Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description
Overview
The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes.
Performance Highlight:
In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior.
The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well.
## Key Innovation & Originality
This strategy introduces a unique **dual scoring system** approach:
- **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria
- **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing
Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions.
## Technical Foundation
### Optimized Indicator Parameters
The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns:
**MACD Configuration (3,10,3)**:
- Fast EMA: 3 periods (vs standard 12)
- Slow EMA: 10 periods (vs standard 26)
- Signal Line: 3 periods (vs standard 9)
- **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility
**RSI Configuration (21-period)**:
- Length: 21 periods (vs standard 14)
- Oversold: 30 level
- Extreme Oversold: 25 level
- **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment
**Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance.
### Scoring System Methodology
**Entry Score Components (Minimum 13 points required)**:
1. **RSI Signals** (max 5 points):
- RSI < 30: +2 points
- RSI < 25: +2 points
- RSI turning up: +1 point
2. **MACD Signals** (max 8 points):
- MACD below zero: +1 point
- MACD turning up: +2 points
- MACD histogram improving: +2 points
- MACD bullish divergence: +3 points
3. **Price Action** (max 4 points):
- Long lower wick (>50%): +2 points
- Small body (<30%): +1 point
- Bullish close: +1 point
4. **Pattern Recognition** (max 8 points):
- RSI bullish divergence: +4 points
- Quick recovery pattern: +2 points
- Reversal confirmation: +4 points
**Exit Score Components (Minimum 13 points required)**:
Uses inverse criteria to identify swing tops with similar weighting system.
## Risk Management Features
### Position Sizing & Risk Control
- **Single Position Strategy**: 100% equity allocation per trade
- **No Overlapping Positions**: Ensures focused risk management
- **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets
### Stop Loss & Take Profit Logic
- **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer
- **Risk-Based Take Profit**: Calculated using risk/reward ratio
- **Clean Exit Logic**: Prevents conflicting signals
## Default Settings Optimization
### Key Parameters (Optimized for MSTR/Bitcoin-style volatility):
- **Minimum Entry Score**: 13 (ensures high-conviction entries)
- **Minimum Exit Score**: 13 (prevents premature exits)
- **Risk/Reward Ratio**: 5.0 (accounts for volatility)
- **Lower Wick Threshold**: 50% (identifies true hammer patterns)
- **Divergence Lookback**: 8 bars (optimal for swing timeframes)
### Why These Defaults Work for MSTR:
1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation
2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets
3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks
4. **21-period RSI**: Reduces noise while maintaining sensitivity
## Visual Features
### Score Display System
- **Green Labels**: Entry scores ≥10 points (below bars)
- **Red Labels**: Exit scores ≥10 points (above bars)
- **Large Triangles**: Actual trade entries/exits
- **Small Triangles**: Reversal pattern confirmations
### Chart Cleanliness
- Indicators plotted in separate panes (MACD, RSI)
- TP/SL levels shown only during active positions
- Clear trade markers distinguish signals from actual trades
## Backtesting Specifications
### Realistic Trading Conditions
- **Commission**: 0.1% per trade
- **Slippage**: 3 points
- **Initial Capital**: $1,000
- **Account Type**: Cash (no margin)
### Sample Size Considerations
- Strategy designed for 100+ trade sample sizes
- Recommended timeframes: 4H, 1D for swing trading
- Optimal for trending/volatile markets
## Strategy Limitations & Considerations
### Market Conditions
- **Best Performance**: Trending markets with clear swings
- **Reduced Effectiveness**: Highly choppy, sideways markets
- **Volatility Dependency**: Optimized for moderate to high volatility assets
### Risk Warnings
- **High Allocation**: 100% position sizing increases risk
- **No Diversification**: Single position strategy
- **Backtesting Limitation**: Past performance doesn't guarantee future results
## Usage Guidelines
### Recommended Assets & Timeframes
- **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes
- **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.)
- **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments)
- **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping
### Timeframe Recommendations
- **Primary Scalping**: 5-minute and 15-minute charts
- **Active Monitoring**: 1-minute for precise entries
- **Swing Scalping**: 30-minute to 1-hour timeframes
- **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities)
## Technical Requirements
- **Pine Script Version**: v6
- **Overlay**: Yes (plots on price chart)
- **Additional Panes**: MACD and RSI indicators
- **Real-time Compatibility**: Confirmed bar signals only
## Customization Options
All parameters are fully customizable through inputs:
- Indicator lengths and levels
- Scoring thresholds
- Risk management settings
- Visual display preferences
- Date range filtering
## Conclusion
This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets.
The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets.
**Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
Cerca negli script per "采列VS新圣徒"
Big Move Follow-Through Tracker🚀 What This Indicator Does
Ever wondered if that sudden 5% pump in your favorite crypto will continue or just fade away? This powerful indicator automatically tracks every significant price move and tells you exactly what happened next - momentum continuation or mean reversion.
🎯 Key Features
📊 Smart Move Detection
Automatically identifies "big moves" based on your custom threshold (default 3%)
Uses ATR filtering to ensure moves are truly significant, not just normal volatility
Works on ANY timeframe and ANY crypto pair
🔍 Follow-Through Analysis
Tracks each big move for your specified number of bars (default 5)
Classifies outcomes as either Follow-Through (momentum continues) or Mean Reversion (price reverses)
Uses intelligent 2% thresholds to avoid noise and focus on meaningful moves
📈 Real-Time Statistics Dashboard
Live statistics table showing historical performance
Separate analysis for UP moves vs DOWN moves (crypto often behaves differently!)
Percentage breakdowns of follow-through vs reversion rates
Track total moves detected vs analyzed over time
🎨 Visual Clarity
Clear arrow signals when big moves are detected
Background highlighting during significant moves
Customizable display options - show/hide signals and stats as needed
🛠️ How to Use
Add to any crypto chart (works on BTC, ETH, altcoins, etc.)
Adjust the move threshold (3% for major coins, higher for smaller caps)
Set analysis timeframe (how many bars to track each move)
Watch the statistics build over time to understand your asset's behavior
💡 Trading Applications
For Momentum Traders:
High follow-through rates? → Consider riding the momentum
Trade in direction of big moves when statistics support it
For Mean Reversion Traders:
High reversion rates? → Look for fade opportunities
Counter-trade big moves when they historically reverse
For Risk Management:
Understand typical behavior after significant moves
Size positions based on historical follow-through probabilities
📋 Customizable Settings
Big Move Threshold: Adjust sensitivity (0.5% - 10%)
Analysis Period: How long to track each move (3-20 bars)
Display Options: Toggle signals and statistics table
Alert System: Get notified when big moves occur
🎲 What Makes This Different
Unlike simple momentum indicators, this tool:
✅ Quantifies actual outcomes with real statistics
✅ Adapts to each asset's unique volatility profile
✅ Separates up and down move behavior
✅ Provides actionable probability data
📊 Perfect For
Crypto day traders looking for edge identification
Swing traders wanting to understand momentum vs reversion tendencies
Risk managers needing probability-based position sizing
Strategy developers building data-driven trading systems
⚡ Quick Setup Tips
For Major Cryptos (BTC, ETH): Use 2-4% threshold
For Altcoins: Use 4-8% threshold
For Scalping: Use lower timeframes with 1-2% threshold
For Swing Trading: Use higher timeframes with 5%+ threshold
Multi Asset Comparative📊 Multi Asset Comparative – Compare Baskets of Cryptos Visually
This indicator allows you to compare the performance of two groups of cryptocurrencies (or any assets) over time, using a clean and intuitive chart.
Instead of looking at each asset separately, this tool gives you a global view by showing how one group performs relative to another — all displayed in the form of candlesticks.
🧠 What This Tool Is For
Markets constantly shift, and capital rotates between sectors or tokens. This script helps you visually track those shifts by answering a key question:
"Is this group of assets getting stronger or weaker compared to another group?"
For example:
Compare altcoins vs Bitcoin
Track the DeFi sector vs Ethereum
Analyze your custom portfolio vs the market
Spot moments when money flows from majors to smaller caps, or vice versa
🧩 How It Works (Simplified)
You select two groups of assets:
Group 1 (up to 20 assets) — the one you want to analyze
Group 2 (up to 5 assets) — your comparison baseline
The indicator then creates a single line of candles that represents the performance of Group 1 compared to Group 2. If the candles go up, it means Group 1 is gaining strength over Group 2. If the candles go down, it's losing ground.
This lets you see market dynamics in one glance, instead of switching charts or running calculations manually.
🚀 Why It's Unique
Unlike many indicators that just show data from one asset, this one provides a bird's-eye view of multiple assets at once — condensed into a simple visual ratio.
It’s:
Customizable (you choose the assets)
Visual and intuitive (no need to interpret tables or formulas)
Actionable (helps with trend confirmation, macro views, and market rotation)
Whether you're a swing trader, a macro analyst, or building your own strategy, this tool can help you spot opportunities hidden in plain sight.
✅ How to Use It
Choose your two groups of assets (e.g., altcoins vs BTC/ETH)
Watch the direction of the candles:
Uptrend = Group 1 gaining strength over Group 2
Downtrend = Group 1 weakening
Use it to confirm market shifts, anticipate rotations, or analyze sector strength
Advanced MA Crossover with RSI Filter
===============================================================================
INDICATOR NAME: "Advanced MA Crossover with RSI Filter"
ALTERNATIVE NAME: "Triple-Filter Moving Average Crossover System"
SHORT NAME: "AMAC-RSI"
CATEGORY: Trend Following / Momentum
VERSION: 1.0
===============================================================================
ACADEMIC DESCRIPTION
===============================================================================
## ABSTRACT
The Advanced MA Crossover with RSI Filter (AMAC-RSI) is a sophisticated technical analysis indicator that combines classical moving average crossover methodology with momentum-based filtering to enhance signal reliability and reduce false positives. This indicator employs a triple-filter system incorporating trend analysis, momentum confirmation, and price action validation to generate high-probability trading signals.
## THEORETICAL FOUNDATION
### Moving Average Crossover Theory
The foundation of this indicator rests on the well-established moving average crossover principle, first documented by Granville (1963) and later refined by Appel (1979). The crossover methodology identifies trend changes by analyzing the intersection points between short-term and long-term moving averages, providing traders with objective entry and exit signals.
### Mathematical Framework
The indicator utilizes the following mathematical constructs:
**Primary Signal Generation:**
- Fast MA(t) = Exponential Moving Average of price over n1 periods
- Slow MA(t) = Exponential Moving Average of price over n2 periods
- Crossover Signal = Fast MA(t) ⋈ Slow MA(t-1)
**RSI Momentum Filter:**
- RSI(t) = 100 -
- RS = Average Gain / Average Loss over 14 periods
- Filter Condition: 30 < RSI(t) < 70
**Price Action Confirmation:**
- Bullish Confirmation: Price(t) > Fast MA(t) AND Price(t) > Slow MA(t)
- Bearish Confirmation: Price(t) < Fast MA(t) AND Price(t) < Slow MA(t)
## METHODOLOGY
### Triple-Filter System Architecture
#### Filter 1: Moving Average Crossover Detection
The primary filter employs exponential moving averages (EMA) with default periods of 20 (fast) and 50 (slow). The exponential weighting function provides greater sensitivity to recent price movements while maintaining trend stability.
**Signal Conditions:**
- Long Signal: Fast EMA crosses above Slow EMA
- Short Signal: Fast EMA crosses below Slow EMA
#### Filter 2: RSI Momentum Validation
The Relative Strength Index (RSI) serves as a momentum oscillator to filter signals during extreme market conditions. The indicator only generates signals when RSI values fall within the neutral zone (30-70), avoiding overbought and oversold conditions that typically result in false breakouts.
**Validation Logic:**
- RSI Range: 30 ≤ RSI ≤ 70
- Purpose: Eliminate signals during momentum extremes
- Benefit: Reduces false signals by approximately 40%
#### Filter 3: Price Action Confirmation
The final filter ensures that price action aligns with the indicated trend direction, providing additional confirmation of signal validity.
**Confirmation Requirements:**
- Long Signals: Current price must exceed both moving averages
- Short Signals: Current price must be below both moving averages
### Signal Generation Algorithm
```
IF (Fast_MA crosses above Slow_MA) AND
(30 < RSI < 70) AND
(Price > Fast_MA AND Price > Slow_MA)
THEN Generate LONG Signal
IF (Fast_MA crosses below Slow_MA) AND
(30 < RSI < 70) AND
(Price < Fast_MA AND Price < Slow_MA)
THEN Generate SHORT Signal
```
## TECHNICAL SPECIFICATIONS
### Input Parameters
- **MA Type**: SMA, EMA, WMA, VWMA (Default: EMA)
- **Fast Period**: Integer, Default 20
- **Slow Period**: Integer, Default 50
- **RSI Period**: Integer, Default 14
- **RSI Oversold**: Integer, Default 30
- **RSI Overbought**: Integer, Default 70
### Output Components
- **Visual Elements**: Moving average lines, fill areas, signal labels
- **Alert System**: Automated notifications for signal generation
- **Information Panel**: Real-time parameter display and trend status
### Performance Metrics
- **Signal Accuracy**: Approximately 65-70% win rate in trending markets
- **False Signal Reduction**: 40% improvement over basic MA crossover
- **Optimal Timeframes**: H1, H4, D1 for swing trading; M15, M30 for intraday
- **Market Suitability**: Most effective in trending markets, less reliable in ranging conditions
## EMPIRICAL VALIDATION
### Backtesting Results
Extensive backtesting across multiple asset classes (Forex, Cryptocurrencies, Stocks, Commodities) demonstrates consistent performance improvements over traditional moving average crossover systems:
- **Win Rate**: 67.3% (vs 52.1% for basic MA crossover)
- **Profit Factor**: 1.84 (vs 1.23 for basic MA crossover)
- **Maximum Drawdown**: 12.4% (vs 18.7% for basic MA crossover)
- **Sharpe Ratio**: 1.67 (vs 1.12 for basic MA crossover)
### Statistical Significance
Chi-square tests confirm statistical significance (p < 0.01) of performance improvements across all tested timeframes and asset classes.
## PRACTICAL APPLICATIONS
### Recommended Usage
1. **Trend Following**: Primary application for capturing medium to long-term trends
2. **Swing Trading**: Optimal for 1-7 day holding periods
3. **Position Trading**: Suitable for longer-term investment strategies
4. **Risk Management**: Integration with stop-loss and take-profit mechanisms
### Parameter Optimization
- **Conservative Setup**: 20/50 EMA, RSI 14, H4 timeframe
- **Aggressive Setup**: 12/26 EMA, RSI 14, H1 timeframe
- **Scalping Setup**: 5/15 EMA, RSI 7, M5 timeframe
### Market Conditions
- **Optimal**: Strong trending markets with clear directional bias
- **Moderate**: Mild trending conditions with occasional consolidation
- **Avoid**: Highly volatile, range-bound, or news-driven markets
## LIMITATIONS AND CONSIDERATIONS
### Known Limitations
1. **Lagging Nature**: Inherent delay due to moving average calculations
2. **Whipsaw Risk**: Potential for false signals in choppy market conditions
3. **Range-Bound Performance**: Reduced effectiveness in sideways markets
### Risk Considerations
- Always implement proper risk management protocols
- Consider market volatility and liquidity conditions
- Validate signals with additional technical analysis tools
- Avoid over-reliance on any single indicator
## INNOVATION AND CONTRIBUTION
### Novel Features
1. **Triple-Filter Architecture**: Unique combination of trend, momentum, and price action filters
2. **Adaptive Alert System**: Context-aware notifications with detailed signal information
3. **Real-Time Analytics**: Comprehensive information panel with live market data
4. **Multi-Timeframe Compatibility**: Optimized for various trading styles and timeframes
### Academic Contribution
This indicator advances the field of technical analysis by:
- Demonstrating quantifiable improvements in signal reliability
- Providing a systematic approach to filter optimization
- Establishing a framework for multi-factor signal validation
## CONCLUSION
The Advanced MA Crossover with RSI Filter represents a significant evolution of classical moving average crossover methodology. Through the implementation of a sophisticated triple-filter system, this indicator achieves superior performance metrics while maintaining the simplicity and interpretability that make moving average systems popular among traders.
The indicator's robust theoretical foundation, empirical validation, and practical applicability make it a valuable addition to any trader's technical analysis toolkit. Its systematic approach to signal generation and false positive reduction addresses key limitations of traditional crossover systems while preserving their fundamental strengths.
## REFERENCES
1. Granville, J. (1963). "Granville's New Key to Stock Market Profits"
2. Appel, G. (1979). "The Moving Average Convergence-Divergence Trading Method"
3. Wilder, J.W. (1978). "New Concepts in Technical Trading Systems"
4. Murphy, J.J. (1999). "Technical Analysis of the Financial Markets"
5. Pring, M.J. (2002). "Technical Analysis Explained"
FACTOR MONITORThe Factor Monitor is a comprehensive designed to track relative strength and standard deviation movements across multiple market segments and investment factors. The indicator calculates and displays normalized percentage moves and their statistical significance (measured in standard deviations) across daily, 5-day, and 20-day periods, providing a multi-timeframe view of market dynamics.
Key Features:
Real-time tracking of relative performance between various ETF pairs (e.g., QQQ vs SPY, IWM vs SPY)
Standard deviation scoring system that identifies statistically significant moves
Color-coded visualization (green/red) for quick interpretation of relative strength
Multiple timeframe analysis (1-day, 5-day, and 20-day moves)
Monitoring of key market segments:
Style factors (Value, Growth, Momentum)
Market cap segments (Large, Mid, Small)
Sector relative strength
Risk factors (High Beta vs Low Volatility)
Credit conditions (High Yield vs Investment Grade)
The tool is particularly valuable for:
Identifying significant factor rotations in the market
Assessing market breadth through relative strength comparisons
Spotting potential trend changes through statistical deviation analysis
Monitoring sector leadership and market regime shifts
Quantifying the magnitude of market moves relative to historical norms
Tops & Bottoms by Volume [SS]Hey everyone,
Releasing this indicator that helps you time entries by alerting to potential tops and bottoms in the market.
Background to the indicator:
I was playing around with things that signalled reversals / tops and bottoms in SPSS and R using Pivot Points to mark tops and bottoms. Happened to come across a generally statistically significant relationship between sell to buy volume that was tracked over 10 to 50 candles back and pivot highs and pivot lows.
So I put it into a beta version of an indicator to see how it looked and was a bit surprised.
Since then, I have went back and narrowed down the details of what works/what doesn't work and this is the tentative result!
What it does / How to Use:
It tracks the cumulative buy vs sell volume. Buy volume is cumulated as close > open (or green candles) and sell is open > close (or red candles).
It then cumulates this over a user-defined period (defaulted to 14). It then looks back to see the highest vs lowest areas of sell and buy volume and makes determinations based on this relationship.
The relationship was determined by me using my own analysis and programmed into the indicators algorithm (using highest vs lowest function in pine).
It will plot areas of potential reversal to the upside as green on the histogram or red for a downside reversal. Once this becomes significant enough to signal an actual bottom or top, it will then change the SMA colour from white to green (for bottom) or red (for top).
Your entries generally should be once the SMA turns back to white. So from green to white, you would enter long or inverse for red to white (enter short).
Settings and Customizability:
Here are the key points to keep in mind if you are using this indicator:
Your lookback length should be between 10 to 50. I have left it open for you to modify it below and above this lookback period; however, this is the major periods deemed to be significant in identifying tops and bottoms. Thus, I advise against operating outside of those parameters.
You can toggle between smoothed look or historgram with SMA. The strength in this indicator comes from using the SMA and watching the SMA for signals of reversals, so if you want to filter out the background noise, you can simply look at the plotted SMA. If you want a more responsive indication of impending reversals, leave the smoothed option off and view the histogram in conjunction with the SMA.
The indicator will change the candle colour to red for bearish reversal and green to bullish reversal. This is based on the SMA. You can toggle this off and/or on as desired.
It is recommended to leave ETH (extended trading hours) turned off and RTH turned on.
Please read the instructions carefully.
If you require further assistance, I have posted a tutorial video.
Please be sure you are reading and/or watching carefully.
If you have questions, please feel free to post them below. But bear in mind I likely will not respond if it is already addressed in the description above (this happens often).
Also, feel free to leave your comments or suggestions below as well.
Thanks for checking this out. If you are interested in volume based trading, I suggest also checking out my Buyer to Seller volume indicator which cumulates total buying vs selling volume over a designated lookback period. Both of these used in conjunction are very powerful tools for volume based traders! ( Available here )
NOTE:
The boxes drawn in the chart are my own for demonstration purposes. I unfortunately cannot get the indicator to overlay the boxes on the chart in a separate viewing pane. That is why I opted to use the barcolor function to change the candle color instead :-).
Thanks again everyone and safe trades!
ATRvsDTR + ADR Zone + SSS50%This Script is to be used for intra day as far as the adr zones. The adr zones are used as support and resistance but also can be used to determine whether the stock is breaking out or not. Also being that the adr zones are calculated using a 5 or 10 day period unless you change the settings, and are set when price opens. It does really help you know whether a stock is moving more than it does on average to me it just signifies its directional. So I added the atr vs dtr so you can see what a stock moves on average versus what it has moved today.
The atr period is calculated based on the daily period unless you change the settings. I added to the original script 3 more percentages the atr vs dtr will change as it goes higher so that you can be aware when the stock is getting closer to moving 100% of its atr. Even though a stock breaks above or below the adr that doesn't mean it has moved more than it normally moves.
I also have the weekly open on the script as I trade the strat and I want to know, at what price the the week will change from bearish to bullish and vice versa. So that I can understand the trend when I am trading intraday.
The 50% lines were added for Sara strat snipers 50% rule and you can change the timeframes on them. This is used to know whether a candle will go 3. This also can help with retracements vs reversals, because in traditional technical analysis 50% is around where people start think its a reversal more so than a retracement.
I believe the script will be very help as it can show you price being directional but can also let you know when the stock is getting close to moving more than it normally has or if it has moved more than it normally has. As well as being able to see if something is a retracement vs a reversal. I trade TheStrat strategy so this can be very helpful in that regard
The 50% retracement levels are default 1h and daily. You can change them and whether or not they show
In the example chart you can see we are below weekly open which is bearish and you can also see where price reverses out of the upper adr zone. As well as how much of the atr we have moved on this day in time.
Bitcoin Block Height (Total Blocks)Bitcoin Block Height by RagingRocketBull 2020
Version 1.0
Differences between versions are listed below:
ver 1.0: compare QUANDL Difficulty vs Blockchain Difficulty sources, get total error estimate
ver 2.0: compare QUANDL Hash Rate vs Blockchain Hash Rate sources, get total error estimate
ver 3.0: Total Blocks estimate using different methods
--------------------------------
This indicator estimates Bitcoin Block Height (Total Blocks) using Difficulty and Hash Rate in the most accurate way possible, since
QUANDL doesn't provide a direct source for Bitcoin Block Height (neither QUANDL:BCHAIN, nor QUANDL:BITCOINWATCH/MINING).
Bitcoin Block Height can be used in other calculations, for instance, to estimate the next date of Bitcoin Halving.
Using this indicator I demonstrate:
- that QUANDL data is not accurate and differ from Blockchain source data (industry standard), but still can be used in calculations
- how to plot a series of data points from an external csv source and compare it with another source
- how to accurately estimate Bitcoin Block Height
Features:
- compare QUANDL Difficulty source (EOD, D1) with external Blockchain Difficulty csv source (EOD, D1, embedded)
- show/hide Quandl/Blockchain Difficulty curves
- show/hide Blockchain Difficulty candles
- show/hide differences (aqua vertical lines)
- show/hide time gaps (green vertical lines)
- count source differences within data range only or for the whole history
- multiply both sources by alpha to match before comparing
- floor/round both matched sources when comparing
- Blockchain Difficulty offset to align sequences, bars > 0
- count time gaps and missing bars (as result of time gaps)
WARNING:
- This indicator hits the max 1000 vars limit, adding more plots/vars/data points is not possible
- Both QUANDL/Blockchain provide daily EOD data and must be plotted on a daily D1 chart otherwise results will be incorrect
- current chart must not have any time gaps inside the range (time gaps outside the range don't affect the calculation). Time gaps check is provided.
Otherwise hardcoded Blockchain series will be shifted forward on gaps and the whole sequence become truncated at the end => data comparison/total blocks estimate will be incorrect
Examples of valid charts that can run this indicator: COINBASE:BTCUSD,D1 (has 8 time gaps, 34 missing bars outside the range), QUANDL:BCHAIN/DIFF,D1 (has no gaps)
Usage:
- Description of output plot values from left to right:
- c_shifted - 4x blockchain plotcandles ohlc, green/black (default na)
- diff - QUANDL Difficulty
- c_shifted - Blockchain Difficulty with offset
- QUANDL Difficulty multiplied by alpha and rounded
- Blockchain Difficulty multiplied by alpha and rounded
- is_different, bool - cur bar's source values are different (1) or not (0)
- count, number of differences
- bars, total number of bars/data points in the range
- QUANDL daily blocks
- Blockchain daily blocks
- QUANDL total blocks
- Blockchain total blocks
- total_error - difference between total_blocks estimated using both sources as of cur bar, blocks
- number_of_gaps - number of time gaps on a chart
- missing_bars - number of missing bars as result of time gaps on a chart
- Color coding:
- Blue - QUANDL data
- Red - Blockchain data
- Black - Is Different
- Aqua - number of differences
- Green - number of time gaps
- by default the indicator will show lots of vertical aqua lines, 138 differences, 928 bars, total error -370 blocks
- to compare the best match of the 2 sources shift Blockchain source 1 bar into the future by setting Blockchain Difficulty offset = 1, leave alpha = 0.01 =>
this results in no vertical aqua lines, 0 differences, total_error = 0 blocks
if you move the mouse inside the range some bars will show total_error = 1 blocks => total_error <= 1 blocks
- now uncheck Round Difficulty Values flag => some filled aqua areas, 218 differences.
- now set alpha = 1 (use raw source values) instead of 0.01 => lots of filled aqua areas, 871 differences.
although there are many differences this still doesn't affect the total_blocks estimate provided Difficulty offset = 1
Methodology:
To estimate Bitcoin Block Height we need 3 steps, each step has its own version:
- Step 1: Compare QUANDL Difficulty vs Blockchain Difficulty sources and estimate error based on differences
- Step 2: Compare QUANDL Hash Rate vs Blockchain Hash Rate sources and estimate error based on differences
- Step 3: Estimate Bitcoin Block Height (Total Blocks) using different methods in the most accurate way possible
QUANDL doesn't provide block time data, but we can calculate it using the Hash Rate approximation formula:
estimated Hash rate/sec H = 2^32 * D / T, where D - Difficulty, T - block time, sec
1. block time (T) can be derived from the formula, since we already know Difficulty (D) and Hash Rate (H) from QUANDL
2. using block time (T) we can estimate daily blocks as daily time / block time
3. block height (total blocks) = cumulative sum of daily blocks of all bars on the chart (that's why having no gaps is important)
Notes:
- This code uses Pinescript v3 compatibility framework
- hash rate is in THash/s, although QUANDL falsely states in description GHash/s! THash = 1000 GHash
- you can't read files, can only embed/hardcode raw data in script
- both QUANDL and Blockchain sources have no gaps
- QUANDL and Blockchain series are different in the following ways:
- all QUANDL data is already shifted 1 bar into the future, i.e. prev day's value is shown as cur day's value => Blockchain data must be shifted 1 bar forward to match
- all QUANDL diff data > 1 bn (10^12) are truncated and have last 1-2 digits as zeros, unlike Blockchain data => must multiply both values by 0.01 and floor/round the results
- QUANDL sometimes rounds, other times truncates those 1-2 last zero digits to get the 3rd last digit => must use both floor/round
- you can only shift sequences forward into the future (right), not back into the past (left) using positive offset => only Blockchain source can be shifted
- since total_blocks is already a cumulative sum of all prev values on each bar, total_error must be simple delta, can't be also int(cum()) or incremental
- all Blockchain values and total_error are na outside the range - move you mouse cursor on the last bar/inside the range to see them
TLDR, ver 1.0 Conclusion:
QUANDL/Blockchain Difficulty source differences don't affect total blocks estimate, total error <= 1 block with avg 150 blocks/day is negligible
Both QUANDL/Blockchain Difficulty sources are equally valid and can be used in calculations. QUANDL is a relatively good stand in for Blockchain industry standard data.
Links:
QUANDL difficulty source: www.quandl.com
QUANDL hash rate source: www.quandl.com
Blockchain difficulty source (export data as csv): www.blockchain.com
RedK_Supply/Demand Volume Viewer v1Background
============
VolumeViewer is a volume indicator, that offers a simple way to estimate the movement and balance (or lack of) of supply & demand volume based on the shape of the price bar. i put this together few years ago and i have a version of this published for another platform under different names (Directional Volume, BetterVolume) in case you come across them
what is V.Viewer
=====================
The idea here is to find a "simple proxy" for estimating the demand or supply portions of a volume bar - these 2 forces have the potential to affect the current price trend so we want an easy way to track them - or to understand if a stock is in accumulation or distribution - we want to do this without having access to Level II or bid/ask data, and without having to get into the complexity of exploring the lower timeframe price & volume data
- to achieve that, we depend on a simple assumption, that the volume associated with an up move is "demand" and the volume associated with a down move is "Supply". so we basically extrapolate these supply and demand values based on how the bar looks like - a full "green" price bar / candle will be considered 100% demand, and a full "red" price bar will be considered 100% supply - a bar that opens and closes at the same level will be 50/50 split between supply & demand.
- you may say this is a "too simple" of an assumption to make, but believe me, it works :) at least at the basic scenario we need here: i'm just exploring the volume movement and finding key levels - and it provides a good improvement compared to the classic way we see volume on a chart - which is still available here in VolumeViewer.
in all cases, i consider this to be work in progress, so i'd welcome any ideas to improve (without getting too complicated) - there's already a host of great volume-based indicators that will do the multi timeframe drill down, but that's not my scope here.
Technical Jargon & calculation
===========================
1. first we calculate a score % for the volume portion that is considered demand based on the bar shape
skip this part if it sounds too technical => if you're into coding indicators, you would probably know there are couple of different concepts for that algorithm - for example, the one used in Balance Of Power formula - which i'm a big fan of - but the one i use here is different. (how?) this is my own, ant it simply applies double weight for the "wick" parts of a price bar compared to the "body of the bar" -- i did some side-by-side comparison in past and decided this one works better. you can change it in the code if you like
2. after calculating the Bull vs Bears portion of volume, we take a moving average of both for the length you set, to come up with what we consider to be the Demand vs Supply - as usual, i use a weighted moving average (WMA) here.
3. the balance or net volume between these 2 lines is calculated, then we apply a final smoothing and that's the main plot we will get
4. being a very visual person, i did my best to build up the visuals in the correct order - then also to ensure the "study title" bar is properly organized and is simple and useful (Full Volume, Supply, Demand, Net Volume).
- i wish there was a way in Pine to hide a value that i still need to visually plot but don't want it showing its value on the study title bar, but couldn't find it. so the last plot value is repeated twice.
How to use
===========
- V.Viewer is set up to show the simplified view by default for simplicity. so when you first add it to a chart, you will get only the supply vs demand view you can see in the middle pane in the above chart
- Optional / detailed mode: go into the settings, and expose all other plots, you will be able to add the classic volume histogram, and the Supply / Demand lines - note these 2 lines will be overlay-ed on top of each other - this provides an easy way to see who is in control - especially if you change the display of these 2 lines into "area" style. This is what is showing in the lower pane in the above chart.
** Exploring Key Price Levels
- the premise is, at spots where there's big lack of balance, that's where to expect to find key price levels (support / resistance) and these price levels will come into play in future so can be used to set entry / exit targets for our trades - see the example in the AAPL chart where you can easily locate these "balance or reversal levels" using the tops/bottoms/zero-crossings from the Net Volume line
** Use for longer-term Price Analysis
- we can also use this simple indicator to gain more insights (at a high level) of the price in terms of accumulation vs distribution and if the sellers or buyers are in control - for example, in the above AAPL chart, V.Viewer tells us that buyers have been in control since October 19 - even during the recent drop, demand continued to be in play - compare that to DIS chart below for the same period, where it shows that the market was dumping DIS thru the weakness. DIS was bleeding red most of the time
Final thoughts
=============
- V.Viewer is an attempt to enhance the way we see and use Volume by leveraging the shape of the price bar to estimate volume supply & demand - and the Net between the 2
- it will work for stocks and other instruments as long as there's volume data
- note that V.Viewer does not track trend. each bar is taken in isolation of prior bars - the price may be going down and V.Viewer is showing supply going up (absorption scenario?) - so i suggest you do not use it to make decisions without consulting other trend / momentum indicators - of course this is a possible improvement idea, or can be implemented in another indicator, add in trend somehow, or maybe think of making this a +100 / -100 Oscillator .. feel free to play with these thoughts
- all thoughts welcome - if this is useful to you in your trading, please share with other trades here to learn from each other
- the code is commented - please feel free to use it as you like, or build things on top of it - but please continue to credit the author of this code :)
good luck!
-
Chiki-Poki BFXLS Longs Shorts Abs Normalized Volume Pro by RRBChiki-Poki BFXLS Longs vs Shorts Absolute Normalized Volume Value Pro by RagingRocketBull 2018
Version 1.0
This indicator displays Longs vs Shorts in a side by side graph, shows volume's absolute price value and normalized volume of Longs/Shorts for the current asset. This allows for more accurate L/S comparisons (like a log scale for volume) since volume on spot exchanges (Bitstamp, Bitfinex, Coinbase etc) is measured in coins traded, not USD traded. Similarly, L/S is usually the amount of coins in open L/S positions, not their total USD value. On Bitmex and other futures exchanges volume is measured in USD traded, so you don't need to apply the Volume Absolute Price Value checkbox to compare L/S. You should always check first whether your source is measured in coins or USD.
Chiki-Poki BFXLS primarily uses *SHORTS/LONGS feeds from Bitfinex for the current crypto asset, but you can specify custom L/S source tickers instead.
This 2-in-1 works both in the Main Chart and in the indicator pane below. You can switch between Main/Sub Window panes using RMB on the indicator's name and selecting Move To/Pane Above/Below.
This indicator doesn't use volume of the current asset. It uses L/S ticker's OHLC as a source for SHORTS/LONGS volumes instead. Essentially L/S => L/S Volume == L/S
Features:
- Display Longs vs Shorts side by side graph for the current crypto asset, i.e. for BTCUSD - BTCUSDLONGS/BTCUSDSHORTS, for ETHUSD - ETHUSDLONGS/ETHUSDSHORTS etc.
- Use custom OHLC ticker sources for Longs/Shorts from different exchanges/crypto assets with/without exchange prefix.
- Plot Longs/Shorts as lines or candles
- Show/Hide L/S, Diff, MAs, ATH/ATL
- Use Longs/Shorts Volume Absolute Price Value (Price * L/S Volume) instead of Coins Traded in open L/S positions to compare total L/S value/capitalization
- Normalize L/S Volume using Price / Price MA / L/S Volume MA
- Supports any existing type of MA: SMA, EMA, WMA, HMA etc
- Volume Absolute Price Value / Normalize also works on candles
- Oscillator mode with negative axis (works in both Main Chart/Subwindow panes).
- Highlight L/S Volume spikes above L/S MAs in both lines/oscillator.
- Change L/S MA color based on a number of last rising/falling L/S bars, colorize candles
- Display L/S volume as 1000s, mlns, or blns using alpha multiplier
1. based on BFXLS Longs vs Shorts and Compare Style, uses plot*, security and custom hma functions
2. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
Notes:
- Make sure that Left Price Scale shows up with Auto Fit Data enabled. You can reattach indicator to a different scale in Style.
- It is not recommended to switch modes multiple times due to TradingView's scale reattachment bugs. You should switch between Main Chart and Sub Window only once.
- When the USD price of an asset is lower you can trade more coins but capitalization value won't be as significant as when there are less coins for a higher price. Same goes for Shorts/Longs.
Current ATH in shorts doesn't trigger a squeeze because its total value is now far less than before and we are in a bear market where it's normal to have a higher number of shorts.
- You should always subtract Hedged L/S from L/S because hedged positions are temporary - used to preserve the value of the main position in the opposite direction and should be disregarded as such.
- Low margin rates increase the probability of a move in an underlying direction because it is cheaper. High margin rates => the market is anticipating a move in this direction, thus a more expensive rate. Sudden 5-10x rate raises imply a possible reversal soon. high - 0.1%, avg - 0.01-0.02%, low - 0.001-0.005%
You can also check out:
- BFXLS Longs/Shorts on BFXData
- Bitfinex L/S margin rates and Hedged L/S on datamish
- Bitmex L/S on Coinfarm.online
4 diffs (CB & IBIT Premium)📊 Script Name: 4 diffs (CB & IBIT Premium)
Version: Pine Script® v6
Overlay: Yes (table displayed on chart)
🧠 What it Does:
This script tracks four important Bitcoin price differentials to monitor spot/perpetual/futures price inefficiencies and ETF premium/discounts, and displays them in a live table on the chart. It helps traders identify arbitrage opportunities or institutional pricing signals.
📈 Displayed Metrics:
Coinbase Premium
→ Difference between Coinbase spot and Binance spot prices.
→ Use case: US vs. offshore spot market divergence.
Coinbase Spot vs Binance Perpetual
→ Difference between Coinbase spot and Binance perpetual price.
→ Use case: Spot-perp basis, often used for funding rate insights or market stress.
Bybit vs Binance Perpetual
→ Difference between Bybit perp and Binance perp price.
→ Use case: Compare derivative pricing across major offshore exchanges.
IBIT Premium (CME vs ETF-implied)
→ Compares CME futures price vs. IBIT’s implied spot BTC value
→ IBIT implied BTC = IBIT ETF price ÷ (BTC held / shares outstanding)
→ Use case: Gauge institutional premium/discount and ETF arbitrage clues.
🛠️ Customization:
Text color of the table is adjustable via the input setting.
📌 Visual Output:
A fixed 2×4 table appears in the top-right corner of the chart.
Each row shows a label and the live price difference in USD.
Volume Data Table (Real-time & Historical Volume Analysis)Volume Data Table (Real-time & Historical Volume Analysis)
Overview:
The Volume Data Table indicator is a powerful tool designed to provide concise, real-time, and historical volume insights directly on your chart. It aggregates critical volume metrics into an organized, customizable table, making it incredibly easy to identify unusual volume activity, sudden surges, or sustained interest in a particular asset.
This indicator is perfect for traders who rely on volume analysis to confirm price movements, spot potential reversals, or gauge market conviction.
Key Features & How It Works:
Real-time Volume Metrics:
The table prominently displays the volume data for the current (last) candle, including:
Time: The precise time of the current candle's close, formatted in IST (Indian Standard Time - UTC+5:30) for your convenience.
Volume: The total volume for the current candle, smartly formatted in K (Thousands) or M (Millions) for readability.
Change % (Chg%): The percentage change in volume compared to the immediately preceding candle. This helps you quickly spot sudden increases or decreases in trading activity.
Vs 4-Avg % (vs4Avg%): The percentage change in volume compared to the average volume of the last 4 preceding candles. This is crucial for identifying volume surges or drops relative to recent historical activity, which can signal significant market events.
Configurable Historical Data:
Beyond the current candle, you can customize how many previous candles' volume data you wish to display. A simple input setting allows you to choose from 1 to 20 historical rows, giving you flexibility to review recent volume trends. Each historical row also provides its own "Change %" and "Vs 4-Avg %" for detailed analysis of past candle activity.
Intuitive Color-Coding:
Percentage change values are intuitively color-coded for instant visual cues:
Green: Indicates a positive (increase) in volume percentage.
Red: Indicates a negative (decrease) in volume percentage.
Clean & Organized Table Display:
The indicator presents all this data in a neat, easy-to-read table positioned at the top-right of your chart. The table automatically adjusts its height based on the number of historical rows you choose, ensuring a compact and efficient use of screen space.
Ideal Use Cases:
Volume Confirmation: Quickly confirm the conviction behind price movements. A strong price move on high "Vs 4-Avg %" volume often indicates higher reliability.
Spotting Abnormal Volume: Identify candles with unusually high or low volume compared to their recent average, which can precede or accompany significant price action.
Momentum Analysis: Understand if buying/selling pressure is increasing or decreasing over recent periods.
Scalping & Day Trading: The real-time updates and concise format make it highly effective for fast-paced short-term decision-making.
Complements Other Indicators: Use it alongside price action, candlestick patterns, or other technical indicators for a more robust analysis.
Customization Options:
Number of Historical Rows: Adjust Number of Historical Rows from 1 to 20 to tailor the depth of your historical volume review.
Important Disclaimer:
This indicator is a technical analysis tool and should be used as part of a comprehensive trading strategy. It is not financial advice. Trading in financial markets involves substantial risk, and you could lose money. Always perform your own research and risk management.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
---
💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
---
🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
---
🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
---
📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
---
🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
---
📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
---
⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
---
📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
[blackcat] L2 Trend Guard OscillatorOVERVIEW
📊 The L2 Trend Guard Oscillator is a comprehensive technical analysis framework designed specifically to identify market trend reversals using adaptive filtering algorithms that combine price action dynamics with statistical measures of volatility and momentum.
Key Purpose:
Generate reliable early warning signals before major trend changes occur
Provide clear directional bias indicators aligned with institutional investor behavior patterns
Offer risk-managed entry/exit opportunities suitable for various timeframes
TECHNICAL FOUNDATION EXPLAINED
🎓 Core Mechanism Breakdown:
→ Advanced smoothing technique emphasizing recent data points more heavily than older ones
↓ Reduces lag while maintaining signal integrity compared to traditional MA approaches
• Short-term Momentum Assessment:
🔶 Relative strength between closing prices vs lower bounds
• Long-term Directional Bias Analysis:
📈 Extended timeframe comparison generating structural context
• Defense Level Generation:
➜ Protective boundary calculation incorporating EMAs for stability enhancement
PARAMETER CONFIGURATION GUIDE
🔧 Adjustable Settings Explained In Detail:
Timeframe Selection:**
↔ Controls lookback period sensitivity affecting responsiveness
↕ Adjusts reaction speed vs accuracy trade-off dynamically
Weight Factor Specification:**
⚡ Influences emphasis on newer versus historical observations
🎯 Defines key decision-making thresholds clearly
ALGORITHM EXECUTION FLOW
💻 Processing Sequence Overview:
:
→ Gather raw pricing inputs across required periods
↓ Normalize values preparing them for subsequent processing stages
:
✔ Calculate relative strength positions against established ranges
❌ Filter outliers maintaining signal integrity consistently
⟶ Apply dual-pass filtering reducing false signals effectively
➡ Generate actionable trading opportunities systematically
VISUALIZATION ARCHITECTURE
🎨 Display Elements Designated Purpose:
🔵 Primary Indicator Traces:
→ Aqua Trace: Buy/Sell Signal Progression
↑ Red Line: Opposing Force Boundary
🟥 Gray Dashed: Zero Reference Point
🏷️ Label System For Critical Events:
✅ BUY: Bullish Opportunity Markers
❌ SELL: Bearish Setup Validations
STRATEGIC IMPLEMENTATION FRAMEWORK
📋 Practical Deployment Steps:
Initial Integration Protocol:
• Select appropriate timeframe matching strategy objectives
• Configure input parameters aligning with target asset behavior traits
• Conduct thorough backtesting under simulated environments initially
Active Monitoring Procedures:
→ Regular observation of labeled event placements versus actual movements
↓ Track confirmation patterns leading up to signaled opportunities carefully
↑ Evaluate overall framework reliability across different regime types regularly
Execution Guidelines Formulation:
✔ Enter positions only after achieving minimum number of confirming inputs
❌ Avoid isolated occurrences lacking adequate supporting evidence always
➞ Look for convergent factors strengthening conviction before acting decisively
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Continuous Improvement Strategies:
Parameter Calibration Approach:
✓ Start testing default suggested configurations thoroughly
↕ Gradually adjust individual components observing outcome changes methodically
✨ Document findings building personalized version profile incrementally
Context Adaptability Methods:
🔄 Add supplementary indicators enhancing overall reliability when needed
🔧 Remove unnecessary complexity layers avoiding confusion/distracted decisions
💫 Incorporate custom rules adapting specific security behaviors effectively
Efficiency Improvement Tactics:
⚙️ Streamline redundant computational routines wherever possible efficiently
♻️ Leverage shared data streams minimizing resource utilization significantly
⏳ Optimize refresh frequencies balancing update speed vs overhead properly
Multi Scanner Plot & Table V1Here's how to interpret each column in the table:
Price vs MAs:
What it shows: Where the current price is relative to the short-term (e.g., 20-period) and long-term (e.g., 50-period) Simple Moving Averages (SMAs) calculated on your current chart's timeframe.
Interpretation:
Above Both (Green background): Price is above both the short and long MAs. Generally considered a bullish sign for the current trend.
Below Both (Red background): Price is below both MAs. Generally considered a bearish sign.
Mixed (Gray background): Price is between the two MAs (e.g., above the short but below the long, or vice-versa). Indicates indecision or a potential trend change.
RSI Value:
What it shows: The actual numerical value of the Relative Strength Index (RSI) calculated on your current chart's timeframe.
Interpretation: Just the raw RSI number (e.g., 65.32). The background is always gray. You compare this value to standard overbought/oversold levels (like 70/30) or the levels defined in the script's inputs.
RSI Status:
What it shows: Interprets the RSI Value based on the Overbought/Oversold levels set in the script's inputs (default 70/30). Calculated on your current chart's timeframe.
Interpretation:
Overbought (Red background): RSI is above the overbought level (e.g., > 70). Suggests the asset might be due for a pullback or reversal downwards. Red indicates a potentially bearish condition.
Oversold (Green background): RSI is below the oversold level (e.g., < 30). Suggests the asset might be due for a bounce or reversal upwards. Green indicates a potentially bullish condition.
Neutral (Gray background): RSI is between the oversold and overbought levels.
Last Sig Price:
What it shows: The price level where the last "SIG NOW" Buy or Sell signal occurred on your current chart's timeframe.
Interpretation: Helps you see the entry price of the most recent short-term signal generated by this script. The background color matches the signal type: Green for the last Buy signal, Red for the last Sell signal. N/A if no signal has occurred yet.
SIG NOW:
What it shows: This is the main short-term signal generated by the script based on conditions on your current chart's timeframe. It combines the "Price vs MAs" status and specific RSI conditions (price must be above/below both MAs and RSI must be within a certain range defined in the inputs).
Interpretation:
BUY (Green background): The specific buy conditions are met right now. (Price above both MAs AND RSI is strong but not necessarily overbought).
SELL (Red background): The specific sell conditions are met right now. (Price below both MAs AND RSI is weak but not necessarily oversold).
NEUTRAL (Gray background): Neither the Buy nor the Sell conditions are currently met.
ALERT:
What it shows: Flags unusual volume activity on the current bar compared to the recent average volume (calculated on your current chart's timeframe).
Interpretation:
SPIKE (Yellow background, black text): Current volume is significantly higher than the recent average (defined by the Volume Spike Multiplier). Can indicate strong interest or a potential climax.
DUMP (Purple background): Current volume is significantly lower than the recent average (defined by the Volume Dump Multiplier). Can indicate fading interest.
NONE (Gray background): Volume is within the normal range for the lookback period.
SD$:
What it shows: The price level where the last Volume Spike or Dump occurred on your current chart's timeframe.
Interpretation: Shows the price associated with the most recent significant volume event. The background color indicates the type of the last event: Green if the last event was a Spike, Red if the last event was a Dump. N/A if no Spike/Dump has occurred yet.
BB Value (%B):
What it shows: This relates to Bollinger Bands, but specifically calculated on a Higher Timeframe (HTF) that you can set in the inputs (e.g., Daily BBs while viewing an Hourly chart). It shows the Bollinger Band Percent B (%B) value for that HTF. %B measures where the HTF closing price is relative to the HTF upper and lower bands.
Interpretation:
Value > 1: HTF price closed above the HTF upper Bollinger Band.
Value < 0: HTF price closed below the HTF lower Bollinger Band.
Value between 0 and 1: HTF price closed within the HTF Bollinger Bands (e.g., 0.5 is exactly on the middle band).
The background is always gray.
LTS (Long Term Signal):
What it shows: A signal derived only from the Higher Timeframe (HTF) Bollinger Bands.
Interpretation:
BUY (Green background): The HTF price closed above the HTF upper Bollinger Band (see BB Value > 1). Considered a strong bullish signal from the higher timeframe perspective.
SELL (Red background): The HTF price closed below the HTF lower Bollinger Band (see BB Value < 0). Considered a strong bearish signal from the higher timeframe perspective.
NEUTRAL (Gray background): The HTF price closed within the HTF Bollinger Bands.
How to Understand Bollinger Bands and Signals in this Context:
Bollinger Bands are primarily used for the Long Term Signal (LTS) column. This script calculates BBs on a higher timeframe (you choose which one, or it defaults to the chart's timeframe if left blank).
The "LTS" signal triggers:
A BUY when the price on that higher timeframe closes above its upper Bollinger Band. This often indicates strong momentum or a potential breakout.
A SELL when the price on that higher timeframe closes below its lower Bollinger Band. This often indicates strong negative momentum or a potential breakdown.
The "BB Value" column gives you the raw %B number from that same higher timeframe, showing you exactly where the price is relative to the bands (is it just barely above/below, or way outside?).
The script does not directly use Bollinger Bands from the current chart timeframe for the "SIG NOW" or other table signals. The main short-term signals ("SIG NOW") rely on Moving Averages and RSI on the current timeframe. The LTS provides a longer-term perspective using HTF Bollinger Bands.
In summary: Look at the table to quickly gauge:
Short-term trend (Price vs MAs).
Short-term momentum (RSI Status, SIG NOW).
Recent short-term entry points (Last Sig Price).
Current volume anomalies (ALERT).
Long-term strength/weakness based on HTF Bollinger Bands (LTS, BB Value).
Combine these pieces of information to get a more rounded view of the current market conditions according to this specific script's logic.
Easy MA SignalsEasy MA Signals
Overview
Easy MA Signals is a versatile Pine Script indicator designed to help traders visualize moving average (MA) trends, generate buy/sell signals based on crossovers or custom price levels, and enhance chart analysis with volume-based candlestick coloring. Built with flexibility in mind, it supports multiple MA types, crossover options, and customizable signal appearances, making it suitable for traders of all levels. Whether you're a day trader, swing trader, or long-term investor, this indicator provides actionable insights while keeping your charts clean and intuitive.
Configure the Settings
The indicator is divided into three input groups for ease of use:
General Settings:
Candlestick Color Scheme: Choose from 10 volume-based color schemes (e.g., Sapphire Pulse, Emerald Spark) to highlight high/low volume candles. Select “None” for TradingView’s default colors.
Moving Average Length: Set the MA period (default: 20). Adjust for faster (lower values) or slower (higher values) signals.
Moving Average Type: Choose between SMA, EMA, or WMA (default: EMA).
Show Buy/Sell Signals: Enable/disable signal plotting (default: enabled).
Moving Average Crossover: Select a crossover type (e.g., MA vs VWAP, MA vs SMA50) for signals or “None” to disable.
Volume Influence: Adjust how volume impacts candlestick colors (default: 1.2). Higher values make thresholds stricter.
Signal Appearance Settings:
Buy/Sell Signal Shape: Choose shapes like triangles, arrows, or labels for signals.
Buy/Sell Signal Position: Place signals above or below bars.
Buy/Sell Signal Color: Customize colors for better visibility (default: green for buy, red for sell).
Custom Price Alerts:
Custom Buy/Sell Alert Price: Set specific price levels for alerts (default: 0, disabled). Enter a non-zero value to enable.
Set Up Alerts
To receive notifications (e.g., sound, popup, email) when signals or custom price levels are hit:
Click the Alert button (alarm clock icon) in TradingView.
Select Easy MA Signals as the condition and choose one of the four alert types:
MA Crossover Buy Alert: Triggers on MA crossover buy signals.
MA Crossover Sell Alert: Triggers on MA crossover sell signals.
Custom Buy Alert: Triggers when price crosses above the custom buy price.
Custom Sell Alert: Triggers when price crosses below the custom sell price.
Enable Play Sound and select a sound (e.g., “Bell”).
Set the frequency (e.g., Once Per Bar Close for confirmed signals) and create the alert.
Analyze the Chart
Moving Average Line: Displays the selected MA with color changes (green for bullish, red for bearish, gray for neutral) based on price position relative to the MA.
Buy/Sell Signals: Appear as shapes or labels when crossovers or custom price levels are hit.
Candlestick Colors: If a color scheme is selected, candles change color based on volume strength (high, low, or neutral), aiding in trend confirmation.
Why Use Easy MA Signals?
Easy MA Signals is designed to simplify technical analysis while offering advanced customization. It’s ideal for traders who want:
A clear visualization of MA trends and crossovers.
Flexible signal generation based on MA crossovers or custom price levels.
Volume-enhanced candlestick coloring to identify market strength.
Easy-to-use settings with tooltips for beginners and pros alike.
This script is particularly valuable because it combines multiple features into one indicator, reducing chart clutter and providing actionable insights without overwhelming the user.
Benefits of Easy MA Signals
Highly Customizable: Supports SMA, EMA, and WMA with adjustable lengths.
Offers multiple crossover options (VWAP, SMA10, SMA20, etc.) for tailored strategies.
Custom price alerts allow precise targeting of key levels.
Volume-Based Candlestick Coloring: 10 unique color schemes highlight volume strength, helping traders confirm trends.
Adjustable volume influence ensures adaptability to different markets.
Flexible Signal Visualization: Choose from various signal shapes (triangles, arrows, labels) and positions (above/below bars).
Customizable colors improve visibility on any chart background.
Alert Integration: Built-in alert conditions for crossovers and custom prices support sound, email, and app notifications.
Easy setup for real-time trading decisions.
User-Friendly Design: Organized input groups with clear tooltips make configuration intuitive.
Suitable for beginners and advanced traders alike.
Example Use Cases
Swing Trading with MA Crossovers:
Scenario: A trader wants to trade Bitcoin (BTC/USD) on a 4-hour chart using an EMA crossover strategy.
Setup:
Set Moving Average Type to EMA, Length to 20.
Set Moving Average Crossover to “MA vs SMA50”.
Enable Show Buy/Sell Signals and choose “arrowup” for buy, “arrowdown” for sell.
Select “Emerald Spark” for candlestick colors to highlight volume surges.
Usage: Buy when the EMA20 crosses above the SMA50 (green arrow appears) and volume is high (dark green candles). Sell when the EMA20 crosses below the SMA50 (red arrow). Set alerts for real-time notifications.
Scalping with Custom Price Alerts:
Scenario: A day trader monitors Tesla (TSLA) on a 5-minute chart and wants alerts at specific support/resistance levels.
Setup:
Set Custom Buy Alert Price to 150.00 (support) and Custom Sell Alert Price to 160.00 (resistance).
Use “labelup” for buy signals and “labeldown” for sell signals.
Keep Moving Average Crossover as “None” to focus on price alerts.
Usage: Receive a sound alert and label when TSLA crosses 150.00 (buy) or 160.00 (sell). Use volume-colored candles to confirm momentum before entering trades.
When NOT to Use Easy MA Signals
High-Frequency Trading: Reason: The indicator relies on moving averages and volume, which may lag in ultra-fast markets (e.g., sub-second trades). High-frequency traders may need specialized tools with real-time tick data.
Alternative: Use order book or market depth indicators for faster execution.
Low-Volatility or Sideways Markets:
Reason: MA crossovers and custom price alerts can generate false signals in choppy, range-bound markets, leading to whipsaws.
Alternative: Use oscillators like RSI or Bollinger Bands to trade within ranges.
This indicator is tailored more towards less experienced traders. And as always, paper trade until you are comfortable with how this works if you're unfamiliar with trading! We hope you enjoy this and have great success. Thanks for your interested in Easy MA Signals!
Stochastic Overlay - Regression Channel (Zeiierman)█ Overview
The Stochastic Overlay – Regression Channel (Zeiierman) is a next-generation visualization tool that transforms the traditional Stochastic Oscillator into a dynamic price-based overlay.
Instead of leaving momentum trapped in a lower subwindow, this indicator projects the Stochastic oscialltor directly onto price itself — allowing traders to visually interpret momentum, overbought/oversold conditions, and market strength without ever taking their eyes off price action.
⚪ In simple terms:
▸ The Bands = The Stochastic Oscillator — but on price.
▸ The Midline = Stochastic 50 level
▸ Upper Band = Stochastic Overbought Threshold
▸ Lower Band = Stochastic Oversold Threshold
When the price moves above the midline → it’s the same as the oscillator moving above 50
When the price breaks above the upper band → it’s the same as Stochastic entering overbought.
When the price reaches the lower band →, think of it like Stochastic being oversold.
This makes market conditions visually intuitive. You’re literally watching the oscillator live on the price chart.
█ How It Works
The indicator layers 3 distinct technical elements into one clean view:
⚪ Stochastic Momentum Engine
Tracks overbought/oversold conditions and directional strength using:
%K Line → Momentum of price
%D Line → Smoothing filter of %K
Overbought/Oversold Bands → Highlight potential reversal zones
⚪ Volatility Adaptive Bands
Dynamic bands plotted above and below price using:
ATR * Stochastic Scaling → Creates wider bands during volatile periods & tighter bands in calm conditions
Basis → Moving average centerline (EMA, SMA, WMA, HMA, RMA selectable)
This means:
→ In strong trends: Bands expand
→ In consolidations: Bands contract
⚪ Regression Channel
Projects trend direction with different models:
Logarithmic → Captures non-linear growth (perfect for crypto or exponential stocks)
Linear → Classic regression fit
Adaptive → Dynamically adjusts sensitivity
Leading → Projects trend further ahead (aggressive mode)
Channels include:
Midline → Fair value trend
Upper/Lower Bounds → Deviation-based support/resistance
⚪ Heatmap - Bull & Bear Power Strength
Visual heatmeter showing:
% dominance of bulls vs bears (based on close > or < Band Basis)
Automatic normalization regardless of timeframe
Table display on-chart for quick visual insight
Dynamic highlighting when extreme levels are reached
⚪ Trend Candlestick Coloring
Bars auto-color based on trend filter:
Above Basis → Bullish Color
Below Basis → Bearish Color
█ How to Use
⚪ Trend Trading
→ Use Band direction + Regression Channel to identify trend alignment
→ Longs favored when price holds above the Basis
→ Shorts favored when price stays below the Basis
→ Use the Bull & Bear heatmap to asses if the bulls or the bears are in control.
⚪ Mean Reversion
→ Look for price to interact with Upper or Lower Band extremes
→ Stochastic reaching OB/OS zones further supports reversals
⚪ Momentum Confirmation
→ Crossovers between %K and %D can confirm continuation or divergence signals
→ Especially powerful when happening at band boundaries
⚪ Strength Heatmap
→ Quickly visualize current buyer vs seller control
→ Sharp spikes in Bull Power = Aggressive buying
→ Sharp spikes in Bear Power = Heavy selling pressure
█ Why It Useful
This is not a typical Stochastic or regression tool. The tool is designed for traders who want to:
React dynamically to price volatility
Map momentum into volatility context
Use adaptive regression channels across trend styles
Visualize bull vs bear power in real-time
Follow trends with built-in reversal logic
█ Settings
Stochastic Settings
Stochastic Length → Period of calculation. Higher = smoother, Lower = faster signals.
%K Smoothing → Smooths the Stochastic line itself.
%D Smoothing → Smooths the moving average of %K for slower signals.
Stochastic Band
Band Length → Length of the Moving Average Basis.
Volatility Multiplier → Controls band width via ATR scaling.
Band Type → Choose MA type (EMA, SMA, WMA, HMA, RMA).
Regression Channel
Regression Type → Logarithmic / Linear / Adaptive / Leading.
Regression Length → Number of bars for regression calculation.
Heatmap Settings
Heatmap Length → Number of bars to calculate bull/bear dominance.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Multi-Timeframe EMAsMulti Timeframe EMA's
The 'Multi-Timeframe EMA Band Comparison' indicator is a tool designed to analyze trend direction across multiple timeframes using Exponential Moving Averages. it calculates the 50, 100, and 200 period EMAs for fiver user defined timeframes and compares their relationships to provide a visual snapshot of bullish or bearish momentum.
How it Works:
EMA Calculations: For each selected timeframe, the indicator computes the 50, 100, and 200 period EMAs based on the closing price.
Band Comparisons: Three key relationships are evaluated:
50 EMA vs 100 EMA
100 EMA vs 200 EMA
50 EMA vs 200 EMA
Scoring System: Each comparison is assigned a score:
🟢 (Green Circle): The shorter EMA is above the longer EMA, signaling bullish momentum.
🔴 (Red Circle): The shorter EMA is below the longer EMA, signaling bearish momentum.
⚪️ (White Circle): The EMAs are equal or data is unavailable (rare).
Average Score:
An overall average score is calculated across all 15 comparisons ranging from 1 to -1, displayed with two decimal places and color coded.
Customization:
This indicator is fully customizable from the timeframe setting to the color of the table. The only specific part that is not changeable is the EMA bands.
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
STRX - Correlation DominationThis indicator displays the correlation among three selected assets (for example, Gold, Dollar Index, and Nasdaq) on a custom timeframe. A table positioned at the top-right corner of the chart lets you quickly see the correlation between:
Asset 1 vs Asset 2
Asset 1 vs Asset 3
Asset 2 vs Asset 3
Correlations are calculated using the Pearson correlation function (ta.correlation). If the correlation is greater than or equal to 0.4, the value appears in green (strong positive correlation). If it is less than or equal to -0.4, it appears in red (strong negative correlation). Otherwise, it is displayed in yellow (weak correlation).
Multi-asset and multi-timeframe: Compare up to three instruments at once on your chosen timeframe.
Customizable period: Use the “Correlation Period” setting to adjust the correlation calculation window.
Clear table format: The results are immediately visible in an easy-to-read table.
Disclaimer: This script is provided solely for educational and informational purposes. It does not constitute a recommendation or an invitation to invest. Use it as an additional resource and always conduct thorough market analysis before opening any trading positions. Past performance does not guarantee future results.
ICT Professional Accumulation DistributionICT Professional Accumulation Distribution (ICT AD) provides a x-ray view into market accumulation and distribution. You can literally see the institutions at work.
The indicator consists of two cumulative lines derived from:
Cumulative change from open to close
Cumulative change from previous close to new open
By overlaying these two cumulative lines, you can detect real meaningful divergence that is narrative based not mathematically derived. You're seeing the real works of algorithms in play working in this area.
These divergences are only useful at extremes (topping or bottoming formations), not while trending. It will probably confirm your suspicion about making a important high or low.
This works on all timeframes but is most impactful on the daily.
How to use:
Method 1:
Enable the option for "Show Open vs Close."
Calculate the shift by subtracting the "Open vs Close" line value from the ICT Accumulation/Distribution (AD) line value.
Look for divergences between the two cumulative lines.
Method 2:
Switch the chart's display mode to "Line View" (representing the Open vs Close).
look for divergences between the line chart and the ICT AD line.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
Divergence Indicator [Trendoscope®]🎲 New Divergence Indicator by Trendoscope
Our latest Divergence Indicator revolutionizes the way traders identify market trends and potential reversals. Built upon the robust foundation of the Zigzag Trend Divergence Detector and inline with our recent implementation of the Divergence Goggles indicator, this tool is designed to be intuitive yet powerful, making it an essential addition to any trader's toolkit.
We received several queries on extending the Divergence Goggles to last N bars instead of using an interactive widget. Though it is possible, we thought the better approach is to enable the indicator to use any oscillator and trend indicator in order to define the divergence.
🎯 Key Features
Flexible Oscillator Integration : Choose from a wide range of built-in oscillators or import your own, including options like the innovative Multiband Oscillator. This versatility extends to using volume indicators like OBV for divergence calculations, broadening the scope of analysis.
Trend Identification Versatility : Utilize built-in methods like Zigzag and MA Difference, or integrate external trend indicators. Our system adapts to various methods, ensuring you have the right tools for precise trend identification.
Customizable Zigzag Sensitivity : Adjust the Zigzag based on your chosen oscillator's sensitivity to ensure divergence lines are accurate and visually coherent.
Repainting vs. Delayed Signals : Tailor the indicator to your strategy by choosing between immediate repainting signals and slightly delayed but more stable signals.
🎯 Understanding Divergence: Key Rules
Bullish Divergence
Happens only in downtrend
Observed on Pivot Lows
Price makes lower low whereas oscillator makes higher low, indicating weakness and possible reversal
Bearish Divergence
Happens only in uptrend
Observed on Pivot Highs
Price makes higher high whereas oscillator makes lower high, indicating weakness and possible reversal
Bullish Hidden Divergence
Happens only in uptrend
Observed on Pivot Lows
Price makes higher low, whereas indicator makes lower low due to price consolidation. In bullish trend, this is considered as bullish as the price gets a breather and get ready to surge further.
Bearish Hidden Divergence
Happens only in downtrend
Observed on Pivot Highs
Price makes lower high whereas oscillator makes higher high due to price consolidation. In bearish trend, this is considered as bearish as the price gets a breather and get ready to fall further.
🎯 Visual Insights: Divergence and Hidden Divergence
For a clearer understanding, refer to our visual guides:
🎲 Using the Divergence Indicator: A Step-by-Step Guide
🎯 Step 1 - Selecting the Oscillator
Customize your analysis by choosing from a variety of oscillators or importing your preferred one. Options are available to select a range of built-in oscillators and the loopback length. However, if the oscillator that user want to use is not in the list, they can simply load the oscillator from the indicator library and use it as an external signal.
In our current example, we are using a custom oscillator called - Multiband Oscillator
This also means, the indicator option is not limited to oscillators. Users can even make use of volume indicators such as OBV for the calculation of divergence.
🎯 Step 2 - Choosing the Trend Identification Method
Select from our built-in methods or integrate an external indicator to accurately identify market trends. Trend is one of the key parameters of divergence type identification. Trend can be identified mathematically by various methods. Some of them are as simple as above or below 200 moving average and some can follow trend based indicators such as supertrend and others can be very complex.
To cater for a wider audience, here too we have provided the option to use an external trend indicator. The simple condition for the external trend indicator is that it should return positive value for uptrend and negative value for downtrend.
Other than that, we also have 2 built in trend identification methods.
Zigzag - The trend is defined by the starting pivot of divergence line. If the starting pivot is Higher High or Higher Low, then it is considered uptrend. And if the starting pivot is either Lower Low or Lower High, then we consider it as downtrend.
MA Difference - In this case, the difference between the moving average of pivots joining the divergence line will determine the trend. It is considered uptrend if the moving average increased from starting pivot to ending pivot of the divergence line, and it is considered downtrend if the moving average decreased from starting pivot to the ending pivot of the divergence line.
🎯 Step 3 - Adjusting Zigzag Sensitivity
Fine-tune the Zigzag to match the oscillator's sensitivity, ensuring divergence lines are accurate and visually coherent.
🎯 Step 4 - Managing Repainting
Understand the implications of repainting in the last pivot of the Zigzag and choose between immediate or delayed signals based on your trading strategy. The last pivot of the zigzag repaint by design. This is not necessarily a bad thing. Users can just choose not to use the last pivot, but instead use the last but one for all the calculations. But, this also means, the signals will be delayed.
Indicator provides option to use repainting signal vs delayed signal. If you select the repaint option, the signals are shown immediately as and when they occur. But, there is a possibility that these signals change when the new price candles change zigzag pivot.
If you chose not to select the repaint option, then the divergence signals may lag by a few bars.
