ROC / VWAP / ATR / RSI / MACD Combo//@version=5
indicator("ROC / VWAP / ATR / RSI / MACD Combo", overlay=true)
// === INPUTS ===
showROC = input.bool(true, "Show ROC")
rocLength = input.int(14, "ROC Length")
showVWAP = input.bool(true, "Show VWAP")
showATR = input.bool(true, "Show ATR")
atrLength = input.int(14, "ATR Length")
showRSI = input.bool(true, "Show RSI")
rsiLength = input.int(14, "RSI Length")
showMACD = input.bool(true, "Show MACD")
fastLen = input.int(12, "MACD Fast Length")
slowLen = input.int(26, "MACD Slow Length")
sigLen = input.int(9, "MACD Signal Length")
// === CALCULATIONS ===
// ROC
roc = ta.roc(close, rocLength)
// VWAP
vwap = ta.vwap
// ATR
atr = ta.atr(atrLength)
// RSI
rsi = ta.rsi(close, rsiLength)
// MACD
macdLine = ta.ema(close, fastLen) - ta.ema(close, slowLen)
signal = ta.ema(macdLine, sigLen)
hist = macdLine - signal
// === PLOTTING ===
// ROC (separate scale)
plot(showROC ? roc : na, title="ROC", color=color.aqua, display=display.none)
// VWAP (on chart)
plot(showVWAP ? vwap : na, title="VWAP", color=color.orange, linewidth=2)
// ATR (separate scale)
plot(showATR ? atr : na, title="ATR", color=color.red, display=display.none)
// RSI (separate scale, 0-100)
plot(showRSI ? rsi : na, title="RSI", color=color.blue, display=display.none)
hline(70, "RSI Overbought", color=color.gray, linestyle=hline.style_dotted)
hline(30, "RSI Oversold", color=color.gray, linestyle=hline.style_dotted)
// MACD (separate scale)
plot(showMACD ? macdLine : na, title="MACD Line", color=color.green, display=display.none)
plot(showMACD ? signal : na, title="Signal Line", color=color.red, display=display.none)
plot(showMACD ? hist : na, title="MACD Histogram", style=plot.style_columns, color=hist>=0 ? color.new(color.green,50) : color.new(color.red,50), display=display.none)
Padrões gráficos
goforthfx: 4EMA, Patterns, Pivots & Pin BarsMerging 4 ema, pivot standards, pin bars and 3 candle reversal indicator into one.
Use it for information purposes so to see if what is going on with the charts
VLM ALERTalert when there is unusual volume on the chart. Instead of sitting around waiting for us to go out, waiting for something to come in and see
Smart Market Structure🔹 What it does:
Detects swing highs & lows automatically
Marks Break of Structure (BOS) and Market Structure Shifts (MSS) in real time
Plots Order Blocks and auto-removes them if invalidated
Colors candles by market structure bias (bullish / bearish)
Comes with a built-in Dashboard showing:
Last BOS & MSS direction
Current trend bias
Swings since last MSS
Active Bullish/Bearish OB count
A Trend Strength Meter to gauge momentum
🔹 Goal:
To give traders a clearer picture of price action, so instead of staring at raw candles and second-guessing, you get structure + context instantly.
Source: www.reddit.com
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.
Trend Score with Dynamic Stop Loss HTF
How the Trend Score System Works
This indicator uses a Trend Score (TS) to measure price momentum over time. It tracks whether price is breaking higher or lower, then sums these moves into a cumulative score to define trend direction.
⸻
1. Trend Score (+1 / -1 Mechanism)
On each new bar:
• +1 point: if the current bar breaks the previous bar’s high.
• −1 point: if the current bar breaks the previous bar’s low.
• If both happen in the same bar, they cancel each other out.
• If neither happens, the score does not change.
This creates a simple running measure of bullish vs bearish pressure.
⸻
2. Cumulative Trend Score
The Trend Score is cumulative, meaning each new +1 or -1 is added to the total score, building a continuous count.
• Rising scores = buyers are consistently pushing price to higher highs.
• Falling scores = sellers are consistently pushing price to lower lows.
This smooths out noise and helps identify persistent momentum rather than single-bar spikes.
⸻
3. Trend Flip Trigger (default = 3)
A trend flip occurs when the cumulative Trend Score changes by 3 points (default setting) in the opposite direction of the current trend.
• Bullish Flip:
• Cumulative TS rises 3 points from its most recent low pivot.
• Marks a potential start of a new uptrend.
• A bullish stop-loss (SL) is set at the most recent swing low.
• Bearish Flip:
• Cumulative TS falls 3 points from its most recent high pivot.
• Marks a potential start of a new downtrend.
• A bearish SL is set at the most recent swing high.
Example:
• TS is at -2, then climbs to +1.
• That’s a +3 change, triggering a bullish flip.
⸻
4. Visual Summary
• Green background: Active bullish trend.
• Red background: Active bearish trend.
• ▲ Triangle Up: A bullish flip occurred this bar.
• Stop Loss Line: Shows the structural low used for risk management.
⸻
Why This Matters
The Trend Score measures trend pressure simply and objectively:
• +1 / -1 mechanics track real price behavior (breakouts of highs and lows).
• Cumulative changes of 3 points act like a momentum filter, ignoring small reversals.
• This helps you see true regime shifts on higher timeframes, which is especially useful for swing trades and investing decisions.
⸻
Key Takeaways
• Only flips after meaningful swings: prevents overreacting to single-bar noise.
• SL shows invalidation point: helps you know where a trend thesis fails.
• Works best on Daily or Weekly charts: for smoother, more reliable signals. Using Trend Score for Long-Term Investing
This indicator is designed to support decision-making for higher timeframe investing, such as swing trades, multi-month positions, or even multi-year holds.
It helps you:
• Identify major bullish regimes.
• Decide when to add to winning positions (DCA up).
• Know when to pause buying or consider trimming during weak periods.
• Stay disciplined while holding long-term winners.
Important Note:
These are suggestions for context. Always combine them with your own analysis, portfolio allocation rules, and risk tolerance.
⸻
1. Start With the Higher Timeframe
• Use Weekly charts for a broad investing view.
• Use Daily charts only for fine-tuning entry points or deciding when to add.
• A Bullish Flip on Weekly suggests the market may be entering a major uptrend.
• If Weekly is bullish and Daily also turns bullish, it’s extra confirmation of strength.
⸻
2. Building a Position with DCA
Goal: Grow your position gradually during strong bullish regimes while staying aware of risk.
A. Initial Buy
• Start with a small initial allocation when a Bullish Flip appears on Weekly or Daily.
• This is just a starter position to get exposure while the new trend develops.
B. Adding Through Strength (DCA Up)
• Consider adding during pullbacks, as long as price stays above the active SL line.
• Each add should be smaller or equal to your first buy.
• Spread out adds over time or price levels, instead of going all-in at once.
C. Pause Buying When:
• Price approaches or touches the SL level (trend invalidation).
• A Bearish Flip appears on Weekly or Daily — this signals potential weakness.
• Your total position size reaches your maximum allocation limit for that asset.
⸻
3. Holding Winners
When a position grows in profit:
• Stay in the trend as long as the Weekly regime remains bullish.
• The indicator’s green background acts as a reminder to hold, not panic sell.
• Use the SL bubble to monitor where the trend could potentially break.
• Avoid selling just because of small pullbacks — focus on big-picture trend health.
⸻
4. Taking Partial Profits
While this tool is designed to help hold long-term winners, there may be times to lighten risk:
• After large, rapid moves far above the SL, consider trimming a small portion of your position.
• When MFE (Maximum Favorable Excursion) in the table reaches unusually high levels, it may signal overextension.
• If the Weekly chart turns Neutral or Bearish, you can gradually reduce exposure while waiting for the next Bullish Flip.
⸻
5. Using the Stop Loss Line for Awareness
The Dynamic SL line represents a structural level that, if broken, may suggest the bullish trend is weakening.
How to think about it:
• Above SL: Market remains structurally healthy — continue holding or adding gradually.
• Close to SL: Pause adds. Be cautious and consider tightening your risk.
• Below SL: Treat this as a potential signal to reassess your position, especially if the break is confirmed on Weekly.
The SL is not a hard stop — it’s a visual guide to help you manage expectations.
⸻
6. Example Use Case
Imagine you are investing in a growth stock:
• Weekly Bullish Flip: You open a small starter position.
• Price pulls back slightly but stays above SL: You add a second, smaller tranche.
• Trend continues up for months: You hold and stop adding once your desired allocation is reached.
• Price doubles: You trim 10–20% to lock some profits, but continue holding the majority.
• Price later dips below SL: You slow down, reassess, and decide whether to reduce exposure.
This keeps you:
• Participating in major uptrends.
• Avoiding overcommitment during weak phases.
• Making adjustments gradually, not emotionally.
⸻
7. Suggested Workflow
1. Check Weekly chart → is it Bullish?
2. If yes, review Daily chart to fine-tune entry or adds.
3. Build exposure gradually while Weekly remains bullish.
4. Watch SL bubbles as awareness points for risk management.
5. Use partial trims during big rallies, but avoid exiting entirely too soon.
6. Reassess if Weekly turns Neutral or Bearish.
⸻
Key Takeaways
• Use this as a compass, not a command system.
• Weekly flips = big picture direction.
• Daily flips = timing and precision.
• Add gradually (DCA) while above SL, pause near SL, reassess below SL.
• Hold winners as long as Weekly remains bullish.
4H Range Breakout Strategy — ETH 4H optimized + dynamic stop4H Range Breakout Strategy — ETH Optimized + Risk Management + Forecast
This strategy trades 4H range breakouts on ETH, using the previous confirmed 4-hour candle as the reference range. It combines multi-timeframe context, professional risk management, and a Forecast Engine that sketches likely future paths based on dynamic support/resistance and trend conditions.
Key Features
4H Breakout Logic
Long when price breaks above the prior 4H high; short when it breaks below the prior 4H low.
Optional trend filter (Daily EMA200 + ADX) plus volatility/volume filters to reduce false signals.
Advanced Risk Management
Stop via ATR or fixed percent.
Take-profit via R-multiple, ATR-multiple, or percent.
Scale-out at TP1 (default 60%).
Chandelier-style ATR trailing stop.
Fixed-Risk Position Sizing: each trade risks a fixed % of equity (e.g., 0.5%) for consistent sizing across varying volatility.
Prop-Firm Style Kill Switch
Daily loss cap (% of equity).
Trade halt after N consecutive losses.
Automatic cool-off for a set number of bars.
Optional reset at the start of each trading day.
Auto Regime Engine
Classifies market as Trend, Range, High-Vol, or Neutral using ADX, EMA slope, and ATR Z-score.
Dynamically adjusts buffers, stops, targets, and trailing according to the active regime.
Forecast Path (Scenario Planning)
Draws bullish/bearish path candidates using nearest HTF support/resistance (pivot-based, non-repainting).
Includes an evaluation panel tracking hits/misses to monitor scenario quality over time.
How to Use
Primary timeframes: ETH 1H or 4H (optimized for ETH but adaptable).
Choose a preset (e.g., ETH 4H Optimized or Prop-Firm) or fine-tune inputs.
The Forecast module does not predict; it visualizes conditional paths to aid trade planning and post-analysis.
For robust testing, run backtests across multiple market regimes and review the evaluation panel.
Notes & Best Practices
Combine with higher-timeframe context (Daily/Weekly levels) and news/flow awareness.
Keep risk per trade modest (e.g., 0.25–1.0% of equity).
Consider disabling entries during extremely low volume or during major news releases.
Disclaimer
This script is for educational and research purposes. Trading involves substantial risk. Past results do not guarantee future returns. Always test thoroughly and trade responsibly.
Trend Score with Dynamic Stop Loss RTH
📘 Trend Score with Dynamic Stop Loss (RTH) — Guide
🔎 Overview
This indicator tracks intraday momentum during Regular Trading Hours and flags trend flips using a cumulative TrendScore. It also draws dynamic stop-loss levels and shows a live stats table for quick decision-making and journaling.
⸻
⚙️ Core Concepts
1) TrendScore (per bar)
• +1 if the current bar makes a higher high than the previous bar (counted once per bar).
• –1 if the current bar makes a lower low than the previous bar (counted once per bar).
• If a bar takes both the prior high and low, the net contribution can cancel out within that bar.
2) Cumulative TrendScore (running total)
• The per-bar TrendScore accumulates across the session to form the cumulative TrendScore (TS).
• TS resets to 0 at session open and is cleared at session close.
• Rising TS = persistent upside pressure; falling TS = persistent downside pressure.
⸻
🔄 Flip Rules (3-point reversal of the cumulative TrendScore)
A flip occurs when the cumulative TrendScore reverses by 3 points in the opposite direction of the current trend.
• Bullish Flip
• Trigger: After a decline, the cumulative TrendScore rises by +3 from its down-leg.
• Interpretation: Bulls have taken control.
• Stop-loss: the lowest price of the prior (down) leg.
• Bearish Flip
• Trigger: After a rise, the cumulative TrendScore falls by –3 from its up-leg.
• Interpretation: Bears have taken control.
• Stop-loss: the highest price of the prior (up) leg.
Flip bars are marked with ▲ (lime) for bullish and ▼ (red) for bearish.
Note: If you prefer a different reversal distance, adjust the flip distance setting in the script’s inputs (default is 3).
⸻
📏 Stop-Loss Lines
• A dotted line is drawn at the prior leg’s extreme:
Green (below price) after a bullish flip.
Red (above price) after a bearish flip.
• Options:
Remove on touch for a clean chart.
Freeze on touch to keep a visual record for journaling.
• All stop lines are cleared at session end.
⸻
🧮 Stats Table (what you see)
• Trend: Bull / Bear / Neutral
• Bars in Trend: Count since the flip bar
• Since Flip: Current close minus flip bar close
• Since SL: Current close minus active stop level
• MFE-Maximum Favorable Excursion: Highest favorable move since flip
• MAE-Maximum Adverse Excursion: Largest adverse move since flip
Table colors reflect the current trend (green for bull, red for bear).
⸻
📊 Trading Playbook
Entries
• Aggressive: Enter immediately on a flip marker.
• Conservative: Wait for a small pullback that doesn’t violate the stop.
Stops
• Place the stop at the script’s flip stop-loss line (the prior leg extreme).
Exits
Choose one style and stick with it:
• Stop-only: Exit when the stop is hit.
• Time-based: Flatten at session close.
• Targets: Scale/close at 1R, 2R.
• Trailing: Trail behind minor swings once MFE > 1R.
Ultimately Exit choice is your own edge, so you must decide for yourself.
💡 Best Practices
• Skip the first few bars after the open (gap noise).
• Use regular candles (Heikin-Ashi will distort highs/lows).
• If you want fewer flips, increase the flip distance (e.g., 4 or 5). For more
responsiveness, use 2. Otherwise, increase your time frame to 5m, 10m, 15m.
• Keep SL lines frozen (not auto-removed) if you’re journaling.
Morning Structure – Live 30 Min Range (with Alerts)This indicator captures the morning price structure by tracking the high and low during the first 30 minutes after market open (default: 9:30 AM to 10:00 AM, New York time). This version enables the ability to set alerts.
MM8 Best Regression ChannelMM8 Best Regression Channel — Smart regression channel with auto-optimized length and density histogram
\ Summary\
This indicator automatically searches the optimal regression length (optimalLength) between 50 and 200 (step 5) and draws a channel whose effective width is minimized. It then overlays a color-gradient regression channel plus a compact, right-edge density histogram to show where price spends most of its time inside the channel. The goal is to blend mean-reversion context with breakout assessment in a clean, visual way.
\ How it works\
1. Length optimization: For each candidate length (50…200, step 5) the script computes variance of the source and its linear correlation with time (bar\_index). Residual volatility (MAD proxy) is estimated via sqrt(v − v\*r^2). The channel width is evaluated as 2×MAD with an internal optimizer multiplier (mult\_opt = 2.0). The length that yields the smallest effective width is selected as optimalLength.
2. Regression and channel: Using optimalLength, the slope (alpha) and intercept (beta) are derived from source vs. bar\_index. Upper/lower channel boundaries are set at ±MAD scaled by the user “Multiplier”.
3. Density histogram: The channel span is split into N bins. For each bin, the script counts how many of the last optimalLength bars fall inside that band and draws a short horizontal tick on the right edge. Longer ticks imply higher dwell time.
\ Inputs\
* Bins Number: number of histogram bands (default 7).
* Multiplier: scales the final channel width used for drawing (separate from mult\_opt used only in the optimizer).
* Source: input data (default Close).
* Style → Show Histogram: toggle the right-edge density ticks.
* Style → Channel Color (Lower/Upper): colors for the channel gradient (from lower to upper).
* Style → Histogram Bins Color: color for the right-edge ticks.
* Style → Line Style: channel line style (solid / dashed / dotted).
\ What you see\
* A regression channel rendered with a lower→upper color gradient.
* A right-edge horizontal histogram for each band; tick length encodes the count of bars residing in that band over the last optimalLength window.
* To reduce overhead, lines are deleted/rebuilt and the drawing routine executes on the last bar (barstate.islast).
\ Interpretation and use\
* Mean reversion: Touches or brief pierces of outer bands with low local density can suggest short-term fade setups.
* Breakout context: A sustained push with rising density near a boundary, backed by structure and volume, can support continuation.
* Multiplier tuning: Smaller → tighter/more sensitive channel; larger → smoother/less noisy.
* Bins tuning: More bins give finer distribution detail (at the cost of a busier plot).
\ Practical notes\
* On noisier symbols/timeframes, consider a larger Multiplier.
* If the right-edge histogram looks too crowded, reduce Bins or increase Multiplier.
* Combine with market structure (HH/HL/LH/LL), volume, and supply/demand zones for confirmation.
\ Limitations\
* The optimizer search range is fixed at 50…200 with step 5 for simplicity/performance. Adjust start\_length / end\_length / step\_length in code if you need a different space.
* Lines are rebuilt each update; many instances or very long histories can add overhead on weaker machines.
* This is a contextual tool, not a definitive buy/sell signal.
\ Recommended settings\
* Many crypto pairs work well on 15m to 4h for a good balance of noise vs. signal.
* In strong trends, increase Multiplier or demand structural confirmation before fading an outer band.
* In ranges, focus on outer-band reactions with low local density and seek quick re-entries.
\ Compatibility\
* Pine Script v5. Uses max\_lines\_count=500. When running multiple instances, monitor performance.
\ Disclaimer\
* This is for analytical/educational purposes only and does not constitute financial advice. Use at your own risk.
Keywords: Regression Channel, Linear Regression, MAD, Mean Reversion, Breakout, Volatility, Distribution, Histogram, Liquidity, Crypto, BTC, Technical Analysis
clement fail proof 9-Indicator Buy/Sell Zones & Triggersthis is a combination of 9 indicators to make buying and selling a easy task for short term and long term traders...not for day traders..clementfranny@gmail.com designed to help beginners and experts ..so go ahead and trade like an expert..90 percent fail proof for long term but not for day trading...may work but you need to test..
BTC – 6 o'clock Windows (AM/PM) • stable v6Treat 02:30 and 14:30 UTC with Respect
This study focuses on two recurring intraday windows on BTC: 02:30 and 14:30 UTC. Using a time-based overlay that highlights 60–90 minute windows around these timestamps, you’ll notice that many days feature a sharp move, often kicked off by a quick liquidity sweep.
On the chart:
• Boxes visualize each window’s High–Low range.
• Labels show only the dollar change across the window (no decimals).
• Gray label = net up (Close − Open > 0). Purple label = net down (Close − Open < 0).
Why exactly 02:30 and 14:30 UTC?
1. Session overlap and peak liquidity. 02:30 sits inside Asia; 14:30 lands during prime U.S. hours. Block orders and rebalancing cluster here, lifting volatility.
2. Perpetuals mechanics. Funding, scheduled rolls, and liquidations often bunch around these times, triggering stop runs and occasional cascades.
3. Algorithmic execution. CTAs/HFTs batch orders near session turns and around key candle opens/closes.
4. Liquidity grabs. Fast sweeps above/below obvious highs/lows harvest stops before the real direction develops.
How to trade around these windows
• Time alerts at 02:25 and 14:25 UTC.
• Reduce size or hedge from \~10–15 minutes before to 30–90 minutes after.
• Avoid obvious swing-point stops; use ATR-based buffers.
• Wait for confirmation: liquidity sweep plus structure shift (MSB/CHOCH) with volume—don’t chase the first spike.
• Check the calendar first; CPI/FOMC/CME and major macro prints can magnify moves.
Method
Windows are highlighted strictly around 02:30 and 14:30 UTC on 15–30 minute charts. The magnitude cue comes from the window’s High–Low range, while label color reflects the net result (Close − Open): gray for net up, purple for net down. Repeated observations across recent days show this timing effect clearly.
Bottom line
The 02:30 and 14:30 UTC windows are liquidity magnets. Even if you trade swing or trend, acknowledging the elevated volatility here can materially improve entries, risk placement, and position durability.
This is an analytical view, not financial advice.
World TrendWorld Trend Strategy
The World Trend strategy is designed to capture strong, long-term market trends by combining multiple confirmations:
✅ Directional Strength through ADX and DI filters
✅ Momentum Confirmation with EMA alignment (63, 2400, 4800)
✅ Breakout Validation on candle closes above prior highs
✅ Structural Gap Filter between mid and long EMAs based on ATR
Entries are only taken when all conditions align, ensuring trades occur during periods of strong directional bias and volatility support. Exits are managed with trend reversals (DI cross or close below EMA63).
A dynamic EMA63 line acts like a Supertrend, changing colors depending on position state, with visual signals for entries/exits.
Additionally, a clean confirmation table is displayed on the chart, so you can instantly verify which conditions are active.
This strategy is optimized for higher-timeframe consistency (H1 recommended), aligning with the daily 200 EMA structure for robust filtering.
ATR + Moving Average Indicator//@version=5
indicator("ATR + Moving Average Indicator", overlay=true)
// === Inputs ===
atrLength = input.int(14, "ATR Length")
maLength = input.int(50, "Moving Average Length")
maType = input.string("EMA", "Moving Average Type", options= )
// === ATR Calculation ===
atr = ta.atr(atrLength)
// === Moving Average Calculation ===
ma = switch maType
"SMA" => ta.sma(close, maLength)
"EMA" => ta.ema(close, maLength)
"WMA" => ta.wma(close, maLength)
// === Plot Moving Average ===
plot(ma, title="Moving Average", color=color.yellow, linewidth=2)
// === Show ATR on separate panel ===
plot(atr, title="ATR", color=color.red, linewidth=2, display=display.none) // hides ATR from chart
// To see ATR in a separate pane, enable this line instead:
// indicator("ATR + Moving Average Indicator", overlay=false)
Berdins Indicator - EMA-POC (RSI + MTF + Alerts)EMA-POC Momentum System (RSI + MTF + Alerts)
What it does
• Trend: plots EMA 20 (red), EMA 50 (blue), EMA 238 (orange)
• Key level: simplified POC line = close of the highest-volume bar within a lookback window
• Momentum: Buy/Sell signals when RSI crosses 50 in the direction of the EMA trend
• Filters: optional higher-timeframe trend alignment, EMA slope filter, and minimum distance from POC to avoid chop
• Alerts: separate Buy/Sell alerts or one combined alert (choose in settings)
How to use
1) Add to chart and keep “Confirm on bar close” enabled for non-repainting signals.
2) For intraday, consider enabling MTF Trend (e.g., chart = 5m/15m, HTF = 60m).
3) Optional: set Min distance from POC to ~0.5–1.0% to avoid entries right on the POC.
4) Create alerts via the Alerts panel: choose “Buy Alert”, “Sell Alert”, or “Combined”.
Inputs (quick reference)
• EMA Fast/Mid/Slow = 20/50/238
• POC Lookback (default 200)
• RSI Length (default 14)
• Use Higher Timeframe Trend? (default off) + HTF for Trend
• Require EMA20 & EMA50 slope (default on)
• Min distance from POC (% of price)
• Confirm signals on bar close (default on)
• Use ONE combined alert (default off)
Notes
• POC here is a lightweight approximation and not a full volume profile.
• Signals are informational/educational. Always manage risk and confirm with your own process.
ADR LadderAverage Daily Range levels by percentage.
I enter a trade when the volume is medium to high and when the price closes above 3% (buy) and below 3% (sell). I use the opposite side as SL. TP above 50%.
Ranges by TraderHaroThis indicator highlights a custom price range for a selected date/time period on your chart. It draws key levels (0.00, 0.25, 0.50, 0.75, 1.00) within the range, visually marking the Premium Zone (upper range) and Discount Zone (lower range).
Features:
- Define a specific date/time range for the analysis.
- Optional fill between top and bottom levels with customizable color and transparency.
- Shows mid-levels (0.25, 0.50, 0.75) for additional guidance.
- Lines and fill can be extended to the right side of the chart.
- Labels for levels can be displayed or hidden.
Use Case:
Quickly identify where price is trading relative to a defined range, visualize potential zones of premium (resistance) and discount (support), and make better-informed trading decisions.
Market Roadmap by Jeffrey TurnmierJeffrey Turnmier offered his Market Roadmap in Trading View for free on a YouTube video. I copied it and worked on it for Version 6. I use it to determine if a security is above or below the indicator. I added several other indicators that produce buy and sell signals. I am mostly a swing trader.
Ultimate EMA (Futures) - (Moneybytomorrow)This Indicator is still in the Beta phase and set for testing. Enjoy! - Made for Futures Trading in mind but can be used for stocks etc.
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
" Date: " + date_str + " " + time_str +
" Trade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
" Rank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
" Percentile: " + str.tostring(percentile, "#.#") + "%" +
" Magnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
