Pure FVG [Textbook]1. The Core Concept
This is not a standard "show all gaps" indicator. It is a specific entry signal generator based on Smart Money Concepts (SMC).
It focuses on Consequent Encroachment (The 50% Level). The underlying principle is that a Fair Value Gap (FVG) represents a market inefficiency where opposing traders are trapped. When price retraces at least 50% back into this gap, it creates pressure as these trapped positions look to exit—either through stop-losses or position reversal. This makes the gap most likely to act as a reversal zone.
2. How It Works (The Lifecycle)
The indicator logic follows a strict sequence of events. A signal is generated only if all conditions are met in order:
-- Phase 1: Identification (The Fresh Gap)
The script scans for the classic 3-candle FVG pattern (where the 1st and 3rd candles do not overlap).
Visual: It draws a box (Green for Bullish, Red for Bearish) extending to the right.
The 50% Line: A dashed line is drawn through the center of the gap.
-- Phase 2: Mitigation (The Gray Zone)
This is the critical filter. The indicator waits for a candle to CLOSE past the 50% dashed line.
Once this happens, the gap is considered "Deeply Mitigated."
Visual: The box changes color to Gray. This tells the trader: "Price is deep in the zone, watch for a reaction."
-- Phase 3: The Signal (Rejection)
Once the box is Gray, the script watches for a "Rejection Candle."
Bullish Scenario: Price is deep in the gap (Gray). The script waits for a candle to close higher than it opened (a green candle).
Bearish Scenario: Price is deep in the gap (Gray). The script waits for a candle to close lower than it opened (a red candle).
Visual: A Triangle Label (▲ or ▼) appears, signaling an entry.
-- Phase 4: Invalidation
If the price closes completely past the far edge of the box (the Stop Loss level), the box is deleted immediately.
3. Key Options
These are the most important settings for the user:
-- Min Gap Size (%):
Filters out "noise." It ensures the script ignores tiny, insignificant gaps that are less than X% in height.
-- Max Visible Gaps:
Keeps your chart clean. It limits how many open boxes can be on the screen at once (e.g., only show the last 3 unclosed gaps).
-- Show Signal History Only:
Feature Highlight: When enabled, this hides all the "noise" of open or failed gaps. It only draws the boxes that successfully produced a Rejection Signal in the past.
Indicadores e estratégias
TMT Sessions - Hitesh_NimjeTMT Session - HiteshNimje
Overview
This indicator highlights four configurable trading sessions (default: New York / London / Tokyo / Sydney) and draws session ranges, session VWAPs, session mean/trendline, max/min lines and optional dashboard info. It was built for students of Thought Magic Trading (TMT) to quickly visualize intraday structure across major sessions.
Key features
4 separate sessions (A/B/C/D) — customizable names, times and colors.
Session Range boxes (high/low), optional outline and labels.
VWAP per session (volume-weighted average price).
Mean / Trendline for session price (optional).
Optional session Max/Min lines.
Small on-chart descriptive labels explaining what each plotted line means.
Simple dashboard showing session status (Active/Inactive), volume, trend strength and standard deviation (optional).
Timezone offset or use exchange timezone.
Default colors
Session A — Blue
Session B — Black
Session C — Red
Session D — Orange
Usage / Notes
Designed for intraday analysis — works best on intraday timeframes.
Toggle any session, overlay, or label via input settings to reduce chart clutter.
Labels and dashboard are optional; enable them only when you want the additional on-chart information.
The indicator does not provide buy/sell signals. Use it as a structural reference in conjunction with your trading plan.
Access & License
EXCLUSIVE ACCESS: This indicator is for TMT students only.
Distribution: Invite-only (author permission required) — the author will grant access by invitation.
Redistribution, modification, or public reposting without permission is prohibited.
Support / Contact
For access requests or issues, contact the author: Hitesh_Nimje (Thought Magic Trading).
(Provide invite requests directly to the author — do not attempt to share copies.)
Disclaimer
For educational purposes only. Trading involves risk. Past performance is not indicative of future results. The author is not responsible for trading losses.
EMA Crossover + Angle + Candle Pattern + Breakout (Clean)mrdfgdfew;qwiohj'fjpqwpodkqsk [pal
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EMA Crossover + Angle + Candle Pattern + Breakout (Clean)+mrit uses 9 15 ema startegy with angle and candle also candle used are pin bar , hammer, full body
Easy Crypto Signal FREE🆓 FREE Bitcoin & Crypto Trading Indicator
Easy Crypto Signal FREE helps you make better trading decisions with real-time BUY/SELL signals based on multiple technical indicators.
✅ What you get in FREE version:
• Real-time BUY/SELL signals (green/red arrows)
• Trading SCORE (0-100%) - market strength indicator
• Works on BTC, ETH, and all major altcoins
• Optimized for 4h timeframe (works on all timeframes)
• Simple visual interface
• Basic alert system
📊 How it works:
The indicator combines RSI, MACD, EMA trends, and volume analysis to generate a composite SCORE (0-100%).
• SCORE > 65% = BUY signal 🟢
• SCORE < 35% = SELL signal 🔴
• SCORE 35-65% = WAIT (neutral zone) 🟡
⚠️ FREE Version Limitations:
• No detailed RSI values
• No MACD trend details
• No trend strength indicators
• Fixed sensitivity (65%)
• Limited customization
💎 Want the FULL PRO version?
🚀 PRO includes:
• Full RSI + MACD + Trend analysis displayed
• Customizable sensitivity (40-80%)
• Advanced alert customization
• Professional clean interface
• Volume strength indicator
• NO watermarks
• Premium support
📊 Proven Backtest Results:
• 57.1% Win Rate
• 3.36 Profit Factor (Excellent)
• +9.55% return in 3 months
• Only -2.69% Max Drawdown (Low Risk)
🔗 Get PRO version:
📈 Best practices:
1. Use on 4h timeframe for best results
2. Combine with your own analysis
3. Always set Stop Loss (5-10%)
4. Test on demo account first
5. Don't trade based on signals alone
⚠️ Risk Disclaimer:
Cryptocurrency trading involves substantial risk. This indicator is for educational purposes only and does not guarantee profits. Past performance does not indicate future results. Always do your own research and never invest more than you can afford to lose.
📧 Questions or Feedback?
Comment below or message me directly!
🌟 If you find this helpful, please give it a like and share!
v1.0 - Initial FREE release
• Basic BUY/SELL signal system
• Score indicator 0-100%
• Optimized for 4h timeframe
• Works on all crypto pairs
mayank raj indicatorit uses 9 and 15 ema strategy with angle so that u dont enter in sideways market also the candle entries are hmmer,pinbar,fullbody
Weighted KDE Mode🙏🏻 The ‘ultimate’ typical value estimator, for the highest computational cost @ time complexity O(n^2). I am not afraid to say: this is the last resort BFG9000 you can ‘ever’ get to make dem market demons kneel before y’all
Quickguide
pls read it, you won’t find it anywhere else in open access
When to use:
If current market activity is so crazy || things on your charts are really so bad (contaminated data && (data has very heavy tails || very pronounced peak)), the only option left is to use the peak (mode) of Kernel Density Estimate , instead of median not even mentioning mean. So when WMA won’t help, when WPNR won’t help, you need this thing.
Setting it up:
Interval: choose what u need, you can use usual moving windows, but I also added yearly and session anchors alike in old VWAP (always prefer 24h instead of Session if your plan allows). Other options like cumulative window are also there.
Parameters: this script ain't no joke, it needs time to make calculations, so I added a setting to calculate only for the last N bars (when “starting at bar N” is put on 0). If it’s not zero it acts as a starting point after which the calculations happen (useful for backtesting). Other parameters keep em as they are, keep student5 kernel , turn off appropriate weights if u apply it to other than chart data, on other studies etc.
But instead of listening to me just experiment with parameters and see what they change, would take 5 mins max
Been always saying that VWAP is ish, not time-aware etc, volume info is incorporated in a lil bit wrong way… So I decided not just to fix VWAP (you can do it yourself in 5 mins), but instead to drop there the Ultimate xD typical value estimator that is ever possible to do. Time aware, volume / inferred volume aware, resistant to all kinds of BS. This is your shieldwall.
How it works:
You can easily do a weighted kernel density estimation, in our case including temporal and intensity information while accumulating densities. Here are some details worth mentioning about the thing:
Kernels are raw (not unit variance), that’s easier to work with later.
h_constants for each kernel were calculated ^^ given that ^^ with python mpmath module with high decimal precision.
In bandwidth calculation instead of using empirical standard deviation as a scaler, I use... ta.range(src, len) / math.sqrt(12)
...that takes data range and converts it to standard deviation, assuming data is uniformly distributed. That’s exactly what we need: a scaler that is coherent with the KDE, that has nothing to do with stdevs, as the kernels except for gaussian ones (that we don’t even need to use). More importantly, if u take multiple windows and see over time which distro they approach on the long term, that would be the uniform one (not the normal one as many think). Sometimes windows are multimodal, sometimes Laplace like etc, so in general all together they are uniform ish.
The one and only kernel you really need is Student t with v = 5 , for the use case I highlighted in the first part of the post for TV users. It’s as far as u can get until ish becomes crazy like undefined variance etc. It has the highest kurtosis = 9 of all distros, perfect for the real use case I mentioned. Otherwise, you don’t even need KDE 4 real, but still I included other senseful kernels for comparison or in case I am trippin there.
Btw, don’t believe in all that hype about Epanechnikov kernel which in essence is made from beta distribution with alpha = beta = 2, idk why folk call it with that weird name, it’s beta2 kernel. Yes on papers it really minimises AMISE (that’s how I calculated h constants for all dem kernels in the script), but for really crazy data (proper use case for us), it ain't provides even ‘closely’ compared with student5 kernel. Not much else to add.
Shout out to @RicardoSantos for inspiration, I saw your KDE script a long time ago brotha, finna got my hands on it.
∞
Diff Price (Future - Spot)Diff Line (Future – Spot) plots a grid of spot-price levels derived from the current futures price.
It rounds the current futures price up to the nearest price block (e.g. every 25 points), then subtracts a user‑defined Diff (Future – Spot) to find the main spot level and draws that as the central line. Additional lines are plotted above and below at equal block distances, with labels showing both Future and Spot values (e.g. 4250 (4215)), plus a compact diff info box for quick reference.
Regime Filter [BigBeluga]🔵 OVERVIEW
Regime Filter is a dual-factor trend condition tool combining price trend momentum and volume expansion into a single, easy-to-read visual framework. It quantifies recent trend direction and volume shifts, then shows them as:
Two oscillator plots for Trend and Volume regimes
Dynamic candle coloring for trend clarity
A quadrant scatter map in your chart corner for immediate regime recognition.
This filter helps traders quickly detect when a trend is healthy & confirmed by strong volume, or weakening & vulnerable due to low volume.
🔵 CONCEPTS
Trend Oscillator: A loop-based trend value calculated by comparing the current smoothed price (HMA of HLC3) against its own trailing history. Positive values indicate trend-up regimes, negative values signal trend-down phases.
Volume Oscillator: Similar loop logic but on smoothed volume (HMA of Volume) — highlighting whether trading activity is expanding or contracting relative to past bars.
hma = ta.hma(hlc3, 15)
vol = ta.hma(volume, 15)
for i = 0 to len
if hma > hma
trend += 1
else
trend -= 1
for i = 0 to len
if vol > vol
voltrend += 1
else
voltrend -= 1
Regime Map Scatter Plot: A unique 2D quadrant displayed in the bottom-right corner. This shows where the market is sitting:
> Top Right (green): Trend ↑ and Volume ↑ → strong confirmed up trend.
> Top Left (red): Trend ↓ but Volume ↑ → strong sell momentum.
> Bottom Right (blue): Trend ↑ but Volume ↓ → uptrend losing steam.
> Bottom Left (yellow): Trend ↓ and Volume ↓ → weak bearish drift.
Dynamic Candle Coloring: Candles are colored by trend only: green for uptrends, red for downtrends, and orange near reversals.
Threshold Fills: The oscillator region is shaded green above +10 (healthy uptrend) and red below -10 (strong downtrend) for instant confidence.
🔵 FEATURES
Normalized trend and volume values adapt automatically to your lookback length.
Candlestick color overrides highlight current trend state in real-time.
Clear zero-line and fill bands help you gauge strength vs. noise.
Scatter regime dashboard updates live to track when trend and volume align or decouple.
Color gradients show intensification or cooling in both oscillators and the regime map.
🔵 HOW TO USE
Look for sustained positive trend and volume values to confirm strong directional moves.
Watch for the scatter dot in the green square (top right) for high-confidence breakouts.
If the dot drops to bottom right, uptrend may be tiring — possible exit zone.
If the dot jumps top left, bearish drive is reinforced by heavy volume — caution on longs.
Use the orange trend coloring as an early warning that trend pressure may be shifting.
Combine with breakout levels or moving averages for a robust regime filter system.
🔵 CONCLUSION
The Regime Filter distills price trend and volume dynamics into an actionable multi-mode display: oscillators, color-coded candles, and an intuitive scatter map. This all-in-one layout helps traders visually read market regime strength and spot fading trends before they turn — perfect for swing traders, intraday scalpers, and macro trend followers alike.
Physics of PricePhysics of Price is a non-repainting kinematic reversal and volatility overlay. It models price as a physical object with position, velocity, and acceleration, then builds adaptive bands and a short-term predictive “ghost cone” to highlight where reversals are statistically more likely.
CONCEPT
Instead of using only moving averages, the core engine tracks a smoothed price (position), trend speed (velocity), and change in trend speed (acceleration). Standard deviation of the model error defines probabilistic bands around this kinematic centerline. When price stretches too far away and snaps back, the move is treated as a potential exhaustion event.
CORE COMPONENTS
– Kinematic centerline (Alpha–Beta–Gamma style filter) that bends with trend instead of lagging like a simple MA.
– Inner and outer bands based on the standard deviation of residuals between price and the kinematic model.
– Regime filter using R² and band width to avoid signals in chaotic or ultra-wide regimes.
– Optional RSI “hook” filter that waits for momentum to actually turn instead of buying into a falling RSI.
– Optional divergence add-on using kinematic velocity, so a marginal new price extreme with weaker velocity is recognized as a possible exhaustion pattern.
REVERSAL EVENTS AND SCORING
Raw events are detected when price wicks through the outer band and closes back inside (band hit with snap). These are plotted as diamonds and treated as candidates, not automatic trades.
Each event is then scored from 0 to 100 using several factors:
– How far price overshot the outer band.
– How strongly it snapped back inside.
– Whether an RSI hook is present (if enabled).
– Regime quality from the kinematic model.
– Basic kinematic safety to avoid the most aggressive “knife-catch” situations.
– Optional divergence bonus when price makes a new extreme but velocity does not.
Only events with a score above the chosen threshold become confirmed signals (triangles labeled PHYSICS REV).
GHOST CONE (PREDICTIVE BAND)
On the latest bar, the script projects a short-horizon “ghost cone” into the future using position, velocity, and a damped acceleration term. This creates a curved predictive band that visualizes a plausible short-term path and range, rather than a simple straight line. The cone is meant as context for trade management and risk, not as a hard target.
FILTERS AND OPTIONS
– Regime filter (R² and band width) can be tightened or relaxed depending on how selective you want the engine to be.
– RSI and volume filters can be toggled on for extra confirmation or off to see the raw kinematic behavior.
– An optional trend baseline (EMA) can be enabled to bias or restrict reversals relative to a higher-timeframe trend.
– Dynamic cooldown scales with volatility so the script does not spam signals in fast environments.
HOW TO USE
Physics of Price is primarily a mean-reversion and exhaustion tool. It works best in markets that respect ranges, swings, and two-sided order flow. Confirmed PHYSICS REV signals near the outer bands, with decent model health and a clean RSI hook, are the core use case. The bands and ghost cone can also be used as a context overlay alongside your own entries, exits, and risk framework.
This is an indicator, not a complete trading system. It does not use lookahead or higher-timeframe security calls and is designed for “once per bar close” alerts. Always combine it with your own risk management and confluence.
Double Relative Strength IndexBase on Regular Relative Streng Index, I am add 1 more RSI on it.
Using method:
When faster RSI cross lower RSI, price direction move at the same direction. It faster to know the direction of price than just using 1 RSI.
Hope it useful for you.
First Green/Red Day of Week (Break Prior Day)gives you the first red day or candle of the week that closes below the low of the previous day and the first green day or candle of the week that closes above the high of the previous day
6x EMA Set (5/20/50/100/200/300)This Pine Script indicator utilizes six Exponential Moving Averages (5, 20, 50, 100, 200, and 300 EMA) to visualize market trends and support/resistance levels across multiple timeframes on a single chart. The code is highly customizable, allowing the user to input and adjust the period length and color for each EMA directly within the indicator settings. The calculation engine uses Pine Script v5's optimized ta.ema() function to compute each average based on the closing price, with the EMA formula naturally weighting recent price action more heavily. This multi-layered structure enables the trader to quickly compare short-term momentum (Fast EMAs) against long-term structural trends (Slow EMAs).
Gravestone Doji ScannerSpeaks for itself. Set it on the chart. Use Arrow Keys to move through the watchlist.
Inverse Intermarket Confirmation Pro PlusInverse Intermarket Confirmation Pro Plus using MACD and VOLUME by Bales
Keltner Hull Suite [QuantAlgo]🟢 Overview
The Keltner Hull Suite combines Hull Moving Average positioning with double-smoothed True Range banding to identify trend regimes and filter market noise. The indicator establishes upper and lower volatility bounds around the Hull MA, with the trend line conditionally updating only when price violates these boundaries. This mechanism distinguishes between genuine directional shifts and temporary price fluctuations, providing traders and investors with a systematic framework for trend identification that adapts to changing volatility conditions across multiple timeframes and asset classes.
🟢 How It Works
The calculation foundation begins with the Hull Moving Average, a weighted moving average designed to minimize lag while maintaining smoothness:
hullMA = ta.hma(priceSource, hullPeriod)
The indicator then calculates true range and applies dual exponential smoothing to create a volatility measure that responds more quickly to volatility changes than traditional ATR implementations while maintaining stability through the double-smoothing process:
tr = ta.tr(true)
smoothTR = ta.ema(tr, keltnerPeriod)
doubleSmooth = ta.ema(smoothTR, keltnerPeriod)
deviation = doubleSmooth * keltnerMultiplier
Dynamic support and resistance boundaries are constructed by applying the multiplier-scaled volatility deviation to the Hull MA, creating upper and lower bounds that expand during volatile periods and contract during consolidation:
upperBound = hullMA + deviation
lowerBound = hullMA - deviation
The trend line employs a conditional update mechanism that prevents premature trend reversals. The system maintains the current trend line until price action violates the respective boundary, at which point the trend line snaps to the violated bound:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Directional bias determination compares the current trend line value against its previous value, establishing bullish conditions when rising and bearish conditions when falling. Signal generation occurs on state transitions, triggering alerts when the trend state shifts from neutral or opposite direction:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
longSignal = trendState == 1 and trendState != 1
shortSignal = trendState == -1 and trendState != -1
The visualization layer creates a trend band by plotting both the current trend line and a two-bar shifted version, with the area between them filled to create a visual channel that reinforces directional conviction.
🟢 How to Use This Indicator
▶ Long and Short Signals: The indicator generates long/buy signals when the trend state transitions to bullish (trend line begins rising) and short/sell signals when transitioning to bearish (trend line begins falling). These state changes represent structural shifts in momentum where price has broken through the adaptive volatility bands, confirming directional commitment.
▶ Trend Band Dynamics: The spacing between the main trend line and its shifted counterpart creates a visual band whose width reflects trend strength and momentum consistency. Expanding bands indicate accelerating directional movement and strong trend persistence, while contracting or flattening bands suggest decelerating momentum, potential trend exhaustion, or impending consolidation. Monitoring band width provides early warning of regime transitions from trending to range-bound conditions.
▶ Preconfigured Presets: Three optimized parameter sets accommodate different trading styles and timeframes. Default (14, 20, 2.0) provides balanced trend identification suitable for daily charts and swing trading, Fast Response (10, 14, 1.5) delivers aggressive signal generation optimized for intraday scalping and momentum trading on 1-15 minute timeframes, while Smooth Trend (18, 30, 2.5) offers conservative trend confirmation ideal for position trading on 4-hour to daily charts with enhanced noise filtration.
▶ Built-in Alerts: Three alert conditions enable automated monitoring - Bullish Trend Signal triggers on long setup confirmation, Bearish Trend Signal activates on short setup confirmation, and Trend Change alerts on any directional transition. These notifications allow you to respond to regime shifts without continuous chart monitoring.
▶ Color Customization: Five visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and display preferences, ensuring optimal contrast and visual clarity across trading environments.
Sanjay AhirPull Backs , Swings Marking
useful for market structure
useful For Smc Strcture
useful for ICT mapping
Ehlers Dominant Cycle Stochastic RSIEhlers Enhanced Cycle Stochastic RSI
OVERVIEW
The Ehlers Enhanced Cycle Stochastic RSI is a momentum oscillator that automatically adjusts its lookback periods based on the dominant market cycle. Unlike traditional Stochastic RSI which uses fixed periods, this indicator detects the current cycle length and scales its calculations—making it responsive in fast markets and stable in slow ones.
The indicator combines John Ehlers' digital signal processing research with the classic Stochastic RSI indicator, then adds a confirmation system to ensure cycle measurements are reliable.
THE THEORY
Traditional oscillators use fixed lookback periods (ie, 14-bar RSI). This creates a fundamental problem: markets don't move in fixed cycles. A 14-period RSI might capture the rhythm perfectly during one market phase, then completely miss it when conditions change.
Ehlers' research demonstrated that price data contains measurable cyclical components. If you can detect the dominant cycle length, you can tune your indicators to match it—like tuning a radio to the right frequency.
This indicator takes that concept further by using three independent cycle detection methods and only trusting the measurement when they agree:
Hilbert Transform — A mathematical technique from signal processing that extracts cycle period from the phase relationship between price and its derivative. It is fast but can be noisy.
Autocorrelation Periodogram — Measures how similar the price series is to lagged versions of itself. The lag with highest correlation reveals the dominant cycle. More stable than Hilbert, but slightly slower to adapt.
Goertzel Algorithm (DFT) — A frequency-domain approach that calculates spectral power at each candidate period. Identifies which frequencies contain the most energy.
When all three methods converge on similar period estimates, confidence is high. When they disagree, the market may be in a non-cyclical or in transition.
HOW IT CHANGES THE STOCHASTIC RSI
Standard Stochastic RSI:
1. Calculate RSI with fixed period (14 bars)
2. Apply Stochastic formula over fixed period (14 bars)
3. Smooth with fixed periods
Ehlers Enhanced Cycle Stochastic RSI:
1. Detect dominant cycle using three methods
2. Confirm cycle measurement (methods must agree)
3. Calculate RSI with period scaled to the detected cycle
4. Apply Stochastic formula with cycle-scaled lookback
5. Smooth adaptively
The result: when the market is cycling quickly (say, 15-bar cycles), the indicator uses shorter periods and responds faster. When the market stretches into longer cycles (such as 40-bar cycles), it automatically extends its lookback to avoid whipsaws.
The Period Multipliers let you fine-tune this relationship:
• 1.0 = Use the full detected cycle (smoother, fewer signals)
• 0.5 = Use half the cycle (more responsive, catches turns earlier)
INTERPRETATION
Reading the Oscillator:
• K Line (Blue) — The main signal line. Moves between 0 and 100.
• D Line (Orange) — Smoothed version of K. Use for confirmation.
• Above 80 — Overbought. Momentum stretched to upside.
• Below 20 — Oversold. Momentum stretched to downside.
• Crossovers — K crossing above D suggests bullish momentum shift; K crossing below D suggests bearish.
Spectral Dilation (optional):
When enabled, applies a bandpass filter before cycle detection. This isolates the frequency band of interest and reduces noise. Useful for:
• Very noisy instruments
• Lower timeframes
• When confidence stays persistently low
NIFTY Weekly Option Seller DirectionalHere’s a straight description you can paste into the TradingView “Description” box and tweak if needed:
---
### NIFTY Weekly Option Seller – Regime + Score + Management (Single TF)
This indicator is built for **weekly option sellers** (primarily NIFTY) who want a **structured regime + scoring framework** to decide:
* Whether to trade **Iron Condor (IC)**, **Put Credit Spread (PCS)** or **Call Credit Spread (CCS)**
* How strong that regime is on the current timeframe (score 0–5)
* When to **DEFEND** existing positions and when to **HARVEST** profits
> **Note:** This is a **single timeframe** tool. The original system uses it on **4H and 1D separately**, then combines scores manually (e.g., using `min(4H, 1D)` for conviction and lot sizing).
---
## Core logic
The script classifies the market into 3 regimes:
* **IC (Iron Condor)** – range/mean-reversion conditions
* **PCS (Put Credit Spread)** – bullish/trend-up conditions
* **CCS (Call Credit Spread)** – bearish/trend-down conditions
For each regime, it builds a **0–5 score** using:
* **EMA stack (8/13/34)** – trend structure
* **ADX (custom DMI-based)** – trend strength vs range
* **Previous-day CPR** – in CPR vs break above/below
* **VWAP (session)** – near/far value
* **Camarilla H3/L3** – for IC context
* **RSI (14)** – used as a **brake**, not a primary signal
* **Daily trend / Daily ADX** – used as **hard gates**, not double-counted as extra points
Then:
* Scores for PCS / CCS / IC are **cross-penalised** (they pull each other down if conflicting)
* Final scores are **smoothed** (current + previous bar) to avoid jumpy signals
The **background colour** shows the current regime and conviction:
* Blue = IC
* Green = PCS
* Red = CCS
* Stronger tint = higher regime score
---
## Scoring details (per timeframe)
**PCS (uptrend, bullish credit spreads)**
* +2 if EMA(8) > EMA(13) > EMA(34)
* +1 if ADX > ADX_TREND
* +1 if close > CPR High
* +1 if close > VWAP
* RSI brake:
* If RSI < 50 → PCS capped at 2
* If RSI > 75 → PCS capped at 3
* Daily gating:
* If daily EMA stack is **not** uptrend → PCS capped at 2
**CCS (downtrend, bearish credit spreads)**
* +2 if EMA(8) < EMA(13) < EMA(34)
* +1 if ADX > ADX_TREND
* +1 if close < CPR Low
* +1 if close < VWAP
* RSI brake:
* If RSI > 50 → CCS capped at 2
* If RSI < 25 → CCS capped at 3
* Daily gating:
* If daily EMA stack is **not** downtrend → CCS capped at 2
**IC (range / mean-reversion)**
* +2 if ADX < ADX_RANGE (low trend)
* +1 if close inside CPR
* +1 if near VWAP
* +0.5 if inside Camarilla H3–L3
* +1 if daily ADX < ADX_RANGE (daily also range-like)
* +0.5 if RSI between 45 and 55 (classic balance zone)
* Daily gating:
* If daily ADX ≥ ADX_TREND → IC capped at 2 (no “strong IC” in strong trends)
**Cross-penalty & smoothing**
* Each regime’s raw score is reduced by **0.5 × max(other two scores)**
* Final IC / PCS / CCS scores are then **smoothed** with previous bar
* Scores are always clipped to ** **
---
## Regime selection
* If one regime has the highest score → that regime is selected.
* If there is a tie or close scores:
* When ADX is high, trend regimes (PCS/CCS) are preferred in the direction of the EMA stack.
* When ADX is low, IC is preferred.
The selected regime’s score is used for:
* Background colour intensity
* Minimum score gate for alerts
* Display in the info panel
---
## DEFEND / HARVEST / REGIME alerts
The script also defines **management signals** using ATR-based buffers and Camarilla breaks:
* **DEFEND**
* Price moving too close to short strikes (PCS/CCS/IC) relative to ATR, or
* Trend breaks through Camarilla with ADX strong
→ Suggests rolling away / widening / converting to reduce risk.
* **HARVEST**
* Price has moved far enough from your short strikes (in ATR multiples) and market is still range-compatible
→ Suggests booking profits / rolling closer / reducing risk.
* **REGIME CHANGED**
* Regime flips (IC ↔ PCS/CCS) with cooldown and minimum score gate
→ Suggests switching playbook (range vs trend) for new entries.
Each of these has a plotshape label plus an `alertcondition()` for TradingView alerts.
---
## UI / Panel
The **top-right panel** (optional) shows:
* Strategy + final regime score (IC / PCS / CCS, x/5)
* ADX / RSI values
* CPR status (Narrow / Normal / Wide + %)
* EMA Stack (Up / Down / Mixed) and EMA tightness
* VWAP proximity (Near / Away)
* Final **IC / PCS / CCS** scores (for this timeframe)
* H3/L3, H4/L4, CPR Low/High and VWAP levels (rounded)
These values are meant to be **read quickly at the decision time** (e.g. near the close of the 4H bar or daily bar).
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## Intended workflow
1. Run the script on **4H** and **1D** charts separately.
2. For each timeframe, read the panel’s **IC / PCS / CCS scores** and regime.
3. Decide:
* Final regime (IC vs PCS vs CCS)
* Combined score (e.g. `AlignScore = min(Score_4H, Score_1D)`)
4. Map that combined score to **your own lot-size buckets** and trade rules.
5. During the life of the position, use **DEFEND / HARVEST / REGIME** alerts to adjust.
The script does **not** auto-calculate lot size or P&L. It focuses on giving a structured, consistent **market regime + strength + levels + management** layer for weekly option selling.
---
## Disclaimer
This is a discretionary **decision-support tool**, not a guarantee of profit or a replacement for risk management.
No performance is implied or promised. Always size positions and manage risk according to your own capital, rules, and regulations.
ZLSMA Cross ATR Targets - Enhanced Trading StrategyZLSMA Cross ATR Targets - Enhanced Trading Strategy
📊 Overview
This indicator combines Zero-Lag Least Squares Moving Average (ZLSMA) crossover signals with ATR-based dynamic risk management to provide precise entry and exit points. Unlike standard moving average crossovers, this system uses a zero-lag implementation to reduce signal delays and incorporates multi-timeframe analysis for improved accuracy.
🎯 What Makes This Script Unique
1. Zero-Lag LSMA Implementation:
Uses a dual-smoothing technique: 2 * SMA(price, length) - SMA(SMA(price, length), length)
This eliminates the typical lag found in standard moving averages
Provides faster reaction to price changes while maintaining smoothness
2. Multi-Timeframe Signal Generation:
Analyzes price action on a higher timeframe (default: 15-min) regardless of chart timeframe
Reduces noise and false signals common in single-timeframe systems
All calculations (ZLSMA, ATR, close price) are synchronized to the signal timeframe
3. Dynamic ATR-Based Risk Management:
Stop Loss: Automatically calculated using ATR multiplier (default: 1.0x)
Take Profit 1: First target at 1.5x ATR (adjustable)
Take Profit 2: Extended target at 3.0x ATR (adjustable)
Risk-Reward ratios are displayed on each trade label for transparency
4. Optional Signal Filters:
Trend Filter: Uses 200 EMA to filter trades - only buys above, sells below (optional)
Volatility Filter: Ensures minimum ATR % to avoid low-volatility false signals (optional)
Both filters can be independently toggled on/off
5. Real-Time Performance Tracking:
Automatically tracks completed trades (TP1, TP2, or SL hits)
Calculates win rate, total P/L, and average P/L per trade
Live P/L displayed for current open position
Performance-based color coding (Green/Blue/Orange/Red)
🔧 How It Works
Signal Generation:
BUY Signal: Triggered when price crosses above ZLSMA on the signal timeframe
SELL Signal: Triggered when price crosses below ZLSMA on the signal timeframe
If filters are enabled, signals are validated against trend direction and volatility conditions
Trade Execution:
Entry price is locked at the close of the crossover bar
SL, TP1, and TP2 are calculated using the ATR value from the signal timeframe
Horizontal lines extend into the future (default: 240 bars) for visual clarity
Labels display all trade parameters including risk-reward ratios
Position Management:
System monitors each bar to detect if price hits SL, TP1, or TP2
Once a target is hit, the trade is marked as complete and statistics update
"Show Only Latest Trade" toggle cleans up historical signals for chart clarity
📈 How to Use
Settings:
Signal Timeframe: Timeframe for ZLSMA and ATR calculations (higher = fewer signals)
ZLSMA Length: Lookback period (100 default, lower = more responsive)
ATR Length: Period for volatility measurement (14 default)
SL/TP Multipliers: Adjust risk-reward profile to your trading style
Filters: Enable/disable trend and volatility filters as needed
Dashboard:
Fixed position (top-right corner) shows:
Current trade status and live P/L
Entry, SL, TP1, TP2 prices
Total performance statistics
Strategy settings summary
Alerts:
Enable alerts in settings to receive notifications on new signals
Each alert includes full trade details (Entry, SL, TP1, TP2)
⚙️ Why This Combination Works
The mashup of ZLSMA, multi-timeframe analysis, ATR-based targets, and optional filters creates a complete trading system:
ZLSMA provides faster signals than traditional moving averages
Higher timeframe reduces noise and improves signal quality
ATR-based targets adapt to current market volatility (no fixed pip targets)
Trend filter keeps you aligned with the bigger picture
Volatility filter avoids choppy, low-conviction setups
Performance tracking allows data-driven strategy optimization
This is not just a combination of existing indicators—it's a complete risk-managed trading framework with built-in analytics.
⚠️ Risk Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
Higher Timeframe MA High Low BandsHigher Timeframe Customer MA High Low Bands. There are 3 different Moving Average Parameters Available. Indicator will plot 3 lines of MA Length With Source of High, Close and Low. User can change relevant MA parameters / Show or Hide MA.
Happy Trading
IBIT premium（vs NAV）This Pine Script calculates and plots the real-time trading premium or discount of the IBIT ETF relative to its official Net Asset Value (NAV).
It shows whether IBIT is trading above NAV (premium) or below NAV (discount) in percentage terms.
This version is accurate because it uses TradingView’s built-in ETF NAV financial data, rather than estimating BTC per share.
⸻
Key Data Sources Used
• Market Price:
The script pulls the live IBIT market price from NASDAQ:IBIT.
• Official NAV:
It retrieves the daily Net Asset Value (NAV) using TradingView’s financial data function and expands it across all intraday timeframes so it can be compared with real-time prices.
• Platform used: TradingView
⸻
How the Premium Is Calculated
The script uses the standard ETF premium formula:
\text{Premium (\%)} = \frac{\text{Market Price} - \text{NAV}}{\text{NAV}} \times 100
• Positive value → IBIT is trading at a premium
• Negative value → IBIT is trading at a discount
• Zero → IBIT is trading exactly at NAV
⸻
What the Chart Displays
• A real-time premium (%) line in a separate indicator panel
• A 0% reference line showing fair value
• ±1% and ±2% guide lines for abnormal deviation detection
• A live value label on the latest bar showing the exact current premium
⸻
Why This Script Is Accurate
• Uses official ETF NAV, not a BTC-per-share estimate
• NAV updates once per day, exactly as reported by the issuer
• Works on all timeframes (1-minute to daily)
• Shows true market mispricing, not synthetic BTC tracking error
⸻
How Traders Typically Use It
• Detect temporary dislocations between IBIT price and NAV
• Monitor liquidity stress during high volatility
• Validate whether IBIT is trading efficiently versus BTC
• Support ETF–BTC–Futures arbitrage analysis
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Important Limitation
• NAV is only updated once per trading day
• During fast BTC moves, the premium may widen temporarily and normalize later via authorized participant (AP) arbitrage
