Bitcoin Impact AnalyzerSummary of the "Bitcoin Impact Analyzer" script, the adjustments users can make, and an explanation of what the chart and table represent:
Script Summary:
The "Bitcoin Impact Analyzer" script is designed to help traders and analysts understand the relationship between a chosen altcoin and Bitcoin (BTC). It does this by:
Fetching price data for the specified altcoin and Bitcoin.
Calculating several key comparative metrics:
Normalized Prices: Shows the percentage performance of both assets from a common starting point.
Price Correlation: Measures how similarly the two assets' prices move over a defined period.
Beta: Indicates the altcoin's volatility relative to Bitcoin.
Altcoin/BTC Ratio: Shows the altcoin's value expressed in Bitcoin.
Fetching and displaying Bitcoin Dominance (BTC.D) data.
Visualizing these metrics on the chart as distinct plots.
Displaying the current values of these key metrics in a data table on the chart for quick reference.
The script aims to provide insights into whether an altcoin is outperforming or underperforming Bitcoin, how closely its price movements are tied to Bitcoin's, and its relative volatility.
User Adjustments:
Users can customize the script's behavior through several input settings:
Symbol Inputs:
Altcoin Symbol: Users can enter the ticker symbol for any altcoin they wish to analyze (e.g., BINANCE:ETHUSDT, KUCOIN:SOLUSDT).
Bitcoin Reference Symbol: Users can specify the Bitcoin pair to use as a reference, though BINANCE:BTCUSDT is a common default.
Lookback for Correlation/Beta:
Lookback Period: This integer value (default 50 periods) determines how many past candles are used to calculate the price correlation and beta.
A shorter lookback makes the metrics more sensitive to recent price action.
A longer lookback provides a smoother, more stable indication of the longer-term relationship.
Plot Visibility Options:
Users can toggle on or off the display of each individual plot on the chart:
Normalized BTC & Altcoin Prices
Altcoin/BTC Ratio
Correlation Plot
Bitcoin Dominance (BTC.D)
Beta Plot
This allows users to focus on specific metrics and reduce chart clutter.
What the Chart Represents:
The chart visually displays the historical trends and relationships of the selected metrics:
Normalized Prices Plot: Two lines (typically orange for BTC, blue for the altcoin) show the percentage growth of each asset from the start of the loaded chart data (or the first available data point for each symbol). This makes it easy to see which asset has performed better over time on a relative basis.
Correlation Plot: A single line (purple) oscillates between -1 and +1.
Values near +1 indicate a strong positive correlation (altcoin and BTC prices tend to move in the same direction).
Values near -1 indicate a strong negative correlation (they tend to move in opposite directions).
Values near 0 indicate little to no linear relationship.
Lines at +0.7 and -0.7 are often plotted as thresholds for "strong" correlation.
Beta Plot (if enabled): A single line (teal) shows the altcoin's volatility relative to BTC.
A Beta of 1 (often marked by a dashed line) means the altcoin has, on average, the same volatility as BTC.
Beta > 1 suggests the altcoin is more volatile than BTC (moves by a larger percentage for a given BTC move).
Beta < 1 suggests the altcoin is less volatile than BTC.
Bitcoin Dominance Plot: An area plot (gray) shows the percentage of the total cryptocurrency market capitalization that Bitcoin holds. This helps understand broader market sentiment and capital flows.
Altcoin/BTC Ratio Plot: A line (fuchsia) shows the price of the altcoin denominated in BTC.
An upward trend means the altcoin is gaining value against Bitcoin (outperforming).
A downward trend means the altcoin is losing value against Bitcoin (underperforming).
What the Table Represents:
The data table, typically located in the bottom-right corner of the chart, provides a snapshot of the current values for the most important calculated metrics. It includes:
Altcoin: The ticker symbol of the analyzed altcoin.
Bitcoin Ref: The ticker symbol of the Bitcoin reference.
Correlation (lookback): The current correlation coefficient between the altcoin and BTC, based on the specified lookback period. The value is color-coded (e.g., green for strong positive, red for strong negative).
Beta (lookback): The current beta value of the altcoin relative to BTC, based on the specified lookback period. The value may be color-coded to highlight significantly high or low volatility.
BTC.D Current: The current Bitcoin Dominance percentage.
ALT/BTC Ratio: The current price of the altcoin expressed in Bitcoin.
The table offers a quick, at-a-glance summary of the present market dynamics between the two assets without needing to interpret the lines on the chart for their exact current values.
Ciclos
Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
Candle Rating (1–5)This “Candle Rating (1–5)” indicator measures where each bar’s close sits within its own high-low range and assigns a simple strength score:
Range Calculation
It computes the candle’s total range (high − low) and finds the close’s position as a percentage of that range (0 = close at low, 1 = close at high).
Five-Point Rating
1 (Strong Buy): Close in the top 20% of the range
2 (Moderate Buy): 60–80%
3 (Neutral): 40–60%
4 (Moderate Sell): 20–40%
5 (Strong Sell): Bottom 20%
Visual Feedback
It plots the numeric rating above each bar (colored green → red), giving you an at-a-glance read of candle momentum and potential reversal strength across any timeframe.
Parsifal.Swing.TrendScoreThe Parsifal.Swing.TrendScore indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
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Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
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The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
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The Parsifal.Swing.TrendScore – Specifics
The Parsifal.Swing.TrendScore module combines short-term trend data with information about the current swing state, derived from raw price data and classical technical indicators. It provides an indication of how well the short-term trend aligns with the prevailing swing, based on recent market behavior.
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How Swing.TrendScore Works
The Swing.TrendScore calculates a swing score by collecting data within a bin (i.e., a single candle or time bucket) that signals an upside or downside swing. These signals are then aggregated together with insights from classical swing indicators.
Additionally, it calculates a short-term trend score using core technical signals, including:
• The Z-score of the price's distance from various EMAs
• The slope of EMAs
• Other trend-strength signals from additional technical indicators
These two components—the swing score and the trend score—are then combined to form the Swing.TrendScore indicator, which evaluates the short-term trend in context with swing behavior.
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How to Interpret Swing.TrendScore
The trend component enhances Swing.TrendScore’s ability to provide stronger signals when the short-term trend and swing state align.
It can also override the swing score; for example, even if a mean reversion appears to be forming, a dominant short-term trend may still control the market behavior.
This makes Swing.TrendScore particularly valuable for:
• Short-term trend-following strategies
• Medium-term swing trading
Unlike typical swing indicators, Swing.TrendScore is designed to respond more to medium-term swings rather than short-lived fluctuations.
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Behavior and Chart Representation
The Swing.TrendScore indicator fluctuates within a range, as most of its components are range-bound (though Z-score components may technically extend beyond).
• Historically high or low values may suggest overbought or oversold conditions
• The chart displays:
o A fast curve (orange)
o A slow curve (white)
o A shaded background representing the market state
• Extreme values followed by curve reversals may signal a developing mean reversion
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TrendScore Background Value
The Background Value reflects the combined state of the short-term trend and swing:
• > 0 (shaded green) → Bullish mode: swing and short-term trend both upward
• < 0 (shaded red) → Bearish mode: swing and short-term trend both downward
• The absolute value represents the confidence level in the market mode
Notably, the Background Value can remain positive during short downswings if the short-term trend remains bullish—and vice versa.
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How to Use the Parsifal.Swing.TrendScore
Several change points can act as entry triggers or aids:
• Fast Trigger: change in slope of the fast signal curve
• Trigger: fast line crosses slow line or the slope of the slow signal changes
• Slow Trigger: change in sign of the Background Value
Examples of these trigger points are illustrated in the accompanying chart.
Additionally, market highs and lows aligning with the swing indicator values may serve as pivot points in the evolving price process.
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As always, this indicator should be used in conjunction with other tools and market context in live trading.
While it provides valuable insight and potential entry points, it does not predict future price action.
Instead, it reflects recent tendencies and should be used judiciously.
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Extensions
The aggregation of information—whether derived from bins or technical indicators—is currently performed via simple averaging. However, this can be modified using alternative weighting schemes, based on:
• Historical performance
• Relevance of the data
• Specific market conditions
Smoothing periods used in calculations are also modifiable. In general, the EMAs applied for smoothing can be extended to reflect expectations based on relevance-weighted probability measures.
Since EMAs inherently give more weight to recent data, this allows for adaptive smoothing.
Additionally, EMAs may be further extended to incorporate negative weights, akin to wavelet transform techniques.
Modern Economic Eras DashboardOverview
This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison.
Data Sources & Indicators
All data is loaded monthly from official FRED series and rescaled to improve readability:
🔵 Real GDP (FRED:GDP): Total output of the U.S. economy.
🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation.
⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP.
🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force.
🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices.
🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries.
🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled.
Historical Crashes
The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context.
Era Classification
Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder.
Best Use Cases
✅ Long-term macro investors studying structural market behavior
✅ Educators and analysts explaining economic transitions
✅ Portfolio managers aligning strategy with macroeconomic phases
✅ Traders using history for cycle timing and risk assessment
Technical Notes
Designed for monthly timeframe, though it works on weekly.
Uses close price and standard request.security calls for consistency.
Max labels/lines configured for broader history (from 1860s to present).
All plotted series are rescaled manually for better visibility.
Originality
This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
Day Range DividerThe indicator divides the chart into Israeli trading days, starting at one o’clock after midnight and ending a minute before the next midnight, marking each day’s open with a thin vertical line whose color and width you can choose. A label with the day’s name (in Hebrew) can appear on the very first bar of the session, while another label is placed midway through the previous day, beneath the candles at a fixed distance from the bottom so it doesn’t obscure price. You can adjust the label’s color, size, and letter spacing, customize the line style, and decide whether to show the early-session label. The indicator ignores Saturday and Sunday, works on any intraday timeframe, never repaints after plotting, and lets you quickly spot daily sequences and time-of-day patterns for market analysis.
LANZ Strategy 3.0🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Strategy with Execution Window Logic
LANZ Strategy 3.0 is a rule-based trading system that utilizes the Asian session range to project Fibonacci levels and manage entries during a defined execution window. Designed for Forex and index traders, this strategy focuses on structured price behavior around key levels before the New York session.
🧠 Core Components:
Asian Session Range Mapping: Automatically detects the high, low, and midpoint during the Asian session.
Fibonacci Level Projection: Projects configurable Fibonacci retracement and extension levels based on the Asian range.
Execution Window Logic: Uses the 01:15 NY candle as a reference to validate potential reversals or continuation setups.
Conditional Entry System: Includes logic for limit order entries (buy or sell) at specific Fib levels, with reversal logic if price breaks structure before execution.
Risk Management: Entry orders are paired with dynamic SL and TP based on Fibonacci-based distances, maintaining a risk-reward ratio consistent with intraday strategies.
📊 Visual Features:
Asian session high/low/mid lines.
Fibonacci levels: Original (based on raw range) and Optimized (user-adjustable).
Session background coloring for Asia, Execution Window, and NY session.
Labels and lines for entry, SL, and TP targets.
Dynamic deletion of untriggered orders after execution window expires.
⚙️ How It Works:
The script calculates the Asian session range.
Projects Fibonacci levels from the range.
Waits for the 01:15 NY candle to close to validate a signal.
If valid, a limit entry order (BUY or SELL) is plotted at the selected level.
If price structure changes (e.g., breaks the high/low), reversal logic may activate.
If no trade is triggered, orders are cleared before the NY session.
🔔 Alerts:
Alerts trigger when a valid setup appears after 01:15 NY candle.
Optional alerts for order activation, SL/TP hit, or trade cancellation.
📝 Notes:
Intended for semi-automated or discretionary trading.
Best used on highly liquid markets like Forex majors or indices.
Script parameters include session times, Fib ratios, SL/TP settings, and reversal logic toggle.
Credits:
Developed by LANZ, this script merges traditional session-based analysis with Fibonacci tools and structured execution timing, offering a unique framework for morning volatility plays.
6 Moving Averages Difference TableIndicator Summary: 6 Moving Averages Difference Table (6MADIFF)
This TradingView indicator calculates and plots up to six distinct moving averages (MAs) directly on the price chart. Users have extensive control over each MA, allowing selection of:
Type: SMA, EMA, WMA, VWMA, HMA, RMA
Length: Any positive integer
Color: User-defined
Visibility: Can be toggled on/off
A core feature is the on-chart data table, designed to provide a quick overview of the relationships between the MAs and the price. This table displays:
$-MA Column: The absolute difference between the user-selected Input Source (e.g., Close, Open, HLC3) and the current value of each MA.
MA$ Column: The actual calculated price value of each MA for the current bar.
MA vs. MA Matrix: A grid showing the absolute difference between every possible pair of the calculated MAs (e.g., MA1 vs. MA2, MA1 vs. MA3, MA2 vs. MA5, etc.).
Customization Options:
Input Source: Select the price source (Open, High, Low, Close, HL2, HLC3, OHLC4) used for all MA calculations and the price difference column.
Table Settings: Control the table's visibility, position on the chart, text size, decimal precision for displayed values, and the text used for the column headers ("$-MA" and "MA$").
Purpose:
This indicator is useful for traders who utilize multiple moving averages in their analysis. The table provides an immediate, quantitative snapshot of:
How far the current price is from each MA.
The exact value of each MA.
The spread or convergence between different MAs.
This helps in quickly assessing trend strength, potential support/resistance levels based on MA clusters, and the relative positioning of short-term versus long-term averages.
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Bitcoin Monthly Seasonality [Alpha Extract]The Bitcoin Monthly Seasonality indicator analyzes historical Bitcoin price performance across different months of the year, enabling traders to identify seasonal patterns and potential trading opportunities. This tool helps traders:
Visualize which months historically perform best and worst for Bitcoin.
Track average returns and win rates for each month of the year.
Identify seasonal patterns to enhance trading strategies.
Compare cumulative or individual monthly performance.
🔶 CALCULATION
The indicator processes historical Bitcoin price data to calculate monthly performance metrics
Monthly Return Calculation
Inputs:
Monthly open and close prices.
User-defined lookback period (1-15 years).
Return Types:
Percentage: (monthEndPrice / monthStartPrice - 1) × 100
Price: monthEndPrice - monthStartPrice
Statistical Measures
Monthly Averages: ◦ Average return for each month calculated from historical data.
Win Rate: ◦ Percentage of positive returns for each month.
Best/Worst Detection: ◦ Identifies months with highest and lowest average returns.
Cumulative Option
Standard View: Shows discrete monthly performance.
Cumulative View: Shows compounding effect of consecutive months.
Example Calculation (Pine Script):
monthReturn = returnType == "Percentage" ?
(monthEndPrice / monthStartPrice - 1) * 100 :
monthEndPrice - monthStartPrice
calcWinRate(arr) =>
winCount = 0
totalCount = array.size(arr)
if totalCount > 0
for i = 0 to totalCount - 1
if array.get(arr, i) > 0
winCount += 1
(winCount / totalCount) * 100
else
0.0
🔶 DETAILS
Visual Features
Monthly Performance Bars: ◦ Color-coded bars (teal for positive, red for negative returns). ◦ Special highlighting for best (yellow) and worst (fuchsia) months.
Optional Trend Line: ◦ Shows continuous performance across months.
Monthly Axis Labels: ◦ Clear month names for easy reference.
Statistics Table: ◦ Comprehensive view of monthly performance metrics. ◦ Color-coded rows based on performance.
Interpretation
Strong Positive Months: Historically bullish periods for Bitcoin.
Strong Negative Months: Historically bearish periods for Bitcoin.
Win Rate Analysis: Higher win rates indicate more consistently positive months.
Pattern Recognition: Identify recurring seasonal patterns across years.
Best/Worst Identification: Quickly spot the historically strongest and weakest months.
🔶 EXAMPLES
The indicator helps identify key seasonal patterns
Bullish Seasons: Visualize historically strong months where Bitcoin tends to perform well, allowing traders to align long positions with favorable seasonality.
Bearish Seasons: Identify historically weak months where Bitcoin tends to underperform, helping traders avoid unfavorable periods or consider short positions.
Seasonal Strategy Development: Create trading strategies that capitalize on recurring monthly patterns, such as entering positions in historically strong months and reducing exposure during weak months.
Year-to-Year Comparison: Assess how current year performance compares to historical seasonal patterns to identify anomalies or confirmation of trends.
🔶 SETTINGS
Customization Options
Lookback Period: Adjust the number of years (1-15) used for historical analysis.
Return Type: Choose between percentage returns or absolute price changes.
Cumulative Option: Toggle between discrete monthly performance or cumulative effect.
Visual Style Options: Bar Display: Enable/disable and customize colors for positive/negative bars, Line Display: Enable/disable and customize colors for trend line, Axes Display: Show/hide reference axes.
Visual Enhancement: Best/Worst Month Highlighting: Toggle special highlighting of extreme months, Custom highlight colors for best and worst performing months.
The Bitcoin Monthly Seasonality indicator provides traders with valuable insights into Bitcoin's historical performance patterns throughout the year, helping to identify potentially favorable and unfavorable trading periods based on seasonal tendencies.
ICT Macro and Daye QT ShiftEST Vertical Lines - Auto DST Adjustment
Overview
This indicator draws customizable vertical lines at specific Eastern Time (EST/EDT) points throughout the trading day, automatically adjusting for daylight savings time. Designed for precision trading on 1-minute and 5-minute charts, it highlights key intraday moments when price action tends to accelerate.
Features
- **18 pre-configured NY session times** (09:50-15:45 ET)
- **Auto timezone conversion** - Always shows correct EST/EDT regardless of your local timezone
- **3 line styles** - Choose between solid/dashed/dotted lines
- **Clean labeling** - Optional time markers above each line
- **1m/5m optimized** - Perfect for scalpers and day traders
- **Visual alerts** - "TOUCH" labels when price interacts with lines
Inputs
| Parameter | Description | Default |
|-----------|-------------|---------|
| Line Times | Comma-separated HH:MM times | 09:50,10:10,...15:45 |
| Line Color | Line color | Black |
| Line Width | 1-5px thickness | 2 |
| Line Style | Solid/Dashed/Dotted | Solid |
| Show Labels | Display time markers | true |
How To Use
1. Apply to 1m or 5m charts
2. Lines appear automatically at specified EST times
3. Watch for price reactions at these key levels
4. Customize styles via indicator settings
Ideal For
- NY open/London close traders
- Earnings/News traders
- Breakout traders
- Market open/close strategies
Updates
v1.1 - Added line style customization
v1.0 - Initial release
Central Bank Assets YoY % with StdDev BandsCentral Bank Assets YoY % with StdDev Bands - Indicator Documentation
Overview
This indicator tracks the year-over-year (YoY) percentage change in combined central bank assets using a custom formula. It displays the annual growth rate along with statistical bands showing when the growth is significantly above or below historical norms.
Formula Components
The indicator is based on a custom symbol combining multiple central bank balance sheets:
Federal Reserve balance sheet (FRED)
Bank of Japan assets converted to USD (FX_IDC*FRED)
European Central Bank assets converted to USD (FX_IDC*FRED)
Subtracting Fed reverse repo operations (FRED)
Subtracting Treasury General Account (FRED)
Calculations
Year-over-Year Percentage Change: Calculates the percentage change between the current value and the value from exactly one year ago (252 trading days).
Formula: ((current - year_ago) / year_ago) * 100
Statistical Measures:
Mean (Average): The 252-day simple moving average of the YoY percentage changes
Standard Deviation: The 252-day standard deviation of YoY percentage changes
Display Components
The indicator displays:
Main Line: YoY percentage change (green when positive, red when negative)
Zero Line: Reference line at 0% (gray dashed)
Mean Line: Average YoY change over the past 252 days (blue)
Standard Deviation Bands: Shows +/- 1 standard deviation from the mean
Upper band (+1 StdDev): Green, line with breaks style
Lower band (-1 StdDev): Red, line with breaks style
Interpretation
Values above zero indicate YoY growth in central bank assets
Values below zero indicate YoY contraction
Values above the +1 StdDev line indicate unusually strong growth
Values below the -1 StdDev line indicate unusually severe contraction
Crossing above/below the mean line can signal shifts in central bank policy trends
Usage
This indicator is useful for:
Monitoring global central bank liquidity trends
Identifying unusual periods of balance sheet expansion/contraction
Analyzing correlations between central bank activity and market performance
Anticipating potential market impacts from changes in central bank policy
The 252-day lookback period (approximately one trading year) provides a balance between statistical stability and responsiveness to changing trends in central bank behavior.
CUSTOM PRO RANGE V2.0 with AlertsCore Functions
Tracks High/Low Ranges
Daily (DR) or Initial (IDR) ranges within custom time windows (e.g., 9:30 AM–4:00 PM).
Optional extended hours (e.g., overnight).
Visual Tools
Draws boxes/lines for range boundaries, midpoints, and opening prices.
Custom colors/styles for clarity.
Smart Alerts
Notifies when price breaks high/low/mid of the range.
Avoids spam with once-per-bar alerts.
Flexible Timeframes
Works for intraday, daily, or even quarterly ranges with minor tweaks.
🎯 Who It Helps
Day Traders: Spot breakouts/reversals.
Swing Traders: Identify key support/resistance.
Analysts: Study price behavior in specific sessions.
Sine Swing OscillatorThe Sine Swing Oscillator (SSO) is a custom momentum indicator that transforms price movement into a sine-based oscillator ranging from -1 to +1. It does this by measuring the deviation of the current price from a reference price, which is updated at fixed bar intervals. The price deviation is normalized using the Average True Range (ATR) over the same interval, then mapped through a sine transformation to create a bounded oscillator. This transformation helps identify cyclical price behavior in a consistent range.
The resulting sine values are smoothed using a Simple Moving Average (SMA), and a signal line is derived by applying an Exponential Moving Average (EMA) to the smoothed oscillator. Traders can use signal line crossovers, or moves through the zero line, to help identify potential entry or exit signals based on cyclical momentum shifts.
The oscillator and signal line are plotted in a separate pane, with user-configurable smoothing lengths and colors. The zero line is also included for reference.
Candle SequenceLooking to easily identify moments of strong market conviction? "Racha Velas" (or your chosen English name like "Consecutive Candles Streak") allows you to visualize clearly and directly sequences of consecutive bullish and bearish candles.
**Key Features:**
* **Real-time Counting:** Displays the number of consecutive candles directly on the chart.
* **Visual Customization:** Adjust the text size and color for optimal visualization.
* **Vertical Offset:** Control the position of the counter to avoid obstructions.
* **Maximum Streaks Table (Optional):** Visualize the largest bullish and bearish streaks found in the chart's history, useful for understanding volatility and price behavior.
* **Easy to Use:** Simply add the indicator to your chart and start analyzing.
This indicator is a valuable tool for traders looking to confirm trends, identify potential exhaustion points, or simply understand price dynamics at a glance. Give it a try and discover the market's streaks!
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¿Buscas identificar momentos de fuerte convicción del mercado? "Racha Velas" te permite visualizar de forma clara y directa las secuencias de velas consecutivas alcistas y bajistas.
**Características principales:**
* **Conteo en Tiempo Real:** Muestra el número de velas consecutivas directamente en el gráfico.
* **Personalización Visual:** Ajusta el tamaño y color del texto para una visualización óptima.
* **Offset Vertical:** Controla la posición del contador para evitar obstrucciones.
* **Tabla de Rachas Máximas (Opcional):** Visualiza las mayores rachas alcistas y bajistas encontradas en el historial del gráfico, útil para entender la volatilidad y el comportamiento del precio.
* **Fácil de Usar:** Simplemente añade el indicador a tu gráfico y comienza a analizar.
Este indicador es una herramienta valiosa para traders que buscan confirmar tendencias, identificar posibles agotamientos o simplemente entender la dinámica del precio en un vistazo. ¡Pruébalo y descubre las rachas del mercado!
Entropy [ScorsoneEnterprises]This indicator calculates the entropy of price log returns over a user-defined lookback period, providing insights into market complexity and unpredictability. Entropy measures the randomness or disorder in price movements, helping traders identify periods of high or low market uncertainty.
How It Works
The indicator computes the entropy of log returns (log(close/close )) using a histogram-based approach with customizable bins. Log returns are stored in an array of size N (lookback period), and entropy is calculated by:
Binning the returns into bins intervals based on their range.
Computing the probability distribution across bins.
Calculating entropy as -Σ(p * log(p)), where p is the probability of each bin.
A reference Simple Moving Average (SMA) of the entropy, with a separate lookback period (SMA_N), is plotted to highlight trends in market complexity. The entropy plot uses a gradient color scheme (red for lower entropy, teal for higher), while the SMA color shifts based on whether entropy is above (teal) or below (red) the SMA.
Key Features
Inputs:
Lookback Period (default: 50): Number of bars for calculating log returns.
Reference SMA Lookback Period (default: 100): Period for the entropy SMA.
Number of Bins (default: 20): Number of histogram bins for entropy calculation.
Plots:
Entropy: Gradient-colored line reflecting market randomness.
Reference SMA: Trend line to compare entropy against its average.
Interpretation
High Entropy: Indicates chaotic, unpredictable price movements, often during volatile or trendless markets.
Low Entropy: Suggests more predictable, ordered price behavior, often in trending or stable markets.
Compare entropy to its SMA to gauge whether current market complexity is above or below its recent average.
Usage
Use this indicator to assess market regimes. High entropy may signal choppy, range-bound conditions, while low entropy could indicate trending opportunities. Combine with price action or other indicators for confirmation.
Examples
We see on this PEPPERSTONE:COCOA chart that when entropy is low it signals a strong trend, either up or down. High entropy signals indecision and choppiness in the market. We can determine this by noticing when the value is above or below its recent average.
Entropy is used in high frequency trading often. It is a nice tool for lower time frames to determine how predictable and strong a trend is.
Inputs
Users can enter the lookback value for entropy, bin count, and the look back for the entropy moving average.
No tool is perfect, the Entropy value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
Long-Term VWAP Mean Reversion SDCACore Idea:
This indicator is designed to support Strategic Dollar Cost Averaging (SDCA) for Bitcoin using a cumulative VWAP-based mean reversion model. It helps long-term investors identify high-conviction buy zones and overbought conditions using statistical deviation from the cumulative VWAP. This indicator evaluates how much price is stretched from the true market average price, weighted by cumulative volume over time.
Core Concepts and Formulas:
Cumulative VWAP (Volume Weighted Average Price):
VWAP cumulative = ∑(Price×Volume) / ∑Volume
A long-term anchor that reflects the average dollar cost of all market participants across all candles. This version does not reset daily, unlike intraday VWAP.
VWAP Deviation % :
Deviation% = Price - VWAP cumulative / VWAP cumulative x 100
Shows how far current price has diverged from the long-term fair value.
Z-Score of VWAP Deviation:
Z= (Price−VWAP)−μ / σ (lookback period: default 200)
SDCA Multiplier Mapping:
*Keep in mind in my Z-Score system, -2 represents the overbought level (white horizontal line) and +2 represents oversold (cyan horizontal line) conditions. So the scores on the Y axis and Z-score in the table are reversed.
| Z-Score Range | SDCA Multiplier |
---------------------------------------------
| ≤ -2 | 0.25×
| -1 to +1 | 1.0×
| > +2 | 2.0×
The pink line plots this multiplier. It’s meant to control buy weight at each time step.
How to Use This for SDCA:
-Buy normally when the multiplier is 1.0× (Z-score between -1 and +1)
-Accelerate buying when Z-score is deeply negative (price far below VWAP)
-Slow or pause buying when Z-score is high (price far above VWAP)
-Use the stats panel to track current Z-score, VWAP level, deviation %, and multiplier
-Watch the red/blue backgrounds as visual confirmation of oversold/overbought zones
Inputs:
Z-Score Lookback Length:
Default: 200 but can be adjusted.
Visuals:
Z-Score Line (cyan): shows current standardized deviation from VWAP
Multiplier Line (bright pink): your SDCA intensity signal
Background Zones: cyan = oversold, white = overbought
Horizontal Lines: +2 and -2 standard deviation thresholds
Stats Panel (bottom right): live values for Z-score, multiplier, price, VWAP, and the deviation formula
Suited For:
-Long-term Bitcoin investors
-SDCA Systems
-Mean reversion systems
-Macro-level buy/sell planning
sideways market for strangleThis Pine Script is designed to identify **sideways or range-bound markets**, which are often ideal conditions for trading **options strangle strategies**. Here's a breakdown of what the script does:
---
### 🛠 **Purpose:**
To **detect low-volatility, sideways market conditions** where price is not trending strongly in either direction — suitable for **neutral options strategies like short strangles**.
---
### 📌 **Key Components:**
#### 1. **Inputs:**
- `RSI Length`: Default 14 — used for calculating the Relative Strength Index (RSI).
- `ADX Length`: Default 14 — used for calculating the Average Directional Index (ADX), DI+ (positive directional movement), and DI- (negative directional movement).
#### 2. **RSI Calculation:**
- `rsiValue` is calculated using the built-in `ta.rsi(close, rsiLength)`.
- A **sideways market** is expected when RSI is in the **40–60 range**, indicating lack of strong momentum.
#### 3. **ADX and Directional Indicators (DI+ and DI-):**
- `diPlus` and `diMinus` are calculated based on recent price movements and the True Range.
- `dx` (Directional Index) measures the strength of trend direction using the difference between DI+ and DI-.
- `adx` is a smoothed version of `dx` and represents **overall trend strength**.
#### 4. **Sideways Market Conditions:**
- **RSI Condition**: RSI is between 40 and 60.
- **ADX Condition**:
- `adx <= 25` → Weak or no trend.
- `adx < diPlus` and `adx < diMinus` → Confirms ADX is lower than directional components, reducing likelihood of a trending market.
#### 5. **Signal Plot:**
- A **green label below the bar** (`shape.labelup`) is plotted when both conditions are met.
- Indicates potential sideways market conditions.
---
### ✅ **Use Case:**
- This signal can help identify **low-volatility zones** suitable for **short strangles** or **iron condors**, where you profit from time decay while expecting the price to stay within a range.
True Range Orginal📌 Description – True Range Original
This indicator calculates the range (price spread) of the last N candles and displays it directly on the chart, along with suggested dynamic stop-loss levels based on recent volatility. Ideal for scalpers and day traders working on short timeframes such as 1-minute charts.
🔍 Features:
Calculates the difference between the highest high and lowest low of the last N bars (default: 15).
Plots a floating label with the current range value, updated every 5 candles.
Displays 4 dynamic stop levels:
For long positions:
Stop at 1x range (green line)
Stop at 1.5x range (light green line)
For short positions:
Stop at 1x range (red line)
Stop at 1.5x range (dark red line)
⚙️ Inputs:
Range period (number of bars)
Stop multiplier 1 (default: 1.0)
Stop multiplier 2 (default: 1.5)
📈 Usage:
This tool helps you size your stop-loss dynamically based on recent price action instead of using fixed values. It can be used alone or in combination with other tools like support/resistance, volume, or aggression indicators.
ICT Macro H1"H1 Candle Time Box" is a custom TradingView indicator that highlights a configurable time window surrounding the close of each 1-hour (H1) candle. The indicator draws a transparent box 15 minutes before and after each H1 candle close (by default), helping traders visualize time-based reaction zones.
🔍 Features:
Custom time window: Users can set how many minutes before and after the H1 close the box should appear.
Dynamic positioning: Boxes are drawn slightly above the candles to avoid overlap with price bars.
Live time labels: Each box displays its time range (e.g., "08:45 - 09:15") based on the start and end time of the zone.
Auto-cleaning: Only a limited number of recent boxes (default: 5) are shown, keeping the chart clean.
Requires 1-minute chart for precise timing.
This tool is especially helpful for intraday traders to identify areas of interest or market reactions before and after key hourly closes.
WaveTrend Matrix (1m-1w) – Custom ThresholdsA visual control panel for momentum exhaustion across ten key time-frames.
—
🧬 DNA
This is a fork of LazyBear’s original WaveTrend Oscillator .
The oscillator logic is 100 % intact; I simply stream the values into a compact table so that day- and swing-traders can see the “bigger picture” at a glance.
📈 What does it do?
Calculates WaveTrend on ten granularities: 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 1d, 1w.
Displays the current oscillator print in a color-coded matrix.
• Red = overbought (≥ high threshold)
• Green = oversold (≤ low threshold)
• Gray = neutral / in-range
All thresholds are user-adjustable.
Built on Pine v5, zero repainting, works on any symbol.
🛠 Parameters
Channel Length – WT “n1” (default 10)
Average Length – WT “n2” (default 21)
Red from – overbought cut-off (default +60)
Green under – oversold cut-off (default –60)
🚀 How to use it
1. Apply the indicator to your chart – no extra setup required.
2. Read the matrix top-down before every entry:
• Multiple deep-green rows → market broadly oversold → watch for longs.
• Multiple deep-red rows → market broadly overbought → watch for shorts or stay flat.
3. Combine with your trend filter (EMA-stack, VWAP, structure) to avoid counter-trend trades.
CYCLE BY RiotWolftradingDescription of the "CYCLE" Indicator
The "CYCLE" indicator is a custom Pine Script v5 script for TradingView that visualizes cyclic patterns in price action, dividing the trading day into specific sessions and 90-minute quarters (Q1-Q4). It is designed to identify and display market phases (Accumulation, Manipulation, Distribution, and Continuation/Reversal) along with key support and resistance levels within those sessions. Additionally, it allows customization of boxes, lines, labels, and colors to suit user preferences.
Main Features
Cycle Phases:
Accumulation (1900-0100): Represents the phase where large operators accumulate positions.
Manipulation (0100-0700): Identifies potential manipulative moves to mislead retail traders.
Distribution (0700-1300): The phase where large operators distribute their positions.
Continuation/Reversal (1300-1900): Indicates whether the price continues the trend or reverses.
90-Minute Quarters (Q1-Q4):
Divides each 6-hour cycle (360 minutes) into four 90-minute quarters (Q1: 00:00-01:30, Q2: 01:30-03:00, Q3: 03:00-04:30, Q4: 04:30-06:00 UTC).
Each quarter is displayed with a colored box (Q1: light purple, Q2: light blue, Q3: light gray, Q4: light pink) and labels (defaulted to black).
Support and Resistance Visualization:
Draws boxes or lines (based on settings) showing the high and low levels of each session.
Optionally displays accumulated volume at the highs and lows within the boxes.
Daily Lines and Last 3 Boxes:
How to Use the Indicator
Step 1: Add the Indicator to TradingView
Open TradingView and select the chart where you want to apply the indicator (e.g., UMG9OOR on a 5-minute timeframe, as shown in the screenshot).
Go to the Pine Editor (at the bottom of the TradingView interface).
Copy and paste the provided code.
Click Compile and then Add to Chart.
Step 2: Configure the Indicator
Click on the indicator name on the chart ("CYCLE") and select Settings (or double-click the name).
Adjust the options based on your needs:
Cycle Phases: Enable/disable phases (Accumulation, Manipulation, Distribution, Continuation/Reversal) and adjust their time slots if needed.
90-Minute Quarters: Enable/disable quarters (Q1-Q4).
Step 3: Interpret the Indicator
Identify Cycle Phases:
Observe the red boxes indicating the phases (Accumulation, Manipulation, etc.).
The high and low levels within each phase are potential support/resistance zones.
If volume is enabled, pay attention to the accumulated volume at highs and lows, as it may indicate the strength of those levels.
Use the 90-Minute Quarters (Q1-Q4):
The colored boxes (Q1-Q4) divide the day into 90-minute segments.
Each quarter shows the price range (high and low) during that period.
Use these boxes to identify price patterns within each quarter, such as breakouts or consolidations.
The labels (Q1, Q2, etc.) help you track time and anticipate potential moves in the next quarter.
Analyze Support and Resistance:
The high and low levels of each phase/quarter act as support and resistance.
Daily lines (if enabled) show key levels from the previous day, useful for planning entries/exits.
The "last 3 boxes below price" (if enabled) highlight potential support levels the price might target.
Avoid Manipulation:
During the Manipulation phase (0100-0700), be cautious of sharp moves or false breakouts.
Use the high/low levels of this phase to identify potential traps (as explained in your first question about manipulation candles).
Step 4: Trading Strategy
Entries and Exits:
Support/Resistance: Use the high/low levels of phases and quarters to set entry or exit points.
For example, if the price bounces off a Q1 support level, consider a buy.
Breakouts: If the price breaks a high/low of a quarter (e.g., Q2), wait for confirmation to enter in the direction of the breakout.
Volume: If accumulated volume is high near a key level, that level may be more significant.
Risk Management:
Place stop-loss orders below lows (for buys) or above highs (for sells) identified by the indicator.
Avoid trading during the Manipulation phase unless you have a specific strategy to handle false breakouts.
Time Context:
Use the quarters (Q1-Q4) to plan your trades based on time. For example, if Q3 is typically volatile in your market, prepare for larger moves between 03:00-04:30 UTC.
Step 5: Adjustments and Testing
Test on Different Timeframes: The indicator is set for a 5-minute timeframe (as in the screenshot), but you can test it on other timeframes (e.g., 1-minute, 15-minute) by adjusting the time slots if needed.
Adjust Colors and Styles: If the default colors are not visible on your chart, change them for better clarity.
---
📌 1. **Accumulation: Strong Institutional Activity**
- During the **accumulation phase, we see **high volume: 82.773K, which suggests strong buying interest**, likely from institutional players.
- This sets the base for the following upward move in price.
---
📌 2. **Manipulation: False Breakout with Lower Volume**
- Later, there's a manipulation phase where price breaks above previous highs, but the volume (71.814K) is **lower than during accumulation**.
- This implies that buyers are not as aggressive as before—no real demandbehind the breakout.
- It’s likely a bull trap, where smart money is selling into the breakout to exit their positions.
---
### 📌 3. Distribution: Weakness and Lack of Demand
- The market enters a distribution phase, and volume drops even further (only 7.914K).
- Price struggles to go higher, and you start seeing rejections at the top.
- This shows that demand is drying up, and smart money is offloading positions**—not accumulating anymore.
---
### 💡 Why Take the Short Here?
- Volume is not increasing with new highs—showing weak demand**.
- The manipulation volume is weaker than the accumulation volume, confirming the breakout was likely false.
- Structure starts to break down (Q levels falling), which confirms weakness.
- This creates a high-probability short setup:
- **Entry:** after confirmation of distribution and structural breakdown.
- **Stop loss:** above the manipulation high.
- **Target:** down toward previous lows or value zones.
---
### ✅ Conclusion
Since the manipulation volume failed to exceed the accumulation volume, the breakout lacked real strength. Combined with decreasing volume in the distribution phase, this indicates fading demand and supply taking control—which justifies entering a short position.
Schaff Trend Cycle (STC) - t0rdn3Schaff Trend Cycle (STC)
By t0rdn3 (original STC by , now with more descriptive naming)
Description
The Schaff Trend Cycle (STC) is a momentum-based oscillator that combines the speed of a fast EMA crossover with cyclical normalization. Developed by Doug Schaff, it identifies market turning points more responsively than MACD or RSI.
How It Works
1. EMA Difference : Calculates the difference between two EMAs of the source series (default: close).
2. Cycle Percentage : Normalizes that difference to a 0–100 range over the cycle period.
3. Smoothing : Applies exponential smoothing twice—first to the cycle percentage, then to its normalized cycles—to reduce noise.
4. Final STC Line : Produces a smoothed oscillator oscillating between 0 and 100.
Alerts
- "STC turned down above 75" : Fires once when STC makes a local peak above the upper threshold ( 75 ).
- "STC turned up below 25" : Fires once when STC makes a local trough below the lower threshold ( 25 ).
Inputs
Cycle Period : 12 — Lookback in bars for normalization
Fast EMA Length : 26 — Period of the fast EMA
Slow EMA Length : 50 — Period of the slow EMA
Smoothing Factor : 0.5 — Exponential smoothing coefficient (0–1)
Usage
Readings above 75 indicate an overbought cycle; readings below 25 indicate an oversold cycle. Crossings of the 50 midline can confirm trend direction:
- STC rising through 50 → bullish shift
- STC falling through 50 → bearish shift
Combine STC with price action or other trend filters to improve signal quality. You can adjust the cycle period and EMA lengths to match different timeframes or instruments.
Coinbase BTC Premium by BIGTAKERBTC Premium Gap Analysis: Binance, Coinbase, Upbit
This indicator provides real-time analysis and visualization of the premium gap between the Binance BTCUSDT price and the BTC prices on Coinbase (BTCUSD) and Upbit (BTCKRW).
Key Features
Coinbase Premium Gap
Measures the price difference between Coinbase and Binance as a percentage.
To improve visibility, the Coinbase premium is visually amplified by 10x.
Upbit Premium Gap
Calculates the premium by comparing Upbit's BTCKRW price (converted into USD using the real-time USDKRW exchange rate) against Binance BTCUSDT.
Dynamic Color Coding
Premiums above 0% are displayed in lime green, indicating positive premiums.
Premiums below 0% are displayed in red, indicating discounts.
Real-Time Labels
Displays real-time premium values for both Coinbase and Upbit on the right side of the chart.
Additional Notes
Upbit premiums are adjusted for the USD/KRW exchange rate to ensure accurate USD-based comparison.
The Coinbase premium is magnified visually (10x) to better capture minor movements, while the actual premium value remains correctly displayed.
The indicator is optimized for traders who monitor global BTC market price disparities across major exchanges.
How to Use
Quickly track global BTC price discrepancies across Binance, Coinbase, and Upbit.
Detect "Kimchi Premium" conditions in the Korean market through Upbit premiums.
Analyze buying and selling pressure in North American markets through Coinbase premiums.
