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Trend Filter (2-pole) [BigBeluga]Trend Filter (2-pole) The Trend Filter (2-pole) is an advanced trend-following indicator based on a two-pole filter, which smooths out market noise while effectively highlighting trends and their strength. It incorporates color gradients and support/resistance dots to enhance trend visualization and decision-making for traders. SP500: 🔵What is a Two-Pole Filter? A two-pole filter is a digital signal processing technique widely used in electronics, control systems, and time series data analysis to smooth data and reduce noise. //@function Two-pole filter //@param src (series float) Source data (e.g., price) //@param length (float) Length of the filter (higher value means smoother output) //@param damping (float) Damping factor for the filter //@returns (series float) Filtered value method two_pole_filter(float src, int length, float damping) => // Calculate filter coefficients float omega = 2.0 * math.pi / length float alpha = damping * omega float beta = math.pow(omega, 2) // Initialize the filter variables var float f1 = na var float f2 = na // Update the filter f1 := nz(f1 ) + alpha * (src - nz(f1 )) f2 := nz(f2 ) + beta * (f1 - nz(f2 )) f2 It operates using two cascaded smoothing stages (poles), allowing for a more refined and responsive output compared to simple moving averages or other basic filters. Two-pole filters are particularly valued for their ability to maintain smooth transitions while reducing lag, making them ideal for applications where precision and responsiveness are critical. In trading, this filter helps detect trends by smoothing price data while preserving significant directional changes. 🔵Key Features of the Indicator: Gradient-Colored Trend Filter Line: The main filter line dynamically changes color based on trend strength and direction: - Green: Strong uptrend. - Red: Strong downtrend. - Yellow: Indicates a transition phase, signaling potential trend shifts. Support and Resistance Dots with Signals: - Dots are plotted below the filter line during uptrends and above it during downtrends. - These dots represent consecutive rising or falling conditions of the filter line, which traders can set in the settings (e.g., the number of consecutive rises or falls required). - The dots often act as dynamic support or resistance levels, providing valuable guidance during trends. - Trend Signals: Customizable Sensitivity: The indicator allows traders to adjust the filter length, damping factor, and the threshold for rising/falling conditions, enabling it to adapt to different trading styles and timeframes. Bar Color Option: The indicator can optionally color bars to match the gradient of the filter line, enhancing visual clarity of trends directly on the price chart. 🔵How It Works: The Trend Filter (2-pole) smooths price data using a two-pole filter, which reduces noise and highlights the underlying trend. The gradient coloring of the filter line helps traders visually assess the strength and direction of trends. Rising and falling conditions of the filter line are tracked, and dots are plotted when consecutive conditions meet the threshold, acting as potential support or resistance levels during trends. The yellow transition color signals periods of indecision, helping traders anticipate potential reversals or consolidations. 🔵Use Cases: Identify and follow strong uptrends and downtrends with gradient-based visual cues. Use the yellow transition color to anticipate trend shifts or consolidation zones. Leverage the plotted dots as dynamic support and resistance levels to refine entry and exit strategies. Combine with other indicators for confirmation of trends and reversals. This indicator is perfect for traders who want a visually intuitive and highly customizable tool to spot trends, gauge their strength, and make informed trading decisions.
Индикатор Pine Script™
от BigBeluga
11
buy sel StrategyGöstergenin Amacı Bu gösterge: Alım ve satım sinyalleri üretmek için MACD ve Bollinger Bantları kombinasyonunu kullanır. Sinyalleri grafik üzerinde göstermek için oklar (yukarı ve aşağı) çizer. Önemli sinyal durumlarında kullanıcıyı uyarmak için uyarı mekanizması içerir. 2. Kullanılan Teknik Göstergeler A) MACD (Moving Average Convergence Divergence) MACD, iki üstel hareketli ortalama arasındaki farkı ölçer: Hızlı MACD Periyodu: Kısa dönem EMA (varsayılan: 12). Yavaş MACD Periyodu: Uzun dönem EMA (varsayılan: 26). Sinyal MACD Periyodu: MACD hattının yumuşatılmış versiyonu (varsayılan: 9). Koşullar: Alım Sinyali: MACD hattı, sinyal hattını yukarı yönde keser (ta.crossover fonksiyonu). Satım Sinyali: MACD hattı, sinyal hattını aşağı yönde keser (ta.crossunder fonksiyonu). B) Bollinger Bantları Bollinger Bantları, fiyatın oynaklığını (volatilite) ölçmek için kullanılır: Orta Bant: Fiyatın hareketli ortalamasıdır (varsayılan: 20 periyotluk SMA). Üst Bant: Orta banda, standart sapmanın belirli bir katı eklenir (varsayılan: 2.0). Alt Bant: Orta bandan, standart sapmanın belirli bir katı çıkarılır (varsayılan: 2.0). 3. Göstergenin İşlevselliği A) Alım Koşulu (buy_condition): pinescript Kopyala Düzenle buy_condition = ta.crossover(macd_line, signal_line) and close > bb_lower Al sinyali, şu iki şart sağlandığında tetiklenir: MACD hattı, sinyal hattını yukarı yönde keserse (pozitif momentum). Fiyat, Bollinger Bantları'nın alt bandının üzerine çıkarsa (fiyatın potansiyel dipten yukarı dönüşü). B) Satım Koşulu (sell_condition): pinescript Kopyala Düzenle sell_condition = ta.crossunder(macd_line, signal_line) and close < bb_upper Sat sinyali, şu iki şart sağlandığında tetiklenir: MACD hattı, sinyal hattını aşağı yönde keserse (negatif momentum). Fiyat, Bollinger Bantları'nın üst bandının altına düşerse (fiyatın potansiyel zirveden dönüşü). 4. Grafik Üzerindeki Gösterim A) Bollinger Bantları: Üst Bant (kırmızı çizgi). Alt Bant (yeşil çizgi). Orta Bant (turuncu çizgi). B) Alım ve Satım Sinyalleri: Oklar: Yeşil ok (yukarı): Alım sinyali. Kırmızı ok (aşağı): Satım sinyali. C) Plotlama: plotarrow fonksiyonu, yukarı ve aşağı sinyalleri oklarla grafik üzerinde gösterir: pinescript Kopyala Düzenle plotarrow(buy_condition ? 1 : sell_condition ? -1 : na, colorup=color.green, colordown=color.red, offset=-1) 5. Uyarılar Uyarılar, sinyallerle kullanıcıyı bilgilendirir: Alım Sinyali Uyarısı: Mesaj: "MACD ve fiyat, Bollinger Bandı'nın alt sınırının üzerine çıktı." Satım Sinyali Uyarısı: Mesaj: "MACD ve fiyat, Bollinger Bandı'nın üst sınırının altına indi." 6. Kodun Avantajları Kombinasyon Stratejisi: MACD ve Bollinger Bantları’nın birleşimi daha doğruluklu sinyaller üretebilir. Basit ve Görsel: Grafik üzerinde sinyaller net bir şekilde belirtilmiştir. Uyarı Mekanizması: Otomatik olarak işlem yapmak veya uyarı almak isteyen kullanıcılar için uygundur. 7. Dezavantajlar Lag (Gecikme): Hem MACD hem de Bollinger Bantları gecikmeli göstergelerdir, bu da sinyalin gecikmesine neden olabilir. Trend Filtreleme Eksikliği: Yanlış sinyalleri azaltmak için trend yönünü doğrulayan ek bir filtre (ör. EMA 200) faydalı olabilir. 8. Geliştirme Önerileri Trend Filtresi: Yanlış sinyalleri azaltmak için EMA (200) gibi bir trend filtresi eklenebilir. Fazla Sinyallerin Azaltılması: RSI gibi bir gösterge ile daha fazla doğrulama katmanı eklenebilir. Zaman Aralığı Testi: Bu strateji en iyi 15 dakika, 1 saat veya 1 günlük zaman aralıklarında test edilerek optimize edilebilir. Bu kod, daha sofistike stratejiler oluşturmak için güçlü bir başlangıç noktasıdır. Doğru parametre ayarlarıyla etkili bir ticaret aracı haline gelebilir.
Индикатор Pine Script™
от alivurun
Advanced Swing High/Low Trend Lines# Advanced Swing High/Low Trend Lines Indicator ## Features: ### Dynamic Trend Lines This indicator dynamically identifies swing highs and swing lows based on the user-defined `Swing Length`. It then connects these points to create trend lines that visualize the market's direction and key support/resistance levels. ### Customizable Settings - **Swing Length**: Define the sensitivity for detecting swing highs and lows. - **Points Required to Draw Trend**: Specify the minimum number of swing highs or lows required to establish a valid trend line. - **Show Old Trends**: Toggle the visibility of previous trend lines to focus on the current market structure. - **Line Appearance**: Customize the color, style (`solid`, `dotted`, `dashed`), and width of both trend and support lines. ### Trend Break Detection - Automatically detects and highlights when the price breaks above a high trend line or below a low trend line. - The broken trend line changes its color to indicate a trend break, helping traders quickly identify significant market shifts. ### Continuous Updates - As new swing highs or lows are detected, the indicator updates existing trend lines or creates new ones, ensuring relevance in dynamic market conditions. - Trend lines extend into the future, projecting potential areas of interest for traders. ## Benefits: 1. **Enhanced Market Visualization**: - Provides a clear view of market trends, swing points, and potential reversal zones. 2. **Trend Reversal Alerts**: - Identifies and visually emphasizes trend breaks, enabling proactive trading decisions. 3. **Fully Customizable**: - Adjust settings to suit your trading style and strategy, ensuring compatibility with various markets and timeframes. 4. **Real-Time Adaptation**: - Automatically adapts to changing market conditions, maintaining accuracy and relevance. ## Use Cases: - **Trend Following**: Identify and trade in the direction of established trends. - **Breakout Trading**: Spot trend breaks and capitalize on momentum shifts. - **Support and Resistance Analysis**: Use trend lines to identify key levels where price may react. This indicator is an essential tool for traders seeking to combine technical precision with visual clarity in their analysis.
Индикатор Pine Script™
от doganayy2
[Elite Algo Modded]// ALERT READY ON TELEGRAM ==> t.me //@version=5 indicator(" ", overlay=true, max_lines_count=500, max_labels_count=500, max_boxes_count=350) // FUNCTIONS // Close to Close Volatility f_coc(x, period, sqrtAnnual) => mean = ta.sma(x, period) s = array.new_float(0) for i = 0 to period - 1 by 1 array.push(s, math.pow(x - mean, 2)) sqrtAnnual * math.sqrt(array.sum(s) / (period - 1)) // // Parkinson Volatility f_park(period, sqrtAnnual) => var LOG2 = math.log(2) powLogHighLow = math.pow(math.log(high / low), 2) sqrtAnnual * math.sqrt(1.0 / period * math.sum(1.0 / (4.0 * LOG2) * powLogHighLow, period)) // Garman Klass Volatility f_gk(period, sqrtAnnual) => var LOG2 = math.log(2) var SQRT_1_PERIOD = math.sqrt(1 / period) powLogHighLow = math.pow(math.log(high / low), 2) powLogCloseOpen = math.pow(math.log(close / open), 2) tmp = 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) * powLogCloseOpen sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD // Rogers Satchell Volatility f_rsv(period, sqrtAnnual) => tmp = math.log(high / close) * math.log(high / open) + math.log(low / close) * math.log(low / open) sqrtAnnual * math.sqrt(math.sum(tmp, period) / period) // Garman Klass Yang Zhang Extension Volatility f_gkyz(period, sqrtAnnual) => var LOG2 = math.log(2) var SQRT_1_PERIOD = math.sqrt(1 / period) powLogHighLow = math.pow(math.log(high / low), 2) powLogCloseOpen = math.pow(math.log(close / open), 2) lastClose = nz(close , close) powLogOpenClose1 = math.pow(math.log(open / lastClose), 2) tmp = powLogOpenClose1 + 0.5 * powLogHighLow - (2.0 * LOG2 - 1.0) * powLogCloseOpen sqrtAnnual * math.sqrt(math.sum(tmp, period)) * SQRT_1_PERIOD // Yang Zhang Volatility f_yz(a, period, sqrtAnnual) => o = math.log(open) - math.log(nz(close , close)) u = math.log(high) - math.log(open) d = math.log(low) - math.log(open) c = math.log(close) - math.log(open) nMinusOne = period - 1 avgo = ta.sma(o, period) avgc = ta.sma(c, period) so = array.new_float(0) sc = array.new_float(0) for i = 0 to period - 1 by 1 array.push(so, math.pow(o - avgo, 2)) array.push(sc, math.pow(c - avgc, 2)) sumo = array.sum(so) sumc = array.sum(sc) Vo = sumo / nMinusOne Vc = sumc / nMinusOne Vrs = math.sum(u * (u - c) + d * (d - c), period) / period k = (a - 1.0) / (a + (period + 1.0) / nMinusOne) sqrtAnnual * math.sqrt(Vo + k * Vc + (1.0 - k) * Vrs) // Exponentially Weighted Volatility f_ewma(source, period, sqrtAnnual) => var lambda = (period - 1) / (period + 1) squared = math.pow(source, 2) float v = na v := lambda * nz(v , squared) + (1.0 - lambda) * squared sqrtAnnual * math.sqrt(v) // Mean Absolute Deviation (Adjusted) f_mad(source, period, sqrtAnnual) => var SQRT_HALF_PI = math.sqrt(math.asin(1)) mean = ta.sma(source, period) S = array.new_float(0) for i = 0 to period - 1 by 1 array.push(S, math.abs(source - mean)) sumS = array.sum(S) sqrtAnnual * (sumS / period) * SQRT_HALF_PI // Median Absolute Deviation f_mead(source, period, sqrtAnnual) => median = ta.percentile_nearest_rank(source, period, 50) E = 0.0 for i = 0 to period - 1 by 1 E += math.abs(source - median) E sqrtAnnual * math.sqrt(2) * (E / period) //Rescale Function f_rescale(_src, _size) => math.max(0, math.min(_size, int(_src / 100 * _size))) // label Panel Function _label(T, color_PnL) => label PnL_Label = na label.delete(PnL_Label ) PnL_Label := label.new(time, 0, text=T, color=color_PnL, textcolor=color.white, size=size.normal, style=label.style_label_left, xloc=xloc.bar_time, textalign=text.align_left) label.set_x(PnL_Label, label.get_x(PnL_Label) + math.round(ta.change(time) * 3)) // Round Function Round(src, digits) => p = math.pow(10, digits) math.round(math.abs(src) * p) / p * math.sign(src) //Options for Inputs ON = 'On' OFF = 'Off' CTC = 'Close to Close' PKS = 'Parkinson' GK = 'Garman Klass' RS = 'Rogers Satchell' GKYZ = 'Garman Klass Yang Zhang Extension' YZ = 'Yang Zhang' EWMA = 'EWMA' MAD = 'Mean Absolute Deviation' MAAD = 'Median Absolute Deviation' L = 'Line' SL = 'StepLine' Ar = 'Area' CL = 'Columns' // Settings H = EWMA period = 10 Annual = 365 a = 1.34 Plen = 365 Pco = ON sma = ON malen = 55 bsg = OFF stl = CL lT = 3 i_invert = OFF bg = OFF sp = OFF // bgcolor(bg ? color.new(#000000, 20) : na, title='Dark Background', transp=90) var sqrtAnnual = math.sqrt(Annual) * 100 logr = math.log(close / close ) // Historical Volatiity Models Hv = if H == CTC f_coc(logr, period, sqrtAnnual) else if H == PKS f_park(period, sqrtAnnual) else if H == RS f_rsv(period, sqrtAnnual) else if H == GK f_gk(period, sqrtAnnual) else if H == GKYZ f_gkyz(period, sqrtAnnual) else if H == EWMA f_ewma(logr, period, sqrtAnnual) else if H == YZ f_yz(a, period, sqrtAnnual) else if H == MAD f_mad(logr, period, sqrtAnnual) else // H == "Median Absolute Deviation" f_mead(logr, period, sqrtAnnual) pstyle = stl == L ? plot.style_linebr : stl == SL ? plot.style_stepline : stl == Ar ? plot.style_area : stl == CL ? plot.style_columns : plot.style_line //Hv Stats avgHV = ta.sma(Hv, malen) HVP = ta.percentrank(Hv, Plen) NearZero = HVP < 1.5 ? 1 : 0 HV50 = ta.percentile_nearest_rank(Hv, Plen, 50) // // Text Functions // texthv() => // ' HV: ' + str.tostring(Round(Hv, 2)) // textphv() => // 'HV 50áµ—Ê° Percentile: ' + str.tostring(Round(HV50, 2)) // texthvp() => // 'HV Percentile: ' + str.tostring(Round(HVP, 2)) + 'áµ—Ê°' // // Coloring // var c_ = array.new_color(na) // if barstate.isfirst // array.push(c_, #0effff) // array.push(c_, #00fdf6) // array.push(c_, #00fbee) // array.push(c_, #00f9e4) // array.push(c_, #00f6db) // array.push(c_, #00f4d1) // array.push(c_, #13f1c6) // array.push(c_, #24efbc) // array.push(c_, #31ecb1) // array.push(c_, #3ce9a6) // array.push(c_, #47e69b) // array.push(c_, #51e390) // array.push(c_, #5adf85) // array.push(c_, #62dc7a) // array.push(c_, #6ad96e) // array.push(c_, #72d563) // array.push(c_, #7ad157) // array.push(c_, #81cd4b) // array.push(c_, #88ca3f) // array.push(c_, #8fc532) // array.push(c_, #96c123) // array.push(c_, #9cbd0e) // array.push(c_, #a3b800) // array.push(c_, #a9b300) // array.push(c_, #b0ae00) // array.push(c_, #b6a900) // array.push(c_, #bca300) // array.push(c_, #c29e00) // array.push(c_, #c29e00) // array.push(c_, #c89800) // array.push(c_, #ce9100) // array.push(c_, #d48b00) // array.push(c_, #da8400) // array.push(c_, #df7c00) // array.push(c_, #e57400) // array.push(c_, #ea6c00) // array.push(c_, #ef6200) // array.push(c_, #f35800) // array.push(c_, #f74c00) // array.push(c_, #fb3e00) // array.push(c_, #ff2d00) // if i_invert // array.reverse(c_) // var sizeOf = array.size(c_) - 1 // colorHV = Pco ? array.get(c_, f_rescale(HVP, sizeOf)) : color.aqua // Plots // plot(Hv, 'HV', color=colorHV, linewidth=lT, style=plot.style_line) // plot(sma ? avgHV : na, 'sma', color=color.new(#FFFFFF, 25), linewidth=2) //bgcolor(Hv > avgHV ? color.lime : na) // if sp // _label(H + texthv() + ' ' + textphv() + ' ' + texthvp() + ' ', #000000c0) // col2 = HVP >= 1 ? color.yellow : HVP <= 1 and HVP >= 0.5 ? color.orange : HVP <= 0.5 ? #8D0000 : color.silver // // bgcolor(bsg and NearZero ? col2 : na, transp=50) //Custrom MAS maa = avgHV / 100 * 140 mab = avgHV / 100 * 180 mac = avgHV / 100 * 240 mad = avgHV / 100 * 60 mae = avgHV / 100 * 20 // Auto Sensivity Volatility Band Settings float volatility = 0.0 if Hv < maa and Hv > avgHV // ilk band ust volatility := 3.15 else if Hv < mab and Hv > maa // ikinci band ust volatility := 3.5 else if Hv < mac and Hv > mab // ucuncu band ust volatility := 3.6 else if Hv > mac // volatilite en ust degerde volatility := 4 else if Hv < maa and Hv > mad // altdaki ilk band volatility := 3 else if Hv < mad and Hv > mae // altdaki ikinci band volatility := 2.85 else if Hv < mae // volatilite butun bandlarin anltinda volatility := 3 //plot(volatility,color = color.red) // plot(maa, 'maa', color=color.new(color.aqua, 25)) // plot(mab, 'mab', color=color.new(color.aqua, 25)) // plot(mac, 'mac', color=color.new(color.aqua, 25)) // plot(mad, 'mad', color=color.new(color.aqua, 25)) // plot(mae, 'mae', color=color.new(color.aqua, 25)) //-------------- Elite Algo v22 | elitesignals.com -----------------// // Get user input enableDashboard = input(true, "Enable Dashboard", group="DASHBOARD SETTINGS") locationDashboard = input.string("Middle right", "Location", , group="DASHBOARD SETTINGS") sizeDashboard = input.string("Tiny", "Size", , group="DASHBOARD SETTINGS") colorBackground = input(#2A2E39, "Bg color", group="DASHBOARD SETTINGS") colorFrame = input(#2A2E39, "Frame color", group="DASHBOARD SETTINGS") colorBorder = input(#363A45, "Border color", group="DASHBOARD SETTINGS") showSignals = input(true, "Show signals", group="BUY AND SELL SIGNALS SETTINGS") strategy = input.string("Normal", "Strategy", , group="BUY AND SELL SIGNALS SETTINGS") sensitivity11 = input.float(defval=1.8, title="Sensitivity", minval=1, maxval=20, group = 'Signals') sensitivity = sensitivity11 auto_button = input.bool(defval = true , title = "Auto Sensitivity", group = 'Signals') consSignalsFilter = input(false, "Consolidation signals filter", group="BUY AND SELL SIGNALS SETTINGS") smartSignalsOnly = input(false, "Smart signals only", group="BUY AND SELL SIGNALS SETTINGS") candleColors = input(false, "Candle colors", group="BUY AND SELL SIGNALS SETTINGS") momentumCandles = input(false, "Momentum candles", group="BUY AND SELL SIGNALS SETTINGS") highVolSignals = input(false, "High volume signals only", group="BUY AND SELL SIGNALS SETTINGS") enableTrailingSL = input(false, "Enable trailing stop-loss", group="RISK MANAGEMENT SETTINGS") usePercSL = input(false, "% Trailing sl", inline="2", group="RISK MANAGEMENT SETTINGS") percTrailingSL = input.float(1, "", 0, step=0.1, inline="2", group="RISK MANAGEMENT SETTINGS") enableSwings = input(false, "Enable Swing High's & Swing's Low's", inline="3", group="RISK MANAGEMENT SETTINGS") periodSwings = input.int(10, "", 2, inline="3", group="RISK MANAGEMENT SETTINGS") enableTpSlAreas = input(false, "Enable take profit/stop-loss areas", group="RISK MANAGEMENT SETTINGS") useTP1 = input(true, "", inline="4", group="RISK MANAGEMENT SETTINGS") multTP1 = input.float(1, "TP 1", 0, inline="4", group="RISK MANAGEMENT SETTINGS") useTP2 = input(true, "", inline="5", group="RISK MANAGEMENT SETTINGS") multTP2 = input.float(2, "TP 2", 0, inline="5", group="RISK MANAGEMENT SETTINGS") useTP3 = input(true, "", inline="6", group="RISK MANAGEMENT SETTINGS") multTP3 = input.float(3, "TP 3", 0, inline="6", group="RISK MANAGEMENT SETTINGS") tpLabels = input(true, "Take profit labels", group="RISK MANAGEMENT SETTINGS") showTrendCloud = input(true, "Show Trend cloud", group="TREND CLOUD SETTINGS") periodTrendCloud = input.string("New", "Trend cloud period", , group="TREND CLOUD SETTINGS") signalsTrendCloud = input(false, "Trend only signals", group="TREND CLOUD SETTINGS") fastTrendCloud = input(false, "Fast trend cloud", group="TREND CLOUD SETTINGS") fastTrendCloudLen = input.int(55, "Fast trend cloud", 2, group="TREND CLOUD SETTINGS") enableAutoTrend = input(false, "Enable Auto Trendlines", group="AUTO TRENDLINES SETTINGS") srcTrendChannel = input(close, "Trend channel source", group="AUTO TRENDLINES SETTINGS") lenTrendChannel = input.int(200, "Trend channel loopback", 2, group="AUTO TRENDLINES SETTINGS") enableSR = input(false, "Enable support and resistance", group="AUTO SUPPORT AND RESISTANCE SETTINGS") lineSrStyle = input.string("Dashed", "Line Style", , group="AUTO SUPPORT AND RESISTANCE SETTINGS") lineSrWidth = input.int(2, "Line Width", 1, 4, group="AUTO SUPPORT AND RESISTANCE SETTINGS") showCons = input(false, "Consolidation Zones", group="CONSOLIDATION ZONES") lbPeriod = input.int(10, "Loopback Period", 2, 50, group="CONSOLIDATION ZONES") lenCons = input.int(5, "Min Consolidation Length", 2, 20, group="CONSOLIDATION ZONES") paintCons = input(true, "Paint Consolidation Area", group="CONSOLIDATION ZONES") colorZone = input(color.new(color.blue, 70), "Zone Color", group="CONSOLIDATION ZONES") box_ob = input.bool(false, "Toggle Order Block", group="ORDER BLOCK") box_hide_gray = input.bool(false, "Hide gray boxes", group="ORDER BLOCK") bos_type = input.string("High and Low", "MSB trigger", , group="ORDER BLOCK") box_sv = input.bool(true, "Plot demand boxes", group="ORDER BLOCK") box_test_delay = input.int(3, "Delay to count test of demand box", 1, group="ORDER BLOCK") box_fill_delay = input.int(3, "Delay to count fill of demand box", 1, group="ORDER BLOCK") box_test_sv = input.bool(true, "Dim tested demand boxes", group="ORDER BLOCK") box_stop_sv = input.bool(true, "Stop plotting filled demand boxes", group="ORDER BLOCK") eliteVP = input(false, "Elite volume profile", group="ELITE VOLUME PROFILE") colorBorderVP = input(color.new(color.black, 80), "Border color", group="ELITE VOLUME PROFILE") colorBuyVP = input(#7F1623, "Buy volume", group="ELITE VOLUME PROFILE") colorSellVP = input(#00DD00, "Sell volume", group="ELITE VOLUME PROFILE") offset = input.int(2, "Offset", 2, 20, group="ELITE VOLUME PROFILE") lookback = input.int(100, "Lookback", 14, 10000, group="ELITE VOLUME PROFILE") levelNum = input.int(100, "Number of levels", 10, 1000, group="ELITE VOLUME PROFILE") levelWidth = input.int(50, "Level width", 2, 100, group="ELITE VOLUME PROFILE") if auto_button == false sensitivity else if auto_button == true sensitivity := volatility // Functions f_chartTfInMinutes() => float _resInMinutes = timeframe.multiplier * ( timeframe.isseconds ? 1. / 60 : timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60. * 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na) atr(len) => tr = ta.tr atr = 0.0 atr := nz(atr + (tr - atr ) / len, tr) supertrend(src, factor, len) => atr = ta.atr(len) upperBand = src + factor * atr lowerBand = src - factor * atr prevLowerBand = nz(lowerBand ) prevUpperBand = nz(upperBand ) lowerBand := lowerBand > prevLowerBand or close < prevLowerBand ? lowerBand : prevLowerBand upperBand := upperBand < prevUpperBand or close > prevUpperBand ? upperBand : prevUpperBand int direction = na float superTrend = na prevSuperTrend = superTrend if prevSuperTrend == prevUpperBand direction := close > upperBand ? 1 : -1 else direction := close < lowerBand ? -1 : 1 superTrend := direction == 1 ? lowerBand : direction == -1 ? upperBand : na dchannel(len)=> hh = ta.highest(len) ll = ta.lowest (len) trend = 0 trend := close > hh ? 1 : close < ll ? -1 : nz(trend ) trendScalper(show, len1, len2, len3, colorBull, colorBear, colorBarBull, colorBarBear) => avgOC = math.avg(open, close) ha_o = 0.0, ha_o := na(ha_o ) ? avgOC : (ha_o + ohlc4 ) / 2 ema1 = ta.ema(ha_o, len1), ema2 = ta.ema(ha_o, len2), ema3 = ta.ema(ha_o, len3) ris1 = ema1 > ema1 , ris2 = ema2 > ema2 , ris3 = ema3 > ema3 fal1 = ema1 < ema1 , fal2 = ema2 < ema2 , fal3 = ema3 < ema3 colorEma1 = ris1 ? colorBull : fal1 ? colorBear : na, colorEma2 = ris2 ? colorBull : fal2 ? colorBear : na, colorEma3 = ris3 ? colorBull : fal3 ? colorBear : na fillEma1 = avgOC > ema1 ? colorBull : avgOC < ema1 ? colorBear : na, fillEma2 = ema1 > ema2 ? colorBull : ema1 < ema2 ? colorBear : na, fillEma3 = ema2 > ema3 ? colorBull : ema2 < ema3 ? colorBear : na colorBar = close < ema1 and close < ema2 ? colorBarBear : colorBarBull candlesMom() => = ta.macd(close, 12, 26, 9) (macd > 0 and macd > macd ) or (macd < 0 and macd < macd ) trailingSL(buy, sell, factor, len, usePerc, perc) => atr = atr(len) upperBand = high + (usePerc ? high * (perc / 100) : factor * atr) lowerBand = low - (usePerc ? low * (perc / 100) : factor * atr) prevLowerBand = nz(lowerBand ) prevUpperBand = nz(upperBand ) lowerBand := lowerBand > prevLowerBand or buy ? lowerBand : prevLowerBand upperBand := upperBand < prevUpperBand or sell ? upperBand : prevUpperBand int direction = na float stop = na prevSuperTrend = stop if prevSuperTrend == prevUpperBand direction := buy ? 1 : -1 else direction := sell ? -1 : 1 stop := direction == 1 ? lowerBand : direction == -1 ? upperBand : na add_to_zz(zz, val, bi) => array.unshift(zz, bi) array.unshift(zz, val) if array.size(zz) > 12 array.pop(zz) update_zz(zz, val, bi, dir) => if array.size(zz) == 0 add_to_zz(zz, val, bi) else if dir == 1 and val > array.get(zz, 0) or dir == -1 and val < array.get(zz, 0) array.set(zz, 0, val) array.set(zz, 1, bi) 0 float ph = ta.pivothigh(high, 10, 10) float pl = ta.pivotlow (low , 10, 10) LSRstyle = lineSrStyle == "Dashed" ? line.style_dashed : lineSrStyle == "Solid" ? line.style_solid : line.style_dotted prdhighest = ta.highest(300) prdlowest = ta.lowest (300) cwidth = (prdhighest - prdlowest) * 10 / 100 var pivotvals = array.new_float(0) if ph or pl array.unshift(pivotvals, ph ? ph : pl) if array.size(pivotvals) > 20 array.pop(pivotvals) get_sr_vals(ind) => float lo = array.get(pivotvals, ind) float hi = lo int numpp = 0 for y = 0 to array.size(pivotvals) - 1 by 1 float cpp = array.get(pivotvals, y) float wdth = cpp <= lo ? hi - cpp : cpp - lo if wdth <= cwidth lo := cpp <= lo ? cpp : lo hi := cpp > lo ? cpp : hi numpp += 1 numpp var sr_up_level = array.new_float(0) var sr_dn_level = array.new_float(0) sr_strength = array.new_float(0) find_loc(strength) => ret = array.size(sr_strength) for i = ret > 0 ? array.size(sr_strength) - 1 : na to 0 by 1 if strength <= array.get(sr_strength, i) break ret := i ret ret check_sr(hi, lo, strength) => ret = true for i = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1 if array.get(sr_up_level, i) >= lo and array.get(sr_up_level, i) <= hi or array.get(sr_dn_level, i) >= lo and array.get(sr_dn_level, i) <= hi if strength >= array.get(sr_strength, i) array.remove(sr_strength, i) array.remove(sr_up_level, i) array.remove(sr_dn_level, i) ret else ret := false ret break ret // Get components rsi = ta.rsi(close, 14) vosc = ta.obv - ta.ema(ta.obv, 20) bs = ta.ema(nz(math.abs((open - close) / (high - low) * 100)), 3) ema = ta.ema(close, 200) emaBull = close > ema equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes() higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes() too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10) securityNoRep(sym, res, src) => bool bull = na bull := equal_tf(res) ? src : bull bull := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src) if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res) bull := array.pop(bull_array) array.clear(bull_array) bull TF1Bull = securityNoRep(syminfo.tickerid, "1" , emaBull) TF3Bull = securityNoRep(syminfo.tickerid, "3" , emaBull) TF5Bull = securityNoRep(syminfo.tickerid, "5" , emaBull) TF10Bull = securityNoRep(syminfo.tickerid, "10" , emaBull) TF15Bull = securityNoRep(syminfo.tickerid, "15" , emaBull) TF30Bull = securityNoRep(syminfo.tickerid, "30" , emaBull) TF60Bull = securityNoRep(syminfo.tickerid, "60" , emaBull) TF120Bull = securityNoRep(syminfo.tickerid, "120" , emaBull) TF240Bull = securityNoRep(syminfo.tickerid, "240" , emaBull) TF720Bull = securityNoRep(syminfo.tickerid, "720" , emaBull) TFDBull = securityNoRep(syminfo.tickerid, "1440", emaBull) ema150 = ta.ema(close, 150) ema250 = ta.ema(close, 250) hma55 = ta.hma(close, 55 ) = ta.macd(close, 12, 26, 9) supertrend = supertrend(ohlc4, sensitivity, 10) maintrend = dchannel(30) confBull = (ta.crossover (close, supertrend) or (ta.crossover (close, supertrend) and maintrend < 0)) and macd > 0 and macd > macd and ema150 > ema250 and hma55 > hma55 and maintrend > 0 confBear = (ta.crossunder(close, supertrend) or (ta.crossunder(close, supertrend) and maintrend > 0)) and macd < 0 and macd < macd and ema150 < ema250 and hma55 < hma55 and maintrend < 0 trendcloud = supertrend(ohlc4, periodTrendCloud == "Long term" ? 7 : 4, 10) hma = fastTrendCloud ? ta.hma(close, fastTrendCloudLen) : na none = close > 0 = ta.dmi(14, 14) consFilter = adx > 20 smartFilter = ta.ema(close, 200) volFilter = (ta.ema(volume, 25) - ta.ema(volume, 26)) / ta.ema(volume, 26) > 0 trendFilter = trendcloud bull = (strategy == "Normal" ? ta.crossover (close, supertrend) : confBull and not confBull ) and strategy != "Trend scalper" and (smartSignalsOnly ? close > smartFilter : none) and (consSignalsFilter ? consFilter : none) and (highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud == "New" ? ema150 > ema250 : close > trendFilter) : none) bear = (strategy == "Normal" ? ta.crossunder(close, supertrend) : confBear and not confBear ) and strategy != "Trend scalper" and (smartSignalsOnly ? close < smartFilter : none) and (consSignalsFilter ? consFilter : none) and (highVolSignals ? volFilter : none) and (signalsTrendCloud ? (periodTrendCloud == "New" ? ema150 < ema250 : close < trendFilter) : none) countBull = ta.barssince(bull) countBear = ta.barssince(bear) trigger = nz(countBull, bar_index) < nz(countBear, bar_index) ? 1 : 0 = trendScalper(strategy == "Trend scalper" ? true : false, 5, 9, 21, color.green, color.red, #00DD00, #DD0000) trailingStop = trailingSL(bull, bear, 2.2, 14, usePercSL, percTrailingSL) float _ph = ta.highestbars(high, periodSwings) == 0 ? high : na float _pl = ta.lowestbars (low, periodSwings) == 0 ? low : na var _dir = 0, dir_ = _pl and na(_ph) ? -1 : _dir, _dir := _ph and na(_pl) ? 1 : dir_, dirChg = ta.change(_dir) var zz = array.new_float(0), zzOld = array.copy(zz) float zzLive = _ph or _pl ? (dirChg ? add_to_zz(zz, _dir == 1 ? _ph : _pl, bar_index) : update_zz(zz, _dir == 1 ? _ph : _pl, bar_index, _dir)) : na aA = ta.wma(srcTrendChannel, lenTrendChannel), b = ta.sma(srcTrendChannel, lenTrendChannel) A = 4 * b - 3 * aA, B = 3 * aA - 2 * b m = (A - B) / (lenTrendChannel - 1) d = 0., for i = 0 to lenTrendChannel - 1 by 1 l = B + m * i d += math.pow(srcTrendChannel - l, 2) rmse = math.sqrt(d / (lenTrendChannel - 1)) * 2 float hb_ = ta.highestbars(lbPeriod) == 0 ? high : na float lb_ = ta.lowestbars (lbPeriod) == 0 ? low : na var int dir = 0 float zz_ = na float pp = na var int consCnt = 0 var float condHi = na var float condLo = na float H_ = ta.highest(lenCons) float L_ = ta.lowest (lenCons) var line lineUp = na var line lineDn = na bool breakUp = false bool breakDn = false var float pvh1_price = array.new_float(1000, na) var int pvh1_time = array.new_int (1000, na) var float pvl1_price = array.new_float(1000, na) var int pvl1_time = array.new_int (1000, na) var float pvh2_price = array.new_float(1000, na) var int pvh2_time = array.new_int (1000, na) var float pvl2_price = array.new_float(1000, na) var int pvl2_time = array.new_int (1000, na) var float htcmrll_price = na var int htcmrll_time = na var float ltcmrhh_price = na var int ltcmrhh_time = na var box long_boxes = array.new_box() var box short_boxes = array.new_box() var float temp_pv_0 = na var float temp_pv_1 = na var float temp_pv_2 = na bool pvh = high < high and high > high bool pvl = low > low and low < low int pv1_time = bar_index float pv1_high = high float pv1_low = low float trigger_high = bos_type == "High and Low" ? high : math.max(open, close) float trigger_low = bos_type == "High and Low" ? low : math.min(open, close) rangeHigh = ta.highest(high, lookback) rangeLow = ta.lowest(low, lookback) rangeHeight = rangeHigh - rangeLow histogramHeight = rangeHeight / levelNum histogramLowList = array.new_float(levelNum, na) histogramHighList = array.new_float(levelNum, na) histogramBuyVolumeList = array.new_float(levelNum, 0.0) histogramSellVolumeList = array.new_float(levelNum, 0.0) var buyBars = array.new_box(365, na) for i = 0 to 364 box.delete(array.get(buyBars, i)) var sellBars = array.new_box(365, na) for i = 0 to 364 box.delete(array.get(sellBars, i)) // Colors green = #00DD00, green50 = color.new(green, 50), green20 = color.new(green, 80) red = #DD0000, red50 = color.new(red, 50), red20 = color.new(red, 80) silver = #B2B5BE, silver50 = color.new(silver, 50), silver20 = color.new(silver, 80) // Plots atrBand = usePercSL ? (trigger ? low : high) * (percTrailingSL / 100) : ta.atr(14) * 2.2 atrStop = trigger ? low - atrBand : high + atrBand lastTrade(src) => ta.valuewhen(bull or bear, src, 0) entry_y = lastTrade(close) stop_y = lastTrade(atrStop) tp1_y = (entry_y-lastTrade(atrStop))*multTP1 + entry_y tp2_y = (entry_y-lastTrade(atrStop))*multTP2 + entry_y tp3_y = (entry_y-lastTrade(atrStop))*multTP3 + entry_y labelTpSl(cond, y, txt, color) => label labelTpSl = enableTpSlAreas and cond ? label.new(bar_index + 1, y, txt, xloc.bar_index, yloc.price, color, label.style_label_left, color.white, size.normal) : na label.delete(labelTpSl ) labelTpSl(none, entry_y, "Entry : " + str.tostring(math.round_to_mintick(entry_y)), color.orange) labelTpSl(none, stop_y , "Stop loss : " + str.tostring(math.round_to_mintick(atrStop)), color.red) labelTpSl(useTP1 and multTP1 != 0, tp1_y, "TP 1 : " + str.tostring(math.round_to_mintick(tp1_y)), color.green) labelTpSl(useTP2 and multTP2 != 0, tp2_y, "TP 2 : " + str.tostring(math.round_to_mintick(tp2_y)), color.green) labelTpSl(useTP3 and multTP3 != 0, tp3_y, "TP 3 : " + str.tostring(math.round_to_mintick(tp3_y)), color.green) lineTpSl(cond, y, color, style) => line lineTpSl = enableTpSlAreas and cond ? line.new(bar_index - (trigger ? countBull : countBear), y, bar_index + 1, y, xloc.bar_index, extend.none, color, style) : na line.delete(lineTpSl ) lineTpSl(none, entry_y, color.orange, line.style_dashed) lineTpSl(none, stop_y , color.red , line.style_solid ) lineTpSl(useTP1 and multTP1 != 0, tp1_y, color.green, line.style_dotted) lineTpSl(useTP2 and multTP2 != 0, tp2_y, color.green, line.style_dotted) lineTpSl(useTP3 and multTP3 != 0, tp3_y, color.green, line.style_dotted) var dashboard_loc = locationDashboard == "Top right" ? position.top_right : locationDashboard == "Top left" ? position.top_left : locationDashboard == "Middle right" ? position.middle_right : locationDashboard == "Middle left" ? position.middle_left : locationDashboard == "Bottom right" ? position.bottom_right : position.bottom_left var dashboard_size = sizeDashboard == "Tiny" ? size.tiny : sizeDashboard == "Small" ? size.small : size.normal var dashboard = table.new(dashboard_loc, 2, 20, colorBackground, colorFrame, 3, colorBorder, 3) dashboard_cell(column, row, txt) => table.cell(dashboard, column, row, txt, 0, 0, color.white, text_size=dashboard_size) dashboard_cell_bg(column, row, col) => table.cell_set_bgcolor(dashboard, column, row, col) if barstate.islast and enableDashboard dashboard_cell(0, 0 , "Current strategy") dashboard_cell(0, 1 , "Current sensitivity") dashboard_cell(0, 2 , "Current Position") dashboard_cell(0, 3 , "Current trend") dashboard_cell(0, 4 , "Trend strength") dashboard_cell(0, 5 , "Volume") dashboard_cell(0, 6 , "Volatility") dashboard_cell(0, 7 , "Momentum") dashboard_cell(0, 8 , "Timeframe trends📊"), table.merge_cells(dashboard, 0, 8, 1, 8) dashboard_cell(0, 9 , "1 min") dashboard_cell(0, 10, "3 min") dashboard_cell(0, 11, "5 min") dashboard_cell(0, 12, "10 min") dashboard_cell(0, 13, "15 min") dashboard_cell(0, 14, "30 min") dashboard_cell(0, 15, "1 Hour") dashboard_cell(0, 16, "2 Hour") dashboard_cell(0, 17, "4 Hour") dashboard_cell(0, 18, "12 Hour") dashboard_cell(0, 19, "Daily") dashboard_cell(1, 0 , strategy) dashboard_cell(1, 1 , str.tostring(sensitivity)) dashboard_cell(1, 2 , strategy != "Trend scalper" ? (trigger ? "Buy" : "Sell") : ""), dashboard_cell_bg(1, 2, strategy != "Trend scalper" ? (trigger ? color.green : color.red) : colorBackground) dashboard_cell(1, 3 , emaBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 3, emaBull ? color.green : color.red) dashboard_cell(1, 4 , str.tostring(bs, "0.0") + " %") dashboard_cell(1, 5 , vosc > 0 ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 5, vosc > 0 ? color.green : color.red) dashboard_cell(1, 6 , adx > 20 ? "Trending 🚀" : "Ranging ⚠️"), dashboard_cell_bg(1, 6, adx > 20 ? color.green : color.orange) dashboard_cell(1, 7 , rsi > 50 ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 7, rsi > 50 ? color.green : color.red) dashboard_cell(1, 9 , TF1Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 9 , TF1Bull ? color.green : color.red) dashboard_cell(1, 10, TF3Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 10, TF3Bull ? color.green : color.red) dashboard_cell(1, 11, TF5Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 11, TF5Bull ? color.green : color.red) dashboard_cell(1, 12, TF10Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 12, TF10Bull ? color.green : color.red) dashboard_cell(1, 13, TF15Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 13, TF15Bull ? color.green : color.red) dashboard_cell(1, 14, TF30Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 14, TF30Bull ? color.green : color.red) dashboard_cell(1, 15, TF60Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 15, TF60Bull ? color.green : color.red) dashboard_cell(1, 16, TF120Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 16, TF120Bull ? color.green : color.red) dashboard_cell(1, 17, TF240Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 17, TF240Bull ? color.green : color.red) dashboard_cell(1, 18, TF720Bull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 18, TF720Bull ? color.green : color.red) dashboard_cell(1, 19, TFDBull ? "Bullish" : "Bearish"), dashboard_cell_bg(1, 19, TFDBull ? color.green : color.red) l(css, k) => line lr = enableAutoTrend ? line.new(bar_index - lenTrendChannel + 1, A + k, bar_index, B + k, extend=extend.right, color=css) : na line.delete(lr ) l(color.blue, rmse), l(color.blue, 0), l(color.blue, -rmse) // //======================================
Индикатор Pine Script™
от ckovan
1
XAUUSD STRATGEY BUY AND SELL SIGNALSThis indicator primarily focuses on the concepts of Overbought and Oversold conditions, serving as a tool for short-term trading strategies. It provides modest yet reliable signals for traders. The fundamental operation of the indicator is outlined as follows: For purchasing, the indicator monitors the asset for an Oversold condition as indicated by the Relative Strength Index (RSI). Subsequently, a buy signal is generated when the price chart crosses the lower boundary of the Envelope indicator from below to above. Conversely, for selling, the indicator observes the asset for an Overbought condition according to the RSI. A sell signal is triggered when the price chart crosses the upper boundary of the Envelope indicator from above to below. The underlying principle is the alignment between the price movement and the RSI readings. The optimal settings I have developed are as follows: - Time frame: 15 minutes - Overbought threshold: 80 - Oversold threshold: 25 - RSI Length: 8 This approach can be applied across various financial instruments, but it is essential to establish clear profit and loss limits.
Индикатор Pine Script™
от cupra_inc
1
[blackat] L2 Bull and Bear Heaven LineOVERVIEW The L2 Bull and Bear Heaven Line script is a custom indicator designed to visualize trend directions using Exponential Moving Average (EMA)-based lines and generate trade signals based on crossovers between those lines. It also incorporates an RSI-like feature to provide additional insight into overbought and oversold conditions. FEATURES Utilizes two EMAs: a longer-term "Heaven Line" (default 60 bars) and a shorter-term "Trading Line" (default 30 bars). Generates buy/sell signals based on crossovers between the "Trading Line" and "Heaven Line". Identifies potential turning points in the market, indicating shifts from bullish to bearish or vice versa. Includes an "Operation Line" similar to RSI, aiding in detecting overbought/oversold levels. HOW TO USE Add the script to your TradingView chart. Observe the crossovers between the "Trading Line" and "Heaven Line": Buy signal when the "Trading Line" crosses above the "Heaven Line". Sell signal when the "Trading Line" crosses below the "Heaven Line". Monitor the "Operation Line" for additional confirmation: Secondary sell signal when the "Operation Line" drops below 90% and there is downward price action. Complementary buy signal when the "Operation Line" rises above 10% and there is upward price action. Consider the identified trend direction and potential turning points to make informed trading decisions. LIMITATIONS The effectiveness of the signals depends on the chosen time frame and specific market conditions. False signals may occur due to volatile price movements or rapid changes in market sentiment. NOTES This script combines traditional technical analysis tools like EMAs with an RSI-like approach to enhance decision-making processes. Users should backtest the strategy under various market scenarios before implementing it in live trading. THANKS Special thanks to the contributors whose work inspired parts of this script.
Индикатор Pine Script™
от blackcat1402
1
Ultra Round NumbersThe Ultra Round Numbers indicator is designed to improve your market analysis by visually emphasizing significant price levels. These round numbers often act as psychological levels where traders and investors tend to make decisions. With this tool, you can easily spot these levels, adjust their precision, and customize their appearance. Detailed Description Ultra Round Numbers dynamically plots horizontal lines at key price intervals based on user-defined step sizes. These intervals represent round-numbered price levels, which can serve as critical support and resistance zones. Step Configurations The indicator features three customizable steps: Biggest, Middle, and Smallest. Each step allows you to define: The step size in price to determine the intervals for the lines. The maximum number of lines above and below the current price. The color, style, and thickness of the lines for better visualization. The script efficiently handles the creation and deletion of lines to prevent clutter on the chart. It ensures only the relevant lines (from biggest step to lowest step) are displayed based on your settings and the current price movement. This indicator is a powerful yet user-friendly indicator for identifying psychological price levels on your charts. With fully customizable steps, dynamic line management, and clean visuals, this tool empowers traders of all skill levels to make more informed trading decisions.
Индикатор Pine Script™
от Rathack
RV- ProTime Dynamic Trend AnalyzerRV-ProTime Dynamic Trend Analyzer is a state-of-the-art trading indicator meticulously designed to provide unparalleled insights across all timeframes. It combines essential tools for trend, momentum, and key level analysis, making it a one-stop solution for traders. The core feature, Dynamic Multi-Timeframe Supertrend, sets this indicator apart, complemented by additional tools for comprehensive market analysis. Here’s everything this indicator offers: Key Features: 1. Dynamic Multi-Timeframe Supertrend (Core Feature) Daily, Weekly, Monthly, and Yearly Supertrends are plotted directly on the chart, providing precise trend direction across multiple timeframes. Lower timeframe Supertrends are automatically hidden on higher timeframe charts (e.g., Weekly and Monthly ) to reduce clutter and maintain precision, ensuring a clean and actionable view. These Supertrends help identify major trend reversals, pullbacks, and continuation zones, empowering traders to make informed decisions regardless of the trading horizon. Whether you’re scalping on intraday charts or strategizing long-term trades, this feature ensures you always have the right trend perspective at your fingertips. 2. Quarterly and Yearly Earnings Table A built-in table to display Quarterly and Yearly Earnings, allowing traders to incorporate fundamental analysis into their strategies effortlessly. Provides quick insights into the financial health and performance of stocks, helping traders align with strong-performing assets. 3. RSI & MACD Multi-Timeframe Table Visualize RSI and MACD values across multiple timeframes, including 1-minute, 5-minute, 15-minute, 1-hour, Daily, Weekly, and Monthly. This table helps detect overbought/oversold zones and shifts in momentum, offering a robust foundation for entry and exit strategies. 4. Exponential Moving Averages (EMAs) Includes four customizable EMAs to support moving average crossovers, trend identification, and dynamic support/resistance levels. Ideal for traders seeking to refine their entries and exits based on trend-following strategies. 5. Fibonacci Pivots Features two sets of Fibonacci-based Pivot Points for higher and lower timeframes. These pivots act as critical support and resistance zones, aiding traders in identifying key price levels for potential reversals or breakouts. 6. Auto 52-Week and All-Time High/Low Levels Automatically plots 52-week highs/lows and all-time highs/lows, with visually distinct candle coloring for added clarity. Provides immediate identification of stocks reaching pivotal breakout or reversal zones, making it invaluable for trend-following and breakout strategies. 7. User-Friendly Customization All features are toggleable, allowing traders to customize the indicator based on their unique trading preferences and strategies. Why This Indicator Stands Out: The RV-ProTime Dynamic Trend Analyzer isn’t just another indicator—it’s a comprehensive trend detection and market analysis system. The Daily, Weekly, Monthly Supertrends serve as its backbone, offering unmatched flexibility and adaptability for traders across all timeframes. These Supertrends allow traders to: Identify and align with the prevailing trend at any level. Avoid conflicting signals by dynamically hiding lower timeframe trends on higher timeframe charts. Gain an edge in both short-term and long-term trading strategies by providing a consistent view of market direction. Whether you’re an intraday scalper, swing trader, or position trader, this indicator adapts to your needs, combining the power of trend-following tools with fundamental and technical insights. Unlock the ultimate trading experience with the RV-ProTime Dynamic Trend Analyzer: backtest the indicator, take trades with the best risk-reward setups, and trade with a stop-loss aligned with your strategy to achieve consistent success!
Индикатор Pine Script™
от rupatil
FGW | dobofulopThis indicator automatically detects recent swing highs and lows, then plots two Fibonacci-based retracement lines to highlight the “Golden Zone.” By default, it uses the 50% and 61.8% Fibonacci levels as potential support or resistance. The script can also fill the zone between these levels to visually emphasize possible reversal areas. Ideal for identifying key pullback zones in a trending market, the Fibonacci Golden Wave helps traders gauge where a correction might end and a trend may resume.
Индикатор Pine Script™
от Dfulop98
Fear and Greed Index By EquityPath(DevHunainmq)Description: 🚀 **Fear and Greed Index Indicator for TradingView** 🚀 Unlock the power of **market sentiment analysis** with this sleek and futuristic Fear and Greed Index indicator! 🎯 Designed for traders who want to make data-driven decisions, this indicator visualizes the emotional state of the market directly on your charts. 🌟 🔴 **Fear Zones:** Spot undervalued opportunities as fear dominates the market. 🟠 **Neutral Zones:** Identify consolidation and prepare for breakout moves. 🟢 **Greed Zones:** Detect potential market euphoria and risk of overvaluation. With gradient backgrounds, dynamic thresholds, and real-time labels, this tool is not just functional but visually stunning. Perfect for any trader looking to incorporate **sentiment analysis** into their strategy. 📈 **Features:** ✅ Easy-to-read Fear and Greed graph 📊 ✅ Dynamic color-coded zones (Red for Fear, Green for Greed) ✅ Auto-updating sentiment labels 📍 ✅ Designed for all market types (crypto, stocks, forex) Take control of your trades by understanding **when to buy** and **when to sell** using this powerful indicator. 💡 Let the market sentiment guide your strategy! --- ### Hashtags: #TradingView #Indicator #FearAndGreedIndex #MarketSentiment #CryptoTrading #ForexTrading #StockTrading #TechnicalAnalysis #TradingTools #FuturisticTrading #SentimentAnalysis #FearZones #GreedZones #TradingStrategy #TradeSmarter #MarketPsychology
Индикатор Pine Script™
от hunainmq
XAUUSD TDFI & EMA TREND STRATEGYThe Trend Direction Force Index v2 (TDFI) strategy is a powerful tool designed to identify trend direction and momentum shifts in the market. This strategy leverages the TDFI indicator to signal entries and exits based on trend strength and directional force. Key features include: Customizable Moving Averages: Users can select from various moving average types (EMA, WMA, VWMA, Hull, TEMA, etc.) for precise trend analysis. Dynamic EMA Filters: The strategy integrates an EMA filter, allowing users to choose between 20, 50, or 100-period EMA for refined entry and exit signals. Clear Entry and Exit Logic: Enter long when the TDFI signal exceeds the high threshold, and the price stays above the selected EMA. Exit long when the price closes below the selected EMA. Enter short when the TDFI signal drops below the low threshold, and the price remains under the selected EMA. Exit short when the price closes above the selected EMA. Use Case: This strategy is ideal for trend-following traders seeking automated decision-making in identifying strong uptrends or downtrends. It combines momentum strength with customizable filters to adapt to different market conditions. Settings: Lookback Periods: Configurable for TDFI calculation and dynamic adjustment. Filter Thresholds: High and low thresholds to define overbought/oversold zones. Moving Average Types: Choose the preferred smoothing method for the trend. Note: The TDFI line is not plotted, as the focus is on entry/exit actions driven by the signal. Fine-tune the parameters to align with your trading strategy.
Стратегия Pine Script™
от cupra_inc
Fibonacci TsunamiFibonacci Moving Averages (FMAs) are a technical analysis tool used in financial markets to help identify trends and potential reversal points. They combine the concept of moving averages with Fibonacci retracement levels, which are widely used in technical analysis to predict possible support and resistance levels based on the Fibonacci sequence. Key Concepts: Moving Averages (MA): A moving average is a mathematical calculation that smooths out past price data to create a trend-following indicator. It helps to identify the direction of the trend and reduce market noise. Fibonacci Sequence: This is a series of numbers where each number is the sum of the two preceding ones. In technical analysis, Fibonacci retracement levels (like 23.6%, 38.2%, 50%, 61.8%, and 100%) are often used to identify potential support and resistance levels. How Fibonacci Moving Averages Work: Fibonacci Moving Averages are calculated by applying Fibonacci ratios to the standard moving average calculation. The most common Fibonacci ratios used in FMAs are 34, 55, 89, 144, and 233. These numbers are significant because they are part of the Fibonacci sequence and are believed to represent key points of support and resistance in financial markets. For example: A 34-period Fibonacci moving average would be calculated using the last 34 data points. A 55-period Fibonacci moving average would be calculated using the last 55 data points. Other Fibonacci periods, such as 89 and 144, could also be used depending on the trader's preferences. How Traders Use Fibonacci Moving Averages: Trend Identification: Traders use FMAs to help identify the direction of the trend. When the price is above a Fibonacci moving average, it suggests that the market is in an uptrend. Conversely, when the price is below the moving average, it may indicate a downtrend. Support and Resistance Levels: The Fibonacci moving averages themselves can act as dynamic support and resistance levels. For instance, if the price is approaching a Fibonacci moving average from below, it may encounter resistance. If the price is approaching from above, it may find support. Crossovers: Similar to other moving averages, Fibonacci moving averages are often used in conjunction with one another. A crossover of a shorter-term FMA (e.g., 34-period) above a longer-term FMA (e.g., 233-period) can indicate a bullish signal, while the opposite crossover may signal a bearish trend. Combining with Other Indicators: Many traders use FMAs in conjunction with other technical analysis tools, like the relative strength index (RSI) or MACD, to confirm signals and enhance decision-making. Example: If a trader is using the 34-period and 55-period Fibonacci moving averages, a bullish crossover would occur when the 34-period FMA crosses above the 55-period FMA. This is often considered a buy signal. If the price is approaching the 89-period Fibonacci moving average after an uptrend, the 89-period level may act as resistance and could be used to set a target price.
Индикатор Pine Script™
от ForexStop
BTCUSDT 4h Chart - Supertrend [CYRANO]This strategy uses the Supertrend indicator to generate buy and sell signals based on trend direction. It is specifically designed for the BTC/USDT pair on a 4-hour chart. Here's a detailed breakdown of its components and functionality: Key Features: Supertrend Indicator: Uses the Average True Range (ATR) to calculate dynamic support and resistance levels. Generates an uptrend (green) or downtrend (red) signal based on price action: Uptrend (green): When the price is above the Supertrend level. Downtrend (red): When the price is below the Supertrend level. Date Range Filter: Allows users to specify a backtesting period using Start Date and End Date. All trades are executed only within this date range. If the current date is outside the range, the strategy closes all open positions. Trade Logic: Buy Signal: Enter a long position when the trend changes to green (uptrend). Sell Signal: Exit the long position when the trend changes to red (downtrend). Visualizations: Plots the Supertrend line for both uptrend and downtrend scenarios. Fills the area between the Supertrend line and the midpoint of the candle body for visual clarity: Green Fill: Indicates an uptrend. Red Fill: Indicates a downtrend. Alerts: Alerts are set up for: Uptrend (green). Downtrend (red). Trend changes (switch between uptrend and downtrend). Strategy Settings: Uses 100% of equity for each trade. Configures a commission of 0.1% and slippage of 3. Indicator Inputs: ATR Length: Default: 10. Determines the number of bars used to calculate the Average True Range. Factor: Default: 3.0. Multiplier used to calculate the Supertrend levels above and below the price. Start and End Date: Default: 1st January 2018 to 31st December 2069. Controls the date range for backtesting. Execution Logic: Entry Conditions: A long position is entered when the trend is green (uptrend). Exit Conditions: The long position is closed when the trend turns red (downtrend). Strengths: Simplicity: The strategy is straightforward and easy to understand, relying solely on trend direction from the Supertrend indicator. Visual Clarity: The plots and filled areas make it easy to interpret market trends at a glance. Customizable: Inputs allow users to adjust the ATR length and factor to fit their trading style and market conditions. Limitations: No Short Trades: The strategy only supports long trades and does not enter short positions. Whipsaw Risk: In ranging markets, frequent trend changes may lead to false signals and losses. No Risk Management: Does not include stop-loss or take-profit levels, relying entirely on trend changes for exits. Use Case: This strategy is ideal for trend-following traders who want a clean and visual approach to identifying market trends. Its focus on simplicity and robust indicator logic makes it suitable for volatile instruments like BTC/USDT on higher timeframes. However, traders may need to incorporate additional risk management techniques or complementary indicators for enhanced performance.
Стратегия Pine Script™
от Cyrano
Auto Support/ResistanceThis script is an Auto Support/Resistance indicator for Pine Script. It automatically detects and displays support and resistance levels based on pivot points. The user can configure the lookback period to determine how many bars are considered for identifying pivot highs and lows. The script plots the support (green line), resistance (red line), and a centerline (blue line) on the chart. It also marks pivot points with labels and displays the current values of support, resistance, and the centerline in a table on the chart. This tool helps traders identify key price levels for their trading strategies.
Индикатор Pine Script™
от LickMeCrypto
NK-Heikin-ashi entry with defined Target and SL//Buy - Green heikin-ashi (with no lower shadow) is formed above vwap and Target at 50 pts and sqr off at cost.Exit at 15:01 if not //closed by then. //Sell - Red heikin-ashi (with no upper shadow) is formed below vwap and Target at 50 pts and sqr off at cost.Exit at 15:01 if not //closed by then. // need to update the code for trailing SL and fine tuning of Target for ATR Or ATR/2 or 40 pts for Nifty, etc..
Стратегия Pine Script™
от vikinyuvi
Trend Strength Signals Multi timeframe arrayAn experimental script used for contrarian purposes. When indicator shows Long TP market is expected to trend upwards and bulls start taking their profits, overall signaling bullish conditions but also overbought market. Likewise when Short TP pops up, market is expected to trend downwards and bears start taking their profits, overall signaling bearish conditions but with also oversold market. Ideally we wish to enter on a trending market after a pullback, therefore a possible use of this script could be to detect trending conditions on a higher timeframe then wait for a counter conditions on a lower timeframe and when the two timeframes align again look for possible entry in the direction of main timeframe e.g. assume we have bullish conditions on the 1h timeframe, with bulls starting to take their profits. At some point we will have a deeper pullback and so we expect that bears on the lower timeframe i.e 15m will start taking their profits. Once we start having bulls again on the lower timeframe taking profits we may consider that we are back in the main trend of the 1h chart and start looking for a bullish entry. The script is purely experimental, does not constitute financial advice and further testing is required! I strongly encourage people to feel free and play around, tweak and improve the script. Good luck!
Индикатор Pine Script™
от chriskokal1