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buy & sell//@version=5 indicator("Smoothed Heiken Ashi with Signals", " איתותי קנייה + איתותי מכירה", overlay=true, timeframe="", timeframe_gaps=true) import wallneradam/TAExt/8 // // User inputs // ha_smooth_length = input.int(10, "Smooth Length", minval=1, group="Before HA") ha_smooth_ma_type = input.string('EMA', 'MA Type', options= , group="Before HA") ha_after_smooth_length = input.int(10, "After Smooth Length", minval=1, group="After HA") ha_after_smooth_ma_type = input.string('EMA', 'After MA Type', options= , group="After HA") // // Calculation // = TAExt.heiken_ashi(smooth_length=ha_smooth_length, smooth_ma_type=ha_smooth_ma_type, after_smooth_length=ha_after_smooth_length) // // Support level calculation based on the last 14 candles // supportLevel = ta.lowest(l, 14) // // Buy/Sell Signals // buySignal = ta.crossover(c, o) // Close crosses above Open sellSignal = ta.crossunder(c, o) // Close crosses below Open // // Buy Signal 2 - After returning near support // buySignal2 = ta.crossover(c, o) and (l <= supportLevel or l - supportLevel < 0.005 * supportLevel) // // Plotting // plotcandle(o, h, l, c, title="Smoothed Heiken Ashi", color=o > c ? color.new(color.red, 60) : color.new(color.lime, 60), wickcolor=o > c ? color.new(color.red, 20) : color.new(color.lime, 20), bordercolor=o > c ? color.new(color.red, 10) : color.new(color.lime, 10)) // Plot Buy Signals plotshape(series=buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY") // Plot Sell Signals plotshape(series=sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL") // Plot Buy Signal 2 plotshape(series=buySignal2, title="Buy Signal 2", location=location.belowbar, color=color.blue, style=shape.labelup, text="BUY2")
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mos4516の投稿
1
buy & sell//@version=5 indicator("Smoothed Heiken Ashi with Signals", " איתותי קנייה + איתותי מכירה", overlay=true, timeframe="", timeframe_gaps=true) import wallneradam/TAExt/8 // // User inputs // ha_smooth_length = input.int(10, "Smooth Length", minval=1, group="Before HA") ha_smooth_ma_type = input.string('EMA', 'MA Type', options= , group="Before HA") ha_after_smooth_length = input.int(10, "After Smooth Length", minval=1, group="After HA") ha_after_smooth_ma_type = input.string('EMA', 'After MA Type', options= , group="After HA") // // Calculation // = TAExt.heiken_ashi(smooth_length=ha_smooth_length, smooth_ma_type=ha_smooth_ma_type, after_smooth_length=ha_after_smooth_length) // // Support level calculation based on the last 14 candles // supportLevel = ta.lowest(l, 14) // // Buy/Sell Signals // buySignal = ta.crossover(c, o) // Close crosses above Open sellSignal = ta.crossunder(c, o) // Close crosses below Open // // Buy Signal 2 - After returning near support // buySignal2 = ta.crossover(c, o) and (l <= supportLevel or l - supportLevel < 0.005 * supportLevel) // // Plotting // plotcandle(o, h, l, c, title="Smoothed Heiken Ashi", color=o > c ? color.new(color.red, 60) : color.new(color.lime, 60), wickcolor=o > c ? color.new(color.red, 20) : color.new(color.lime, 20), bordercolor=o > c ? color.new(color.red, 10) : color.new(color.lime, 10)) // Plot Buy Signals plotshape(series=buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY") // Plot Sell Signals plotshape(series=sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL") // Plot Buy Signal 2 plotshape(series=buySignal2, title="Buy Signal 2", location=location.belowbar, color=color.blue, style=shape.labelup, text="BUY2")
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mos4516の投稿
buy & sell//@version=5 indicator("Smoothed Heiken Ashi with Signals", " איתותי קנייה + איתותי מכירה", overlay=true, timeframe="", timeframe_gaps=true) import wallneradam/TAExt/8 // // User inputs // ha_smooth_length = input.int(10, "Smooth Length", minval=1, group="Before HA") ha_smooth_ma_type = input.string('EMA', 'MA Type', options= , group="Before HA") ha_after_smooth_length = input.int(10, "After Smooth Length", minval=1, group="After HA") ha_after_smooth_ma_type = input.string('EMA', 'After MA Type', options= , group="After HA") // // Calculation // = TAExt.heiken_ashi(smooth_length=ha_smooth_length, smooth_ma_type=ha_smooth_ma_type, after_smooth_length=ha_after_smooth_length) // // Support level calculation based on the last 14 candles // supportLevel = ta.lowest(l, 14) // // Buy/Sell Signals // buySignal = ta.crossover(c, o) // Close crosses above Open sellSignal = ta.crossunder(c, o) // Close crosses below Open // // Buy Signal 2 - After returning near support // buySignal2 = ta.crossover(c, o) and (l <= supportLevel or l - supportLevel < 0.005 * supportLevel) // // Plotting // plotcandle(o, h, l, c, title="Smoothed Heiken Ashi", color=o > c ? color.new(color.red, 60) : color.new(color.lime, 60), wickcolor=o > c ? color.new(color.red, 20) : color.new(color.lime, 20), bordercolor=o > c ? color.new(color.red, 10) : color.new(color.lime, 10)) // Plot Buy Signals plotshape(series=buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY") // Plot Sell Signals plotshape(series=sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL") // Plot Buy Signal 2 plotshape(series=buySignal2, title="Buy Signal 2", location=location.belowbar, color=color.blue, style=shape.labelup, text="BUY2")
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mos4516の投稿
Simulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2x Simulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2x
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C4LV1NBRの投稿
ZelosKapital Market BehaviourThe ZelosKapital Market Behaviour Indicator is a powerful tool designed to visually highlight market structure periods directly on your trading chart. This indicator identifies and labels the four key price action phases: Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL). Understanding these phases is critical for traders aiming to follow the trend or anticipate potential reversals.
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HrEichZelosKapitalの投稿
1
MVRV Z-Score (Topos e Fundos)No MVRV Z-Score, a linha roxa (que representa o valor do indicador) atingir ou ultrapassar a faixa vermelha geralmente indica que o ativo está em uma zona de sobrevalorização. Isso significa que o mercado pode estar próximo de um topo, e historicamente, esses momentos tendem a ser seguidos por correções de preço. O que acontece quando a linha roxa atinge a faixa vermelha? Zona Vermelha (Topo): Quando a linha roxa entra na faixa vermelha, o ativo está sendo negociado muito acima do seu valor realizado (Realized Value). Isso sugere que muitos investidores estão com lucros não realizados significativos, o que pode levar a vendas em massa e, consequentemente, a uma correção de preço. Sinal para traders e investidores: Para traders, pode ser um sinal de que o preço está próximo de um topo e que pode ser um bom momento para realizar lucros. Para investidores de longo prazo, pode ser um alerta para evitar compras nesse momento, aguardando uma possível correção. E se a linha roxa não atingir a faixa vermelha? Se a linha roxa não atingir a faixa vermelha, o ativo pode ainda ter espaço para valorização antes de atingir um topo. No entanto, é importante observar outros fatores do mercado, como volume, sentimento e contexto macroeconômico.
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1a15feab814f4d8fafa825daaa814cの投稿
CMS-Inspired SMC Strategy with Liquidity and FVG//@version=5 indicator("CMS-Inspired SMC Strategy with Liquidity and FVG", overlay=true) // === إعدادات المستخدم === capital = input.float(1000, title="رأس المال ($)", step=10) // رأس المال الكلي risk_percent = input.float(1, title="نسبة المخاطرة (%)", step=0.1) // نسبة المخاطرة max_trades = input.int(2, title="عدد الصفقات اليومية", step=1) // الحد الأقصى للصفقات اليومية session_start = input.time(timestamp("0000-01-01 08:00 +0000"), title="بداية الجلسة") // جلسة لندن session_end = input.time(timestamp("0000-01-01 16:00 +0000"), title="نهاية الجلسة") // جلسة لندن news_time = input.time(timestamp("0000-01-01 09:00 +0000"), title="وقت الأخبار المهمة") // الوقت المتوقع للأخبار // === أدوات إضافية === session_active = (time >= session_start and time <= session_end) // الجلسة الزمنية atr = ta.atr(14) // مؤشر ATR // === تحديد مناطق السيولة === highest_liq = ta.highest(high, 20) // أعلى نقطة في الـ 20 فترة lowest_liq = ta.lowest(low, 20) // أدنى نقطة في الـ 20 فترة // === فجوات القيمة العادلة (FVG) === fvg_condition = close > high and close < high // عندما يكون هناك فجوة بين الإغلاق والارتفاع // === إشارات التداول === // كسر الهيكل (BOS) high_break = ta.highest(high, 5) < close low_break = ta.lowest(low, 5) > close // مناطق Order Block bullish_ob = close < open // إشارات الشراء بناءً على الإغلاق bearish_ob = close > open // إشارات البيع بناءً على الإغلاق // إشارات الشراء والبيع بناءً على جميع الشروط long_signal = session_active and high_break and bullish_ob and fvg_condition and not (time >= news_time and time <= news_time + 3600000) // تجنب الأخبار short_signal = session_active and low_break and bearish_ob and fvg_condition and not (time >= news_time and time <= news_time + 3600000) // تجنب الأخبار // === إدارة رأس المال === capital_per_trade = (capital * risk_percent / 100) // نسبة رأس المال في الصفقة lot_size = capital_per_trade / (atr * 1.5) // حجم اللوت بناءً على الـ ATR ووقف الخسارة stop_loss = atr * 1.5 // وقف الخسارة بناءً على ATR take_profit = stop_loss * 2 // الهدف (نسبة مخاطرة/عائد 1:2) // === رسم الإشارات === var trade_count = 0 // عداد الصفقات اليومية if session_active if trade_count < max_trades if long_signal label.new(bar_index, high, "شراء", color=color.green, style=label.style_label_down) trade_count += 1 if short_signal label.new(bar_index, low, "بيع", color=color.red, style=label.style_label_up) trade_count += 1 // === تنبيه إشارات === if long_signal or short_signal alert("إشارة جديدة: " + (long_signal ? "شراء" : "بيع"), alert.freq_once_per_bar)
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boudiha636の投稿
Wilder Moving AverageThe Wilder Moving Average (WMA) is a technical analysis tool developed by J. Welles Wilder Jr. It is designed to identify trends and potential entry and exit points in the financial markets2. Unlike the simple moving average (SMA) or the exponential moving average (EMA), the Wilder Moving Average places more emphasis on recent price movements, making it more responsive to short-term changes in the market. Key Features: Smoothing Technique: Wilder's Moving Average uses a smoothing technique that gives greater weight to more recent data points. This results in a faster and more responsive moving average2. Calculation: The calculation involves subtracting the previous average from the current price and adding the resulting difference to the previous average. Usage: Traders use the Wilder Moving Average to identify trends, support and resistance levels, and potential crossovers, where the price crosses above or below the moving average, indicating a potential trend reversal.
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evanhallenの投稿
Regime Classifier Oscillator (AiBitcoinTrend)The Regime Classifier Oscillator (AiBitcoinTrend) is an advanced tool for understanding market structure and detecting dynamic price regimes. By combining filtered price trends, clustering algorithms, and an adaptive oscillator, it provides traders with detailed insights into market phases, including accumulation, distribution, advancement, and decline. This innovative tool simplifies market regime classification, enabling traders to align their strategies with evolving market conditions effectively. 👽 What is a Regime Classifier, and Why is it Useful? A Regime Classifier is a concept in financial analysis that identifies distinct market conditions or "regimes" based on price behavior and volatility. These regimes often correspond to specific phases of the market, such as trends, consolidations, or periods of high or low volatility. By classifying these regimes, traders and analysts can better understand the underlying market dynamics, allowing them to adapt their strategies to suit prevailing conditions. 👽 Common Uses in Finance Risk Management: Identifying high-volatility regimes helps traders adjust position sizes or hedge risks. Strategy Optimization: Traders tailor their approaches—trend-following strategies in trending regimes, mean-reversion strategies in consolidations. Forecasting: Understanding the current regime aids in predicting potential transitions, such as a shift from accumulation to an upward breakout. Portfolio Allocation: Investors allocate assets differently based on market regimes, such as increasing cash positions in high-volatility environments. 👽 Why It’s Important Markets behave differently under varying conditions. A regime classifier provides a structured way to analyze these changes, offering a systematic approach to decision-making. This improves both accuracy and confidence in navigating diverse market scenarios. 👽 How We Implemented the Regime Classifier in This Indicator The Regime Classifier Oscillator takes the foundational concept of market regime classification and enhances it with advanced computational techniques, making it highly adaptive. 👾 Median Filtering: We smooth price data using a custom median filter to identify significant trends while eliminating noise. This establishes a baseline for price movement analysis. 👾 Clustering Model: Using clustering techniques, the indicator classifies volatility and price trends into distinct regimes: Advance: Strong upward trends with low volatility. Decline: Downward trends marked by high volatility. Accumulation: Consolidation phases with subdued volatility. Distribution: Topping or bottoming patterns with elevated volatility. This classification leverages historical price data to refine cluster boundaries dynamically, ensuring adaptive and accurate detection of market states. Volatility Classification: Price volatility is analyzed through rolling windows, separating data into high and low volatility clusters using distance-based assignments. Price Trends: The interaction of price levels with the filtered trendline and volatility clusters determines whether the market is advancing, declining, accumulating, or distributing. 👽 Dynamic Cycle Oscillator (DCO): Captures cyclic behavior and overlays it with smoothed oscillations, providing real-time feedback on price momentum and potential reversals. Regime Visualization: Regimes are displayed with intuitive labels and background colors, offering clear, actionable insights directly on the chart. 👽 Why This Implementation Stands Out Dynamic and Adaptive: The clustering and refit mechanisms adapt to changing market conditions, ensuring relevance across different asset classes and timeframes. Comprehensive Insights: By combining price trends, volatility, and cyclic behaviors, the indicator provides a holistic view of the market. This implementation bridges the gap between theoretical regime classification and practical trading needs, making it a powerful tool for both novice and experienced traders. 👽 Applications 👾 Regime-Based Trading Strategies Traders can use the regime classifications to adapt their strategies effectively: Advance & Accumulation: Favorable for entering or holding long positions. Decline & Distribution: Opportunities for short positions or risk management. 👾 Oscillator Insights for Trend Analysis Overbought/oversold conditions: Early warning of potential reversals. Dynamic trends: Highlights the strength of price momentum. 👽 Indicator Settings 👾 Filter and Classification Settings Filter Window Size: Controls trend detection sensitivity. ATR Lookback: Adjusts the threshold for regime classification. Clustering Window & Refit Interval: Fine-tunes regime accuracy. 👾 Oscillator Settings Dynamic Cycle Oscillator Lookback: Defines the sensitivity of cycle detection. Smoothing Factor: Balances responsiveness and stability. Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
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aibitcointrendの投稿
خطوط عمودی تایم‌فریم//@version=5 indicator("خطوط عمودی تایم‌فریم", overlay=true) var line_color_daily = color.new(color.blue, 50) // رنگ خطوط روزانه var line_color_weekly = color.new(color.green, 50) // رنگ خطوط هفتگی var line_color_monthly = color.new(color.red, 50) // رنگ خطوط ماهانه // بررسی تایم‌فریم is_daily = timeframe.isintraday and timeframe.multiplier == 5 or timeframe.multiplier == 30 is_weekly = timeframe.isintraday and timeframe.multiplier == 60 is_monthly = timeframe.isintraday and timeframe.multiplier == 240 // رسم خطوط روزانه if is_daily and ta.change(time("D")) != 0 line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_daily, width=1) // رسم خطوط هفتگی if is_weekly and ta.change(time("W")) != 0 line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_weekly, width=2) // رسم خطوط ماهانه if is_monthly and ta.change(time("M")) != 0 line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_monthly, width=3)
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Real_MTの投稿
Binary Options Pro Helper By Himanshu AgnihotryThe Binary Options Pro Helper is a custom indicator designed specifically for one-minute binary options trading. This tool combines technical analysis methods like moving averages, RSI, Bollinger Bands, and pattern recognition to provide precise Buy and Sell signals. It also includes a time-based filter to ensure trades are executed only during optimal market conditions. Features: Moving Averages (EMA): Uses short-term (7-period) and long-term (21-period) EMA crossovers for trend detection. RSI-Based Signals: Identifies overbought/oversold conditions for entry points. Bollinger Bands: Highlights market volatility and potential reversal zones. Chart Pattern Recognition: Detects double tops (sell signals) and double bottoms (buy signals). Time-Based Filter: Trades only within specified hours (e.g., 9:30 AM to 11:30 AM) to avoid unnecessary noise. Visual Signals: Plots buy and sell markers directly on the chart for ease of use. How to Use: Setup: Add this script to your TradingView chart and select a 1-minute timeframe. Signal Interpretation: Buy Signal: Triggered when EMA crossover occurs, RSI is oversold (<30), and a double bottom pattern is detected. Sell Signal: Triggered when EMA crossover occurs, RSI is overbought (>70), and a double top pattern is detected. Timing: Ensure trades are executed only during the specified time window for better accuracy. Best Practices: Use this indicator alongside fundamental analysis or market sentiment. Test it thoroughly with historical data (backtesting) and in a demo account before live trading. Adjust parameters (e.g., EMA periods, RSI thresholds) based on your trading style.
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himanshuaggnihotry881の投稿
Equilibrium ZonesEquilibrium Zones This script identifies equilibrium zones within a specified range of bars, providing valuable insights into potential support and resistance levels. By analyzing the highest and lowest prices over a user-defined range, the script calculates the equilibrium price and additional levels around it to highlight demand, supply, and resistance/support zones. Features: Equilibrium Zone: Calculates the equilibrium price as the midpoint between the range's highest and lowest prices. Highlights key levels around the equilibrium, such as primary and secondary support/resistance levels. Visual Representation: Displays horizontal lines for each level with customizable colors and styles. Adds descriptive labels next to the lines for better clarity on the chart. User Inputs: Range Length: Specify the number of bars to analyze for calculating the range. Offset: Adjust the label placement for better visibility. Dynamic Updates: Automatically updates lines and labels to keep the chart clean and focused. How to Use: Add the script to your chart. Customize the Range Length and Offset inputs to fit your analysis style. Observe the equilibrium zones and use them to identify potential breakout, reversal, or consolidation areas.
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AbhayJagdaleの投稿