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ForexMasterStochastic//@version=5 indicator(title="ForexMasterStochastic", shorttitle="Stoch", format=format.price, precision=2, timeframe="", timeframe_gaps=true) periodK = input.int(14, title="%K Length", minval=1) smoothK = input.int(3, title="%K Smoothing", minval=1) periodD = input.int(3, title="%D Smoothing", minval=1) k = ta.sma(ta.stoch(close, high, low, periodK), smoothK) d = ta.sma(k, periodD) plot(k, title="%K", color=#2962FF) plot(d, title="%D", color=#FF6D00) h0 = hline(80, "Upper Band", color=#787B86) hline(50, "Middle Band", color=color.new(#787B86, 50)) h1 = hline(20, "Lower Band", color=#787B86) fill(h0, h1, color=color.rgb(33, 150, 243, 90), title="Background")
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RAJESHGURAV87 tarafından
Combined Stochastic, ADX & BreakoutTrading View Indicator Explanation Entry Signal Logic This indicator identifies two specific buying opportunities during an uptrend following a correction: Entry Signal #1 - Post-Correction Breakout Wait for price to establish an uptrend above EMA9 Look for at least one lower high (correction) Entry trigger: Breakout above the previous candle's high Stop loss: Place below the most recent swing low Entry Signal #2 - Strong Trend Correction Requires a blue triangle marker above the candle (on closing basis) Must occur during a strong uptrend (confirmed by high ADX reading) Requires a deep technical correction (measured by Stochastic) Entry conditions: Price must be above EMA9 Current candle must break above previous candle's high Stop loss: Place below the most recent swing low Notes Sell signals have been removed to reduce chart clutter Recommended exit strategy: Sell at new swing highs The second signal specifically filters for stronger trend conditions Technical Indicators Used EMA9: Trend direction filter Stochastic: Measures depth of correction ADX: Confirms strength of uptrend Price action: Candle high/low relationships This is designed to catch continuation moves in established uptrends after healthy corrections, emphasizing high-probability entries with clearly defined stop levels.
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DaxiDriver tarafından
1
200-SMA, 20-EMA & VWAPThis custom TradingView indicator combines three powerful tools to help traders identify trends and key price levels: ✅ 200-SMA (Simple Moving Average) – A long-term trend indicator used to gauge overall market direction. ✅ 20-EMA (Exponential Moving Average) – A short-term moving average that reacts faster to price changes, helping with entry and exit points. ✅ VWAP (Volume Weighted Average Price) – A key institutional trading level that represents the average price weighted by volume, often used for determining fair value. 🔹 Features: • Toggle on/off for each indicator • Customizable colors • Clean and minimalistic display Ideal for day traders, swing traders, and investors looking to refine their market analysis.
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laravandres tarafından
Scalping Strategy//@version=5 strategy("Scalping Strategy", overlay=true) // Indicators ma50 = ta.sma(close, 50) ema20 = ta.ema(close, 20) ema200 = ta.ema(close, 200) rsi = ta.rsi(close, 14) osc = ta.stoch(close, high, low, 14) vol = volume // Trend Confirmation bullishTrend = ema20 > ema200 and close > ma50 bearishTrend = ema20 < ema200 and close < ma50 // RSI Divergence Detection rsiOverbought = rsi > 70 rsiOversold = rsi < 30 // Oscillator Confirmation oscBull = osc < 20 oscBear = osc > 80 // Volume Confirmation highVolume = vol > ta.sma(vol, 20) // Entry Conditions buySignal = bullishTrend and rsiOversold and oscBull and highVolume sellSignal = bearishTrend and rsiOverbought and oscBear and highVolume // Execute Trades if buySignal strategy.entry("Buy", strategy.long) if sellSignal strategy.entry("Sell", strategy.short) // Plot indicators plot(ma50, color=color.blue, title="MA 50") plot(ema20, color=color.green, title="EMA 20") plot(ema200, color=color.red, title="EMA 200")
Pine Script™ stratejisi
azmatwaqas093 tarafından
Turtle Trading Mejorado para BTC 1Hturtle trading adapated to 1h Canales Donchian: Entrada: Periodo de 20 para detectar rupturas (largas y cortas). Salida: Periodo de 10 para cerrar posiciones. ATR (Average True Range): Periodo de 14 para medir volatilidad y calcular el tamaño de las posiciones. Gestión de Riesgo: Riesgo por operación: 2% del capital. Máximo de 4 unidades por posición. Condiciones de Entrada: Larga: Precio alto supera el máximo de 20 periodos. Corta: Precio bajo cae por debajo del mínimo de 20 periodos. Condiciones de Salida: Larga: Precio bajo cae por debajo del mínimo de 10 periodos. Corta: Precio alto supera el máximo de 10 periodos. Añadir Unidades: Se añaden unidades si el precio se mueve 0.5 ATR a favor, hasta 4 unidades. Stop Loss: Dinámico, basado en 2 ATR desde el precio de entrada.
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Maverick_aguiar tarafından
Triple Moving Average with LabelsThis indicator "Triple Moving Average with Labels", overlays the 50, 100, and 200 period Simple Moving Averages (SMAs) on the chart and provides customizable floating labels for each line. By default, the labels display "50 MA", "100 MA", and "200 MA", but users can modify or remove the text entirely through the indicator settings. The moving average periods (50, 100, or 200) are also adjustable. The labels are positioned slightly above and to the right of their respective lines for clear visibility.
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Trading_Consults tarafından
Custom MA Indicator// @version=6 indicator("Custom MA Indicator", overlay=true) // Define the moving average periods ma_red_period = 50 ma_orange_period = 100 ma_green_period = 200 // Calculate the moving averages ma_red = ta.sma(close, ma_red_period) ma_orange = ta.sma(close, ma_orange_period) ma_green = ta.sma(close, ma_green_period) // Plot the moving averages with specified colors plot(ma_red, color=color.red, title="Red MA") plot(ma_orange, color=color.orange, title="Orange MA") plot(ma_green, color=color.green, title="Green MA")
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byswav tarafından
Acceleration Bands HTF This version gives you the ability to see the indicator from the HIGHER timeframes when you are on the timeframes. Please note that this is not the original formula, but a factored one that I found effective for identifying market trends. Thanks to @capissimo who provided the base open-code. Acceleration Bands are designed to capture potential price breakouts or reversals in an asset. They are calculated based on a stock's price movements over a specified period, typically using the high, low, and closing prices. The idea is to identify moments when the price is accelerating (hence the name) beyond its normal range, which might indicate the beginning of a new trend. Calculation Acceleration Bands consist of three lines: Upper Band (AB Upper): This is calculated by adding a certain percentage of the simple moving average (SMA) to the highest high over a given period. Middle Band: This is typically the SMA of the stock's price. Lower Band (AB Lower): This is calculated by subtracting the same percentage of the SMA from the lowest low over a given period. Mathematically : AB Upper = SMA + (Highest High * Percentage) AB Lower = SMA - (Lowest Low * Percentage) OR Upper Band = SMA x (1 + (High - Low) / SMA) Lower Band = SMA x (1 - (High - Low) / SMA) Interpretation The bands are used to identify periods when the price of a security is accelerating or decelerating: Breakout Above Upper Band: This is usually considered a bullish signal, suggesting that the price is accelerating upwards and a new uptrend may be starting. Breakdown Below Lower Band: This is usually considered a bearish signal, suggesting that the price is accelerating downwards and a new downtrend may be starting. Reversal Between Bands: When the price re-enters the region between the bands after breaking out, it can be seen as a potential reversal signal. Trading Strategy Entry Signals: Buy when the price breaks above the upper band. Sell or short when the price breaks below the lower band. Exit Signals: Close a long position when the price falls back into the area between the bands. Close a short position when the price rises back into the area between the bands. Advantages Helps capture early trends. Can be used across various time frames and assets. Provides clear entry and exit signals.
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ZoharCho tarafından
1
Machine Learning: Lorentzian Classification/ ==================== // ==== Background ==== // ==================== // When using Machine Learning algorithms like K-Nearest Neighbors, choosing an // appropriate distance metric is essential. Euclidean Distance is often used as // the default distance metric, but it may not always be the best choice. This is // because market data is often significantly impacted by proximity to significant // world events such as FOMC Meetings and Black Swan events. These major economic // events can contribute to a warping effect analogous a massive object's // gravitational warping of Space-Time. In financial markets, this warping effect // operates on a continuum, which can analogously be referred to as "Price-Time". // To help to better account for this warping effect, Lorentzian Distance can be // used as an alternative distance metric to Euclidean Distance. The geometry of // Lorentzian Space can be difficult to visualize at first, and one of the best // ways to intuitively understand it is through an example involving 2 feature // dimensions (z=2). For purposes of this example, let's assume these two features // are Relative Strength Index (RSI) and the Average Directional Index (ADX). In // reality, the optimal number of features is in the range of 3-8, but for the sake // of simplicity, we will use only 2 features in this example. // Fundamental Assumptions: // (1) We can calculate RSI and ADX for a given chart. // (2) For simplicity, values for RSI and ADX are assumed to adhere to a Gaussian // distribution in the range of 0 to 100. // (3) The most recent RSI and ADX value can be considered the origin of a coordinate // system with ADX on the x-axis and RSI on the y-axis. // Distances in Euclidean Space: // Measuring the Euclidean Distances of historical values with the most recent point // at the origin will yield a distribution that resembles Figure 1 (below). // // | // | // | // ...:::.... // .:.:::••••••:::•::.. // .:•:.:•••::::••::••....::. // ....:••••:••••••••::••:...:•. // ...:.::::::•••:::•••:•••::.:•.. // ::•:.:•:•••••••:.:•::::::...:.. // |--------.:•••..•••••••:••:...:::•:•:..:..---------- // 0 :•:....:•••••::.:::•••::••:..... // ::....:.:••••••••:•••::••::..:. // .:...:••:::••••••••::•••....: // ::....:.....:•::•••:::::.. // ..:..::••..::::..:•:.. // .::..:::.....: // | // | // | // | // _|_ 0 // // Figure 1: Neighborhood in Euclidean Space // Distances in The Space: // However, the same set of historical values measured using The Distance will // yield a different distribution that resembles Figure 2 (below). // // // ::.. | ..::: // ..... | ...... // .••••::. | :••••••. // .:•••••:. | :::••••••. // .•••••:... | .::.••••••. // .::•••••::.. | :..••••••.. // .:•••••••::.........::••••••:.. // ..::::••••.•••••••.•••••••:. // ...:•••••••.•••••••••::. // .:..••.••••••.••••.. // |---------------.:•••••••••••••••••.--------------- // 0 .:•:•••.••••••.•••••••. // .••••••••••••••••••••••••:. // .:••••••••••::..::.::••••••••:. // .::••••••::. | .::•••:::. // .:••••••.. | :••••••••. // .:••••:... | ..•••••••:. // ..:••::.. | :.•••••••. // .:•.... | ...::.:••. // ...:.. | :...:••. // :::. | ..:: // _|_ 0 // // Figure 2: Neighborhood in the Space // Observations: // (1) In the Space, the shortest distance between two points is not // necessarily a straight line, but rather, a geodesic curve. // (2) The warping effect of Lorentzian distance reduces the overall influence // of outliers and noise. // (3) The Distance becomes increasingly different from Euclidean Distance // as the number of nearest neighbors used for comparison increases.
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LudvigTheriault tarafından
Opening Range BoxIndicator Name: Opening Range Box with Extensions Author: YanivBull Description: The Opening Range Box with Extensions is a powerful tool designed to visualize the trading range established during the first 30 minutes of a market session, a critical period for setting the day's trend. This indicator plots a box representing the high and low prices formed within this opening range, with dashed extension lines projecting these levels forward throughout the session. Its primary purpose is to identify the boundaries of the initial trend at the start of trading. When these boundaries are breached, it serves as a trigger for potential trading opportunities: a breakout above the box high signals a possible long entry, while a breakdown below the box low indicates a potential short entry. The indicator also includes historical boxes for up to 5 previous days (configurable), allowing traders to analyze past opening ranges and their extensions for context and pattern recognition. Key Features: Customizable session start time (hour and minute) to adapt to various markets (e.g., NYSE, DAX, etc.). Displays the current session's opening range box in blue and historical boxes in gray. Plots dashed extension lines from the high and low of each box, limited to 500 bars or the end of the trading day. Adjustable number of historical days (1-20, default 5). Usage: Set the Session Start Hour and Session Start Minute according to your market's opening time (relative to your chart's timezone, e.g., UTC+2). Watch for price action around the box boundaries—breakouts above the high or below the low can be used as signals for initiating long or short trades, respectively. Combine with other technical analysis tools for confirmation. This indicator is ideal for day traders looking to capitalize on early session momentum and breakout strategies.
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YanivBull tarafından