Sun Moon Conjunctions Trine Oppositions 2025this script is an astrological tool designed to overlay significant Sun-Moon aspect events for 2025 on a Bitcoin chart. It highlights key lunar phases and aspects—Conjunctions (New Moon) in blue, Squares in red, Oppositions (Full Moon) in purple, and Trines in green—using background colors and labeled markers. Users can toggle visibility for each aspect type and adjust label sizes via customizable inputs. The script accurately marks events from January through December 2025, with labels appearing once per event, making it a valuable resource for exploring potential correlations between lunar cycles and Bitcoin price movements.
Cerca negli script per "bitcoin"
Z-Score Normalized Volatility IndicesVolatility is one of the most important measures in financial markets, reflecting the extent of variation in asset prices over time. It is commonly viewed as a risk indicator, with higher volatility signifying greater uncertainty and potential for price swings, which can affect investment decisions. Understanding volatility and its dynamics is crucial for risk management and forecasting in both traditional and alternative asset classes.
Z-Score Normalization in Volatility Analysis
The Z-score is a statistical tool that quantifies how many standard deviations a given data point is from the mean of the dataset. It is calculated as:
Z = \frac{X - \mu}{\sigma}
Where X is the value of the data point, \mu is the mean of the dataset, and \sigma is the standard deviation of the dataset. In the context of volatility indices, the Z-score allows for the normalization of these values, enabling their comparison regardless of the original scale. This is particularly useful when analyzing volatility across multiple assets or asset classes.
This script utilizes the Z-score to normalize various volatility indices:
1. VIX (CBOE Volatility Index): A widely used indicator that measures the implied volatility of S&P 500 options. It is considered a barometer of market fear and uncertainty (Whaley, 2000).
2. VIX3M: Represents the 3-month implied volatility of the S&P 500 options, providing insight into medium-term volatility expectations.
3. VIX9D: The implied volatility for a 9-day S&P 500 options contract, which reflects short-term volatility expectations.
4. VVIX: The volatility of the VIX itself, which measures the uncertainty in the expectations of future volatility.
5. VXN: The Nasdaq-100 volatility index, representing implied volatility in the Nasdaq-100 options.
6. RVX: The Russell 2000 volatility index, tracking the implied volatility of options on the Russell 2000 Index.
7. VXD: Volatility for the Dow Jones Industrial Average.
8. MOVE: The implied volatility index for U.S. Treasury bonds, offering insight into expectations for interest rate volatility.
9. BVIX: Volatility of Bitcoin options, a useful indicator for understanding the risk in the cryptocurrency market.
10. GVZ: Volatility index for gold futures, reflecting the risk perception of gold prices.
11. OVX: Measures implied volatility for crude oil futures.
Volatility Clustering and Z-Score
The concept of volatility clustering—where high volatility tends to be followed by more high volatility—is well documented in financial literature. This phenomenon is fundamental in volatility modeling and highlights the persistence of periods of heightened market uncertainty (Bollerslev, 1986).
Moreover, studies by Andersen et al. (2012) explore how implied volatility indices, like the VIX, serve as predictors for future realized volatility, underlining the relationship between expected volatility and actual market behavior. The Z-score normalization process helps in making volatility data comparable across different asset classes, enabling more effective decision-making in volatility-based strategies.
Applications in Trading and Risk Management
By using Z-score normalization, traders can more easily assess deviations from the mean in volatility, helping to identify periods when volatility is unusually high or low. This can be used to adjust risk exposure or to implement volatility-based trading strategies, such as mean reversion strategies. Research suggests that volatility mean-reversion is a reliable pattern that can be exploited for profit (Christensen & Prabhala, 1998).
References:
• Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2012). Realized volatility and correlation dynamics: A long-run approach. Journal of Financial Economics, 104(3), 385-406.
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christensen, B. J., & Prabhala, N. R. (1998). The relation between implied and realized volatility. Journal of Financial Economics, 50(2), 125-150.
• Whaley, R. E. (2000). Derivatives on market volatility and the VIX index. Journal of Derivatives, 8(1), 71-84.
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
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Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
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Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
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Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
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Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
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Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
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Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
Risk-On / Risk-Off ScoreRisk-On / Risk-Off Score (Macro Sentiment Indicator)
This indicator calculates a custom Risk-On / Risk-Off Score to objectively assess the current market risk sentiment using a carefully selected basket of macroeconomic assets and intermarket relationships.
🧠 What does this indicator do?
The score is based on 14 key components grouped into three categories:
🟢 Risk-On Assets (rising = appetite for risk)
(+1 if performance over X days is positive, otherwise –1)
NASDAQ 100 (NAS100USD)
S&P 500 (SPX)
Bitcoin (BTCUSD)
Copper (HG1!)
WTI Crude Oil (CLK2025)
🔴 Risk-Off Assets (rising = flight to safety)
(–1 if performance is positive, otherwise +1)
Gold (XAUUSD)
US Treasury Bonds (TLT ETF) (TLT)
US Dollar Index (DXY)
USD/CHF
USD/JPY
US 10Y Yields (US10Y) (yields are interpreted inversely)
⚖️ Risk Spreads / Relative Indicators
(+1 if rising, –1 if falling)
Copper/Gold Ratio → HG1! / XAUUSD
NASDAQ/VIX Ratio → NAS100USD / VIX
HYG/TLT Ratio → HYG / TLT
📏 Score Calculation
Total score = sum of all components
Range: from –14 (extreme Risk-Off) to +14 (strong Risk-On)
Color-coded output:
🟢 Score > 2 = Risk-On
🟠 –2 to +2 = Neutral
🔴 Score < –2 = Risk-Off
Displayed as a line plot with background color and signal markers
🧪 Timeframe of analysis:
Default: 5 days (adjustable via input)
Calculated using Rate of Change (% change)
🧭 Use Cases:
Quickly assess macro sentiment
Filter for position sizing, hedging, or intraday bias
Especially useful for:
Swing traders
Day traders with macro filters
Volatility and options traders
📌 Note:
This is not a buy/sell signal indicator, but a contextual sentiment tool designed to help you stay aligned with overall market conditions.
STH Unrealized Profit/Loss Ratio (STH-NUPL) | [DeV]STH-NUPL
The Short-Term Holder Net Unrealized Profit/Loss Ratio (STH-NUPL) is an analytical tool designed to approximate the unrealized profit or loss of Bitcoin’s short-term holders (STHs)—typically those holding coins for less than 155 days—within the constraints of TradingView’s price-based environment. Drawing inspiration from the canonical STH-NUPL metric, which assesses the difference between the market value and realized value of STH-held coins, this indicator adapts the concept into a normalized ratio using Bitcoin’s price data as a proxy. It offers a window into the sentiment and behavior of short-term market participants, who are often more sensitive to price fluctuations than long-term holders.
In its raw form, STH-NUPL oscillates around a break-even threshold of 0, where positive values indicate aggregate unrealized profits for STHs (market value exceeds realized value), and negative values suggest losses. This inflection point frequently acts as a key level: in bear markets, it can signal capitulation as STHs sell at break-even or below, while in bull markets, it may reflect reluctance to realize losses, providing support. The indicator enhances this metric with smoothing, a moving average overlay, and sophisticated visualization options, delivering a statistically informed perspective on short-term holder dynamics tailored for institutional-grade analysis.
STH-NUPL Settings -
Lookback Length (Default: 150 days): Defines the SMA period for estimating realized value. This 150-day window aligns with traditional STH definitions (e.g., <155 days), capturing a broad yet relevant historical cost basis for short-term holders, ideal for assessing cyclical behavior.
Smoothing Period (Default: 5 days): Applies an EMA to the raw STH-NUPL ratio, with a short default period to maintain responsiveness to recent price shifts while filtering out daily volatility. This setting is particularly suited for tactical analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the STH-NUPL’s moving average, offering a medium-term trend signal that contrasts with the 150-day lookback, enabling detection of momentum shifts within broader market phases.
MA Type (Default: EMA): Provides six moving average types, from the straightforward SMA to the volume-sensitive VWMA. The default EMA balances smoothness and reactivity, while options like HMA or VWMA cater to specialized needs, such as emphasizing recent action or volume trends.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the STH-NUPL MA plot, allowing users to focus solely on the smoothed ratio when desired.
Show Background Colors (Default: True): Activates dynamic background shading to visually reinforce market regimes.
Background Color Source (Default: STH-NUPL): Enables users to tie the background to either the STH-NUPL’s midline (reflecting sthNupl > 0) or the MA’s trend direction (maNupl > maNupl ), aligning the visual context with the chosen analytical focus.
Analytical Applications -
Bear Market Capitulation: When the smoothed STH-NUPL approaches or falls below zero, it often signals loss realization among STHs, a precursor to capitulation in downtrends. A declining MA crossing zero can confirm this selling pressure.
Bull Market Support: Positive STH-NUPL values with a rising MA indicate STHs are in profit and reluctant to sell at a loss, forming support zones in uptrends as sell pressure wanes.
Sentiment Extremes: Significant deviations above or below zero highlight over-optimism or despair among STHs, offering contrarian opportunities when paired with price action or other on-chain metrics.
**Limitations**
As a TradingView-based approximation, this indicator uses price data (close) rather than true on-chain STH supply and realized price, which are available through providers like Glassnode. The 150-day SMA for realized value simplifies the cost basis, potentially underrepresenting the diversity of STH transactions. Despite this, the smoothed ratio and moving average overlay provide a practical proxy for tracking STH sentiment within TradingView’s ecosystem.
Spent Output Profit Ratio (SOPR) Z-Score | [DeV]SOPR Z-Score
The Spent Output Profit Ratio (SOPR) is an advanced on-chain metric designed to provide deep insights into Bitcoin market dynamics by measuring the ratio between the combined USD value of all Bitcoin outputs spent on a given day and their combined USD value at the time of creation (typically, their purchase price). As a member of the Realized Profit/Loss family of metrics, SOPR offers a window into aggregate seller behavior, effectively representing the USD amount received by sellers divided by the USD amount they originally paid. This indicator enhances this metric by normalizing it into a Z-Score, enabling a statistically robust analysis of market sentiment relative to historical trends, augmented by a suite of customizable features for precision and visualization.
SOPR Settings -
Lookback Length (Default: 150 days): Determines the historical window for calculating the Z-Score’s mean and standard deviation. A longer lookback captures broader market cycles, providing a stable baseline for identifying extreme deviations, which is particularly valuable for long-term strategic analysis.
Smoothing Period (Default: 100 days): Applies an EMA to the raw SOPR, balancing responsiveness to recent changes with noise reduction. This extended smoothing period ensures the indicator focuses on sustained shifts in seller behavior, ideal for institutional-grade trend analysis.
Moving Average Settings -
MA Lookback Length (Default: 90 days): Sets the period for the Z-Score’s moving average, offering a shorter-term trend signal relative to the 150-day Z-Score lookback. This contrast enhances the ability to detect momentum shifts within the broader context.
MA Type (Default: EMA): Provides six moving average types, from the simple SMA to the volume-weighted VWMA. The default EMA strikes an optimal balance between smoothness and responsiveness, while alternatives like HMA (Hull) or VWMA (volume-weighted) allow for specialized applications, such as emphasizing recent price action or incorporating volume dynamics.
Display Settings -
Show Moving Average (Default: True): Toggles the visibility of the Z-Score MA plot, enabling users to focus solely on the raw Z-Score when preferred.
Show Background Colors (Default: True): Activates dynamic background shading, enhancing visual interpretation of market regimes.
Background Color Source (Default: SOPR): Allows users to tie the background color to either the SOPR Z-Score’s midline (reflecting adjustedZScore > 0) or the MA’s trend direction (zScoreMA > zScoreMA ). This dual-source option provides flexibility to align the visual context with the primary analytical focus.
Analytical Applications -
Bear Market Resistance: When the Z-Score approaches or exceeds zero (raw SOPR near 1), it often signals resistance as sellers rush to exit at break-even, a pattern historically observed during downtrends. A rising Z-Score MA crossing zero can confirm this pressure.
Bull Market Support: Conversely, a Z-Score dropping below zero in uptrends indicates reluctance to sell at a loss, forming support as sell pressure diminishes. The MA’s bullish coloring reinforces confirmation of renewed buying interest.
Extreme Deviations: Values significantly above or below zero highlight overbought or oversold conditions, respectively, offering opportunities for contrarian positioning when paired with other on-chain or price-based metrics.
AI Trend Momentum SniperThe AI Trend Momentum Sniper is a powerful technical analysis tool designed for day trading. This strategy combines multiple momentum and trend indicators to identify high-probability entry and exit points. The indicator utilizes a combination of Supertrend, MACD, RSI, ATR (Average True Range), and On-Balance Volume (OBV) to generate real-time signals for buy and sell opportunities.
Key Features:
Supertrend for detecting market direction (bullish or bearish).
MACD for momentum confirmation, highlighting changes in market momentum.
RSI to filter out overbought/oversold conditions and ensure high-quality trades.
ATR as a volatility filter to adjust for changing market conditions.
OBV (On-Balance Volume) to confirm volume strength and trend validity.
Dynamic Stop-Loss & Take-Profit based on ATR to manage risk and lock profits.
This indicator is tailored for intraday traders looking for quick market moves, especially in volatile and high liquidity assets like Bitcoin (BTC) and Ethereum (ETH). It helps traders capture short-term trends with efficient risk management tools.
How to Apply:
Set Your Chart: Apply the AI Trend Momentum Sniper to a 5-minute (M5) or 15-minute (M15) chart for optimal performance.
Buy Signal: When the indicator generates a green arrow below the bar, it indicates a buy signal based on positive trend and momentum alignment.
Sell Signal: A red arrow above the bar signals a sell condition when the trend and momentum shift bearish.
Stop-Loss and Take-Profit: The indicator automatically calculates dynamic stop-loss and take-profit levels based on the ATR value for each trade, ensuring proper risk management.
Alerts: Set up custom alerts for buy or sell signals, and get notified instantly when opportunities arise.
Best Markets for Use:
BTC/USDT, ETH/USDT – High liquidity and volatility.
Major altcoins with sufficient volume.
Avoid using it on low-liquidity assets where price action may become erratic.
Timeframes:
This indicator is best suited for lower timeframes (5-minute to 15-minute charts) to capture quick price movements in trending markets.
NHPF (Normalized Hodrick-Prescott Filter)This indicator applies a normalized Hodrick–Prescott filter (NHPF) to Bitcoin’s price data. It separates the underlying trend from short-term cyclical fluctuations by recursively smoothing the price using a user-defined lambda (HP Filter Period). The raw trend is then normalized by calculating a ratio between the trend and the current price, which is scaled and shifted according to subjective parameters (Mean and Scale). The result is a dimensionless value that highlights deviations from the long-term trend—serving as a signal for potential overbought (positive values) or oversold (negative values) market conditions. A zero line provides a clear reference, allowing traders to visually gauge when Bitcoin’s price is significantly above or below its expected trajectory.
Feel free to adjust the inputs to best match your analysis preferences.
Relative Crypto Dominance Polar Chart [LuxAlgo]The Relative Crypto Dominance Polar Chart tool allows traders to compare the relative dominance of up to ten different tickers in the form of a polar area chart, we define relative dominance as a combination between traded dollar volume and volatility, making it very easy to compare them at a glance.
🔶 USAGE
The use is quite simple, traders just have to load the indicator on the chart, and the graph showing the relative dominance will appear.
The 10 tickers loaded by default are the major cryptocurrencies by market cap, but traders can select any ticker in the settings panel.
Each area represents dominance as volatility (radius) by dollar volume (arc length); a larger area means greater dominance on that ticker.
🔹 Choosing Period
The tool supports up to five different periods
Hourly
Daily
Weekly
Monthly
Yearly
By default, the tool period is set on auto mode, which means that the tool will choose the period depending on the chart timeframe
timeframes up to 2m: Hourly
timeframes up to 15m: Daily
timeframes up to 1H: Weekly
timeframes up to 4H: Monthly
larger timeframes: Yearly
🔹 Sorting & Sizing
Traders can sort the graph areas by volatility (radius of each area) in ascending or descending order; by default, the tickers are sorted as they are in the settings panel.
The tool also allows you to adjust the width of the chart on a percentage basis, i.e., at 100% size, all the available width is used; if the graph is too wide, just decrease the graph size parameter in the settings panel.
🔹 Set your own style
The tool allows great customization from the settings panel, traders can enable/disable most of the components, and add a very nice touch with curved lines enabled for displaying the areas with a petal-like effect.
🔶 SETTINGS
Period: Select up to 5 different time periods from Hourly, Daily, Weekly, Monthly and Yearly. Enable/disable Auto mode.
Tickers: Enable/disable and select tickers and colors
🔹 Style
Graph Order: Select sort order
Graph Size: Select percentage of width used
Labels Size: Select size for ticker labels
Show Percent: Show dominance in % under each ticker
Curved Lines: Enable/disable petal-like effect for each area
Show Title: Enable/disable graph title
Show Mean: Enable/disable volatility average and select color
BTC & SPX vs Yield Curve: Recession Risk ZonesBTC & SPX vs Yield Curve – Recession Risk Zones
This tool helps you track Bitcoin (BTC) and the S&P 500 (SPX) against key macro signals from the U.S. yield curve to spot potential recession risks.
🟪 Color Legend:
🔴 Red = Yield curve is inverted (warning starts)
🟡 Yellow = Projected 6–18 month recession risk (if inversion still active)
🟠 Orange = Active 6–18 month risk window (after inversion ends)
💜 Fuchsia = Real historical U.S. recessions
📈 What’s Plotted:
🔵 BTCUSD (blue line) – Normalized price
🟢 S&P 500 (green line) – Normalized price
🟠 10Y–2Y Yield Spread – Macro signal for risk
✅ Use it to:
Spot macro pressure zones
See how BTC and SPX behave around economic stress
Stay cautious when red/orange/yellow areas appear
Let me know if you'd like to enable toggles to hide/show BTC or SPX independently!
GLXY Support & Resistance ZonesHere’s a structured trading strategy for Galaxy Digital Holdings Ltd. (GLXY) based on a combination of technical analysis, market sentiment, and macro crypto market movement:
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1. Timeframe
• Swing trading timeframe: 1-week to 1-month trades.
• Monitor daily and 4H charts for entries and exits.
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2. Key Factors Driving GLXY
• Strongly correlated to Bitcoin and Ethereum price movement.
• Sensitive to regulatory news in Canada/US and institutional crypto adoption.
• Watch Galaxy’s quarterly earnings and treasury BTC/ETH position updates.
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3. Entry Strategy
A) Technical Setup:
• Buy at major support zones:
• Key support levels: $7.00 CAD, $9.00 CAD (verify current chart levels).
• Enter long positions on bullish reversal candles at these supports.
• Breakout trades:
• Enter long positions on confirmed breakouts above significant resistance (watch volume and 1D close).
• Moving Average Confirmation:
• Only trade long if price is above the 50-day moving average and 50 MA is upward sloping.
B) Macro Confirmation:
• Only take aggressive long positions if BTC price is in an uptrend (above its own 50-day MA).
• Monitor ETH/BTC pair as additional confidence for alt sentiment.
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4. Exit Strategy
• First partial profit target: Previous swing highs or Fibonacci extension levels (commonly 1.272 or 1.618).
• Trailing stop: Move stop-loss to entry when trade is +10%.
• Hard stop-loss: Below the last daily support (2-5% risk).
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5. Diversification
• Do not exceed 5-7% of total portfolio per trade.
• Hedge exposure by monitoring crypto futures or crypto sentiment indexes (eg. Fear & Greed Index).
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6. Optional Short Setup
• Only short if price breaks major support with strong volume, and BTC/ETH are in confirmed downtrends.
• Short target: next daily support zone.
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7. News / Event-based Catalyst
• Enter small positions before major earnings or after big regulatory decisions if crypto sentiment is bullish.
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8. Review
• Reassess the strategy every month based on BTC market structure.
• Track your trade results for GLXY separately to refine position sizing and entry criteria.
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M2SL/DXY RatioThis is the ratio of M2 money supply (M2SL) to the U.S. dollar index (DXY), taking into account the impact of U.S. dollar strength and weakness on liquidity.
M2SL/DXY better represents the current impact of the United States on cryptocurrency prices.
BTC Volatility ForecastThe "BTC Volatility Forecast" indicator is designed to help traders anticipate Bitcoin (BTC) price volatility by analyzing historical daily price ranges and projecting future fluctuations. Inspired by advanced volatility forecasting studies, it calculates an approximate realized variance using the squared difference between each day’s high and low prices. By applying a simple linear regression model over the past five days of variance data (customizable via the "Lag Period" input), the indicator provides a forecast for the next day’s volatility. This makes it a valuable tool for BTC traders looking to gauge potential market turbulence and adjust their strategies accordingly.
On the chart, the indicator displays two lines: a blue solid line representing the current realized variance and an orange line showing the forecasted volatility for the upcoming day. Traders can set a "Volatility Threshold" to trigger alerts when the forecast exceeds a specified level, aiding in risk management or trade planning. A debug label on the last bar also shows the exact current and forecasted values for quick reference. While this version uses daily data for simplicity, it captures the essence of volatility prediction and can be a starting point for understanding BTC market dynamics—perfect for both novice and experienced traders on TradingView.
Market Structure Break with Volume & ATR#### Indicator Overview:
The *Market Structure Break with Volume & ATR (MSB+VolATR)* indicator is designed to identify significant market structure breakouts and breakdowns using a combination of price action, volume analysis, and volatility (ATR). It is particularly useful for traders who rely on higher timeframes for swing trading or positional trading. The indicator highlights bullish and bearish breakouts, retests, fakeouts, and potential buy/sell signals based on RSI overbought/oversold conditions.
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### Key Features:
1. *Market Structure Analysis*:
- Identifies swing highs and lows on a user-defined higher timeframe.
- Detects breakouts and breakdowns when price exceeds these levels with volume and ATR validation.
2. *Volume Validation*:
- Ensures breakouts are accompanied by above-average volume, reducing the likelihood of false signals.
3. *ATR Filter*:
- Filters out insignificant breakouts by requiring the breakout size to exceed a multiple of the ATR.
4. *RSI Integration*:
- Adds a momentum filter by considering overbought/oversold conditions using RSI.
5. *Visual Enhancements*:
- Draws colored boxes to highlight breakout zones.
- Labels breakouts, retests, and fakeouts for easy interpretation.
- Displays stop levels for potential trades.
6. *Alerts*:
- Provides alert conditions for buy and sell signals, enabling real-time notifications.
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### Input Settings and Their Effects:
1. **Timeframe (tf):
- Determines the higher timeframe for market structure analysis.
- *Effect*: A higher timeframe (e.g., 1D) reduces noise and provides more reliable swing points, while a lower timeframe (e.g., 4H) may generate more frequent but less reliable signals.
2. **Lookback Period (length):
- Defines the number of historical bars used to identify significant highs and lows.
- *Effect*: A longer lookback period (e.g., 50) captures broader market structure, while a shorter period (e.g., 20) reacts faster to recent price action.
3. **ATR Length (atr_length):
- Sets the period for ATR calculation.
- *Effect*: A shorter ATR length (e.g., 14) reacts faster to recent volatility, while a longer length (e.g., 21) smooths out volatility spikes.
4. **ATR Multiplier (atr_multiplier):
- Filters insignificant breakouts by requiring the breakout size to exceed ATR × multiplier.
- *Effect*: A higher multiplier (e.g., 0.2) reduces false signals but may miss smaller breakouts.
5. **Volume Multiplier (volume_multiplier):
- Sets the volume threshold for breakout validation.
- *Effect*: A higher multiplier (e.g., 1.0) ensures stronger volume confirmation but may reduce the number of signals.
6. **RSI Length (rsi_length):
- Defines the period for RSI calculation.
- *Effect*: A shorter RSI length (e.g., 10) makes the indicator more sensitive to recent price changes, while a longer length (e.g., 20) smooths out RSI fluctuations.
7. *RSI Overbought/Oversold Levels*:
- Sets the thresholds for overbought (default: 70) and oversold (default: 30) conditions.
- *Effect*: Adjusting these levels can make the indicator more or less conservative in generating signals.
8. **Stop Loss Multiplier (SL_Multiplier):
- Determines the distance of the stop-loss level from the entry price based on ATR.
- *Effect*: A higher multiplier (e.g., 2.0) provides wider stops, reducing the risk of being stopped out prematurely but increasing potential losses.
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### How It Works:
1. *Breakout Detection*:
- A bullish breakout occurs when the close exceeds the highest high of the lookback period, with volume above the threshold and breakout size exceeding ATR × multiplier.
- A bearish breakout occurs when the close falls below the lowest low of the lookback period, with similar volume and ATR validation.
2. *Retest Logic*:
- After a breakout, if price retests the breakout zone without closing beyond it, a retest label is displayed.
3. *Fakeout Detection*:
- If price briefly breaks out but reverses back into the range, a fakeout label is displayed.
4. *Buy/Sell Signals*:
- A sell signal is generated when price reverses below a bullish breakout zone and RSI is overbought.
- A buy signal is generated when price reverses above a bearish breakout zone and RSI is oversold.
5. *Stop Levels*:
- Stop-loss levels are plotted based on ATR × SL_Multiplier, providing a visual guide for risk management.
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### Who Can Use It and How:
1. *Swing Traders*:
- Use the indicator on daily or 4-hour timeframes to identify high-probability breakout trades.
- Combine with other technical analysis tools (e.g., trendlines, Fibonacci levels) for confirmation.
2. *Positional Traders*:
- Apply the indicator on weekly or daily charts to capture long-term trends.
- Use the stop-loss levels to manage risk over extended periods.
3. *Algorithmic Traders*:
- Integrate the buy/sell signals into automated trading systems.
- Use the alert conditions to trigger trades programmatically.
4. *Risk-Averse Traders*:
- Adjust the ATR and volume multipliers to filter out low-probability trades.
- Use wider stop-loss levels to avoid premature exits.
---
### Where to Use It:
- *Forex*: Identify breakouts in major currency pairs.
- *Stocks*: Spot trend reversals in high-volume stocks.
- *Commodities*: Trade breakouts in gold, oil, or other commodities.
- *Crypto*: Apply to Bitcoin, Ethereum, or other cryptocurrencies for volatile breakout opportunities.
---
### Example Use Case:
- *Timeframe*: 1D
- *Lookback Period*: 50
- *ATR Length*: 14
- *ATR Multiplier*: 0.1
- *Volume Multiplier*: 0.5
- *RSI Length*: 14
- *RSI Overbought/Oversold*: 70/30
- *SL Multiplier*: 1.5
In this setup, the indicator will:
1. Identify significant swing highs and lows on the daily chart.
2. Validate breakouts with volume and ATR filters.
3. Generate buy/sell signals when price reverses and RSI confirms overbought/oversold conditions.
4. Plot stop-loss levels for risk management.
---
### Conclusion:
The *MSB+VolATR* indicator is a versatile tool for traders seeking to capitalize on market structure breakouts with added confirmation from volume and volatility. By customizing the input settings, traders can adapt the indicator to their preferred trading style and risk tolerance. Whether you're a swing trader, positional trader, or algorithmic trader, this indicator provides actionable insights to enhance your trading strategy.
CCT Pi Cycle Top/BottomPi Cycle Top/bottom: The Ultimate Market Cycle Indicator
Introduction
The Pi Cycle Top/bottom Indicator is one of the most reliable tools for identifying Bitcoin market cycle peaks and bottoms. Its effectiveness lies in the strategic combination of moving averages that historically align with major market cycle reversals. Unlike traditional moving average crossovers, this indicator applies an advanced iterative approach to pinpoint price extremes with higher accuracy.
This version, built entirely with Pine Script™ v6, introduces unprecedented precision in detecting both the Pi Cycle Top and Pi Cycle Bottom, eliminating redundant labels, optimizing visual clarity, and ensuring the indicator adapts dynamically to evolving market conditions.
What is the Pi Cycle Theory?
The Pi Cycle Top and Pi Cycle Bottom were originally introduced based on a simple yet profound discovery: key moving average crossovers consistently align with macro market tops and bottoms.
Pi Cycle Top: The crossover of the 111-day Simple Moving Average (SMA) and the 350-day SMA multiplied by 2 has historically signaled market tops with astonishing accuracy.
Pi Cycle Bottom: The intersection of the 150-day Exponential Moving Average (EMA) and the 471-day SMA has repeatedly marked significant market bottoms.
While traditional moving average strategies often suffer from lag and false signals, the Pi Cycle Indicator enhances accuracy by applying a range-based scanning methodology, ensuring that only the most critical reversals are detected.
How This Indicator Works
Unlike basic moving average crossovers, this script introduces a unique iteration process to refine the detection of Pi Cycle points. Here’s how it works:
Detecting Crossovers:
Identifies the Golden Cross (bullish crossover) and Death Cross (bearish crossover) for both the Pi Cycle Top and Pi Cycle Bottom.
Iterating Through the Cycle:
Instead of plotting a simple crossover point, this script scans the range between each Golden and Death Cross to identify the absolute lowest price (Pi Cycle Bottom) and highest price (Pi Cycle Top) within that cycle.
Precision Labeling:
The indicator dynamically adjusts label positioning:
If the price at the crossover is below the fast moving average → the label is placed on the moving average with a downward pointer.
If the price is above the fast moving average → the label is placed below the candle with an upward pointer.
This ensures optimal visibility and prevents misleading signal placement.
Advanced Pine Script v6 Features:
Labels and moving average names are only shown on the last candle, reducing chart noise while maintaining clarity.
Offers full user customization, allowing traders to toggle:
Pi Cycle Top & Bottom visibility
Moving average labels
Crossover labels
Why This Indicator is Superior
This script is not just another moving average crossover tool—it is a market cycle tracker designed for long-term investors and analysts who seek:
✔ High-accuracy macro cycle identification
✔ Elimination of false signals using an iterative range-based scan
✔ Automatic detection of market extremes without manual adjustments
✔ Optimized visuals with smart label positioning
✔ First-of-its-kind implementation using Pine Script™ v6 capabilities
How to Use It?
Bull Market Tops:
When the Pi Cycle Top indicator flashes, consider the potential for a market cycle peak.
Historically, Bitcoin has corrected significantly after these signals.
Bear Market Bottoms:
When the Pi Cycle Bottom appears, it suggests a macro accumulation phase.
These signals have aligned perfectly with historical cycle bottoms.
Final Thoughts
The Pi Cycle Top/bottom Indicator is a must-have tool for traders, investors, and analysts looking to anticipate long-term trend reversals with precision. With its refined methodology, superior label positioning, and cutting-edge Pine Script™ v6 optimizations, this is the most reliable version ever created.
BTC Momentum Detector 1h# BTC Momentum Detector 1h
This indicator is designed to detect significant momentum movements in Bitcoin price on the 1-hour timeframe. It identifies candles with percentage changes within a specific range, which often precede larger price movements.
## How It Works
The indicator analyzes price movements to detect potential momentum shifts:
- Identifies candles with percentage changes between configurable thresholds (default: 1.7% - 2.8%)
- Requires neutral or inverse movement in the prior candle to avoid false signals
- Optional volume filter ensures signals are confirmed by above-average trading activity
- Tracks price continuation to calculate success rates and average returns
## Key Features
- **Signal Detection**: Green triangles below price bars indicate upward momentum signals; red triangles above price bars indicate downward momentum signals
- **Continuation Tracking**: Dashed horizontal lines show the entry price levels of active signals being tracked
- **Statistics Panel**: Displays real-time metrics including signal counts, success rates, and average returns
- **Current Status**: Shows the current price change percentage and active signals being monitored
## Parameters
- **Minimum Percentage Threshold**: Minimum price change to trigger a signal (default: 1.7%)
- **Maximum Percentage Threshold**: Maximum price change to filter out extreme moves (default: 2.8%)
- **Continuation Periods**: Number of periods to track after signal (default: 2)
- **Require Prior Neutral/Inverse**: Filters signals by requiring neutral or opposite prior movement
- **Neutral Threshold**: Defines what's considered a neutral movement (default: 0.1%)
- **Volume Filter**: Option to require above-average volume for confirmation
- **Volume Multiplier**: Volume must exceed average by this factor (default: 2x)
## Strategy Concept
The underlying strategy is based on the concept that when Bitcoin makes a controlled, significant move (not too small, not too large) after a period of neutral or opposite movement, it often continues in that direction for the next few periods. This pattern reflects the early stages of momentum development in the market.
Mogwai Method with RSI and EMA - BTCUSD 15mThis is a custom TradingView indicator designed for trading Bitcoin (BTCUSD) on a 15-minute timeframe. It’s based on the Mogwai Method—a mean-reversion strategy—enhanced with the Relative Strength Index (RSI) for momentum confirmation. The indicator generates buy and sell signals, visualized as green and red triangle arrows on the chart, to help identify potential entry and exit points in the volatile cryptocurrency market.
Components
Bollinger Bands (BB):
Purpose: Identifies overextended price movements, signaling potential reversions to the mean.
Parameters:
Length: 20 periods (standard for mean-reversion).
Multiplier: 2.2 (slightly wider than the default 2.0 to suit BTCUSD’s volatility).
Role:
Buy signal when price drops below the lower band (oversold).
Sell signal when price rises above the upper band (overbought).
Relative Strength Index (RSI):
Purpose: Confirms momentum to filter out false signals from Bollinger Bands.
Parameters:
Length: 14 periods (classic setting, effective for crypto).
Overbought Level: 70 (price may be overextended upward).
Oversold Level: 30 (price may be overextended downward).
Role:
Buy signal requires RSI < 30 (oversold).
Sell signal requires RSI > 70 (overbought).
Exponential Moving Averages (EMAs) (Plotted but not currently in signal logic):
Purpose: Provides trend context (included in the script for visualization, optional for signal filtering).
Parameters:
Fast EMA: 9 periods (short-term trend).
Slow EMA: 50 periods (longer-term trend).
Role: Can be re-added to filter signals (e.g., buy only when Fast EMA > Slow EMA).
Signals (Triangles):
Buy Signal: Green upward triangle below the bar when price is below the lower Bollinger Band and RSI is below 30.
Sell Signal: Red downward triangle above the bar when price is above the upper Bollinger Band and RSI is above 70.
How It Works
The indicator combines Bollinger Bands and RSI to spot mean-reversion opportunities:
Buy Condition: Price breaks below the lower Bollinger Band (indicating oversold conditions), and RSI confirms this with a reading below 30.
Sell Condition: Price breaks above the upper Bollinger Band (indicating overbought conditions), and RSI confirms this with a reading above 70.
The strategy assumes that extreme price movements in BTCUSD will often revert to the mean, especially in choppy or ranging markets.
Visual Elements
Green Upward Triangles: Appear below the candlestick to indicate a buy signal.
Red Downward Triangles: Appear above the candlestick to indicate a sell signal.
Bollinger Bands: Gray lines (upper, middle, lower) plotted for reference.
EMAs: Blue (Fast) and Orange (Slow) lines for trend visualization.
How to Use the Indicator
Setup
Open TradingView:
Log into TradingView and select a BTCUSD chart from a supported exchange (e.g., Binance, Coinbase, Bitfinex).
Set Timeframe:
Switch the chart to a 15-minute timeframe (15m).
Add the Indicator:
Open the Pine Editor (bottom panel in TradingView).
Copy and paste the script provided.
Click “Add to Chart” to apply it.
Verify Display:
You should see Bollinger Bands (gray), Fast EMA (blue), Slow EMA (orange), and buy/sell triangles when conditions are met.
Trading Guidelines
Buy Signal (Green Triangle Below Bar):
What It Means: Price is oversold, potentially ready to bounce back toward the Bollinger Band middle line.
Action:
Enter a long position (buy BTCUSD).
Set a take-profit near the middle Bollinger Band (bb_middle) or a resistance level.
Place a stop-loss 1-2% below the entry (or based on ATR, e.g., ta.atr(14) * 2).
Best Context: Works well in ranging markets; avoid during strong downtrends.
Sell Signal (Red Triangle Above Bar):
What It Means: Price is overbought, potentially ready to drop back toward the middle line.
Action:
Enter a short position (sell BTCUSD) or exit a long position.
Set a take-profit near the middle Bollinger Band or a support level.
Place a stop-loss 1-2% above the entry.
Best Context: Effective in ranging markets; avoid during strong uptrends.
Trend Filter (Optional):
To reduce false signals in trending markets, you can modify the script:
Add and ema_fast > ema_slow to the buy condition (only buy in uptrends).
Add and ema_fast < ema_slow to the sell condition (only sell in downtrends).
Check the Fast EMA (blue) vs. Slow EMA (orange) alignment visually.
Tips for BTCUSD on 15-Minute Charts
Volatility: BTCUSD can be erratic. If signals are too frequent, increase bb_mult (e.g., to 2.5) or adjust RSI levels (e.g., 75/25).
Confirmation: Use volume spikes or candlestick patterns (e.g., doji, engulfing) to confirm signals.
Time of Day: Mean-reversion works best during low-volume periods (e.g., Asian session in crypto).
Backtesting: Use TradingView’s Strategy Tester (convert to a strategy by adding entry/exit logic) to evaluate performance with historical BTCUSD data up to March 13, 2025.
Risk Management
Position Size: Risk no more than 1-2% of your account per trade.
Stop Losses: Always use stops to protect against BTCUSD’s sudden moves.
Avoid Overtrading: Wait for clear signals; don’t force trades in choppy or unclear conditions.
Example Scenario
Chart: BTCUSD, 15-minute timeframe.
Buy Signal: Price drops to $58,000, below the lower Bollinger Band, RSI at 28. A green triangle appears.
Action: Buy at $58,000, target $59,000 (middle BB), stop at $57,500.
Sell Signal: Price rises to $60,500, above the upper Bollinger Band, RSI at 72. A red triangle appears.
Action: Sell at $60,500, target $59,500 (middle BB), stop at $61,000.
This indicator is tailored for mean-reversion trading on BTCUSD. Let me know if you’d like to tweak it further (e.g., add filters, alerts, or alternative indicators)!
Inverted USDT DominanceInverted USDT Dominance Indicator
This simple yet powerful indicator plots the inverted USDT Dominance (USDT.D), making it visually intuitive to analyze market sentiment shifts. Typically, USDT dominance rises when investors seek stability, indicating a "risk-off" market environment. Conversely, it falls when investors pursue riskier assets like cryptocurrencies, signaling a "risk-on" environment.
Why invert the USDT Dominance chart?
By flipping USDT Dominance around the zero line, this indicator allows traders and investors to more clearly visualize its correlation and divergence with traditional market indicators like the 10-year Treasury yield (TNX), Bitcoin, or equity indices. A rising line on this inverted indicator intuitively indicates increasing market risk appetite, whereas a falling line highlights growing risk aversion.
Use cases:
Quickly visualize market sentiment (risk-on vs. risk-off).
Identify divergences and correlations between crypto markets and traditional financial instruments.
Enhance portfolio allocation decisions by clearly seeing sentiment changes.
BTC: Open InterestThis indicator tracks the 7-day (default) percentage change in open interest (OI), providing insights into market participation trends. It includes customizable periods and colors, allowing traders to adjust settings for better visualization.
Open interest (OI) is the total number of active contracts (futures or options) that haven’t been closed or settled. It represents the total open positions in the market.
Thus when OI increases, more traders are entering new positions, signaling growing market interest. Conversely, when OI decreases, positions are being closed, suggesting lower trader participation or liquidation.
Attributes & Features:
Open Interest Percentage Change – Measures the 7-day % change in open interest to track market participation.
Customizable Calculation Period – Users can adjust the period (default: 7 days) for more flexible analysis.
Adjustable Colors – Allows modification of colors for better visualization.
Trend Identification – Highlights rising vs. falling open interest trends.
Works Across Assets – Can be used for cryptos, stocks, and futures with open interest data.
Overlay or Separate Panel – Can be plotted on price chart or as a separate indicator.
How It Works:
Fetches Open Interest Data – Retrieves open interest values for each day for USD, USDT, and USDC Bitcoin Perpetual Derivitives.
Calculates Percentage Change – Compares current open interest to its value X days ago (Default = 7 days).
Standard Deviation – Applies standard deviation ranging from -2 to +2 deviations to identify large shifts in OI.
Visual Alerts – Can highlight extreme increases or decreases signaling potential market shifts.
NOTE: THE INDICATOR DATA ONLY GOES BACK TO START OF 2022
Price AltimeterThis indicator should help visualize the price, inspired by a Digital Altimeter in a Pilots HUD.
It's by default calibrated to Bitcoin, with the small levels showing every $100 and the larger levels setup to display on every $1000. But you can change this to whatever you want by changing the settings for: Small and Large Level Increments.
The default colors are grey, but can be changed to whatever you want, and there are two cause if you want they work as a gradient.
There are options to fade as the values go away from the current price action.
There are options for Forward and Backward Offsets, 0 is the current price and each value represents a candle on whatever time frame your currently on.
Other Options include the Fade Ratio, the Line Width and Style, which are all self explanatory.
Hope you Enjoy!
Backtest it in fast mode to see it in action a little better...
Known Issues:
For some reason it bug's out when either or are displaying more than 19 lines, unsure why so its limited to that for now.
Extra Note on what this may be useful for: I always wanted to make this, but didn't realize how to put things in front of the price action... Offset! Duh! Anyways, I thought of this one because I often it's hard on these charts to really get an idea for absolute price amounts across different time frames, this in an intuitive, at a glance way to see it because the regular price thing on the right always adds values between values when you zoom in and you can sometimes get lost figuring out the proportions of things.
Could also be useful for Scalping?
Mayer Multiple ZonesMayer Multiple Zones
The Mayer Multiple Zones indicator is a powerful market valuation tool that helps traders identify key price zones based on multiples of the 200-period moving average. Originally inspired by the Bitcoin Mayer Multiple concept, this versatile indicator works across all markets and timeframes to visualize the relative valuation of any asset.
Key Features:
Color-coded valuation zones: Instantly recognize if the current price represents a strong buy opportunity, fair value, or potential bubble territory
Customizable multiplier levels: Adjust all zone thresholds to suit specific markets or trading strategies
Real-time status indicator: Clear market status display showing current valuation zone
Comprehensive information table: View all critical price levels and current multiple at a glance
Multi-timeframe compatible: Works seamlessly across all timeframes while maintaining accurate MA200 reference
Visual zone labeling: Clear labels for each price zone directly on the chart
How to Use:
The indicator divides price action into six distinct zones based on the MA200:
Strong Buy Zone (default: below 0.6x MA200): Extreme undervaluation, historically excellent buying opportunities
Value Buy Zone (default: 0.6x-0.8x MA200): Attractive buying range for long-term value
Accumulation Zone (default: 0.8x-1.0x MA200): Price building strength below the MA200
Fair Value Zone (default: 1.0x-2.0x MA200): Reasonable valuation range
Take Profit Zone (default: 2.0x-2.5x MA200): Overvaluation suggesting partial profit taking
Bubble Zone (default: above 2.5x MA200): Extreme overvaluation, historically unsustainable levels
This indicator serves as both a strategic planning tool for long-term investors and a tactical guide for shorter-term traders, helping identify potential reversal zones and price targets based on historical valuation patterns.
Settings:
MA Length: Adjust the moving average period (default: 200)
Multipliers: Customize each zone threshold to adapt to specific market characteristics
Perfect for all traders seeking to understand relative market valuation across any timeframe.
Ragi's 24h volumeThis script is a TradingView Pine Script indicator that displays the 24-hour trading volume for a given asset. It provides both the native volume of the asset and, if the asset is not already listed on Binance, also displays the 24-hour volume from Binance (if applicable). Here's a breakdown of the key components:
Volume Calculation:
It sums the volume data over different time frames: 1-minute, 5-minute (for daily charts), or 60-minute intervals.
The volume is calculated based on the asset's volume type (either "quote" volume or a calculated value of close * volume).
For crypto assets, if the volume data is unavailable, it raises an error.
Binance Volume:
If the asset is not from Binance, the script fetches 24-hour volume data from Binance for that symbol, ensuring it is using the correct currency rate.
Display:
The indicator displays a table with the 24-hour volume in the chosen position on the chart (top, middle, or bottom).
The table displays the current exchange's volume, and if applicable, the Binance volume.
The volume is color-coded based on predefined thresholds:
Attention: Displays a warning color for volumes exceeding the attention level.
Warning: Shows an alert color for volumes above the warning threshold.
Normal: Displays in standard color when the volume is lower than the warning level.
The text and background color are customizable, and users can adjust the text size and position of the table.
User Inputs:
The script allows customization of table text size, position, background color, and volume thresholds for attention and warning.
In summary, this indicator is designed to track and display 24-hour volume on a chart, with additional volume information from Binance if necessary, and provides visual cues based on volume levels to help traders quickly assess trading activity.
Delta VolDelta Volume BTC - Multi Pair
Description The Delta Volume BTC - Multi Pair indicator visualizes the balance between buying and selling volume across multiple Bitcoin exchanges. By analyzing price action within each bar, it provides insight into underlying market pressure that traditional volume indicators miss. This indicator allows traders to:
Compare volume flow across Coinbase, Binance, and Binance Perpetual markets
Identify divergences between exchanges that may signal market shifts
Detect accumulation or distribution patterns through volume imbalances
View exchanges individually or in aggregate for comprehensive analysis
Calculation Methods The indicator offers three volume delta calculation methods:
VWAP Based (default):
price_range = high - low
buy_percent = (close - low) / price_range
sell_percent = (high - close) / price_range
delta = volume * (buy_percent - sell_percent)
This method distributes volume based on where price closed within the bar's range, providing a nuanced view of buying/selling pressure.
Tick Based :
delta = volume * sign(hlc3 - previous_hlc3)
This approach assigns volume based on the direction of typical price movement between bars, capturing momentum between periods.
Simple :
delta = close > open ? volume : close < open ? -volume : 0
A straightforward method that assigns positive volume to up bars and negative volume to down bars.
When Aggregate Mode is enabled, the indicator sums the volume deltas from all selected exchanges:
aggregate_delta = coinbase_delta + binance_delta + binance_perp_delta
Features
Multi-Exchange Support : Track volume delta across Coinbase, Binance, and Binance Perpetual futures
Advanced Calculation Methods : Choose between VWAP-based, tick-based, or simple volume delta algorithms
Flexible Display Options : Visualize as histogram, columns, area, or line charts
Customizable Colors : Distinct color schemes for each exchange and direction
Smoothing Options : Apply EMA, SMA, or WMA to reduce noise
Aggregate Mode : Combine all exchanges to see total market flow
How to Use
Individual Exchange Analysis : Uncheck "Aggregate Mode" to see each exchange separately, revealing where smart money may be positioning
Divergence Detection : Watch for one exchange showing buying while others show selling
Volume Trend Confirmation : Strong price moves should be accompanied by strong delta in the same direction
Liquidity Analysis : Compare spot vs futures volume delta to identify market sentiment shifts
The Delta Volume BTC - Multi Pair indicator helps identify the "hidden" buying and selling pressure that may not be apparent from price action alone, giving you an edge in understanding market dynamics across the Bitcoin ecosystem.
