No Gaps - JizzanyNo Gaps – Jizzany
Fill the blanks. Own the patterns.
Don’t let thin futures feeds or blazing-fast 1 s bars break your flow—this overlay stitches every missing pixel back into your chart so you can:
🔍 Analyze low-liquidity markets (futures, exotic FX, crypto alt-pairs) without awkward jumps
⏱️ Trade ultra-low timeframes (1 s, tick charts) with full confidence in every wick
📈 Spot price patterns seamlessly, even when your broker’s feed skips a beat
How it works: Auto-detects gaps between sessions or feeds, then draws miniature candles from the prior close to the current open—using real intrabar highs/lows—so nothing ever goes unseen.
Perfect for scalpers, day traders, and anyone who demands continuity in every bar. Try it on your next chart and rediscover the story in every candle.
Turn This
Into This
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在腳本中搜尋"liquidity"
FVG (Nephew sam remake)Hello i am making my own FVG script inspired by Nephew Sam as his fvg code is not open source. My goal is to replicate his Script and then add in alerts and more functions. Thus, i spent few days trying to code. There is bugs such as lower time frame not showing higher time frame FVG.
This script automatically detects and visualizes Fair Value Gaps (FVGs) — imbalances between demand and supply — across multiple timeframes (15-minute, 1-hour, and 4-hour).
15m chart shows:
15m FVGs (green/red boxes)
1H FVGs (lime/maroon)
4H FVGs (faded green/red with borders) (Bugged For now i only see 1H appearing)
1H chart shows:
1H FVGs
4H FVGs
4H chart shows:
4H FVGs only
There is the function to auto close FVG when a future candle fully disrespected it.
You're welcome to:
🔧 Customize the appearance: adjust box colors, transparency, border style
🧪 Add alerts: e.g., when price enters or fills a gap
📅 Expand to Daily/Weekly: just copy the logic and plug in "D" or "W" as new layers
📈 Build confluence logic: combine this with order blocks, liquidity zones, or ICT concepts
🧠 Experiment with entry signals: e.g., candle confirmation on return to FVG
🚀 Improve performance: if you find a lighter way to track gaps, feel free to optimize!
Supertrend with Volume Filter AlertSupertrend with Volume Filter Alert - Indicator Overview
What is the Supertrend Indicator?
The Supertrend indicator is a popular trend-following tool used by traders to identify the direction of the market and potential entry/exit points. It is based on the Average True Range (ATR), which measures volatility, and plots a line on the chart that acts as a dynamic support or resistance level. When the price is above the Supertrend line, it signals an uptrend (bullish), and when the price is below, it indicates a downtrend (bearish). The indicator is particularly effective in trending markets but can generate false signals during choppy or sideways conditions.
How This Script Works
The "Supertrend with Volume Filter Alert" enhances the classic Supertrend indicator by adding a customizable volume filter to improve signal reliability.
Here's how it functions:
Supertrend Calculation:The Supertrend is calculated using the ATR over a user-defined period (default: 55) and a multiplier (default: 1.85). These parameters control the sensitivity of the indicator:A higher ATR period smooths out volatility, making the indicator less reactive to short-term price fluctuations.The multiplier determines the distance of the Supertrend line from the price, affecting how quickly it responds to trend changes.The script plots the Supertrend line in cyan for uptrends and red for downtrends, making it easy to visualize the market direction.
Volume Filter:A key feature of this script is the volume filter, which helps filter out false signals in choppy markets. The filter compares the current volume to the average volume over a lookback period (default: 20) and only triggers signals if the volume exceeds the average by a specified multiplier (default: 2.0).This ensures that trend changes are accompanied by significant market participation, increasing the likelihood of a genuine trend shift.
Signals and Alerts:
Buy signals (cyan triangle below the bar) are generated when the price crosses above the Supertrend line (indicating an uptrend) and the volume condition is met.Sell signals (red triangle above the bar) are generated when the price crosses below the Supertrend line (indicating a downtrend) and the volume condition is met.Alerts are set up for both buy and sell signals, notifying traders only when the volume filter confirms the trend change.
Customizable Settings for Multiple Markets
The default settings in this script (ATR Period: 55, ATR Multiplier: 1.85, Volume Lookback Period: 20, Volume Multiplier: 2.0) were carefully chosen to provide a balance of sensitivity and reliability across various markets, including stocks, indices (like the S&P 500), forex, and cryptocurrencies.
Here's why these settings work well:
ATR Period (55): A longer ATR period smooths out volatility, making the indicator less prone to whipsaws in volatile markets like crypto or forex, while still being responsive enough for trending markets like indices.
ATR Multiplier (1.85): This multiplier strikes a balance between capturing early trend changes and avoiding noise. A smaller multiplier would make the indicator too sensitive, while a larger one might miss early opportunities.
Volume Lookback Period (20): A 20-bar lookback for volume averaging provides a robust baseline for identifying significant volume spikes, adaptable to both short-term (e.g., daily charts) and longer-term (e.g., weekly charts) timeframes.
Volume Multiplier (2.0): Requiring volume to be at least 2x the average ensures that only high-conviction moves trigger signals, which is crucial for markets with varying liquidity levels.
These parameters are fully customizable, allowing traders to adjust the indicator to their specific market, timeframe, or trading style. For example, you might reduce the ATR period for faster-moving markets or increase the volume multiplier for more conservative signal filtering.
How the Volume Filter Reduces Bad Trades in Choppy Markets
One of the main drawbacks of the Supertrend indicator is its tendency to generate false signals during choppy or ranging markets, where price fluctuates without a clear trend. The volume filter in this script addresses this issue by ensuring that trend changes are backed by significant market activity:
In choppy markets, price movements often lack strong volume, leading to false breakouts or reversals. By requiring volume to be a multiple (default: 2x) of the average volume over the lookback period, the script filters out these low-volume, low-conviction moves.This reduces the likelihood of taking bad trades during sideways markets, as only trend changes with strong volume confirmation will trigger signals. For example, on a daily chart of the S&P 500, a buy signal will only fire if the price crosses above the Supertrend line and the volume on that day is at least twice the 20-day average, indicating genuine buying pressure.
Usage Tips
Markets and Timeframes: This indicator is versatile and can be used on various assets (stocks, indices, forex, crypto) and timeframes (1-minute, 1-hour, daily, etc.). Adjust the settings based on the market's volatility and your trading strategy.
Combine with Other Indicators: While the volume filter improves reliability, consider using additional indicators like RSI or MACD to confirm trends, especially in ranging markets.
Backtesting: Test the indicator on historical data for your chosen market to optimize the settings and ensure they align with your trading goals.
Alerts: Set up alerts for buy and sell signals to stay informed of high-probability trend changes without constantly monitoring the chart.
ConclusionThe "Supertrend with Volume Filter Alert" is a powerful tool for trend-following traders, combining the simplicity of the Supertrend indicator with a volume-based filter to enhance signal accuracy. Its customizable settings make it adaptable to multiple markets, while the volume filter helps reduce false signals in choppy conditions, allowing traders to focus on high-probability trades. Whether you're trading stocks, indices, forex, or crypto, this indicator can help you identify trends with greater confidence.
Swing Highs and Lows Detector🔍 Swing Highs and Lows Detector
The Swing Highs and Lows Detector is a powerful tool for traders looking to identify meaningful structural shifts in price action, based on swing point logic and internal trend shifts.
📈 What It Does
This indicator automatically identifies and labels:
HH (Higher High) – Price broke above the previous swing high
LH (Lower High) – Price failed to break the previous high, signaling potential weakness
LL (Lower Low) – Price broke below the previous swing low
HL (Higher Low) – Price maintained a higher support level, indicating strength
The script distinguishes between bullish and bearish internal shifts and tracks the highest/lowest points between those shifts to determine the swing structure.
⚙️ How It Works
You can choose between two shift detection modes:
"Open": Compares closing price to the first open of the opposite streak
"High/Low": Uses the high of bearish or low of bullish candles
Once a shift is confirmed, the indicator scans the bars between shifts to find the most significant swing high or low
When a valid swing is detected, it’s labeled directly on the chart with color-coded markers
🛎️ Built-in Alerts
Set alerts for:
Higher High
Lower High
Lower Low
Higher Low
These alerts help you catch key structural shifts in real time — great for breakout traders, structure-based analysts, and smart money concepts (SMC) strategies.
✅ How to Use
Confirm Trend Strength or Reversals – Use HH/HL to confirm an uptrend, LL/LH to confirm a downtrend
Combine with Liquidity Sweeps or Zones – Ideal for SMC or Wyckoff-style setups
Entry/Exit Triggers – Use swing breaks to time entries or exits near key structural points
Weighted Regression Bands (Zeiierman)█ Overview
Weighted Regression Bands is a precision-engineered trend and volatility tool designed to adapt to the real market structure instead of reacting to price noise.
This indicator analyzes Weighted High/Low medians and applies user-selectable smoothing methods — including Kalman Filtering, ALMA, and custom Linear Regression — to generate a Fair Value line. Around this, it constructs dynamic standard deviation bands that adapt in real-time to market volatility.
The result is a visually clean and structurally intelligent trend framework suitable for breakout traders, mean reversion strategies, and trend-driven analysis.
█ How It Works
⚪ Structural High/Low Analysis
At the heart of this indicator is a custom high/low weighting system. Instead of using just the raw high or low values, it calculates a midline = (high + low) / 2, then applies one of three weighting methods to determine which price zones matter most.
Users can select the method using the “Weighted HL Method” setting:
Simple
Selects the single most dominant median (highest or lowest) in the lookback window. Ideal for fast, reactive signals.
Advanced
Ranks each bar based on a composite score: median × range × recency. This method highlights structurally meaningful bars that had both volatility and recency. A built-in Kalman filter is applied for extra stability.
Smooth
Blends multiple bars into a single weighted average using smoothed decay and range. This provides the softest and most stable structural response.
⚪ Smoothing Methods (ALMA / Linear Regression)
ALMA provides responsive, low-lag smoothing for fast trend reading.
Linear Regression projects the Fair Value forward, ideal for trend modeling.
⚪ Kalman Smoothing Filter
Before trend calculations, the indicator applies an optional Kalman-style smoothing filter. This helps:
Reduce choppy false shifts in trend,
Retain signal clarity during volatile periods,
Provide stability for long-term setups.
⚪ Deviation Bands (Dynamic Volatility Envelopes)
The indicator builds ±1, ±2, and ±3 standard deviation bands around the fair value line:
Calculated from the standard deviation of price,
Bands expand and contract based on recent volatility,
Visualizes potential overbought/oversold or trending conditions.
█ How to Use
⚪ Trend Trading & Filtering
Use the Fair Value line to identify the dominant direction.
Only trade in the direction of the slope for higher probability setups.
⚪ Volatility-Based Entries
Watch for price reaching outer bands (+2σ, +3σ) for possible exhaustion.
Mean reversion entries become higher quality when far from Fair Value.
█ Settings
Length – Lookback for Weighted HL and trend smoothing
Deviation Multiplier – Controls how wide the bands are from the fair value line
Method – Choose between ALMA or Linear Regression smoothing
Smoothing – Strength of Kalman Filter (1 = none, <1 = stronger smoothing)
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Wick Spike 50% Detector (15m & 1h)This script identifies candles with significant upper or lower wicks (spikes) based on a percentage of the total candle range. It helps spot potential reversals, exhaustion moves, or liquidity grabs — especially useful in volatile markets.
📍 Key Features:
15-Minute Timeframe:
Red Triangle Above: Candle range ≥ 0.35% and upper wick ≥ 50% of the range.
Green Triangle Below: Candle range ≥ 0.30% and lower wick ≥ 50% of the range.
1-Hour Timeframe:
Red Circle Above: Candle range ≥ 0.50% and upper wick ≥ 50%.
Green Circle Below: Candle range ≥ 0.50% and lower wick ≥ 50%.
📢 Alerts:
Alerts trigger when the 50% spike condition is met — within the last 60 seconds before candle close — ensuring timely notifications.
🎯 Designed to assist traders in identifying spike-driven opportunities and refining entry/exit strategies.
Anchored VWAP by Time (Math by Thomas)📄 Description
This tool lets you plot an Anchored Volume Weighted Average Price (VWAP) starting from any specific date and time you choose. Unlike standard VWAPs that reset daily or weekly, this version gives you full control to track institutional pricing zones from precise anchor points—such as key swing highs/lows, market open, or news-driven candles.
It’s especially useful for price action and Smart Money Concepts (SMC) traders who track liquidity, fair value gaps (FVGs), and institutional zones.
🇮🇳 For NSE India Traders
You can anchor VWAP to Indian market open (e.g., 9:15 AM IST) or major events like RBI policy, earnings, or breakout candles.
The time input uses UTC by default, so for Indian Standard Time (IST), remember:
9:15 AM IST = 3:45 AM UTC
3:30 PM IST = 10:00 AM UTC
⚙️ How to Use
Add the indicator to your chart.
Open the settings panel.
Under “Anchor Start Time”, choose the date & time to begin the VWAP.
Use UTC format (adjust from IST if needed).
Customize the line color and thickness to suit your chart style.
The VWAP will begin plotting from that time forward.
🔎 Best Use Cases
Track VWAP from intraday range breakouts
Anchor from swing highs/lows to identify mean reversion zones
Combine with your FVGs, Order Blocks, or CHoCHs
Monitor VWAP reactions during key macro events or expiry days
🔧 Clean Design
No labels are used, keeping your chart clean.
Works on all timeframes (1min to Daily).
Designed for serious intraday & positional traders.
ZenAlgo - DominatorThis indicator provides a structured multi-ticker overview of market momentum and relative strength by analyzing short-term price behavior across selected assets in comparison with broader crypto dominance and Bitcoin/ETH performance.
Ticker and Market Data Handling
The script accepts up to 9 user-defined symbols (tickers) along with BTCUSD and ETHUSD. For each symbol:
It retrieves the current price.
It also requests the daily opening price from the "D" timeframe to compute intraday percentage change.
For BTC, ETH, and dominance (sum of BTC, USDT, and USDC dominance), daily change is calculated using this same method.
This comparison enables tracking relative performance from the daily open, which provides meaningful insight into intraday strength or weakness among different assets.
Dominance Logic
The indicator aggregates dominance data from BTC , USDT , and USDC using TradingView’s CRYPTOCAP indices. This combined dominance is used as a reference in directional and status calculations. ETH dominance is also analyzed independently.
Changes in dominance are used to infer whether market attention is shifting toward Bitcoin/stablecoins (typically indicating risk-off sentiment) or away from them (typically risk-on behavior, benefiting altcoins).
Price Direction Estimation
The script estimates directional bias using an EMA-based deviation technique:
A short EMA (user-defined lookback , default 4 bars) is calculated.
The current close is compared to the EMA to assess directional bias.
Recent candle changes are also inspected to confirm a consistent short-term trend (e.g., 3 consecutive higher closes for "up").
A small threshold is used to avoid classifying flat movements as trends.
This directionality logic is applied separately to:
The selected ticker's price
BTC price
Combined dominance
This allows the script to contextualize the movement of each asset within broader market conditions.
Market Status Evaluation
A custom function analyzes ETH and BTC dominance trends along with their relative strength to define the overall market regime:
Altseason is identified when BTC dominance is declining, ETH dominance rising, and ETH outperforms BTC.
BTC Season occurs when BTC dominance is rising, ETH dominance falling, and BTC outperforms ETH.
If neither condition is met, the state is Neutral .
This classification is shown alongside each ticker's row in the table and helps traders assess whether market conditions favor Bitcoin, Ethereum, or altcoins in general.
Ticker Status Classification
Each ticker is analyzed independently using the earlier directional logic. Its status is then determined as follows:
Full Bull : Ticker is trending up while dominance is declining or BTC is also rising.
Bullish : Ticker is trending up but not supported by broader bullish context.
Bearish : Ticker is trending down but without broader confirmation.
Full Bear : Ticker is trending down while dominance rises or BTC falls.
Neutral : No strong directional bias or conflicting context.
This classification reflects short-term momentum and macro alignment and is color-coded in the results table.
Table Display and Plotting
A configurable table is shown on the chart, which:
Displays the name and status of each selected ticker.
Optionally includes BTC, ETH, and market state.
Uses color-coding for intuitive interpretation.
Additionally, price changes from the daily open are plotted for each selected ticker, BTC, ETH, and combined dominance. These values are also labeled directly on the chart.
Labeling and UX Enhancements
Labels next to the current candle display price and percent change for each active ticker and for BTC, ETH, and combined dominance.
Labels update each bar, and old labels are deleted to avoid clutter.
Ticker names are dynamically shortened by stripping exchange prefixes.
How to Use This Indicator
This tool helps traders:
Spot early rotations between Bitcoin and altcoins.
Identify intraday momentum leaders or laggards.
Monitor which tickers align with or diverge from broader market trends.
Detect possible sentiment shifts based on dominance trends.
It is best used on lower to mid timeframes (15m–4h) to capture intraday to short-term shifts. Users should cross-reference with longer-term trend tools or structural indicators when making directional decisions.
Interpretation of Values
% Change : Measures intraday move from daily open. Strong positive/negative values may indicate breakouts or reversals.
Status : Describes directional strength relative to market conditions.
Market State : Gives a general bias toward BTC dominance, ETH strength, or altcoin momentum.
Limitations & Considerations
The indicator does not analyze liquidity or volume directly.
All logic is based on short-term movements and may produce false signals in ranging or low-volume environments.
Dominance calculations rely on external CRYPTOCAP indices, which may differ from exchange-specific flows.
Added Value Over Other Free Tools
Unlike basic % change tables or price overlays, this indicator:
Integrates dominance-based macro context into ticker evaluation.
Dynamically classifies market regimes (BTC season / Altseason).
Uses multi-factor logic to determine ticker bias, avoiding single-metric interpretation.
Displays consolidated information in a table and chart overlays for rapid assessment.
Canuck Trading IndicatorOverview
The Canuck Trading Indicator is a versatile, overlay-based technical analysis tool designed to assist traders in identifying potential trading opportunities across various timeframes and market conditions. By combining multiple technical indicators—such as RSI, Bollinger Bands, EMAs, VWAP, MACD, Stochastic RSI, ADX, HMA, and candlestick patterns—the indicator provides clear visual signals for bullish and bearish entries, breakouts, long-term trends, and options strategies like cash-secured puts, straddles/strangles, iron condors, and short squeezes. It also incorporates 20-day and 200-day SMAs to detect Golden/Death Crosses and price positioning relative to these moving averages. A dynamic table displays key metrics, and customizable alerts help traders stay informed of market conditions.
Key Features
Multi-Timeframe Adaptability: Automatically adjusts parameters (e.g., ATR multiplier, ADX period, HMA length) based on the chart's timeframe (minute, hourly, daily, weekly, monthly) for optimal performance.
Comprehensive Signal Generation: Identifies short-term entries, breakouts, long-term bullish trends, and options strategies using a combination of momentum, trend, volatility, and candlestick patterns.
Candlestick Pattern Detection: Recognizes bullish/bearish engulfing, hammer, shooting star, doji, and strong candles for precise entry/exit signals.
Moving Average Analysis: Plots 20-day and 200-day SMAs, detects Golden/Death Crosses, and evaluates price position relative to these averages.
Dynamic Table: Displays real-time metrics, including zone status (bullish, bearish, neutral), RSI, MACD, Stochastic RSI, short/long-term trends, candlestick patterns, ADX, ROC, VWAP slope, and MA positioning.
Customizable Alerts: Over 20 alert conditions for entries, exits, overbought/oversold warnings, and MA crosses, with actionable messages including ticker, price, and suggested strategies.
Visual Clarity: Uses distinct shapes, colors, and sizes to plot signals (e.g., green triangles for bullish entries, red triangles for bearish entries) and overlays key levels like EMA, VWAP, Bollinger Bands, support/resistance, and HMA.
Options Strategy Signals: Suggests opportunities for selling cash-secured puts, straddles/strangles, iron condors, and capitalizing on short squeezes.
How to Use
Add to Chart: Apply the indicator to any TradingView chart by selecting "Canuck Trading Indicator" from the Pine Script library.
Interpret Signals:
Bullish Signals: Green triangles (short-term entry), lime diamonds (breakout), blue circles (long-term entry).
Bearish Signals: Red triangles (short-term entry), maroon diamonds (breakout).
Options Strategies: Purple squares (cash-secured puts), yellow circles (straddles/strangles), orange crosses (iron condors), white arrows (short squeezes).
Exits: X-cross shapes in corresponding colors indicate exit signals.
Monitor: Gray circles suggest holding cash or monitoring for setups.
Review Table: Check the top-right table for real-time metrics, including zone status, RSI, MACD, trends, and MA positioning.
Set Alerts: Configure alerts for specific signals (e.g., "Short-Term Bullish Entry" or "Golden Cross") to receive notifications via TradingView.
Adjust Inputs: Customize input parameters (e.g., RSI period, EMA length, ATR period) to suit your trading style or market conditions.
Input Parameters
The indicator offers a wide range of customizable inputs to fine-tune its behavior:
RSI Period (default: 14): Length for RSI calculation.
RSI Bullish Low/High (default: 35/70): RSI thresholds for bullish signals.
RSI Bearish High (default: 65): RSI threshold for bearish signals.
EMA Period (default: 15): Main EMA length (15 for day trading, 50 for swing).
Short/Long EMA Length (default: 3/20): For momentum oscillator.
T3 Smoothing Length (default: 5): Smooths momentum signals.
Long-Term EMA/RSI Length (default: 20/15): For long-term trend analysis.
Support/Resistance Lookback (default: 5): Periods for support/resistance levels.
MACD Fast/Slow/Signal (default: 12/26/9): MACD parameters.
Bollinger Bands Period/StdDev (default: 15/2): BB settings.
Stochastic RSI Period/Smoothing (default: 14/3/3): Stochastic RSI settings.
Uptrend/Short-Term/Long-Term Lookback (default: 2/2/5): Candles for trend detection.
ATR Period (default: 14): For volatility and price targets.
VWAP Sensitivity (default: 0.1%): Threshold for VWAP-based signals.
Volume Oscillator Period (default: 14): For volume surge detection.
Pattern Detection Threshold (default: 0.3%): Sensitivity for candlestick patterns.
ROC Period (default: 3): Rate of change for momentum.
VWAP Slope Period (default: 5): For VWAP trend analysis.
TradingView Publishing Compliance
Originality: The Canuck Trading Indicator is an original script, combining multiple technical indicators and custom logic to provide unique trading signals. It does not replicate existing public scripts.
No Guaranteed Profits: This indicator is a tool for technical analysis and does not guarantee profits. Trading involves risks, and users should conduct their own research and risk management.
Clear Instructions: The description and usage guide are detailed and accessible, ensuring users understand how to apply the indicator effectively.
No External Dependencies: The script uses only built-in Pine Script functions (e.g., ta.rsi, ta.ema, ta.vwap) and requires no external libraries or data sources.
Performance: The script is optimized for performance, using efficient calculations and adaptive parameters to minimize lag on various timeframes.
Visual Clarity: Signals are plotted with distinct shapes and colors, and the table provides a concise summary of market conditions, enhancing usability.
Limitations and Risks
Market Conditions: The indicator may generate false signals in choppy or low-liquidity markets. Always confirm signals with additional analysis.
Timeframe Sensitivity: Performance varies by timeframe; test settings on your preferred chart (e.g., 5-minute for day trading, daily for swing trading).
Risk Management: Use stop-losses and position sizing to manage risk, as suggested in alert messages (e.g., "Stop -20%").
Options Trading: Options strategies (e.g., straddles, iron condors) carry unique risks; consult a financial advisor before trading.
Feedback and Support
For questions, suggestions, or bug reports, please leave a comment on the TradingView script page or contact the author via TradingView. Your feedback helps improve the indicator for the community.
Disclaimer
The Canuck Trading Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
Asia Session Reversal Strategy GOLD (Full Version)📈 Asia Session Reversal Strategy (Gold/XAUUSD)
This indicator identifies high-probability reversal trades during the second hour of the Asia session (01:00–02:00 UTC) based on 30-minute candle bias. It:
Detects initial directional push and signals reversal trades on the 1-minute chart
Plots entry, stop-loss, and take-profit levels using a 3:1 reward-to-risk ratio
Includes real-time PnL tracking, daily auto-reset, and alert notifications for BUY/SELL setups
Ideal for scalpers and intraday traders focusing on Gold during consistent, high-liquidity session windows.
[blackcat] L2 Multi-Level Price Condition TrackerOVERVIEW
The L2 Multi-Level Price Condition Tracker represents an innovative approach to analyzing financial markets by simultaneously monitoring multiple price levels, thus providing traders with a holistic view of market dynamics. By combining dynamic calculations based on moving averages and price deviations, this tool aims to deliver precise and actionable insights into potential entry and exit points. It leverages sophisticated statistical measures to identify key thresholds that signify shifts in market sentiment, thereby aiding traders in making well-informed decisions. 🎯
Key benefits encompass:
• Comprehensive calculation of midpoints and average prices indicating short-term trend directions.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by precise condition evaluations.
TECHNICAL ANALYSIS COMPONENTS
📉 Midpoint Calculations:
Computes central reference points derived from high-low ranges establishing baseline supports/resistances.
Utilizes Simple Moving Averages (SMAs) along with standardized deviation formulas smoothing out volatility while preserving long-term trends accurately.
Facilitates identification of directional biases reflecting underlying market forces dynamically.
🕵️♂️ Advanced Price Level Detection:
Derives upper/lower bounds adjusting sensitivities adaptively responding to changing conditions flexibly.
Employs proprietary logic distinguishing between bullish/bearish sentiments promptly signaling transitions effectively.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy robustly.
🎥 Dynamic Signal Generation:
Detects crossovers indicating dominance shifts between buyers/sellers promptly triggering timely alerts.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations systematically.
Supports adaptive thresholds tuning sensitivities based on evolving market conditions flexibly accommodating varying scenarios.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages alongside standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time midpoint markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively highlighting key activations clearly.
Background shading emphasizing proximity to crucial threshold activations enhancing visibility focusing attention on vital signals promptly.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals assessing concurrent market sentiment factors.
Validate entry decisions considering alignment between calculated midpoints and broader trend directions ensuring coherence.
Monitor cumulative breaches signifying potential trend reversals executing partial/total closes contingent upon predetermined loss limits preserving capital efficiently.
🚫 Exit Mechanisms:
Trigger exits upon hitting predefined thresholds derived from historical analyses promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement implementing corrective actions iteratively enhancing performance metrics steadily.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Lookback Period: Governs responsiveness versus stability balancing sensitivity/stability governing moving averages aligning with preferred granularity.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately tailoring strategies accordingly.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts evaluating adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity sustaining balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches preserving capital efficiently.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines managing exposures prudently.
Mandatorily apply trailing stop-loss orders conforming to script outputs enforcing discipline rigorously preventing adverse consequences.
Allocate positions proportionately relative to available capital reserves conducting periodic reviews gauging effectiveness continuously identifying improvement opportunities steadily.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously preparing contingency plans proactively mitigating risks effectively.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically implementing corrective actions reliably.
Prepare proactive responses amid adverse movements ensuring seamless functionality amidst fluctuating conditions fortifying resilience against anomalies robustly.
PERFORMANCE MONITORING METRICS
🔍 Evaluation Criteria:
Assess win percentages consistently across diverse trading instruments gauging reliability measuring profitability efficiency accurately evaluating downside risks comprehensively uncovering systematic biases potentially skewing outcomes.
Calculate average profit ratios per successful execution benchmarking actual vs expected performances documenting results meticulously tracking progress dynamically addressing identified shortcomings proactively fostering continuous improvements.
📈 Historical Data Analysis Tools:
Maintain detailed logs capturing every triggered event recording realized profits/losses comparing simulated projections accurately identifying discrepancies warranting investigation implementing iterative refinements steadily enhancing performance metrics progressively.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily addressing identified shortcomings proactively fostering continuous enhancements dynamically improving robustness resiliently.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes enhancing signal integrity excluding low-liquidity assets prone to erratic movements effectively.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities introducing buffer intervals safeguarding major news/event impacts mitigating distortions seamlessly verifying reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably.
💡 Effective Resolution Pathways:
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently recalibrating parameters periodically adapting strategies flexibly responding appropriately amidst varying conditions dynamically improving robustness resiliently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably bolstering overall efficacy systematically addressing identified shortcomings dynamically fostering continuous advancements.
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights regarding multi-level price condition-based trading methodologies! ✨
[blackcat] L1 Net Volume DifferenceOVERVIEW
The L1 Net Volume Difference indicator serves as an advanced analytical tool designed to provide traders with deep insights into market sentiment by examining the differential between buying and selling volumes over precise timeframes. By leveraging these volume dynamics, it helps identify trends and potential reversal points more accurately, thereby supporting well-informed decision-making processes. The key focus lies in dissecting intraday changes that reflect short-term market behavior, offering critical input for both swing and day traders alike. 📊
Key benefits encompass:
• Precise calculation of net volume differences grounded in real-time data.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by dynamic volume shifts.
TECHNICAL ANALYSIS COMPONENTS
📉 Volume Accumulation Mechanisms:
Monitors cumulative buy/sell volumes derived from comparative closing prices.
Periodically resets accumulation counters aligning with predefined intervals (e.g., 5-minute bars).
Facilitates identification of directional biases reflecting underlying market forces accurately.
🕵️♂️ Sentiment Detection Algorithms:
Employs proprietary logic distinguishing between bullish/bearish sentiments dynamically.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
Supports adaptive thresholds adjusting sensitivities based on changing market conditions flexibly.
🎯 Dynamic Signal Generation:
Detects transitions indicating dominance shifts between buyers/sellers promptly.
Triggers timely alerts enabling swift reactions to evolving market dynamics effectively.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages along with standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time net volume markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between net volume readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Reset Interval: Governs responsiveness versus stability balancing sensitivity/stability.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights about volume-based trading methodologies! ✨
DXY Monthly Return (+3M Lead)This indicator calculates the rolling monthly return (based on 21 trading days) for the U.S. Dollar Index (DXY), applying a +3-month forward shift (lead) to the series.
It is designed to help visualize the leading effect of USD strength or weakness on other macro-sensitive assets — particularly Bitcoin and crypto markets, which often react to changes in global dollar liquidity with a lag of approximately 10 weeks.
Note: This script does not invert the values directly. To match the inverted Y-axis visual used by Steno Research — where negative USD returns are displayed at the top — simply right-click the Y-axis in the chart panel and select “Invert Scale.”
💡 Use this tool for macro trend analysis, early crypto signal generation, or studying inverse correlations between USD and risk assets.
Source logic: Steno Research, Bloomberg, Macrobond.
The ICT Ultimate Grid | MarketMaverisk GroupThe ICT Ultimate Grid | MarketMaverisk Group
This script is a fully customizable checklist based on ICT (Inner Circle Trader) concepts. It helps traders validate entry conditions across three timeframes:
LTP (Long-Term), ITP (Intermediate-Term), and STP (Short-Term).
⸻
✅ Purpose & Utility:
Instead of generating simple buy/sell signals, this tool assists traders in making structured, confirmation-based decisions. It presents a visual checklist with 11 customizable columns—each can be individually toggled for each timeframe and displays ✅ or ❌ confirmation status.
⸻
🧠 Confirmation Structure:
The checklist covers the following core elements from the ICT methodology:
• ERL⇔IRL and IRL⇔ERL (presented as special confirmations below the table)
• DOL – Drow On liqudity Level
• PD – permium or discuant
• SMT – Smart Money Trap / Inter-market Divergence
• CSD – Change in State of dlivery
• MSS – Market Structure Shift
• MMXM – Market maker (buy or sell) model
• FVG – Fair Value Gap
• OB – Order Block
• BRK.B – breker Block
Each item can be enabled or disabled for LTP, ITP, and STP individually.
⸻
📊 Visual Design:
• Clean, compact table displayed in the top-right corner of the chart.
• Clear color scheme (✅ Green = Confirmed, ❌ Red = Not Confirmed, Grey = Hidden/Disabled).
• Timeframes are stacked row-wise (LTP, ITP, STP).
• Inputs allow fine-grained control over what elements are shown in each timeframe.
• Additional rows are used to confirm:
• HTF Key Level
• Direction: Reversal ↩️ or Continuation 🔂
• Bias: Bullish 🔼 or Bearish 🔽
⸻
📈 Use Case:
This tool is ideal for traders who follow:
• ICT-based trading approaches
• Market structure + Liquidity analysis
• Day trading, scalping, or swing setups
• Confirmation-based entries after higher-timeframe alignment
⸻
⚙️ Recommended Timeframe Settings:
• LTP = D1 or 4H
• ITP = 1H or 15min
• STP = 5min or 3min or 1min
• Session time: Best used between 02:00 and 05:00 on london killzone & 08:00 and 12:00 on New york killzone in New York timezone (UTC -5)
(you can customize this in strategy version)
⸻
🛠 Technical Note:
This version is an indicator and does not generate signals or alerts by itself. For full automation, a strategy version is also available upon request.
⸻
Let me know if you’d like me to also write a “strategy description” or help you prepare the public chart layout 📊 to make your publish clean and attractivE
[blackcat] L2 Z-Score of PriceOVERVIEW
The L2 Z-Score of Price indicator offers traders an insightful perspective into how current prices diverge from their historical norms through advanced statistical measures. By leveraging Z-scores, it provides a robust framework for identifying potential reversals in financial markets. The Z-score quantifies the number of standard deviations that a data point lies away from the mean, thus serving as a critical metric for recognizing overbought or oversold conditions. 🎯
Key benefits encompass:
• Precise calculation of Z-scores reflecting true price deviations.
• Interactive plotting features enhancing visual clarity.
• Real-time generation of buy/sell signals based on crossover events.
STATISTICAL ANALYSIS COMPONENTS
📉 Mean Calculation:
Utilizes Simple Moving Averages (SMAs) to establish baseline price references.
Provides smooth representations filtering short-term noise preserving long-term trends.
Fundamental for deriving subsequent deviation metrics accurately.
📈 Standard Deviation Measurement:
Quantifies dispersion around established means revealing underlying variability.
Crucial for assessing potential volatility levels dynamically adapting strategies accordingly.
Facilitates precise Z-score derivations ensuring statistical rigor.
🕵️♂️ Z-SCORE DETECTION:
Measures standardized distances indicating relative positions within distributions.
Helps pinpoint extreme conditions signaling impending reversals proactively.
Enables early identification of trend exhaustion phases prompting timely actions.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Integrates SMAs along with standardized deviation formulas generating precise Z-scores.
Employs Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
🖱️ User Interface Elements:
Dedicated plots displaying real-time Z-score markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between Z-score readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Length: Governs responsiveness versus smoothing trade-offs balancing sensitivity/stability.
Price Source: Dictates primary data series driving Z-score computations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
[blackcat] L3 Mean Reversion ATR Stop Loss OVERVIEW
The L3 Mean Reversion ATR Stop Loss indicator is meticulously crafted to empower traders by offering statistically-driven stop-loss levels that adapt seamlessly to evolving market dynamics. By harmoniously blending mean reversion concepts with Advanced True Range (ATR) metrics, it delivers a robust framework for managing risks more effectively. 🌐 The primary objective is to furnish traders with intelligent exit points grounded in both short-term volatility assessments and long-term trend evaluations.
Key highlights encompass:
• Dynamic calculation of Z-scores to evaluate deviations from established means
• Adaptive stop-loss pricing leveraging real-time ATR measurements
• Clear visual cues enabling swift decision-making processes
TECHNICAL ANALYSIS COMPONENTS
📉 Z-SCORE CALCULATION
Measures how many standard deviations an asset's current price lies away from its average
Facilitates identification of extreme conditions indicative of impending reversals
Utilizes simple moving averages and standard deviation computations
📊 STANDARD DEVIATION MEASUREMENT
Quantifies dispersion of closing prices around the mean
Provides insights into underlying price distribution characteristics
Crucial for assessing potential volatility levels accurately
🕵️♂️ ADAPTIVE STOP-LOSS DETECTION
Employs ATR as a proxy for prevailing market volatility
Modulates stop-loss placements dynamically responding to shifting trends
Ensures consistent adherence to predetermined risk management protocols
INDICATOR FUNCTIONALITY
🔢 Core Algorithms
Integrate Smooth Moving Averages (SMAs) alongside standardized deviation formulas
Generate precise Z-scores reflecting true price deviations
Leverage ATR-derived multipliers for fine-grained stop-loss adjustments
🖱️ User Interface Elements
Interactive plots displaying real-time stop-loss markers
Context-sensitive color coding enhancing readability
Background shading indicating proximity to stop-level activations
STRATEGY IMPLEMENTATION
✅ Entry Conditions
Confirm bullish/bearish setups validated through multiple confirmatory signals
Ensure alignment between Z-score readings and broader trend directions
Validate entry decisions considering concurrent market sentiment factors
🚫 Exit Mechanisms
Trigger exits upon hitting predefined ATR-based stop-loss thresholds
Monitor continuous breaches signifying potential trend reversals
Execute partial/total closes contingent upon cumulative loss limits
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines
Period Length: Governs responsiveness versus smoothing trade-offs
ATR Length: Dictates the temporal scope for volatility analysis
Stop Loss ATR Multiplier: Tunes sensitivity towards stop-trigger activations
💬 Customization Recommendations
Commence with baseline defaults; iteratively refine parameters
Evaluate impacts independently prior to combined adjustments
Prioritize minimizing erroneous trigger occurrences first
Sustain balanced risk-reward profiles irrespective of chosen settings
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques
Enforce strict compliance with pre-defined maximum leverage constraints
Mandatorily apply trailing stop-loss orders conforming to script outputs
Allocate positions proportionately relative to available capital reserves
Conduct periodic reviews gauging strategy effectiveness rigorously
⚠️ Potential Pitfalls & Solutions
Address frequent violations arising during heightened volatility phases
Manage false alerts warranting manual interventions judiciously
Prepare contingency plans mitigating margin call possibilities
Continuously assess automated system reliability amidst fluctuating conditions
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics
Assess win percentages consistently across diverse trading instruments
Calculate average profit ratios per successful execution
Measure peak drawdown durations alongside associated magnitudes
Analyze signal generation frequencies revealing hidden patterns
📈 Historical Data Analysis Tools
Maintain comprehensive records capturing every triggered event
Compare realized profits/losses against backtested simulations
Identify recurrent systematic errors demanding corrective actions
Implement iterative refinements bolstering overall efficacy steadily
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges
Unpredictable behaviors emerging within thinly traded markets
Latency issues manifesting during abrupt price fluctuations
Overfitted models yielding suboptimal results post-extensive tuning
Inaccuracies stemming from incomplete or delayed data inputs
💡 Effective Resolution Pathways
Exclude low-liquidity assets prone to erratic movements
Introduce buffer intervals safeguarding major news/event impacts
Limit ongoing optimization attempts preventing model degradation
Verify seamless connectivity ensuring uninterrupted data flows
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
A heartfelt acknowledgment extends to all developers contributing invaluable insights about adaptive stop-loss strategies using statistical measures! ✨
CVD Divergenz System – modular with Exchange + LabelsA smart volume-based strategy tool using CVD divergence, ATR-based risk management, and Open Interest filters — now with visual chart labels and exchange switching.
Designed for crypto traders who want precise entry signals, volume insight, and a clean UI.
🔍 Key Features:
✅ CVD Divergence Detection
Automatically detects bullish or bearish divergences between price and cumulative delta (CVD)
✅ Open Interest Logic (Simulated)
Signals are only valid when OI is rising – otherwise a warning is issued
✅ ATR-Based Entry, Stop & Target Zones
Auto-calculated based on your chosen R multiple (e.g., 1.5R), plotted in the chart
✅ Visual Dashboard Panel (table)
Compact panel with CVD, OI change, ATR, signal status, and selected exchange — always visible in top-right
✅ Exchange Selector + Fallback to Binance
Choose between Binance, Bybit, Bitget, or Coinbase — if data is unavailable, Binance is used automatically
✅ Modular Chart Labels
Optionally display 📈 LONG, 📉 SHORT or ⚠️ WARNING labels directly on the chart with a toggle
✅ Alerts Built-In
Get notified instantly when a setup triggers (long, short, or warning) — works with app, popup, or webhook
✅ Fully Modular Controls
Enable or disable the dashboard, trade zones, and labels via simple checkboxes
⚠️ Technical Notes:
CVD is calculated from delta volume (volume * sign(close - open)) — not true order flow
Open Interest is simulated using volume as a placeholder (due to Pine Script limitations)
Best suited for 5–30min timeframes on crypto futures pairs like BTCUSDT, ETHUSDT, etc.
💡 Pro Tips:
Use near key support/resistance zones or liquidity levels
Combine with price action and higher timeframe confluence
Alerts work best with "Once Per Bar Close" trigger setting
📈 Built to support faster decisions, cleaner setups, and institutional-level insights — all in one tool.
Bloomberg Financial Conditions Index (Proxy)The Bloomberg Financial Conditions Index (BFCI): A Proxy Implementation
Financial conditions indices (FCIs) have become essential tools for economists, policymakers, and market participants seeking to quantify and monitor the overall state of financial markets. Among these measures, the Bloomberg Financial Conditions Index (BFCI) has emerged as a particularly influential metric. Originally developed by Bloomberg L.P., the BFCI provides a comprehensive assessment of stress or ease in financial markets by aggregating various market-based indicators into a single, standardized value (Hatzius et al., 2010).
The original Bloomberg Financial Conditions Index synthesizes approximately 50 different financial market variables, including money market indicators, bond market spreads, equity market valuations, and volatility measures. These variables are normalized using a Z-score methodology, weighted according to their relative importance to overall financial conditions, and then aggregated to produce a composite index (Carlson et al., 2014). The resulting measure is centered around zero, with positive values indicating accommodative financial conditions and negative values representing tighter conditions relative to historical norms.
As Angelopoulou et al. (2014) note, financial conditions indices like the BFCI serve as forward-looking indicators that can signal potential economic developments before they manifest in traditional macroeconomic data. Research by Adrian et al. (2019) demonstrates that deteriorating financial conditions, as measured by indices such as the BFCI, often precede economic downturns by several months, making these indices valuable tools for predicting changes in economic activity.
Proxy Implementation Approach
The implementation presented in this Pine Script indicator represents a proxy of the original Bloomberg Financial Conditions Index, attempting to capture its essential features while acknowledging several significant constraints. Most critically, while the original BFCI incorporates approximately 50 financial variables, this proxy version utilizes only six key market components due to data accessibility limitations within the TradingView platform.
These components include:
Equity market performance (using SPY as a proxy for S&P 500)
Bond market yields (using TLT as a proxy for 20+ year Treasury yields)
Credit spreads (using the ratio between LQD and HYG as a proxy for investment-grade to high-yield spreads)
Market volatility (using VIX directly)
Short-term liquidity conditions (using SHY relative to equity prices as a proxy)
Each component is transformed into a Z-score based on log returns, weighted according to approximated importance (with weights derived from literature on financial conditions indices by Brave and Butters, 2011), and aggregated into a composite measure.
Differences from the Original BFCI
The methodology employed in this proxy differs from the original BFCI in several important ways. First, the variable selection is necessarily limited compared to Bloomberg's comprehensive approach. Second, the proxy relies on ETFs and publicly available indices rather than direct market rates and spreads used in the original. Third, the weighting scheme, while informed by academic literature, is simplified compared to Bloomberg's proprietary methodology, which may employ more sophisticated statistical techniques such as principal component analysis (Kliesen et al., 2012).
These differences mean that while the proxy BFCI captures the general direction and magnitude of financial conditions, it may not perfectly replicate the precision or sensitivity of the original index. As Aramonte et al. (2013) suggest, simplified proxies of financial conditions indices typically capture broad movements in financial conditions but may miss nuanced shifts in specific market segments that more comprehensive indices detect.
Practical Applications and Limitations
Despite these limitations, research by Arregui et al. (2018) indicates that even simplified financial conditions indices constructed from a limited set of variables can provide valuable signals about market stress and future economic activity. The proxy BFCI implemented here still offers significant insight into the relative ease or tightness of financial conditions, particularly during periods of market stress when correlations among financial variables tend to increase (Rey, 2015).
In practical applications, users should interpret this proxy BFCI as a directional indicator rather than an exact replication of Bloomberg's proprietary index. When the index moves substantially into negative territory, it suggests deteriorating financial conditions that may precede economic weakness. Conversely, strongly positive readings indicate unusually accommodative financial conditions that might support economic expansion but potentially also signal excessive risk-taking behavior in markets (López-Salido et al., 2017).
The visual implementation employs a color gradient system that enhances interpretation, with blue representing neutral conditions, green indicating accommodative conditions, and red signaling tightening conditions—a design choice informed by research on optimal data visualization in financial contexts (Few, 2009).
References
Adrian, T., Boyarchenko, N. and Giannone, D. (2019) 'Vulnerable Growth', American Economic Review, 109(4), pp. 1263-1289.
Angelopoulou, E., Balfoussia, H. and Gibson, H. (2014) 'Building a financial conditions index for the euro area and selected euro area countries: what does it tell us about the crisis?', Economic Modelling, 38, pp. 392-403.
Aramonte, S., Rosen, S. and Schindler, J. (2013) 'Assessing and Combining Financial Conditions Indexes', Finance and Economics Discussion Series, Federal Reserve Board, Washington, D.C.
Arregui, N., Elekdag, S., Gelos, G., Lafarguette, R. and Seneviratne, D. (2018) 'Can Countries Manage Their Financial Conditions Amid Globalization?', IMF Working Paper No. 18/15.
Brave, S. and Butters, R. (2011) 'Monitoring financial stability: A financial conditions index approach', Economic Perspectives, Federal Reserve Bank of Chicago, 35(1), pp. 22-43.
Carlson, M., Lewis, K. and Nelson, W. (2014) 'Using policy intervention to identify financial stress', International Journal of Finance & Economics, 19(1), pp. 59-72.
Few, S. (2009) Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press, Oakland, CA.
Hatzius, J., Hooper, P., Mishkin, F., Schoenholtz, K. and Watson, M. (2010) 'Financial Conditions Indexes: A Fresh Look after the Financial Crisis', NBER Working Paper No. 16150.
Kliesen, K., Owyang, M. and Vermann, E. (2012) 'Disentangling Diverse Measures: A Survey of Financial Stress Indexes', Federal Reserve Bank of St. Louis Review, 94(5), pp. 369-397.
López-Salido, D., Stein, J. and Zakrajšek, E. (2017) 'Credit-Market Sentiment and the Business Cycle', The Quarterly Journal of Economics, 132(3), pp. 1373-1426.
Rey, H. (2015) 'Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence', NBER Working Paper No. 21162.
Dynamic Volume Clusters with Retest Signals (Zeiierman)█ Overview
The Dynamic Volume Clusters with Retest Signals indicator is designed to detect key Volume Clusters and provide Retest Signals. This tool is specifically engineered for traders looking to capitalize on volume-based trends, reversals, and key price retest points.
The indicator seamlessly combines volume analysis, dynamic cluster calculations, and retest signal logic to present a comprehensive trading framework. It adapts to market conditions, identifying clusters of volume activity and signaling when the price retests critical zones.
█ How It Works
⚪ Volume Cluster Detection
The indicator dynamically calculates volume clusters by analyzing the highest and lowest price points within a specified lookback period.
Cluster Logic:
Bright Lines (Strong Red/Green):
These indicate that the price has frequently revisited these levels, creating a dense cluster.
Such areas serve as support or resistance, where significant historical trading has occurred, often acting as barriers to price movement.
Traders should consider these levels as potential reversal zones or consolidation points.
Faded or Darker Lines:
These lines indicate areas where the price has less historical activity, suggesting weaker clustering.
These zones have less market memory and are more likely to break, supporting trend continuation and rapid price movement.
⚪ Candle Color Logic (Market Memory)
Blue Candles (High Cluster Density):
Candles turn blue when the price has revisited a particular area many times.
This signals a highly clustered zone, likely to act as a barrier, creating consolidation or range phases.
These areas indicate strong market memory, potentially rejecting price attempts to break through.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these dense clusters, the candles turn green (bullish) or red (bearish).
This suggests the price has moved into a less clustered territory, where the path forward is clearer and trends are likely to extend without immediate resistance.
⚪ Retest Signal Logic
The indicator identifies critical retest points where the price crosses a cluster boundary and then reverses. These points are essential for traders looking to catch continuation or reversal setups.
⚪ Dynamic Price Clustering
The indicator dynamically adapts the clustering logic based on price movement and volume shifts.
Uses a dynamic moving average (VPMA) to maintain adaptive cluster levels.
Integrates a Kalman Filter for smoothing, reducing noise, and improving trend clarity.
Automatically updates as new data is received, keeping the clusters relevant in real-time.
█ How to Use
⚪ Trend Following & Reversal Detection
Use Retest signals to identify potential trend continuation or reversal points.
⚪ Trading Volume Clusters and Market Memory
Identify Key Zones:
Focus on bright, saturated cluster lines (strong red or green) as they indicate high market memory, where price has spent significant time in the past.
These zones are likely to exhibit a more choppy market. Apply range or mean reversion strategies.
Spot Potential Breakouts:
Faded or darker cluster lines indicate areas of low market memory, where the price has moved quickly and spent less time.
Use these areas to identify possible trend setups, as they represent lower resistance to price movement.
⚪ Interpreting Candle Colors for Market Phases
Blue Candles (High Cluster Density):
When candles turn blue, it signals that the price has revisited this area multiple times, creating a dense cluster.
These zones often trap price movement, leading to consolidations or range phases.
Use these areas as caution zones, where price can slow down or reverse.
Green or Red Candles (Low Cluster Density):
Once the price breaks out of these clustered zones, the candles turn green (bullish) or red (bearish), indicating lower market memory.
This signals a trend initiation with less immediate resistance, ideal for momentum and breakout trades.
Use these signals to identify emerging trends and ride the momentum.
█ Settings
Range Lookback Period: Sets the number of bars for calculating the range.
Zone Width (% of Range): Determines how wide the volume clusters are relative to the calculated range.
Volume Line Colors: Customize the appearance of bullish and bearish lines.
Retest Signals: Toggle the appearance of Triangle Up/Down retest markers.
Minimum Bars for Retest: Define the minimum number of bars required before a retest is valid.
Maximum Bars for Retest: Set the maximum number of bars within which a retest can occur.
Price Cluster Period: Adjusts the sensitivity of the dynamic clustering logic.
Cluster Confirmation: Controls how tightly the clusters respond to price action.
Price Cluster Start/Peak: Sets the minimum and maximum touches required to fully form a cluster.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
SSRO Z-ScoreSSRO Z-Score Indicator — Description
What it does:
This indicator measures the Stablecoin Supply Ratio (SSR) relative to Bitcoin’s market cap and calculates a normalized Z-Score of this ratio to help identify potential market tops and bottoms in the crypto market.
How it works:
The Stablecoin Supply Ratio (SSR) is calculated by dividing Bitcoin’s market capitalization by the combined market capitalization of major stablecoins (USDT, USDC, TUSD, DAI, FRAX).
The SSR is then smoothed over a user-defined lookback period to reduce noise.
A Z-Score is computed by normalizing the SSR over a specified moving window, which shows how far the current SSR deviates from its historical average in terms of standard deviations.
This Z-Score is further smoothed using an exponential moving average (EMA) to filter short-term volatility.
How to read the Z-Score:
Z-Score = 0: SSR is at its historical average.
Z-Score > 0: SSR is above average, indicating Bitcoin’s market cap is relatively high compared to stablecoin supply, potentially signaling bullish market conditions.
Z-Score < 0: SSR is below average, indicating stablecoin supply is high relative to Bitcoin’s market cap, possibly signaling bearish pressure or increased liquidity waiting to enter the market.
Upper and Lower Bands: These user-defined levels (e.g., +2 and -2) represent thresholds for extreme conditions. Values above the upper band may indicate overbought or overheated market conditions, while values below the lower band may indicate oversold or undervalued conditions.
Additional Features:
A dynamic table displays a linear scaled Z-Score alongside the main plot, clamped between -2 and +2 relative to the upper and lower bands for intuitive interpretation.
Usage Tips:
Combine the SSRO Z-Score with other technical indicators or volume analysis for more reliable signals.
Look for divergence between price and Z-Score extremes as potential reversal signals.
Velez Price Action Signals (with 20 & 200 SMA)Velez Price Action Signals – With 20 & 200 SMA Overlay
This TradingView Pine Script is a clean and powerful reversal signal tool inspired by Oliver Velez’s price action philosophy, enhanced with trend context via two Simple Moving Averages.
🔍 Signal Logic
Buy Signal:
Current candle sweeps below the previous 5-bar low (liquidity grab).
Candle is bullish (close > open).
The lower wick is significantly larger than the body (e.g. ratio > 1.5).
Sell Signal:
Current candle sweeps above the previous 5-bar high.
Candle is bearish (close < open).
The upper wick is significantly larger than the body.
Signals appear as BUY/SELL labels on the chart (non-repainting).
LULD Bands & Trading Halt Detector [Volume Vigilante]📖 LULD Bands & Trading Halt Detector
This advanced tool visualizes official Limit Up / Limit Down (LULD) price bands and detects regulatory trading halts and resumptions based on SEC and NASDAQ rules. It is engineered for high accuracy by anchoring all calculations to the 1-minute timeframe, ensuring reliable signals across any chart resolution.
📌 What Does This Script Do?
- Draws real-time LULD price band estimations and optional buffer (caution) zones directly on the chart.
- Detects trading halt resumptions by monitoring time gaps between candles and other regulatory criteria. (Note: Due to Pine Script limitations, halts cannot be detected in real-time, only resumptions after they occur.)
- Triggers real-time alerts for:
- Trading Resumptions (Limit Up & Limit Down)
- LULD Zone Entries (Caution Zone)
- Band Breaches (Limit Up and Limit Down)
- Plots historical halt resumption markers to analyse past events.
📐 How It Works:
- Implements official SEC/NASDAQ LULD rules for Tier 1 and Tier 2 securities.
- Applies special band adjustments for the final 25 minutes of trading (after 3:35 PM ET).
- Anchors all logic to the 1-minute timeframe for precise calculations, even on higher timeframe charts.
- Includes adjustable volume and volatility filters to eliminate false signals (ghost halts) on low-- liquidity assets, especially Tier 2 securities when TradingView fails to print candles.
⚙️ How to Use It:
1.) Apply the script to any asset or timeframe.
2.) Adjust Volume and Volatility Filters to reduce noise. (Recommended: 500,000+ volume, 10%+ volatility.)
3.) Enable or disable visual components like bands, buffer zones, and halt resumption labels.
4.) Configure alerts directly from the script settings panel.
5.) Apply alerts to individual assets via "Add Alert On..." or to entire watchlists using "Add Alert on the List."
🧩 What Makes This Script Unique?
- True 1-Minute Anchored Calculations: Ensures alerts and visuals match official trading halt criteria regardless of chart timeframe.
- Customisable Buffered Zones: Visualise proximity to regulatory price limits and avoid volatility traps.
- Combines halt resumption detection, limit up/down band visualisation, and real-time alerts into one clean, modular tool.
📚 Disclaimer:
This script is for educational purposes only and does not constitute financial advice. Use at your own discretion and consult a licensed financial advisor before making trading decisions based on it.
Official Resources:
- NASDAQ LULD Regulations (FAQ):
www.nasdaqtrader.com
Current Nasdaq Trading Halts:
www.nasdaqtrader.com
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.
