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Market Balance LevelMarket Balance Level (MBL) This indicator dynamically identifies price consolidation zones (market balance levels) and plots a horizontal line at the average midpoint of the range once a valid breakout occurs. It helps traders visualize key zones where the market was previously in equilibrium and is likely to retest before continuing its trend. How It Works: Detects consolidation ranges using consecutive candles within a tight high-low structure. When a breakout occurs (above or below the range), it plots a line at the average midpoint of the consolidation. Triangles are drawn on breakouts to visually confirm the breakout direction. Lines can be customized by color, width, and breakout direction (bullish, bearish, or both). Recommended Use: Wait for price to return to the Market Balance Level (MBL). These levels often act as strong support or resistance. Enter upon engulfment (candle closes strongly in the direction of the breakout), confirming continuation. Features: Adjustable consolidation sensitivity and line length. Option to show/hide bullish or bearish MBLs. Visual breakout markers (triangles) with alert support. Optional alert messages for breakout events. Use this tool to enhance your structure-based or SMC-style trading strategies.
Pine Script® indicator
by The_Forex_Steward
Turtle God IndicatorThe Turtle God indicator displays a turtle icon 🐢 on the most recent candle only, helping traders track current candle behavior at a glance. ✅ Green Turtle above the candle if it’s bullish (close > open) 🔻 Red Turtle below the candle if it’s bearish (close < open) 📌 Only the latest candle is marked — no historical clutter This tool is useful for: Live price action observation Real-time signal overlays Clean chart setups with dynamic candle feedback
Pine Script® indicator
by namtrhg
Enhanced MA Cloud Guru ProEnhanced MA Cloud Guru Pro — Indicator Description The Enhanced MA Cloud Guru Pro is a multi-layered trend and signal tool designed to visualize both short-term momentum and long-term trend context using six customizable moving averages. 🔹 Core Features: MA Clouds: Two distinct "clouds" are plotted: MA Cloud 1–3 (short-term trend) MA Cloud 4–6 (long-term trend) Clouds are color-coded: bullish, bearish, or neutral, based on moving average alignment. Contrarian Crossover Signals: Buy signal: when MA1 crosses above MA3, but long-term cloud (MA4–6) is bearish or neutral — suggesting a potential reversal or early trend shift. Sell signal: when MA1 crosses below MA3, while MA4–6 is bullish or neutral — indicating a possible breakdown or reversal. Cloud-to-Cloud Entry Signals: Bullish signal: when the short-term MA cloud enters upward into the long-term cloud from below. Bearish signal: when the short-term MA cloud enters downward into the long-term cloud from above. These mark potential trend transition zones or conflict between timeframes. Cooldown Logic: Adjustable cooldown bars prevent signal clustering and reduce noise. 🔹 Customization: All MAs are independently adjustable in length and type (SMA, EMA, WMA, HMA). Cloud transparency, colors, and signal timing can be tailored to user preference. 🧠 Use Case: This indicator is ideal for: Traders who want early trend reversal clues (contrarian logic) Visualizing interaction between short- and long-term structure Combining momentum shifts with long-term trend filters
Pine Script® indicator
by Es-Sniper
Volatility Quality [Alpha Extract]The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands. 🔶 CALCULATION The indicator processes volatility quality data through a series of analytical steps: Bar Range Calculation: Measures true range (TR) to capture price volatility. Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range. VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI). vqiRaw = ta.ema(weightedVol, vqiLen) Smoothing: Applies an additional EMA to smooth the VQI for clearer signals. Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows. Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds. vqiStdev = ta.stdev(vqiSmoothed, vqiLen) upperBand1 = vqiSmoothed + (vqiStdev * stdevMultiplier1) upperBand2 = vqiSmoothed + (vqiStdev * stdevMultiplier2) upperBand3 = vqiSmoothed + (vqiStdev * stdevMultiplier3) lowerBand1 = vqiSmoothed - (vqiStdev * stdevMultiplier1) lowerBand2 = vqiSmoothed - (vqiStdev * stdevMultiplier2) lowerBand3 = vqiSmoothed - (vqiStdev * stdevMultiplier3) Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode). Formula: Bar Range = True Range (TR) Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0) VQI Raw = EMA(Weighted Volatility, VQI Length) VQI Smoothed = EMA(VQI Raw, Smoothing Length) VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200 Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N) Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N) 🔶 DETAILS Visual Features: VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative). Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds. Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context. Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode). Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative). Interpretation: VQI ≥ 200 (Normalized): Overbought condition, strong sell signal. VQI 100–200: High volatility, potential selling opportunity. VQI 0–100: Neutral bullish momentum. VQI 0 to -100: Neutral bearish momentum. VQI -100 to -200: High volatility, strong bearish momentum. VQI ≤ -200 (Normalized): Oversold condition, strong buy signal. 🔶 EXAMPLES Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol. Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits. Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities. Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries. Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum. Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions. Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements. Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods. 🔶 SETTINGS Customization Options: VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50). Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50). Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0). Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50). Display Style: Switch between line or histogram plot for VQI. Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative). The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Pine Script® indicator
by AlphaExtract
1
Multifractal Forecast [ScorsoneEnterprises]Multifractal Forecast Indicator The Multifractal Forecast is an indicator designed to model and forecast asset price movements using a multifractal framework. It uses concepts from fractal geometry and stochastic processes, specifically the Multifractal Model of Asset Returns (MMAR) and fractional Brownian motion (fBm), to generate price forecasts based on historical price data. The indicator visualizes potential future price paths as colored lines, providing traders with a probabilistic view of price trends over a specified trading time scale. Below is a detailed breakdown of the indicator’s functionality, inputs, calculations, and visualization. Overview Purpose: The indicator forecasts future price movements by simulating multiple price paths based on a multifractal model, which accounts for the complex, non-linear behavior of financial markets. Key Concepts: Multifractal Model of Asset Returns (MMAR): Models price movements as a multifractal process, capturing varying degrees of volatility and self-similarity across different time scales. Fractional Brownian Motion (fBm): A generalization of Brownian motion that incorporates long-range dependence and self-similarity, controlled by the Hurst exponent. Binomial Cascade: Used to model trading time, introducing heterogeneity in time scales to reflect market activity bursts. Hurst Exponent: Measures the degree of long-term memory in the price series (persistence, randomness, or mean-reversion). Rescaled Range (R/S) Analysis: Estimates the Hurst exponent to quantify the fractal nature of the price series. Inputs The indicator allows users to customize its behavior through several input parameters, each influencing the multifractal model and forecast generation: Maximum Lag (max_lag): Type: Integer Default: 50 Minimum: 5 Purpose: Determines the maximum lag used in the rescaled range (R/S) analysis to calculate the Hurst exponent. A higher lag increases the sample size for Hurst estimation but may smooth out short-term dynamics. 2 to the n values in the Multifractal Model (n): Type: Integer Default: 4 Purpose: Defines the resolution of the multifractal model by setting the size of arrays used in calculations (N = 2^n). For example, n=4 results in N=16 data points. Larger n increases computational complexity and detail but may exceed Pine Script’s array size limits (capped at 100,000). Multiplier for Binomial Cascade (m): Type: Float Default: 0.8 Purpose: Controls the asymmetry in the binomial cascade, which models trading time. The multiplier m (and its complement 2.0 - m) determines how mass is distributed across time scales. Values closer to 1 create more balanced cascades, while values further from 1 introduce more variability. Length Scale for fBm (L): Type: Float Default: 100,000.0 Purpose: Scales the fractional Brownian motion output, affecting the amplitude of simulated price paths. Larger values increase the magnitude of forecasted price movements. Cumulative Sum (cum): Type: Integer (0 or 1) Default: 1 Purpose: Toggles whether the fBm output is cumulatively summed (1=On, 0=Off). When enabled, the fBm series is accumulated to simulate a price path with memory, resembling a random walk with long-range dependence. Trading Time Scale (T): Type: Integer Default: 5 Purpose: Defines the forecast horizon in bars (20 bars into the future). It also scales the binomial cascade’s output to align with the desired trading time frame. Number of Simulations (num_simulations): Type: Integer Default: 5 Minimum: 1 Purpose: Specifies how many forecast paths are simulated and plotted. More simulations provide a broader range of possible price outcomes but increase computational load. Core Calculations The indicator combines several mathematical and statistical techniques to generate price forecasts. Below is a step-by-step explanation of its calculations: Log Returns (lgr): The indicator calculates log returns as math.log(close / close ) when both the current and previous close prices are positive. This measures the relative price change in a logarithmic scale, which is standard for financial time series analysis to stabilize variance. Hurst Exponent Estimation (get_hurst_exponent): Purpose: Estimates the Hurst exponent (H) to quantify the degree of long-term memory in the price series. Method: Uses rescaled range (R/S) analysis: For each lag from 2 to max_lag, the function calc_rescaled_range computes the rescaled range: Calculate the mean of the log returns over the lag period. Compute the cumulative deviation from the mean. Find the range (max - min) of the cumulative deviation. Divide the range by the standard deviation of the log returns to get the rescaled range. The log of the rescaled range (log(R/S)) is regressed against the log of the lag (log(lag)) using the polyfit_slope function. The slope of this regression is the Hurst exponent (H). Interpretation: H = 0.5: Random walk (no memory, like standard Brownian motion). H > 0.5: Persistent behavior (trends tend to continue). H < 0.5: Mean-reverting behavior (price tends to revert to the mean). Fractional Brownian Motion (get_fbm): Purpose: Generates a fractional Brownian motion series to model price movements with long-range dependence. Inputs: n (array size 2^n), H (Hurst exponent), L (length scale), cum (cumulative sum toggle). Method: Computes covariance for fBm using the formula: 0.5 * (|i+1|^(2H) - 2 * |i|^(2H) + |i-1|^(2H)). Uses Hosking’s method (referenced from Columbia University’s implementation) to generate fBm: Initializes arrays for covariance (cov), intermediate calculations (phi, psi), and output. Iteratively computes the fBm series by incorporating a random term scaled by the variance (v) and covariance structure. Applies scaling based on L / N^H to adjust the amplitude. Optionally applies cumulative summation if cum = 1 to produce a path with memory. Output: An array of 2^n values representing the fBm series. Binomial Cascade (get_binomial_cascade): Purpose: Models trading time (theta) to account for non-uniform market activity (e.g., bursts of volatility). Inputs: n (array size 2^n), m (multiplier), T (trading time scale). Method: Initializes an array of size 2^n with values of 1.0. Iteratively applies a binomial cascade: For each block (from 0 to n-1), splits the array into segments. Randomly assigns a multiplier (m or 2.0 - m) to each segment, redistributing mass. Normalizes the array by dividing by its sum and scales by T. Checks for array size limits to prevent Pine Script errors. Output: An array (theta) representing the trading time, which warps the fBm to reflect market activity. Interpolation (interpolate_fbm): Purpose: Maps the fBm series to the trading time scale to produce a forecast. Method: Computes the cumulative sum of theta and normalizes it to . Interpolates the fBm series linearly based on the normalized trading time. Ensures the output aligns with the trading time scale (T). Output: An array of interpolated fBm values representing log returns over the forecast horizon. Price Path Generation: For each simulation (up to num_simulations): Generates an fBm series using get_fbm. Interpolates it with the trading time (theta) using interpolate_fbm. Converts log returns to price levels: Starts with the current close price. For each step i in the forecast horizon (T), computes the price as prev_price * exp(log_return). Output: An array of price levels for each simulation. Visualization: Trigger: Updates every T bars when the bar state is confirmed (barstate.isconfirmed). Process: Clears previous lines from line_array. For each simulation, plots a line from the current bar’s close price to the forecasted price at bar_index + T. Colors the line using a gradient (color.from_gradient) based on the final forecasted price relative to the minimum and maximum forecasted prices across all simulations (red for lower prices, teal for higher prices). Output: Multiple colored lines on the chart, each representing a possible price path over the next T bars. How It Works on the Chart Initialization: On each bar, the indicator calculates the Hurst exponent (H) using historical log returns and prepares the trading time (theta) using the binomial cascade. Forecast Generation: Every T bars, it generates num_simulations price paths: Each path starts at the current close price. Uses fBm to model log returns, warped by the trading time. Converts log returns to price levels. Plotting: Draws lines from the current bar to the forecasted price T bars ahead, with colors indicating relative price levels. Dynamic Updates: The forecast updates every T bars, replacing old lines with new ones based on the latest price data and calculations. Key Features Multifractal Modeling: Captures complex market dynamics by combining fBm (long-range dependence) with a binomial cascade (non-uniform time). Customizable Parameters: Allows users to adjust the forecast horizon, model resolution, scaling, and number of simulations. Probabilistic Forecast: Multiple simulations provide a range of possible price outcomes, helping traders assess uncertainty. Visual Clarity: Gradient-colored lines make it easy to distinguish bullish (teal) and bearish (red) forecasts. Potential Use Cases Trend Analysis: Identify potential price trends or reversals based on the direction and spread of forecast lines. Risk Assessment: Evaluate the range of possible price outcomes to gauge market uncertainty. Volatility Analysis: The Hurst exponent and binomial cascade provide insights into market persistence and volatility clustering. Limitations Computational Intensity: Large values of n or num_simulations may slow down execution or hit Pine Script’s array size limits. Randomness: The binomial cascade and fBm rely on random terms (math.random), which may lead to variability between runs. Assumptions: The model assumes log-normal price movements and fractal behavior, which may not always hold in extreme market conditions. Adjusting Inputs: Set max_lag based on the desired depth of historical analysis. Adjust n for model resolution (start with 4–6 to avoid performance issues). Tune m to control trading time variability (0.5–1.5 is typical). Set L to scale the forecast amplitude (experiment with values like 10,000–1,000,000). Choose T based on your trading horizon (20 for short-term, 50 for longer-term for example). Select num_simulations for the number of forecast paths (5–10 is reasonable for visualization). Interpret Output: Teal lines suggest bullish scenarios, red lines suggest bearish scenarios. A wide spread of lines indicates high uncertainty; convergence suggests a stronger trend. Monitor Updates: Forecasts update every T bars, so check the chart periodically for new projections. Chart Examples This is a daily AMEX:SPY chart with default settings. We see the simulations being done every T bars and they provide a range for us to analyze with a few simulations still in the range. On this intraday PEPPERSTONE:COCOA chart I modified the Length Scale for fBm, L, parameter to be 1000 from 100000. Adjusting the parameter as you switch between timeframes can give you more contextual simulations. On BITSTAMP:ETHUSD I modified the L to be 1000000 to have a more contextual set of simulations with crypto's volatile nature. With L at 100000 we see the range for NASDAQ:TLT is correctly simulated. The recent pop stays within the bounds of the highest simulation. Note this is a cherry picked example to show the power and potential of these simulations. Technical Notes Error Handling: The script includes checks for array size limits and division by zero (math.abs(denominator) > 1e-10, v := math.max(v, 1e-10)). External Reference: The fBm implementation is based on Hosking’s method (www.columbia.edu), ensuring a robust algorithm. Conclusion The Multifractal Forecast is a powerful tool for traders seeking to model complex market dynamics using a multifractal framework. By combining fBm, binomial cascades, and Hurst exponent analysis, it generates probabilistic price forecasts that account for long-range dependence and non-uniform market activity. Its customizable inputs and clear visualizations make it suitable for both technical analysis and strategy development, though users should be mindful of its computational demands and parameter sensitivity. For optimal use, experiment with input settings and validate forecasts against other technical indicators or market conditions.
Pine Script® indicator
by ScorsoneEnterprises
Eliora Phase 4.2.2 – Precision Bloom Mode | DAX 5minPhase shifts and market cohesion using math. Sure! Let’s break down the **simple trading bot concept** for **TradingView** step by step, focusing on the logic, purpose, and key elements of the strategy. This bot uses a **trend-following strategy** combined with **risk management** to automate trades based on moving averages and the RSI indicator. --- ### **Trading Bot Concept:** #### **Objective:** The primary objective of this bot is to **identify trends** and **execute buy and sell orders** based on those trends, while also ensuring **risk management** through stop-loss and take-profit levels. The bot uses two **core indicators**: * **Exponential Moving Averages (EMAs)**: To identify the trend direction. * **Relative Strength Index (RSI)**: To filter out overbought and oversold conditions, helping avoid entering trades during extreme market conditions. --- ### **Key Components:** #### 1. **Exponential Moving Averages (EMA)** * **50-period EMA** (Short-Term Trend): Tracks the price's movement in the recent past, offering more weight to recent prices. This helps the bot react quicker to short-term market shifts. * **200-period EMA** (Long-Term Trend): Represents the broader market trend, helping the bot assess the overall market direction. **Buy Signal**: * A buy signal is triggered when the **50-period EMA crosses above** the **200-period EMA** (a **bullish crossover**), suggesting that the market is entering an uptrend. **Sell Signal**: * A sell signal is triggered when the **50-period EMA crosses below** the **200-period EMA** (a **bearish crossover**), indicating that the market might be reversing into a downtrend. #### 2. **Relative Strength Index (RSI)** * **RSI** is a momentum oscillator that measures the speed and change of price movements, indicating whether an asset is overbought or oversold. * **Buy Condition**: The bot only takes buy trades if the **RSI is above 30**. This ensures that the market isn't in an **oversold** condition, which could indicate a potential reversal. * **Sell Condition**: The bot will only take sell actions if the **RSI is below 70**, avoiding trades during **overbought** conditions where prices might be excessively high. --- ### **How the Bot Works:** 1. **Buy Signal Conditions:** * The **50-period EMA** crosses **above** the **200-period EMA** (bullish crossover), indicating the potential start of an uptrend. * The **RSI is above 30**, ensuring that the market isn’t oversold and a reversal isn’t imminent. * If both of these conditions are true, the bot will **enter a long (buy) position**. 2. **Sell Signal Conditions:** * The **50-period EMA** crosses **below** the **200-period EMA** (bearish crossover), signaling that the market might be transitioning into a downtrend. * The **RSI is below 70**, meaning the market isn’t in an overbought state and the sell-off is not due to excessive bullish momentum. * If both of these conditions are met, the bot will **exit** any long position (i.e., sell). --- ### **Risk Management:** To protect against significant losses, the bot includes two essential features of **risk management**: 1. **Stop-Loss**: * The bot will automatically **exit the trade if the price moves against it by 2%** (or another user-defined percentage). This minimizes potential losses in case the market moves unfavorably after entry. 2. **Take-Profit**: * The bot will automatically **exit the trade once it reaches a profit of 5%** (or another user-defined percentage). This locks in profits if the market moves favorably. --- ### **Script Breakdown:** Here’s the **key flow** of the Pine Script: 1. **Define Parameters**: The script begins by defining input values for the **EMA periods** and **RSI length**. It also defines the **RSI overbought (70)** and **RSI oversold (30)** levels. 2. **Calculate the EMAs and RSI**: * The 50-period and 200-period **EMAs** are calculated using the `ta.ema()` function. * The **RSI** is calculated using `ta.rsi()`, and it helps determine if the asset is overbought or oversold. 3. **Trading Conditions**: * A buy signal is generated when the **short-term EMA crosses above** the **long-term EMA** and the RSI is **above 30**. * A sell signal is triggered when the **short-term EMA crosses below** the **long-term EMA** and the RSI is **below 70**. 4. **Strategy Execution**: * When the buy condition is met, the bot **enters a long position** using `strategy.entry()`. * When the sell condition is met, the bot **closes the position** using `strategy.close()`. 5. **Risk Management**: * The `strategy.exit()` function is used to set **stop-loss** and **take-profit** values. If the price moves **2% against** the trade, the bot will exit. If it moves **5% in favor**, it will lock in profits. --- ### **Visual Elements**: 1. **EMAs**: * The **50-period EMA** is plotted in **green**. * The **200-period EMA** is plotted in **red**. 2. **RSI**: * The **RSI line** is plotted in **blue** on a separate pane below the main chart. * Horizontal lines mark the **overbought** (70) and **oversold** (30) levels, helping visualize potential reversal zones. 3. **Buy and Sell Signals**: * When the bot triggers a buy, a **green arrow** appears on the chart. * When it triggers a sell, a **red arrow** appears on the chart. --- ### **How to Use the Bot on TradingView:** 1. **Go to TradingView** and open a chart of the asset you want to trade. 2. **Click on the "Pine Editor"** tab at the bottom. 3. **Paste the script** provided into the editor. 4. **Click "Add to Chart"** to see the strategy in action. 5. The bot will begin executing trades based on the logic described and display buy/sell signals directly on the chart. --- ### **Advantages of This Strategy**: * **Trend-Following**: This bot is based on the classic moving average crossover strategy, which is effective in trending markets. * **Simple and Clear**: The logic is easy to follow and understand, making it beginner-friendly. * **Built-in Risk Management**: The stop-loss and take-profit functionality ensures that the bot limits potential losses and locks in profits automatically. * **Customizable**: You can easily tweak the parameters (e.g., EMA periods, RSI levels, stop-loss, take-profit) to fit different timeframes or market conditions. --- ### **Limitations**: * **Sideways Markets**: The bot might struggle in flat or sideways markets because moving average crossovers can produce false signals. * **No Advanced Features**: It doesn’t incorporate more advanced strategies like **momentum indicators**, **news sentiment**, or **machine learning models** for decision-making. --- ### **In Conclusion:** This is a **basic but effective trend-following trading bot** that you can deploy on TradingView with minimal effort. It provides a great foundation for traders who want to automate a simple strategy with **risk management**, while offering plenty of room for customization and improvement. Let me know if you want to explore more complex features or strategies, or if you need help tweaking the bot for specific assets or markets!
Pine Script® strategy
by Ashleysantiago98
Math by Thomas - SMC OB + FVG📄 Description This script is designed for traders following the Smart Money Concepts (SMC) methodology. It automatically detects: ✅ Bullish and Bearish Order Blocks (OBs) based on structural breakouts, displacement, and volume conditions. ✅ Fair Value Gaps (FVGs) using a 3-candle price imbalance model. 🔄 Both OBs and FVGs clean up dynamically when invalidated by price action. Built with institutional logic, this tool helps identify areas of interest for potential reversals, liquidity grabs, or mitigation plays. ⚙️ How It Works 🔷 Order Blocks (OB) A Bullish OB is marked after a Break of Structure (BOS) to the upside. A Bearish OB is marked after BOS to the downside. Filters like displacement candle and volume spike can be toggled in settings. Boxes are drawn from the opposing candle in the move, and will disappear once broken or expired. 🟥 Fair Value Gaps (FVG) FVGs are detected when the middle candle leaves a price imbalance between the first and third candle. Zones are marked with transparent boxes. Labels (FVG) appear only once every 20 bars to reduce clutter. Gaps are removed only after a full candle closes through the zone (conservative logic). 🛠️ User Settings Choose volume multiplier and ATR period for OB displacement logic. Set box extension, label transparency, and cleanup behavior. Full control over colors and midline display. 📈 How to Use Apply the indicator to any chart (works best on indices, forex, crypto). Use OBs as points of interest for potential reaction zones or mitigation setups. Use FVGs to identify imbalances that may attract price. Watch for confluence between OBs and FVGs for high-probability entries. 📚 Best Practice Use on 15m–1h timeframe for clean structure. Align with higher TF bias for direction. Combine with liquidity sweeps, EQH/EQL, or breaker blocks for refinement.
Pine Script® indicator
by MathThomas
3
Smart Order Block IdentifierThis custom TradingView indicator identifies and highlights Smart Money Order Blocks (OBs) based on refined multi-candle price action logic. It detects bearish and bullish order blocks using a structured pattern involving five candles. For a bearish order block, the central (OB) candle must have a high that is greater than the highs of both the candle before and after it—signaling local strength. Additionally, the high of the candle two bars after (the “next-next” candle) must be lower than the OB candle’s low, indicating a potential shift in momentum and confirming bearish intent. Conversely, a bullish order block is identified when the OB candle has a low lower than the lows of both the previous and following candle. The candle two bars later must have a low higher than the OB candle’s high, showing price rejection and a likely reversal. The indicator marks these blocks visually with boxes on the chart and optionally filters out mitigated zones.
Pine Script® indicator
by confidentMoth0305
Smart OBsSmart Order Block Indicator with Mitigation Detection This indicator identifies bullish and bearish order blocks on the chart using a price action-based logic. For a bearish order block, it detects a candle whose high is higher than the highs of the candles immediately before and after it, followed by a candle after the next one whose high is below the low of the order block candle. Conversely, a bullish order block is identified where a candle’s low is lower than the lows of its neighboring candles and the subsequent candle after next has a low above the high of the order block candle. This method helps to spot potential areas where institutional buying or selling occurred. Once identified, the indicator plots rectangular zones on the chart highlighting these order blocks, allowing traders to visualize key supply and demand areas. The zones extend forward by a configurable number of bars to anticipate potential future price reactions. Additionally, the indicator checks if the order block zone has been “mitigated” or “consumed” by current price action, meaning price has retraced into or through the zone, potentially weakening its strength. Mitigated zones are not replotted, keeping the chart cleaner. This tool assists traders in spotting high-probability reversal or continuation zones, aiding in entry, stop-loss, and take-profit placement decisions by visually marking institutional order flow areas.
Pine Script® indicator
by confidentMoth0305
EMAs mit RSI & Candlestick-Signalen & großen KerzenkörpernMulti-Signal Indicator: EMAs, Candlestick Patterns & RSI Signals This versatile indicator combines three proven technical analysis tools in a single script: 🔹 1. Exponential Moving Averages (EMAs) Multiple EMAs are displayed on the chart, helping to quickly identify trends. You can customize the periods - ideal for short-term and long-term strategies. 🔹 2. candlestick pattern recognition The indicator automatically recognizes common bullish and bearish candlestick formations such as: Hammer / Hanging Man Engulfing Pattern Doji / Spinning Top As soon as a pattern is recognized, a visual marker appears on the chart. 🔹 3. RSI-based signals The Relative Strength Index (RSI) is analyzed to identify overbought and oversold conditions. Additional visual cues help to identify potential reversal points. ✅ Advantages: All-in-one indicator - no overload from multiple scripts Visual clarity through clear markings and coloring Fully customizable in the settings menu ⚙️ Application: Suitable for traders who want to trade technical patterns, follow trends or react to RSI reversal points. Note: This indicator is for educational purposes only and is not a substitute for sound trading strategy or financial advice.
Pine Script® indicator
by Carlos735
Head-Flag basicAttention: I've been waiting... seconds, minutes, even hours... But the real one isn't there. They're ghosts, illusions. Yet, look... the eyes of humanity are fixed on that. Detailed Description: How to Use the "Head-Flag Basic" Indicator This indicator is designed to automatically detect classic chart patterns widely used in technical analysis. These patterns help identify possible trend reversals or continuations. The script works on any timeframe and with any asset, as long as data is available. Patterns Detected by the Indicator Head and Shoulders A red cross appears above the bar. Indicates a potential reversal from an uptrend to a downtrend. The pattern forms when there’s a higher peak (the head) between two lower peaks (the shoulders), and the current low is below the middle low. Inverted Head and Shoulders A green diamond appears below the bar. Indicates a potential reversal from a downtrend to an uptrend. The opposite of the previous pattern: there’s a lower trough (the head) between two higher troughs (the shoulders), and the current high exceeds the head’s high. Bull Flag A blue flag appears below the bar. Suggests a potential continuation of an upward trend. The price forms higher highs and lows, and closes above a recent resistance. Bear Flag A yellow flag appears above the bar. Suggests a potential continuation of a downward trend. The price forms lower highs and lows, and closes below a recent support. Ascending Triangle A purple triangle appears above the bar. Signals a consolidation pattern with a potential breakout to the upside. Highs are flat (horizontal resistance), while lows are rising. Descending Triangle An orange triangle appears below the bar. Signals a consolidation pattern with a potential breakout to the downside. Lows are flat (horizontal support), while highs are falling. How to Use the Indicator on the Chart Copy the Pine Script code and paste it into the TradingView Pine Editor. Click “Add to Chart.” The indicator will automatically display graphic symbols above or below bars when patterns are detected. Use the signals as alerts. Always confirm with other tools (such as volume, moving averages, RSI, or support/resistance zones). Never trade solely based on the indicator. It should serve as a visual clue — not a confirmation by itself. Final Notes This is a simple, visual, and straightforward indicator. It helps you notice patterns that may go unnoticed in the market’s flow. However, no tool should be used in isolation. Use it wisely, validate it with broader context, and always follow your risk management plan.
Pine Script® indicator
by Canhoto-Medium