CMO_EMA (Chande Momentum Oscillator and EMA)
The absolute value of "CMO" alone makes it impossible to know the current location for the waves and there is a possibility of doing useless entry.
To prevent this, display EMA.
Cerca negli script per "entry"
Systematic TF IndicatorThis is a simple trend following indicator which works off moving averages for trend bias and breakouts for entry.
Ichimoku Lagging Background ColorThis script colors the background, 26 bars ago, based upon the lagging line being above or below the closing price of 26 bars ago. The lagging line is used as a confirmation for your current entry.
Momentum Linear RegressionThe original script was posted on ProRealCode by user Nicolas.
This is an indicator made of the linear regression applied to the rate of change of price (or momentum). I made a simple signal line just by duplicating the first one within a period decay in the past, to make those 2 lines cross. You can add more periods decay to made signal smoother with less false entry.
ATR Anchored Range %b by TradeSeekersAll time highs got you spooked to enter with no levels in sight?
Stuck in a multi-week range and wondering where the heck the pivots are!?
Wondering if you're longing the top or shorting the potential bottom and about to get smoked, sending you back to burger flipping?!
Fret not trading friends!
I've been crafting the ultimate map for scalpers, slingers, swingers, swindlers, swashbucklers -and traders too.
Why should I care about this, what's an ATR!?
Nearly any trader that's entered the markets has heard of ATR, perhaps even taken a stab at trying to calculate the flux capacity of a weekly ATR on a lower timeframe. Continually calculating things manually sucks!
Ok, so you haven't heard of ATR? It's the average true range... what's the true range!? It's simply the low subtracted from the high (high - low) of any given candle.
How is ATR useful?
The theory is simple, if the ATRs on the daily timeframe for a stock are 5, then traders may have a reasonable expectation that any day in the near future the stock will mostly move +/- 5 pts. This +/- 5 can be used as a possible daily high and low for traders to use.
But ATR changes as time passes, with every billionaire X post, viral cat meme, fed announcement or government shutdown the market makes it's move. This means without this tool, traders need to run the standard lame (sorry) ATR indicator and then hand draw a bunch of important levels (barf).
I'm convinced and ready to join the ATR army, what do I do?
Glad to have you aboard sailor, slap this indicator on your layout - it'll initially display a bottom panel, say nice things to it.
Usage
The lower panel provides a %b plot representative of the current price relative to the timeframe and period ATR. (Defaults to 1D timeframe and 20 - 20 trading days in a month yo)
This %b plot is a map for price against the key ATR based levels and resets each time the timeframe change occurs.
Keep reading! (maybe grab a snack, you're doing great)
If you want to see what the indicator sees, how it maths the math, open the settings and check the "overlay" option... it's amazing, I know.
Main base of operations
This will be the gray area between first red and green lines, imagine this is a future candle for the timeframe anchored. The red would represent the candle high (red means stop/overbought), and the green would represent the candle low (green means go/oversold).
Regardless of the timeframe anchored, this area always represents the area the ATR indicates will be the building area of the current candle being formed. Traders should expect most of the trading to occur within this area.
The mid line
Don't diddle in the middle, this by default is the open price and it's the ultimate bias filter for bull or bear riders.
Extension areas
Beyond the gray area is the extension zone, this provides a whole ATR from the mid line to the extension.
Assembling a trade plan
There are just a couple of key concepts to master in order to become the ultimate ATR samurai warrior, capable of slicing through even the messiest liquidity.
Above the midline and holding, but still within the gray area? Could be a great long entry with targets to upper levels. The same holds true for below open and holding while still being within the lower gray area.
As price makes it's ascension or decline towards the ends of the initial gray ATR range, consider managing trades here. If it's suspected, due to a strong hold of the midline, that the range low or high is the midline, then continue to manage trades towards the extension zones.
Timeframes and periods oh my
The tooltips already provide some hints, but not everyone goes around clicking and hovering everything in sight (maybe I'm the only one that does that?).
There's a thoughtful approach to the default values, I like to consider the big market participants with my day trades, swings trades and beyond.
By default I've chosen the daily timeframe and a period of 20, one for each trading day of the calendar month.
It's no large leap to consider alternatives, what about 1W timeframe and a period of 4 (1 month) or 52 (1 year)?
The possibilities are nearly infinite, comment on any particular favorite combos.
An Italian Special Bonus!!!
...sorry, it's not pizza....
First, did you know the famous Italian Fibonacci's real name was actually Leonardo? I'm not sure how I feel about that. Fun fact, my ancestors are Italian.
Alright, you may have guessed that the special bonus is the mythical Fibonacci inspired "Golden Pocket", maybe it's a foreshadowing of your pockets - one can only hope.
Use this feature to show the commonly referenced Fibonacci levels within each major ATR range. I've seen some totally mathematical epic-ness with these hence the addition.
Once key ATR levels have been hit look for reversals back to golden pockets (you tricksy hobbits) for potential entry back towards the prior hit ATR level.
The %b turns gold if you have the feature enabled and of course the overlay displays them also, how fun!
Final thoughts
I hope you have as much fun using this indicator as I do, it has brought much joy to my trading experience. If you don't have fun with it, well I hope you had fun reading about it at least.
100% human crafted and darn proud of it
- SyntaxGeek
Yuki Leverage RR Calculator**YUKI LEVERAGE RR CALCULATOR**
A professional-grade risk/reward calculator for leveraged crypto or forex trades.
Instantly visualizes entry, stop loss, targets, leverage, and risk-to-reward ratios — helping you plan precise positions with confidence.
──────────────────────────────
**WHAT IT DOES**
Calculates position value, quantity, stop-loss price, liquidation estimate, and per-target profit.
Displays everything in an on-chart table with optional price tags and alerts.
──────────────────────────────
**KEY FEATURES**
• Long / Short toggle (only one active at a time)
• Leverage-aware position sizing based on Position Cost ($) and Leverage
• Dynamic Stop Loss: input % → auto price + $ risk
• Up to 3 Take-Profit Targets with scaling logic
• Instant R:R ratios per target
• Liquidation estimate (approximation only)
• ENTRY / SL / T1 / T2 / T3 / LIQ visual tags
• Dark/Light mode, adjustable table and tag size
• Built-in alerts for Targets and Stop Loss
──────────────────────────────
**INPUTS**
• Long or Short selection
• Entry Price, Stop Loss %
• Target 1 / Target 2 / Target 3 + Take Profit %
• Position Cost ($), Leverage
• Visual preferences: show/hide table, table corner, font size, tag offset, text size
──────────────────────────────
**TABLE OUTPUTS**
Position Info: Type, Entry, Position Cost, Leverage, Value
Risk Section: Stop Loss %, Stop Loss Price, Total Risk ($), Liquidation % & Price
Targets 1–3: Profit ($), R:R, Take Profit ($), Runner % or PnL
──────────────────────────────
**ALERTS**
• Target 1 Hit – when price crosses T1
• Target 2 Hit – when price crosses T2
• Target 3 Hit – when price crosses T3
• Stop Loss Hit – triggers based on direction
(Use TradingView Alerts → Condition → Indicator → select desired alert)
──────────────────────────────
**HOW TO USE**
1. Choose Long or Short
2. Enter Entry Price, Stop Loss %, Position Cost, and Leverage
3. Add Targets 1–3 with optional Take Profit %
4. Adjust visuals as desired
5. Monitor table + alerts for live trade planning
──────────────────────────────
**NOTES**
• Liquidation values are estimates only
• Fees, slippage, and funding not included
• Designed for educational and planning purposes
──────────────────────────────
⚠️ **DISCLAIMER**
For educational use only — not financial advice.
Trading leveraged products involves high risk of loss.
Always confirm calculations with your exchange and trade responsibly.
Prop Algo Prop Algo — MTF Trend + Signals + SMC Toolkit
**What it is**
Prop Algo is a multi-tool trading assistant that blends trend following, contrarian timing, and Smart Money Concepts (SMC). It plots clean buy/sell labels, paints candles by momentum state, maps TP/SL levels automatically, shows a compact **Smart Panel** (dashboard), and draws **auto-trendlines**, **trend clouds**, and **institutional zones** (OB/BB/MB). It’s built to help discretionary traders make faster, rules-based decisions without drowning in settings.
---
Core Signals
* **Buy / Strong Buy** and **Sell / Strong Sell** labels driven by:
* **Supertrend** cross + confirmation stack (MACD slope, HMA(55) impulse, EMA150/EMA250 bias, channel direction).
* Optional **Contrarian Mode** via RSI “trend shifter” (fast/slow crossover with guardrails).
* Optional **High-Volume Filter** and **Consolidation Filter** (ADX).
* Optional **Trend Cloud Filter** (Smooth / Scalping / Scalping+ / Swing).
* **Trend Scalper preset** (5/9/21 EMA on HA-smoothed price) with color-filled momentum bands.
---
Risk & Trade Management
* **Dynamic TP/SL** visuals: entry, stop, and **TP1/TP2/TP3** auto-projections.
* **ATR or %-based trailing stop** (toggle).
* **RSI-based TP markers** (cross levels for staged exits).
* Optional **market structure swings** (HH/HL/LH/LL labels).
Dashboard
A one-glance status block showing:
* **MTF bias:** 5m, 15m, 30m, 1h, 4h (green/red tiles based on 200-EMA state).
* **Market State:** Trending / Ranging / Inactive (TVR proxy).
* **Volatility %** (ATR/StdDev normalization).
* **Institutional Activity** (volume filter).
* **Current Session** (Sydney/Tokyo/London/New York).
* **Trend Pressure** (EMA9 slope: Bullish / Bearish / Flat).
---
Smart Money Concepts
* **Automated BoS** (Break of Structure) labeling.
* **Order Blocks:** Bu-OB / Be-OB with extend-right boxes.
* **Break Blocks / Mitigation Blocks:** Bu-BB / Be-BB and Bu-MB / Be-MB.
* **Auto maintenance:** zones extend, alert when price enters, and optionally delete when invalidated.
* **Minimal ZigZag** backbone (length-driven pivots) with Fib-based confirmation logic.
Trend Cloud & Candle Heatmap
* **Trend Cloud:** Smooth / Scalping / Scalping+ / Swing; optional EMA150/EMA250 fill for higher-timeframe bias.
* **MACD heatmap candles:** multi-tier green/red/yellow body coloring based on MACD and histogram progression.
Auto Trendlines
* **Regression-style channel** from WMA/SMA blend with **±RMSE envelopes**, extended to the right for developing support/resistance rails.
Inputs
* **Signal Mode / Filters:** Trending, Contrarian, High Volume, Strong-only, and Cloud filters.
* **Sensitivity / Tuner:** Supertrend factor & length, Reversal Dot tuner.
* **Risk Management:** Use % or ATR, TP multipliers (TP1/2/3), Trailing SL toggle.
* **Market Structure:** Show swings, swing length.
* **Dashboard:** On/off, position, size.
* **Sessions:** Auto detection (Sydney/Tokyo/London/New York).
*(Default “Presets” is **All Signals**; you can still use the “Trend Scalper” subset by enabling the dedicated view inside the script.)*
Alerts
* **Normal Buy / Strong Buy**
* **Normal Sell / Strong Sell**
* **Stop-Loss Crossed**
* **Target 1 / Target 2 / Target 3 Crossed**
* **Cloud Turned Bullish / Bearish**
* **MSB (Market Structure Break)**
> Tip: set alerts on “Once Per Bar Close” for cleaner signals.
How to Use
1. **Pick a mode:** start with **Trending Signals ** + **Smooth Cloud** for swing/position, or **Scalping/Scalping+** for intraday.
2. **Confirm bias:** glance at the **MTF tiles** and **Trend Pressure**. Trade in alignment or deliberately fade (Contrarian Mode) with tight risk.
3. **Plan risk:** use the auto **Entry/SL/TP** lines; enable **Trailing SL** if you prefer dynamic exits.
4. **Watch zones:** when price enters **OB/BB/MB** boxes, expect reactions; combine with signal labels for confluence.
5. **Respect structure:** BoS prints are context—don’t fight fresh structure without a plan.
Best Practices
* Works on **crypto, indices, FX, commodities, stocks**.
* Timeframes: from **5m** up to **4H/1D**. Lower TFs benefit from Cloud filters or Strong-only mode.
* Avoid over-stacking filters at first; add filters only if you need fewer, higher-quality signals.
Notes & Limits
* This is **not** a standalone “autopilot.” It’s a **decision support** system.
* Past performance ≠ future results. Always test on **replay** and **paper** first.
* No financial advice. Manage risk like a professional.
⚡ Hidden Impulse# ⚡ Hidden Impulse | Advanced Multi-Timeframe Trading System
## Overview
**Hidden Impulse** is a sophisticated multi-timeframe indicator that combines three powerful technical analysis tools to identify high-probability trading opportunities. The indicator uses Schaff Trend Cycle (STC), Force Index, and EMA filters to generate precise entry signals across multiple timeframes.
This indicator is designed for traders who want to catch momentum shifts early while filtering out false signals using multi-timeframe confirmation.
---
## Core Components
### 1. **Schaff Trend Cycle (STC)**
The STC is an advanced oscillator that combines MACD and Stochastic indicators to identify trend changes faster than traditional oscillators. It oscillates between 0 and 100:
- **Below 25**: Oversold zone (potential bullish reversal)
- **Above 75**: Overbought zone (potential bearish reversal)
- **Crossovers**: Signal potential trend changes
**Key Advantage**: The STC reacts faster to price changes than MACD while producing fewer false signals than Stochastic.
### 2. **Force Index**
Developed by Dr. Alexander Elder, the Force Index measures the strength behind price movements by combining:
- Price change
- Volume
It helps confirm the legitimacy of trends:
- **Positive values**: Bulls are in control
- **Negative values**: Bears are in control
- **Zero-line crosses**: Potential momentum shifts
### 3. **EMA Filter (50-period)**
Acts as a trend filter to ensure trades align with the broader market direction:
- Price above EMA → Look for LONG setups
- Price below EMA → Look for SHORT setups
---
## Three Trading Setups
### 📊 **Setup A: Classic (Most Frequent)**
**Entry Conditions - LONG:**
- Higher timeframe STC > 25 (bullish confirmation)
- Primary timeframe STC crosses above 25
- Force Index positive or crossing above zero
- Price above EMA 50
**Entry Conditions - SHORT:**
- Higher timeframe STC < 75 (bearish confirmation)
- Primary timeframe STC crosses below 75
- Force Index negative or crossing below zero
- Price below EMA 50
**Best for:** Catching trend continuations with multi-timeframe confirmation
---
### 💎 **Setup B: Divergence (Highest Win Rate)**
**Bullish Divergence:**
- Price makes a Lower Low (LL)
- Force Index makes a Higher Low (HL)
- STC in oversold zone (<25)
- Trigger: STC starts rising + Force Index crosses above zero
**Bearish Divergence:**
- Price makes a Higher High (HH)
- Force Index makes a Lower High (LH)
- STC in overbought zone (>75)
- Trigger: STC starts falling + Force Index crosses below zero
**Best for:** Identifying trend reversals with strong risk/reward ratios
---
### ⚡ **Setup C: Bounce (Fast Scalping)**
**LONG Bounce:**
- Price touches EMA 50 from above
- STC in extreme oversold (<15)
- Force Index positive
**SHORT Bounce:**
- Price touches EMA 50 from below
- STC in extreme overbought (>85)
- Force Index negative
**Best for:** Quick mean-reversion trades during strong trends
---
## Key Features
### ✅ **Multi-Timeframe Analysis**
- Choose any timeframe for primary STC calculation
- Select a higher timeframe for trend confirmation
- Visual display of both timeframes on one chart
### ✅ **Smart Signal Filtering**
- Only shows signals when all conditions align
- Filters out weak setups automatically
- Color-coded labels for easy identification
### ✅ **Comprehensive Information Panel**
Real-time dashboard showing:
- Current STC values for both timeframes
- Force Index direction
- Price position relative to EMA
- Active trend direction
- Current signal type
### ✅ **Visual Clarity**
- STC oscillator with oversold/overbought zones
- Force Index histogram (normalized for easy reading)
- Clear level lines at 25, 50, and 75
- Green/red background shading in extreme zones
### ✅ **Flexible Alerts**
- Individual alerts for each setup type (A, B, C)
- Separate LONG and SHORT alerts
- General "ANY LONG" and "ANY SHORT" alerts
- Custom alert messages for quick recognition
---
## Settings & Customization
### **Schaff Trend Cycle**
- **Length 1** (default: 23): Fast MACD period
- **Length 2** (default: 50): Slow MACD period
- **Smoothing** (default: 10): Stochastic smoothing period
- **Lower Level** (default: 25): Oversold threshold
- **Upper Level** (default: 75): Overbought threshold
### **Timeframes**
- **Primary Timeframe**: Leave empty for chart timeframe or select custom
- **Higher Timeframe** (default: 30min): For trend confirmation
### **Force Index**
- **EMA Period** (default: 13): Smoothing period for Force Index
### **EMA Filter**
- **Period** (default: 50): Trend filter period
### **Signal Controls**
- Toggle Setup A (Classic)
- Toggle Setup B (Divergence)
- Toggle Setup C (Bounce)
- Show/hide chart labels
- Show/hide higher timeframe STC
---
## How to Use
### **Step 1: Set Your Timeframes**
Choose your primary trading timeframe (current chart) and a higher timeframe for confirmation. Common combinations:
- 5min + 15min (scalping)
- 15min + 30min (day trading)
- 30min + 1H (swing trading)
- 1H + 4H (position trading)
### **Step 2: Wait for Signal**
The indicator will automatically display labeled signals when conditions align:
- 🟢 Green labels = LONG signals
- 🔴 Red labels = SHORT signals
- A/B/C prefix indicates setup type
### **Step 3: Check Information Panel**
Before entering, verify in the info panel:
- Both STC values confirm the direction
- Force Index aligns with signal
- Price position relative to EMA is correct
- Trend shows green (LONG) or red (SHORT)
### **Step 4: Set Alerts**
Create alerts for your preferred setup types:
- Setup B alerts for highest quality signals
- "ANY LONG/SHORT" for maximum opportunities
- Individual setup alerts for specific strategies
---
## Trading Tips
### **Best Practices:**
1. **Setup B (Divergence)** typically offers the best risk/reward ratios
2. Use **Setup A** for trend continuation in strong markets
3. **Setup C** works best in ranging markets with clear EMA respect
4. Always check higher timeframe confirmation before entering
5. Consider volume spikes when Force Index shows strong readings
### **Risk Management:**
- Place stops below/above recent swing points
- Use ATR-based position sizing
- Take partial profits at STC extreme levels (15/85)
- Avoid trading against higher timeframe STC direction
### **Market Conditions:**
- **Trending markets**: Focus on Setup A
- **Ranging markets**: Focus on Setup C
- **Reversal points**: Focus on Setup B
- **High volatility**: Increase timeframes for stability
---
## Technical Details
**Indicator Type:** Oscillator (separate window)
**Overlay:** No (displays in separate pane below chart)
**Repainting:** No - signals are confirmed on bar close
**Max Bars Back:** 500 (adjustable)
**Compatible with:** All markets (Forex, Stocks, Crypto, Futures)
---
## Credits
This indicator combines:
- **Schaff Trend Cycle** by Doug Schaff
- **Force Index** by Dr. Alexander Elder
- **EMA filtering** and multi-timeframe analysis
Original implementation and trading setups developed for TradingView.
---
## Disclaimer
This indicator is a technical analysis tool and does not guarantee profitable trades. Always use proper risk management, combine with your own analysis, and never risk more than you can afford to lose. Past performance does not indicate future results.
---
## Support & Updates
For questions, suggestions, or bug reports, please use the comments section below. Regular updates and improvements are planned based on user feedback.
**Happy Trading! 📈**
HTF Cross Breakout [CHE] HTF Cross Breakout — Detects higher timeframe close crossovers for breakout signals, anchors VWAP for trend validation, and flags continuations or traps with visual extensions for delta percent and stop levels.
Summary
This indicator spots moments when the current chart's close price crosses a higher timeframe close, marking potential breakouts only when the current bar shows directional strength. It anchors a volume-weighted average price line from the breakout point to track trend health, updating labels to show if the move continues or reverses into a trap. Extensions add a dotted line linking the breakout level to the current close with percent change display, plus a stop-loss marker at the VWAP end. Signals gain robustness from higher timeframe confirmation and anti-repainting options, reducing noise in live bars compared to simple crossover tools.
Motivation: Why this design?
Traders often face false breakouts from intrabar wiggles on lower timeframes, especially without higher timeframe alignment, leading to whipsaws in volatile sessions. This design uses higher timeframe close as a stable reference for crossover detection, combined with anchored volume weighting to gauge sustained momentum. It addresses these by enforcing bar confirmation and directional filters, providing clearer entry validation and risk points without overcomplicating the chart.
What’s different vs. standard approaches?
Reference baseline
Standard crossover indicators like moving average crosses operate solely on the chart timeframe, ignoring higher timeframe context and lacking volume anchoring.
Architecture differences
- Higher timeframe data pulls via security calls with optional repainting control for stability.
- Anchored VWAP resets at each signal, accumulating from the breakout bar only.
- Label dynamics update in real-time for continuation checks, with extensions for visual delta and stop computation.
- Event-driven line finalization prunes old elements after a set bar extension.
Practical effect
Charts show persistent lines and labels that extend live but finalize cleanly on new events, avoiding clutter. This matters for spotting trap reversals early via label color shifts, and extensions provide quick risk visuals without manual calculations, improving decision speed in trend trades.
How it works (technical)
The indicator first determines a higher timeframe based on user selection, pulling its close price securely. It checks for crossovers or crossunders of the current close against this higher close, but only triggers on confirmed bars with matching directional opens and closes. On a valid event, a horizontal line and label mark the higher close level, while a dashed VWAP line starts accumulating typical price times volume from that bar onward. During the active phase, the breakout line extends to the current bar, the label repositions and updates text based on whether the current close holds above or below the level for bulls or bears. A background tint warns if the close deviates adversely from the current VWAP. Extensions draw a vertical dotted line at the last bar between the breakout level and close, placing a midpoint label with percent difference; separately, a label at the VWAP end shows a computed stop price. Persistent variables track the active state and accumulators, resetting on new events after briefly extending old elements. Repaint risk from security calls is mitigated by confirmed bar gating or user opt-in.
Parameter Guide
Plateau Length (reserved for future, currently unused): Sets a length for potential plateau detection in extensions; default 3, minimum 1. Higher values would increase stability but are not active yet—leave at default to avoid tuning.
Line Width: Controls thickness of breakout, VWAP, and extension lines; default 2, range 1 to 5. Thicker lines improve visibility on busy charts but may obscure price action—use 1 for clean views, 3 or more for emphasis.
+Bars after next HTF event (finalize old, then delete): Extends old lines and labels by this many bars before deletion on new signals; default 20, minimum 0. Shorter extensions keep charts tidy but risk cutting visuals prematurely; longer aids review but builds clutter over time.
Evaluate label only on HTF close (prevents gray traps intrabar): When true, label updates wait for higher timeframe confirmation; default true. Enabling reduces intrabar flips for stabler signals, though it may delay feedback—disable for faster live trading at repaint cost.
Allow Repainting: Permits real-time security data without confirmation offset; default false. False ensures historical accuracy but lags live bars; true speeds updates but can repaint on HTF closes.
Timeframe Type: Chooses HTF method—Auto Timeframe (dynamic steps up), Multiplier (chart multiple), or Manual (fixed string); default Auto Timeframe. Auto adapts to chart scale for convenience; Multiplier suits custom scaling like 5 times current; Manual for precise like 1D on any chart.
Multiplier for Alternate Resolution: Scales chart timeframe when Multiplier type selected; default 5, minimum 1. Values near 1 mimic current resolution for subtle shifts; higher like 10 jumps to broader context, increasing signal rarity.
Manual Resolution: Direct timeframe string like 60 for 1H when Manual type; default 60. Match to trading horizon—shorter for swing, longer for positional—to balance frequency and reliability.
Show Extension 1: Toggles dotted line and delta percent label between breakout level and current close; default true. Disable to simplify for basic use, enable for precise momentum tracking.
Dotted Line Width: Thickness for Extension 1 line; default 2, range 1 to 5. Align with main Line Width for consistency.
Text Size: Size for delta percent label; options tiny, small, normal, large; default normal. Smaller reduces overlap on dense charts; larger aids glance reads.
Decimals for Δ%: Precision in percent change display; default 2, range 0 to 6. Fewer decimals speed reading; more suit low-volatility assets.
Positive Δ Color: Hue for upward percent changes; default lime. Choose contrasting for visibility.
Negative Δ Color: Hue for downward percent changes; default red. Pair with positive for quick polarity scan.
Dotted Line Color: Color for Extension 1 line; default gray. Neutral tones blend well; brighter for emphasis.
Background Transparency (0..100): Opacity for delta label background; default 90. Higher values fade for subtlety; lower solidifies for readability.
Show Extension 2: Toggles stop-loss label at VWAP end; default true. Turn off for entry focus only.
Stop Method: Percent from VWAP end or fixed ticks; options Percent, Ticks; default Percent. Percent scales with price levels; Ticks suits tick-based instruments.
Stop %: Distance as fraction of VWAP for Percent method; default 1.0, step 0.05, minimum 0.0. Tighter like 0.5 reduces risk but increases stops; wider like 2.0 allows breathing room.
Stop Ticks: Tick count offset for Ticks method; default 20, minimum 0. Adjust per asset volatility—fewer for tight control.
Price Decimals: Rounding for stop price text; default 4, range 0 to 10. Match syminfo.precision for clean display.
Text Size: Size for stop label; options tiny, small, normal, large; default normal. Scale to chart zoom.
Text Color: Foreground for stop text; default white. Ensure contrast with background.
Inherit VWAP Color (BG tint): Bases stop label background on VWAP hue; default true. True maintains theme; false allows custom black base.
BG Transparency (0..100): Opacity for stop label background; default 0. Zero for no tint; up to 100 for full fade.
Reading & Interpretation
Breakout lines appear green for bullish crosses or red for bearish, extending live until a new event finalizes them briefly then deletes. Labels start blank, updating to Bull Cont. or Bear Cont. in matching colors if holding the level, or gray Bull Trap/Bear Trap on reversal. VWAP dashes yellow for bulls, orange for bears, sloping with accumulated volume weight—deviations trigger faint red background warnings. Extension 1's dotted vertical shows at the last bar, with midpoint label green/red for positive/negative percent from breakout to close. Extension 2 places a left-aligned label at VWAP end with stop price and method note, tinted to VWAP for context.
Practical Workflows & Combinations
For trend following, enter long on green Bull Cont. labels above VWAP with higher highs confirmation, filtering via rising structure; short on red Bear Cont. below. Pair with volume surges or RSI above 50 for bulls to avoid traps. For exits, trail stops using the Extension 2 level, tightening on warnings or gray labels—aggressive on continuations, conservative post-trap. In multi-timeframe setups, use default Auto on 15m charts for 1H signals, scaling multiplier to 4 for daily context on hourly; test on forex/stocks where volume is reliable, avoiding low-liquidity assets.
Behavior, Constraints & Performance
Signals confirm on bar close with HTF gating when strict mode active, but live bars may update if repainting enabled—opt false for backtest fidelity, true for intraday speed. Security calls risk minor repaints on HTF closes, mitigated by confirmation offsets. Resources cap at 1000 bars back, 50 lines/labels total, with event prunes to stay under budgets—no loops, minimal arrays. Limits include VWAP lag in low-volume periods and dependency on accurate HTF data; gaps or holidays may skew anchors.
Sensible Defaults & Quick Tuning
Defaults suit 5m-1H charts on liquid assets: Auto HTF, no repaint, 1% stops. For choppy markets with excess signals, enable strict eval and bump multiplier to 10 for rarer triggers. If sluggish in trends, shorten extend bars to 10 and allow repainting for quicker visuals. On high-vol like crypto, widen stop % to 2.0 and use Ticks method; for stables like indices, tighten to 0.5% and keep Percent.
What this indicator is—and isn’t
This is a signal visualization layer for breakout confirmation and basic risk marking, best as a filter in discretionary setups. It isn’t a standalone system or predictive oracle—combine with price structure, news awareness, and sizing rules for real edges.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Lucas' Money GlitchHere's a description you can use to publish your indicator to TradingView:
Title: Triple SuperTrend + RSI + Fib BB + Volume Oscillator
Short Description:
Advanced multi-indicator system combining three SuperTrends, RSI, Fibonacci Bollinger Bands, DEMA filter, and Volume Oscillator for precise trade entry and exit signals.
Full Description:
Overview
This comprehensive trading indicator combines multiple proven technical analysis tools to identify high-probability trade setups with built-in risk management through automated take profit levels.
Key Features
📊 Triple SuperTrend System
Uses three SuperTrend indicators with different ATR periods (10, 11, 12) and multipliers (1.0, 2.0, 3.0)
Requires all three SuperTrends to align before generating signals
Reduces false signals and confirms trend strength
📈 Volume Oscillator Filter
Calculates volume momentum using short and long-term moving averages
Requires volume oscillator to be above 20% threshold for trade entries
Ensures trades only occur during periods of strong volume activity
Displayed as a clean histogram in separate pane (green = bullish, red = bearish)
🎯 RSI Confirmation
7-period RSI must be above 50 for buy signals
RSI must be below 50 for sell signals
Prevents counter-trend entries
🌊 200 DEMA Trend Filter
Double Exponential Moving Average acts as major trend filter
Optional: Only buy above DEMA, only sell below DEMA
Can be toggled on/off based on trading style
📐 Fibonacci Bollinger Bands
Uses 2.618 Fibonacci multiplier (Golden Ratio)
200-period basis
Price touching bands triggers exit signals
Helps identify overextended moves
Entry Signals
BUY Signal (Green Triangle):
All three SuperTrends turn bullish simultaneously
RSI > 50
Price above 200 DEMA (if filter enabled)
Volume Oscillator > 20%
SELL Signal (Red Triangle):
All three SuperTrends turn bearish simultaneously
RSI < 50
Price below 200 DEMA (if filter enabled)
Volume Oscillator > 20%
Exit Signals
Automatic Exits Occur When:
Any of the three SuperTrends changes direction
Price touches Fibonacci Bollinger Band (upper or lower)
Take Profit target is reached (1.5x the distance from entry to ST1)
Exit Labels:
🟠 "TP" = Take Profit hit
🟡 "X" = SuperTrend change or BB touch
Visual Elements
Orange Line: Dynamic take profit level based on SuperTrend distance
Green/Red Lines: Three SuperTrend levels (varying opacity)
Purple Bands: Fibonacci Bollinger Bands with shaded area
Blue Line: 200 DEMA
Background Tint: Green when all bullish, red when all bearish
Volume Histogram: Separate pane showing volume oscillator
Dashboard Display
Real-time information table showing:
Current position status (Long/Short/Flat)
RSI value
Volume Oscillator percentage
Overall trend direction
Alert Conditions
Set up custom alerts for:
Buy signals
Sell signals
Take profit hits
Exit signals
Customizable Parameters
SuperTrend Settings:
Individual ATR periods and multipliers for each SuperTrend
Default: ST1(10,1.0), ST2(11,2.0), ST3(12,3.0)
Volume Oscillator:
Short length (default: 5)
Long length (default: 10)
Threshold percentage (default: 20%)
Toggle filter on/off
Other Filters:
RSI length (default: 7)
DEMA length (default: 200)
Fib BB length and multiplier
Take profit multiplier (default: 1.5x)
Best Use Cases
Trend following strategies
Swing trading
Day trading on higher timeframes (15min+)
Works on all markets: Stocks, Forex, Crypto, Futures
Notes
This is an indicator, not an automated strategy
Signals are for informational purposes only
Always practice proper risk management
Test on historical data before live trading
Works best in trending markets
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Bull-Bear EfficiencyBull-Bear Efficiency
This indicator measures the directional efficiency of price movement across many historical entry points to estimate overall market bias. It is designed as a trend gauge rather than a timing signal.
Concept
For each historical bar (tau) and a chosen lookahead horizon (h), the script evaluates how efficiently price has traveled from that starting point to the endpoint. Efficiency is defined as the net price change divided by the total absolute movement that occurred along the path.
Formula:
E(tau,h) = ( Price - Price ) / ( Sum from i = tau+1 to tau+h of | Price - Price | )
This measures how "straight" the path was from the entry to the current bar:
If price moved steadily upward, the numerator and denominator are nearly equal, and E approaches +1 (efficient bullish trend).
If price moved steadily downward, E approaches -1 (efficient bearish trend).
If price chopped back and forth, the denominator grows faster than the numerator, and E approaches 0 (inefficient movement).
The algorithm computes this efficiency for many past starting points and multiple horizons, optionally normalizing by ATR to account for volatility. The efficiencies are then weighted by recency to emphasize more recent behavior.
From this, the script derives:
Bull = weighted average of positive efficiencies
Bear = weighted average of negative efficiencies (absolute value)
Net = Bull - Bear (net directional efficiency)
Interpretation
Bull, Bear, and Net quantify how coherently the market has been trending.
Bull near 1.0, Bear near 0.0, Net > 0 -> clean upward trends; long positions have been more efficient.
Bear near 1.0, Bull near 0.0, Net < 0 -> clean downward trends; short positions have been more efficient.
Bull and Bear both small or similar -> low-efficiency, range-bound environment.
Net therefore acts as a "trend coherence index" that measures whether price action is directionally organized or noisy.
Practical Use
Trend filter:
Apply trend-following systems only when Net is strongly positive or negative.
Avoid them when Net is near zero.
Regime change detection:
Crossings through zero often correspond to transitions between trending and ranging regimes.
Momentum loss detection:
If price makes new highs but Net or Bull weakens, it suggests trend exhaustion.
Settings Overview
Lookback: Number of historical bars considered as entry points (tau values).
Horizons: List of forward projection lengths (in bars) for measuring efficiency.
Recency Decay (lambda): Exponential weighting that emphasizes recent data.
Normalize by ATR: Adjusts "effort" to account for volatility changes.
Display Options: Toggle Bull, Bear, Net, or Signed Average (S). Customize line colors.
Notes
This indicator does not produce entry or exit signals.
It is a statistical tool that measures how efficiently price has trended over time.
High Net values indicate smooth, coherent trends.
Low or neutral Net values indicate noisy, directionless conditions.
Triple SuperTrend + RSI + Fib BBTriple SuperTrend + RSI + Fibonacci Bollinger Bands Strategy
📊 Overview
This advanced trading strategy combines the power of three SuperTrend indicators with RSI confirmation and Fibonacci Bollinger Bands to generate high-probability trade signals. The strategy is designed to capture strong trending moves while filtering out false signals through multi-indicator confluence.
🔧 Core Components
Three SuperTrend Indicators
The strategy uses three SuperTrend indicators with progressively longer periods and multipliers:
SuperTrend 1: 10-period ATR, 1.0 multiplier (fastest, most sensitive)
SuperTrend 2: 11-period ATR, 2.0 multiplier (medium sensitivity)
SuperTrend 3: 12-period ATR, 3.0 multiplier (slowest, most stable)
This layered approach ensures that all three timeframe perspectives align before generating a signal, significantly reducing false entries.
RSI Confirmation (7-period)
The Relative Strength Index acts as a momentum filter:
Long signals require RSI > 50 (bullish momentum)
Short signals require RSI < 50 (bearish momentum)
This prevents entries during weak or divergent price action.
Fibonacci Bollinger Bands (200, 2.618)
Uses a 200-period Simple Moving Average with 2.618 standard deviation bands (Fibonacci ratio). These bands serve dual purposes:
Visual representation of price extremes
Automatic exit trigger when price reaches overextended levels
📈 Entry Logic
LONG Entry (BUY Signal)
A LONG position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn green (bullish)
RSI(7) is above 50
This is the first bar where all conditions align (no repainting)
SHORT Entry (SELL Signal)
A SHORT position is opened when ALL of the following conditions are met simultaneously:
All three SuperTrend indicators turn red (bearish)
RSI(7) is below 50
This is the first bar where all conditions align (no repainting)
🚪 Exit Logic
Positions are automatically closed when ANY of these conditions occur:
SuperTrend Color Change: Any one of the three SuperTrend indicators changes direction
Fibonacci BB Touch: Price reaches or exceeds the upper or lower Fibonacci Bollinger Band (2.618 standard deviations)
This dual-exit approach protects profits by:
Exiting quickly when trend momentum shifts (SuperTrend change)
Taking profits at statistical price extremes (Fib BB touch)
🎨 Visual Features
Signal Arrows
Green Up Arrow (BUY): Appears below the bar when long entry conditions are met
Red Down Arrow (SELL): Appears above the bar when short entry conditions are met
Yellow Down Arrow (EXIT): Appears above the bar when exit conditions are met
Background Coloring
Light Green Tint: All three SuperTrends are bullish (uptrend environment)
Light Red Tint: All three SuperTrends are bearish (downtrend environment)
SuperTrend Lines
Three colored lines plotted with varying opacity:
Solid line (ST1): Most responsive to price changes
Semi-transparent (ST2): Medium-term trend
Most transparent (ST3): Long-term trend structure
Dashboard
Real-time information panel showing:
Individual SuperTrend status (UP/DOWN)
Current RSI value and color-coded status
Current position (LONG/SHORT/FLAT)
Net Profit/Loss
⚙️ Customizable Parameters
SuperTrend Settings
ATR periods for each SuperTrend (default: 10, 11, 12)
Multipliers for each SuperTrend (default: 1.0, 2.0, 3.0)
RSI Settings
RSI length (default: 7)
RSI source (default: close)
Fibonacci Bollinger Bands
BB length (default: 200)
BB multiplier (default: 2.618)
Strategy Options
Enable/disable long trades
Enable/disable short trades
Initial capital
Position sizing
Commission settings
💡 Strategy Philosophy
This strategy is built on the principle of confluence trading - waiting for multiple independent indicators to align before taking a position. By requiring three SuperTrend indicators AND RSI confirmation, the strategy filters out the majority of low-probability setups.
The multi-timeframe SuperTrend approach ensures that short-term, medium-term, and longer-term trends are all in agreement, which typically occurs during strong, sustainable price moves.
The exit strategy is equally important, using both trend-following logic (SuperTrend changes) and mean-reversion logic (Fibonacci BB touches) to adapt to different market conditions.
📊 Best Use Cases
Trending Markets: Works best in markets with clear directional bias
Higher Timeframes: Designed for 15-minute to daily charts
Volatile Assets: SuperTrend indicators excel in assets with clear trends
Swing Trading: Hold times typically range from hours to days
⚠️ Important Notes
No Repainting: All signals are confirmed and will not change on historical bars
One Signal Per Setup: The strategy prevents duplicate signals on consecutive bars
Exit Protection: Always exits before potentially taking an opposite position
Visual Clarity: All three SuperTrend lines are visible simultaneously for transparency
🎯 Recommended Settings
While default parameters are optimized for general use, consider:
Crypto/Volatile Markets: May benefit from slightly higher multipliers
Forex: Default settings work well for major pairs
Stocks: Consider longer BB periods (250-300) for daily charts
Lower Timeframes: Reduce all periods proportionally for scalping
📝 Alerts
Built-in alert conditions for:
BUY signal triggered
SELL signal triggered
EXIT signal triggered
Set up notifications to never miss a trade opportunity!
Disclaimer: This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always backtest thoroughly and practice proper risk management before live trading.
Adaptive CE-VWAP Breakout Framework [KedArc Quant]📘 Description
A structured framework that unites three complementary systems into one charting engine:
>Chandelier Exit (CE) – ATR-based trailing logic that defines trend direction, stop placement, and risk/reward overlays.
>Swing-Anchored VWAP (SWAV) – a dynamically anchored VWAP that re-starts from each confirmed swing and adapts its smoothness to volatility.
>Pivot S/R with Volume Breaks – confirmed horizontal levels with alerts when broken on expanding volume.
This script builds a single workflow for bias → trigger → management>without mixing unrelated indicators. Each module is internally linked rather than layered cosmetically, making it a true analytical framework—not.
🙏 Acknowledgment
Special thanks to Dynamic Swing Anchored VWAP by @Zeiierman, whose swing-anchoring concept inspired a part of the SWAV module’s implementation and adaptation logic.
Support and Resistance Levels with Breaks by @luxalgo for S/R breakout logic.
🎯 How this helps traders
>Trend clarity – CE color-codes direction and provides evolving stops.
>Context value – SWAV traces adaptive mean paths so traders see where price is “heavy” or “light.”
>Action filter – Pivot+volume logic highlights true structural breaks, filtering false moves.
>Discipline tool – Optional R:R boxes visualize risk and target zones to enforce planning.
🧩 Entry / Exit guidelines (for study purposes only)
Bias Use CE direction: green = long bias · red = short bias
Entry
1. Breakout method>– Trade in CE direction when a pivot level breaks on valid volume.
2. VWAP confirmation>– Prefer breaks occurring around the nearest SWAV path (fair-value cross or re-test).
Exit
>Stop = CE line / recent swing HL / ATR × (multiplier)
>Target = R-multiple × risk (default 2 R)
>Optional live update keeps SL/TP aligned with current CE state.
🧮 Core formula concepts
>ATR Stop: `Stop = High/Low – ATR × multiplier`
>VWAP calc: `Σ(price × vol) / Σ(vol)` anchored at swing pivot, adapted by APT (Adaptive Price Tracking) ratio ∝ ATR volatility.
>Volume oscillator: `100 × (EMA₅ – EMA₁₀)/EMA₁₀`; valid break when > threshold %.
⚙️ Input configuration (high-level)
Master Controls
• Show CE / SWAV modules • Theme & Fill opacity
CE Section
• ATR period & multiplier • Use Close for extremums
• Show buy/sell labels • Await bar confirmation
• Risk-Reward overlay: R-multiple, Stop basis (CE/Swing/ATR×), Live update toggle
SWAV Section
• Swing period • Adaptive Price Tracking length • Volatility bias (ATR-based adaptation) • Line width
Pivot & Volume Breaks
• Left/Right bar windows • Volume threshold % • Show Break labels and alerts
⏱ Best timeframes
>Intraday: 5 m – 30 m for breakout confirmation
>Swing: 1 h – 4 h for trend context
Settings scale with instrument volatility—adjust ATR period and volume threshold to match liquidity.
📘 Glossary
>ATR: Average True Range (volatility metric)
>CE: Chandelier Exit (trailing stop/trend filter)
>SWAV: Swing-Anchored VWAP (anchored mean price path)
>Pivot H/L: Confirmed local extrema using left/right bar windows
>R-multiple: Profit target as a multiple of initial risk
💬 FAQ
Q: Does it repaint? A: No—pivots wait for confirmation and VWAP updates forward-only.
Q: Can modules be disabled? A: Yes—each section has its own toggle.
Q: Can it trade automatically? A: This is an indicator/study, not an auto-strategy.
Q: Is this financial advice? A: No—educational use only.
⚠️ Disclaimer
This script is for educational and analytical purposes only.
It is not financial advice. Trading involves risk of loss. Past performance does not guarantee future results. Always apply sound risk management.
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision
Overview
The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise.
Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier.
Theoretical Foundation
The traditional RSI measures relative strength by comparing average gains and losses, but suffers from:
Lag in trend recognition : Signals often arrive after momentum has shifted.
Noise sensitivity : High-frequency price movements generate unreliable crossovers.
Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns.
The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into:
Level (Lₜ) : Represents the smoothed central tendency of RSI.
Trend (Tₜ) : Captures rate-of-change in smoothed momentum.
Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum.
By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted.
How It Works
The Enhanced Holt-Winters RSI builds its signal framework through several layers:
1. Base RSI Calculation
Computes standard RSI over the selected period as the primary momentum input.
2. Triple Exponential Smoothing (Holt-Winters)
The RSI is smoothed recursively to extract underlying momentum structure:
Level, trend, and seasonal components are combined to produce a smoothed RSI.
This internal smoothing reduces lag and enhances signal reliability.
3. Momentum Analysis
Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength.
4. Volume Confirmation (Optional)
Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts.
5. Visual Output
Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions.
Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context.
Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones.
Interpretation
The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action:
Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity.
Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness.
Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum.
High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits.
Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise.
By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data.
Strategy Integration
The Enhanced Holt-Winters RSI can be applied across trading styles:
Trend Following
Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction.
Strong slope in the smoothed RSI signals trend continuation.
Reversal Trading
Look for RSI extremes with momentum shifts and strong signal markers.
Compression in oscillator values often precedes reversal setups.
Breakout Detection
Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions.
Multi-Timeframe Confluence
Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics.
Technical Implementation Details
Input Source : Close, open, high, low, or price.
Smoothing : Holt-Winters triple exponential smoothing applied to RSI.
Parameters :
Level (α) : Controls smoothing of RSI.
Trend (β) : Adjusts responsiveness to momentum changes.
Seasonal Length : Defines cycles for short-term adjustments.
Delta Smoothing : Reduces choppiness in smoothed RSI difference.
Outputs :
Smoothed RSI
Colored candles and oscillator panel
Buy/Sell signal markers (with optional strength filtering)
Volume Filtering : Optional threshold to confirm signals.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters.
Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions.
Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals.
Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations.
Timeframe Optimization:
Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals.
Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones.
Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals.
Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks.
Integration Guidelines
Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation.
Use volume and signal strength markers to filter low-conviction trades.
Slope, color, and signal alignment can guide entry, stop placement, and scaling.
Disclaimer
The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
T3 ATR [DCAUT]█ T3 ATR
📊 ORIGINALITY & INNOVATION
The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output.
This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation.
The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations.
📐 MATHEMATICAL FOUNDATION
The T3 ATR calculation process involves two distinct stages:
Stage 1: True Range Calculation
The True Range (TR) is calculated using the standard formula:
TR = max(high - low, |high - close |, |low - close |)
This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves.
Stage 2: T3 Smoothing Application
The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession:
First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period)
Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period)
Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period)
Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter:
a = VF / 2
c1 = -a³
c2 = 3a² + 3a³
c3 = -6a² - 3a - 3a³
c4 = 1 + 3a + a³ + 3a²
The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness:
Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise
Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag
📊 COMPREHENSIVE SIGNAL ANALYSIS
Volatility Level Interpretation:
High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events
Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods
Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk
Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies
Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies
Volume Factor Impact on Signals:
Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations
Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading
High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis
🎯 STRATEGIC APPLICATIONS
Position Sizing Strategy:
Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience)
Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values)
Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR
Calculate position size: Position Size = (Account × Risk %) / Stop Distance
Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point
Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses)
Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading
Dynamic Stop-Loss Placement:
Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR)
For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value)
For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value)
Trail stop-losses by recalculating based on current T3 ATR as the trade progresses
Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops
Market Regime Identification:
Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA)
High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets
Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure
Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion
Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early
Risk Management Implementation:
Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital)
For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR)
When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position)
When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position)
This approach maintains constant dollar risk per trade regardless of market volatility changes
Use consistent volume factor settings across all positions to ensure uniform risk measurement
📋 DETAILED PARAMETER CONFIGURATION
ATR Length Parameter:
Default Setting: 14 periods
This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes
Selection Principles:
Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings
Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes
The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument
Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods
Practical Approach:
Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions
If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes
If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response
Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range
Test different periods using historical data for your specific instrument and strategy before committing to live trading
T3 Volume Factor Parameter:
Default Setting: 0.7
This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles
Understanding the Volume Factor:
Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering
Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly
The trade-off is between immediacy and stability - there is no universally optimal setting
Selection Principles:
Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF
Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response
Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay
Practical Adjustment Guidelines:
Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions
If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing
If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response
Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice
Test adjustments in simulation or paper trading before applying to live positions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments.
Signal Stability:
Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations.
Comparison with Standard ATR:
Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement
Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments
Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy
Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications
Suitable Use Cases:
T3 ATR is well-suited for the following scenarios:
Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions
Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading)
Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions
Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments
Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection
Known Limitations:
Like all technical indicators, T3 ATR has limitations that users should understand:
Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty
Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions
Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed
Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds
Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis
Performance Expectations:
T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied:
It can help reduce position risk during volatile periods through appropriate position sizing
It can help identify optimal times for more aggressive position sizing during stable periods
It can improve stop-loss placement by adapting to current market conditions
It can assist in strategy selection by identifying volatility regimes
However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology.
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms.
Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
Short-Term Capitulation Oscillator (STCO, Diodato 2019)Description:
This script is a faithful implementation of the Short-Term Capitulation Oscillator (STCO) from Chris Diodato's 2019 CMT paper, "Making The Most Of Panic". It's a tactical breadth and volume oscillator designed to "fish for market bottoms" by identifying short-term investor capitulation.
What It Is
The STCO combines the 10-day moving averages of NYSE up-volume and advancing issues. It measures the ratio of advancing momentum (in both volume and number of issues) relative to the total traded momentum. The result is a raw, un-normalized oscillator that typically ranges from 0 to 200.
How to Interpret
The STCO is a tactical tool for identifying near-term oversold conditions and potential bounces.
Low Readings: Indicate that sellers have likely exhausted themselves in the short term, creating a potential entry point for a bounce. The paper found that readings below 90, 85, and 80 were often followed by strong market performance over the next 5-20 days.
Overbought/Oversold Lines: Use the customizable overbought/oversold lines to define your own capitulation zones and potential entry areas.
Settings
Data Sources: Allows toggling the use of "Unchanged" issues/volume data.
Thresholds: You can set the overbought and oversold levels based on the paper's research or your own testing.
Adaptive Trend Breaks Adaptive Trend Breaks
## WHAT IT DOES
This script is a modified and enhanced version of "Trendline Breakouts With Targets" concept by ChartPrime.
Adaptive Trend Breaks (ATB) is a trendline breakout system optimized for scalping liquid futures contracts. The indicator automatically draws dynamic support and resistance trendlines based on pivot points, then generates trade signals when price breaks through these levels with confirmation filters. It includes automated target and stop-loss placement with real-time P&L tracking in dollars.
## HOW IT WORKS
**Trendline Detection Method:**
The indicator uses pivot high/low detection to identify significant price turning points. When a new pivot forms, it calculates the slope between consecutive pivots to draw dynamic trendlines. These lines extend forward based on the established trend angle, creating actionable support and resistance zones.
**Band System:**
Around each trendline, the script creates a "band" using a volatility-adjusted calculation: `ATR(14) * 0.2 * bandwidth multiplier / 2`. This adaptive band accounts for current market conditions - wider during volatile periods, tighter during quiet markets.
**Breakout Logic:**
A breakout signal triggers when:
1. Price closes beyond the trendline + band zone
2. Volume exceeds the 20-period moving average by your set multiplier (default 1.2x)
3. Price is within Regular Trading Hours (9:30-16:00 EST) if session filter enabled
4. Current ATR meets minimum volatility threshold (prevents trading dead markets)
**Target & Stop Calculation:**
Upon breakout confirmation:
- **Entry**: Trendline breach point
- **Target**: Entry ± (bandwidth × target multiplier) - default 8x for quick scalps
- **Stop**: Entry ± (bandwidth × stop multiplier) - default 8x for 1:1 risk/reward
- Multipliers adjust automatically to market volatility through the ATR-based band
**P&L Conversion:**
The script converts point movements to dollars using:
```
Dollar P&L = (Price Points × Contract Point Value × Quantity)
```
For example, a 10-point NQ move with 2 contracts = 10 × $20 × 2 = $400
## HOW TO USE IT
**Setup:**
1. Select your instrument (NQ/ES/YM/RTY) - point values auto-configure
2. Set contract quantity for accurate dollar P&L
3. Choose pivot period (lower = more signals but more noise, default 5 for scalping)
4. Adjust bandwidth multiplier if trendlines are too tight/loose (1-5 range)
**Filters Configuration:**
- **Volume Filter**: Requires breakout volume > moving average × multiplier. Increase multiplier (1.5-2.0) for higher conviction trades
- **Session Filter**: Enable to trade only RTH. Disable for 24-hour trading
- **ATR Filter**: Prevents signals during low volatility. Increase minimum % for more active markets only
**Risk Management:**
- Set target/stop multipliers based on your risk tolerance
- 8x bandwidth = approximately 1:1 risk/reward for most liquid futures
- Enable trailing stops for trend-following approach (moves stop to protect profits)
- Adjust line length to see targets further into the future
**Statistics Table:**
- Choose timeframe to analyze: all-time, today, this week, custom days
- Monitor win rate, profit factor, and net P&L in dollars
- Track long vs short performance separately
- See real-time unrealized P&L on active trades
**Reading Signals:**
- **Green triangle below bar** = Long breakout (resistance broken)
- **Red triangle above bar** = Short breakout (support broken)
- **White dashed line** = Entry price
- **Orange line** = Take profit target with dollar value
- **Red line** = Stop loss with dollar value
- **Green checkmark (✓)** = Target hit, winning trade
- **Red X (✗)** = Stop hit, losing trade
## WHAT IT DOES NOT DO
**Limitations to Understand:**
- Does not predict future trendline formations - it reacts to breakouts after they occur
- Historical trendlines disappear after breakout (not kept on chart for clarity)
- Requires sufficient volatility - may not signal in extremely quiet markets
- Volume filter requires exchange volume data (not available on all symbols)
- Statistics are indicator-based simulations, not actual trading results
- Does not account for slippage, commissions, or order fills
## BEST PRACTICES
**Recommended Settings by Market:**
- **NQ (Nasdaq)**: Default settings work well, consider volume multiplier 1.3-1.5
- **ES (S&P 500)**: Slightly slower, try period 7-8, volume 1.2
- **YM (Dow)**: Lower volatility, reduce bandwidth to 1.5-2
- **RTY (Russell)**: Higher volatility, increase bandwidth to 3-4
**Risk Management:**
- Never risk more than 2-3% of account per trade
- Use contract quantity calculator: Max Risk $ ÷ (Stop Distance × Point Value)
- Start with 1 contract while learning the system
- Backtest your specific timeframe and instrument before live trading
**Optimization Tips:**
- Increase pivot period (7-10) for fewer but higher-quality signals
- Raise volume multiplier (1.5-2.0) in choppy markets
- Lower target/stop multipliers (5-6x) for tighter profit taking
- Use trailing stops in strong trending conditions
- Disable session filter for overnight gaps and Asia session moves
## TECHNICAL DETAILS
**Key Calculations:**
- Pivot Detection: `ta.pivothigh(high, period, period/2)` and `ta.pivotlow(low, period, period/2)`
- Slope Calculation: `(newPivot - oldPivot) / (newTime - oldTime)`
- Adaptive Band: `min(ATR(14) * 0.2, close * 0.002) * multiplier / 2`
- Breakout Confirmation: Price crosses trendline + 10% of band threshold
**Data Requirements:**
- Minimum bars in view: 500 for proper pivot calculation
- Volume data required for volume filter accuracy
- Intraday timeframes recommended (1min - 15min) for scalping
- Works on any timeframe but optimized for fast execution
**Performance Metrics:**
All statistics calculate based on indicator signals:
- Tracks every signal as a trade from entry to TP/SL
- P&L in actual contract dollar values
- Win rate = (Winning trades / Total trades) × 100
- Profit factor = Gross profit / Gross loss
- Separates long/short performance for bias analysis
## IDEAL FOR
- Futures scalpers and day traders
- Traders who prefer visual trendline breakouts
- Those wanting automated TP/SL placement
- Traders tracking performance in dollar terms
- Multiple timeframe analysis (compare 1min vs 5min signals)
## NOT SUITABLE FOR
- Swing trading (targets too close)
- Stocks/forex without modifying point values
- Extremely low timeframes (<30 seconds) - too much noise
- Markets without volume data if using volume filter
- Illiquid contracts (signals may not execute at shown prices)
---
**Settings Summary:**
- Core: Period, bandwidth, extension, trendline style
- Filters: Volume, RTH session, ATR volatility
- Risk: R:R ratio, target/stop multipliers, trailing stop
- Display: Stats table position, size, colors
- Stats: Timeframe selection (all-time to custom days)
**License:** This indicator is published open-source under Mozilla Public License 2.0. You may use and modify the code with proper attribution.
**Disclaimer:** This indicator is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and test thoroughly before live trading.
---
## CREDITS & ATTRIBUTION
This script builds upon the "Trendline Breakouts With Targets" concept by ChartPrime with significant enhancements:
**Major Improvements Added:**
- **Futures-Specific Calculations**: Automated dollar P&L conversion using actual contract point values (NQ=$20, ES=$50, YM=$5, RTY=$50)
- **Advanced Statistics Engine**: Comprehensive performance tracking with customizable timeframe analysis (today, week, month, custom ranges)
- **Multi-Layer Filtering System**: Volume confirmation, RTH session filter, and ATR volatility filter to reduce false signals
- **Professional Trade Management**: Enhanced visual trade tracking with separate TP/SL lines, dollar value labels, and optional trailing stops
- **Optimized for Scalping**: Faster pivot periods (5 vs 10), tighter bands, and reduced extension bars for quick entries
Original trendline detection methodology by ChartPrime - used with modification under Mozilla Public License 2.0.
EMA+SuperThis comprehensive indicator combines multiple powerful trend-following tools into a single chart overlay, designed for traders seeking clear entry and exit signals with market context.
Features:
Exponential Moving Averages (EMAs): Five EMAs (9, 21, 50, 100, 200) plotted for multi-timeframe trend analysis and dynamic support/resistance.
Supertrend: Classic volatility-based trend indicator highlighting bullish and bearish phases with dynamic colored bands.
NovaWave Cloud: Custom trend cloud created using fast and slow EMAs plus a signal moving average for visualizing market momentum shifts.
Displaced Moving Averages (20, 50, 200 DMA): Simple moving averages with optional displacement to assess lagged trend confirmation and cyclical ranges.
Buy/Sell Signal Labels: Automated labels show “BUY” when the 9 EMA crosses above the 21 EMA, and “SELL” when the 9 EMA crosses below the 21 EMA, providing timely entry/exit cues.
Intended Use:
Perfect for swing and position traders, this indicator combines trend confirmation and actionable signals to help identify sustained price moves in various markets. It works well on multiple timeframes, offering a clear visual framework for market direction and trading decisions.
How to Use:
Look for BUY labels for potential long entry opportunities when momentum shifts bullish.
Look for SELL labels as potential exit or short signals when a bearish momentum crossover occurs.
Use the overlaying EMAs, Supertrend, and cloud as additional confirmation for trend strength and timing.
This all-in-one tool is ideal for traders who want a unified view of trend dynamics combined with simple, clear signals without needing multiple separate indicators.
Feel free to modify or expand based on your style. Let me know if you want a shorter summary or technical details added!
EMA Ribbon Reversal + Retest Signal🧩 1. Core Concept
This indicator combines EMA ribbon trend detection, reversal identification, and EMA144/233 retest confirmation to capture structured market transitions.
It’s designed to:
Detect trend changes when all EMAs align.
Confirm entry zones when price retests major EMAs (144, 233).
Avoid false signals through compression, volume, and body strength filters.
🧠 2. How to Read the Indicator on Chart
🟢 BUY Sequence (Bullish Scenario)
Reversal Detected → Candle closes above all EMAs (label: “BUY”).
Retest Phase → Price pulls back to EMA144 or EMA233 but stays above (label: “Retest BUY Strong/Weak”).
Confirmation → A bullish candle forms with strong volume — continuation likely.
Trend continues upward until opposite “SELL Reversal” occurs.
🔴 SELL Sequence (Bearish Scenario)
Reversal Detected → Candle closes below all EMAs (label: “SELL”).
Retest Phase → Price retests EMA144/233 from below but fails to break up (label: “Retest SELL Strong/Weak”).
Confirmation → Bearish candle + strong volume — continuation likely.
Downtrend continues until new “BUY Reversal” appears.
📈 3. How to Use in Real Trading
Step 1 — Identify Market Context
Use higher timeframe (e.g., 1H or 4H) to confirm main trend via EMA144 & 233.
Avoid entries during flat EMA ribbons (compression zones).
Step 2 — Watch for Reversal Signal
“BUY” or “SELL” label = early trend shift.
Wait for at least one candle close after the reversal for confirmation.
Step 3 — Wait for Retest Confirmation
Price should touch or bounce near EMA144/233.
“Retest BUY/SELL Strong” = higher probability entry zone.
Step 4 — Filter by Volume
Strong signals appear only if volume > SMA(volume) × multiplier.
Low-volume retests are weaker and more likely to fail.
Step 5 — Manage Trades
Enter on confirmed “Strong” retests.
Use EMA233 or ATR-based stop loss.
Exit on opposite reversal or loss of trend alignment.
💡 4. Reading Behavior Tips
EMA compression low (<0.2) → sideways market → avoid entries.
Strong retest + high volume → high probability continuation.
Weak retest or compressed EMA → caution; may be fakeout.
EMA144 & 233 cross → long-term trend shift zone.
Spaced signals = stable trend; clustered signals = volatility zone.
🔔 5. Using Alerts
You can set TradingView alerts for:
BUY/SELL Reversal: Trend direction change
Retest BUY/SELL Strong: Confirmation entry
BUY/SELL Breakout: First strong test after new reversal
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
MACD Enhanced [DCAUT]█ MACD Enhanced
📊 ORIGINALITY & INNOVATION
The MACD Enhanced represents a significant improvement over traditional MACD implementations. While Gerald Appel's original MACD from the 1970s was limited to exponential moving averages (EMA), this enhanced version expands algorithmic options by supporting 21 different moving average calculations for both the main MACD line and signal line independently.
This improvement addresses an important limitation of traditional MACD: the inability to adapt the indicator's mathematical foundation to different market conditions. By allowing traders to select from algorithms ranging from simple moving averages (SMA) for stability to advanced adaptive filters like Kalman Filter for noise reduction, this implementation changes MACD from a fixed-algorithm tool into a flexible instrument that can be adjusted for specific market environments and trading strategies.
The enhanced histogram visualization system uses a four-color gradient that helps communicate momentum strength and direction more clearly than traditional single-color histograms.
📐 MATHEMATICAL FOUNDATION
The core calculation maintains the proven MACD formula: Fast MA(source, fastLength) - Slow MA(source, slowLength), but extends it with algorithmic flexibility. The signal line applies the selected smoothing algorithm to the MACD line over the specified signal period, while the histogram represents the difference between MACD and signal lines.
Available Algorithms:
The implementation supports a comprehensive spectrum of technical analysis algorithms:
Basic Averages: SMA (arithmetic mean), EMA (exponential weighting), RMA (Wilder's smoothing), WMA (linear weighting)
Advanced Averages: HMA (Hull's low-lag), VWMA (volume-weighted), ALMA (Arnaud Legoux adaptive)
Mathematical Filters: LSMA (least squares regression), DEMA (double exponential), TEMA (triple exponential), ZLEMA (zero-lag exponential)
Adaptive Systems: T3 (Tillson T3), FRAMA (fractal adaptive), KAMA (Kaufman adaptive), MCGINLEY_DYNAMIC (reactive to volatility)
Signal Processing: ULTIMATE_SMOOTHER (low-pass filter), LAGUERRE_FILTER (four-pole IIR), SUPER_SMOOTHER (two-pole Butterworth), KALMAN_FILTER (state-space estimation)
Specialized: TMA (triangular moving average), LAGUERRE_BINOMIAL_FILTER (binomial smoothing)
Each algorithm responds differently to price action, allowing traders to match the indicator's behavior to market characteristics: trending markets benefit from responsive algorithms like EMA or HMA, while ranging markets require stable algorithms like SMA or RMA.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Histogram Interpretation:
Positive Values: Indicate bullish momentum when MACD line exceeds signal line, suggesting upward price pressure and potential buying opportunities
Negative Values: Reflect bearish momentum when MACD line falls below signal line, indicating downward pressure and potential selling opportunities
Zero Line Crosses: MACD crossing above zero suggests transition to bullish bias, while crossing below indicates bearish bias shift
Momentum Changes: Rising histogram (regardless of positive/negative) signals accelerating momentum in the current direction, while declining histogram warns of momentum deceleration
Advanced Signal Recognition:
Divergences: Price making new highs/lows while MACD fails to confirm often precedes trend reversals
Convergence Patterns: MACD line approaching signal line suggests impending crossover and potential trade setup
Histogram Peaks: Extreme histogram values often mark momentum exhaustion points and potential reversal zones
🎯 STRATEGIC APPLICATIONS
Comprehensive Trend Confirmation Strategies:
Primary Trend Validation Protocol:
Identify primary trend direction using higher timeframe (4H or Daily) MACD position relative to zero line
Confirm trend strength by analyzing histogram progression: consistent expansion indicates strong momentum, contraction suggests weakening
Use secondary confirmation from MACD line angle: steep angles (>45°) indicate strong trends, shallow angles suggest consolidation
Validate with price structure: trending markets show consistent higher highs/higher lows (uptrend) or lower highs/lower lows (downtrend)
Entry Timing Techniques:
Pullback Entries in Uptrends: Wait for MACD histogram to decline toward zero line without crossing, then enter on histogram expansion with MACD line still above zero
Breakout Confirmations: Use MACD line crossing above zero as confirmation of upward breakouts from consolidation patterns
Continuation Signals: Look for MACD line re-acceleration (steepening angle) after brief consolidation periods as trend continuation signals
Advanced Divergence Trading Systems:
Regular Divergence Recognition:
Bullish Regular Divergence: Price creates lower lows while MACD line forms higher lows. This pattern is traditionally considered a potential upward reversal signal, but should be combined with other confirmation signals
Bearish Regular Divergence: Price makes higher highs while MACD shows lower highs. This pattern is traditionally considered a potential downward reversal signal, but trading decisions should incorporate proper risk management
Hidden Divergence Strategies:
Bullish Hidden Divergence: Price shows higher lows while MACD displays lower lows, indicating trend continuation potential. Use for adding to existing long positions during pullbacks
Bearish Hidden Divergence: Price creates lower highs while MACD forms higher highs, suggesting downtrend continuation. Optimal for adding to short positions during bear market rallies
Multi-Timeframe Coordination Framework:
Three-Timeframe Analysis Structure:
Primary Timeframe (Daily): Determine overall market bias and major trend direction. Only trade in alignment with daily MACD direction
Secondary Timeframe (4H): Identify intermediate trend changes and major entry opportunities. Use for position sizing decisions
Execution Timeframe (1H): Precise entry and exit timing. Look for MACD line crossovers that align with higher timeframe bias
Timeframe Synchronization Rules:
Daily MACD above zero + 4H MACD rising = Strong uptrend context for long positions
Daily MACD below zero + 4H MACD declining = Strong downtrend context for short positions
Conflicting signals between timeframes = Wait for alignment or use smaller position sizes
1H MACD signals only valid when aligned with both higher timeframes
Algorithm Considerations by Market Type:
Trending Markets: Responsive algorithms like EMA, HMA may be considered, but effectiveness should be tested for specific market conditions
Volatile Markets: Noise-reducing algorithms like KALMAN_FILTER, SUPER_SMOOTHER may help reduce false signals, though results vary by market
Range-Bound Markets: Stability-focused algorithms like SMA, RMA may provide smoother signals, but individual testing is required
Short Timeframes: Low-lag algorithms like ZLEMA, T3 theoretically respond faster but may also increase noise
Important Note: All algorithm choices and parameter settings should be thoroughly backtested and validated based on specific trading strategies, market conditions, and individual risk tolerance. Different market environments and trading styles may require different configuration approaches.
📋 DETAILED PARAMETER CONFIGURATION
Comprehensive Source Selection Strategy:
Price Source Analysis and Optimization:
Close Price (Default): Most commonly used, reflects final market sentiment of each period. Best for end-of-day analysis, swing trading, daily/weekly timeframes. Advantages: widely accepted standard, good for backtesting comparisons. Disadvantages: ignores intraday price action, may miss important highs/lows
HL2 (High+Low)/2: Midpoint of the trading range, reduces impact of opening gaps and closing spikes. Best for volatile markets, gap-prone assets, forex markets. Calculation impact: smoother MACD signals, reduced noise from price spikes. Optimal when asset shows frequent gaps, high volatility during specific sessions
HLC3 (High+Low+Close)/3: Weighted average emphasizing the close while including range information. Best for balanced analysis, most asset classes, medium-term trading. Mathematical effect: 33% weight to high/low, 33% to close, provides compromise between close and HL2. Use when standard close is too noisy but HL2 is too smooth
OHLC4 (Open+High+Low+Close)/4: True average of all price points, most comprehensive view. Best for complete price representation, algorithmic trading, statistical analysis. Considerations: includes opening sentiment, smoothest of all options but potentially less responsive. Optimal for markets with significant opening moves, comprehensive trend analysis
Parameter Configuration Principles:
Important Note: Different moving average algorithms have distinct mathematical characteristics and response patterns. The same parameter settings may produce vastly different results when using different algorithms. When switching algorithms, parameter settings should be re-evaluated and tested for appropriateness.
Length Parameter Considerations:
Fast Length (Default 12): Shorter periods provide faster response but may increase noise and false signals, longer periods offer more stable signals but slower response, different algorithms respond differently to the same parameters and may require adjustment
Slow Length (Default 26): Should maintain a reasonable proportional relationship with fast length, different timeframes may require different parameter configurations, algorithm characteristics influence optimal length settings
Signal Length (Default 9): Shorter lengths produce more frequent crossovers but may increase false signals, longer lengths provide better signal confirmation but slower response, should be adjusted based on trading style and chosen algorithm characteristics
Comprehensive Algorithm Selection Framework:
MACD Line Algorithm Decision Matrix:
EMA (Standard Choice): Mathematical properties: exponential weighting, recent price emphasis. Best for general use, traditional MACD behavior, backtesting compatibility. Performance characteristics: good balance of speed and smoothness, widely understood behavior
SMA (Stability Focus): Equal weighting of all periods, maximum smoothness. Best for ranging markets, noise reduction, conservative trading. Trade-offs: slower signal generation, reduced sensitivity to recent price changes
HMA (Speed Optimized): Hull Moving Average, designed for reduced lag. Best for trending markets, quick reversals, active trading. Technical advantage: square root period weighting, faster trend detection. Caution: can be more sensitive to noise
KAMA (Adaptive): Kaufman Adaptive MA, adjusts smoothing based on market efficiency. Best for varying market conditions, algorithmic trading. Mechanism: fast smoothing in trends, slow smoothing in sideways markets. Complexity: requires understanding of efficiency ratio
Signal Line Algorithm Optimization Strategies:
Matching Strategy: Use same algorithm for both MACD and signal lines. Benefits: consistent mathematical properties, predictable behavior. Best when backtesting historical strategies, maintaining traditional MACD characteristics
Contrast Strategy: Use different algorithms for optimization. Common combinations: MACD=EMA, Signal=SMA for smoother crossovers, MACD=HMA, Signal=RMA for balanced speed/stability, Advanced: MACD=KAMA, Signal=T3 for adaptive behavior with smooth signals
Market Regime Adaptation: Trending markets: both fast algorithms (EMA/HMA), Volatile markets: MACD=KALMAN_FILTER, Signal=SUPER_SMOOTHER, Range-bound: both slow algorithms (SMA/RMA)
Parameter Sensitivity Considerations:
Impact of Parameter Changes:
Length Parameter Sensitivity: Small parameter adjustments can significantly affect signal timing, while larger adjustments may fundamentally change indicator behavior characteristics
Algorithm Sensitivity: Different algorithms produce different signal characteristics. Thoroughly test the impact on your trading strategy before switching algorithms
Combined Effects: Changing multiple parameters simultaneously can create unexpected effects. Recommendation: adjust parameters one at a time and thoroughly test each change
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Response Characteristics by Algorithm:
Fastest Response: ZLEMA, HMA, T3 - minimal lag but higher noise
Balanced Performance: EMA, DEMA, TEMA - good trade-off between speed and stability
Highest Stability: SMA, RMA, TMA - reduced noise but increased lag
Adaptive Behavior: KAMA, FRAMA, MCGINLEY_DYNAMIC - automatically adjust to market conditions
Noise Filtering Capabilities:
Advanced algorithms like KALMAN_FILTER and SUPER_SMOOTHER help reduce false signals compared to traditional EMA-based MACD. Noise-reducing algorithms can provide more stable signals in volatile market conditions, though results will vary based on market conditions and parameter settings.
Market Condition Adaptability:
Unlike fixed-algorithm MACD, this enhanced version allows real-time optimization. Trending markets benefit from responsive algorithms (EMA, HMA), while ranging markets perform better with stable algorithms (SMA, RMA). The ability to switch algorithms without changing indicators provides greater flexibility.
Comparative Performance vs Traditional MACD:
Algorithm Flexibility: 21 algorithms vs 1 fixed EMA
Signal Quality: Reduced false signals through noise filtering algorithms
Market Adaptability: Optimizable for any market condition vs fixed behavior
Customization Options: Independent algorithm selection for MACD and signal lines vs forced matching
Professional Features: Advanced color coding, multiple alert conditions, comprehensive parameter control
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always combine with proper risk management and thorough strategy testing.
Aladin Pair Trading System v1Aladin Pair Trading System v1
What is This Indicator?
The Aladin Pair Trading System is a sophisticated tool designed to help traders identify profitable opportunities by comparing two related stocks that historically move together. Think of it as finding when one twin is running ahead or lagging behind the other - these moments often present trading opportunities as they tend to return to moving together.
Who Should Use This?
Beginners: Learn about statistical arbitrage and pair trading
Intermediate Traders: Execute mean-reversion strategies with confidence
Advanced Traders: Fine-tune parameters for optimal pair relationships
Portfolio Managers: Implement market-neutral strategies
💡 What is Pair Trading?
Imagine two ice cream shops next to each other. They usually have similar customer traffic because they're in the same area. If one day Shop A is packed while Shop B is empty, you might expect this imbalance to correct itself soon.
Pair trading works the same way:
You find two stocks that normally move together (like TCS and Infosys)
When one stock moves too far from the other, you trade expecting them to realign
You buy the lagging stock and sell the leading stock
When they come back together, you profit from both sides
Key Features
1. Z-Score Analysis
What it is: A statistical measure showing how far the price relationship has deviated from normal
What it means:
Z-Score near 0 = Normal relationship
Z-Score at +2 = Stock A is expensive relative to Stock B (Sell A, Buy B)
Z-Score at -2 = Stock A is cheap relative to Stock B (Buy A, Sell B)
2. Multiple Timeframe Analysis
Long-term Z-Score (300 bars): Shows the big picture trend
Short-term Z-Score (100 bars): Shows recent movements
Signal Z-Score (20 bars): Generates quick trading signals
3. Statistical Validation
The indicator checks if the pair is suitable for trading:
Correlation (must be > 0.7): Confirms the stocks move together
1.0 = Perfect positive correlation
0.7 = Strong correlation
Below 0.7 = Warning: pair may not be reliable
ADF P-Value (should be < 0.05): Tests if the relationship is stable
Low value = Good for pair trading
High value = Relationship may be random
Cointegration: Confirms long-term equilibrium relationship
YES = Pair tends to revert to mean
NO = Pair may drift apart permanently
Visual Elements Explained
Chart Zones (Color-Coded Areas)
Yellow Zone (-1.5 to +1.5)
Normal Zone: Relationship is stable
Action: Wait for better opportunities
Blue Zone (±1.5 to ±2.0)
Entry Zone: Deviation is significant
Action: Prepare for potential trades
Green/Red Zone (±2.0 to ±3.0)
Opportunity Zone: Strong deviation
Action: High-probability trade setups
Beyond ±3.0
Risk Limit: Extreme deviation
Action: Either maximum opportunity or structural break
Signal Arrows
Green Arrow Up (Buy A + Sell B):
Stock A is undervalued relative to B
Buy Stock A, Short Stock B
Red Arrow Down (Sell A + Buy B):
Stock A is overvalued relative to B
Sell Stock A, Buy Stock B
Settings Guide
Symbol Inputs
Pair Symbol (Symbol B): Choose the second stock to compare
Default: NSE:INFY (Infosys)
Example pairs: TCS/INFY, HDFCBANK/ICICIBANK, RELIANCE/ONGC
Z-Score Parameters
Long Z-Score Period (300): Historical context
Short Z-Score Period (100): Recent trend
Signal Period (20): Trading signals
Z-Score Threshold (2.0): Entry trigger level
Higher = Fewer but stronger signals
Lower = More frequent signals
Statistical Parameters
Correlation Period (240): How many bars to check correlation
Hurst Exponent Period (50): Measures mean-reversion tendency
Probability Lookback (100): Historical probability calculations
Trading Parameters
Entry Threshold (0.0): Minimum Z-score for entry
Risk Threshold (1.5): Warning level
Risk Limit (3.0): Maximum deviation to trade
How to Use (Step-by-Step)
Step 1: Choose Your Pair
Add the indicator to your chart (this becomes Stock A)
In settings, select Stock B (the comparison stock)
Choose stocks from the same sector for best results
Step 2: Verify Pair Quality
Check the Statistics Table (top-right corner):
✅ Correlation > 0.70 (Green = Good)
✅ ADF P-value < 0.05 (Green = Good)
✅ Cointegrated = YES (Green = Good)
If all three are green, the pair is suitable for trading!
Step 3: Wait for Signals
BUY SIGNAL (Green Arrow Up)
Z-Score crosses above -2.0
Action: Buy Stock A, Sell Stock B
Exit: When Z-Score returns to 0
SELL SIGNAL (Red Arrow Down)
Z-Score crosses below +2.0
Action: Sell Stock A, Buy Stock B
Exit: When Z-Score returns to 0
Step 4: Risk Management
Yellow Zone: Monitor only
Blue Zone: Prepare for entry
Green/Red Zone: Active trading zone
Beyond ±3.0: Maximum risk - use caution
⚠️ Important Warnings
Not All Pairs Work: Always check the statistics table first
Market Conditions Matter: Correlation can break during market stress
Use Stop Losses: Set stops at Z-Score ±3.5 or beyond
Position Sizing: Trade both legs with appropriate hedge ratios
Transaction Costs: Factor in brokerage and slippage for both stocks
Example Trade
Scenario: TCS vs INFOSYS
Correlation: 0.85 ✅
Z-Score: -2.3 (TCS is cheap vs INFY)
Action to be taken:
Buy 1lot of TCS Future
Sell 1lot of INFOSYS Future
Expected Outcome:
As Z-Score moves toward 0, TCS outperforms INFOSYS
Close both positions when Z-Score crosses 0
Profit from the convergence
Best Practices
Test Before Trading: Use paper trading first
Sector Focus: Choose pairs from the same industry
Monitor Statistics: Check correlation daily
Avoid News Events: Don't trade pairs during earnings/major news
Size Appropriately: Start small, scale with experience
Be Patient: Wait for high-quality setups (±2.0 or beyond)
What Makes This Indicator Unique?
Multi-timeframe Z-Score analysis: Three different perspectives
Statistical validation: Built-in correlation and cointegration tests
Visual risk zones: Easy-to-understand color-coded areas
Real-time statistics: Live pair quality monitoring
Beginner-friendly: Clear signals with educational zones
Technical Background
The indicator uses:
Engle-Granger Cointegration Test: Validates pair relationship
ADF (Augmented Dickey-Fuller) Test: Tests stationarity
Pearson Correlation: Measures linear relationship
Z-Score Normalization: Standardizes deviations
Log Returns: Handles price differences properly
Support & Community
For questions, suggestions, or to share your pair trading experiences:
Comment below the indicator
Share your successful pair combinations
Report any issues for quick fixes
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Pair trading involves risk, including the risk of loss.
Always:
Do your own research
Understand the risks
Trade with money you can afford to lose
Consider consulting a financial advisor
📌 Quick Reference Card
Z-ScoreInterpretationAction-3.0 to -2.0A very cheap vs BStrong Buy A, Sell B-2.0 to -1.5A cheap vs BBuy A, Sell B-1.5 to +1.5Normal rangeHold/Wait+1.5 to +2.0A expensive vs BSell A, Buy B+2.0 to +3.0A very expensive vs BStrong Sell A, Buy B
Good Pair Statistics:
Correlation: > 0.70
ADF P-value: < 0.05
Cointegration: YES
Version: 1.0
Last Updated: 10th October 2025
Compatible: TradingView Pine Script v6
Happy Trading!
