NSE Bullish Swing Strategy - 7-8% TargetHelps capture bullish swing trading set ups ( PULL BACK , BREAKOUT & MOMENTUM ) and achieve 7-8 % profit in minimum possible time. Also scans the trend continuously & gives the strength of the trend. Use in daily time frame.
Only for educational use.
Educational
30-Minute High and Low30-Minute High and Low Levels
This indicator plots the previous 30-minute candle’s high and low on any intraday chart.
These levels are widely used by intraday traders to identify key breakout zones, liquidity pools, micro-range boundaries, and early trend direction.
Features:
• Automatically pulls the previous 30-minute candle using higher-timeframe HTF requests
• Displays the HTF High (blue) and HTF Low (red) on lower-timeframe charts
• Works on all intraday timeframes (1m, 3m, 5m, 10m, etc.)
• Levels stay fixed until the next 30-minute bar completes
• Ideal for ORB strategies, scalping, liquidity sweeps, and reversal traps
Use Cases:
• Watch for breakouts above the 30-minute high
• Monitor for liquidity sweeps and fakeouts around the high/low
• Treat the mid-range as a magnet during consolidation
• Combine with VWAP or EMA trend structure for high-precision intraday setups
This indicator is simple, fast, and designed for traders who rely on HTF micro-structure to guide intraday execution.
VWolf – Slope GuardOVERVIEW
Slope Guard combines a momentum core (WaveTrend + RSI/MFI + QQE family) with a directional bias (EMA/DEMA and a DEMA-slope filter). Trade direction can be constrained by the Supertrend regime (Normal or Pivot). Risk is managed with ATR-based stops and targets, optional Supertrend-anchored dynamic levels, and a two-stage take-profit that can shift the stop to break-even after the first partial. The strategy supports explicit Backtest and Forward-test windows and adapts certain thresholds by market type (Forex vs. Stocks).
RECOMMENDED USE
Markets: Forex and equities; use Market Type to properly scale the DEMA-slope gate.
Timeframes: M15–H4 for intraday-swing and H1–D1 for slower swing; avoid ultra-low TFs without tightening ADX/QQE.
Assets: Instruments with persistent trends and orderly pullbacks; avoid flat ranges without sufficient ADX.
Strengths
Multi-layer confluence: trend bias + momentum + regime + strength.
Flexible risk engine: ATR vs. Supertrend anchoring, staged exits, and automatic break-even.
Clean research workflow: separated Backtest and Forward-test windows.
Precautions
Structural latency: Pivot-based constructs confirm with delay; validate with Forward-test.
Filter interaction: QQE Strict + ADX + WT zero-line can become overly selective; calibrate by asset/TF.
Overfitting risk: Prefer simple, portable parameter sets and validate across symbols/TFs.
CONCLUSION
Slope Guard is a “trend + momentum” framework with risk control at its core. By enforcing a baseline bias, validating momentum with the Vuman composite, and offering ATR or Supertrend-anchored exits—plus staged profits and break-even shifts—it seeks to capture the core of directional swings while compressing drawdowns. Keep testing windows isolated, start with moderate filters (QQE Normal, ADX ~20–25), and only add stricter gates (WT zero-line, DEMA slope) once they demonstrably improve stability without starving signals.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Shadow PulseOVERVIEW
The Trend Momentum Breakout Strategy is a rule-based trading system designed to identify high-probability entries in trending markets using a combination of trend confirmation, momentum filtering, and precise trigger conditions. The strategy is suitable for intermediate to advanced traders who prefer mechanical systems with clear entry/exit logic and configurable risk management options.
At its core, this strategy seeks to enter pullbacks within strong trends, capitalizing on momentum continuation after brief pauses in price movement. By integrating multiple moving averages (MAs) for trend validation, ADX (Average Directional Index) as a strength filter, and Stochastic RSI as an entry trigger, the strategy filters out weak trends and avoids overextended market conditions. Exit logic is based on a customizable fixed stop-loss (SL) and take-profit (TP) framework, with optional dynamic risk-reduction mechanisms powered by the Supertrend indicator.
This strategy is designed to perform best in clearly trending markets and is especially effective in avoiding false breakouts or choppy sideways action thanks to its ADX-based filtering. It can be deployed across a variety of asset classes, including forex, stocks, cryptocurrencies, and indices, and is optimized for intra-day to swing trading timeframes.
RECOMMENDED USE
This strategy is designed to be flexible across multiple markets, but it performs best under certain conditions:
Best Suited For:
Trending markets with clear directional momentum.
High-volume instruments that avoid erratic price action.
Assets with intraday volatility and swing patterns.
Recommended Asset Classes:
Forex pairs (e.g., EUR/USD, GBP/JPY)
Cryptocurrencies (e.g., BTC/USD, ETH/USDT)
Major indices (e.g., S&P 500, NASDAQ, DAX)
Large-cap stocks (especially those with consistent liquidity)
Suggested Timeframes:
15-minute to 1-hour charts for intraday setups.
4-hour and daily charts for swing trading.
Lower timeframes (1–5 min) may generate too much noise unless fine-tuned.
Market Conditions to Avoid:
Ranging or sideways markets with low ADX values.
Assets with irregular price structures or low liquidity.
News-heavy periods with unpredictable price spikes.
CONCLUSION
This strategy stands out for its robust and modular approach to trend-following trading, offering a high level of customization while maintaining clear logic and structural discipline in entries and exits. By combining three distinct layers of confirmation—trend identification (via configurable moving averages), trend strength validation (via the DMI filter), and timing (via the Stochastic RSI trigger)—it aims to reduce noise and increase the probability of entering trades with directional bias and momentum on its side.
Its flexibility is one of its strongest points: users can tailor the strategy to fit various trading styles and market conditions. Whether the trader prefers conservative setups using only the slowest moving average, or more aggressive entries requiring full alignment of fast, medium, and slow MAs, the system adjusts accordingly. Likewise, exit management offers both static and dynamic methods—such as ATR-based stop losses, Supertrend-based adaptive exits, and partial profit-taking mechanisms—allowing risk to be managed with precision.
This makes the strategy particularly suitable for trend-driven markets, such as major currency pairs, indices, or volatile stocks that demonstrate clear directional moves. It is not ideal for sideways or choppy markets, where multiple filters may reduce the number of trades or result in whipsaws.
From a practical standpoint, the strategy also incorporates real-world trading mechanics, like time-based filters and account risk control, which elevate it from a purely theoretical model to a more execution-ready system.
In summary, this is a well-structured, modular trend strategy ideal for intermediate to advanced traders who want to maintain control over their system parameters while still benefiting from layered signal confirmation. With proper calibration, it has the potential to become a reliable tool in any trader’s arsenal—particularly in markets where trends emerge clearly and sustainably.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Raptor ClawOVERVIEW
The 'VWolf - Raptor Claw' is a straightforward scalping strategy designed for high-frequency trades based on the Stochastic RSI indicator. It focuses exclusively on identifying potential trend reversals through stochastic cross signals in extreme zones, without the need for additional confirmations. This makes it highly responsive to market movements, capturing rapid price shifts while maintaining simplicity.
This strategy is best suited for highly liquid and volatile markets like forex, indices, and major cryptocurrencies, where quick momentum shifts are common. It is ideal for experienced scalpers who prioritize fast entries and exits, but it can also be adapted for swing trading in lower timeframes.
Entry Conditions:
Long Entry:Stochastic RSI crosses above the oversold threshold (typically 20), indicating a potential bullish reversal.
Short Entry:Stochastic RSI crosses below the overbought threshold (typically 80), indicating a potential bearish reversal.
Exit Conditions:
Stop Loss: Set at the minimum (for longs) or maximum (for shorts) within a configurable lookback window to reduce risk.
Take Profit: Defined by a risk-reward ratio (RRR) input to optimize potential gains relative to risk.
CONCLUSION
The 'VWolf - Raptor Claw' strategy is perfect for traders seeking a simple yet aggressive approach to the markets. It capitalizes on sharp momentum shifts in extreme zones, relying on precise stop loss and take profit settings to capture rapid profits while minimizing risk. This approach is highly effective in high-volatility environments where quick decision-making is essential.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Quantum DriftOVERVIEW
The Quantum Drift strategy is a sophisticated, highly customizable trading approach designed to identify market entries and exits by leveraging multiple technical indicators. The strategy uniquely combines the Dynamic Exponential Moving Average (DEMA), QQE indicators, Volume Oscillator, and Hull Moving Average (HULL), enabling precise detection of trend direction, momentum shifts, and volatility adjustments. It stands out due to its adaptability across different market conditions by allowing significant user customization through various input parameters.
RECOMMENDED USE
Markets: Ideal for Forex and Stocks due to the strategy's volatility-sensitive and trend-following nature.
Timeframes: Best suited for medium to higher timeframes (15m, 1H, 4H), where clearer trend signals and less noise occur, enhancing strategy reliability.
CONCLUSION
The Quantum Drift strategy is tailored for intermediate to advanced traders seeking a versatile and adaptive system. Its strength lies in combining momentum, volatility, and trend-following components, providing robust entry and exit signals. However, its effectiveness relies significantly on accurate parameter tuning by traders familiar with the underlying indicators and market behavior.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – Pivot VumanSkewOVERVIEW
This strategy blends a lightweight trend scaffold (EMA/DEMA) with a skew-of-volatility filter and VuManchu/WaveTrend momentum signals. It’s designed to participate only when trending structure, momentum alignment, and volatility asymmetry converge, while delegating execution management to either a standard SuperTrend or a Pivot-based SuperTrend. Position sizing is risk‑based, with optional two‑step profit taking and automatic stop movement once price confirms in favor.
RECOMMENDED USE
Markets: Designed for Forex and equities, and readily adaptable to indices or liquid futures.
Timeframes: Performs best from 15m to 4h where momentum and trend layers both matter; daily can be used for confirmation/context.
Conditions: Trending or range‑expansion phases with clear volatility asymmetry. Avoid extremely compressed sessions unless thresholds are relaxed.
Strengths
Multi‑layer confluence (trend + skew + momentum) reduces random signals.
Dual SuperTrend modes provide flexible trailing and regime control.
Built‑in hygiene (ADX/DMI, lockout after loss, ATR gap) curbs over‑trading.
Risk‑% sizing and two‑step exits support consistent, plan‑driven execution.
Precautions
Over‑tight thresholds can lead to missed opportunities; start from defaults and tune gradually.
High sensitivity in momentum settings may overfit to a single instrument/timeframe.
In very low volatility, ATR‑gap or skew filters may block entries—consider adaptive thresholds.
CONCLUSION
VWolf – Pivot VumanSkew is a disciplined trend‑participation strategy that waits for directional structure, volatility asymmetry, and synchronized momentum before acting. Its execution layer—selectable between Normal and Pivot SuperTrend—keeps management pragmatic: scale out early when appropriate, trail intelligently, and defend capital with volatility‑aware stops. For users building a diversified playbook, Pivot VumanSkew serves as a trend‑continuation workhorse that can be tightened for precision or relaxed for higher participation depending on the market’s rhythm.
VWolf – Momentum TwinOVERVIEW
VWolf – Momentum Twin is designed to identify high-probability momentum reversals emerging from overbought or oversold market conditions. It employs a double confirmation from the Stochastic RSI oscillator, optionally filtered by trend and directional movement conditions, before executing trades.
The strategy emphasizes consistent risk management by scaling stop-loss and take-profit targets according to market volatility (ATR), and it provides advanced position management features such as partial profit-taking and automated stop-loss adjustments.
RECOMMENDED USE
Markets: Major FX pairs, index futures, large-cap stocks, and top-volume cryptocurrencies.
Timeframes: Best suited for M15–H4; adaptable for swing trading on daily charts.
Trader Profile: Traders who value structured, volatility-adjusted momentum reversal setups.
Strengths:
Double confirmation filters out many false signals.
Multiple filter options allow strategic flexibility.
ATR scaling maintains consistent risk across assets.
Trade management tools improve adaptability in dynamic markets.
Precautions:
May produce fewer trades in strong one-direction trends.
Over-filtering can reduce trade frequency.
Requires validation across instruments and timeframes before deployment.
CONCLUSION
The VWolf – Momentum Twin offers a disciplined framework for capturing momentum reversals while preserving flexibility through its customizable filters and risk controls. Its double confirmation logic filters out a significant portion of false reversals, while ATR-based scaling ensures consistency across varying market conditions. The optional trade management features, including partial profit-taking and automatic stop adjustments, allow the strategy to adapt to both trending and ranging environments. This makes it a versatile tool for traders who value structured entries, robust risk control, and adaptable management in a variety of markets and timeframes.
🐋 MACRO POSITION TRADER - Quarterly Alignment 💎Disclaimer: This tool is an alignment filter and educational resource, not financial advice. Backtest and use proper risk management. Past performance does not guarantee future returns.
so the idea behind this one came from an experience i had when i first started learning how to trade. dont laugh at me but i was the guy to buy into those stupid AI get rich quick schemes or the first person to buy the "golden indicator" just to find out that it was a scam. Its also to help traders place trades they can hold for months with high confidence and not have to sit in front of charts all day, and to also scale up quickly with small accounts confidently. and basically what it does is gives an alert once the 3 mo the 6 mo and the 12 mo tfs all align with eachother and gives the option to toggle on or off the 1 mo tf as well for extra confidence. Enter on the 5M–15M after a sweep + CHOCH in the direction of the aligned 1M–12M bias. that simple just continue to keep watching key levels mabey take profit 1-2 weeks and jump back in scaling up if desired..easy way to combine any small account size.
Perfect balance of:
low risk
high R:R
optimal precision
minimal chop
best sweep/CHOCH clarity
hope you guys enjoy this one.
VWolf – EquinoxOVERVIEW
The VWolf – Equinox strategy integrates multiple technical filters, skew deviation logic, and advanced momentum indicators to identify high-probability trend continuation and reversal setups. Built upon the Vumanchu framework, this strategy applies filters such as EMA, DEMA, Supertrend, QQE, ADX/DMI, and customized skew thresholds. It combines these with divergence detection, volatility conditions, and risk-managed trade execution for dynamic adaptability across market conditions.
Its architecture is designed to provide flexibility for both backtesting and forward testing periods, while allowing traders to fine-tune entry confirmations and risk management tools based on their preferred market or timeframe.
RECOMMENDED USE
Markets: Forex, equities, and potentially crypto markets due to skew/volatility adaptability.
Timeframes: Works best on intraday (15m–1H) and swing-trading (4H–1D) horizons.
Trader Profile: Suited for intermediate to advanced traders who value multiple confirmation layers and dynamic risk management.
Strengths:
Robust filter system reduces false signals.
Flexible exit strategies with dynamic profit-taking.
Adaptability across different assets and timeframes.
Precautions:
Complexity may overwhelm beginners; careful parameter tuning is recommended.
Too many active filters can reduce signal frequency, potentially missing opportunities.
Divergence and skew thresholds require calibration to each market’s volatility regime.
CONCLUSION
The VWolf – Equinox stands out as one of the most comprehensive strategies in the VWolf library, combining skew deviation with a wide array of technical filters. Its layered confirmation system reduces noise and improves reliability across volatile markets. While powerful, its effectiveness depends on thoughtful parameter selection and disciplined risk management. This makes it a strong candidate for experienced traders seeking depth, adaptability, and dynamic trade control.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Basic EdgeOVERVIEW
VWolf - Basic Edge is a clean and accessible crossover strategy built on the core principle of moving average convergence. Designed for simplicity and ease of use, it allows traders to select from multiple types of moving averages—including EMA, SMA, HULL, and DEMA—and defines entry points strictly based on the crossover of two user-defined MAs.
This strategy is ideal for traders seeking a minimal, no-frills trend-following system with flexible exit conditions. Upon crossover in the selected direction (e.g., fast MA crossing above slow MA for a long entry), the strategy opens a trade and then manages the exit based on the user’s chosen method:
Signal-Based Exit:Trades are closed on the opposite crossover signal (e.g., long is exited when the fast MA crosses below the slow MA).
Fixed SL/TP Exit:The trade is closed based on fixed Stop Loss and Take Profit levels.Both SL and TP values are customizable via the strategy’s input settings.Once either the TP or SL is reached, the position is exited.
Additional filters such as date ranges and session times are available for backtesting control, but no extra indicators are used—staying true to the “basic edge” philosophy. This strategy works well as a starting framework for beginners or as a reliable, lightweight system for experienced traders wanting clean, rule-based entries and exits.
RECOMMENDED FOR
- Beginner to intermediate traders who want a transparent and easy-to-follow system.
- Traders looking to understand or build upon classic moving average crossover logic.
- Users who want a customizable but uncluttered strategy framework.
🌍 Markets & Instruments:
Well-suited for liquid and trending markets, including:Major forex pairs
Stock indices
Commodities (e.g., gold, oil)
Cryptocurrencies with stable trends (e.g., BTC, ETH)
⏱ Recommended Timeframes:
Performs best on higher intraday or swing trading timeframes, such as:15m, 1h, 4h, and 1D
Avoid low-timeframe noise (e.g., 1m, 3m) unless paired with strict filters or volatility controls.
FOR MORE INFORMATION VISIT vwolftrading.com
ShooterViz Lazy Trader EMA SystemShooterViz Lazy Trader EMA System - Complete User Guide
What This Script Does
This is a position scaling indicator that tells you exactly when to enter, add to, and exit trades using a simplified 5-EMA system. It removes the guesswork and decision fatigue from trading by giving you clear visual signals.
The Core Concept
3 entry signals that build your position from 20% → 50% → 100%
2 exit signals that scale you out at 50% → 50% (complete exit)
1 higher timeframe filter that keeps you on the right side of the trend
No Fibonacci calculations, no RSI divergence, no multi-indicator confusion. Just EMAs and price action.
What You'll See On Your Chart
1. Colored EMA Lines
Blue Lines (Entry Zone):
3 EMA (lightest blue) - Early reversal detector
5 EMA (darker blue) - Confirmation line
Green Lines (Add Zone):
21 EMA (bright green) - First add location
34 EMA (lighter green) - Final add location
Red Lines (Exit Zone):
89 EMA (lighter red) - First exit trigger
144 EMA (darker red) - Final exit trigger
Orange Lines (Hyper Frame - optional):
Hyper 21 EMA (from higher timeframe) - Trend direction
Hyper 34 EMA (from higher timeframe) - Bias confirmation
2. Triangle Signals
Green Triangles (Below Price) = BUY/ADD:
Lime triangle with "20%" = Entry 1: Price reclaimed 3→5 EMA (starter position)
Green triangle with "30%" = Entry 2: Price bounced off 21 EMA (first add)
Teal triangle with "50%" = Entry 3: Price broke out from 34 EMA compression (final add)
Red Triangles (Above Price) = SELL:
Orange triangle with "50% OFF" = Exit 1: Price broke below 89 EMA (take half off)
Red triangle with "EXIT ALL" = Exit 2: Price broke below 144 EMA (close remaining position)
3. Background Color (Trend Bias)
Light green background = Hyper frame EMAs trending up (bias LONG)
Light red background = Hyper frame EMAs trending down (bias SHORT)
Gray background = Neutral/choppy (be cautious)
4. Info Table (Top Right Corner)
A live status dashboard showing:
Which entry signals are currently active (✓ or —)
Which exit signals are currently active (⚠ or ⛔)
Current hyper frame bias (🟢 LONG / 🔴 SHORT / ⚪ NEUTRAL)
Which timeframe you're using for hyper frame filtering
How to Install and Set Up
Step 1: Add the Script to TradingView
Open TradingView
Click "Pine Editor" at the bottom of the screen
Copy the entire script code
Paste it into the Pine Editor
Click "Add to Chart"
Step 2: Configure Your Settings
Click the gear icon ⚙️ next to "LazyEMA" in your indicators list.
Critical Settings to Configure:
Hyper Frame Selection (Most Important!)
Location: "Hyper Frame (Pick ONE)" section
Setting: "Timeframe"
What to choose:
Trading 15min or 1H charts? → Use "240" (4-hour)
Trading 4H or Daily charts? → Use "D" (Daily)
Trading Daily or Weekly charts? → Use "W" (Weekly)
Why this matters: This filter keeps you aligned with the bigger trend. Only take longs when this timeframe is green, shorts when it's red.
MA Type (Optional, default is fine)
Location: "MA Config" section
Default: EMA (recommended)
Options: EMA, SMA, WMA, HMA, RMA, VWMA
Most traders should stick with EMA
Visual Toggles (Customize your view)
Entry Zone: Turn individual EMAs on/off (3, 5, 21, 34)
Exit Zone: Turn individual EMAs on/off (89, 144)
Hyper Frame: Toggle the higher timeframe EMAs on/off
Step 3: Clean Up Your Chart
Turn OFF these if visible:
Volume bars (they clutter the view)
Any other indicators you have loaded
Grid lines (optional, but cleaner)
Keep ONLY:
Price candles
Your ShooterViz Lazy Trader EMA System
Maybe support/resistance levels if you manually draw them
How to Trade With This Script
The Basic Workflow
Before the Market Opens:
Check the background color and info table bias
Green background? Look for LONG setups only
Red background? Look for SHORT setups only
Gray background? Stay flat or trade small
During the Trading Session:
LONGS (When hyper frame is bullish):
Wait for Entry 1 signal:
Lime triangle appears with "20%"
Price has reclaimed the 5 EMA after dipping to 3 EMA
Action: Enter 20% of your intended position
Stop loss: Place below the 5 EMA or recent swing low
Wait for Entry 2 signal:
Green triangle appears with "30%"
Price pulled back to 21 EMA and bounced
Action: Add 30% more (you're now at 50% total)
Move stop: Trail it up to below 21 EMA
Wait for Entry 3 signal:
Teal triangle appears with "50%"
Price compressed at 34 EMA and broke out
Action: Add final 50% (you're now 100% loaded)
Move stop: Trail it up to below 34 EMA
Wait for Exit 1 signal:
Orange triangle appears with "50% OFF"
Price broke below 89 EMA
Action: Exit 50% of your position immediately
Move stop on rest: Trail to 89 EMA or lock in profits
Wait for Exit 2 signal:
Red triangle appears with "EXIT ALL"
Price broke below 144 EMA
Action: Exit remaining 50% (you're now flat)
Or: Stop gets hit at 89 EMA (same result)
SHORTS (When hyper frame is bearish):
Same process, but inverted
Triangles appear above price instead of below
Look for breakdowns below EMAs instead of bounces off them
Exit when price reclaims 89 and 144 EMAs
Real-World Example Walkthrough
Setup: Trading ES (S&P 500 Futures) on 1H Chart
Chart Configuration:
Timeframe: 1 Hour
Hyper Frame: 240 (4-hour)
Ticker: ES
Pre-Market Check:
Background is light green
Info table shows "🟢 LONG" for Hyper Bias
Decision: Only look for long entries today
9:30 AM - Market Opens
Price dips and touches 3 EMA
Watch for: Reclaim of 5 EMA
9:45 AM - Entry 1 Triggers
Lime triangle appears below bar
Price closed above 5 EMA at $4,550
Action taken:
Enter long 20% position (2 contracts if targeting 10 total)
Stop loss at $4,545 (below 5 EMA)
Risk: $10 per contract × 2 = $20 risk
10:30 AM - Entry 2 Triggers
Price rallied to $4,565, pulls back
Green triangle appears at 21 EMA ($4,555)
Action taken:
Add 30% (3 more contracts, now have 5 total)
Move stop to $4,550 (below 21 EMA)
Current P/L: +$25 ($5 gain on original 2 contracts, break-even on new 3)
11:15 AM - Entry 3 Triggers
Price consolidates at 34 EMA around $4,560
Teal triangle appears as price breaks to $4,568
Action taken:
Add final 50% (5 more contracts, now have 10 total)
Move stop to $4,555 (below 34 EMA)
Current P/L: +$70
1:00 PM - Price Extends
Price rallies to $4,595 (on track)
89 EMA is at $4,575
No action yet, let it run
2:15 PM - Exit 1 Triggers
Price pulls back from $4,600
Orange triangle appears as price breaks below 89 EMA at $4,580
Action taken:
Exit 50% (5 contracts closed at $4,580)
Keep 5 contracts with stop at 89 EMA ($4,575)
Banked: +$150 average gain on closed 5 contracts
2:45 PM - Exit 2 Triggers
Price continues down
Red triangle appears as price breaks 144 EMA at $4,570
Action taken:
Exit remaining 5 contracts at $4,570
Banked: +$100 on remaining 5 contracts
Final Results:
Total gain: $250 on the trade
Initial risk: $50 (if stopped out at Entry 1)
Risk/Reward: 5:1
Time in trade: ~5 hours
Common Questions
"What if I miss Entry 1? Can I still take Entry 2?"
Yes! Each entry is independent. If you miss the 3→5 reclaim, wait for the 21 EMA bounce. You'll start with a 30% position instead of 20%, but that's fine.
Rule: Never chase. Wait for the next EMA setup.
"What if multiple entry signals trigger at the same bar?"
Rare, but possible. If you see both Entry 1 and Entry 2 trigger together:
Take Entry 1 first (20%)
If the next bar confirms Entry 2 is still valid, add 30%
When in doubt, scale in gradually
"The hyper frame is green but I'm seeing short signals?"
Don't take them. The hyper frame is your bias filter. If it says "go long," ignore short setups. They're usually lower probability and will get stopped out.
"Can I use this for swing trading overnight?"
Absolutely. Just switch your hyper frame:
If you're on Daily charts, use Weekly hyper frame
If you're on 4H charts, use Daily hyper frame
Adjust position sizes for overnight risk
"What if the signal appears right at market close?"
Don't chase it. Wait for the next bar (next day) to confirm. Signals that appear in the last 5 minutes are often noise.
"How do I set up alerts?"
Right-click on the chart
Select "Add Alert"
Choose "LazyEMA" from the condition dropdown
Select which signal you want alerts for:
Entry 1: 3→5 Reclaim
Entry 2: 21 EMA Add
Entry 3: 34 EMA Breakout
Exit 1: 89 EMA Break
Exit 2: 144 EMA Break
Click "Create"
Pro tip: Set up all 5 alerts so you never miss a signal.
Position Sizing Guide see
swingtradenotes.substack.com
Critical Rule: Know your total risk BEFORE you take Entry 1. Don't wing it.
Customization Tips
For Day Traders (Scalpers)
Use 5min or 15min charts
Hyper frame: 1H or 4H
Expect 2-4 setups per day
Tighter stops (0.5% risk per entry)
For Swing Traders
Use 4H or Daily charts
Hyper frame: Daily or Weekly
Expect 1-2 setups per week
Wider stops (1-2% risk per entry)
For Position Traders
Use Daily or Weekly charts
Hyper frame: Weekly or Monthly
Expect 1-2 setups per month
Widest stops (2-3% risk per entry)
The "Don't Be Stupid" Checklist
Before taking ANY signal from this script, ask:
✅ Is the hyper frame bias pointing in my direction?
✅ Is the signal clean (not at a weird time or during news)?
✅ Do I know my stop loss level?
✅ Do I know my position size?
✅ Can I afford to lose if this trade fails?
If you answered "no" to ANY of these, skip the trade.
Troubleshooting
"I'm not seeing any signals"
Possible causes:
The "Show Lazy Trader System" toggle is off (turn it on)
Your chart timeframe is too high (try 1H or 4H)
Market is in a tight range (EMAs are compressed)
You need to refresh the chart
"Too many signals, getting whipsawed"
Fixes:
Increase your chart timeframe (go from 15m to 1H)
Switch to a less volatile ticker
Only trade when hyper frame bias is STRONG (not neutral)
Add a minimum bar count between signals
"The info table is covering my price action"
Fix:
Edit the script
Find the line: table.new(position.top_right, ...
Change position.top_right to position.bottom_right or position.top_left
"Signals appear then disappear"
This is normal (repainting). Some signals (especially compression breakouts) can disappear if the next bar reverses. This is why you:
Wait for bar close before acting
Use alerts that only fire on confirmed bars
Don't chase signals mid-bar
Final Thoughts
This script is a decision-making tool, not a crystal ball. It shows you high-probability setups based on EMA dynamics and trend structure. You still need to:
Manage your risk
Choose your position size
Stick to the rules
Accept losses when they happen
The system works when YOU work the system.
Print this guide, tape it next to your monitor, and follow it religiously for 20 trades before making ANY changes.
Good luck, and stay lazy (the smart way).
SHUBHAM 50000 ULTRA OPTIONSHUBHAM 50000 ULTRA OPTION
OptionFlow Pro: Smart Money & Anomaly Detection Indicator
Tagline: Don't just follow the flow. Understand it.
Core Concept:
OptionFlow Pro is an advanced, real-time market scanner and visual indicator that transforms raw options chain data into actionable trading intelligence. It goes beyond simple volume and open interest by identifying Unusual Options Activity (UOA), tracking Sweep Orders, and calculating the Volume-Weighted Put/Call Ratio to highlight where institutional "smart money" is placing its bets.
Key Features for Traders:
Unusual Activity & Sweep Detector:
What it does: Scans every tick for orders that significantly deviate from normal trading patterns—large block trades executed at the ask (for calls) or bid (for puts), and "sweep" orders that clean out multiple price levels instantly.
Trader Benefit: Pinpoints potential breakout or breakdown candidates before major moves occur in the underlying stock. Alerts you to aggressive, high-conviction buying or selling that retail traders often miss.
Volume-Weighted Put/Call Ratio (with Trend):
What it does: Calculates the put/call ratio not just by volume, but by the premium spent. A high premium-weighted put/call ratio shows bears are putting serious money behind their bets, making it a stronger signal.
Trader Benefit: Offers a more nuanced view of market sentiment than standard PCR. Helps gauge extreme fear (potential oversold bounce) or complacency (overbought top) in a specific stock or index (SPX/SPY).
Max Pain & Gamma Exposure (GEX) Visualizer:
What it does: Dynamically calculates the "Max Pain" strike (where option sellers face minimal losses) and estimates Gamma Exposure levels. Visual overlays on the chart show key pin levels and large gamma walls.
Trader Benefit: Identifies potential price magnets for weekly/monthly expiry. Understand where hedging activity by market makers may amplify volatility (negative gamma) or suppress it (positive gamma), aiding in entry/exit planning.
Implied Volatility (IV) Rank & Skew Analysis:
What it does: Compares current IV to its historical range (IV Rank) and visualizes the volatility smile/skew across strikes. Highlights expensive vs. cheap option premiums.
Trader Benefit: Empowers you to sell overpriced volatility (high IV Rank) and buy underpriced volatility (low IV Rank). Skew anomalies can signal asymmetric risk/reward opportunities or market fears about a sharp directional move.
Customizable Alerts & Heatmaps:
What it does: Set alerts for specific UOA criteria, PCR spikes, or IV changes. The platform-wide heatmap aggregates flow data across all symbols to show sector-level money movement.
Trader Benefit: Saves hours of manual scanning. Focus only on the setups that match your strategy (e.g., "Alert me for any $1M+ call sweeps in tech stocks").
Who Is It For?
Active Options Traders & Scalpers: Find high-probability directional plays with institutional confirmation.
Hedgers & Portfolio Managers: Identify tail-risk hedging activity and gauge overall market dealer positioning.
Volatility Traders: Precisely time entries for strangles, straddles, or iron condors based on IV regime and gamma.
Swing Traders & Technical Analysts: Confirms or diverges from classic chart patterns (e.g., breakout with strong call flow = higher conviction).
Why It's Different:
Most indicators look backward at price. OptionFlow Pro looks forward at market structure, liquidity, and dealer hedging flows. It doesn't predict the future; it reveals the present positioning that will influence future price action.
Platform Integration: Available as a standalone web platform, a TradingView custom script, and a direct data feed into thinkorswim, Interactive Brokers, and other major brokerages.
RenkoFlow PercentualIt calculates brick size as a percentage of the chart’s initial price and updates bricks only when price moves one full brick size up or down.
Green bricks represent upward movement and red bricks represent downward movement.
This tool is designed to help visualize directional price changes independently of time and can be used as a clean trend-filtering reference on any timeframe.
Long Term Holder Supply 155 DayThe “Long Term Holder Supply 155 Day” indicator is designed to bring on-chain inspired long-term analysis directly into chart-based technical trading.
The concept comes from the idea of Long-Term Holder (LTH) Supply, frequently used in Bitcoin on-chain analytics to identify price zones where long-term holders accumulated coins. These areas tend to act as strong support and resistance because long-term holders historically accumulate during undervaluation phases and distribute during overheated cycles.
What makes this script original
Unlike traditional moving averages or basic Donchian channels, this indicator combines both concepts using the same 155-day window, creating a unified model that visually represents:
The average long-term holder cost basis (via SMA 155).
The range of supply and demand zones historically defined by price extremes (via Donchian 155).
A trend-reactive color system that makes interpretation intuitive and immediate.
This dual-structure is not commonly found in standard TradingView scripts and is inspired by on-chain research methodology adapted for chart traders.
How it works
1. SMA 155 (LTH Mean Price)
Represents the long-term holder cost basis proxy.
Turns green when price is above it (market strength above holder basis).
Turns red when price is below it (market trading at a discount relative to long-term holders).
This allows traders to quickly identify whether Bitcoin is in a LTH profit or LTH loss environment — a critical on-chain concept.
2. Donchian Channel 155 (LTH Supply Range)
Upper Band (Green): Highest high of the last 155 days — interpreted as the upper bound of LTH supply/resistance.
Lower Band (Red): Lowest low of the last 155 days — interpreted as the lower bound of LTH accumulation/support.
This creates a long-term structural range showing where long-term holders were historically more likely to buy (lower band) or distribute (upper band).
How to use it
Bullish conditions:
Price breaks above the SMA 155.
Price begins approaching or breaking the upper Donchian band → signs of macro strength and potential long-term breakout.
Bearish conditions:
Price drops below SMA 155 (LTH basis lost).
Price moves toward the lower Donchian band → zone where long-term holders historically accumulate during deep value phases.
Sideways Accumulation:
Price oscillates inside the Donchian bands while hugging the SMA 155 → potential long-term consolidation before trend reversal.
Who this indicator is for
Long-term Bitcoin analysts
Swing traders
Investors tracking macro cycles
Traders who want lightweight on-chain logic without needing blockchain datasets
Core methodology behind the script
The indicator is built around:
SMA 155 → represents long-term average cost basis
Donchian 155 → long-term supply/demand range
Color-based trend confirmation → chart-based interpretation of on-chain behavior
This combination brings an on-chain inspired long-term model into pure price action, making it usable even by traders without access to blockchain data.
Market Structure Shift (MSS) [Sword & Shield]MARKET STRUCTURE SHIFT (MSS)
A clean and focused indicator for identifying Market Structure Shifts in price action.
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WHAT IS MARKET STRUCTURE SHIFT (MSS)?
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A Market Structure Shift occurs when price breaks a significant swing high or swing low,
indicating a potential change in market direction. This indicator automatically detects
and plots these key levels.
BULLISH MSS: Price breaks above a previous swing high
BEARISH MSS: Price breaks below a previous swing low
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FEATURES
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CLEAN DISPLAY
- Shows only the last 2 MSS by default (1 bullish + 1 bearish)
- Keeps charts clean and focused on recent structure
- Automatically removes old MSS when new ones appear
CUSTOMIZABLE DETECTION
- Adjustable swing detection (left/right bars)
- Choose break confirmation method (Close or Wick)
- Fixed-length lines (no infinite extension by default)
SMART FILTERING
- Only plots one MSS per direction until opposite MSS occurs
- Prevents duplicate signals in the same direction
- Clear visual distinction between bullish (blue) and bearish (red)
CLEAN LABELS
- Text labels positioned above lines
- No background tooltips for cleaner appearance
- Color-matched to their respective MSS lines
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SETTINGS
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SWING DETECTION
- Swing Left Bars (default: 2)
- Swing Right Bars (default: 2)
- Higher values = more significant swings detected
BREAK CONFIRMATION
- Close: MSS confirmed when candle closes beyond level
- Wick: MSS confirmed when wick touches beyond level
DISPLAY OPTIONS
- Show Only Last 2 MSS: ON by default (keeps chart clean)
- Extend lines to the right: OFF by default (fixed-length lines)
- Line bars (when not extended): 50 bars (customizable)
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HOW IT WORKS
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DETECTION LOGIC
1. Identifies swing highs and swing lows using pivot detection
2. Monitors price action for breaks of these levels
3. Confirms break based on selected method (Close or Wick)
4. Plots MSS line at the broken level
FILTERING LOGIC
- Only one MSS per direction is allowed consecutively
- Example: If bullish MSS appears, no new bullish MSS until bearish MSS occurs
- This prevents multiple signals in trending markets
DISPLAY LOGIC
- When "Show Only Last 2 MSS" is enabled:
• Only the most recent bullish MSS is shown
• Only the most recent bearish MSS is shown
• Old MSS are automatically deleted when new ones appear
- When disabled: All historical MSS remain visible
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USAGE EXAMPLES
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FOR TREND IDENTIFICATION
- Bullish MSS = Potential uptrend beginning
- Bearish MSS = Potential downtrend beginning
- Use in conjunction with other indicators for confirmation
FOR ENTRY SIGNALS
- Wait for MSS to confirm trend change
- Enter on pullback to MSS level
- Use MSS as support/resistance
FOR SCALPING (Lower Timeframes)
- Swing Left/Right Bars: 2-3 (more sensitive)
- Break Confirmation: Close (more reliable)
- Show Only Last 2 MSS: ON (cleaner charts)
FOR SWING TRADING (Higher Timeframes)
- Swing Left/Right Bars: 5-10 (more significant swings)
- Break Confirmation: Close (avoid false breaks)
- Show Only Last 2 MSS: ON or OFF based on preference
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VISUAL DESIGN
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LINES
- Dashed style for easy identification
- Blue for bullish MSS
- Red for bearish MSS
- Fixed length (50 bars default) for cleaner appearance
LABELS
- "MSS" text positioned above each line
- No background for clean display
- Color-matched to line color
- Small size to avoid chart clutter
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CREDITS & LICENSE
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© Sword & Shield
This Pine Script code is subject to the terms of the Mozilla Public License 2.0
mozilla.org
Precious Matrix Signal-S-L15-sum⭐ PRECIOUS MATRIX SIGNAL™
Today Range + R1–R6 Multi-Layer Market Structure Engine
Final Output → 🔵 BUY | 🔴 SELL | ⏹ NEUTRAL
A powerful, multi-range decision engine that reads today’s live structure and compares it with six major past ranges, Δ/E shifts, and daily strength summaries to generate a precise directional signal.
📘 What This Indicator Does
This indicator builds a complete price-behavior matrix combining:
🔹 Today’s High–Low structure
🔹 Six custom historical ranges (R1–R6)
🔹 Live Δ/E trend shifts
🔹 A/R (Above–Below Range) positioning
🔹 Remaining Potential %
🔹 Last-5, Last-10, Last-15 day trend summary
🔹 Auto Spot–Future selection
🔹 Lot size & Margin info
( Not for dark mode &only on NSE Futures & Spot )
All layers combine to produce a single actionable signal.
🔶 How It Works (Simple Flow)
1️⃣ Symbol Auto-Detection
If chart is futures, uses futures data
If futures range missing → switches to continuous 1!
If chart is spot, uses spot cleanly
Auto-reads lot size and margin
2️⃣ Today’s Live Range Engine
Live High / Low
Time of High & Low
Δ (Range size)
A/R (Where current price sits inside the range)
Remaining Potential % (powerful continuation measure)
3️⃣ R1–R6 Custom Range Engine
Each user-set range displays:
High & Low
Δ
A/R positioning
Remaining Potential %
Overshoot/Breakdown markers
Δ/E (Direction shift)
Color-coded range strength
4️⃣ Δ/E Shift Logic (Live Mode)
For each R1–R6:
Prev = previous close before the range
E = end-close of the range
Δ/E = Direction:
▲ Positive → Bullish
▼ Negative → Bearish
■ Neutral → Sideways
If the range ends today → uses intraday close (E*).
5️⃣ Trend Validation (Last-5 / 10 / 15 Days)
Automatic summary tables:
Daily Date
Close
H/L
Δ
A/R
Net Trend Color
Strongest zone marked
This prevents false signals and confirms bias.
6️⃣ Final Signal Engine
Uses a weighted scoring across:
Today’s bias
R1–R6 bias
Δ/E direction
Remaining potential
Last-5/10/15 confirmation
🔵 BUY
→ Majority Ranges UP
→ Today’s structure UP
→ Δ/E = ▲
→ Last-5 positive
🔴 SELL
→ Majority Ranges DOWN
→ Today’s structure DOWN
→ Δ/E = ▼
→ Last-5 negative
⏹ NEUTRAL
→ Mixed or no clear dominance
→ Low potential/compressed price
📊 Dashboard Panels
Panel 1 – Today + R1–R6 Master Matrix
Shows:
H / L / Δ
A/R
Remaining Potential %
Δ/E (live option)
Range badges & colors
Panel 2 – Last-5 / 10 / 15 Summary
Your secondary confirmation panel.
Panel 3 – Lot Size + Margin
Auto margin estimate at 24%.
⚙️ Input Controls
Show/Hide HLX Panel
Custom Range Start/End
Δ/E Live Override
Force Intraday Mode
Last-5/10/15 Selector ( last work properly display on mobile )
Nudge (Panel Offset)
Potential % thresholds
Designed to adjust smoothly for all timeframes.
🎯 Recommended Usage
Use on 3m / 5m / 15m / 30m / 1H / 2H / 4H
Works great on Index Futures, Stock Futures, and Spot
Keep Option-2 Δ/E enabled for live trading
Last-5 and R2–R6 give strongest confirmation for trend days
📈 Who Is This For?
Traders who want:
Multi-range professional context
Reliable bias confirmation
High-probability directional entries
Auto-range intelligence without manual marking
Futures–spot multi-engine precision
🟢 SUPER-SIMPLE FLOWCHART
START
|
Detect Spot/Future + Lot
|
Compute TODAY H/L
|
Compute R1–R6 Ranges
|
Apply Δ/E Live Logic
|
Build Range Strength Score
|
Build Last5/10/15 Trend
|
Combine All Scores (matrix)
|
BUY ? SELL ? NEUTRAL ?
|
Display Full Dashboard
🛑 Disclaimer
This is an educational tool.
No buy/sell recommendations.
Always use proper risk management.
Elliott Wave Principle Pro - Frost & Prechter [abusuhil]الوصف العربي اسفل الوصف الإنجليزي .
✅ Professional Description (English)
Elliott Wave Principle Pro – Frost & Prechter Edition
A complete, professional-grade Elliott Wave detection and trading system designed for traders who want to identify market structure with precision and execute trades based on confirmed wave completion signals — without repainting.
This indicator combines the classical Elliott Wave rules from Frost & Prechter’s “Elliott Wave Principle” with modern algorithmic detection, Fibonacci validation, ZigZag pivot systems, and fully automated entry/exit levels.
⭐ Core Features
1. Automatic Elliott Wave Detection
Detects Impulse Waves (5-3-5-3-5)
Detects Corrective Waves (ABC) including:
• Zigzag
• Flat
• Expanded Flat
Supports multiple wave degrees (Cycle → Minuette)
2. Strict Elliott Rule Engine
All major EW rules are applied:
Wave 2 never retraces beyond Wave 1
Wave 4 must not overlap Wave 1
Wave 3 is never the shortest
Wave relationships validated using Fibonacci ratios
You can choose Strict / Standard / Flexible rule modes.
⭐ 3. Non-Repainting Confirmation System
Waves are confirmed only after pivot completion
Signals never change once displayed
Historical signals remain stable
Fully resistant to repainting
⭐ 4. Automated Trading Signals
Every completed structure triggers:
BUY Signals
End of Wave C
End of bearish Impulse (Wave 5)
SELL Signals
End of Wave 5 in bullish impulse
End of bullish ABC correction
Each signal includes:
Entry Line
Stop Loss (3 methods: Wave / ATR / Fixed)
TP1 – TP2 – TP3 (Fibonacci-based or Wave Projected)
Optional PRZ (Potential Reversal Zone)
You may show only the latest signal for clarity.
⭐ 5. Advanced Visual Tools
Wave numbers (1–5 / A–B–C)
Wave lines
Channels
Projection levels
Degree colors
Customizable labels and signal shapes (Box / Arrow / No Text)
A clean Simple Mode is available to hide all waves and show signals only.
⭐ 6. Informational Table (Optional)
Displays:
Last detected structure
Direction (Bullish / Bearish)
Active signal status (Buy / Sell / Wait)
⭐ How Traders Benefit
This tool helps traders:
Understand the full Elliott Wave context instantly
Know exactly when a wave cycle has completed
Enter trades with predefined, optimized levels
Avoid emotional decisions and subjective wave counting
Rely on a non-repainting analytical engine
Identify high-probability reversal zones
Improve trade timing and risk management
Perfect for swing trading, intraday trading, and wave practitioners.
🇸🇦 الوصف الاحترافي (العربية)
Elliott Wave Principle Pro – نسخة فروسـت وبريشتـر
مؤشر احترافي متكامل لتحليل موجات إليوت واكتشاف البُنى السعريّة بشكل آلي ودقيق، مع إعطاء إشارات تداول مؤكدة عند اكتمال الموجات — بدون إعادة رسم (Non-Repainting).
يجمع هذا المؤشر بين قواعد مدرسة إليوت الكلاسيكية من كتاب “Elliott Wave Principle” وبين خوارزميات حديثة تعتمد على الـ ZigZag، والفيبوناتشي، والتحقق الرياضي من صحة الموجة.
⭐ أهم المزايا
1. اكتشاف آلي كامل لموجات إليوت
اكتشاف الموجات الدافعة Impulse 5-3-5-3-5
اكتشاف الموجات التصحيحية ABC بما يشمل:
• Zigzag
• Flat
• Expanded Flat
دعم جميع درجات الموجة من Cycle حتى Minuette
⭐ 2. محرك قواعد إليوت الاحترافي
يطبق المؤشر جميع القواعد الأساسية لموجات إليوت، مثل:
الموجة 2 لا تتجاوز بداية الموجة 1
الموجة 4 يجب ألا تتداخل مع الموجة 1
الموجة 3 ليست الأقصر
تأكيد العلاقات باستخدام نسب فيبوناتشي
مع إمكانية اختيار نمط القواعد: صارم / قياسي / مرن.
⭐ 3. نظام تأكيد بدون إعادة رسم
لا يتم تأكيد الموجة إلا بعد اكتمالها فعليًا
لا يتم حذف أي إشارة بعد ظهورها
جميع النتائج ثابتة وغير قابلة للتغيير
مقاوم لإعادة الرسم 100%
⭐ 4. إشارات تداول تلقائية
يصدر المؤشر إشارات شراء وبيع عند اكتمال التركيبات التالية:
إشارات BUY
نهاية موجة C
نهاية موجة 5 الهابطة (انعكاس صاعد)
إشارات SELL
نهاية موجة 5 الصاعدة
نهاية تصحيح ABC الصاعد
وتتضمن الإشارة:
مستوى الدخول
وقف الخسارة (Wave / ATR / نسبة ثابتة)
الأهداف TP1 – TP2 – TP3
منطقة انعكاس محتملة PRZ (اختيارية)
ويمكن عرض آخر إشارة فقط لسهولة القراءة.
⭐ 5. أدوات بصرية متقدمة
ترقيم الموجات 1–5 و A–B–C
خطوط الموجات
قنوات Elliott
مستويات الإسقاط
ألوان الدرجات
تخصيص شكل الإشارة (مربع / سهم / بدون نص)
كما يمكن تفعيل الوضع البسيط لإظهار الإشارات فقط.
⭐ 6. جدول معلومات الاختياري
يعرض:
نوع آخر موجة مكتشفة
اتجاهها (صاعد / هابط)
حالة الإشارة الحالية (شراء / بيع / انتظار)
⭐ فوائد استخدام المؤشر للمتداول
هذا المؤشر يساعدك على:
فهم بنية موجات إليوت دون قراءة الشارت يدويًا
اكتشاف نقاط الانعكاس القوية قبل حدوثها
الدخول في صفقات محسوبة مسبقًا (Entry + SL + TP)
تقليل التشتت والتقدير الشخصي في العدّ
تحسين إدارة المخاطر
تعزيز دقة التوقيت في بداية الاتجاهات الجديدة
دراسة السوق بطريقة احترافية تعتمد على قاعدة علمية واضحة
مثالي للمضارب اليومي، المتداول المتأرجح، ولممارسي مدرسة إليوت.
MTF Alignment & Key Levelsso this one is specifically for the 1hr and 4hr time frame. but what it does is alert you once the monthly weekly and daily timeframes align with a trend in a certain direction wether its bearish or bullish but then it will mark out key levels on the 1hr and 4hr time frame to indicate when price breaks through that level to enter a trade in the direction of the higher timeframes alignment.
Fed Net Liquidity [Premium] [by Golman Armi]This indicator visualizes the USD Net Liquidity injected into the financial system by the Federal Reserve.
It is a fundamental macro-economic tool essential for understanding the underlying "fuel" driving risk assets such as the S&P 500 (SPX), Nasdaq (NDX), and Bitcoin (BTC).
Unlike many other liquidity scripts that incorrectly use Commercial Bank Assets (USCBBS), this script uses the Federal Reserve Total Assets (WALCL) to provide a mathematically accurate representation of Central Bank liquidity.
How It Works (The Formula)
Net Liquidity represents the actual cash available to the banking system for investment after government liabilities are subtracted. The formula used is:
NetLiquidity=WALCL−TGA−RRP
Where:
WALCL (Fed Balance Sheet): The total assets held by the Federal Reserve (The source of money printing).
TGA (Treasury General Account - WTREGEN): The checking account of the US Government. When the TGA goes up, money is removed from the economy; when it goes down, money is spent into the economy.
RRP (Reverse Repo - RRPONTTLD): Cash parked by banks and money market funds at the Fed overnight. A rise in RRP removes liquidity from the markets.
Features
Accurate Data Sourcing: Pulls daily data directly from FRED (Federal Reserve Economic Data).
Unit Correction: Automatically adjusts conflicting units (Millions vs Billions) from TradingView data feeds to output a correct value in Trillions of Dollars.
Trend Cloud: Features a smoothing EMA (Exponential Moving Average) with a color-coded cloud to easily identify the macro trend (Green for expansion, Red for contraction).
How to Use
Trend Correlation:
Rising Line (Green): Liquidity is expanding. Historically, this supports bullish trends in stocks and crypto.
Falling Line (Red): Liquidity is being drained (QT or TGA refill). This often leads to volatility or bearish trends in risk assets.
Divergences (The most powerful signal):
If the S&P 500 or Bitcoin makes a New High, but Net Liquidity makes a Lower High, it indicates a "hollow rally" lacking fundamental support, often preceding a correction.
Disclaimer
This tool is for educational purposes and macro-economic analysis only. It is not financial advice.
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.
Absorption RatioThe Hidden Connections Between Markets
Financial markets are not isolated islands. When panic spreads, seemingly unrelated assets suddenly begin moving in lockstep. Stocks, bonds, commodities, and currencies that normally provide diversification benefits start falling together. This phenomenon, where correlations spike during crises, has devastated portfolios throughout history. The Absorption Ratio provides a quantitative measure of this hidden fragility.
The concept emerged from research at State Street Associates, where Mark Kritzman, Yuanzhen Li, Sebastien Page, and Roberto Rigobon developed a novel application of principal component analysis to measure systemic risk. Their 2011 paper in the Journal of Portfolio Management demonstrated that when markets become tightly coupled, the variance explained by the first few principal components increases dramatically. This concentration of variance signals elevated systemic risk.
What the Absorption Ratio Measures
Principal component analysis, or PCA, is a statistical technique that identifies the underlying factors driving a set of variables. When applied to asset returns, the first principal component typically captures broad market movements. The second might capture sector rotations or risk-on/risk-off dynamics. Additional components capture increasingly idiosyncratic patterns.
The Absorption Ratio measures the fraction of total variance absorbed or explained by a fixed number of principal components. In the original research, Kritzman and colleagues used the first fifth of the eigenvectors. When this fraction is high, it means a small number of factors are driving most of the market movements. Assets are moving together, and diversification provides less protection than usual.
Consider an analogy: imagine a room full of people having independent conversations. Each person speaks at different times about different topics. The total "variance" of sound in the room comes from many independent sources. Now imagine a fire alarm goes off. Suddenly everyone is talking about the same thing, moving in the same direction. The variance is now dominated by a single factor. The Absorption Ratio captures this transition from diverse, independent behavior to unified, correlated movement.
The Implementation Approach
TradingView does not support matrix algebra required for true principal component analysis. This implementation uses a closely related proxy: the average absolute correlation across a universe of major asset classes. This approach captures the same underlying phenomenon because when assets are highly correlated, the first principal component explains more variance by mathematical necessity.
The asset universe includes eight ETFs representing major investable categories: SPY and QQQ for large cap US equities, IWM for small caps, EFA for developed international markets, EEM for emerging markets, TLT for long-term treasuries, GLD for gold, and USO for oil. This selection provides exposure to equities across geographies and market caps, plus traditional diversifying assets.
From eight assets, there are twenty-eight unique pairwise correlations. The indicator calculates each using a rolling window, takes the absolute value to measure coupling strength regardless of direction, and averages across all pairs. This average correlation is then transformed to match the typical range of published Absorption Ratio values.
The transformation maps zero average correlation to an AR of 0.50 and perfect correlation to an AR of 1.00. This scaling aligns with empirical observations that the AR typically fluctuates between 0.60 and 0.95 in practice.
Interpreting the Regimes
The indicator classifies systemic risk into four regimes based on AR levels.
The Extreme regime occurs when the AR exceeds 0.90. At this level, nearly all asset classes are moving together. Diversification has largely failed. Historically, this regime has coincided with major market dislocations: the 2008 financial crisis, the 2020 COVID crash, and significant correction periods. Portfolios constructed under normal correlation assumptions will experience larger drawdowns than expected.
The High regime, between 0.80 and 0.90, indicates elevated systemic risk. Correlations across asset classes are above normal. This often occurs during the build-up to stress events or during volatile periods where fear is spreading but has not reached panic levels. Risk management should be more conservative.
The Normal regime covers AR values between 0.60 and 0.80. This represents typical market conditions where some correlation exists between assets but diversification still provides meaningful benefits. Standard portfolio construction assumptions are reasonable.
The Low regime, below 0.60, indicates that assets are behaving relatively independently. Diversification is working well. Idiosyncratic factors dominate returns rather than systematic risk. This environment is favorable for active management and security selection strategies.
The Relationship to Portfolio Construction
The implications for portfolio management are significant. Modern portfolio theory assumes correlations are stable and uses historical estimates to construct efficient portfolios. The Absorption Ratio reveals that this assumption is violated precisely when it matters most.
When AR is elevated, the effective number of independent bets in a diversified portfolio shrinks. A portfolio holding stocks, bonds, commodities, and real estate might behave as if it holds only one or two positions during high AR periods. Position sizing based on normal correlation estimates will underestimate portfolio risk.
Conversely, when AR is low, true diversification opportunities expand. The same nominal portfolio provides more independent return streams. Risk can be deployed more aggressively while maintaining the same effective exposure.
Component Analysis
The indicator separately tracks equity correlations and cross-asset correlations. These components tell different stories about market structure.
Equity correlations measure coupling within the stock market. High equity correlation indicates broad risk-on or risk-off behavior where all stocks move together. This is common during both rallies and selloffs driven by macroeconomic factors. Stock pickers face headwinds when equity correlations are elevated because individual company fundamentals matter less than market beta.
Cross-asset correlations measure coupling between different asset classes. When stocks, bonds, and commodities start moving together, traditional hedges fail. The classic 60/40 stock/bond portfolio, for example, assumes negative or low correlation between equities and treasuries. When cross-asset correlation spikes, this assumption breaks down.
During the 2022 market environment, for instance, both stocks and bonds fell significantly as inflation and rate hikes affected all assets simultaneously. High cross-asset correlation warned that the usual defensive allocations would not provide their expected protection.
Mean Reversion Characteristics
Like most risk metrics, the Absorption Ratio tends to mean-revert over time. Extremely high AR readings eventually normalize as panic subsides and assets return to more independent behavior. Extremely low readings tend to rise as some level of systematic risk always reasserts itself.
The indicator tracks AR in statistical terms by calculating its Z-score relative to the trailing distribution. When AR reaches extreme Z-scores, the probability of normalization increases. This creates potential opportunities for strategies that bet on mean reversion in systemic risk.
A buy signal triggers when AR recovers from extremely elevated levels, suggesting the worst of the correlation spike may be over. A sell signal triggers when AR rises from unusually low levels, warning that complacency about diversification benefits may be excessive.
Momentum and Trend
The rate of change in AR carries information beyond the absolute level. Rapidly rising AR suggests correlations are increasing and systemic risk is building. Even if AR has not yet reached the high regime, acceleration in coupling should prompt increased vigilance.
Falling AR momentum indicates normalizing conditions. Correlations are decreasing and assets are returning to more independent behavior. This often occurs in the recovery phase following stress events.
Practical Application
For asset allocators, the AR provides guidance on how much diversification benefit to expect from a given allocation. During high AR periods, reducing overall portfolio risk makes sense because the usual diversifiers provide less protection. During low AR periods, standard or even aggressive allocations are more appropriate.
For risk managers, the AR serves as an early warning indicator. Rising AR often precedes large market moves and volatility spikes. Tightening risk limits before correlations reach extreme levels can protect capital.
For systematic traders, the AR provides a regime filter. Mean reversion strategies may work better during high AR periods when panics create overshooting. Momentum strategies may work better during low AR periods when trends can develop independently across assets.
Limitations and Considerations
The proxy methodology introduces some approximation error relative to true PCA-based AR calculations. The asset universe, while representative, does not include all possible diversifiers. Correlation estimates are inherently backward-looking and can change rapidly.
The transformation from average correlation to AR scale is calibrated to match typical published ranges but is not mathematically equivalent to the eigenvalue ratio. Users should interpret levels directionally rather than as precise measurements.
Correlation regimes can persist longer than expected. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. High AR can remain elevated throughout extended crisis periods.
References
Kritzman, M., Li, Y., Page, S., and Rigobon, R. (2011). Principal Components as a Measure of Systemic Risk. Journal of Portfolio Management, 37(4), 112-126.
Kritzman, M., and Li, Y. (2010). Skulls, Financial Turbulence, and Risk Management. Financial Analysts Journal, 66(5), 30-41.
Billio, M., Getmansky, M., Lo, A., and Pelizzon, L. (2012). Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors. Journal of Financial Economics, 104(3), 535-559.
