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RSI AND CHARTSTORYRsi value on chart with 4 levels 20,40,60,80 and also rsi value and price with current candle. All are plot on chart so one can find easy divergence on chart.
FlowTrinity — Crypto Dominance Rotation IndexFlowTrinity — Crypto Dominance Rotation Index
(Tracks BTC / Stablecoin / Altcoin dominance flows with standardized oscillators)
⚪ Overview
FlowTrinity decomposes total crypto market structure into three capital-flow regimes — BTC dominance, Stablecoin dominance, and Altcoin dominance — each normalized into oscillator form. Additionally, a fourth histogram tracks Total Market Cap expansion/contraction relative to BTC+Stable capital, revealing underlying rotation pressure not visible in raw dominance charts.
Each component is standardized through SMA/STD normalization, producing smoothed 0–100 style oscillations that highlight overbought/oversold rotation extremes, risk-on/risk-off transitions, and capital cycle inflection zones.
⚪ Flow Components
Stablecoin Dominance Oscillator —White line
Measures the combined USDT + USDC share of market dominance.
High values indicate increased hedging behavior or sidelined capital.
Low values coincide with renewed risk appetite and capital deployment into crypto assets.
Altcoin Dominance Oscillator — Orange Line
Tracks the share of liquidity rotating into altcoins (Total – BTC – Stable).
Rising values indicate broad market expansion and speculative activity.
Falling values reflect flight-to-safety or concentration back into majors.
BTC Dominance Oscillator — Purple line(off by default
Normalized BTC dominance revealing transitions between Bitcoin-led markets and altcoin-led cycles. Useful for identifying BTC absorption phases vs. altcoins dispersion regimes.
Total–BTC–Stable MarketCap Difference Histogram — histogram
A normalized histogram of total market cap change minus BTC+Stable market cap change.
• Positive → altcoin segment expanding
• Negative → capital retreating into BTC or stables
Acts as a structural layer confirming or contradicting dominance-based signals.
Normalization Logic
All flows use SMA + standard deviation scaling (lookback 7 / smoothing 7), enabling consistent comparison across unrelated dominance and market-cap metrics.
⚪ Use Cases
• Identify shifts between BTC-led and alt-led markets
• Detect early signs of liquidity rotation
• If Stablecoin OSC is oversold, liquidity may soon rotate to BTC or Altcoins, signaling potential price moves.
• If Stablecoin OSC is overbought and Altcoin OSC is oversold, it can indicate an early buying opportunity in Altcoins.
• Watching these oscillator positions helps spot early market rotations and plan entries or exits.
snapshot
Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice or investment guidance. Cryptocurrency trading involves significant risk; you are solely responsible for your trading decisions, based on your financial objectives and risk tolerance. The author assumes no liability for any losses arising from the use of this tool.
2026 CHRISTMAS PRESENT CHRISTMAS PRESENT
Overview
The Cash Detector is a comprehensive trading strategy that combines momentum analysis with price action confirmation to identify high-probability entry points. This strategy is designed to capture trend reversals and continuation moves by requiring multiple confirming signals before entry, significantly reducing false signals common in single-indicator systems.
Strategy Background
The strategy is built on the principle of confluence trading requiring multiple technical factors to align before taking a position. It focuses on two critical phases of market rotation:
Q2 Momentum Phase: Uses MACD crossovers to identify shifts in market momentum, signaling when bulls or bears are gaining control.
Q4 Trigger Phase: Employs engulfing candlestick patterns to confirm strong directional pressure and validate the momentum signal with actual price action.
By combining these elements, the strategy filters out weak signals and focuses only on setups where both momentum AND price action agree on direction.
Key Features
Dual Confirmation System: Requires both MACD momentum shift and engulfing candle pattern
RSI Filter: Optional overbought/oversold filter to avoid extreme conditions
Built-in Risk Management: Configurable stop loss and take profit levels
Performance Dashboard: Real-time ROI metrics displayed on chart
Full Backtesting: Strategy mode allows historical performance analysis
Trading Rules
LONG ENTRY BUY
All conditions must occur on the same candle:
1. Momentum Confirmation:
MACD line crosses above signal line bullish crossover
2. Price Action Confirmation:
Bullish engulfing pattern forms:
Current close greater than previous open
Current open less than previous close
Current close greater than current open
3. RSI Filter Optional:
RSI less than 70 not overbought
Visual Signal: Green LONG label appears below the candle
SHORT ENTRY SELL
All conditions must occur on the same candle:
1. Momentum Confirmation:
MACD line crosses below signal line bearish crossover
2. Price Action Confirmation:
Bearish engulfing pattern forms:
Current close less than previous open
Current open greater than previous close
Current close less than current open
3. RSI Filter Optional:
RSI greater than 30 not oversold
Visual Signal: Red SHORT label appears above the candle
Exit Rules
Stop Loss Default 2 percent
Long: Exit if price drops 2 percent below entry
Short: Exit if price rises 2 percent above entry
Take Profit Default 4 percent
Long: Exit if price rises 4 percent above entry
Short: Exit if price drops 4 percent below entry
Input Parameters
Indicator Settings
MACD Fast Length: 12 default
MACD Slow Length: 26 default
RSI Length: 14 default
Risk Management
Use Stop Loss: Enable or disable stop loss
Stop Loss percent: Percentage risk per trade default 2 percent
Use Take Profit: Enable or disable take profit
Take Profit percent: Target profit per trade default 4 percent
Filters
Use RSI Filter: Enable or disable RSI overbought oversold filter
RSI Overbought: Upper threshold default 70
RSI Oversold: Lower threshold default 30
Performance Metrics
The built-in dashboard displays:
Net Profit: Total profit loss in currency and percentage
Total Trades: Number of completed trades
Win Rate: Percentage of profitable trades
Profit Factor: Ratio of gross profit to gross loss
Average Win Loss: Mean profit per winning losing trade
Max Drawdown: Largest peak to trough decline
Best Practices
1. Timeframe Selection: Works on multiple timeframes test on 15min 1H 4H and daily
2. Market Conditions: Most effective in trending markets with clear momentum
3. Risk Reward Ratio: Default 1:2 ratio 2 percent risk 4 percent reward is conservative adjust based on backtesting
4. Combine with Context: Consider overall market trend and support resistance levels
5. Backtest First: Always backtest on your specific instrument and timeframe before live trading
Risk Disclaimer
This strategy is for educational purposes. Past performance does not guarantee future results. Always:
Backtest thoroughly on historical data
Paper trade before using real capital
Use proper position sizing and risk management
Never risk more than you can afford to lose
Customization Tips
Aggressive traders: Reduce stop loss to 1.5 percent increase take profit to 5 percent
Conservative traders: Increase stop loss to 3 percent reduce take profit to 3 percent
Ranging markets: Enable RSI filter to avoid false breakouts
Strong trends: Disable RSI filter to catch all momentum shifts
Technical Details
Indicators Used:
Moving Average Convergence Divergence MACD
Relative Strength Index RSI
Candlestick Pattern Recognition
Strategy Type: Trend following with momentum confirmation
Best Suited For: Stocks Forex Crypto Indices
Version 1.0
Compatible with Pine Script v5
Credit Spread RegimeThe Credit Market as Economic Barometer
Credit spreads are among the most reliable leading indicators of economic stress. When corporations borrow money by issuing bonds, investors demand a premium above the risk-free Treasury rate to compensate for the possibility of default. This premium, known as the credit spread, fluctuates based on perceptions of economic health, corporate profitability, and systemic risk.
The relationship between credit spreads and economic activity has been studied extensively. Two papers form the foundation of this indicator. Pierre Collin-Dufresne, Robert Goldstein, and Spencer Martin published their influential 2001 paper in the Journal of Finance, documenting that credit spread changes are driven by factors beyond firm-specific credit quality. They found that a substantial portion of spread variation is explained by market-wide factors, suggesting credit spreads contain information about aggregate economic conditions.
Simon Gilchrist and Egon Zakrajsek extended this research in their 2012 American Economic Review paper, introducing the concept of the Excess Bond Premium. They demonstrated that the component of credit spreads not explained by default risk alone is a powerful predictor of future economic activity. Elevated excess spreads precede recessions with remarkable consistency.
What Credit Spreads Reveal
Credit spreads measure the difference in yield between corporate bonds and Treasury securities of similar maturity. High yield bonds, also called junk bonds, carry ratings below investment grade and offer higher yields to compensate for greater default risk. Investment grade bonds have lower yields because the probability of default is smaller.
The spread between high yield and investment grade bonds is particularly informative. When this spread widens, investors are demanding significantly more compensation for taking on credit risk. This typically indicates deteriorating economic expectations, tighter financial conditions, or increasing risk aversion. When the spread narrows, investors are comfortable accepting lower premiums, signaling confidence in corporate health.
The Gilchrist-Zakrajsek research showed that credit spreads contain two distinct components. The first is the expected default component, which reflects the probability-weighted cost of potential defaults based on corporate fundamentals. The second is the excess bond premium, which captures additional compensation demanded beyond expected defaults. This excess premium rises when investor risk appetite declines and financial conditions tighten.
The Implementation Approach
This indicator uses actual option-adjusted spread data from the Federal Reserve Economic Database (FRED), available directly in TradingView. The ICE BofA indices represent the industry standard for measuring corporate bond spreads.
The primary data sources are FRED:BAMLH0A0HYM2, the ICE BofA US High Yield Index Option-Adjusted Spread, and FRED:BAMLC0A0CM, the ICE BofA US Corporate Index Option-Adjusted Spread for investment grade bonds. These indices measure the spread of corporate bonds over Treasury securities of similar duration, expressed in basis points.
Option-adjusted spreads account for embedded options in corporate bonds, providing a cleaner measure of credit risk than simple yield spreads. The methodology developed by ICE BofA is widely used by institutional investors and central banks for monitoring credit conditions.
The indicator offers two modes. The HY-IG excess spread mode calculates the difference between high yield and investment grade spreads, isolating the pure compensation for below-investment-grade credit risk. This measure is less affected by broad interest rate movements. The HY-only mode tracks the absolute high yield spread, capturing both credit risk and the overall level of risk premiums in the market.
Interpreting the Regimes
Credit conditions are classified into four regimes based on Z-scores calculated from the spread proxy.
The Stress regime occurs when spreads reach extreme levels, typically above a Z-score of 2.0. At this point, credit markets are pricing in significant default risk and economic deterioration. Historically, stress regimes have coincided with recessions, financial crises, and major market dislocations. The 2008 financial crisis, the 2011 European debt crisis, the 2016 commodity collapse, and the 2020 pandemic all triggered credit stress regimes.
The Elevated regime, between Z-scores of 1.0 and 2.0, indicates above-normal risk premiums. Credit conditions are tightening. This often occurs in the build-up to stress events or during periods of uncertainty. Risk management should be heightened, and exposure to credit-sensitive assets may be reduced.
The Normal regime covers Z-scores between -1.0 and 1.0. This represents typical credit conditions where spreads fluctuate around historical averages. Standard investment approaches are appropriate.
The Low regime occurs when spreads are compressed below a Z-score of -1.0. Investors are accepting below-average compensation for credit risk. This can indicate complacency, strong economic confidence, or excessive risk-taking. While often associated with favorable conditions, extremely tight spreads sometimes precede sudden reversals.
Credit Cycle Dynamics
Beyond static regime classification, the indicator tracks the direction and acceleration of spread movements. This reveals where credit markets stand in the credit cycle.
The Deteriorating phase occurs when spreads are elevated and continuing to widen. Credit conditions are actively worsening. This phase often precedes or coincides with economic downturns.
The Recovering phase occurs when spreads are elevated but beginning to narrow. The worst may be over. Credit conditions are improving from stressed levels. This phase often accompanies the early stages of economic recovery.
The Tightening phase occurs when spreads are low and continuing to compress. Credit conditions are very favorable and improving further. This typically occurs during strong economic expansions but may signal building complacency.
The Loosening phase occurs when spreads are low but beginning to widen from compressed levels. The extremely favorable conditions may be normalizing. This can be an early warning of changing sentiment.
Relationship to Economic Activity
The predictive power of credit spreads for economic activity is well-documented. Gilchrist and Zakrajsek found that the excess bond premium predicts GDP growth, industrial production, and unemployment rates over horizons of one to four quarters.
When credit spreads spike, the cost of corporate borrowing increases. Companies may delay or cancel investment projects. Reduced investment leads to slower growth and eventually higher unemployment. The transmission mechanism runs from financial conditions to real economic activity.
Conversely, tight credit spreads lower borrowing costs and encourage investment. Easy credit conditions support economic expansion. However, excessively tight spreads may encourage over-leveraging, planting seeds for future stress.
Practical Application
For equity investors, credit spreads provide context for market risk. Equities and credit often move together because both reflect corporate health. Rising credit spreads typically accompany falling stock prices. Extremely wide spreads historically have coincided with equity market bottoms, though timing the reversal remains challenging.
For fixed income investors, spread regimes guide sector allocation decisions. During stress regimes, flight to quality favors Treasuries over corporates. During low regimes, spread compression may offer limited additional return for credit risk, suggesting caution on high yield.
For macro traders, credit spreads complement other indicators of financial conditions. Credit stress often leads equity volatility, providing an early warning signal. Cross-asset strategies may use credit regime as a filter for position sizing.
Limitations and Considerations
FRED data updates with a lag, typically one business day for the ICE BofA indices. For intraday trading decisions, more current proxies may be necessary. The data is most reliable on daily timeframes.
Credit spreads can remain at extreme levels for extended periods. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. The 2008 crisis saw spreads remain elevated for many months before normalizing.
The indicator is calibrated for US credit markets. Application to other regions would require different data sources such as European or Asian credit indices. The relationship between spreads and subsequent economic activity may vary across market cycles and structural regimes.
References
Collin-Dufresne, P., Goldstein, R.S., and Martin, J.S. (2001). The Determinants of Credit Spread Changes. Journal of Finance, 56(6), 2177-2207.
Gilchrist, S., and Zakrajsek, E. (2012). Credit Spreads and Business Cycle Fluctuations. American Economic Review, 102(4), 1692-1720.
Krishnamurthy, A., and Muir, T. (2017). How Credit Cycles across a Financial Crisis. Working Paper, Stanford University.
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
Macro Timing Window Signal ⏱️ Macro Timing Window Signal – Check/X Indicator
This indicator displays a green check mark ✔️ or red X ✖️ in the top-right corner of the chart based on a repeating macro time cycle that divides every hour into active and inactive windows.
How it works:
• ✔️ Green Check (Active Macro Window):
Appears from xx:45 → xx:15 of the next hour (30-minute macro window).
• ✖️ Red X (Inactive Macro Window):
Appears from xx:16 → xx:44 (mid-hour cooldown window).
• Optional flash signal at the exact macro flip points (xx:45, xx:00, xx:15) to highlight transitions.
• Supports sound alerts so you never miss the start or end of a macro window.
This tool is designed for traders who incorporate macro-driven time cycles, liquidity sessions, or algorithmic delivery windows into their strategy.
The display is fixed on-screen, clean, and unobtrusive, ensuring instant recognition of the current macro state without cluttering the chart.
BTC DCA Risk Metric StrategyBTC DCA Risk Strategy - Automated Dollar Cost Averaging with 3Commas Integration
Overview
This strategy combines the proven Oakley Wood Risk Metric with an intelligent tiered Dollar Cost Averaging (DCA) system, designed to help traders systematically accumulate Bitcoin during periods of low risk and take profits during high-risk conditions.
Key Features
📊 Multi-Component Risk Assessment
4-Year SMA Deviation: Measures Bitcoin's distance from its long-term mean
20-Week MA Analysis: Tracks medium-term momentum shifts
50-Day/50-Week MA Ratio: Captures short-to-medium term trend strength
All metrics are normalized by time to account for Bitcoin's maturing market dynamics
💰 3-Tier DCA Buy System
Level 1 (Low Risk): Conservative entry with base allocation
Level 2 (Lower Risk): Increased allocation as opportunity improves
Level 3 (Extreme Low Risk): Maximum allocation during rare buying opportunities
Buys execute every bar while risk remains below thresholds, enabling true DCA accumulation
📈 Progressive Profit Taking
Sell Level 1: Take initial profits as risk increases
Sell Level 2: Scale out further positions during elevated risk
Sell Level 3: Final exit during extreme market conditions
Sell levels automatically reset when new buy signals occur, allowing flexible re-entry
🤖 3Commas Integration
Fully automated webhook alerts for Custom Signal Bots
JSON payloads formatted per 3Commas API specifications
Supports multiple exchanges (Binance, Coinbase, Kraken, Gemini, Bybit)
Configurable quote currency (USD, USDT, BUSD)
How It Works
The strategy calculates a composite risk metric (0-1 scale):
0.0-0.2: Extreme buying opportunity (green zone)
0.2-0.5: Favorable accumulation range (yellow zone)
0.5-0.8: Neutral to cautious territory (orange zone)
0.8-1.0+: High risk, profit-taking zone (red zone)
Buy Logic: As risk decreases, position sizes increase automatically. If risk drops from L1 to L3 threshold, the strategy combines all three tier allocations for maximum exposure.
Sell Logic: Sequential profit-taking ensures you capture gains progressively. The system won't advance to Sell L2 until L1 completes, preventing premature full exits.
Configuration
Risk Metric Parameters:
All calculations use Bitcoin price data (any BTC chart works)
Time-normalized formulas adapt to market maturity
No manual parameter tuning required
Buy Settings:
Set risk thresholds for each tier (default: 0.20, 0.10, 0.00)
Define dollar amounts per tier (default: $10, $15, $20)
Fully customizable to your risk tolerance and capital
Sell Settings:
Configure risk thresholds for profit-taking (default: 1.00, 1.50, 2.00)
Set percentage of position to sell at each level (default: 25%, 35%, 40%)
3Commas Setup:
Create a Custom Signal Bot in 3Commas
Copy Bot UUID and Secret Token into strategy inputs
Enable 3Commas Alerts checkbox
Create TradingView alert: Condition → "alert() function calls only", Webhook → api.3commas.io
Backtesting Results
Strengths:
Systematically buys dips without emotion
Averages down during extended bear markets
Captures explosive bull run profits through tiered exits
Pyramiding (1000 max orders) allows true DCA behavior
Considerations:
Requires sufficient capital for multiple buys during prolonged downtrends
Backtest on Daily timeframe for most reliable signals
Past performance does not guarantee future results
Visual Design
The indicator pane displays:
Color-coded risk metric line: Changes from white→red→orange→yellow→green as risk decreases
Background zones: Green (buy), yellow (hold), red (sell) areas
Dashed threshold lines: Clear visual markers for each buy/sell level
Entry/Exit labels: Green buy labels and orange/red sell labels mark all trades
Credits
Original Risk Metric: Oakley Wood
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Modifications: pommesUNDwurst
Disclaimer
This strategy is for educational and informational purposes only. Cryptocurrency trading carries substantial risk of loss. Always conduct your own research and never invest more than you can afford to lose. The authors are not financial advisors and assume no responsibility for trading decisions made using this tool.
BTC - FRIC: Friction & Realized Intensity CompositeTitle: BTC - FRIC: Friction & Realized Intensity Composite
Data: IntoTheBlock
Overview & Philosophy
FRIC (Friction & Realized Intensity Composite) is a specialized on-chain oscillator designed to visualize the "psychological battlegrounds" of the Bitcoin network.
Most indicators focus on Price or Momentum. FRIC focuses on Cost Basis. It operates on the thesis that the market experiences maximum "Friction" when the price revisits the cost basis of a large number of holders. These are the zones where investors are emotionally triggered to react—either to exit "at breakeven" after a loss (creating resistance) or to defend their entry (creating support).
This indicator answers two questions simultaneously:
Intensity: Is the market hitting a Wall (High Friction) or a Vacuum (Low Friction)?
Valuation: Is this happening at a market bottom or a top?
The "Alpha" (Wall vs. Vacuum)
Why we visualize both extremes: This indicator filters out the "Noise" (the middle range) to show you only the statistically significant anomalies.
1. The "Wall" (Positive Z-Score Bars)
What it is : A statistically high number of addresses are at breakeven.
The Implication : Expect a grind. Price action often slows down or reverses here because "Bag Holders" are selling into strength to get out flat, or new buyers are establishing a floor.
2. The "Vacuum" (Negative Z-Score Bars)
What it is : A statistically low number of addresses are at breakeven.
The Implication : Expect acceleration. The price is moving through a zone where very few people have a cost basis. With no natural "breakeven supply" to block the path, price often enters Price Discovery or Free Fall.
Methodology
The indicator constructs a composite view using two premium metrics from IntoTheBlock:
1. The "Activity" (Friction Z-Score): We utilize the Breakeven Addresses Percentage. This measures the % of all addresses where the current price equals the average cost basis.
- Normalization: We apply a rolling Z-Score (Standard Deviation) to this data.
- The Filter: We hide the "Noise" (e.g., Z-Scores between -2.0 and +2.0) to isolate only the events where market structure is truly stretched.
2. The "Context" (Valuation Heatmap): We utilize the MVRV Ratio to color-code the friction.
Deep Value (< 1.0): Price is below the average "Fair Value" of the network.
Overheated (> 3.0): Price is significantly extended above the "Fair Value."
Credit: The MVRV Ratio was originally conceptualized by Murad Mahmudov and David Puell. It remains one of the gold standards for detecting Bitcoin's fair value deviations.
How to Read the Indicator
The chart is visualized as a Noise-Filtered Heatmap.
1. The Bars (Intensity)
Bars Above Zero: High Friction (Congestion). The market is fighting through a supply wall.
Bars Below Zero: Low Friction (Vacuum). The market is accelerating through thin air.
Gray/Ghosted: Noise. Routine market activity; no significant signal.
2. The Colors (Valuation Context) The color tells you why the friction is happening:
🟦 Deep Blue (The "Capitulation Buy"):
Signal: High Friction + Low MVRV.
Meaning : Investors are panic-selling at breakeven/loss, but the asset is fundamentally undervalued. Historically, these are high-conviction cycle bottoms.
🟥 Dark Red (The "FOMO Sell"):
Signal: High Friction + High MVRV.
Meaning : Investors are churning at high valuations. Smart money is often distributing to late retail arrivers. Historically marks cycle tops.
🟨 Yellow/Orange (The "Trend Battle"):
Signal: High Friction + Neutral MVRV.
Meaning : The market is contesting a level within a trend (e.g., a mid-cycle correction).
Visual Guide & Features
10-Zone Heatmap: A granular color gradient that shifts from Dark Blue (Deep Value) → Sky Blue → Grey (Neutral) → Orange → Dark Red (Top).
Noise Filter
A unique feature that "ghosts out" insignificant data, leaving only the statistically relevant signals visible.
Data Check Monitor
A diagnostic table in the bottom-right corner that confirms the live connection to IntoTheBlock data streams and displays the current regime in real-time.
Settings
Lookback Period (Default: 90): The rolling window used for the Z-Score calculation. Shortening this (e.g., to 30) makes the indicator more sensitive to local volatility; lengthening it (e.g., to 365) aligns it with macro cycles.
Noise Threshold (Default: 2.0): The strictness of the filter. Only friction events exceeding this Z-Score will be highlighted in full color.
Show Status Table : Toggles the on-screen dashboard.
Disclaimer
This script is for research and educational purposes only. It relies on third-party on-chain data which may be subject to latency or revision. Past performance of on-chain metrics does not guarantee future price action.
Tags
bitcoin, btc, on-chain, mvrv, intotheblock, friction, z-score, fundamental, valuation, cycle
window//@version=5
indicator("Smart Money Time Windows (GMT+3:30)", overlay=true)
// ✅ Window 1 — 08:30 to 09:05 Tehran Time
w1 = time(timeframe.period, "0830-0905", "Asia/Tehran")
// ✅ Window 2 — 13:50 to 14:40 Tehran Time
w2 = time(timeframe.period, "1350-1440", "Asia/Tehran")
// ✅ Window 3 — 17:15 to 18:00 Tehran Time
w3 = time(timeframe.period, "1715-1800", "Asia/Tehran")
bgcolor(not na(w1) ? color.new(color.blue, 85) : na)
bgcolor(not na(w2) ? color.new(color.orange, 85) : na)
bgcolor(not na(w3) ? color.new(color.purple, 85) : na)
5-Bar BreakoutThis indicator shows if the price is breaking out above the high or the low of the previous 5 bars
猛の掟・初動スクリーナー_完成版//@version=5
indicator("猛の掟・初動スクリーナー_完成版", overlay=true)
// =============================
// 入力パラメータ
// =============================
emaLenShort = input.int(5, "短期EMA", minval=1)
emaLenMid = input.int(13, "中期EMA", minval=1)
emaLenLong = input.int(26, "長期EMA", minval=1)
macdFastLen = input.int(12, "MACD Fast", minval=1)
macdSlowLen = input.int(26, "MACD Slow", minval=1)
macdSignalLen = input.int(9, "MACD Signal", minval=1)
macdZeroTh = input.float(0.2, "MACDゼロライン近辺とみなす許容値", step=0.05)
volMaLen = input.int(5, "出来高平均日数", minval=1)
volMinRatio = input.float(1.3, "出来高倍率(初動判定しきい値)", step=0.1)
volStrongRatio = input.float(1.5, "出来高倍率(本物/三点シグナル用)", step=0.1)
highLookback = input.int(60, "直近高値の参照本数", minval=10)
pullbackMin = input.float(5.0, "押し目最小 ", step=0.5)
pullbackMax = input.float(15.0, "押し目最大 ", step=0.5)
breakLookback = input.int(15, "レジブレ後とみなす本数", minval=1)
wickBodyMult = input.float(2.0, "ピンバー:下ヒゲが実体の何倍以上か", step=0.5)
// ★ シグナル表示 ON/OFF
showMou = input.bool(true, "猛シグナルを表示")
showKaku = input.bool(true, "確シグナルを表示")
// =============================
// 基本指標計算
// =============================
emaShort = ta.ema(close, emaLenShort)
emaMid = ta.ema(close, emaLenMid)
emaLong = ta.ema(close, emaLenLong)
= ta.macd(close, macdFastLen, macdSlowLen, macdSignalLen)
volMa = ta.sma(volume, volMaLen)
volRatio = volMa > 0 ? volume / volMa : 0.0
recentHigh = ta.highest(high, highLookback)
prevHigh = ta.highest(high , highLookback)
pullbackPct = recentHigh > 0 ? (recentHigh - close) / recentHigh * 100.0 : 0.0
// ローソク足
body = math.abs(close - open)
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
// =============================
// A：トレンド条件
// =============================
emaUp = emaShort > emaShort and emaMid > emaMid and emaLong > emaLong
goldenOrder = emaShort > emaMid and emaMid > emaLong
aboveEma2 = close > emaLong and close > emaLong
trendOK = emaUp and goldenOrder and aboveEma2
// =============================
// B：MACD条件
// =============================
macdGC = ta.crossover(macdLine, macdSignal)
macdNearZero = math.abs(macdLine) <= macdZeroTh
macdUp = macdLine > macdLine
macdOK = macdGC and macdNearZero and macdUp
// =============================
// C：出来高条件
// =============================
volInitOK = volRatio >= volMinRatio // 8条件用
volStrongOK = volRatio >= volStrongRatio // 三点シグナル用
volumeOK = volInitOK
// =============================
// D：ローソク足パターン
// =============================
isBullPinbar = lowerWick > wickBodyMult * body and lowerWick > upperWick and close >= open
isBullEngulf = close > open and open < close and close > open
isBigBullCross = close > emaShort and close > emaMid and open < emaShort and open < emaMid and close > open
candleOK = isBullPinbar or isBullEngulf or isBigBullCross
// =============================
// E：価格帯（押し目＆レジブレ）
// =============================
pullbackOK = pullbackPct >= pullbackMin and pullbackPct <= pullbackMax
isBreakout = close > prevHigh and close <= prevHigh
barsSinceBreak = ta.barssince(isBreakout)
afterBreakZone = barsSinceBreak >= 0 and barsSinceBreak <= breakLookback
afterBreakPullbackOK = afterBreakZone and pullbackOK and close > emaShort
priceOK = pullbackOK and afterBreakPullbackOK
// =============================
// 8条件の統合
// =============================
allRulesOK = trendOK and macdOK and volumeOK and candleOK and priceOK
// =============================
// 最終三点シグナル
// =============================
longLowerWick = lowerWick > wickBodyMult * body and lowerWick > upperWick
macdGCAboveZero = ta.crossover(macdLine, macdSignal) and macdLine > 0
volumeSpike = volStrongOK
finalThreeSignal = longLowerWick and macdGCAboveZero and volumeSpike
buyConfirmed = allRulesOK and finalThreeSignal
// =============================
// 描画
// =============================
plot(emaShort, color=color.new(color.yellow, 0), title="EMA 短期(5)")
plot(emaMid, color=color.new(color.orange, 0), title="EMA 中期(13)")
plot(emaLong, color=color.new(color.blue, 0), title="EMA 長期(26)")
// シグナル表示（ON/OFF付き）
plotshape(showMou and allRulesOK, title="猛の掟 8条件クリア候補", location=location.belowbar, color=color.new(color.lime, 0), text="猛")
plotshape(showKaku and buyConfirmed, title="猛の掟 最終三点シグナル確定", location=location.belowbar, color=color.new(color.yellow, 0), text="確")
// =============================
// アラート条件
// =============================
alertcondition(allRulesOK, title="猛の掟 8条件クリア候補", message="猛の掟 8条件クリア候補シグナル発生")
alertcondition(buyConfirmed, title="猛の掟 最終三点シグナル確定", message="猛の掟 最終三点シグナル＝買い確定")
Renko Scalp ScannerThis scanner is optimized for short term bursts for Renko.
DESCRIPTION: This indicator scans the 7 major forex pairs (EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD) on 1-pip Renko charts. It ranks them from BEST (#1, top row) to WORST (#7, bottom row) based on a predictive score (0-100) that combines LIVE momentum (current run length, whipsaws, brick timing) + 24-HOUR HISTORICAL consistency (clean long runs, stability).
Higher score = longer, cleaner, more predictable runs ahead (backtested 74% hit rate for 5+ brick continuations).
HOW TO USE THE TABLE:
1. Add to a 1-second Renko chart (Traditional, Box Size: 0.0001 for non-JPY; 0.01 for JPY pairs).
2. RANK: Position 1–7 (green highlight on #1 = switch to this pair NOW).
3. PAIR: Symbol + direction arrow (↑=buy bias, ↓=sell bias).
4. SCORE: 0–100 total (≥85=monster run; ≥75=strong; ≥60=decent; <60=avoid).
5. RUN │ HIST% │ SEC: Current live run length │ % of 24h runs that were clean 8+ bricks │ Live avg seconds per brick (ideal 5–12s).
6. Trade the #1 pair in the arrow direction until whipsaw or score drops <75. Set alerts for score ≥83.
Backtested on 1-year data: Catches 84% of 10+ brick runners. Refreshes every second.
Zero Lag EMA_BhavatThis is a test script for zelma. This is intended to cut down the lag from traditional ema indicators.
specific breakout FiFTOStrategy Description: 10:14 Breakout Only
Overview This is a time-based intraday trading strategy designed to capture momentum bursts that occur specifically after the 10:14 AM candle closes. It operates on the logic that if price breaks the high of this specific candle within a short window, a trend continuation is likely.
Core Logic & Rules
The Setup Candle (10:14 AM)
The strategy waits specifically for the minute candle at 10:14 to complete.
Once this candle closes, the strategy records its High price.
Defining the Entry Level
It calculates a trigger price by taking the 10:14 High and adding a user-defined Buffer (e.g., +1 point).
Formula: Entry Level = 10:14 High + Buffer
The "Active Window" (Expiry)
The trade setup does not remain open all day. It has a strict time limit.
By default, the setup is valid from 10:15 to 10:20.
If the price does not break the Entry Level by the expiry time (default 10:20), the setup is cancelled and no trade is taken for the day.
Entry Trigger
If a candle closes above the Entry Level while the window is open, a Long (Buy) position is opened immediately.
Exits (Risk Management)
Stop Loss: A fixed number of points below the entry price.
Target: A fixed number of points above the entry price.
Visual & Automation Features
Visual Boxes: Upon entry, the strategy draws a "Long Position" style visual on the chart. A green box highlights the profit zone, and a red box highlights the loss zone. These boxes extend automatically until the trade closes.
JSON Alerts: The strategy is pre-configured to send data-rich alerts for automation (e.g., Telegram bots).
Entry Alert: Includes Symbol, Entry Price, SL, and TP.
Exit Alerts: Specific messages for "Target Hit" or "SL Hit".
Summary of User Inputs
Entry Buffer: Extra points added to the high to filter false breaks.
Fixed Stop Loss: Risk per trade in points.
Fixed Target: Reward per trade in points.
Expiry Minute: The minute (10:xx) at which the setup becomes invalid if not triggered.
VIX/VXV Ratio (TitsNany)This script plots the VXV/VIX ratio, which compares medium-term volatility (90-day fear) to short-term volatility (30-day fear). When the ratio rises above key levels like 1.16 or 1.24, it signals that traders expect future stress, often preceding market pullbacks. When the ratio falls toward or below 1.0, short-term fear is spiking, which typically occurs during active selloffs or volatility events. In short, elevated readings warn of potential market drops ahead, while sharp declines in the ratio reflect panic already hitting the market.
Status + BollingersThis combined indicator provides a concise view of the market's current state, volatility, and momentum using key technical metrics displayed on a central dashboard and overlaid on the price chart.
The Bollinger Bands consist of a 20-period Simple Moving Average (SMA) as the middle line, bounded by an upper and lower band (typically $2.0$ Standard Deviations).
Function: Measures volatility.
CRSI (RSI) Red ($>70$), Lime ($<30$) - Indicates Overbought (Red) or Oversold (Lime) pressure, signaling possible reversals.
ADX Orange ($>30$), Gray ($<20$) - Measures Trend Strength, regardless of direction. Orange means strong trend (ideal for trend following); Gray means weak/ranging market.
Volume Status "Bang" (Red) Safe (Green) - Compares current volume to the average. "Patladı" indicates a significant volume spike (momentum confirmation), suggesting institutional activity or a decisive move.
CRR - Reloj Sesiones & DominioIt uses simple rules:
00:00 – 07:00 → Tokyo / ASIA
07:00 – 12:00 → London / EUROPE
12:00 – 21:00 → New York / AMERICA
21:00 – 24:00 → Outside main sessions
Each session is assigned a color:
Tokyo → Blue
London → Yellow
New York → Green
Outside → Gray
2. Displays the current time in GMT format
Example: 14:32 GMT
3. Minimalist on-screen display (HUD)
The top center of the screen shows:
Continent (ASIA / EUROPE / AMERICA)
Which session is currently dominant (TOKYO / LONDON / NEW YORK)
The GMT time
All in a sleek table with dynamic colors based on the session.
🧠 In short:
A smart clock that tells you which session is dominant, which continent you're in, and what time it is in GMT, with a nice on-screen HUD.
NoProcess PivotsNoProcess Pivots
Visualize the structural framework of price action with NoProcess Pivots, a precision tool for multi-timeframe confluence trading.
Pivots are mathematically derived levels where price statistically finds support, resistance, or equilibrium. Institutional order flow respects these levels as key decision points where liquidity pools form and inefficiencies seek rebalancing.
NoProcess Pivots displays historical pivot ranges as period-bounded zones across Daily, Weekly, and Quarterly timeframes—allowing you to observe how price has respected or violated these levels over time. By projecting ±33% extensions beyond R1/S1, traders can identify targets, retracement levels, and key reversal points.
Cross-reference pivots across multiple timeframes to find confluence zones where Daily, Weekly, and Quarterly levels stack. These high-conviction areas offer the clearest setups for entries and exits.
Features:
Multi-timeframe pivots: Daily, Weekly, Quarterly
Historical levels with adjustable depth
Period-bounded zones
±33% extensions
Adaptive light/dark mode table
Real-time Δ PP percentage
Pivot cross alerts
Built for traders who respect the math behind the markets.
BörsenampelThe “VIX/VVIX Traffic Light (Panel)” visualizes the current market risk as a simple traffic light (green / yellow / red) in the top‑right corner of the chart, based on the VIX and VVIX indices.
How it works
The script loads the VIX and VVIX indices via request.security and evaluates them using user‑defined threshold levels.
Green: VIX and VVIX are below their “green” thresholds, indicating a calm market environment and more risk‑on conditions.
Red: VIX and VVIX are above their “red” thresholds, signalling stress or panic phases with elevated risk.
Yellow: Transitional zone between the two extremes.
Chart display
A small panel with the title “Traffic Light” is shown in the upper‑right corner of the chart.
The central box displays the current status (“GREEN”, “YELLOW”, “RED”) with a matching background color.
Optionally, the current VIX and VVIX values are shown below the status.
Inputs and usage
Symbols for VIX and VVIX can be freely chosen (default: CBOE:VIX and CBOE:VVIX).
The green/red thresholds can be adjusted to fit personal volatility rules or different markets.
Indian Scalper 2025 – PSAR + SMA50 + RSI≤50 + High Volume (75%)Best 1-min / 2-min scalping strategy for NIFTY, BANKNIFTY, FINNIFTY & liquid stocks in 2025
✓ PSAR flip + SMA-50 trend filter
✓ RSI ≤50 (avoids chasing)
✓ Only high-volume candles (bright colour)
✓ Loud mobile alerts with price & SL
✓ 1:2+ RR with PSAR trailing
Works like magic 9:15–11:30 AM and 2–3:20 PM
Made with love for the Indian trading community ♥
