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EchoFlowEchoFlow — Where Intelligence Becomes Rhythm
Powered by next-gen AI, EchoFlow transforms data, code, and creativity into seamless motion.
It doesn’t just automate — it anticipates.
From thought to execution, EchoFlow is the pulse of intelligent systems, syncing every action with precision, speed, and intuition.
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph
Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter.
Scope and intent
• Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto
• Timeframes: 5 min to 1 day
• Default demo: SPY on 60 min
• Purpose: fade stretched moves only when multi-anchor context and breadth agree
• Limits: strategy uses standard candles for signals and orders only
Originality and usefulness
• Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM
• Failure mode addressed: chasing extended moves and fading during index-wide thrusts
• Testability: each component is an input and visible in orders list via L and S tags
• Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols
• Open source: method and implementation are disclosed for community review
Method overview in plain language
Base measures
• Range basis: ATR(length = atr_len) as the normalization unit
• Return basis: not used directly; we use rank statistics for stability
Components
• Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len
• Robust Z of Close: median and MAD based Z to avoid outliers
• Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts
• Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided
• Gap Shock: skip signals after large session gaps
Fusion rule
• All required gates must be true: Energy ≥ energy_trig_prc, |Robust Z| ≥ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear
Signal rule
• Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z ≤ −breadth_z_ok
• Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z ≥ +breadth_z_ok
What you will see on the chart
• Standard strategy arrows for entries and exits
• Optional short-side brackets: ATR stop and ATR take profit if enabled
Inputs with guidance
Setup
• Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts.
• ATR length: normalization unit. Typical 10 to 20. Higher reduces noise.
• VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0.
• Robust Z window: 40 to 100. Larger for stability.
• Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only.
• Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches.
• Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs.
Regime and Breadth
• Use breadth gate: on when trading indices or broad ETFs.
• Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts.
• Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade.
Risk — Short only
• Enable short SL TP: on to bracket shorts.
• Short ATR stop mult: 1.0 to 3.0.
• Short ATR take profit mult: 1.0 to 6.0.
Properties visible in this publication
• Initial capital: 25000USD
• Default order size: Percent of total equity 3%
• Pyramiding: 0
• Commission: 0.03 percent
• Slippage: 5 ticks
• Process orders on close: OFF
• Bar magnifier: OFF
• Recalculate after order is filled: OFF
• Calc on every tick: OFF
• request.security lookahead off where used
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Fills and slippage vary by venue
• Shapes can move during bar formation and settle on close
• Standard candles only for strategies
Honest limitations and failure modes
• Economic releases or very thin liquidity can overwhelm mean-reversion logic
• Heavy gap regimes may require larger gap filter or TR-based tuning
• Very quiet regimes reduce signal contrast; extend windows or raise thresholds
Open source reuse and credits
• None
Strategy notice
Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution.
Entries and exits
• Entry logic: as in Signal rule above
• Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup
• Risk model: ATR-based brackets on shorts when enabled
• Tie handling: stop first when both could be touched inside one bar
Dataset and sample size
• Test across your visible history. For robust inference prefer 100 plus trades.
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph
Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter.
Scope and intent
• Markets. Gold and silver futures or spot, other liquid commodities, major indices
• Timeframes. Five minutes to one day. Defaults to 30min for swing pace
• Default demo used in this publication. TVC:GOLD on 30m
• Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias
• Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings
• Testability. Each component has a named input. Entry names L and S are visible in the list of trades
• Portable yardstick. Weekly ATR for stops and R multiples for targets
• Open source. Method and implementation are disclosed for community review
Method overview in plain language
You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope.
Base measures
• Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE
• Return basis. Not required
Components
• Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window
• Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat
• DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens
• Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band
Fusion rule
• All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled
Signal rule
• Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish
• Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish
• Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band
Inputs with guidance
Setup
• Symbol. Default TVC:GOLD (Correlation Asset for internal logic)
• Signal timeframe. Blank follows the chart
• Confirm timeframe. Default 1 day used by the bias block
Directional Convexity Index
• DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier
• DCX rise bars. Typical 3 to 6. Higher demands continuation
• DCX entry threshold. Typical 15 to 35. Higher avoids soft moves
• Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape
• Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence
Adaptive Volatility Envelope
• AVE window. Typical 24 to 48. Higher smooths more
• Midline type. ALMA or HMA or EMA per preference
• TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions
• Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR
• Base envelope mult. Typical 1.4 to 2.2. Width of bands
• Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands
Intermarket Bias
• Use DXY bias. Default ON
• DXY timeframe. Default 1 day
• DXY trend window. Typical 10 to 50
Risk
• Risk percent per trade. Reporting field. Keep live risk near one to two percent
• Weekly ATR. Default 14. Basis for stops
• Stop ATR weekly mult. Typical 1.5 to 3.0
• Take profit R multiple. Typical 1.5 to 3.0
• Trail with AVE band. Optional. OFF by default
Properties visible in this publication
• Initial capital. 20000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3% of the total capital available
• Pyramiding 0
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the expansion logic
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
Open source reuse and credits
• None
Mode
Public open source. Source is visible and free to reuse within TradingView House Rules
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
Trend Telescope v4 Basic Configuration
pine
// Enable only the components you need
Order Flow: ON
Delta Volume: ON
Volume Profile: ON
Cumulative Delta: ON
Volatility Indicator: ON
Momentum Direction: ON
Volatility Compression: ON
📊 Component Breakdown
1. Order Flow Analysis
Purpose: Identifies buying vs selling pressure
Visual: Histogram (Green=Buying, Red=Selling)
Calculation: Volume weighted by price position
Usage: Spot institutional order blocks
2. Delta Volume Values
Purpose: Shows volume imbalance
Bull Volume (Green): Volume on up bars
Bear Volume (Red): Volume on down bars
Usage: Identify volume divergences
3. Anchored Volume Profile
Purpose: Finds high-volume price levels
POC (Point of Control): Price with highest volume
Profile Length: Adjustable (default: 50 bars)
Usage: Identify support/resistance zones
4. Cumulative Volume Delta
Purpose: Tracks net buying/selling pressure over time
Trend Analysis: Rising=Buying pressure, Falling=Selling pressure
Divergence Detection: Price vs Delta divergences
Usage: Confirm trend strength
5. Volatility Indicator
Purpose: Measures market volatility with cycle detection
Volatility Ratio: ATR as percentage of price
Volatility Cycle: SMA of volatility (identifies periods)
Histogram: Difference between current and average volatility
Usage: Adjust position sizing, identify breakout setups
6. Real-time Momentum Direction
Purpose: Multi-factor momentum assessment
Components: Price momentum (50%), RSI momentum (30%), Volume momentum (20%)
Visual: Line plot with color coding
Labels: Clear BULLISH/BEARISH/NEUTRAL signals
Usage: Trend confirmation, reversal detection
7. Volatility Compression Analysis
Purpose: Identifies low-volatility consolidation periods
Compression Detection: True Range below threshold
Strength Meter: How compressed the market is
Histogram: Red when compressed, Gray when normal
Usage: Predict explosive moves, prepare for breakouts
⚙️ Advanced Configuration
Optimal Settings for Different Timeframes
pine
// Scalping (1-15 min)
Profile Length: 20
ATR Period: 10
Momentum Length: 8
Compression Threshold: 0.3
// Day Trading (1H-4H)
Profile Length: 50
ATR Period: 14
Momentum Length: 14
Compression Threshold: 0.5
// Swing Trading (Daily)
Profile Length: 100
ATR Period: 20
Momentum Length: 21
Compression Threshold: 0.7
Alert Setup Guide
Enable "Enable Alerts" in settings
Choose alert types:
Momentum Alerts: When momentum changes direction
Compression Alerts: When volatility compression begins
Set alert frequency to "Once Per Bar"
Configure notification preferences
🎯 Trading Strategies
Strategy 1: Compression Breakout
pine
Entry Conditions:
1. Volatility Compression shows RED histogram
2. Cumulative Delta trending upward
3. Momentum turns BULLISH
4. Price breaks above POC level
Exit: When Momentum turns BEARISH or Compression ends
Strategy 2: Momentum Reversal
pine
Entry Conditions:
1. Strong Order Flow in opposite direction
2. Momentum divergence (price makes new high/low but momentum doesn't)
3. Volume confirms the reversal
Exit: When Order Flow returns to trend direction
Strategy 3: Institutional Accumulation
pine
Identification:
1. High Cumulative Delta but flat/sideways price
2. Consistent Order Flow in one direction
3. Volume Profile shows accumulation at specific levels
Trade: Enter in direction of Order Flow when price breaks level
📈 Interpretation Guide
Bullish Signals
✅ Order Flow consistently green
✅ Cumulative Delta making higher highs
✅ Momentum above zero and rising
✅ Bull Volume > Bear Volume
✅ Price above POC level
Bearish Signals
✅ Order Flow consistently red
✅ Cumulative Delta making lower lows
✅ Momentum below zero and falling
✅ Bear Volume > Bull Volume
✅ Price below POC level
Caution Signals
⚠️ Momentum divergence (price vs indicator)
⚠️ Volatility compression (potential big move coming)
⚠️ Mixed signals across components
🔧 Troubleshooting
Common Issues & Solutions
Problem: Indicators not showing
Solution: Check "Show on Chart" is enabled
Problem: Alerts not triggering
Solution: Verify alert is enabled in both script and TradingView alert panel
Problem: Performance issues
Solution: Reduce number of enabled components or increase timeframe
Problem: Volume Profile not updating
Solution: Adjust Profile Length setting, ensure sufficient historical data
Performance Optimization
Disable unused components
Increase chart timeframe
Reduce historical bar count
Use on lower timeframes with fewer indicators enabled
💡 Pro Tips
Risk Management
Use Volatility Indicator for position sizing
Monitor Cumulative Delta for trend confirmation
Use POC levels for stop-loss placement
Multi-Timeframe Analysis
Use higher timeframe for trend direction
Use current timeframe for entry timing
Correlate signals across timeframes
Market Condition Adaptation
Trending Markets: Focus on Momentum + Order Flow
Ranging Markets: Focus on Volume Profile + Compression
High Volatility: Use smaller position sizes
Low Volatility: Prepare for compression breakouts
📚 Educational Resources
Key Concepts to Master
Volume-price relationships
Market microstructure
Institutional order flow
Volatility regimes
Momentum vs mean reversion
Recommended Learning Path
Start with Order Flow + Momentum only
Add Volume Profile once comfortable
Incorporate Volatility analysis
Master multi-component correlation
🆘 Support
Getting Help
Check component toggles are enabled
Verify sufficient historical data is loaded
Test on major pairs/indices first
Adjust settings for your trading style
Continuous Improvement
Backtest strategies thoroughly
Keep a trading journal
Adjust parameters based on market conditions
Combine with price action analysis
Remember: No indicator is perfect. Use this tool as part of a comprehensive trading plan with proper risk management. Always test strategies in demo accounts before live trading.
Happy Trading! 📈
Dual ATR Trailing Stop with Buy/Sell SignalsThis indicator applies two ATR-based trailing stops (Fast and Slow) together with a four-state market classifier to visualize trend strength and place crossover Buy/Sell markers. It is a trend-following tool and does not predict future prices. Use it alongside independent analysis and risk management.
How it works
The Fast trail uses ATR with period 5 and multiplier 0.5 by default. The Slow trail uses ATR with period 10 and multiplier 3.0 by default. When price remains above the prior trail, the new trail equals the maximum of the previous trail and close minus the stop-loss distance derived from ATR. When price remains below the prior trail, the new trail equals the minimum of the previous trail and close plus that distance. On a side switch the trail is re-anchored from the current bar. The Fast trail reacts more quickly, while the Slow trail aims to confirm direction and filter noise.
Signals
Buy is when the Fast trail crosses above the Slow trail. Sell is when the Fast trail crosses below the Slow trail. These crossovers are continuation cues rather than standalone trade advice.
Four-state coloring
Strong Bull occurs when Fast is above Slow, the close is above Slow, and the low is above Slow. Bull with Pullback occurs when Fast is above Slow and the close is above Slow, but the low dips below Slow. Strong Bear occurs when Slow is above Fast, the close is below Slow, and the high is below Slow. Bear with Bounce occurs when Slow is above Fast and the close is below Slow, but the high pierces above Slow.
Directional bias
Bias is inferred by comparing which of Strong Bull or Strong Bear occurred more recently using a barsSince comparison. The most recent state defines the current bias and can help filter frequent flips in ranges.
Inputs
You can adjust Fast ATR period from 1 to 50 and its multiplier from 0.1 to 5.0. You can adjust Slow ATR period from 1 to 50 and its multiplier from 0.1 to 10.0. Optional toggles control candle coloring, trail visibility, fill between trails, alerts, and the information panel.
On-chart outputs
The indicator plots the Fast trail and the Slow trail, with optional fill between them. It can show Buy and Sell markers at crossovers. The optional information panel can display last signal side, entry price, current price, P&L since last signal, current market state, Fast and Slow ATR values, and inferred bias.
Alerts
Available alerts are Fast crossing above Slow, Fast crossing below Slow, entering Strong Bull, and entering Strong Bear.
Usage guidelines
For trend following, many users wait for a Buy crossover together with Strong Bull coloring and then manage risk against the Slow trail. For scalping, consider lower timeframes and a smaller Fast ATR such as period 3 and multiplier 0.3, while avoiding over-optimization. When publishing screenshots, use a clean chart with the symbol, timeframe, and the indicator’s name visible.
Limitations and realism
The tool works best in directional markets; ranging conditions may cause frequent side switches. It is designed for standard OHLC charts only and is not intended for Heikin Ashi, Renko, Kagi, Point & Figure, or Range charts. No claims are made about accuracy, profits, or future performance. Always use position sizing, stop-losses, and additional confirmation.
Compatibility and version
Pine Script v6. Default inputs in the publication match the values described above. Version 1.0 initial public release.
Notes
For questions and feedback, please use the comments section on the script page.
Smooth Theil-SenI wanted to build a Theil-Sen estimator that could run on more than one bar and produce smoother output than the standard implementation. Theil-Sen regression is a non-parametric method that calculates the median slope between all pairs of points in your dataset, which makes it extremely robust to outliers. The problem is that median operations produce discrete jumps, especially when you're working with limited sample sizes. Every time the median shifts from one value to another, you get a step change in your regression line, which creates visual choppiness that can be distracting even though the underlying calculations are sound.
The solution I ended up going with was convolving a Gaussian kernel around the center of the sorted lists to get a more continuous median estimate. Instead of just picking the middle value or averaging the two middle values when you have an even sample size, the Gaussian kernel weights the values near the center more heavily and smoothly tapers off as you move away from the median position. This creates a weighted average that behaves like a median in terms of robustness but produces much smoother transitions as new data points arrive and the sorted list shifts.
There are variance tradeoffs with this approach since you're no longer using the pure median, but they're minimal in practice. The kernel weighting stays concentrated enough around the center that you retain most of the outlier resistance that makes Theil-Sen useful in the first place. What you gain is a regression line that updates smoothly instead of jumping discretely, which makes it easier to spot genuine trend changes versus just the statistical noise of median recalculation. The smoothness is particularly noticeable when you're running the estimator over longer lookback periods where the sorted list is large enough that small kernel adjustments have less impact on the overall center of mass.
The Gaussian kernel itself is a bell curve centered on the median position, with a standard deviation you can tune to control how much smoothing you want. Tighter kernels stay closer to the pure median behavior and give you more discrete steps. Wider kernels spread the weighting further from the center and produce smoother output at the cost of slightly reduced outlier resistance. The default settings strike a balance that keeps the estimator robust while removing most of the visual jitter.
Running Theil-Sen on multiple bars means calculating slopes between all pairs of points across your lookback window, sorting those slopes, and then applying the Gaussian kernel to find the weighted center of that sorted distribution. This is computationally more expensive than simple moving averages or even standard linear regression, but Pine Script handles it well enough for reasonable lookback lengths. The benefit is that you get a trend estimate that doesn't get thrown off by individual spikes or anomalies in your price data, which is valuable when working with noisy instruments or during volatile periods where traditional regression lines can swing wildly.
The implementation maintains sorted arrays for both the slope calculations and the final kernel weighting, which keeps everything organized and makes the Gaussian convolution straightforward. The kernel weights are precalculated based on the distance from the center position, then applied as multipliers to the sorted slope values before summing to get the final smoothed median slope. That slope gets combined with an intercept calculation to produce the regression line values you see plotted on the chart.
What this really demonstrates is that you can take classical statistical methods like Theil-Sen and adapt them with signal processing techniques like kernel convolution to get behavior that's more suited to real-time visualization. The pure mathematical definition of a median is discrete by nature, but financial charts benefit from smooth, continuous lines that make it easier to track changes over time. By introducing the Gaussian kernel weighting, you preserve the core robustness of the median-based approach while gaining the visual smoothness of methods that use weighted averages. Whether that smoothness is worth the minor variance tradeoff depends on your use case, but for most charting applications, the improved readability makes it a good compromise.
Constant Auto Trendlines (Extended Right)📈 Constant Auto Trendlines (Extended Right)
This indicator automatically detects market structure by connecting swing highs and lows with permanent, forward-projecting trendlines.
Unlike standard trendline tools that stop at the last pivot, this version extends each trendline infinitely into the future — helping traders visualize where price may react next.
🔍 How It Works
The script identifies pivot highs and lows using user-defined left/right bar counts.
When a new lower high or higher low appears, the indicator draws a line between the two pivots and extends it forward using extend.right.
Each new confirmed trendline stays fixed, creating a historical map of structure that evolves naturally with market action.
Optional filters:
Min Slope – ignore nearly flat trendlines
Show Latest Only – focus on the most relevant trendline
Alerts – get notified when price crosses the most recent uptrend or downtrend line
🧩 Why It’s Useful
This tool helps traders:
Spot emerging trends early
Identify dynamic support/resistance diagonals
Avoid redrawing trendlines manually
Backtest structure breaks historically
⚙️ Inputs
Pivot Left / Right bars
Min slope threshold
Line color, width, and style
Show only latest line toggle
Alert options
Statistical Projection over N Days (drift + σ) – v1.2 [EN]🧭 Overview
“Statistical Projection over N Days (drift + σ)” is a quantitative forecasting model that estimates the expected future price range of any asset over a chosen horizon (default = 10 days).
It combines average drift (trend direction) and historical volatility (σ) to produce a probabilistic cone of future price movement.
The indicator displays:
a blue dashed line (expected price path),
1σ / 2σ deviation bands (volatility envelopes),
and a summary table with the key forecast values and expected return.
⚙️ Core Logic (Explained Simply)
The indicator analyses recent price behavior to estimate two key elements:
the average daily tendency of the market (called drift), and
the average daily variability (called volatility).
Here’s how it works, step by step:
Measures daily percentage changes (using logarithmic returns) to understand how much the price typically moves from one bar to the next.
It then calculates the average of those returns over a chosen historical window (for example, 70 bars).
If the average is positive → the market has a rising tendency (upward drift).
If the average is negative → the market tends to decline (downward drift).
At the same time, it computes the standard deviation of those returns — this shows how “wide” the movements are, i.e. how volatile the asset is.
Using these two measures — drift and volatility — it estimates where the price is statistically expected to move over the next N bars:
The mean projection (blue dashed line) represents the most likely price path.
The 1σ and 2σ lines (teal and gray) define confidence zones, where price is expected to remain about 68% and 95% of the time, respectively.
The model updates continuously with every new bar, recalculating both drift and volatility, so the projection cone expands, contracts, or changes direction depending on the latest market behavior.
📉 Interpretation of the Blue Line
The blue dashed line (pMean) is the statistical forecast path of price over the next N bars.
🔹 When the blue line is below the current price
The recent drift (average log return) is negative → the model expects a gradual decline.
Interpretation:
The prevailing statistical bias is bearish — the market is expected to move lower toward equilibrium.
🔹 When the blue line is above the current price
The recent drift is positive → the model expects a continued rise.
Interpretation:
The price is statistically likely to trend upward, maintaining momentum in the direction of the current drift.
🔹 When the blue line is sloping upward
The mean projection pMean is rising with each new bar.
Indicates positive drift → the average daily return is positive.
Interpretation:
The asset is in a growth phase; volatility bands act as potential expansion corridors.
🔹 When the blue line is sloping downward
The mean projection pMean decreases bar after bar.
Indicates negative drift → average daily return is negative.
Interpretation:
The asset is in a corrective or declining phase, with volatility determining potential drawdown limits.
🔹 When the blue line is flat
The drift (μ) is approximately zero.
Interpretation:
The model sees no directional bias; price equilibrium dominates.
Expect a sideways range unless new volatility (σ) expansion occurs.
📈 How to Read the Entire Projection
Blue dashed line → expected mean path (most probable price trajectory).
Teal lines (±1σ) → statistically normal range (≈68% of future outcomes).
Gray lines (±2σ) → extreme bounds (≈95% of outcomes).
Labels on the right show exact forecast prices for each band.
If the actual price moves outside the gray 2σ range →
→ it signals volatility breakout or regime shift, meaning the past volatility no longer explains the present movement.
🧮 Summary Table
Located at the top-right corner, it provides:
Field Description
Projection (days) Number of bars used for projection (h).
Anchor price Starting close used for forecast.
Mean target (h) Expected price after h bars (blue line endpoint).
1σ Band (↓ / ↑) 68% confidence interval.
2σ Band (↓ / ↑) 95% confidence interval.
Expected return Projected % change from current close to mean target.
Colors can be customized — for example:
white headers,
aqua for anchor price,
lime for target,
orange/red for σ bands,
yellow for expected return.
🧠 Practical Meaning
Blue Line State Interpretation Bias
Above price, rising Ongoing positive drift Bullish
Below price, falling Negative drift Bearish
Flat, near price Neutral drift Sideways
Steep slope Strong directional momentum Trend confirmation
Price > +2σ band Excess volatility / overextension Possible correction
Price < −2σ band Undervaluation or panic Reversion likely
⚡ Summary
Aspect Description
Purpose Statistical forecast of expected price range
Method Drift (μ) + Volatility (σ) from log returns
Outputs Mean projection (blue), 1σ & 2σ bands, expected return
Interpretation Directional bias from blue line and its slope
Recommended timeframe Daily
Best use Trend confirmation, probabilistic target estimation, volatility analysis.
NWOG/NDOG + EHPDA🌐 ENGLISH DESCRIPTION
Hybrid NWOG/NDOG + EHPDA – Advanced Gaps & Event Horizon Indicator
(Enhanced with Real-Time Alerts and Info Table)
📊 Overview
This advanced indicator combines automatic detection of weekly gaps (NWOG) and daily gaps (NDOG) with the Event Horizon (EHPDA) concept, now featuring customizable alerts and a real-time info table for a more efficient trading experience. Designed for traders who operate based on institutional price structures, liquidity zones, and SMC/ICT confluences.
✨ Key Features
1. Gap Detection & Visualization
NWOG (New Week Opening Gap): Identifies and visualizes the gap between Friday’s close and Monday’s open.
NDOG (New Day Opening Gap): Detects daily gaps on intraday timeframes.
Enhanced visualization: Semi-transparent boxes, price levels (top, middle, bottom), and lines extended to the current bar.
Customizable labels: Display gap formation date and price levels (optional).
2. Event Horizon (EHPDA)
Automatically calculates the Event Horizon level between two non-overlapping gaps.
Dashed line marking the equilibrium zone between bullish and bearish gaps.
3. Advanced 5pm-6pm Mode
Special option to detect the Sunday-Monday gap using 4H bars.
4. Real-Time Alerts
New gaps (NWOG/NDOG): Immediate notification when a new gap forms.
Gap fill: Alert when price completely fills a gap.
Event Horizon active: Notification when the Event Horizon level is triggered.
5. Info Table
Real-time display: number of active gaps, Event Horizon status, time remaining until weekly/daily close.
Customizable: position, size, and style.
🎨 Customization
Configurable colors for bullish gaps, bearish gaps, and Event Horizon line.
Customizable price labels and date format.
📈 Use Cases
Reversal trading, price targets, liquidity zones, SMC/ICT confluences.
⚙️ Recommended Settings
Timeframes: Daily and intraday (15m, 1H, 4H, etc.).
NWOG: Enable on all timeframes.
NDOG: Enable only on intraday.
Max Gaps: 3-5 for clean charts, 10-15 for historical analysis.
📝 Important Notes
Works best on 24/5 markets (Forex, Crypto).
Gaps automatically close when filled.
Event Horizon only appears with at least 2 non-overlapping gaps.
VBE Pro - Advanced Volatility Bands with Zero Lag & PredictionVBE Pro: Zero-Lag Predictive Bands
A next-gen volatility envelope that blends zero-lag smoothing with forward-looking volatility models (EWMA/GARCH/HAR/ML) to keep bands tight in calm markets, responsive in shocks, and adaptive across regimes.
What it does
Builds volatility from multiple methods (ATR, StDev, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang).
Projects near-term vol with your choice of predictor, then blends it via a weight slider.
Applies zero-lag smoothing (ZLEMA/ZLMA/DEMA/TEMA/HMA/JMA/Ehlers/Kalman/T3) to cut delay without over-shoot.
Auto-adapts band width by regime (high/low/normal) and can expand dynamically with price acceleration.
Optional displacement to align with your execution style.
On-chart
Upper/Lower zero-lag bands with optional fill.
Middle line (ZL-smoothed source).
Regime-tinted background (High/Low).
Displacement marker (if used).
Compact top-right info table: current vs predicted vol, regime, squeeze, multiplier, methods, ZL gain, est. lag reduction.
Signals & Alerts
Break↑ / Break↓ when price crosses the bands.
Vol↑ / Vol↓ expansion/contraction sequences.
“Squeeze” when band width compresses vs its ZL average.
“ZL” marker when significant zero-lag is active.
Prediction divergence ⚠ when projected vol deviates > threshold.
Built-in alertconditions for all of the above.
Quick start
Method: ATR or Hybrid for robustness.
Smoothing: ZLEMA, length 5–8, ZL gain 2–3 (push higher only if you accept more projection).
Bands: Multiplier 2.0, Adaptive on, Dynamic off to start.
Prediction: EWMA, weight 0.25–0.35. Move to GARCH in mean-reverty tapes; HAR-RV for mixed regimes.
Regime lookback: 50.
PulseRPO Zero-Lag BandsPulseRPO is a momentum and volatility timing suite built on a zero-lag Relative Price Oscillator. It pairs an RPO (fast vs slow MA spread, in %) with adaptive volatility envelopes that tighten or widen as conditions change, so you can spot true momentum bursts, exhaustion and “quiet-before-the-move” squeezes—without the usual MA lag.
What it shows
Zero-Lag RPO: Choose EMA, SMA, WMA, RMA, HMA or ZLEMA for the base, then apply ZLEMA/DEMA/TEMA/HMA zero-lag smoothing to cut delay.
Adaptive Bands: StdDev, ATR, Range or Hybrid volatility; bands auto-tighten in high vol and widen in quiet regimes.
Dynamic OB/OS: Levels scale with current regime so extremes mean something even as volatility shifts.
Signal & Histogram: Classic signal cross plus histogram for quick read of acceleration vs deceleration.
Squeeze Paint: Subtle background highlight when band width compresses below its average.
Divergences & Triggers: Optional bullish/bearish divergence tags, plus band-cross and signal-cross alerts out of the box.
How to use it (general guide)
Momentum entries: Look for RPO crossing up its signal from below or snapping out of a squeeze; extra weight if it also re-enters from below the lower band.
Trend continuation: RPO riding outside the upper (or lower) band with rising histogram = power move; trail risk on pullbacks to the signal line.
Exhaustion / fades: Taps beyond dynamic OB/OS or band re-entries can mark mean-revert windows—confirm with price/volume.
Risk filter: During squeeze, size down and prepare for expansion; after expansion, respect extremes.
Tweak the MA type, band method and zero-lag strength to match your timeframe. PulseRPO is designed to be a self-contained read: regime → setup → trigger → alert.
Trend Strength Detector TSDTrend Strength Detector (TSD)
*Objective Trend Quality Measurement for Educational Market Analysis*
Note: This mathematical framework is a proprietary quantitative model developed by Ario Pinelab, inspired by classical EMA, ADX, RSI and MACD principles, yet not documented in any public technical or academic publication.
## 🎯 Purpose & Design Philosophy
The ** Trend Strength Detector- TSD ** is an educational research tool that provides **quantitative measurement of trend quality** through two independent scoring systems (0-100 scale). It answers the analytical question: *"How strong and aligned is the current market trend environment?"*
This indicator is designed with a **modular, complementary approach** to work alongside various analysis methodologies, particularly pattern-based recognition systems.
## 🔗 Complementary Research Framework
### Designed to Work With Pattern Detection Systems
This indicator provides **environmental context measurement** that complements qualitative pattern recognition tools. It works particularly well alongside systems like:
- **RMBS Smart Detector - Multi-Factor Momentum System**
- Traditional chart pattern analyzers
- Any momentum-based pattern identification tools
🔍 **To find RMBS Smart Detector:**
- Search in TradingView Indicators Library: `" RMBS Smart Detector - Multi-Factor Momentum System"`
- Look for: *Multi-Factor Momentum System*
- By author: ` `
### Why This Complementary Approach?
**Trend Quality Measurement** (TSD - this tool) provides:
- ✅ Structural trend alignment (0-100 score)
- ✅ Momentum intensity levels (0-100 score)
- ✅ Environment classification (Strong/Moderate/Weak)
- 📌 **Answers:** *"HOW STRONG is the underlying trend environment?"*
### Educational Research Value
When used together in a research context, these tools enable systematic study of questions like:
- How do reversal patterns behave when Strength Score is above 70 vs below 30?
- Do continuation patterns in weakening environments (declining scores) show different characteristics?
- What is the correlation between high Alignment Scores and pattern "success rates"?
- Can environment classification help identify genuine trend initiation vs false starts?
⚠️ **Important Note:** Both tools are **independent and work standalone**. TSD provides value whether used alone or with other analysis methods. The relationship with RMBS (or any pattern tool) is **complementary for research purposes**, not dependent.
---
###Mathematical Foundation
##TSA Formula: scoring method developed by Ario
-Trend Model (0 – 100)
TAS = EMA Alignment (0–40) + Price Position (0–30) + Trend Consistency (0–30)
EMA Alignment checks EMA_fast vs EMA_slow vs EMA_trend structure.
Price Position evaluates if Close is above/below all EMAs.
Consistency = 3 × max(bullish,bearish bars within 10 candles).
-Strength Model (0 – 100)
Strength = ADX (0–50) + EMA Slope (0–25) + RSI (0–15) + MACD (0–10)
ADX measures trend energy; Slope shows EMA momentum %;
RSI assesses zone positioning; MACD confirms directional agreement.
Note: This formula represents a proprietary quantitative model by Ario_Pinelab, inspired by classical technical concepts but not published in any external reference.________________________________________
📊 Environment Classification
Based on Total Strength Score:
🟢 Strong Environment: Score ≥ 60
→ Well-defined momentum, clear directional bias
🟡 Moderate Environment: 40 ≤ Score < 60
→ Mixed signals, transitional conditions
🔴 Weak Environment: Score < 40
→ Ranging, choppy, low conviction movement
Color Coding:
• Green background: Strong (≥60)
• Yellow background: Moderate (40-59)
• Red background: Weak (<40)
________________________________________
📈 Visual Components
Main Chart Display
Score Labels (Top-Right Corner):
┌─────────────────────────────────┐
│ 📊 Alignment: 75 | Strength: 82 │
│ Environment: Strong 🟢 │
└─────────────────────────────────┘
Color-Coded Background:
• Environment strength visually indicated via background color
• Helps quick identification of market regime
• Customizable transparency (default: 90%)
Reference Lines:
• Dotted line at 60: Strong/Moderate threshold
• Dotted line at 40: Moderate/Weak threshold
• Mid-line at 50: Neutral reference
________________________________________
🔧 Customization Settings
Input Parameters
The best setting is the default mode.
🚫 Important Disclaimers & Limitations
What This Indicator IS:
✅ Educational measurement tool for trend quality research
✅ Quantitative assessment of current market environment
✅ Complementary analysis tool for pattern-based systems
✅ Historical data analyzer for systematic study
✅ Multi-factor scoring system based on technical calculations
What This Indicator IS NOT:
❌ NOT a trading system or signal generator
❌ NOT financial advice or trade recommendations
❌ NOT predictive of future price movements
❌ NOT a guarantee of pattern success/failure
❌ NOT a substitute for comprehensive risk management
________________________________________
Known Limitations
1. Lagging Nature:
⚠️ All components (EMA, ADX, RSI, MACD) are calculated
from historical price data
→ Scores reflect CURRENT and RECENT conditions
→ Cannot predict sudden reversals or black swan events
→ Trend measurements lag actual price turning points
2. Whipsaw Risk:
⚠️ In choppy/ranging markets, scores may fluctuate rapidly
→ Moderate zone (40-60) can see frequent transitions
→ Low timeframes more susceptible to noise
→ Consider higher timeframes for stable measurements
3. Component Conflicts:
⚠️ Individual components may disagree
→ Example: Strong ADX but weak RSI alignment
→ Scores average these conflicts (may hide nuance)
→ Check individual components for deeper insight
4. Not Predictive:
⚠️ High scores do NOT guarantee continuation
⚠️ Low scores do NOT guarantee reversal
→ Measurement ≠ Prediction
→ Use for CONTEXT, not SIGNALS
→ Combine with comprehensive analysis
________________________________________
Risk Acknowledgments
Market Risk:
• All trading involves substantial risk of loss
• Past performance (even systematic studies) does not guarantee future results
• No indicator, system, or methodology can eliminate market risk
Measurement Limitations:
• Scores are mathematical calculations, not market predictions
• Environmental classification is descriptive, not prescriptive
• Strong measurements can deteriorate rapidly without warning
Educational Purpose:
• This tool is designed for LEARNING about market structure
• Not designed, tested, or validated as a standalone trading system
• Any trading decisions are user’s sole responsibility
No Warranty:
• Indicator provided “as-is” for educational purposes
• No guarantee of accuracy, reliability, or profitability
• Users must verify calculations and apply critical thinking
Open Source
Full Pine Script code available for educational study and modification. Feedback and improvement suggestions welcome.
“All logic is presented for research and educational visualization.”
---
**Attribution & Fair Use Notice**
The Trend Strength Detector (TSD) scoring framework (Multi-Factor Momentum System) was originally designed and formulated by *Ahmadrezarahmati( Ario or Ario_ Pine Lab)*.
If you build upon, modify, or republish this logic—please include proper attribution to the original author. This request is made under a spirit of open collaboration and educational fairness.
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MA Oscillator Map [ChartPrime]⯁ OVERVIEW
The MA Oscillator Map transforms moving average deviations into an oscillator framework that highlights overextended price conditions. By normalizing the difference between price and a chosen moving average, the tool maps oscillations between -100 and +100 , with gradient coloring to emphasize bullish and bearish momentum. When the oscillator cools from extreme levels (-100/100), the indicator marks potential reversal points and extends short-term levels from those extremes. A compact side table and dynamic bar coloring make momentum context visible at a glance.
⯁ KEY FEATURES
Oscillator Mapping (±100 Scale):
Price deviation from the selected MA is normalized into a percentage scale, allowing consistent overbought/oversold readings across assets and timeframes.
// MA
MA = ma(close, maLengthInput, maTypeInput)
diff = src - MA
maxVal = ta.highest(math.abs(diff), 50)
osc = diff / maxVal * 100
Customizable MA Types:
Choose SMA, EMA, SMMA, WMA, or VWMA to fine-tune the smoothing method that powers the oscillator.
Extreme Signal Diamonds:
When the oscillator retreats from +100 or -100, the script plots diamonds to flag potential exhaustion and reversal zones.
Dynamic Levels from Extremes:
Upper and lower dotted lines extend from recent overextension points, projecting temporary barriers until broken by price.
Gradient Bar Coloring:
Candles and oscillator values adopt a bullish-to-bearish gradient, making shifts in momentum instantly visible on the chart.
Compact Momentum Map:
A table at the chart’s edge plots the oscillator position with a gradient scale and live percentage label for precise momentum tracking.
⯁ USAGE
Watch for diamonds after the oscillator exits ±100 — these mark potential exhaustion zones.
Use extended dotted levels as short-term reference lines; if broken, trend continuation is favored.
Combine gradient bar coloring with oscillator shifts for confirmation of momentum reversals.
Experiment with different MA types to adapt sensitivity for trending vs. ranging markets.
Use the side momentum table as a quick-read gauge of trend strength in percent terms.
⯁ CONCLUSION
The MA Oscillator Map reframes moving average deviations into a visual momentum tracker with extremes, reversal signals, and dynamic levels. By blending oscillator math with intuitive visuals like gradient candles, diamonds, and a live gauge, it helps traders spot overextension, exhaustion, and momentum shifts across any market.
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Global Crash & Rally IndicatorGlobal Crash & Rally Indicator for TradingView:
Detect Market Crashes and Rallies with Precision
Unlock the Power of Global Market Insights:
Your Ultimate Stock Market Crash Detector and Rally Signal Tool 📈⚠️
In the volatile world of stock trading, staying ahead of market crashes and spotting rally opportunities can make all the difference between massive gains and devastating losses.
The Global Crash & Rally Indicator – a cutting-edge TradingView Pine Script tool, has been designed to monitor global financial signals in real-time. Whether you're a day trader, swing trader, or long-term investor, this indicator acts as your early warning system for potential market downturns and upswings, helping you navigate the complexities of the stock market with confidence.
Traders often search "stock market crash indicator," "global rally detector," "TradingView crash alert," and "market volatility tool,", this indicator ends your endless search and is a must-try for serious traders who want to protect their portfolio and capitalize on bullish/bearish trends.
What Makes the Global Crash & Rally Indicator Stand Out? 🚀
This advanced indicator goes beyond basic price analysis by integrating a wide array of global economic and market factors. It scans for signs of stress across major indices, volatility measures, currency movements, and commodity prices to provide a comprehensive view of market health. Here's what you can expect:
Real-Time Crash Warnings ⚠️ :
Get alerted to potential market crashes through color-coded signals – from watchful orange alerts to critical red crisis modes. It identifies emerging risks early, giving you time to adjust your positions.
Rally Detection for Bullish Opportunities 📈 :
Not just a downside protector, this tool highlights bullish regimes with green signals, spotting when markets are poised for strong upward moves. Ideal for identifying entry points during recoveries or bull runs and tells you when you can stay in the trade.
Multi-Factor Analysis 🔍 :
it monitors key global elements like volatility spikes, yield changes, risk-off assets, breadth metrics, and more – all without overwhelming you with data. The intuitive table UI displays metrics, values, risks, and notes in an easy-to-read format.
Probability Estimates 📊 :
The probability model of this Indicator offers probabilistic insights into downside and upside risks, helping you gauge the likelihood of market moves with percentage-based forecasts.
Customizable Alerts 🔔 :
Set up notifications for crash cautions, crisis starts, rally watches, and rally go signals by setting up just 01 alert. Perfect for day trading strategies or manual oversight.
Optimized for Traders ⚙️:
Whether searching for "best TradingView indicator for market crashes" or "global stock rally scanner," this tool ranks high in utility, delivering actionable insights tailored to US and international markets.
With its focus on intraday timeframes (like 5-min, 15-min, or 60-min charts), the indicator is versatile for use on major indices such as SPX, VIX, DXY, and beyond. It's built to handle up to 5000 bars back, ensuring historical accuracy without performance lags.
How to Use the Global Crash & Rally Indicator on TradingView 🛠️
Add to Your Chart: Search for "Global Crash & Rally Indicator" in TradingView's indicator library and apply it to your preferred chart (e.g., SPX or ES futures).
Customize Settings: Adjust inputs like analysis timeframe, thresholds for warnings, and optional filters (e.g., currency jumps) to fit your trading style. Enable 3-of-4 warning mode for stricter signals.
Interpret the Signals:
Background Colors: Green for safe/bullish, orange for warnings, red for crises.
Table Breakdown:
Check the on-chart table for detailed metrics on VIX changes, breadth, basis stress, and macro health.
Alerts:
Use the built-in alert conditions to get notified via email, app, or webhook when key events trigger.
Combine with Strategies:
Pair it with your favorite oscillators, moving averages, or volume indicators for enhanced decision-making in forex, stocks, crypto, or commodities.
No need for complex setups –
it's plug-and-play, yet powerful enough for professional traders monitoring global events.
Why Traders Love This Market Volatility Tool ❤️
Imagine having a "sixth sense" for when the market is about to crack or soar. Users rave about its ability to flag hidden risks that traditional indicators miss, such as subtle shifts in market depth or global macro stress. It's not just a crash detector; it's a rally detector too, helping you ride waves of optimism while sidestepping pitfalls.
In an era of geopolitical tensions, economic uncertainties, and rapid news cycles, this indicator empowers you to trade smarter. It's SEO-friendly for discovering terms like "best indicator for detecting stock market rallies" or "global financial crash predictor," ensuring you find the edge you need.
Best Features and Rating 🤖
Various AI tools rate its best features to be its holistic multi-factor approach that blends volatility, breadth, and macro signals into a seamless, probabilistic framework, plus the user-friendly table UI that makes complex data meaningful at a glance.
Join the Conversation! 💬
What are your thoughts on the Global Crash & Rally Indicator? Have you spotted any crashes or rallies using similar tools? Share your experiences, strategies, or questions in the comments below – let's discuss and help each other thrive in the markets! Get connected for a free trial via contact method mentioned in our profile page.
KAB 1.2 Beta🚀 KAB 1.2 Indicator by Lastkingkoby 📈
Unlock the power of smart trading with KAB 1 – your ultimate all-in-one tool for spotting 🔑 support/resistance levels and generating 💰 gold-standard buy/sell signals! Crafted by Koby A. Brown (@Lastkingkoby), this Pine Script v5 indicator overlays directly on your charts for seamless analysis. Perfect for traders hunting for high-probability setups in volatile markets! 🌟
🔰 Key Features:
Dynamic Support & Resistance Lines 🛡️⚔️:
Automatically draws robust S/R lines using a blend of RSI, CMO (based on HMA), and pivot calculations. Watch lines evolve in real-time – they break on breaches 🚧, count bounces 🔄, and even flip roles (e.g., support turns resistance) when conditions change! Customizable timeframe for multi-TF precision. Labels show "Support Line" or "Flipped Res" with color-coded vibes (green for support 💚, orange for resistance 🟠).
Gold Prediction & Signals 🔮💹:
Powered by a sophisticated range filter with smoothed averages and multipliers, it detects trends with upward/downward counters. Get clear bar colors: lime for strong buys 🟢, red for sells 🔴, and more! Signals include:
Buy/Long 💸: Bullish conditions with SL suggestions based on lower bands.
Sell/Short 🐻: Bearish triggers with SL from upper bands.
Warning Alerts ⚠️: Spots potential failed bounces (e.g., "Short Warn" or "Long Warn") to avoid traps – ideal for risk management!
Visuals & Alerts 📊🚨:
Enjoy colorful plots: filter line in green/red/orange 🎨, high/low bands in aqua/fuchsia with translucent fills 🌈. Bar colors highlight momentum shifts. Set up alerts for new S/R lines, buys, sells, and warnings – never miss a move!
📝 How to Use:
Add to your chart and tweak inputs like S/R Timeframe, Gold Period (default 100), or Range Coeff (default 5.0) for your style.
Look for confluences: Buy near flipped support 💪, sell at resistance breakdowns 📉.
Combine with your strategy for crypto, forex, or stocks – it's overlay-friendly!
Pro Tip: Use on higher timeframes for major levels, lower for intraday scalps. Trade smart, stay profitable! 🤑📉
© Koby "Lastkingkoby" Brown – Elevate your game today! 🚀
SuperBandsI've been seeing a lot of volatility band indicators pop up recently, and after watching this trend for a while, I figured it was time to throw my two chips in. The original spark for this idea came years ago from RicardoSantos's Vector Flow Channel script, which used decay channels with timed events in an interesting way. That concept stuck with me, and I kept thinking about how to build something that captured the same kind of dynamic envelope behavior but with a different mathematical foundation. What I ended up with is a hybrid that takes the core logic of supertrend trailing stops, smooths them heavily with exponential moving averages, and wraps them in Donchian-style filled bands with momentum-based color gradients.
The basic mechanism here is pretty straightforward. Standard supertrend calculates a trailing stop based on ATR offset from price, then flips direction when price crosses the trail. This implementation does the same thing but adds EMA smoothing to the trail calculation itself, which removes a lot of the choppiness you get from raw supertrend during sideways periods. The smoothing period is adjustable, so you can tune how reactive versus stable you want the bands to be. Lower smoothing values make the bands track price more aggressively, higher values create wider, slower-moving envelopes that only respond to sustained directional moves.
Where this diverges from typical supertrend implementations is in the visual presentation and the separate treatment of bullish and bearish conditions. Instead of a single flipping line, you get persistent upper and lower bands that each track their own trailing stops independently. The bullish band trails below price and stays active as long as price doesn't break below it. The bearish band trails above price and remains active until price breaks above. Both bands can be visible simultaneously, which gives you a dynamic channel that adapts to volatility on both sides of price action. When price is trending strongly, one band will dominate and the other will disappear. During consolidation, both bands tend to compress toward price.
The color gradients are calculated by measuring the rate of change in each band's position and converting that delta into an angle using arctangent scaling. Steeper angles, which correspond to the band moving quickly to catch up with accelerating price, get brighter colors. Flatter angles, where the band is moving slowly or staying relatively stable, fade toward more muted tones. This gives you a visual sense of momentum within the bands themselves, not just from price movement. A rapidly brightening band often precedes expansion or breakout conditions, while fading colors suggest the trend is losing steam or entering consolidation.
The filled regions between price and each band serve a similar function to Donchian channels or Keltner bands, creating clearly defined zones that represent normal price behavior relative to recent volatility. When price hugs one band and the fill area compresses, you're in a strong directional regime. When price bounces between both bands and the fills expand, you're in a ranging environment. The transparency gradients in the fills make it easier to see when price is near the edge of the envelope versus safely inside it.
Configuration is split between bullish and bearish settings, which lets you asymmetrically tune the indicator if you find that your market or timeframe has different characteristics in uptrends versus downtrends. You can adjust ATR period, ATR multiplier, and smoothing independently for each direction. This flexibility is useful for instruments that exhibit different volatility profiles during bull and bear phases, or for strategies that want tighter trailing on longs than shorts, or vice versa.
The ATR period controls the lookback window for volatility measurement. Shorter periods make the bands react quickly to recent volatility spikes, which can be beneficial in fast-moving markets but also leads to more frequent whipsaws. Longer periods smooth out volatility estimates and create more stable bands at the cost of slower adaptation. The multiplier scales the ATR offset, directly controlling how far the bands sit from price. Smaller multipliers keep the bands tight, triggering more frequent direction changes. Larger multipliers create wider envelopes that give price more room to move without breaking the trail.
One thing to note is that this indicator doesn't generate explicit buy or sell signals in the traditional sense. It's a regime filter and envelope tool. You can use band breaks as directional cues if you want, but the primary value comes from understanding the current volatility environment and whether price is respecting or violating its recent behavioral boundaries. Pairing this with momentum oscillators or volume analysis tends to work better than treating band breaks as standalone entries.
From an implementation perspective, the supertrend state machine tracks whether each direction's trail is active, handles resets when price breaks through, and manages the EMA smoothing on the trail points themselves rather than just post-processing the supertrend output. This means the smoothing is baked into the trailing logic, which creates a different response curve than if you just applied an EMA to a standard supertrend line. The angle calculations use RMS estimation for the delta normalization range, which adapts to changing volatility and keeps the color gradients responsive across different market conditions.
What this really demonstrates is that there are endless ways to combine basic technical concepts into something that feels fresh without reinventing mathematics. ATR offsets, trailing stops, EMA smoothing, and Donchian fills are all standard building blocks, but arranging them in a particular way produces behavior that's distinct from each component alone. Whether this particular arrangement works better than other volatility band systems depends entirely on your market, timeframe, and what you're trying to accomplish. For me, it scratched the itch I had from seeing Vector Flow years ago and wanting to build something in that same conceptual space using tools I'm more comfortable with.
Bitgak [Osprey]🟠 INTRODUCTION
Bitgak , translated as "Oblique Angle" in Korean, is a strategy used by multi-hundred-million traders in Korea, sometimes more heavily than Fibonacci retracement.
It is a concept that by connecting two or more pivot points on the chart and creating equidistant parallel lines, we can spot other pivot points. As seen in the example, a line at a different height but with the same angle spots many pivot points.
This indicator spots pivot points on the chart and tests all different possible Bitgak lines with a brute-force method. Then it shows the parallel line configuration with the most pivots hitting it. You may use the lines drawn on the chart as possible reversal points.
It is best to use on Day and Week candles . In the very short range of time, the noise makes it hard to capture meaningful data.
🟠 HOW TO USE
The orange dots are the major pivot points (you can set the period of the long-term pivot) upon which the lines are built.
Change the "Manual Lookback Bars" from 300 to a meaningful period upon your inspection.
"Hit Tolerance %" means how close a pivot needs to be to the line to be considered as having touched the line.
If the line is too narrow, which is not very useful, you may consider increasing the "Long-term Pivot Bars" and experimenting with different settings for Channel Lines and Heuristics.
The result:
"Top Anchors to Test (L)" is how many L highest peaks and L lowest troughs should be weighed heavily when testing the lines. That is, with L = 1, the algorithm will reward the Bitgak lines that touch 1 highest peak and 1 lowest trough. It doesn't make much intuitive sense, so I suggest just testing it out.
🟠 HOW IT WORKS
Step 1: Pivot Detection
The indicator runs two parallel detection systems:
Short-term pivots (default: 7 bars on each side) - Captures minor swing highs/lows for detailed analysis
Long-term pivots (default: 17 bars on each side) - Identifies major structural turning points
These pivots form the foundation for all channel calculations.
Step 2: Anchor Point Selection
From the detected long-term pivots, the algorithm identifies:
The L highest peaks (default L=1, meaning the single highest peak)
The L lowest troughs (default L=1, meaning the single lowest trough)
These become potential "anchor points" for channel construction. Higher L values test more combinations but increase computation time.
Step 3: Channel Candidate Generation
For support channels: Every pair of troughs becomes a potential base line (A-B)
For resistance channels: Every pair of peaks becomes a potential base line (A-B)
The algorithm then tests each peak (for support) or trough (for resistance) as pivot C.
Step 4: Optimal Spacing Calculation
For each A-B-C combination, the algorithm calculates:
Unit Spacing = (Distance from C to A-B line) / Multiplier
It tests multipliers from 0.5 to 4.0 (or your custom range), asking: "If pivot C sits on the 1.0 line, what spacing makes the most pivots hit other lines?"
Step 5: Scoring & Selection
Each configuration is scored by counting how many pivots fall within tolerance (default 1% of price) of any parallel line in the range . The highest-scoring channel is drawn on your chart.
Medium-Term Valuation | MiesOnChartsThis medium-term valuation indicator integrates multiple valuation metrics to assist investors in identifying oversold and overbought market conditions with greater precision.
How to Interpret:
The indicator employs adaptive standard deviation bands to define extreme market zones. The red band signals a strongly overbought condition, while the green band indicates a significantly oversold condition.
How to Apply:
Investors can leverage these extreme levels as strategic points for taking profits or implementing dollar-cost averaging (DCA) strategies, optimizing entry and exit decisions in the market.
Disclaimer: NOT Financial advice. Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.






















