insight into micro trends, structure shifts, and key entry points that may not be visible on the higher Timeframe alone. This approach provides a layered perspective, allowing analysts to closely monitoring how the LTF movements unfold within the overarching HTF context. For a more dynamic and hands-off user experience, the Automatic feature autonomously adjusts the higher Timeframe pairing based the current chart Timeframe, ensuring accurate alignment with the Fractal Model, according to TTrades and his studies Bias Selection: This feature allows analysts complete control over bias and setup detection, allowing one to view bullish or bearish formations exclusively, or opt for a neutral bias to monitor both directions. Easily toggle the bias filter on Fractal Model to align with your higher Timeframe market draw.
Pine Script™指标
由arbitagestocksltd提供
AAKASHThis powerful TradingView script, "AAKASH," offers traders an intuitive way to visualize market trends and easily spot key entry and exit signals. By dynamically changing candle colors, it provides a clear visual cue of market conditions. Candles turn green when the price is trending upwards or when a buy signal occurs, and red when the price is trending downwards or a sell signal is triggered. This dynamic color change ensures that traders can instantly recognize shifts in market momentum, making it easier to time trades. Buy and sell signals are clearly marked with labels, positioned below bars for buys and above bars for sells, making them easy to spot. This script seamlessly integrates trend-following analysis with price action, giving traders the confidence to make well-informed decisions. With its easy-to-read visual cues, "AAKASH" is the perfect tool for anyone looking to enhance their trading strategy and react faster to market movements.
Pine Script™指标
由patelakx提供
Brokerir Market Sessions IndicatorThe Brokerir Market Sessions Indicator is a powerful tool designed to help traders track global market sessions in a highly customizable and visually distinct manner. It supports four market sessions by default: Tokyo, London, New York, and Sydney, but you can fully customize session times, names, and colors to fit your trading needs. This indicator offers four different visualization modes: ✔ Boxes – Clear session boundaries with customizable colors. ✔ Timeline – A minimalistic session tracker along the bottom of the chart. ✔ Zones – Highlights price action during specific sessions. ✔ Colored Candles – Colors candlesticks based on active sessions. Additionally, it includes useful tools such as session High/Low tracking, Open/Close percentage change, pip movement, session equilibrium level, overlapping session merging, and weekend filtering. Key Features ✅ Fully Customizable Sessions – Adjust names, colors, and times. ✅ Four Display Modes – Choose between Boxes, Timelines, Zones, or Candles. ✅ Automatic Timezone Detection – Works across all time zones, no manual adjustments needed. ✅ Session High/Low & Open/Close Tracking – View price movement during each session in pips or percentage. ✅ Overlap Merging – Ensures cleaner charts by merging overlapping sessions. ✅ Equilibrium Levels & Open/Close Lines – Gain insights into session strength and direction. ✅ Weekend Filtering – Avoid plotting sessions when the market is closed. Customization Options 📌 Sessions Settings You can modify each session independently: • Tokyo Session – Set time, color, and name. • London Session – Set time, color, and name. • New York Session – Set time, color, and name. • Sydney Session – Set time, color, and name. 💡 You can also create and track your own custom sessions! 📌 Additional Tools 1️⃣ Pips & Percentage Change Labels – Shows the distance between session high/low or open/close. 2️⃣ Session Overlap Merging – Makes charts cleaner by merging overlapping sessions. 3️⃣ Weekend Filter – Removes unnecessary session tracking when markets are closed. 4️⃣ Open/Close Line – Draws a trend line between session open and close for easy direction tracking. 5️⃣ 0.5 Equilibrium Level – Identifies the middle of a session range to spot price balance points. 6️⃣ Session Candle Coloring – Assigns unique colors to candles based on session activity. 7️⃣ Lookback Period – Customize how far back the indicator displays past session data. 8️⃣ Input Timezone Adjustments – Manually override time zones if needed. Why Choose Brokerir Market Sessions Indicator? 🔹 Complete Customization – Define sessions exactly as you need them. 🔹 Multiple Visualizations – Switch between zones, boxes, timelines, or candle coloring. 🔹 Accurate Time Adjustments – Works regardless of your TradingView time zone settings. 🔹 Professional Trading Tool – Ideal for scalpers, day traders, and institutional analysis. 🔹 Future Updates & Enhancements – Brokerir will continue improving this indicator with new features and functionalities. 💡 Follow Brokerir for updates and improvements to this essential trading tool!
Pine Script™指标
由SasanHATAM提供
Highest Price MarkerHighest Price Marker – Smart Label & Line Indicator This Pine Script v5 indicator highlights the highest price reached within the last 100 bars on your chart. It visually enhances key price levels by: ✅ Placing a label at the highest price, positioned 3 candles to the left for clarity. ✅ Drawing a line connecting the label to the actual high for better visibility. ✅ Auto-updating dynamically whenever a new highest price is detected. This is useful for traders who want to quickly identify resistance levels or analyze historical price peaks without cluttering the chart. 🔹 How to Use: Add the indicator to your chart. Look for the red label marking the highest price within the last 100 bars. The horizontal line helps track the exact price level. 💡 Customization Ideas: Adjust the lookback period (length = 100) to detect longer or shorter trends. Modify colors or label positioning to suit your preferences. 🚀 Perfect for: 🔸 Price Action Traders 🔸 Swing & Breakout Traders 🔸 Support & Resistance Analysis
Pine Script™指标
由bsiele提供
smolka Bayesian Volatile ChannelDescription in English and Russian. Bayesian Volatile Channel The script is a loose interpretation of Bayes' theorem, which allows calculating the probability of events given that another event related to it has occurred, the script analyzes volatility and detects anomalies in price charts using a Bayesian approach, updating the model parameters to accurately estimate market fluctuations and detect changes in trends. How does it work? 1. The script sets the initial parameters (mean price and standard deviation), creating a "hypothesis" about the market behavior. 2. When a new price appears, the script calculates the probability of its compliance with previous expectations. If the new price differs from the forecast, the model parameters (mean and standard deviation) are updated. 3. After updating the model, the probability that the current price and volatility correspond to a normal distribution is calculated. 4. Based on the updated model, volatility channels are built (mean price ± two standard deviations). If the price goes beyond these limits, this signals a possible anomaly indicating changes in the market. 5. The moving averages in the script act as data smoothing and trend analysis, helping to identify the market direction and minimize the impact of random fluctuations. The script uses moving averages to identify uptrends and downtrends, and calculates the average between them to display the overall market balance. These moving averages make market analysis clearer and more resistant to short-term fluctuations. ****************************************************************** Описание на английском и русском языках. Байесовский волатильный канал Скрипт является вольной интерпретацией теоремы Байеса, которая позволяет расчитать вероятность событий при условии, что произошло связанное с ним другое событие, скрипт анализирует волатильность и обнаруживает аномалии в графиках цен, используя байесовский подход, обновляя параметры модели для точной оценки рыночных колебаний и обнаружения изменений в тенденциях. Как это работает? 1. Скрипт устанавливает начальные параметры (среднюю цену и стандартное отклонение), создавая "гипотезу" о поведении рынка. 2. При появлении новой цены скрипт вычисляет вероятность её соответствия предыдущим ожиданиям. Если новая цена отличается от прогноза, параметры модели (среднее и стандартное отклонение) обновляются. 3. После обновления модели рассчитывается вероятность того, что текущая цена и волатильность соответствуют нормальному распределению. 4. На основе обновлённой модели строятся каналы волатильности (средняя цена ± два стандартных отклонения). Если цена выходит за эти пределы, это сигнализирует о возможной аномалии, указывающей на изменения на рынке. 5. Средние скользящие в скрипте выполняют роль сглаживания данных и анализа трендов, помогая выявить направление рынка и минимизировать влияние случайных колебаний. Скрипт использует скользящие средние для определения восходящего и нисходящего трендов, а также рассчитывает среднее значение между ними для отображения общего баланса рынка. Эти скользящие средние делают анализ рынка более чётким и устойчивым к краткосрочным флуктуациям.
Pine Script™指标
由smolka提供
1