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.
Cycles
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.
Session + FVG + Order Blocks + EMAs1. Overall Purpose
This indicator combines four key functions into one pane to help you:
Highlight major market sessions (Asia, London, New York)
Plot Fair Value Gaps (FVG) and Order Blocks
Display up to four fully customizable Exponential Moving Averages (EMAs)
Shift all times via a configurable UTC offset
Together, these features let you see session activity zones, price imbalances, and underlying trend direction all at a glance.
2. Time Zone
Input: “Time Zone”
Set your chart’s UTC offset (e.g. “UTC+2”) so that each session box aligns with your local clock.
3. Market Sessions
Each session is drawn as a shaded rectangle labeled by name:
Session Default UTC Hours Color Toggle Visibility
Asia 00:00 – 08:15 Light blue fill ☑️ Show Asia session
London 09:00 – 12:00 Light green fill ☑️ Show London session
New York 14:30 – 18:00 Soft red fill ☑️ Show NY session
Enable or disable each session via its checkbox.
Adjust start/end times and the fill color for any session.
Border style and thickness are set in “Box Line Style” and “Box Line Thickness.”
4. Fair Value Gaps & Order Blocks
Controls for identifying imbalances and institutional zones:
Setting Description
Max Blocks Maximum number of gaps/order-blocks to display
Filter Gaps by % Only show gaps larger than this percentage
Lookback Bars How many bars back to scan for gaps and blocks
Bullish OB/FVG Color Fill color for bullish blocks & gaps
Bearish OB/FVG Color Fill color for bearish blocks & gaps
Show Fair Value Gaps Toggle visibility of FVG rectangles
Show Order Blocks Toggle visibility of Order Block rectangles
Fair Value Gaps mark small untraded price areas.
Order Blocks highlight previous zones of major buying or selling.
5. EMAs (Exponential Moving Averages)
Up to four EMAs can be displayed independently:
EMA Enable? Length (periods) Color
EMA 1 ☑️ Show EMA 1 20 Orange
EMA 2 ☑️ Show EMA 2 50 Blue
EMA 3 ☑️ Show EMA 3 100 Green
EMA 4 ☑️ Show EMA 4 200 Red
Tick the box to plot an EMA on your chart.
Change its length to match your strategy’s lookback.
Pick a color that stands out against your background.
6. Recommended Workflow
Set your Time Zone so session boxes align with your local trading hours.
Enable only the sessions you trade (e.g. deselect Asia if you focus on London & NY).
Tweak FVG/Order Block parameters:
Adjust Lookback Bars and Filter Gaps by % to fine-tune the number of zones.
Customize your EMAs (periods and colors) to suit your trend-following or mean-reversion approach.
Combine the layers: watch how price behaves within session boxes, around FVG/Order Blocks, and relative to your EMAs to plan entries and exits.
Leonid's Bitcoin Macro & Liquidity Regime Tracker🧠 Macro Overlay Score (Bitcoin Liquidity Regime Tracker)
This indicator combines the most important macroeconomic and on-chain inputs into a single unified score to help investors identify Bitcoin’s long-term cycle phases. Each input is normalized into a 0–100 score and blended using configurable weights to generate a dynamic, forward-looking macro regime tracker.
✅ Best used on the **Bitcoin All Time History Index with Weekly resolution** (`INDEX:BTCUSD`) for maximum historical context and signal clarity.
---
📈 Why Macro?
Macro liquidity conditions — interest rates, monetary expansion, dollar strength, credit risk — drive Bitcoin cycles . Risk assets like BTC thrive during periods of:
Monetary easing
Liquidity injections
Expansionary central bank policy
This overlay surfaces those periods *before* price follows. It captures cycle shifts in the business cycle, monetary policy, and investor sentiment — making it ideal for long-term allocators, macro-aligned investors, and cycle-focused BTC holders.
🔔 This is **not** designed for short-term or swing trading. It is optimized for **macro trend confirmation and regime awareness** — not fast entry/exit signals.
---
🔍 What It Tracks
Macro Inputs:
- 🏭 ISM 3M Trend (Business Cycle)
- 💹 CPI YoY (Inverted Inflation)
- 💵 M2 YoY + M2 Acceleration
- 🇨🇳 China M2 (Global Liquidity)
- 💱 DXY 3M Trend (USD Strength)
- 🏦 TGA & RRP YoY (Treasury / MMF Flows)
- 🏛 Fed Balance Sheet (WALCL)
- 💳 High Yield Spread (Credit Conditions)
- 💧 Net Liquidity Composite = WALCL – TGA – RRP
On-Chain Inputs:
- ⚠️ MVRV Ratio (Valuation Cycles)
- 🚀 Mayer Multiple Acceleration (200DMA Momentum)
---
🧩 How It Works
Each input is:
Normalized to a 0–100 score
Weighted by importance (fully configurable)
Combined into a **composite Macro Score**, then normalized across history
The chart will display:
🔷 A 0–100 **Macro Score Line**
🧭 **Cycle Phase classification**: Accumulation, Expansion, Distribution, Capitulation
📊 Optional **debug table** with all sub-scores
---
🧠 Interpreting the Signal
| Signal Type | Meaning |
|-------------------|---------------------------------------------|
| Macro Score ↑ | Liquidity improving → Bullish regime forming |
| Macro Score ↓ | Liquidity deteriorating → Caution warranted |
| Score < 40 & Rising | 🔵 Accumulation cycle likely beginning |
| Score > 70 & Falling | 🟡 Distribution / Macro exhaustion |
| Net Liquidity ↑ | Strong driver of BTC upside historically |
---
❓ FAQ
Q: Why did the Macro Score peak in March 2021, but Bitcoin topped in November?
> The indicator reflects **macro liquidity**, not price momentum. M2 growth slowed, DXY bottomed, and the Fed stopped expanding WALCL by Q1 2021 — all signs of macro exhaustion. BTC continued on **residual momentum**, but the smart money began exiting months earlier.
Q: What does the score range mean?
- 0–25 : Tight liquidity, unfavorable conditions
- 50 : Neutral environment
- 75–100 : Strong easing, liquidity surge
Q: Is this good for short-term signals?
> No. This is a **macro-level overlay**, best used for 3–12 month context shifts, not day trades.
Q: Can I adjust the weights?
> Yes. You can tune the influence of each input to match your thesis (e.g., overweight on-chain, or global liquidity).
Q: Do I need special data access?
> No. All symbols are public TradingView datasets (FRED, CryptoCap, etc.). Just use this on a BTC chart like `BTCUSD`.
---
✅ How to Use
- Load on **`INDEX:BTCUSD`**, set to **Weekly timeframe**
- Confirm long-term bottoms when score is low and rising (Accumulation → Expansion)
- Watch for tops when score is high and falling (Distribution → Capitulation)
- Combine with price structure, realized profit/loss, and market sentiment
---
🚀 If you're serious about understanding Bitcoin's macro regime, this is your alpha map. Share it, clone it, and build on it.
Chart Plotter & Scanner Table V1Script Summary: "Chart Plotter & Scanner Table V1"
This TradingView indicator is designed to give you a comprehensive analysis of the single stock, crypto, or asset currently displayed on your chart. It does this in two main ways:
Visual Signals on the Chart: It draws helpful information directly onto your price chart:
Trend Lines: Plots two moving average lines (one short-term, one long-term) to help you visualize the current price trend.
Buy/Sell Markers ("SIG NOW"): Shows triangle markers below the price (green for potential Buy) or above the price (red for potential Sell) when specific conditions related to price trend and momentum (RSI) are met.
Volume Activity Markers ("ALERT"): Displays small labels ("S" for Spike, "D" for Dump) when the trading volume is unusually high or low compared to its recent average, indicating potentially significant market activity.
Long-Term Signal Markers ("LTS"): Shows small shapes (circles, diamonds, squares) to indicate potential long-term Buy or Sell signals derived from analyzing price action on up to three different, higher timeframes (like Daily, Weekly, Monthly) that you choose.
Status Summary Table: It displays a neat table on your chart (you choose the corner) that acts like a dashboard, summarizing the key findings for the current asset:
Symbol & Price: Shows the ticker symbol and the latest price.
Price vs. Trend: Tells you if the current price is above both trend lines ("Above Both"), below both ("Below Both"), or in between ("Mixed"), with color-coding (Green/Red/Gray).
Momentum (RSI): Shows the current RSI value and its status ("Overbought", "Oversold", or "Neutral"), with color-coding (Red/Green/Gray).
Immediate Signal ("SIG NOW"): Displays the current Buy, Sell, or Neutral status based on the combined trend and momentum rules, with color-coding (Green/Red/Gray).
Volume Alert ("ALERT"): Shows if there's a volume Spike, Dump, or None, with color-coding (Orange/Purple/Gray).
Long-Term Signals (LTS): Shows the Buy, Sell, or Neutral status calculated from each of the three chosen higher timeframes, including the price at which the signal occurred on that timeframe, with color-coding (Green/Red/Gray).
Essentially, this script combines short-term trend and momentum analysis with volume activity monitoring and longer-term perspective signals, presenting the information clearly on your chart and in a summary table for quick assessment. It also allows you to create TradingView alerts based on these signals.
How to Adjust the Script Settings
You can customize how this script works through its "Settings" panel in TradingView. Here’s a breakdown of each section:
1. Indicator Settings (Chart Timeframe)
These settings control the main calculations done on your current chart's timeframe.
MA Source: Choose which price point (Close, Open, High, Low, etc.) the moving averages should be based on. (Default: Close)
Short MA Period: Set the number of bars for the shorter-term moving average. A smaller number makes it react faster to price changes. (Default: 20)
Long MA Period: Set the number of bars for the longer-term moving average. A larger number shows a smoother, longer-term trend. (Default: 50)
RSI Source: Choose which price point the RSI momentum calculation should use. (Default: Close)
RSI Period: Set the number of bars for the RSI calculation. (Default: 14)
RSI Overbought Level: The RSI level above which the asset is considered potentially "Overbought". (Default: 70)
RSI Oversold Level: The RSI level below which the asset is considered potentially "Oversold". (Default: 30)
SIG NOW RSI Buy Min: The minimum RSI value required (along with price being above MAs) to trigger a "SIG NOW" Buy signal. (Default: 55)
SIG NOW RSI Sell Max: The maximum RSI value required (along with price being below MAs) to trigger a "SIG NOW" Sell signal. (Default: 45)
Volume Lookback (LBV): How many bars to look back to calculate the average volume for the Spike/Dump alerts. (Default: 3)
Volume MA Type: The type of averaging method used for the volume calculation (EMA is generally preferred for responsiveness). (Default: EMA)
2. Volume Alert Settings
These control how sensitive the Volume Spike/Dump alerts are.
Volume Alert Sensitivity: Choose a preset sensitivity level:
"Normal": Standard thresholds for spike/dump detection.
"Sensitive": Requires less deviation from the average volume to trigger an alert.
"Highly Sensitive": Triggers alerts on even smaller volume deviations.
"Custom": Ignores the presets and uses the manual multipliers below.
Custom Spike Multiplier (>1): (Only used if Sensitivity is "Custom") How many times greater than the average volume the current volume must be to trigger a SPIKE. (e.g., 1.5 means 50% higher).
Custom Dump Multiplier (<1): (Only used if Sensitivity is "Custom") How many times smaller than the average volume the current volume must be to trigger a DUMP. (e.g., 0.7 means 30% lower).
3. Long Term Signal (LTS) Settings
These settings control the calculations for the three independent Long-Term Signals, which look at higher timeframes.
LTS Timeframe 1/2/3: Select the higher timeframes (e.g., 'D' for Daily, 'W' for Weekly, 'M' for Monthly) for each of the three LTS calculations.
LTS BB Source: The price source used for the Bollinger Band calculation on the LTS timeframes. (Default: Close)
LTS BB Length: The period (number of bars on the LTS timeframe) used for the Bollinger Band calculation. (Default: 20)
LTS BB StdDev: The standard deviation multiplier for the Bollinger Bands used in the LTS calculation. (Default: 2.0)
4. Plotting Settings
These control what is visually displayed on the price chart itself.
Plot MAs?: Checkbox to show or hide the two moving average lines.
Plot SIG NOW Markers?: Checkbox to show or hide the green/red triangle Buy/Sell markers.
Plot ALERT Markers?: Checkbox to show or hide the "S" / "D" volume Spike/Dump labels.
Plot LTS Markers?: Checkbox to show or hide the long-term signal markers (circles, diamonds, squares).
Plot LTS Markers For: Dropdown to choose whether to show markers for only LTS TF1, TF2, TF3, or "All" of them.
5. Table Settings
These control the appearance and content of the summary table.
Show Status Table?: Checkbox to show or hide the entire summary table.
Table Position: Choose which corner or side of the chart the table should appear on.
Decimal Places (Non-Price): How many decimal places to show for values like the RSI number in the table.
Table Text Size: Adjust the font size inside the table cells.
Setting Up Alerts:
This script creates the conditions for alerts. To actually receive notifications:
Click the "Alert" button (clock icon) in TradingView's top toolbar or right-click on the chart.
In the "Condition" dropdown, select the script name ("Chart Plotter & Scanner Table V1").
You will see a list of available alert conditions created by the script (e.g., "SIG NOW Buy Alert", "RSI Overbought Alert", "LTS TF1 Buy Alert", etc.). Choose the one you want.
Configure the rest of the alert settings (Options, Actions, Message) as desired.
Click "Create". Repeat for any other signals you want alerts for.
By adjusting these settings, you can fine-tune the indicator to match your trading style, the specific asset you are analyzing, and the timeframes you are interested in.
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
Yome Kill Zones ProPerfect for US30 Entry ## Yome Kill Zones Pro
**Yome Kill Zones Pro** is a precision trading tool designed for day traders and scalpers who focus on session-based setups, liquidity sweeps, and directional bias during the London–New York overlap.
---
### **Key Features**
- **Customizable Kill Zone Box**
- Marks session high/low from any user-defined time window (default: 6:00–11:30 UTC).
- **Swing Point Sweep Detection**
- Identifies significant highs/lows swept by price with momentum—ideal for supply/demand or S/R zones.
- **Independent Bias Kill Zone**
- Separate bias calculation window with adjustable start/end time to isolate market sentiment.
- **Bias Table (Always-On Display)**
- **Killzone Bias** – Shows direction based on price change during bias time.
- **Long-Term Bias** – Compares price vs. Open and EMA(50) from any selected timeframe (default: 15m).
- **Full Visual Customization**
- Editable sweep labels, line colors, line style, label visibility, and kill zone extensions.
---
### **How to Use**
1. **Set Your Session Times**
- Use the “Killzone Settings” to define high/low tracking time.
- Use “Bias Killzone Settings” to define when to calculate bias direction.
2. **Check the Bias Table**
- Use **Killzone Bias** for short-term session direction.
- Use **Long-Term Bias** to align with higher timeframe market structure.
3. **Watch for Liquidity Sweeps**
- Look for momentum-based breaks of swing highs/lows within your kill zone window.
- Use these levels to anticipate reversals, retests, or continuations.
4. **Customize It Your Way**
- Everything from line styles, sweep label visibility, thickness, and colors can be customized.
---
### **Best For**
- London & New York session scalpers
- Liquidity & structure-based traders
- Traders using ICT, Smart Money Concepts, or Wyckoff-style analysis
---
> **Tip:** Pair with volume or order block tools for enhanced sniper entries.
OTC COT / smart money Index 2.0 COT/ Smart money Indicator – Institutional Commitment & Position Sizing (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This indicator focuses on visualizing net positions held by commercials (smart money) and other key market participants, using data from the Commitments of Traders (COT) report. Inspired by Bernd Skorupinski’s institutional approach, the tool works hand-in-hand with the COT Index to provide a full picture of institutional sentiment and positioning strength.
👉 Core Functionality:
Displays net-long and net-short positions over time, helping traders understand how heavily institutions are positioned in a market.
Highlights historical extremes in net positions, which can act as warning signs or entry points when combined with technical analysis.
Supports customizable timeframes and asset selection (commodities, forex, indices) for maximum flexibility.
Best used in combination with the COT Index, offering a layered view of both relative extremes (COT Index) and absolute exposure (Net Positions).
The tool is designed to act as a contextual filter—it should complement technical setups rather than provide standalone trade signals.
📊 Applied Example – Gold Trade Using COT Net Position Analysis
To show the practical application, here’s a breakdown of a Gold (GC1!) trade that leveraged both COT Index and COT Net Positions to identify a high-probability setup.
Step 1️⃣ – Identifying Technical Structure:
The analysis started with classic price action review: Gold was approaching a significant demand zone, a well-established area that has historically triggered institutional buying.
Step 2️⃣ – COT Index Confirmation:
Upon reviewing the COT Index, the data revealed a 312-week buying extreme—the most aggressive commercial buying seen in over six years, signaling strong institutional accumulation.
Step 3️⃣ – COT Net Positions Validation:
Next, the COT Net Position Indicator showed that commercials were holding their largest net-long position in over 15 years—a rare and powerful signal of institutional conviction.
Step 4️⃣ – Divergence Check:
For added confirmation, divergence between commercials and retail traders was assessed:
✅ Commercials: Strongly net-long.
❌ Retail traders: Heavily net-short.
This clear divergence between smart money and retail sentiment further validated the setup.
Step 5️⃣ – Trade Execution:
With everything aligned:
Demand zone identified,
312-week COT Index extreme,
15-year high in net positions,
Divergence between commercials and retail,
…the trade was entered with a stop-loss placed just below the demand zone and a target set at a significant prior high. The result: a risk-reward ratio of 1:14.8, reflecting the strength and precision of the setup.
⚙️ What Sets This Tool Apart:
Provides deep insight into institutional exposure, showing both the magnitude of positions and how they evolve over time.
Enhances decision-making by cross-validating positioning extremes with technical levels.
Flexible design allows use across multiple asset classes and timeframes.
📌 Best Practices:
Always pair COT Net Position data with the COT Index to gauge both relative and absolute strength.
Use in conjunction with demand/supply zones or key technical levels for the strongest setups.
Look for divergence signals (institutions vs. retail) to confirm potential reversals.
Indicators Used in the Example:
This trade combined:
🧠 COT Net Position Indicator – to measure institutional exposure.
📊 COT Index – to identify positioning extremes.
📅 Seasonality Forecasting Tool – for time-based confirmation.
Together, these indicators provided a robust, multi-layered framework for high-confidence trading decisions.
OTC - COT Net positions 2.0 COT Net Position Indicator – Institutional Commitment & Position Sizing (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This indicator focuses on visualizing net positions held by commercials (smart money) and other key market participants, using data from the Commitments of Traders (COT) report. Inspired by Bernd Skorupinski’s institutional approach, the tool works hand-in-hand with the COT Index to provide a full picture of institutional sentiment and positioning strength.
👉 Core Functionality:
Displays net-long and net-short positions over time, helping traders understand how heavily institutions are positioned in a market.
Highlights historical extremes in net positions, which can act as warning signs or entry points when combined with technical analysis.
Supports customizable timeframes and asset selection (commodities, forex, indices) for maximum flexibility.
Best used in combination with the COT Index, offering a layered view of both relative extremes (COT Index) and absolute exposure (Net Positions).
The tool is designed to act as a contextual filter—it should complement technical setups rather than provide standalone trade signals.
📊 Applied Example – Gold Trade Using COT Net Position Analysis
To show the practical application, here’s a breakdown of a Gold (GC1!) trade that leveraged both COT Index and COT Net Positions to identify a high-probability setup.
Step 1️⃣ – Identifying Technical Structure:
The analysis started with classic price action review: Gold was approaching a significant demand zone, a well-established area that has historically triggered institutional buying.
Step 2️⃣ – COT Index Confirmation:
Upon reviewing the COT Index, the data revealed a 312-week buying extreme—the most aggressive commercial buying seen in over six years, signaling strong institutional accumulation.
Step 3️⃣ – COT Net Positions Validation:
Next, the COT Net Position Indicator showed that commercials were holding their largest net-long position in over 15 years—a rare and powerful signal of institutional conviction.
Step 4️⃣ – Divergence Check:
For added confirmation, divergence between commercials and retail traders was assessed:
✅ Commercials: Strongly net-long.
❌ Retail traders: Heavily net-short.
This clear divergence between smart money and retail sentiment further validated the setup.
Step 5️⃣ – Trade Execution:
With everything aligned:
Demand zone identified,
312-week COT Index extreme,
15-year high in net positions,
Divergence between commercials and retail,
…the trade was entered with a stop-loss placed just below the demand zone and a target set at a significant prior high. The result: a risk-reward ratio of 1:14.8, reflecting the strength and precision of the setup.
⚙️ What Sets This Tool Apart:
Provides deep insight into institutional exposure, showing both the magnitude of positions and how they evolve over time.
Enhances decision-making by cross-validating positioning extremes with technical levels.
Flexible design allows use across multiple asset classes and timeframes.
📌 Best Practices:
Always pair COT Net Position data with the COT Index to gauge both relative and absolute strength.
Use in conjunction with demand/supply zones or key technical levels for the strongest setups.
Look for divergence signals (institutions vs. retail) to confirm potential reversals.
Indicators Used in the Example:
This trade combined:
🧠 COT Net Position Indicator – to measure institutional exposure.
📊 COT Index – to identify positioning extremes.
📅 Seasonality Forecasting Tool – for time-based confirmation.
Together, these indicators provided a robust, multi-layered framework for high-confidence trading decisions.
OTC Seasonal forecasting tool 2.0Seasonality Forecasting Tool – Advanced Seasonal Pattern Analysis (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This script provides a structured way to analyze seasonal trends across financial markets, helping traders identify historical patterns that tend to repeat at specific times of the year. Inspired by Bernd Skorupinski’s institutional strategy, it has been refined with enhanced smoothing and customization options to improve adaptability across asset classes like commodities, forex, and indices.
👉 Core Functionality:
Analyzes historical price data over multiple lookback periods (5, 10, and 15 years) to calculate average seasonal performance.
Generates a smoothed seasonal curve that visually highlights periods of expected strength or weakness.
Allows users to customize lookback periods and adjust smoothing parameters, offering flexibility based on market type and volatility.
This tool is designed to be used as a contextual filter rather than a trade trigger—adding a layer of time-based confluence to enhance decision-making.
📊 Applied Example – Crude Oil Seasonality & Demand Zone Alignment
To demonstrate practical usage, here’s an example using Light Crude Oil Futures (CL1!) where seasonal tendencies and price structure aligned to create a high-probability setup.
Setup Steps:
1️⃣ Structural Context – Price Reaching a Demand Zone:
The market had been in a decline and approached a well-defined institutional demand area, which historically attracts buying interest.
2️⃣ Seasonality Analysis – Bullish Bias Identified:
The Seasonality Tool was applied using three distinct lookback windows:
5-year average 🟢
10-year average 🔴
15-year average 🔵
All three seasonal curves showed consistent upward trends during the late December to February period, historically signaling accumulation phases in crude oil markets.
3️⃣ Execution – Trade Setup:
With both:
Price action confirming a technical demand zone,
and seasonality indicating a strong historical bullish period,
a long position was taken targeting the next significant supply zone.
Result:
The trade unfolded as anticipated, with price rebounding strongly and delivering a risk-reward ratio of approximately 1:5.8—an outcome consistent with historical seasonal performance patterns.
⚙️ What Sets This Tool Apart:
Combines multi-timeframe seasonal data into a unified, easy-to-interpret visual output.
Includes custom smoothing algorithms to reduce noise, making the seasonal curves clearer and more reliable in fast-moving markets.
Offers flexibility to analyze not only commodities but also forex, indices, and other instruments influenced by recurring cycles (e.g., agricultural products, metals).
📌 Best Practices for Use:
Apply the tool alongside key technical zones (demand/supply) to find optimal trade timing.
Look for confluence across at least two of the seasonal curves (e.g., 5-year and 10-year averages agreeing on direction).
Use in combination with other market analysis tools—such as valuation indicators, COT data, or smart money flow—for full confirmation.
OTC valuation indicator 2.0Valuation Indicator – Relative Asset Valuation Tool (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This script is designed to analyze relative value shifts between two assets—such as Gold (GC1!) and the Dollar Index (DXY)—to identify overvalued and undervalued market conditions. It is inspired by principles from Bernd Skorupinski’s methodology but has been developed with custom adjustments and improvements to enhance flexibility and adaptability across various asset classes.
👉 How It Works:
The script calculates a normalized valuation index by measuring the percentage price deviation between a target asset (e.g., Gold) and a reference asset (e.g., Dollar Index).
A moving average baseline defines fair value, with deviations indicating potential overvaluation or undervaluation.
A volatility-adjusted filter dynamically smooths the output, reducing noise and improving signal accuracy across different market environments.
Parameters such as evaluation period and sensitivity are fully customizable, allowing traders to tailor the tool to commodities, forex, indices, or other asset pairs.
📊 Detailed Example – Gold & Dollar Index Setup:
To demonstrate how the indicator can be used, here’s an example based on a real market scenario:
Context : Identifying high-probability buy setups on Gold when undervaluation is confirmed relative to the Dollar Index.
Conditions :
1️⃣ Gold enters a significant demand zone (identified through traditional technical analysis).
2️⃣ The valuation index (from this script) drops below the -75 level, signaling strong undervaluation
In both October 2022 and October 2023, the valuation index dropped well below -75, and Gold was sitting at major demand zones. The result?
📈 Massive moves to the upside, with Risk-Reward ratios hitting 1:4 or more.
snapshot
This is a textbook Bernd Skorupinski strategy setup, combining macro fundamentals (valuation) with technical structure (demand zones).
This is not just theory — the same conditions repeated multiple times, delivering repeatable, high-probability trades.
This showcases how macro mispricing (Dollar overvalued, Gold undervalued) can be identified visually and quantitatively using the indicator, enabling traders to make more confident, data-backed entry decisions.
⚙️ What Makes It Unique:
Unlike standard correlation or spread indicators, this script combines dynamic volatility filtering with a multi-step comparative analysis to better handle market volatility and price extremes.
It offers flexible asset pairing, allowing traders to adapt the tool to various market scenarios beyond just Gold/DXY—such as Oil vs. Euro or Stocks vs. Forex.
📌 Recommended Use:
Best applied on weekly and daily charts.
Should be combined with other technical tools such as support/resistance levels or demand zones for added confirmation.
Not intended as a standalone signal; it works best as part of a broader market analysis strategy.
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.
Bitcoin Power Law Bayesian Fit with Residual HistogramTitle: Bayesian Bitcoin Power Law Indicator with Residuals Histogram
Description:
This Pine Script implements a Bitcoin (BTC) price indicator based on a power-law relationship between BTC price and time, modeled using Bayesian regression.
Bayesian regression is one of the most robust regression methods.
The indicator provides a robust framework for understanding BTC price trends, highlighting key statistical levels, based on deviation from the power law trend and visualizing the bimodal nature of BTC price behavior through a residual distribution histogram (distribution of the deviation from the Bayesian power law trend).
Features:
Power Law Model with Confidence Levels:
Models BTC price as a power-law function of time using Bayesian regression, displaying the median trendline.
Includes multiple confidence intervals to reflect statistical uncertainty.
Plots a support power-law line, set at 2 standard deviations below the median trend, serving as a critical lower bound for price expectations.
Bimodal Residual Histogram:
Displays a histogram in a lower panel, illustrating the distribution of model residuals (difference between actual BTC price and the power-law model) over a default 100-day window (user-configurable). This is one of the most innovative components of this indicator because it highlights the current shape of the distribution of recent deviations.
Highlights the bimodal nature of BTC price behavior, with two distinct regimes:
Core Power Law: Represents periods (approximately 2 years) when BTC price closely follows the power-law trend, typically when below the median power-law line.
Turbulent Flow BTC: Captures periods when BTC price is above the median power-law line, exhibiting more chaotic, bull-run behavior.
The histogram provides a range of possible prices based on the observed residual distribution, aiding in probabilistic price forecasting.
These analogies with fluid dynamics are part of the power law framework based on parallels in financial physics.
Purpose:
This indicator is designed for traders and analysts seeking to understand BTC price dynamics through a statistically grounded power-law model. The confidence levels and support line offer clear benchmarks for trend and support analysis, while the bimodal histogram provides insight into whether BTC is in a stable "Core Power Law" phase or a volatile "Turbulent Flow" phase, enabling better decision-making based on market regime.
Usage Notes:
Use the histogram to determine whether BTC is in the Core Power Law (below the power-law trend) or Turbulent Flow (above the trend) regime to contextualize price behavior.
Adjust the residual window (default 100 days) to analyze different timeframes for the distribution.
The support power-law line (2 standard deviations below) serves as a critical level for identifying potential price floors.
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.
ETH Growth | AlchimistOfCrypto⚠️ DISCLAIMER: This indicator's source code is kept private as it represents a first-of-its-kind innovation in algorithmic cycle detection and visualization for Ethereum. The mathematical models and proprietary algorithms powering this indicator are the result of extensive research and development.
🌈 ETH Growth Rainbow – Unveiling Ethereum's Logarithmic Growth Fields 🌈
"The ETH Growth Rainbow, engineered through advanced logarithmic mathematics, visualizes the probabilistic distribution of Ethereum's price evolution within a multi-cycle growth paradigm. This indicator employs principles from logarithmic regression where coefficients p001, p002, and p003 create mathematical boundaries that define Ethereum's long-term value progression. Our implementation features algorithmically enhanced rainbow visualization derived from Fast Fourier Transform (FFT) spectral analysis, creating a dynamic representation of Ethereum's logarithmic growth with adaptive color gradients that highlight critical cycle-based phase transitions in the asset's monetary evolution."
📊 Professional Trading Application
The ETH Growth Rainbow transcends traditional price prediction models with a sophisticated multi-band illumination system that reveals the underlying structure of Ethereum's monetary evolution. Scientifically calibrated across multiple 85-week cycles (detected through spectral analysis) and featuring seamless rainbow visualization, it enables investors to perceive Ethereum's position within its macro growth trajectory with unprecedented clarity.
- Cycle Detection Methodology 🔬
The 85-week Ethereum cycle was discovered through sophisticated Fast Fourier Transform (FFT) analysis:
- Logarithmic price returns extracted from historical Ethereum data
- FFT decomposition identifies dominant frequency components in price movements
- Signal amplitude analysis reveals the 85-week cycle as the most statistically significant periodicity
- Adaptive frequency filtering validates cycle consistency across multiple market phases
- Cycle duration rounded to nearest week for practical application
- Visual Theming 🎨
Scientifically designed rainbow gradient optimized for cycle pattern recognition:
- Violet-Blue: Lower value accumulation zones with highest mathematical growth potential
- Green: Fair value equilibrium zone representing the regression mean
- Yellow-Orange: Moderate overvaluation regions indicating potential resistance
- Red: Statistical extreme zones indicating mathematical cycle peaks
- Deep Red: New euphoria band (+6) capturing exceptional market extremes
- Cycle Visualization 🔍
- Precise cycle boundaries demarcating Ethereum's fundamental cycle events
- Adaptive band spacing based on mathematical cycle progression (p003 = 0.858)
- Multiple sub-cycle markers revealing the probabilistic nature of Ethereum's trajectory
- Initial cycle starting from 0.1639 (August 3, 2015) to preserve historical accuracy
🚀 How to Use
1. Identify Macro Position ⏰: Locate Ethereum's current price relative to regression bands
2. Understand Cycle Context 🎚️: Note position within the current 85-week cycle for time-based analysis
3. Assess Mathematical Value 🌈: Determine potential over/undervaluation based on band location
4. Adjust Investment Strategy 🔎: Modulate position sizing based on mathematical value assessment
5. Identify Cycle Phases ✅: Monitor band transitions to detect accumulation and distribution zones
6. Invest with Precision 🛡️: Utilize lower bands for strategic accumulation, upper bands for strategic reduction
7. Manage Risk Dynamically 🔐: Scale investment allocations based on mathematical cycle positioning
#ethereum #ETH #cryptocurrency #tradingview #technicalanalysis #logarithmicregression #rainbowchart #cryptotrading #tradingstrategy #priceaction #cryptoinvesting #ethanalysis #tradingbands #cryptoresearch #FFTanalysis #cyclicalanalysis #ethinvestment #ethusd #buyandsell #accumulation #macroindicator #valueanalysis #priceprediction #ethgrowth #cryptosignals #cyclicpatterns #mathematicaltrading #AI #smartmoney #cryptowhales
Multi 10 Symbol Scanner Table V1Script Summary: "Multi 10 Symbol Scanner Table V1"
This TradingView indicator acts as a powerful market scanner dashboard. Instead of plotting signals on your main price chart, its primary purpose is to display a table summarizing the technical status of up to 10 different assets (stocks, crypto, forex pairs, etc.) that you choose.
Think of it as a watchlist on steroids. It analyzes each symbol you enter based on a consistent set of rules you define and presents the results side-by-side in the table for quick comparison.
Here's what the table shows for each symbol you add:
Symbol: The ticker name of the asset being scanned.
Actual Price: The current market price of that asset.
Price vs. MAs: Indicates the short-term trend based on whether the price (on the chart's current timeframe) is above two moving average lines ("Above Both"), below them ("Below Both"), or in between ("Mixed"). This column is color-coded (Green/Red/Gray).
RSI Value: Shows the current RSI (Relative Strength Index) number, a measure of momentum (calculated on the chart's current timeframe).
RSI Status: Tells you if the RSI is currently "Overbought," "Oversold," or "Neutral" based on the levels you set. This column is color-coded (Red/Green/Gray).
SIG NOW: A combined "immediate signal" based on the Price vs. MAs and RSI Status conditions (calculated on the chart's current timeframe). It shows "BUY," "SELL," or "NEUTRAL" and is color-coded (Green/Red/Gray).
ALERT: Flags unusual trading volume activity (calculated on the chart's current timeframe). It shows "SPIKE" for high volume, "DUMP" for low volume, or "NONE." This column is color-coded (Orange/Purple/Gray).
LTS (TF1), LTS (TF2), LTS (TF3): These three columns show separate Long-Term Signals for each asset. Each signal is calculated independently using Bollinger Bands on a different, higher timeframe that you specify (e.g., Daily, Weekly, Monthly). It shows "BUY," "SELL," or "NEUTRAL" along with the price at which that signal occurred on that specific higher timeframe. These columns are also color-coded (Green/Red/Gray).
In essence: This script lets you monitor multiple assets simultaneously from one place, checking their short-term trend, momentum, volume activity, and longer-term signals across three different time perspectives, all updated in real-time within the table.
Important Note: This script only displays information in the table. It does not plot any lines or signals on your main chart, nor does it generate built-in TradingView alerts. It's purely a visual dashboard for scanning.
How to Adjust the Script Settings
You can customize the scanner through its "Settings" panel in TradingView. Here’s how to adjust each part:
1. Symbols (Enter Ticker IDs like 'BINANCE:BTCUSDT')
Symbol 1 to Symbol 10: These are the 10 slots where you enter the assets you want to scan.
How to Enter: You need the full Ticker ID, often including the exchange prefix. Examples: NASDAQ:AAPL, BINANCE:BTCUSDT, FX:EURUSD, NYSE:GME. You can find these using TradingView's symbol search.
Leaving Blank: If you don't need all 10 slots, just leave the extra ones blank. The table will only show rows for the symbols you've entered.
2. Indicator Settings (Chart Timeframe)
These settings define the rules for the analysis performed using the timeframe of the chart you currently have open. These rules are applied to all symbols in your list for the "Price vs MAs," "RSI," "SIG NOW," and "ALERT" columns.
MA Source: Choose which price point (Close, Open, High, Low, etc.) the moving averages should be based on. (Default: Close)
Short MA Period: Set the number of bars for the shorter-term moving average. A smaller number reacts faster. (Default: 20)
Long MA Period: Set the number of bars for the longer-term moving average. A larger number shows a smoother trend. (Default: 50)
RSI Source: Choose which price point the RSI momentum calculation should use. (Default: Close)
RSI Period: Set the number of bars for the RSI calculation. (Default: 14)
RSI Overbought Level: The RSI level above which an asset is considered "Overbought" in the table. (Default: 70)
RSI Oversold Level: The RSI level below which an asset is considered "Oversold" in the table. (Default: 30)
SIG NOW RSI Buy Min: The minimum RSI value required (along with price being above MAs) to show a "BUY" signal in the "SIG NOW" column. (Default: 55)
SIG NOW RSI Sell Max: The maximum RSI value required (along with price being below MAs) to show a "SELL" signal in the "SIG NOW" column. (Default: 45)
Volume Lookback (LBV): How many bars (on the chart's timeframe) to look back to calculate the average volume for the Spike/Dump alerts. (Default: 3)
Volume MA Type: The type of averaging method used for the volume calculation. (Default: EMA)
3. Volume Alert Settings
These control the sensitivity of the "ALERT" column (Spike/Dump detection) for all symbols.
Volume Alert Sensitivity: Choose a preset:
"Normal": Standard thresholds.
"Sensitive": Easier to trigger alerts.
"Highly Sensitive": Easiest to trigger alerts.
"Custom": Uses the manual multipliers below.
Custom Spike Multiplier (>1): (Only used if Sensitivity is "Custom") Volume must be this many times greater than average to trigger SPIKE. (e.g., 1.5 = 50% higher).
Custom Dump Multiplier (<1): (Only used if Sensitivity is "Custom") Volume must be this many times smaller than average to trigger DUMP. (e.g., 0.7 = 30% lower).
4. Long Term Signal (LTS) Settings
These settings control the calculations for the three independent "LTS" columns in the table. Each LTS column analyzes data from a specific higher timeframe you choose.
LTS Timeframe 1 / 2 / 3: Select the higher timeframes (e.g., 'D' for Daily, 'W' for Weekly, 'M' for Monthly) for each of the three LTS calculations. These will determine the data used for the corresponding LTS columns in the table.
LTS BB Source: The price source used for the Bollinger Band calculation on the selected LTS timeframes. (Default: Close)
LTS BB Length: The period (number of bars on the chosen LTS timeframe) used for the Bollinger Band calculation. (Default: 20)
LTS BB StdDev: The standard deviation multiplier for the Bollinger Bands used in the LTS calculations. (Default: 2.0)
5. Table Settings
These control the appearance of the scanner table itself.
Table Position: Choose which corner or side of the chart the table should appear on.
Decimal Places (Non-Price): How many decimal places to show for values like the RSI number in the table.
Table Text Size: Adjust the font size inside the table cells ("tiny", "small", "normal", "large", "huge").
By adjusting these settings, you can tailor the scanner to focus on the assets, timeframes, and technical conditions that matter most to your trading strategy. Remember to enter valid ticker symbols for the assets you want to track.
