Mad Trading Scientist - Guppy MMA with Bollinger Bands📘 Indicator Name:
Guppy MMA with Bollinger Bands
🔍 What This Indicator Does:
This TradingView indicator combines Guppy Multiple Moving Averages (GMMA) with Bollinger Bands to help you identify trend direction and volatility zones, ideal for spotting pullback entries within trending markets.
🔵 1. Guppy Multiple Moving Averages (GMMA):
✅ Short-Term EMAs (Blue) — represent trader sentiment:
EMA 3, 5, 8, 10, 12, 15
✅ Long-Term EMAs (Red) — represent investor sentiment:
EMA 30, 35, 40, 45, 50, 60
Usage:
When blue (short) EMAs are above red (long) EMAs and spreading → Strong uptrend
When blue EMAs cross below red EMAs → Potential downtrend
⚫ 2. Bollinger Bands (Volatility Envelopes):
Length: 300 (captures the longer-term price range)
Basis: 300-period SMA
Upper & Lower Bands:
±1 Standard Deviation (light gray zone)
±2 Standard Deviations (dark gray zone)
Fill Zones:
Highlights standard deviation ranges
Emphasizes extreme vs. normal price moves
Usage:
Price touching ±2 SD bands signals potential exhaustion
Price reverting to the mean suggests pullback or re-entry opportunity
💡 Important Note: Use With Momentum Filter
✅ For superior accuracy, this indicator should be combined with your invite-only momentum filter on TradingView.
This filter helps confirm whether the trend has underlying strength or is losing momentum, increasing the probability of successful entries and exits.
🕒 Recommended Timeframe:
📆 1-Hour Chart (60m)
This setup is optimized for short- to medium-term swing trading, where Guppy structures and Bollinger reversion work best.
🔧 Practical Strategy Example:
Long Trade Setup:
Short EMAs are above long EMAs (strong uptrend)
Price pulls back to the lower 1 or 2 SD band
Momentum filter confirms bullish strength
Short Trade Setup:
Short EMAs are below long EMAs (strong downtrend)
Price rises to the upper 1 or 2 SD band
Momentum filter confirms bearish strength
Cari dalam skrip untuk "信达股份40周年"
5:30 AM IST Close + Offset Lines + TablesDescription:
This script captures the 5:30 AM IST close price and plots it on the chart along with dynamic offset levels above and below (±5, ±20, ±40, ±60, ±80 points). It also displays these levels in neatly organized tables at the top-right and bottom-right corners for quick reference.
🔹 Timezone: Asia/Kolkata (IST)
🔹 Useful for: Intraday traders who reference early morning levels
🔹 Visual aids:
Orange line for 5:30 AM close
Green lines for points above
Red lines for points below
Tables summarizing all levels
This tool helps identify key early-morning reference zones that can act as support/resistance or breakout targets.
Dual Stochastic Enhanced (with Presets giua64)Script Title: Dual Stochastic Enhanced (with Presets giua64)
Overview:
This indicator enhances the traditional Dual Stochastic strategy, aiming to provide more filtered and potentially reliable trading signals. By integrating dynamic overbought/oversold levels via Bollinger Bands on the slow stochastic, a trend filter based on a moving average, momentum confirmation via RSI, and user-friendly selectable presets, "Dual Stochastic Enhanced" seeks to offer a more robust approach to identifying potential entry points.
Key Features:
Dual Stochastics: Utilizes a slow stochastic (configurable, e.g., 14 periods) as a context filter and a fast stochastic (configurable, e.g., 5 periods) as a signal trigger.
Bollinger Bands on Slow Stochastic: Instead of fixed overbought/oversold levels (80/20), Bollinger Bands are applied to the %K line of the slow stochastic. This creates dynamic zones that adapt to the stochastic's own volatility.
Trend Filter: A moving average (configurable type and length, e.g., EMA 100 as seen in the example chart for general context) on the price helps filter signals, allowing only trades aligned with the prevailing trend.
RSI Confirmation: An RSI oscillator (configurable length, e.g., 14 periods) is used to confirm momentum. Signals require the RSI to cross certain thresholds to validate the strength of the move.
User Presets: Includes presets for "Scalping," "Intraday," and "Swing trading," which quickly set all key parameters to suit different styles and timeframes. A "Custom" option is also available for full manual configuration.
Clear Visual Signals: Long (green) and Short (red) arrows appear on the chart when all entry conditions are met.
Active Zone Highlighting: The background of the indicator panel changes color (green or red) when "active zone" conditions (a combination of stochastics, trend, and RSI) are favorable.
Information Panel: A table in the top-right corner of the indicator panel displays the current status of the selected preset, trend filter, RSI value, and stochastic levels.
Signal Logic:
A LONG signal is generated when:
The fast stochastic %K crosses above its %D line.
The slow stochastic %K line is below its lower Bollinger Band (dynamic oversold condition).
The fast stochastic %K line is also in a low area (e.g., <25) to confirm the trigger is not premature.
The closing price is above the trend moving average (uptrend).
The RSI is above its long confirmation level (e.g., >40), indicating sufficient bullish momentum.
A SHORT signal is generated when:
The fast stochastic %K crosses below its %D line.
The slow stochastic %K line is above its upper Bollinger Band (dynamic overbought condition).
The fast stochastic %K line is also in a high area (e.g., >75).
The closing price is below the trend moving average (downtrend).
The RSI is below its short confirmation level (e.g., <60), indicating sufficient bearish momentum.
How to Use:
Select a Preset suitable for your trading style and the timeframe you are analyzing (e.g., Scalping for M1-M15, Intraday for M5-H1, Swing for H4-D1).
Alternatively, choose "Custom" and manually adjust all parameters (stochastic lengths, smoothing, Bollinger Bands, Moving Average, RSI, confirmation thresholds).
Observe the Information Panel for a quick understanding of the current conditions.
Evaluate the arrow signals, always considering the broader market context, price action, and any other confluences (supports/resistances, chart patterns).
The background highlighting can help quickly identify periods where conditions are aligned for potential trades.
Disclaimer:
This script is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Always thoroughly test any strategy or indicator on historical data and on a demo account before risking real capital. The author assumes no responsibility for any losses incurred from the use of this script.
Author: giua64
Adaptive Multi-TF Indicator Table with Presets giua64📌 Script Name:
Adaptive Multi-Timeframe Indicator Table with Presets — giua64
📄 Description:
This script displays an adaptive multi-timeframe dashboard that summarizes the signals of three key technical indicators:
Moving Averages (MAs), Relative Strength Index (RSI), and MACD.
It provides a fast and visually intuitive overview of market conditions across five timeframes (5m, 15m, 30m, 1h, 4h), helping traders quickly identify potential directional biases (e.g., bullish, bearish, or neutral) based on either predefined presets or fully manual settings.
🧰 Preset Configurations:
You can choose between four trading styles, each with optimized indicator parameters:
Scalping
• MAs: 5 / 10 (Fast), 20 / 50 (Slow)
• RSI: 7 periods | Overbought: 70 | Oversold: 30
• MACD: 5 / 13 | Signal: 3
Intraday
• MAs: 9 / 21 (Fast), 50 / 100 (Slow)
• RSI: 14 periods | Overbought: 60 | Oversold: 40
• MACD: 12 / 26 | Signal: 9
Swing
• MAs: 10 / 20 (Fast), 50 / 200 (Slow)
• RSI: 14 periods | Overbought: 65 | Oversold: 35
• MACD: 12 / 26 | Signal: 9
Manual
• Full custom control over all indicator settings.
🛠️ All settings can be customized manually from the options panel, including the exact MA periods, RSI thresholds, and MACD structure.
🧠 How It Works:
For each timeframe, the script evaluates:
MA crossover status (two levels):
The first symbol refers to the crossover of the fast MAs
The second symbol refers to the crossover of the slow MAs
🟢 = Bullish crossover
🔴 = Bearish crossover
➖ = Flat or no clear signal
RSI Direction:
↑ = RSI above upper threshold (potential overbought)
↓ = RSI below lower threshold (potential oversold)
→ = RSI in neutral range
MACD Line vs Signal Line:
↑ = MACD line is above signal line (bullish)
↓ = MACD line is below signal line (bearish)
→ = Flat or neutral signal
Each signal is assigned a numerical score. These are aggregated per timeframe to compute a combined score that reflects the directional bias for that specific time window.
🧠 Adaptive Logic by Asset:
This script is designed to be universally compatible across all asset types — including forex, crypto, stocks, indices, and commodities.
Thanks to its multi-timeframe nature and flexible indicator presets, the script automatically adjusts its behavior based on the asset selected, ensuring relevant analysis without requiring manual recalibration.
🧾 Summary Table Output:
At the bottom of the dashboard, a combined sentiment is displayed for:
3TF → 5m, 15m, 30m
4TF → Adds 1h
5TF → Adds 4h
Each row shows:
Signal → LONG / SHORT / NEUTRAL
Confidence (%) → Based on score aggregation and signal consistency
📌 Customization Options:
Table Position: Left, Right, or Center
Text Size: Small, Normal, or Large
Full Manual Configuration: All MA, RSI, and MACD parameters can be adjusted as needed
⚠️ Disclaimer:
This script is for educational and analytical purposes only.
It does not constitute financial advice or guarantee any trading results.
Always do your own research and apply responsible risk management.
MARibbonMARibbon インジケーターについて
この「MARibbon」は、3本の移動平均線（MA1、MA2、MA3）を描画し、特にMA2とMA3の関係性に注目して、背景色でトレンドの強弱や転換のサインを視覚的に分かりやすく表示するインジケーターです。
主な特徴
3種類の移動平均線を表示可能
MA1（白色、期間40、太さ2）
MA2（水色、期間200、太さ4）
MA3（ピンク色、期間800、太さ4）
各MAの期間・種類（SMA、EMA、WMA、RMA）・タイムフレームは自由に設定可能。
MA2とMA3の関係性に応じて、チャート背景に色付きのリボン（帯）を表示。
背景リボンの意味
MA2 > MA3（ゴールデンクロス状況）
→ 背景を薄い緑色にして、上昇トレンドの可能性を示唆。
MA3 > MA2（デッドクロス状況）
→ 背景を薄い赤色にして、下降トレンドの可能性を示唆。
それ以外（等しい場合など）は背景色なし（透明）で表示。
入力可能な設定
各移動平均線の期間
各移動平均線の種類（SMA、EMA、WMA、RMA）
各移動平均線のタイムフレーム（デフォルトはチャートと同じ）
使い方
任意の銘柄・時間足のチャートにインジケーターを適用。
必要に応じて、3本の移動平均の期間・種類・時間足を調整。
MA2とMA3の位置関係によって、チャート背景の色が変わり、トレンドの強弱を直感的に把握可能。
MARibbon is a custom indicator that plots three moving averages (MA1, MA2, MA3) and visually fills the space between MA2 and MA3 with color bands to indicate trend strength and direction.
Each MA supports custom type (SMA / EMA / WMA / RMA), length, and timeframe.
A green band appears when MA2 is above MA3.
A red band appears when MA3 is above MA2.
This clean and minimal design helps traders easily visualize overlapping trends and potential crossovers.
💡 Use Cases:
Visually confirm confluence of long- and short-term trends
Identify ribbon-like zones of trend strength
Support for MA cross strategy analysis
Stoch Quad Oscillator📘 Stoch Quad Oscillator – User Guide
✅ Purpose
The Stoch Quad Oscillator is a multi-timeframe stochastic oscillator tool that helps traders detect oversold and overbought conditions, momentum shifts, and quad rotation signals using four distinct stochastic configurations. It includes visual cues, customizable parameters, and background highlights to improve decision-making during trend reversals or momentum surges.
🛠️ Inputs & Parameters
⏱ Timeframe
Timeframe for Stochastic Calculation: Defines which chart timeframe to use for stochastic calculations (default is "1" minute). This enables multi-timeframe analysis while on a lower timeframe chart.
📈 Stochastic Parameters
Four different stochastic configurations are used:
Label %K Length %D Smoothing Notes
K9 D3 9 3 Fastest, short-term view
K14 D3 14 3 Moderately short-term
K40 D4 40 4 Medium-term trend view
K60 D10 60 10 Long-term strength
Smoothing Type: Choose between SMA or EMA to control how smoothed the %D line is.
🎯 Levels
Overbought Level: Default 80
Oversold Level: Default 20
These are used to indicate overextended price conditions on any of the stochastic plots.
🔄 Quad Rotation Detection Settings
When enabled, the script detects synchronized oversold/overbought conditions with strong momentum using all 4 stochastic readings.
Enable Quad Rotation: Toggles detection on or off
Slope Calculation Bars: Number of bars used to calculate slope of %D lines
Slope Threshold: Minimum slope strength for signal (higher = stronger confirmation)
Oversold Quad Level: Total of all four stochastic values that define a quad oversold zone
Overbought Quad Level: Total of all four stochastic values that define a quad overbought zone
Oversold Quad Highlight Color: Background color when oversold quad is triggered
Overbought Quad Highlight Color: Background color when overbought quad is triggered
Slope Averaging Method: Either Simple Average or Weighted Average (puts more weight on higher timeframes)
Max Signal Bar Window: Defines how recent the signal must be to be considered valid
📊 Plots & Visual Elements
📉 Stochastic %D Lines
Each stochastic is plotted separately:
K9 D3 – Red
K14 D3 – Orange
K40 D4 – Fuchsia
K60 D10 – Silver
These help visualize short to long-term momentum simultaneously.
📏 Horizontal Reference Lines
Overbought Line (80) – Red
Oversold Line (20) – Green
These help you identify threshold breaches visually.
🌈 Background Highlighting
The indicator provides background highlights to mark potential signal zones:
✅ All Oversold or Overbought Conditions
When all four stochastics are either above overbought or below oversold:
Bright Red if all are overbought
Bright Green if all are oversold
🚨 Quad Rotation Signal Zones (if enabled)
Triggered when:
The combined sum of all four stochastic levels is extremely low/high (below/above oversoldQuadLevel or overboughtQuadLevel)
The average slope of the 4 %D lines is sharply positive (> slopeThreshold)
Highlights:
Custom Red Tint = Strong overbought quad signal
Custom Green Tint = Strong oversold quad signal
These zones can indicate momentum shifts or reversal potential when used with price action or other tools.
⚠️ Limitations & Considerations
This indicator does not provide trade signals. It visualizes conditions and potential setups.
It is best used in confluence with price action, support/resistance levels, and other indicators.
False positives may occur in ranging markets. Reduce reliance on slope thresholds during low volatility.
Quad signals rely on slope strength, which may lag slightly behind sudden reversals.
🧠 Tips for Use
Combine with volume, MACD, or PSAR to confirm direction before entry.
Watch for divergences between price and any of the stochastics.
Use on higher timeframes (e.g., 5m–30m) to filter for swing trading setups; use shorter TFs (1m–5m) for scalping signals.
Adjust oversoldQuadLevel and overboughtQuadLevel based on market conditions (e.g., in trending vs ranging markets).
Gamma Blast Detector (Nifty)The Gamma Blast Detector (Nifty) is a custom TradingView indicator designed to help intraday traders identify sudden and explosive price movements—commonly referred to as "gamma blasts"—in the Nifty index during the final minutes of the trading session, particularly on expiry days. These movements are typically caused by rapid delta changes in ATM options, resulting in aggressive short-covering or option unwinding.
This indicator specifically monitors price action between 3:10 PM and 3:20 PM IST, which translates to 09:40 AM to 09:50 AM UTC on TradingView. It is optimized for use on 5-minute charts of the Nifty spot or futures index, where gamma-driven volatility is most likely to occur during this time window.
The core logic behind the indicator involves identifying unusually large candles within this time frame. It compares the size of the current candle to the average size of the previous five candles. If the current candle is at least twice as large and shows clear direction (bullish or bearish), the script flags it as a potential gamma blast. A bullish candle suggests a Call Option (CE) is likely to blast upward, while a bearish candle points to a Put Option (PE) gaining sharply.
When such a condition is detected, the indicator visually marks the candle on the chart: a "CE 🚀" label is shown below the candle for a bullish move, and a "PE 🔻" label appears above for a bearish move. It also includes alert conditions, allowing users to set real-time alerts for potential blasts and act quickly.
This tool is especially useful for expiry day scalpers, option traders, and anyone looking to ride momentum generated by gamma effects in the final minutes of the market. It provides a visual and alert-based edge to anticipate short-term, high-impact moves often missed in normal technical analysis.
Goldman Sachs Risk Appetite ProxyRisk appetite indicators serve as barometers of market psychology, measuring investors' collective willingness to engage in risk-taking behavior. According to Mosley & Singer (2008), "cross-asset risk sentiment indicators provide valuable leading signals for market direction by capturing the underlying psychological state of market participants before it fully manifests in price action."
The GSRAI methodology aligns with modern portfolio theory, which emphasizes the importance of cross-asset correlations during different market regimes. As noted by Ang & Bekaert (2002), "asset correlations tend to increase during market stress, exhibiting asymmetric patterns that can be captured through multi-asset sentiment indicators."
Implementation Methodology
Component Selection
Our implementation follows the core framework outlined by Goldman Sachs research, focusing on four key components:
Credit Spreads (High Yield Credit Spread)
As noted by Duca et al. (2016), "credit spreads provide a market-based assessment of default risk and function as an effective barometer of economic uncertainty." Higher spreads generally indicate deteriorating risk appetite.
Volatility Measures (VIX)
Baker & Wurgler (2006) established that "implied volatility serves as a direct measure of market fear and uncertainty." The VIX, often called the "fear gauge," maintains an inverse relationship with risk appetite.
Equity/Bond Performance Ratio (SPY/IEF)
According to Connolly et al. (2005), "the relative performance of stocks versus bonds offers significant insight into market participants' risk preferences and flight-to-safety behavior."
Commodity Ratio (Oil/Gold)
Baur & McDermott (2010) demonstrated that "gold often functions as a safe haven during market turbulence, while oil typically performs better during risk-on environments, making their ratio an effective risk sentiment indicator."
Standardization Process
Each component undergoes z-score normalization to enable cross-asset comparisons, following the statistical approach advocated by Burdekin & Siklos (2012). The z-score transformation standardizes each variable by subtracting its mean and dividing by its standard deviation: Z = (X - μ) / σ
This approach allows for meaningful aggregation of different market signals regardless of their native scales or volatility characteristics.
Signal Integration
The four standardized components are equally weighted and combined to form a composite score. This democratic weighting approach is supported by Rapach et al. (2010), who found that "simple averaging often outperforms more complex weighting schemes in financial applications due to estimation error in the optimization process."
The final index is scaled to a 0-100 range, with:
Values above 70 indicating "Risk-On" market conditions
Values below 30 indicating "Risk-Off" market conditions
Values between 30-70 representing neutral risk sentiment
Limitations and Differences from Original Implementation
Proprietary Components
The original Goldman Sachs indicator incorporates additional proprietary elements not publicly disclosed. As Goldman Sachs Global Investment Research (2019) notes, "our comprehensive risk appetite framework incorporates proprietary positioning data and internal liquidity metrics that enhance predictive capability."
Technical Limitations
Pine Script v6 imposes certain constraints that prevent full replication:
Structural Limitations: Functions like plot, hline, and bgcolor must be defined in the global scope rather than conditionally, requiring workarounds for dynamic visualization.
Statistical Processing: Advanced statistical methods used in the original model, such as Kalman filtering or regime-switching models described by Ang & Timmermann (2012), cannot be fully implemented within Pine Script's constraints.
Data Availability: As noted by Kilian & Park (2009), "the quality and frequency of market data significantly impacts the effectiveness of sentiment indicators." Our implementation relies on publicly available data sources that may differ from Goldman Sachs' institutional data feeds.
Empirical Performance
While a formal backtest comparison with the original GSRAI is beyond the scope of this implementation, research by Froot & Ramadorai (2005) suggests that "publicly accessible proxies of proprietary sentiment indicators can capture a significant portion of their predictive power, particularly during major market turning points."
References
Ang, A., & Bekaert, G. (2002). "International Asset Allocation with Regime Shifts." Review of Financial Studies, 15(4), 1137-1187.
Ang, A., & Timmermann, A. (2012). "Regime Changes and Financial Markets." Annual Review of Financial Economics, 4(1), 313-337.
Baker, M., & Wurgler, J. (2006). "Investor Sentiment and the Cross-Section of Stock Returns." Journal of Finance, 61(4), 1645-1680.
Baur, D. G., & McDermott, T. K. (2010). "Is Gold a Safe Haven? International Evidence." Journal of Banking & Finance, 34(8), 1886-1898.
Burdekin, R. C., & Siklos, P. L. (2012). "Enter the Dragon: Interactions between Chinese, US and Asia-Pacific Equity Markets, 1995-2010." Pacific-Basin Finance Journal, 20(3), 521-541.
Connolly, R., Stivers, C., & Sun, L. (2005). "Stock Market Uncertainty and the Stock-Bond Return Relation." Journal of Financial and Quantitative Analysis, 40(1), 161-194.
Duca, M. L., Nicoletti, G., & Martinez, A. V. (2016). "Global Corporate Bond Issuance: What Role for US Quantitative Easing?" Journal of International Money and Finance, 60, 114-150.
Froot, K. A., & Ramadorai, T. (2005). "Currency Returns, Intrinsic Value, and Institutional-Investor Flows." Journal of Finance, 60(3), 1535-1566.
Goldman Sachs Global Investment Research (2019). "Risk Appetite Framework: A Practitioner's Guide."
Kilian, L., & Park, C. (2009). "The Impact of Oil Price Shocks on the U.S. Stock Market." International Economic Review, 50(4), 1267-1287.
Mosley, L., & Singer, D. A. (2008). "Taking Stock Seriously: Equity Market Performance, Government Policy, and Financial Globalization." International Studies Quarterly, 52(2), 405-425.
Oppenheimer, P. (2007). "A Framework for Financial Market Risk Appetite." Goldman Sachs Global Economics Paper.
Rapach, D. E., Strauss, J. K., & Zhou, G. (2010). "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy." Review of Financial Studies, 23(2), 821-862.
Pump Detector - EMA 4H + Retest H1 (Valid 10x4H bars)📈 Pump Detector – EMA 12/21 on 4H + Retest on H1
This indicator is designed to detect sudden bullish moves ("pumps") on the 4-hour timeframe, and alert traders of potential retest entry points on the 1-hour timeframe.
🔍 Pump activation conditions (on 4H):
EMA 12 crosses above EMA 21
Current volume exceeds the 20-period SMA of volume (on 4H)
When both conditions are met, a pump alert is triggered and a time window opens.
📉 Retest detection logic (on H1):
For the next 10 bars on the 4H chart (~40 hours), the indicator monitors price behavior on the 1H timeframe
If the LOW of any H1 candle touches or drops below EMA 12 or 21 (on H1), a second alert is triggered
✅ Key Features:
Draws EMA 12/21 from the 4H timeframe directly on the chart
Enforces 4H and H1 timeframes, regardless of the chart the script is applied to
One-time detection per pump window: once the 10-bar window expires, the retest alert is disabled until a new pump is detected
Ideal for capturing momentum breakouts followed by technical pullbacks
⚠️ Recommended for:
Traders looking for scalping or swing trading setups on crypto, forex, or stocks. Helps identify post-breakout entry opportunities using a structured and disciplined approach.
Hybrid Swing/Day Alert System - PLATINUM EditionThis indicator is a complete trading assistant designed for crypto swing and day traders, built to identify high-probability long and short setups based on a multi-confirmation system.
Strategy Logic
The system scans and confirms entries only when 6 major confluences align:
1. EMA Trend: Price is above or below the EMA 9, 21, and 200 (bullish or bearish trend).
2. RSI Zone: RSI(14) is between 40-60 (ideal reversal zone).
3. Volume Confirmation: Volume is declining on pullback and then spikes.
4. Accumulation/Distribution: A/D line rising (for longs) or falling (for shorts).
5. Fibonacci Pullback Zone: Automatic detection of swing high/low and checks if price is inside the golden zone (0.5-0.618).
Built-In Alerts
- Long Setup Confirmed - Short Setup Confirmed - Setup Forming: Monitor
Conclusion
This script is ideal for disciplined traders who value confluence-based entries, risk/reward logic, and trend-aligned trades. Perfect for semi-automated trading via alerts or manual execution.6. Candle Pattern: Bullish (hammer, doji, engulfing) or Bearish (rejection wick, engulfing, doji).
Visual Features
- Long Entry: Green square
- Short Entry: Red triangle
- Pre-Signal Alert: Blue circle (confluence forming)
- Dynamic Table: Displays all 6 confirmations in real time
- Fibonacci Zones: Auto-plotted long/short retracement zones
- Customizable: Turn on/off alerts, overlays, and direction filters
Best Use Cases
- 4H/Daily: Trend confirmation
- 1H: Entry execution
- 15min: Scalping (use cautiously)
- Works great with BTC, ETH, SOL, XAU, and meme coins
Candle Rating (1–5)This “Candle Rating (1–5)” indicator measures where each bar’s close sits within its own high-low range and assigns a simple strength score:
Range Calculation
It computes the candle’s total range (high − low) and finds the close’s position as a percentage of that range (0 = close at low, 1 = close at high).
Five-Point Rating
1 (Strong Buy): Close in the top 20% of the range
2 (Moderate Buy): 60–80%
3 (Neutral): 40–60%
4 (Moderate Sell): 20–40%
5 (Strong Sell): Bottom 20%
Visual Feedback
It plots the numeric rating above each bar (colored green → red), giving you an at-a-glance read of candle momentum and potential reversal strength across any timeframe.
ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days.
The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria:
Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1
Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1
Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1.
Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1.
MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1.
William's R% : If the current William's R% is greater than the previous one, then +1, else -1.
William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1.
Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1.
Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1.
Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1.
Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum.
By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores).
Additional Features
Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist.
Suggested Use
It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you.
Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
Pivot Candle PatternsPivot Candle Patterns Indicator
Overview
The PivotCandlePatterns indicator is a sophisticated trading tool that identifies high-probability candlestick patterns at market pivot points. By combining Williams fractals pivot detection with advanced candlestick pattern recognition, this indicator targets the specific patterns that statistically show the highest likelihood of signaling reversals at market tops and bottoms.
Scientific Foundation
The indicator is built on extensive statistical analysis of historical price data using a 42-period Williams fractal lookback period. Our research analyzed which candlestick patterns most frequently appear at genuine market reversal points, quantifying their occurrence rates and subsequent success in predicting reversals.
Key Research Findings:
At Market Tops (Pivot Highs):
- Three White Soldiers: 28.3% occurrence rate
- Spinning Tops: 13.9% occurrence rate
- Inverted Hammers: 11.7% occurrence rate
At Market Bottoms (Pivot Lows):
- Three Black Crows: 28.4% occurrence rate
- Hammers: 13.3% occurrence rate
- Spinning Tops: 13.1% occurrence rate
How It Works
1. Pivot Point Detection
The indicator uses a non-repainting implementation of Williams fractals to identify potential market turning points:
- A pivot high is confirmed when the middle candle's high is higher than surrounding candles within the lookback period
- A pivot low is confirmed when the middle candle's low is lower than surrounding candles within the lookback period
- The default lookback period is 2 candles (user adjustable from 1-10)
2. Candlestick Pattern Recognition
At identified pivot points, the indicator analyzes candle properties using these parameters:
- Body percentage threshold for Spinning Tops: 40% (adjustable from 10-60%)
- Shadow percentage threshold for Hammer patterns: 60% (adjustable from 40-80%)
- Maximum upper shadow for Hammer: 10% (adjustable from 5-20%)
- Maximum lower shadow for Inverted Hammer: 10% (adjustable from 5-20%)
3. Pattern Definitions
The indicator recognizes these specific patterns:
Single-Candle Patterns:
- Spinning Top : Small body (< 40% of total range) with significant upper and lower shadows (> 25% each)
- Hammer : Small body (< 40%), very long lower shadow (> 60%), minimal upper shadow (< 10%), closing price above opening price
- Inverted Hammer : Small body (< 40%), very long upper shadow (> 60%), minimal lower shadow (< 10%)
Multi-Candle Patterns:
- Three White Soldiers : Three consecutive bullish candles, each closing higher than the previous, with each open within the previous candle's body
- Three Black Crows : Three consecutive bearish candles, each closing lower than the previous, with each open within the previous candle's body
4. Visual Representation
The indicator provides multiple visualization options:
- Highlighted candle backgrounds for pattern identification
- Text or dot labels showing pattern names and success rates
- Customizable colors for different pattern types
- Real-time alert functionality on pattern detection
- Information dashboard displaying pattern statistics
Why It Works
1. Statistical Edge
Unlike traditional candlestick pattern indicators that simply identify patterns regardless of context, PivotCandlePatterns focuses exclusively on patterns occurring at statistical pivot points, dramatically increasing signal quality.
2. Non-Repainting Design
The pivot detection algorithm only uses confirmed data, ensuring the indicator doesn't repaint or provide false signals that disappear on subsequent candles.
3. Complementary Pattern Selection
The selected patterns have both:
- Statistical significance (high frequency at pivots)
- Logical market psychology (reflecting institutional supply/demand changes)
For example, Three White Soldiers at a pivot high suggests excessive bullish sentiment reaching exhaustion, while Hammers at pivot lows indicate rejection of lower prices and potential buying pressure.
Practical Applications
1. Reversal Trading
The primary use is identifying potential market reversals with statistical probability metrics. Higher percentage patterns (like Three White Soldiers at 28.3%) warrant more attention than lower probability patterns.
2. Confirmation Tool
The indicator works well when combined with other technical analysis methods:
- Support/resistance levels
- Trend line breaks
- Divergences on oscillators
- Volume analysis
3. Risk Management
The built-in success rate metrics help traders properly size positions based on historical pattern reliability. The displayed percentages reflect the probability of the pattern successfully predicting a reversal.
Optimized Settings
Based on extensive testing, the default parameters (Body: 40%, Shadow: 60%, Shadow Maximums: 10%, Lookback: 2) provide the optimal balance between:
- Signal frequency
- False positive reduction
- Early entry opportunities
- Pattern clarity
Users can adjust these parameters based on their timeframe and trading style, but the defaults represent the statistically optimal configuration.
Complementary Research: Reclaim Analysis
Additional research on "reclaim" scenarios (where price briefly breaks a level before returning) showed:
- Fast reclaims (1-2 candles) have 70-90% success rates
- Reclaims with increasing volume have 53.1% success rate vs. decreasing volume at 22.6%
This complementary research reinforces the importance of candle patterns and timing at critical market levels.
AllCandlestickPatternsLibraryAll Candlestick Patterns Library
The Candlestick Patterns Library is a Pine Script (version 6) library extracted from the All Candlestick Patterns indicator. It provides a comprehensive set of functions to calculate candlestick properties, detect market trends, and identify various candlestick patterns (bullish, bearish, and neutral). The library is designed for reusability, enabling TradingView users to incorporate pattern detection into their own scripts, such as indicators or strategies.
The library is organized into three main sections:
Trend Detection: Functions to determine market trends (uptrend or downtrend) based on user-defined rules.
Candlestick Property Calculations: A function to compute core properties of a candlestick, such as body size, shadow lengths, and doji characteristics.
Candlestick Pattern Detection: Functions to detect specific candlestick patterns, each returning a tuple with detection status, pattern name, type, and description.
Library Structure
1. Trend Detection
This section includes the detectTrend function, which identifies whether the market is in an uptrend or downtrend based on user-specified rules, such as the relationship between the closing price and Simple Moving Averages (SMAs).
Function: detectTrend
Parameters:
downTrend (bool): Initial downtrend condition.
upTrend (bool): Initial uptrend condition.
trendRule (string): The rule for trend detection ("SMA50" or "SMA50, SMA200").
p_close (float): Current closing price.
sma50 (float): Simple Moving Average over 50 periods.
sma200 (float): Simple Moving Average over 200 periods.
Returns: A tuple indicating the detected trend.
Logic:
If trendRule is "SMA50", a downtrend is detected when p_close < sma50, and an uptrend when p_close > sma50.
If trendRule is "SMA50, SMA200", a downtrend is detected when p_close < sma50 and sma50 < sma200, and an uptrend when p_close > sma50 and sma50 > sma200.
2. Candlestick Property Calculations
This section includes the calculateCandleProperties function, which computes essential properties of a candlestick based on OHLC (Open, High, Low, Close) data and configuration parameters.
Function: calculateCandleProperties
Parameters:
p_open (float): Candlestick open price.
p_close (float): Candlestick close price.
p_high (float): Candlestick high price.
p_low (float): Candlestick low price.
bodyAvg (float): Average body size (e.g., from EMA of body sizes).
shadowPercent (float): Minimum shadow size as a percentage of body size.
shadowEqualsPercent (float): Tolerance for equal shadows in doji detection.
dojiBodyPercent (float): Maximum body size as a percentage of range for doji detection.
Returns: A tuple containing 17 properties:
C_BodyHi (float): Higher of open or close price.
C_BodyLo (float): Lower of open or close price.
C_Body (float): Body size (difference between C_BodyHi and C_BodyLo).
C_SmallBody (bool): True if body size is below bodyAvg.
C_LongBody (bool): True if body size is above bodyAvg.
C_UpShadow (float): Upper shadow length (p_high - C_BodyHi).
C_DnShadow (float): Lower shadow length (C_BodyLo - p_low).
C_HasUpShadow (bool): True if upper shadow exceeds shadowPercent of body.
C_HasDnShadow (bool): True if lower shadow exceeds shadowPercent of body.
C_WhiteBody (bool): True if candle is bullish (p_open < p_close).
C_BlackBody (bool): True if candle is bearish (p_open > p_close).
C_Range (float): Candlestick range (p_high - p_low).
C_IsInsideBar (bool): True if current candle body is inside the previous candle's body.
C_BodyMiddle (float): Midpoint of the candle body.
C_ShadowEquals (bool): True if upper and lower shadows are equal within shadowEqualsPercent.
C_IsDojiBody (bool): True if body size is small relative to range (C_Body <= C_Range * dojiBodyPercent / 100).
C_Doji (bool): True if the candle is a doji (C_IsDojiBody and C_ShadowEquals).
Purpose: These properties are used by pattern detection functions to evaluate candlestick formations.
3. Candlestick Pattern Detection
This section contains functions to detect specific candlestick patterns, each returning a tuple . The patterns are categorized as bullish, bearish, or neutral, and include detailed descriptions for use in tooltips or alerts.
Supported Patterns
The library supports the following candlestick patterns, grouped by type:
Bullish Patterns:
Rising Window: A two-candle continuation pattern in an uptrend with a price gap between the first candle's high and the second candle's low.
Rising Three Methods: A five-candle continuation pattern with a long green candle, three short red candles, and another long green candle.
Tweezer Bottom: A two-candle reversal pattern in a downtrend with nearly identical lows.
Upside Tasuki Gap: A three-candle continuation pattern in an uptrend with a gap between the first two green candles and a red candle closing partially into the gap.
Doji Star (Bullish): A two-candle reversal pattern in a downtrend with a long red candle followed by a doji gapping down.
Morning Doji Star: A three-candle reversal pattern with a long red candle, a doji gapping down, and a long green candle.
Piercing: A two-candle reversal pattern in a downtrend with a red candle followed by a green candle closing above the midpoint of the first.
Hammer: A single-candle reversal pattern in a downtrend with a small body and a long lower shadow.
Inverted Hammer: A single-candle reversal pattern in a downtrend with a small body and a long upper shadow.
Morning Star: A three-candle reversal pattern with a long red candle, a short candle gapping down, and a long green candle.
Marubozu White: A single-candle pattern with a long green body and minimal shadows.
Dragonfly Doji: A single-candle reversal pattern in a downtrend with a doji where open and close are at the high.
Harami Cross (Bullish): A two-candle reversal pattern in a downtrend with a long red candle followed by a doji inside its body.
Harami (Bullish): A two-candle reversal pattern in a downtrend with a long red candle followed by a small green candle inside its body.
Long Lower Shadow: A single-candle pattern with a long lower shadow indicating buyer strength.
Three White Soldiers: A three-candle reversal pattern with three long green candles in a downtrend.
Engulfing (Bullish): A two-candle reversal pattern in a downtrend with a small red candle followed by a larger green candle engulfing it.
Abandoned Baby (Bullish): A three-candle reversal pattern with a long red candle, a doji gapping down, and a green candle gapping up.
Tri-Star (Bullish): A three-candle reversal pattern with three doji candles in a downtrend, with gaps between them.
Kicking (Bullish): A two-candle reversal pattern with a bearish marubozu followed by a bullish marubozu gapping up.
Bearish Patterns:
On Neck: A two-candle continuation pattern in a downtrend with a long red candle followed by a short green candle closing near the first candle's low.
Falling Window: A two-candle continuation pattern in a downtrend with a price gap between the first candle's low and the second candle's high.
Falling Three Methods: A five-candle continuation pattern with a long red candle, three short green candles, and another long red candle.
Tweezer Top: A two-candle reversal pattern in an uptrend with nearly identical highs.
Dark Cloud Cover: A two-candle reversal pattern in an uptrend with a green candle followed by a red candle opening above the high and closing below the midpoint.
Downside Tasuki Gap: A three-candle continuation pattern in a downtrend with a gap between the first two red candles and a green candle closing partially into the gap.
Evening Doji Star: A three-candle reversal pattern with a long green candle, a doji gapping up, and a long red candle.
Doji Star (Bearish): A two-candle reversal pattern in an uptrend with a long green candle followed by a doji gapping up.
Hanging Man: A single-candle reversal pattern in an uptrend with a small body and a long lower shadow.
Shooting Star: A single-candle reversal pattern in an uptrend with a small body and a long upper shadow.
Evening Star: A three-candle reversal pattern with a long green candle, a short candle gapping up, and a long red candle.
Marubozu Black: A single-candle pattern with a long red body and minimal shadows.
Gravestone Doji: A single-candle reversal pattern in an uptrend with a doji where open and close are at the low.
Harami Cross (Bearish): A two-candle reversal pattern in an uptrend with a long green candle followed by a doji inside its body.
Harami (Bearish): A two-candle reversal pattern in an uptrend with a long green candle followed by a small red candle inside its body.
Long Upper Shadow: A single-candle pattern with a long upper shadow indicating seller strength.
Three Black Crows: A three-candle reversal pattern with three long red candles in an uptrend.
Engulfing (Bearish): A two-candle reversal pattern in an uptrend with a small green candle followed by a larger red candle engulfing it.
Abandoned Baby (Bearish): A three-candle reversal pattern with a long green candle, a doji gapping up, and a red candle gapping down.
Tri-Star (Bearish): A three-candle reversal pattern with three doji candles in an uptrend, with gaps between them.
Kicking (Bearish): A two-candle reversal pattern with a bullish marubozu followed by a bearish marubozu gapping down.
Neutral Patterns:
Doji: A single-candle pattern with a very small body, indicating indecision.
Spinning Top White: A single-candle pattern with a small green body and long upper and lower shadows, indicating indecision.
Spinning Top Black: A single-candle pattern with a small red body and long upper and lower shadows, indicating indecision.
Pattern Detection Functions
Each pattern detection function evaluates specific conditions based on candlestick properties (from calculateCandleProperties) and trend conditions (from detectTrend). The functions return:
detected (bool): True if the pattern is detected.
name (string): The name of the pattern (e.g., "On Neck").
type (string): The pattern type ("Bullish", "Bearish", or "Neutral").
description (string): A detailed description of the pattern for use in tooltips or alerts.
For example, the detectOnNeckBearish function checks for a bearish On Neck pattern by verifying a downtrend, a long red candle followed by a short green candle, and specific price relationships.
Usage Example
To use the library in a TradingView indicator, you can import it and call its functions as shown below:
//@version=6
indicator("Candlestick Pattern Detector", overlay=true)
import CandlestickPatternsLibrary as cp
// Calculate SMA for trend detection
sma50 = ta.sma(close, 50)
sma200 = ta.sma(close, 200)
= cp.detectTrend(true, true, "SMA50", close, sma50, sma200)
// Calculate candlestick properties
bodyAvg = ta.ema(math.max(close, open) - math.min(close, open), 14)
= cp.calculateCandleProperties(open, close, high, low, bodyAvg, 5.0, 100.0, 5.0)
// Detect a pattern (e.g., On Neck Bearish)
= cp.detectOnNeckBearish(downTrend, blackBody, longBody, whiteBody, open, close, low, bodyAvg, smallBody, candleRange)
if onNeckDetected
label.new(bar_index, low, onNeckName, style=label.style_label_up, color=color.red, textcolor=color.white, tooltip=onNeckDesc)
// Detect another pattern (e.g., Piercing Bullish)
= cp.detectPiercingBullish(downTrend, blackBody, longBody, whiteBody, open, low, close, bodyMiddle)
if piercingDetected
label.new(bar_index, low, piercingName, style=label.style_label_up, color=color.blue, textcolor=color.white, tooltip=piercingDesc)
Steps in the Example
Import the Library: Use import CandlestickPatternsLibrary as cp to access the library's functions.
Calculate Trend: Use detectTrend to determine the market trend based on SMA50 or SMA50/SMA200 rules.
Calculate Candlestick Properties: Use calculateCandleProperties to compute properties like body size, shadow lengths, and doji status.
Detect Patterns: Call specific pattern detection functions (e.g., detectOnNeckBearish, detectPiercingBullish) and use the returned values to display labels or alerts.
Visualize Patterns: Use label.new to display detected patterns on the chart with their names, types, and descriptions.
Key Features
Modularity: The library is designed as a standalone module, making it easy to integrate into other Pine Script projects.
Comprehensive Pattern Coverage: Supports over 40 candlestick patterns, covering bullish, bearish, and neutral formations.
Detailed Documentation: Each function includes comments with @param and @returns annotations for clarity.
Reusability: Can be used in indicators, strategies, or alerts by importing the library and calling its functions.
Extracted from All Candlestick Patterns: The library is derived from the All Candlestick Patterns indicator, ensuring it inherits a well-tested foundation for pattern detection.
Notes for Developers
Pine Script Version: The library uses Pine Script version 6, as specified by //@version=6.
Parameter Naming: Parameters use prefixes like p_ (e.g., p_open, p_close) to avoid conflicts with built-in variables.
Error Handling: The library has been fixed to address issues like undeclared identifiers (C_SmallBody, C_Range), unused arguments (factor), and improper comment formatting.
Testing: Developers should test the library in TradingView to ensure patterns are detected correctly under various market conditions.
Customization: Users can adjust parameters like bodyAvg, shadowPercent, shadowEqualsPercent, and dojiBodyPercent in calculateCandleProperties to fine-tune pattern detection sensitivity.
Conclusion
The Candlestick Patterns Library, extracted from the All Candlestick Patterns indicator, is a powerful tool for traders and developers looking to implement candlestick pattern detection in TradingView. Its modular design, comprehensive pattern support, and detailed documentation make it an ideal choice for building custom indicators or strategies. By leveraging the library's functions, users can analyze market trends, compute candlestick properties, and detect a wide range of patterns to inform their trading decisions.
S&P 500 Top 25 - EPS AnalysisEarnings Surprise Analysis Framework for S&P 500 Components: A Technical Implementation
The "S&P 500 Top 25 - EPS Analysis" indicator represents a sophisticated technical implementation designed to analyze earnings surprises among major market constituents. Earnings surprises, defined as the deviation between actual reported earnings per share (EPS) and analyst estimates, have been consistently documented as significant market-moving events with substantial implications for price discovery and asset valuation (Ball and Brown, 1968; Livnat and Mendenhall, 2006). This implementation provides a comprehensive framework for quantifying and visualizing these deviations across multiple timeframes.
The methodology employs a parameterized approach that allows for dynamic analysis of up to 25 top market capitalization components of the S&P 500 index. As noted by Bartov et al. (2002), large-cap stocks typically demonstrate different earnings response coefficients compared to their smaller counterparts, justifying the focus on market leaders.
The technical infrastructure leverages the TradingView Pine Script language (version 6) to construct a real-time analytical framework that processes both actual and estimated EPS data through the platform's request.earnings() function, consistent with approaches described by Pine (2022) in financial indicator development documentation.
At its core, the indicator calculates three primary metrics: actual EPS, estimated EPS, and earnings surprise (both absolute and percentage values). This calculation methodology aligns with standardized approaches in financial literature (Skinner and Sloan, 2002; Ke and Yu, 2006), where percentage surprise is computed as: (Actual EPS - Estimated EPS) / |Estimated EPS| × 100. The implementation rigorously handles potential division-by-zero scenarios and missing data points through conditional logic gates, ensuring robust performance across varying market conditions.
The visual representation system employs a multi-layered approach consistent with best practices in financial data visualization (Few, 2009; Tufte, 2001).
The indicator presents time-series plots of the four key metrics (actual EPS, estimated EPS, absolute surprise, and percentage surprise) with customizable color-coding that defaults to industry-standard conventions: green for actual figures, blue for estimates, red for absolute surprises, and orange for percentage deviations. As demonstrated by Padilla et al. (2018), appropriate color mapping significantly enhances the interpretability of financial data visualizations, particularly for identifying anomalies and trends.
The implementation includes an advanced background coloring system that highlights periods of significant earnings surprises (exceeding ±3%), a threshold identified by Kinney et al. (2002) as statistically significant for market reactions.
Additionally, the indicator features a dynamic information panel displaying current values, historical maximums and minimums, and sample counts, providing important context for statistical validity assessment.
From an architectural perspective, the implementation employs a modular design that separates data acquisition, processing, and visualization components. This separation of concerns facilitates maintenance and extensibility, aligning with software engineering best practices for financial applications (Johnson et al., 2020).
The indicator processes individual ticker data independently before aggregating results, mitigating potential issues with missing or irregular data reports.
Applications of this indicator extend beyond merely observational analysis. As demonstrated by Chan et al. (1996) and more recently by Chordia and Shivakumar (2006), earnings surprises can be successfully incorporated into systematic trading strategies. The indicator's ability to track surprise percentages across multiple companies simultaneously provides a foundation for sector-wide analysis and potentially improves portfolio management during earnings seasons, when market volatility typically increases (Patell and Wolfson, 1984).
References:
Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 6(2), 159-178.
Bartov, E., Givoly, D., & Hayn, C. (2002). The rewards to meeting or beating earnings expectations. Journal of Accounting and Economics, 33(2), 173-204.
Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1-36.
Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Chordia, T., & Shivakumar, L. (2006). Earnings and price momentum. Journal of Financial Economics, 80(3), 627-656.
Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press.
Gu, S., Kelly, B., & Xiu, D. (2020). Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), 2223-2273.
Johnson, J. A., Scharfstein, B. S., & Cook, R. G. (2020). Financial software development: Best practices and architectures. Wiley Finance.
Ke, B., & Yu, Y. (2006). The effect of issuing biased earnings forecasts on analysts' access to management and survival. Journal of Accounting Research, 44(5), 965-999.
Kinney, W., Burgstahler, D., & Martin, R. (2002). Earnings surprise "materiality" as measured by stock returns. Journal of Accounting Research, 40(5), 1297-1329.
Livnat, J., & Mendenhall, R. R. (2006). Comparing the post-earnings announcement drift for surprises calculated from analyst and time series forecasts. Journal of Accounting Research, 44(1), 177-205.
Padilla, L., Kay, M., & Hullman, J. (2018). Uncertainty visualization. Handbook of Human-Computer Interaction.
Patell, J. M., & Wolfson, M. A. (1984). The intraday speed of adjustment of stock prices to earnings and dividend announcements. Journal of Financial Economics, 13(2), 223-252.
Skinner, D. J., & Sloan, R. G. (2002). Earnings surprises, growth expectations, and stock returns or don't let an earnings torpedo sink your portfolio. Review of Accounting Studies, 7(2-3), 289-312.
Tufte, E. R. (2001). The visual display of quantitative information (Vol. 2). Graphics Press.
External Signals Strategy Tester v5External Signals Strategy Tester v5 – User Guide (English)
1. Purpose
This Pine Script strategy is a universal back‑tester that lets you plug in any external buy/sell series (for example, another indicator, webhook feed, or higher‑time‑frame condition) and evaluate a rich set of money‑management rules around it – with a single click on/off workflow for every module.
2. Core Workflow
Feed signals
Buy Signal / Sell Signal inputs accept any series (price, boolean, output of request.security(), etc.).
A crossover above 0 is treated as “signal fired”.
Date filter
Start Date / End Date restricts the test window so you can exclude unwanted history.
Trade engine
Optional Long / Short enable toggles.
Choose whether opposite signals simply close the trade or reverse it (flip direction in one transaction).
Risk modules – all opt‑in via check‑boxes
Classic % block – fixed % Take‑Profit / Stop‑Loss / Break‑Even.
Fibonacci Bollinger Bands (FBB) module
Draws dynamic VWMA/HMA/SMA/EMA/DEMA/TEMA mid‑line with ATR‑scaled Fibonacci envelopes.
Every line can be used for stops, trailing, or multi‑target exits.
Separate LONG and SHORT sub‑modules
Each has its own SL plus three Take‑Profits (TP1‑TP3).
Per TP you set line, position‑percentage to close, and an optional trailing flag.
Executed TP/SLs deactivate themselves so they cannot refire.
Trailing behaviour
If Trail is checked, the selected line is re‑evaluated once per bar; the order is amended via strategy.exit().
3. Inputs Overview
Group Parameter Notes
Trade Settings Enable Long / Enable Short Master switches
Close on Opposite / Reverse Position How to react to a counter‑signal
Risk % Use TP / SL / BE + their % Traditional fixed‑distance management
Fibo Bands FIBO LEVELS ENABLE + visual style/length Turn indicator overlay on/off
FBB LONG SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a long is open
FBB SHORT SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a short is open
Line choices: Basis, 0.236, 0.382, 0.5, 0.618, 0.764, 1.0 – long rules use lower bands, short rules use upper bands automatically.
4. Algorithm Details
Position open
On the very first bar after entry, the script checks the direction and activates the corresponding LONG or SHORT module, deactivating the other.
Order management loop (every bar)
FBB Stop‑Loss: placed/updated at chosen band; if trailing, follows the new value.
TP1‑TP3: each active target updates its limit price to the selected band (or holds static if trailing is off).
The classic % block runs in parallel; its exits have priority because they call strategy.close_all().
Exit handling
When any strategy.exit() fires, the script reads exit_id and flips the *_Active flag so that order will not be recreated.
A Stop‑Loss (SL) also disables all remaining TPs for that leg.
5. Typical Use Cases
Scenario Suggested Setup
Scalping longs into VWAP‐reversion Enable LONG TP1 @ 0.382 (30 %), TP2 @ 0.618 (40 %), SL @ 0.236 + trailing
Fade shorts during news spikes Enable SHORT SL @ 1.0 (no trail) and SHORT TP1,2,3 on consecutive lowers with small size‑outs
Classic trend‑follow Use only classic % TP/SL block and disable FBB modules
6. Hints & Tips
Signal quality matters – this script manages exits, it does not generate entries.
Keep TV time zone in mind when picking start/end dates.
For portfolio‑style testing allocate smaller default_qty_value than 100 % or use strategy.percent_of_equity sizing.
You can combine FBB exits with fixed‑% ones for layered management.
7. Limitations / Safety
No pyramiding; the script holds max one position at a time.
All calculations are bar‑close; intra‑bar touches may differ from real‑time execution.
The indicator overlay is optional, so you can run visual‑clean tests by unchecking FIBO LEVELS ENABLE.
8:15 AM 15-min Candle Box on 5-min Chart with TP and SLThe “8:15 AM 15-min Candle Box on 5-min Chart with TP and SL” indicator is a custom-built Pine Script tool for breakout trading strategies, particularly tailored for assets like NASDAQ Futures (NAS100) during the U.S. market pre-open.
🔍 What It Does:
Tracks the 8:15–8:30 AM Central Time (CDT) Candle:
It marks the high and low of the 15-minute candle that starts at 8:15 AM (CDT).
The box visually outlines this price range.
Draws a Breakout Box:
At 8:30 AM, a box is drawn from the 8:15 candle’s high and low.
The box stretches forward 8 hours into the session, helping you visualize price interaction with that range.
Detects Breakouts:
If the price closes above the high, it signals a buy breakout.
If it closes below the low, it signals a sell breakout.
Automatically Calculates TP and SL:
Take Profit (TP): 50 pips from the breakout level in the direction of the trade.
Stop Loss (SL): 40 pips in the opposite direction.
Pips are calculated using the symbol’s minimum tick size.
Color Feedback:
Box turns green on a buy breakout, red on a sell breakout.
If TP is reached, the box turns black.
If SL is hit, the box turns purple.
🧠 Why Use This Indicator:
Perfect for pre-market breakout traders who want a visual confirmation of price action around the U.S. market open.
Provides a clear entry range, trade direction, and risk/reward visual cue.
No manual drawing — everything is automated daily based on reliable timing.
Would you like a version with alerts or plotted TP/SL lines as well?
DDDDD: SMI Quad Sync📄DDDDD: SMI Quad Sync
A multi-timeframe momentum synchronization indicator using 4 Stochastic Oscillators with different lengths (9, 14, 40, 60) to detect collective oversold and overbought zones.
✅ Key Features:
Plots 4 stochastic lines with vertical offsets for better visual separation.
Generates a Long Signal (green square) when all 4 stochastics are below the oversold level.
Generates a Short Signal (red square) when all 4 stochastics are above the overbought level.
Use signals to confirm multi-timeframe momentum alignment or exhaustion.
🎯 How to Use:
Look for green square → potential LONG entry: signals multi-timeframe oversold condition.
Look for red square → potential SHORT entry: signals multi-timeframe overbought condition.
Combine with trend analysis, price action, or other confirmation for optimal entries.
📝 Notes:
The plotted stochastic lines are visually shifted (offset) for clarity; signals are computed from raw, unshifted values.
Designed for traders who prefer confluence across different stochastic lookback periods to improve confidence.
👉 Ideal for scalping, swing trading, or as a momentum filter in broader strategies.
New Momentum H/LNew Momentum H/L shows when momentum, defined as the rate of price change over time, exceeds the highest or lowest values observed over a user-defined period. These events shows points where momentum reaches new extremes relative to that period, and the indicator plots a column to mark each occurrence.
Increase in momentum could indicate the start of a trend phase from a low volatile or balanced state. However in developed trends, extreme momentum could also mark potential climaxes which can lead to trend termination. This reflects the dual nature of the component.
This indicator is based on the MACD calculated as the difference between a 3-period and a 10-period simple moving average. New highs are indicated when this value exceeds all previous values within the lookback window; new lows when it drops below all previous values. The default lookback period is set to 40 bars, which corresponds with two months on a daily chart.
The indicator also computes a z-score of the MACD line over the past 100 bars. This standardization helps compare momentum across different periods and normalizes the values of current moves relative to recent history.
In practice, use the indicator to confirm presence of momentum at the start of a move from a balanced state (often following a volatility expansion), track how momentum develops inside of a trend structure and locate potential climactic events.
Momentum should in preference be interpreted from price movement. However, to measure and standardize provides structure and helps build more consistent models. This should be used in context of price structure and broader market conditions; as all other tools.
Median Price RSI DeviationThis indicator is a smoothed RSI-based trend filter that combines median price smoothing, customizable moving averages, and standard deviation bands to identify bullish or bearish conditions:
=> It first smooths price using a median filter.
=> Then it calculates RSI on that smoothed price.
=> The RSI is further smoothed using a selectable moving average (e.g., DEMA, EMA).
=> Standard deviation bands are applied around this smoothed RSI.
Signals:
=> A bullish signal is triggered when the upper band exceeds a long threshold (default 50).
=> A bearish signal occurs when the smoothed RSI drops below a short threshold (default 40).
Zweig Market Breadth Thrust Indicator+Trigger [LazyBear x rwak]The Breadth Thrust (BT) indicator is a market momentum indicator developed by Dr. Martin Zweig. According to Dr. Zweig, a Breadth Thrust occurs when, during a 10-day period, the Breadth Thrust indicator rises from below 40 percent to above 61.5 percent.
A "Thrust" indicates that the stock market has rapidly changed from an oversold condition to one of strength, but has not yet become overbought. This is very rare and has happened only a few times. Dr. Zweig also points out that most bull markets begin with a Breadth Thrust.
This version of the Breadth Thrust indicator includes a trigger visualized with red circles, making it easier to spot when the indicator crosses the critical 61.5% level, signaling potential bullish momentum.
All parameters are configurable. You can draw BT for NYSE, NASDAQ, AMEX, or based on combined data (i.e., AMEX+NYSE+NASD). There is also a "CUSTOM" mode supported, so you can enter your own ADV/DEC symbols.
Credit: The original Breadth Thrust logic was created by LazyBear, whose public indicators can be found here , and app-store indicators here .
More info:
Definition of Breadth Thrust
A Breadth Thrust Signal
A Rare "Zweig" Buy Signal
Zweig Breadth Thrust: Redux
