vdubus BinaryPro - Indicators 1 & 2For both scripts - Go to 'MAKE IT MINE'
Modified scripts for Binary trading 1- 3 min charts / 5 -15 min intervals
vdubus BinaryPro 1
Vdubus BinaryPro 2
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Vdubus BinaryPro Money Management Strategy: $10 - $50,000 in 15 trades
Tip * break consecutive trades down to lots of 5 compounded / repeat to build up a solid equity foundation., then move on the the next 5 x 3 = 15
if you lose one trade out of the 5, restart the proses. You only ever lose the initial trade size you started with * DOUBLE YOUR WINNINGS NOT YOUR LOSSES !
If you struggle to win 5 compounded trades in a row, compound 2 or 3 trades at a time
drive.google.com
חפש סקריפטים עבור "父亲把15万藏被子里被儿子误扔"
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
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1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
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2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
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3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
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4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
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5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
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6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
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7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
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8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
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9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
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10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
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11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
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12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
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13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
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14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
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15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
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16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
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17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
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18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
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19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
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20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
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BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide
Overview
This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition.
How It Works
Core Prediction Logic
- Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes
- Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%)
- Verification: Automatically tracks and displays win/loss statistics in real-time
5-Layer Filter System
The indicator uses a sophisticated scoring system (0-100 points):
1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum
2. Leading Indicators (25 points) - RSI and MACD divergence analysis
3. Volume Confirmation (20 points) - Detects unusual volume patterns
4. Support/Resistance (15 points) - Identifies key price levels
5. Momentum Alignment (15 points) - Measures acceleration and deceleration
Pattern Recognition
Automatically detects and visualizes:
- Double Tops/Bottoms - Reversal patterns
- Triangles - Ascending, descending, symmetrical
- Channels - Trending price channels
- Candlestick Patterns - Engulfing, hammer, hanging man
Multi-Timeframe Analysis
- Uses 1-minute and 5-minute data for confirmation
- Aligns multiple timeframes for higher probability trades
- Monitors trend consistency across timeframes
Key Features
Display Panels
1. Statistics Panel (Top Right)
- Overall win rate percentage
- Hourly performance (wins/losses)
- Daily performance
- Current system status
2. Analysis Panel (Left Side)
- Market trend analysis
- RSI status (overbought/oversold)
- Volume conditions
- Filter scores for each component
- Final HIGH/LOW/WAIT decision
Visual Signals
- Green Triangle (↑) = HIGH prediction
- Red Triangle (↓) = LOW prediction
- Yellow Background = Entry opportunity
- Blue Background = Waiting for result
Configuration Options
Basic Settings
- Range Width: Target price movement (default $50 = ±$25)
- Min Confidence: Minimum confidence to enter (default 75%)
- Max Daily Trades: Risk management limit (default 5)
Filters (Can be toggled on/off)
- Trend Filter
- Volume Confirmation
- Support/Resistance Filter
- Momentum Alignment
Display Options
- Show/hide signals, statistics, analysis
- Minimal Mode for cleaner charts
- EMA line visibility
Important Risk Warnings
Binary Options Trading Risks:
1. High Risk Product - Binary options are extremely risky and banned in many countries
2. Not Investment Advice - This tool is for educational/analytical purposes only
3. No Guaranteed Returns - Past performance doesn't predict future results
4. Capital at Risk - You can lose your entire investment in seconds
Technical Limitations:
- Requires stable internet connection
- Performance varies with market conditions
- High volatility can reduce accuracy
- Not suitable for news events or low liquidity periods
Best Practices
1. Paper Trade First - Test thoroughly on demo accounts
2. Risk Management - Never risk more than 1-2% per trade
3. Market Conditions - Works best in normal volatility conditions
4. Avoid Major Events - Don't trade during major news releases
5. Monitor Performance - Track your actual results vs displayed statistics
Setup Instructions
1. Add to TradingView chart (BTC/USD preferred)
2. Use 30-second or 1-minute chart timeframe
3. Adjust settings based on your risk tolerance
4. Monitor F-Score (should be >65 for entries)
5. Wait for clear HIGH/LOW signals with high confidence
Alert Configuration
The indicator provides three alert types:
- HIGH Signal alerts
- LOW Signal alerts
- General entry opportunity alerts
Legal Disclaimer
Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading.
Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.
Technical Probability MetrixThe provided Pine Script is a comprehensive trading tool called the "Technical Probability Metrix," designed for TradingView in Pine Script version 5. It integrates multiple technical indicators and advanced calculations to generate a probability score indicating the likelihood of bullish or bearish price movement. This study is helpful for traders seeking a consolidated market analysis from several technical perspectives in one integrated view.
How to Use This Script
• Apply the script to any chart on TradingView.
• Customize input parameters like wave detection period, Fibonacci levels, RSI length, MACD settings, stochastic length, and EMA periods to suit your trading style.
• Enable or disable display elements such as Elliott Wave labels, Fibonacci levels, and the summary table as needed.
• Observe the summary table that shows the status, values, strength progress bars, and probability percentages for each indicator category.
• Use the overall "Technical Probability Metrix" score and color-coded signals to determine trade bias and strength.
• Alerts are set up for strong buy/sell signals, trend changes, and EMA crossovers for real-time notification.
How It Is Helpful
• Unified Analysis: Combines momentum, trend, volume, and Fibonacci analysis in a single view, saving time and reducing indicator clutter.
• Probability Scores: Converts complex indicator data into probability percentages, allowing easier interpretation of market direction strength.
• Adaptive Targeting: Provides configurable probability levels indicating multiple targets based on the current trend strength.
• Trend Detection: Uses a trend scoring method combining linear regression, moving averages, and pivot highs/lows for a robust trend bias.
• Alert Conditions: Notifies users of key market signal changes to support timely decision-making.
• Volume and Order Blocks: Includes volume moving average and order block strength which are critical for validating price moves.
• Multi-Timeframe EMA Cross: Incorporates 15-minute EMA crossover analysis adding another confirmation layer.
Indicators Included and Their Role
• RSI (Relative Strength Index): Measures overbought/oversold conditions. Values >70 suggest overbought; <30 suggest oversold.
• MACD (Moving Average Convergence Divergence): Momentum and trend confirmation; bullish when MACD line crosses above signal line.
• Stochastic Oscillator: Identifies momentum and potential trend reversals; bullish when %K crosses above %D under 80.
• Volume Moving Average and Ratio: Detects unusual volume spikes which often precede price moves.
• VWAP (Volume Weighted Average Price): Determines if price is trading above or below average price weighted by volume, indicating institutional interest.
• Order Block Strength: Highlights key supply/demand zones from recent high/low ranges.
• EMA 9/20 Crossover (on 15-min): Short and medium-term trend signals for finer timing.
• Elliott Wave Pivots: Detects significant wave highs and lows to assess price position within swing structures.
• Trend Metrics: Combines moving averages, linear regression slope, higher highs/lows, and bar comparisons to score market trend strength.
How to Analyze Using This Study
• Look for alignment among the indicators: bullish RSI, MACD, stochastic, and volume with positive trend scores and price above VWAP suggest a strong buy.
• Use the probability percentages and progress bars to gauge the power behind signals.
• Observe the overall signal (Strong Buy, Buy, Neutral, Sell, Strong Sell) and corresponding color for quick visual cues.
• Fibonacci levels and wave counts provide context about price targets and retracement zones.
• Alerts notify when conditions for strong entry or exit signals occur, complementing manual analysis.
Benefits for New Traders
• Simplifies Complex Data: Merges multiple technical tools into one dashboard, reducing confusion from using many separate indicators.
• Visual Progress Bars and Status: Easy-to-understand visualization of each indicator’s strength and market probability.
• Educative Value: Shows how classic indicators combine into an overall market assessment, useful for learning indicator interactions.
• Alerts: Helps beginners by signaling trading opportunities without needing constant manual chart monitoring.
• Adjustable Settings: Allows users to experiment with input values and observe how indicators respond.
Disclaimer from aiTrendview
This script and its trading signals are provided for training and educational purposes only. They do not constitute financial advice or a guaranteed trading system. Trading involves substantial risk, and there is the potential to lose all invested capital. Users should perform their own analysis and consult with qualified financial professionals before making any trading decisions. aiTrendview disclaims any liability for losses incurred from using this code or trading based on its signals. Use this tool responsibly, and trade only with risk capital.
BTC/USD 3分バイナリー予測【完全修正版v7.2】## BTC/USD 3-Minute Binary Prediction Indicator v7.2 Documentation
### Overview
This indicator predicts whether BTCUSD price will move ±$25 or more within 3 minutes using a 5-layer filter system and pattern recognition. Designed for 30-second timeframe analysis with statistical tracking.
### ⚠️ Critical Warnings
- **This is a prediction tool, NOT a profit guarantee**
- **30-second timeframe ONLY** (Will not function correctly on other timeframes)
- **BTCUSD pair ONLY**
- **Past performance does not guarantee future results**
- **Test thoroughly in demo before live trading**
- **You can lose your entire investment**
### Core Components
#### 1. Five-Layer Filter System
```
Layer 1: Trend Alignment (25 points) - EMA configuration analysis
Layer 2: Indicator Confluence (25 points) - RSI + MACD confirmation
Layer 3: Volume Analysis (20 points) - Abnormal volume detection
Layer 4: Key Levels (15 points) - Support/Resistance proximity
Layer 5: Momentum (15 points) - Price acceleration measurement
```
#### 2. Pattern Recognition Engine
- Double Top/Bottom formations
- Triangle patterns (Symmetrical, Ascending, Descending)
- Channel patterns
- Candlestick patterns (Engulfing, Hammer, Hanging Man)
#### 3. Performance Tracking
- Overall win rate
- Hourly performance
- Daily performance
- Real-time statistics
### Input Parameters
#### Basic Settings
- `Range Width ($)`: Target price movement (Default: $50 = ±$25)
- `Minimum Confidence (%)`: Required confidence for entry (Default: 75%)
- `Max Daily Trades`: Overtrading prevention (Default: 5)
#### Filter Settings
- `Trend Filter`: EMA alignment validation
- `Volume Confirmation`: Volume spike detection
- `S/R Filter`: Key level analysis
- `Momentum Alignment`: Directional strength confirmation
#### Display Settings
- `Minimal Mode`: Reduced visual elements for experienced users
- `Pattern Display`: Visual pattern overlays
- `EMA Lines`: Moving average visualization
### Usage Instructions
#### Setup Process
1. Open BTCUSD chart on TradingView
2. **Set timeframe to 30 seconds** (CRITICAL)
3. Add indicator to chart
4. Adjust parameters if needed
#### Reading Signals
**Decision Panel (Left Side)**
- `HIGH`: Predicts +$25 move in 3 minutes
- `LOW`: Predicts -$25 move in 3 minutes
- `WAIT`: Conditions building, no entry yet
- `STAY`: No trade opportunity
**F-Score Interpretation**
- 65+ points: Direction suggestion (light color)
- 80+ points: Strong signal (solid color)
- Entry ready: Exclamation mark (!)
**Statistics Panel (Right Side)**
- Win rate: Percentage of successful predictions
- 1H Stats: Last hour performance
- Daily Stats: Today's results
#### Entry Execution
1. Wait for `HIGH!` or `LOW!` in decision panel
2. Large arrow appears on chart (▲ for HIGH, ▼ for LOW)
3. Enter at **next candle open**
4. Result evaluated after 3 minutes (6 candles)
### Algorithm Logic
#### Early Entry System (v7.2 Feature)
The indicator uses predictive analysis starting at F-Score 65 instead of waiting for 80:
- Faster signal generation
- Reduced opportunity loss
- Slightly lower win rate trade-off
#### Confidence Calculation
```
Base confidence: 50%
+ Filter score bonus
+ Pattern recognition bonus
+ Volatility adjustment
- Risk factors
= Final confidence (50-95%)
```
### Technical Specifications
#### Multi-Timeframe Analysis
- Primary: 30-second chart
- Secondary: 1-minute data
- Reference: 5-minute trend
#### Data Processing
- Real-time tick analysis
- No repainting (signals are final)
- Historical verification system
### Limitations & Known Issues
1. **Spread/Commission Not Included**: Actual profits will be lower
2. **30-Second Noise**: High false signal risk on ultra-short timeframe
3. **Network Latency**: Execution delays not accounted for
4. **Market Conditions**: Performance varies with volatility
5. **Algorithm Trading**: Cannot compete with HFT systems
### Performance Metrics
- Target Win Rate: 83% (aspirational)
- Evaluation Period: 3 minutes
- Risk per trade: Fixed ±$25
- Maximum daily exposure: 5 trades
### Troubleshooting Guide
**No signals appearing?**
- Check F-Score (needs 65+)
- Verify 30-second timeframe
- Ensure BTCUSD pair selected
**Low win rate?**
- Only trade 75%+ confidence signals
- Respect daily trade limit
- Avoid news events
**Pattern shows "-"?**
- Normal when no clear pattern exists
- Not all market conditions produce patterns
### Code Modification Notes
Written in Pine Script v6. Key considerations for modifications:
- Global variables use `var` for persistence
- Drawing objects require manual management
- Bar counting varies by timeframe
- Pattern detection runs on confirmed bars only
### Risk Disclosure
**IMPORTANT**: Trading cryptocurrencies involves substantial risk of loss and is not suitable for all investors. The high degree of leverage can work against you as well as for you. Before deciding to trade, you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment and therefore you should not invest money that you cannot afford to lose.
### Support & Updates
- Report issues in TradingView comments
- Check for updates regularly
- Version 7.2 is current release
- Community feedback welcome
### Legal Notice
This indicator is provided for educational and research purposes only. It should not be construed as investment advice. The authors and distributors of this indicator accept no liability for losses incurred through its use. Always consult with a qualified financial advisor before making investment decisions.
---
*Version: 7.2*
*License: Mozilla Public License 2.0*
*Author: *
*Last Updated: 2024*
**FINAL WARNING: This indicator cannot predict the future. Use at your own risk. Start with demo trading. Never trade with money you cannot afford to lose.**
ForecastForecast (FC), indicator documentation
Type: Study, not a strategy
Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars
Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets
⸻
What the indicator does
FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes:
• Absolute: Forecast of the selected symbol
• Relative: Forecast of the ratio symbol / benchmark
• Combined: Average of Absolute and Relative
A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs.
⸻
PineScreener, relative-strength screening
This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale.
Available PineScreener columns
PineScreener reads the plotted series. You will see at least these columns:
• FC, the capped forecast
• from EMA20, (price − EMA20) / ATR in ATR multiples
• from EMA50, (price − EMA50) / ATR in ATR multiples
• ATR, ATR as a percent of price
• Corr, weekly correlation with the chosen benchmark
Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source.
⸻
How it works, step by step
1. Volatility model
Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma.
2. EWMAC momentum, three legs
Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128).
Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor.
3. Breakout momentum, three channels
Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged.
4. Composite forecast
Average the EWMAC composite and the breakout composite, then cap to ±20.
Relative mode runs the same logic on symbol / benchmark.
Combined mode averages Absolute and Relative composites.
5. Weekly correlation
Pearson correlation between weekly closes of the asset and the benchmark over a user-set length.
6. Direction overlay
Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20.
⸻
Plots
• FC, capped forecast on the daily chart
• 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view
• 8-32-128 Abs, 8-32-128 Rel, three-leg composite views
• from EMA20, from EMA50, (price − EMA) / ATR
• ATR, ATR as a percent of price
• Corr, weekly correlation with the benchmark
• Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill
• Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides
Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them.
⸻
Inputs
Symbol selection
• Absolute, Relative, Combined
• Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD
• Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL
Engine selection
• Include:
• 8-32-128, three EWMAC legs plus three breakouts
• 8-32, simplified view based on the 8-32 leg plus a 40-day breakout
EMA, applied to the forecast
• EMA1, EMA2, with line-width controls, plus color and opacity
Volatility
• Span, EW volatility span for daily returns
• 10y %, blend of long-run volatility
• Thresh, Too volatile, placeholders in this version
Background
• Horizontal bg, level shading, enabled by default
• Long BG, Hedge BG, colors and opacities
Show
• Table, Header, Direction, Gain, Extension
• Corr, Length for correlation row
Table settings
• Position, background, opacity, text size, text color
Lines
• 0-lines, 10-lines, 5-lines, level guides
⸻
Reading the outputs
• Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt
• ±10 and ±20 indicate strength on a uniform scale
• EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum
• Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances
⸻
Data handling, repainting, and performance
• Daily and weekly series are fetched with request.security().
• Calculations use closed bars, values can update until the bar closes.
• No lookahead, historical values do not repaint.
• Weekly correlation updates during the week, it finalizes on weekly close.
• On intraday charts most visuals are hidden by design.
⸻
Good practice and limitations
• This is a research indicator, not a trading system.
• The fixed Cap = 20 keeps a common scale, extreme moves will be clipped.
• Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed.
⸻
Credits
Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script.
⸻
Changelog
• First version
⸻
Disclaimer
For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
Indian market session on Gift Nifty chartsGift Nifty Market Session Highlighter
This indicator highlights the official Indian market session on Gift Nifty charts — from 9:15 AM to 3:30 PM IST. It shades the background during this time window so traders can instantly identify when the local market is open.
Features:
Marks 9:15 AM to 3:30 PM (IST) session on intraday charts.
Adjustable highlight color and transparency.
Works seamlessly across lower timeframes (1m, 5m, 15m, etc.).
Helps traders align Gift Nifty activity with NSE market hours.
Use Cases:
Quickly distinguish active market hours from overnight or global sessions.
Backtest trading strategies specific to Indian session volatility.
Improv
e focus on expiry-day setups and intraday opportunities.
Disclaimer:
This tool is provided for educational and informational purposes only. It is not financial advice, nor does it guarantee trading success. Always do your own research and consult a licensed financial professional before making investment decisions.
Session Open Candle MarkerThe "Session Open Candle Marker" is a Pine Script indicator designed for forex and futures traders using Smart Money Concepts (SMC) and RP Profits-inspired strategies. It marks the 15-minute opening range candles for the Asia, London, and NY sessions, where institutional "big players" often gather liquidity. Each session’s range is drawn as a rectangle with a customizable midpoint line, ideal for spotting breakouts, retests, and liquidity sweeps.
Features
Session Open Ranges: Plots rectangles for the 15m open candles of Asia (03:00 EEST), London (10:00 EEST), and NY (15:00 EEST), corresponding to 01:00, 08:00, and 13:00 GMT+1.
Customizable Visualization:
Toggle each session (Asia, London, NY) on/off.
Independent high/low label toggles for each session.
Adjustable rectangle color, midpoint line color, style (solid/dashed/dotted), and width.
Customizable rectangle duration (default: 96 bars, ~24 hours on 15m).
Timezone Flexibility: Default times are set for EEST (UTC+3). Adjust session inputs for your chart’s timezone (e.g., GMT+1: Asia 01:00, London 08:00, NY 13:00; UTC: Asia 00:00, London 07:00, NY 12:00).
Clean Design: Rectangles and labels update dynamically, with proper cleanup to avoid clutter.
Usage:
Setup: Add to a 15m chart (e.g., EURUSD, ES1!). Check your chart’s timezone (Chart Settings > Symbol > Timezone) and adjust session times if needed.
Settings:
Toggle sessions and labels to focus on desired ranges (e.g., London and NY for high volatility).
Customize colors, midpoint line style/width, and rectangle duration.
Trading:
Breakouts/Retests: Trade breakouts above/below the rectangle high/low, with retests back to the range or midpoint (aligned with RP Profits scalping).
Liquidity Sweeps: Watch for price sweeping session highs/lows, reversing for entries (SMC concept).
Custom ORBIT — GSK-VIZAG-AP-INDIA 📌 Description
Custom ORBIT — Opening Range Breakout Indicator Tool
Created by GSK-VIZAG-AP-INDIA
This indicator calculates and visualizes the Opening Range (OR) of the trading session, with customizable start/end times and flexible range duration. The Opening Range is defined by the highest and lowest prices during the selected initial market window.
🔹 Key Features:
User-defined Opening Range duration (default: 15 minutes from 9:15).
Adjustable session start and end times.
Plots Opening Range High (ORH) and Opening Range Low (ORL).
Extends OR levels across the session with multiple line style options (Dotted, Dashed, Solid, Smoothed).
Highlights breakouts (price crossing above/below OR) and reversals (price returning back inside).
Simple chart markers (triangles/labels) for quick visual recognition.
⚠️ Disclaimer:
This tool is intended for educational and analytical purposes only. It does not generate buy/sell signals or provide financial advice. Always use independent analysis and risk management.
CM Indicator About Indicator:-
1) This is best Indicator for trend identification.
2) This is based on 42 EMA with Upper Band and Lower bands for trend identification.
3) This should be used for Line Bar chart only.
4) Line bar chart should be used at 1 hour for 15 line breaks.
How to Use:-
1) To go with trend is best use of this indicator.
2) This is for stocks and options not for index. Indicator used for Stocks at one hour and options for 10-15 minutes line break.
3) There will be 5% profitability defined for each entry, 3 entries with profit are best posible in same continuous trend 4 and 5th entry is in riskier zone in continuous trend.
4) Loss will only happen if there is trend reversal.
5) Loss could only be one trade of profit out of three profitable trades.
6) Back tested on 200 stocks and 100 options.
TIKOLE SVM Sentiment Combo Oscillator MACD"This one has MACD and RSI. Accuracy is very good. Best for 5-minute and 15-minute timeframes."
The script combines MACD-style histogram with RSI logic.
It gives high accuracy signals.
Works best on 5-minute and 15-minute charts (scalping + intraday).
⚡MACD (fast EMA / slow EMA) into the same script along with your RSI sentiment oscillator, so you’ll get a dual-confirmation system (RSI sentiment + MACD crossover + histogram).
TIKOLE SVM Sentiment Combo Oscillator MACD"This one has MACD and RSI. Accuracy is very good. Best for 5-minute and 15-minute timeframes."
So basically, you mean:
The script combines MACD-style histogram with RSI logic.
It gives high accuracy signals.
Works best on 5-minute and 15-minute charts (scalping + intraday).
⚡ If you want, I can also add MACD (fast EMA / slow EMA) into the same script along with your RSI sentiment oscillator, so you’ll get a dual-confirmation system (RSI sentiment + MACD crossover + histogram).
Mikula's Master 360° Square of 12Mikula’s Master 360° Square of 12
An educational W. D. Gann study indicator for price and time. Anchor a compact Square of 12 table to a start point you choose. Begin from a bar’s High or Low (or set a manual start price). From that anchor you can progress or regress the table to study how price steps through cycles in either direction.
What you’re looking at :
Zodiac rail (far left): the twelve signs.
Degree rail: 24 rows in 15° steps from 15° up to 360°/0°.
Transit rail and Natal rail: track one planet per rail. Each planet is placed at its current row (℞ shown when retrograde). As longitude advances, the planet climbs bottom → top, then wraps to the bottom at the next sign; during retrograde it steps downward.
Hover a planet’s cell to see a tooltip with its exact longitude and sign (e.g., 152.4° ♌︎). The linked price cell in the grid moves with the planet’s row so you can follow a planet’s path through the zodiac as a path through price.
Price grid (right): the 12×24 Square of 12. Each column is a cycle; cells are stepped price levels from your start price using your increment.
Bottom rail: shows the current square number and labels the twelve columns in that square.
How the square is read
The square always begins at the bottom left. Read each column bottom → top. At the top, return to the bottom of the next column and read up again. One square contains twelve cycles. Because the anchor can be a High or a Low, you can progress the table upward from the anchor or regress it downward while keeping the same bottom-to-top reading order.
Iterate Square (shifting)
Iterate Square shifts the entire 12×24 grid to the next set of twelve cycles.
Square 1 shows cycles 1–12; Square 2 shows 13–24; Square 3 shows 25–36, etc.
Visibility rules
Pivot cells are table-bound. If you shift the square beyond those prices, their highlights won’t appear in the table.
A/B levels and Transit/Natal planetary lines are chart overlays and can remain visible on the table as you shift the square.
Quick use
Choose an anchor (date/time + High/Low) or enable a manual start price .
Set the increment. If you anchored with a Low and want the table to step downward from there, use a negative value.
Optional: pick Transit and Natal planets (one per rail), toggle their plots, and hover their cells for longitude/sign.
Optional: turn on A/B levels to display repeating bands from the start price.
Optional: enable swing pivots to tint matching cells after the anchor.
Use Iterate Square to shift to later squares of twelve cycles.
Examples
These are exploratory examples to spark ideas:
Overview layout (zodiac & degree rails, Transit/Natal rails, price grid)
A-levels plotted, pivots tinted on the table, real-time price highlighted
Drawing angles from the anchor using price & time read from the table
Using a TradingView Gann box along the A-levels to study reactions
Attribution & originality
This script is an original implementation (no external code copied). Conceptual credit to Patrick Mikula, whose discussion of the Master 360° Square of 12 inspired this study’s presentation.
Further reading (neutral pointers)
Patrick Mikula, Gann’s Scientific Methods Unveiled, Vol. 2, “W. D. Gann’s Use of the Circle Chart.”
W. D. Gann’s Original Commodity Course (as provided by WDGAN.com).
No affiliation implied.
License CC BY-NC-SA 4.0 (non-commercial; please attribute @Javonnii and link the original).
Dependency AstroLib by @BarefootJoey
Disclaimer Educational use only; not financial advice.
Multi-TF Trend Table (Configurable)1) What this tool does (in one minute)
A compact, multi‑timeframe dashboard that stacks eight timeframes and tells you:
Trend (fast MA vs slow MA)
Where price sits relative to those MAs
How far price is from the fast MA in ATR terms
MA slope (rising, falling, flat)
Stochastic %K (with overbought/oversold heat)
MACD momentum (up or down)
A single score (0%–100%) per timeframe
Alignment tick when trend, structure, slope and momentum all agree
Use it to:
Frame bias top‑down (M→W→D→…→15m)
Time entries on your execution timeframe when the higher‑TF stack is aligned
Avoid counter‑trend traps when the table is mixed
2) Table anatomy (each column explained)
The table renders 9 columns × 8 rows (one row per timeframe label you define).
TF — The label you chose for that row (e.g., Month, Week, 4H). Cosmetic; helps you read the stack.
Trend — Arrow from fast MA vs slow MA: ↑ if fastMA > slowMA (up‑trend), ↓ otherwise (down‑trend). Cell is green for up, red for down.
Price Pos — One‑character structure cue:
🔼 if price is above both fast and slow MAs (bullish structure)
🔽 if price is below both (bearish structure)
– otherwise (between MAs / mixed)
MA Dist — Distance of price from the fast MA measured in ATR multiples:
XS < S < M < L < XL according to your thresholds (see §3.3). Useful for judging stretch/mean‑reversion risk and stop sizing.
MA Slope — The fast MA one‑bar slope:
↑ if fastMA - fastMA > 0
↓ if < 0
→ if = 0
Stoch %K — Rounded %K value (default 14‑1‑3). Background highlights when it aligns with the trend:
Green heat when trend up and %K ≤ oversold
Red heat when trend down and %K ≥ overbought Tooltip shows K and D values precisely.
Trend % — Composite score (0–100%), the dashboard’s confidence for that timeframe:
+20 if trendUp (fast>slow)
+20 if fast MA slope > 0
+20 if MACD up (signal definition in §2.8)
+20 if price above fast MA
+20 if price above slow MA
Background colours:
≥80 lime (strong alignment)
≥60 green (good)
≥40 orange (mixed)
<40 grey (weak/contrary)
MACD — 🟢 if EMA(12)−EMA(26) > its EMA(9), else 🔴. It’s a simple “momentum up/down” proxy.
Align — ✔ when everything is in gear for that trend direction:
For up: trendUp and price above both MAs and slope>0 and MACD up
For down: trendDown and price below both MAs and slope<0 and MACD down Tooltip spells this out.
3) Settings & how to tune them
3.1 Timeframes (TF1–TF8)
Inputs: TF1..TF8 hold the resolution strings used by request.security().
Defaults: M, W, D, 720, 480, 240, 60, 15 with display labels Month, Week, Day, 12H, 8H, 4H, 1H, 15m.
Tips
Keep a top‑down funnel (e.g., Month→Week→Day→H4→H1→M15) so you can cascade bias into entries.
If you scalp, consider D, 240, 120, 60, 30, 15, 5, 1.
Crypto weekends: consider 2D in place of W to reflect continuous trading.
3.2 Moving Average (MA) group
Type: EMA, SMA, WMA, RMA, HMA. Changes both fast & slow MA computations everywhere.
Fast Length: default 20. Shorten for snappier trend/slope & tighter “price above fast” signals.
Slow Length: default 200. Controls the structural trend and part of the score.
When to change
Swing FX/equities: EMA 20/200 is a solid baseline.
Mean‑reversion style: consider SMA 20/100 so trend flips slower.
Crypto/indices momentum: HMA 21 / EMA 200 will read slope more responsively.
3.3 ATR / Distance group
ATR Length: default 14; longer makes distance less jumpy.
XS/S/M/L thresholds: define the labels in column MA Dist. They are compared to |close − fastMA| / ATR.
Defaults: XS 0.25×, S 0.75×, M 1.5×, L 2.5×; anything ≥L is XL.
Usage
Entries late in a move often occur at L/XL; consider waiting for a pullback unless you are trading breakouts.
For stops, an initial SL around 0.75–1.5 ATR from fast MA often sits behind nearby noise; use your plan.
3.4 Stochastic group
%K Length / Smoothing / %D Smoothing: defaults 14 / 1 / 3.
Overbought / Oversold: defaults 70 / 30 (adjust to 80/20 for trendier assets).
Heat logic (column Stoch %K): highlights when a pullback aligns with the dominant trend (oversold in an uptrend, overbought in a downtrend).
3.5 View
Full Screen Table Mode: centers and enlarges the table (position.middle_center). Great for clean screenshots or multi‑monitor setups.
4) Signal logic (how each datapoint is computed)
Per‑TF data (via a single request.security()):
fastMA, slowMA → based on your MA Type and lengths
%K, %D → Stoch(High,Low,Close,kLen) smoothed by kSmooth, then %D smoothed by dSmooth
close, ATR(atrLen) → for structure and distance
MACD up → (EMA12−EMA26) > EMA9(EMA12−EMA26)
fastMA_prev → yesterday/previous‑bar fast MA for slope
TrendUp → fastMA > slowMA
Price Position → compares close to both MAs
MA Distance Label → thresholds on abs(close − fastMA)/ATR
Slope → fastMA − fastMA
Score (0–100) → sum of the five 20‑point checks listed in §2.7
Align tick → conjunction of trend, price vs both MAs, slope and MACD (see §2.9)
Important behaviour
HTF values are sampled at the execution chart’s bar close using Pine v6 defaults (no lookahead). So the daily row updates only when a daily bar actually closes.
5) How to trade with it (playbooks)
The table is a framework. Entries/exits still follow your plan (e.g., S/D zones, price action, risk rules). Use the table to know when to be aggressive vs patient.
Playbook A — Trend continuation (pullback entry)
Look for Align ✔ on your anchor TFs (e.g., Week+Day both ≥80 and green, Trend ↑, MACD 🟢).
On your execution TF (e.g., H1/H4), wait for Stoch heat with the trend (oversold in uptrend or overbought in downtrend), and MA Dist not at XL.
Enter on your trigger (break of pullback high/low, engulfing, retest of fast MA, or S/D first touch per your plan).
Risk: consider ATR‑based SL beyond structure; size so 0.25–0.5% account risk fits your rules.
Trail or scale at M/L distances or when score deteriorates (<60).
Playbook B — Breakout with confirmation
Mixed stack turns into broad green: Trend % jumps to ≥80 on Day and H4; MACD flips 🟢.
Price Pos shows 🔼 across H4/H1 (above both MAs). Slope arrows ↑.
Enter on the first clean base‑break with volume/impulse; avoid if MA Dist already XL.
Playbook C — Mean‑reversion fade (advanced)
Use only when higher TFs are not aligned and the row you trade shows XL distance against the higher‑TF context. Take quick targets back to fast MA. Lower win‑rate, faster management.
Playbook D — Top‑down filter for Supply/Demand strategy
Trade first retests only in the direction where anchor TFs (Week/Day) have Align ✔ and Trend % ≥60. Skip counter‑trend zones when the stack is red/green against you.
6) Reading examples
Strong bullish stack
Week: ↑, 🔼, S/M, slope ↑, %K=32 (green heat), Trend 100%, MACD 🟢, Align ✔
Day: ↑, 🔼, XS/S, slope ↑, %K=45, Trend 80%, MACD 🟢, Align ✔
Action: Look for H4/H1 pullback into demand or fast MA; buy continuation.
Late‑stage thrust
H1: ↑, 🔼, XL, slope ↑, %K=88
Day/H4: only 60–80%
Action: Likely overextended on H1; wait for mean reversion or multi‑TF alignment before chasing.
Bearish transition
Day flips from 60%→40%, Trend ↓, MACD turns 🔴, Price Pos “–” (between MAs)
Action: Stand aside for longs; watch for lower‑high + Align ✔ on H4/H1 to join shorts.
7) Practical tips & pitfalls
HTF closure: Don’t assume a daily row changed mid‑day; it won’t settle until the daily bar closes. For intraday anticipation, watch H4/H1 rows.
MA Type consistency: Changing MA Type changes slope/structure everywhere. If you compare screenshots, keep the same type.
ATR thresholds: Calibrate per asset class. FX may suit defaults; indices/crypto might need wider S/M/L.
Score ≠ signal: 100% does not mean “must buy now.” It means the environment is favourable. Still execute your trigger.
Mixed stacks: When rows disagree, reduce size or skip. The tool is telling you the market lacks consensus.
8) Customisation ideas
Timeframe presets: Save layouts (e.g., Swing, Intraday, Scalper) as indicator templates in TradingView.
Alternative momentum: Replace the MACD condition with RSI(>50/<50) if desired (would require code edit).
Alerts: You can add alert conditions for (a) Align ✔ changes, (b) Trend % crossing 60/80, (c) Stoch heat events. (Not shipped in this script, but easy to add.)
9) FAQ
Q: Why do I sometimes see a dash in Price Pos? A: Price is between fast and slow MAs. Structure is mixed; seek clarity before acting.
Q: Does it repaint? A: No, higher‑TF values update on the close of their own bars (standard request.security behaviour without lookahead). Intra‑bar they can fluctuate; decisions should be made at your bar close per your plan.
Q: Which columns matter most? A: For trend‑following: Trend, Price Pos, Slope, MACD, then Stoch heat for entries. The Score summarises, and Align enforces discipline.
Q: How do I integrate with ATR‑based risk? A: Use the MA Dist label to avoid chasing at extremes and to size stops in ATR terms (e.g., SL behind structure at ~1–1.5 ATR).
Impulse Convexity Trend Gate [T1][T69]OVERVIEW 🧭
• A price-only trend engine that opens a “gate” only when trend strength, acceleration, and impulse dominance align.
• Built from three cooperating parts: adaptive slope, directional convexity, and an impulse-vs-pullback ratio.
• Output is a bounded oscillator (−100…+100) plus side-specific gate states (bull/bear), with optional pullback and weakness highlights.
THE IDEA & USEFULNESS 🧪
• Not a simple mashup: each component plays a distinct role—slope for direction, convexity for acceleration agreement, and an impulse ratio to suppress correction noise.
• Adaptive EMA length (series-based) lets the midline adjust to conditions without external indicators.
• Approximation of hyperbolic tangent and clamp keep signals bounded and stable while avoiding library dependencies.
• Designed to help trend traders act only when continuation is likely, and stand down during pullbacks or chop.
HOW IT WORKS (PIPELINE) ⚙️
• Price transform
• Uses log price for scale stability.
• Adaptive midline
• Volatility-aware EMA length is clamped between minimum and maximum, then applied via a custom recursive EMA.
• Slope & convexity
• Slope (first difference of the midline) defines direction; convexity (second difference) verifies acceleration agrees with that direction.
• Impulse vs pullback ratio (R)
• Sums directional progress versus counter-direction pullbacks over a window; requires impulse to dominate.
• Normalization & score
• Slope and convexity are normalized by recent dispersion; combined into a raw score and squashed to −100…+100 using manual tanh.
• Trend gate
• Gate opens only when: R ≥ threshold, |normalized slope| ≥ threshold, and slope/convexity share the same sign.
• States & visuals
• Bull/Bear Gate Entry when gate is open, oscillator crosses ±15 in the correct direction, price is on the correct side of the midline, and slope/convexity agree.
• Pullbacks mark counter-moves while a gate is active; Weakness flags specific fade patterns after pullbacks.
FEATURES ✨
• Bull and Bear Gate Entries (green/red columns).
• Pullback shading and optional trend-weakness highlights (yellow/orange + teal/maroon).
• Background tint reflects the active side (bull or bear).
• Pure price logic; no volume or external filters required.
HOW TO USE 🎯
• Regime filter
• Trade only in the direction of the open gate; ignore signals when the gate is closed.
• Pullback entries
• During an open gate, wait for a pullback zone, then act on trend-resumption (e.g., oscillator re-push through ±15 or structure break in gate direction).
• Exits & risk
• Consider trimming when the oscillator relaxes toward 0 while the gate remains open, or when convexity flips against slope and R deteriorates.
• Timeframes & markets
• Suited for trend following on crypto/FX/indices from M30 to 4H/1D; raise thresholds on lower timeframes to reduce noise.
CONFIGURATION 🔧
• Impulse ratio gate (R ≥): raises/lowers the standard for continuation dominance.
• Slope strength gate (|sN| ≥): controls how strong a slope must be to count.
• Show Pullback Impulse (toggle): enable/disable pullback highlights.
• Show Trend Weakness (toggle): enable/disable weakness flags.
LIMITATIONS ⚠️
• As a trend tool, it can lag at regime transitions; expect whipsaws in tight ranges.
• Parameters are instrument- and timeframe-dependent; tune thresholds before live use.
• Pullback/weakness flags are contextual—not trade signals by themselves; use them with gate state and your execution rules.
ADVANCED TIPS 🛠️
• Tighten R and slope thresholds for lower timeframes; loosen for higher timeframes.
• Pair with NNFX-style money management and pair-level filters; let the gate be the confirmation layer, not the entry trigger by itself.
• Batch-test across 100+ symbols, export metrics, and run Monte Carlo to validate LLN reliability and Sharpe/IQR stability.
• For system hedging, disable entries when both sides trigger on the same asset to avoid internal conflict.
NOTES 📝
• Price-only construction reduces data-vendor differences and keeps behavior consistent across markets.
• Manual tanh/clamp ensure stable, bounded scores even during extremes.
DISCLAIMER 🛡️
• For research and education. No financial advice. Test thoroughly, size conservatively, and respect your risk rules.
Ruptura + EMAs + VWAP + Vela Impulsiva Indicator: Breakout + EMAs + VWAP + Impulsive Candle + TP/SL
This indicator is designed to identify breakout trading opportunities by combining price action, moving averages, volume-weighted price, and impulsive candles, with clearly defined Take Profit (TP) and Stop Loss (SL) levels.
⏱️ Timeframe Logic:
The 15-minute chart is used to define the price range.
Entries are made on the 2-minute chart when breakout conditions align with momentum confirmation.
📌 Key Components:
Range Definition:
Calculates a price range based on a customizable number of candles (rangeBars), typically from the 15-minute timeframe.
Displays a shaded box highlighting this range.
Trend Filters:
Uses a fast EMA (9) and a slow EMA (21) to determine short-term and medium-term trends.
Includes VWAP as a dynamic support/resistance and directional filter.
Only allows trades when both EMAs and price confirm alignment above (for long) or below (for short) the VWAP.
Impulsive Candle Detection:
Confirms breakouts using large-bodied candles that engulf the previous candle's range.
The candle must exceed a certain multiple of the average range (minRangeMult) to qualify.
Breakout Entry Conditions:
Long Setup: Price breaks above the range high, with EMAs and VWAP confirming bullish alignment, and confirmed by an impulsive candle.
Short Setup: Price breaks below the range low, with EMAs and VWAP aligned bearishly, confirmed by an impulsive candle.
Trade Management:
Automatically plots Take Profit and Stop Loss levels based on the size of the entry candle and a customizable TP multiplier.
Visual dashed lines indicate TP (green) and SL (red) zones.
Session Filter:
Entry signals are limited to a specific time window (e.g., 9:00 to 10:00 AM New York time), typically during the NY session open.
Visual Aids:
Background color highlights potential entry zones (green for long, red for short).
Icons mark confirmed impulsive candles and entry signals.
Range box is updated periodically to reflect the active breakout zone.
Script de código abierto
Siguiendo fielmente el espíritu de TradingView, el creador de este script lo ha publicado en código abierto, permitiendo que otros traders puedan revisar y verificar su funcionalidad. ¡Enhorabuena al autor! Puede utilizarlo de forma gratuita, pero tenga en cuenta que la publicación de este código está sujeta a nuestras Normas internas.
Chart-Only Scanner — Pro Table v2.5.1Chart-Only Scanner — Pro Table v2.5
User Manual (Pine Script v6)
What this tool does (in one line)
A compact, on-chart table that scores the current chart symbol (or an optional override) using momentum, volume, trend, volatility, and pattern checks—so you can quickly decide UP, DOWN, or WAIT.
Quick Start (90 seconds)
Add the indicator to any chart and timeframe (1m…1M).
Leave “Override chart symbol” = OFF to auto-use the chart’s symbol.
Choose your layout:
Row (wide horizontal strip), or Grid (title + labeled cells).
Pick a size preset (Micro, Small, Medium, Large, Mobile).
Optional: turn on “Use Higher TF (EMA 20/50)” and set HTF Multiplier (e.g., 4 ⇒ if chart is 15m, HTF is 60m).
Watch the table:
DIR (↑/↓/→), ROC%, MOM, VOL, EMA stack, HTF, REV, SCORE, ACT.
Add an alert if you want: the script fires when |SCORE| ≥ Action threshold.
What to expect
A small table appears on the chart corner you choose, updating each bar (or only at bar close if you keep default smart-update).
The ACT cell shows 🔥 (strong), 👀 (medium), or ⏳ (weak).
Panels & Settings (every option explained)
Core
Momentum Period: Lookback for rate-of-change (ROC%). Shorter = more reactive; longer = smoother.
ROC% Threshold: Minimum absolute ROC% to call direction UP (↑) or DOWN (↓); otherwise →.
Require Volume Confirmation: If ON and VOL ≤ 1.0, the SCORE is forced to 0 (prevents low-volume false positives).
Override chart symbol + Custom symbol: By default, the indicator uses the chart’s symbol. Turn this ON to lock to a specific ticker (e.g., a perpetual).
Higher TF
Use Higher TF (EMA 20/50): Compares EMA20 vs EMA50 on a higher timeframe.
HTF Multiplier: Higher TF = (chart TF × multiplier).
Example: on 3H chart with multiplier 2 ⇒ HTF = 6H.
Volatility & Oscillators
ATR Length: Used to show ATR% (ATR relative to price).
RSI Length: Standard RSI; colors: green ≤30 (oversold), red ≥70 (overbought).
Stoch %K Length: With %D = SMA(%K, 3).
MACD Fast/Slow/Signal: Standard MACD values; we display Line, Signal, Histogram (L/S/H).
ADX Length (Wilder): Wilder’s smoothing (internal derivation); also shows +DI / −DI if you enable the ADX column.
EMAs / Trend
EMA Fast/Mid/Slow: We compute EMA(20/50/200) by default (editable).
EMA Stack: Bull if Fast > Mid > Slow; Bear if Fast < Mid < Slow; Flat otherwise.
Benchmark (optional, OFF by default)
Show Relative Strength vs Benchmark: Displays RS% = ROC(symbol) − ROC(benchmark) over the Momentum Period.
Benchmark Symbol: Ticker used for comparison (e.g., BTCUSDT as a market proxy).
Columns (show/hide)
Toggle which fields appear in the table. Hiding unused fields keeps the layout clean (especially on mobile).
Display
Layout Mode:
Row = a single two-row strip; each column is a metric.
Grid = a title row plus labeled pairs (label/value) arranged in rows.
Size Preset: Micro, Small, Medium, Large, Mobile change text size and the grid density.
Table Corner: Where the panel sits (e.g., Top Right).
Opaque Table Background: ON = dark card; OFF = transparent(ish).
Update Every Bar: ON = update intra-bar; OFF = smart update (last bar / real-time / confirmed history).
Action threshold (|score|): The cutoff for 🔥 and alert firing (default 70).
How to read each field
CHART: The active symbol name (or your custom override).
DIR: ↑ (ROC% > threshold), ↓ (ROC% < −threshold), → otherwise.
ROC%: Rate of change over Momentum Period.
Formula: (Close − Close ) / Close × 100.
MOM: A scaled momentum score: min(100, |ROC%| × 10).
VOL: Volume ratio vs 20-bar SMA: Volume / SMA(Volume,20).
1.5 highlights as yellow (significant participation).
ATR%: (ATR / Close) × 100 (volatility relative to price).
RSI: Colored for extremes: ≤30 green, ≥70 red.
Stoch K/D: %K and %D numbers.
MACD L/S/H: Line, Signal, Histogram. Histogram color reflects sign (green > 0, red < 0).
ADX, +DI, −DI: Trend strength and directional components (Wilder). ADX ≥ 25 is highlighted.
EMA 20/50/200: Current EMA values (editable lengths).
STACK: Bull/Bear/Flat as defined above.
VWAP%: (Close − VWAP) / Close × 100 (premium/discount to VWAP).
HTF: ▲ if HTF EMA20 > EMA50; ▼ if <; · if flat/off.
RS%: Symbol’s ROC% − Benchmark ROC% (positive = outperforming).
REV (reversal):
🟢 Eng/Pin = bullish engulfing or bullish pin detected,
🔴 Eng/Pin = bearish engulfing or bearish pin,
· = none.
SCORE (absolute shown as a number; sign shown via DIR and ACT):
Components:
base = MOM × 0.4
volBonus = VOL > 1.5 ? 20 : VOL × 13.33
htfBonus = use_mtf ? (HTF == DIR ? 30 : HTF == 0 ? 15 : 0) : 0
trendBonus = (STACK == DIR) ? 10 : 0
macdBonus = 0 (placeholder for future versions)
scoreRaw = base + volBonus + htfBonus + trendBonus + macdBonus
SCORE = DIR ≥ 0 ? scoreRaw : −scoreRaw
If Require Volume Confirmation and VOL ≤ 1.0 ⇒ SCORE = 0.
ACT:
🔥 if |SCORE| ≥ threshold
👀 if 50 < |SCORE| < threshold
⏳ otherwise
Practical examples
Strong long (trend + participation)
DIR = ↑, ROC% = +3.2, MOM ≈ 32, VOL = 1.9, STACK = Bull, HTF = ▲, REV = 🟢
SCORE: base(12.8) + volBonus(20) + htfBonus(30) + trend(10) ≈ 73 → ACT = 🔥
Action idea: look for longs on pullbacks; confirm risk with ATR%.
Weak long (no volume)
DIR = ↑, ROC% = +1.0, but VOL = 0.8 and Require Volume Confirmation = ON
SCORE forced to 0 → ACT = ⏳
Action: wait for volume > 1.0 or turn off confirmation knowingly.
Bearish reversal warning
DIR = →, REV = 🔴 (bearish engulfing), RSI = 68, HTF = ▼
SCORE may be mid-range; ACT = 👀
Action: watch for breakdown and rising VOL.
Alerts (how to use)
The script calls alert() whenever |SCORE| ≥ Action threshold.
To receive pop-ups, sounds, or emails: click “⏰ Alerts” in TradingView, choose this indicator, and pick “Any alert() function call.”
The alert message includes: symbol, |SCORE|, DIR.
Layout, Size, and Corner tips
Row is best when you want a compact status ribbon across the top.
Grid is clearer on big screens or when you enable many columns.
Size:
Mobile = one pair per row (tall, readable)
Micro/Small = dense; good for many fields
Large = presentation/screenshots
Corner: If the table overlaps price, change the corner or set Opaque Background = OFF.
Repaint & timeframe behavior
Default smart update prefers stability (last bar / live / confirmed history).
For a stricter, “close-only” behavior (less repaint): turn Update Every Bar = OFF and avoid Heikin Ashi when you want raw market OHLC (HA modifies price inputs).
HTF logic is derived from a clean, integer multiple of your chart timeframe (via multiplier). It works with 3H/4H and any TF.
Performance notes
The script analyzes one symbol (chart or override) with multiple metrics using efficient tuple requests.
If you later want a multi-symbol grid, do it with pages (10–15 per page + rotate) to stay within platform limits (recommended future add-on).
Troubleshooting
No table visible
Ensure the indicator is added and not hidden.
Try toggling Opaque Background or switch Corner (it might be behind other drawings).
Keep Columns count reasonable for the chosen Size.
If you turned ON Override, verify the Custom symbol exists on your data provider.
Numbers look different on HA candles
Heikin Ashi modifies OHLC; switch to regular candles if you need raw price metrics.
3H/4H issues
Use integer HTF Multiplier (e.g., 2, 4). The tool builds the correct string internally; no manual timeframe strings needed.
Power user tips
Volume gating: keeping Require Volume Confirmation = ON filters most fake moves; if you’re a scalper, reduce strictness or turn it off.
Action threshold: 60–80 is typical. Higher = fewer but stronger signals.
Benchmark RS%: great for spotting leaders/laggards; positive RS% = outperformance vs benchmark.
Change policy & safety
This version doesn’t alter your historical logic you tested (no radical changes).
Any future “radical” change (score weights, HTF logic, UI hiding data) will ship with a toggle and an Impact Statement so you can keep old behavior if you prefer.
Glossary (quick)
ROC%: Percent change over N bars.
MOM: Scaled momentum (0–100).
VOL ratio: Volume vs 20-bar average.
ATR%: ATR as % of price.
ADX/DI: Trend strength / direction components (Wilder).
EMA stack: Relationship between EMAs (bullish/bearish/flat).
VWAP%: Premium/discount to VWAP.
RS%: Relative strength vs benchmark.
Open Range Breakout Strategy With Multi TakeProfitHello everyone,
For a while, I’ve been wanting to develop new scripts, but I couldn’t decide what to create. Eventually, I came up with the idea of coding traditional and well-known trading strategies—while adding modern features such as multi–take profit options. For the first strategy in this series, I chose the Open Range Strategy .
For those unfamiliar with it, the Open Range Strategy is a trading approach where you define a specific time period at the beginning of a trading session—such as the first 15 minutes, 30 minutes, or 1 hour—and mark the highest and lowest prices within that range. These levels then act as reference points for potential breakouts: if the price breaks above the range, it may signal a long entry; if it breaks below, it may indicate a short entry. This method is popular among day traders for capturing early momentum in the market.
Since this strategy is generally used as an intraday strategy , I added a Trade Session feature. This allows you to define the exact time window during which trades can be opened. Once the session ends, all positions are automatically closed, ensuring trades remain within your chosen intraday period.
Even though it’s a relatively simple concept, I’ve come across many different variations of it. That’s why I created a highly customizable project. Under the Session Settings, you can select the time window you want to define as your range. Whether it’s the first 15-minute candle or the entire first hour, the choice is entirely yours.
For stop-loss placement, there are two different options:
Middle of the Range – The stop loss is placed at the midpoint between the high and low of the defined range, offering a balanced buffer for both bullish and bearish setups.
Top/Bottom of the Range – The stop loss is placed just beyond the range’s high for short trades or just below the range’s low for long trades, providing a more conservative risk approach.
I’ve always been a big fan of the multi take-profit feature, so I added two different take-profit targets to this project. Take profits are calculated based on a Risk-to-Reward Ratio, which you can adjust in the settings. You can also set different position sizes for each target, allowing you to scale out of trades in a way that suits your strategy.
The result is a flexible, user-friendly strategy script that brings together a classic approach with modern risk management tools—ready to be tailored to your trading style
Intraday Volume Pulse GSK-VIZAG-AP-INDIAIntraday Volume Pulse Indicator
Overview
This indicator is designed to track and visualize intraday volume dynamics during a user-defined trading session. It calculates and displays key volume metrics such as buy volume, sell volume, cumulative delta (difference between buy and sell volumes), and total volume. The data is presented in a customizable table overlay on the chart, making it easy to monitor volume pulses throughout the session. This can help traders identify buying or selling pressure in real-time, particularly useful for intraday strategies.
The indicator resets its calculations at the start of each new day and only accumulates volume data from the specified session start time onward. It uses simple logic to classify volume as buy or sell based on candle direction:
Buy Volume: Assigned to green (up) candles or half of neutral (doji) candles.
Sell Volume: Assigned to red (down) candles or half of neutral (doji) candles.
All calculations are approximate and based on available volume data from the chart. This script does not incorporate external data sources, order flow, or tick-level information—it's purely derived from standard OHLCV (Open, High, Low, Close, Volume) bars.
Key Features
Session Customization: Define the start time of your trading session (e.g., market open) and select from common timezones like Asia/Kolkata, America/New_York, etc.
Volume Metrics:
Buy Volume: Total volume attributed to bullish activity.
Sell Volume: Total volume attributed to bearish activity.
Cumulative Delta: Net difference (Buy - Sell), highlighting overall market bias.
Total Volume: Sum of all volume during the session.
Formatted Display: Volumes are formatted for readability (e.g., in thousands "K", lakhs "L", or crores "Cr" for large numbers).
Color-Coded Table: Uses a patriotic color scheme inspired by general themes (Saffron, White, Green) with dynamic backgrounds based on positive/negative values for quick visual interpretation.
Table Options: Toggle visibility and position (top-right, top-left, etc.) for a clean chart layout.
How to Use
Add to Chart: Apply this indicator to any symbol's chart (works best on intraday timeframes like 1-min, 5-min, or 15-min).
Configure Inputs:
Session Start Hour/Minute: Set to your market's open time (default: 9:15 for Indian markets).
Timezone: Choose the appropriate timezone to align with your trading hours.
Show Table: Enable/disable the metrics table.
Table Position: Place the table where it doesn't obstruct your view.
Interpret the Table:
Monitor for spikes in buy/sell volume or shifts in cumulative delta.
Positive delta (green) suggests buying pressure; negative (red) suggests selling.
Use alongside price action or other indicators for confirmation—e.g., high total volume with positive delta could indicate bullish momentum.
Limitations:
Volume classification is heuristic and not based on actual order flow (e.g., it splits doji volume evenly).
Data accumulation starts from the session time and resets daily; historical backtesting may be limited by the max_bars_back=500 setting.
This is for educational and visualization purposes only—do not use as sole basis for trading decisions.
Calculation Details
Session Filter: Uses timestamp() to define the session start and filters bars with time >= sessionStart.
New Day Detection: Resets volumes on daily changes via ta.change(time("D")).
Volume Assignment:
Buy: Full volume if close > open; half if close == open.
Sell: Full volume if close < open; half if close == open.
Cumulative Metrics: Accumulated only during the session.
Formatting: Custom function f_format() scales large numbers for brevity.
Disclaimer
This script is for educational and informational purposes only. It does not provide financial advice or signals to buy/sell any security. Always perform your own analysis and consult a qualified financial professional before making trading decisions.
© 2025 GSK-VIZAG-AP-INDIA
First Candle ChannelTo create a price channel on the 15-minute timeframe based on the first candle's highest and lowest points, follow these steps:
Identify the first 15-minute candle of the trading session or your observation period.
Note the high and low prices of this first candle.
Draw two horizontal lines on the chart:
The upper line at the highest price of the first candle.
The lower line at the lowest price of the first candle.
These two lines form the channel boundaries for subsequent price action.
You can use this channel to observe price movement, noting when price breaks above (bullish breakout) or below (bearish breakdown) the channel formed by the first candle.
This method creates a simple visual range reference based on the initial price movement of the session or period, often used to gauge early strength or rarity of breakout events.
915 Candle High/Low RaysDraws horizontal rays from the high and low of the first 5-minute candle for any selected date in the NSE equity session (09:15–15:30). Features include:
- Date picker for any trading day (defaults to today, exchange timezone)
- Session-limited rays (do not extend past the session end)
- Option to project levels to all timeframes
- Customizable ray style, label display, and color
- Optional breakout alerts for high/low crossing
- Designed for Indian markets and any NSE equity symbol
☑️VMA Win % Dashboard for Different LengthsVMA Win % Dashboard for Different Lengths
Overview
This Pine Script indicator evaluates the performance of a Variable Moving Average (VMA) for lengths 13 to 17. It tracks the success rate of price hitting target levels during bullish or bearish trends and displays results in a table. It is part of a combination that includes two other indicators: ✅ VMA Avg ATR + Days to Targets Total Improved 🎯 and 📊 Visual MTF VMA Dashboard🔄️.
How It Works
1. Inputs:
- ATR Length: 14 periods (for volatility).
- VMA Lengths: 13, 14, 15, 16, 17.
2. VMA Calculation:
- Uses closing price.
- Measures price increases (pdm) and decreases (mdm).
- Smooths data to calculate a Directional Movement Index (DMI).
- Adjusts VMA based on momentum and volatility.
3. Trend Detection:
- Bullish: VMA rises (green).
- Bearish: VMA falls (red).
- Neutral: No direction (white).
- Confirms trends align with daily and 195-minute timeframes.
4. Performance Tracking:
- Trend Start: Records price, ATR, and time when a trend begins.
- Price Movement: Tracks highest (bullish) or lowest (bearish) price.
- Targets:
---- T1: Starting price ± historical average movement (ATR-based).
---- T2: Starting price ± 6x ATR.
- Statistics:
---- Counts hits (reached T1/T2) and misses (didn’t reach T1).
---- Calculates win percentages: % of trends hitting T1.
5. Dashboard:
- Table with columns: VMA Length, Win % Up, Win % Down.
- Shows win percentages for each length (e.g., 75.23%).
Use Cases
- Trend Trading: Confirms trend direction and success rate.
- Optimization: Finds the best VMA length.
- Risk Management: Sets ATR-based trade targets.
- Combination: Complements ✅ VMA Avg ATR + Days to Targets Total Improved 🎯 and 📊 Visual MTF VMA Dashboard🔄️ for a complete strategy.
Example
- VMA 15: 80% Win Up, 55% Win Down → Best for bullish trades.
- VMA 13: 75% Win Up, 60% Win Down → More balanced.
Limitations
- Based on historical data, not future predictions.
- Only analyzes trends aligned with higher timeframes.
- No VMA lines or signals plotted on the chart.
