Supertrend [TradingConToto]Supertrend — ADX/DI + EMA Gap + Breakout (with Mobile UI)
What makes it original
Supertrend combines trend strength (ADX/DI), multi-timeframe bias (EMA63 and EMA 200D equivalent), a structural filter based on the distance between EMA2400 and EMA4800 expressed in ATR units, and a momentum confirmation through a previous high breakout.
This is not a random mashup — it’s a sequence of filters designed to reduce trades in ranging markets and prioritize mature trends:
Direction: +DI > -DI (trend led by buyers).
Strength: ADX > mean(ADX) (avoids weak, choppy phases).
Short-term bias: Close > EMA63.
Long-term bias: Close > EMA4800 ≈ EMA200 daily on H1.
Momentum: Close > High (immediate breakout).
Structure: (EMA2400 − EMA4800) > k·ATR (ensures separation in ATR units, filters out flat phases).
Entries & exits
Entry: when all six conditions are met and no open position exists.
Exit: if +DI < -DI or Close < EMA63.
Visuals: EMA63 is painted green while in position and red otherwise, with a supertrend-style band; “BUY” labels appear below the green band and “SELL” labels above the red band.
UI: includes a compact table (mobile-friendly) showing the state of each condition.
Default parameters used in this publication
Initial capital: 10,000
Position size: 10% of equity (≤10% per trade is considered sustainable).
Commission: 0.01% per side (adjust to your broker/market).
Slippage: 1 tick
Pyramiding: 0 (only one position at a time)
Adjust commission/slippage to match your market. For US equities, commissions are often per share; for spot crypto, 0.10–0.20% total is common. I publish with 0.01% per side as a conservative example to avoid overestimating results.
Recommended backtest dataset
Timeframe: H1
Multi-cycle window (e.g. 2015–today)
Symbols with high liquidity (e.g. NASDAQ-100 large caps, or BTC/ETH spot) to generate 100+ trades. Avoid cherry-picked short windows.
Why each filter matters
+DI > -DI + ADX > mean: reduce counter-trend trades and weak signals.
Close > EMA63 + Close > EMA4800: enforce trend alignment in short and long horizons.
Breakout High : requires immediate momentum, avoids early entries.
EMA gap in ATR units: blocks flat or compressed structures where EMA200D aligns with price.
Limitations
The breakout filter may skip healthy pullbacks; the design prioritizes continuation over perfect entry price.
No fixed trailing stop/TP; exits depend on trend degradation via DI/EMA63.
Results vary with real costs (commissions, slippage, funding). Adjust defaults to your broker.
How to use
Apply it on a clean chart (no other indicators when publishing).
Keep in mind the default parameters above; if you change them, mention it in your notes and use the same values in the Strategy Tester.
Ensure your dataset produces 100+ trades for statistical validity.
在脚本中搜索"BTC"
Trading Sessions with Holidays & Timer🌍 Trading Sessions Matter
Markets breathe in cycles. When Tokyo, London, or New York steps in, liquidity shifts and price often reacts fast.
Example: New York closed BTC at $110K, and when traders woke up, the price was already $113K. That gap says everything about overnight pressure and the next move.
⚡ Indicator Features
✅ Session boxes (Tokyo, London, NY) with custom colors & time zones
✅ Open/close lines → spot gaps & momentum
✅ Average price per session → see where pressure builds
✅ Tick range → quick volatility check
✅ 🏖 Holiday markers → avoid false quiet markets
✅ Live status table → session OPEN / CLOSED + countdown timer
🚀 How to Use
Works on intraday timeframes (1m–4h)
Watch session opens/closes → liquidity shift points
Compare ranges & averages between Tokyo, London, NY
Use the timer to prep before the next wave
This tool helps you visualize the heartbeat of global markets session by session.
🔖 #BTCUSDT #Forex #TradingSessions #Crypto #DayTrading
Sniper Swing — Short TF (Clean Signals) [v6]📘 How to Use the Sniper Swing Indicator
1. What It Does
It looks for short-term swing breaks in price.
It uses an oscillator (RSI/Stoch) and swing pivots to confirm moves.
It gives you 3 clear signals only:
BUY → Enter long (expecting price to go up).
Gay bear → Enter short (expecting price to go down).
EXIT → Close your trade (long or short).
Candles also change color:
Green = in a BUY trade.
Red = in a Gay bear trade.
Neutral (gray/none) = no trade.
2. When to Use
Works best on short timeframes (1m–5m) for scalping/intraday.
Use on liquid markets (MES/ES, NQ, SPY, BTC, ETH).
Avoid dead hours with no volume (like overnight futures lull or midday chop).
3. How to Trade With It
A. BUY trade
Wait for a BUY triangle below the candle.
Confirm:
Candle turned green.
Price broke a recent swing high.
Oscillator shows strength (indicator does this for you).
Enter long at the close of that candle.
Place your stop-loss:
At the yellow stop line (auto trailing stop), or
Just below the last swing low.
Stay in while candles are green.
Exit when:
An orange X appears, or
Price hits your stop.
B. Gay bear (short) trade
Wait for a Gay bear triangle above the candle.
Confirm:
Candle turned red.
Price broke a recent swing low.
Oscillator shows weakness.
Enter short at the close of that candle.
Place stop-loss:
At the yellow stop line, or
Just above the last swing high.
Stay in while candles are red.
Exit on an orange X or stop hit.
4. Pro Tips for New Traders
Only take one signal at a time → don’t double dip.
Quality > Quantity: ignore weak, sideways markets. Best signals happen during trends.
Start small: trade micros (MES) or small position sizes.
Use alerts: set TradingView alerts for BUY/Gay bear/EXIT so you don’t miss setups.
Think of the indicator like a navigator: it tells you the likely path, but you’re the driver → always manage risk.
5. Quick Mental Checklist
Signal? (BUY or Gay bear triangle)
Confirmed? (candle color + swing break)
Enter? (on close)
Stop? (yellow line or swing)
Exit? (orange X or stop)
Sinyal Gabungan Lengkap (TWAP + Vol + Waktu)Sinyal Gabungan Lengkap (TWAP + Vol + Waktu) volume btc dan total3 dan ema
On-Chain Metrics & Z-Mode SelectionThis indicator provides an on-chain metric analysis framework for cryptocurrencies (currently limited to) BTC and ETH; allowing users to select from popular metrics such as SOPR, Profit Addresses %, NUPL, or MVRV.
It enables various analyses on the chosen metric to capture momentum and rate of change dynamics over time.
Analyses include:
Normalization techniques utilizing Mean or Median with standard deviation, as well as a 'Robust' method using interquartile range-based Z-scoring to accommodate skewed distributions, or raw values without normalization.
An optional differential calculation that highlights the rate of change (first derivative) of the metric.
Moving average smoothing with up to two passes, supporting EMA, SMA, or WMA types.
Optional sigmoid-based compression that scales and centers the indicator output, improving interpretability, mitigating extreme outliers, and allowing the user to scale the output so that the step size or increment of the long and short thresholds remains within a workable range.
Buy and sell signals are generated based on configurable long and short thresholds applied to the processed output.
Visual components such as trend colouring, threshold lines, background shading, and labels make it simple for traders to identify entry signals.
This indicator is suitable for those looking to integrate blockchain behavioral insights into their trading decisions.
Overall, this script transforms complex on-chain data into actionable trade signals by combining adaptive normalization and smoothing techniques. Its versatility and multi-metric support make it a valuable tool for both market monitoring and strategy development.
No financial decisions should be made based solely on this indicator. Always conduct your own research. .
Acknowledgements
Inspiration drawn from: CipherDecoded
ICT FVG Buy/Sell SignalsThis bot is built on ICT (Inner Circle Trader) concepts such as:
Fair Value Gaps (FVGs) – imbalance zones between candles.
Consequent Encroachment (CE) – the midpoint of a gap.
Premium / Discount Arrays – dealing ranges split into premium (sell-side) and discount (buy-side) zones.
Displacement candles – strong impulsive moves that confirm intent.
The bot scans for FVGs, marks CE levels, and waits for price to return to these levels.
When price revisits a valid FVG zone with displacement confirmation and in the correct PD array, the bot generates a BUY or SELL signal.
✅ Signal Rules
Buy Signal
Price trades back into a Bullish FVG.
Current bar shows bullish displacement (large bullish body relative to ATR).
Price is in discount territory of the current dealing range (if PD filter is enabled).
Close is above the CE line of the FVG.
Sell Signal
Price trades back into a Bearish FVG.
Current bar shows bearish displacement.
Price is in premium territory of the current dealing range.
Close is below the CE line of the FVG.
🎯 What You’ll See on the Chart
Green “BUY” labels below candles when long signals trigger.
Red “SELL” labels above candles when short signals trigger.
Shaded background:
Red = Premium zone (sell side).
Teal = Discount zone (buy side).
Yellow line = dealing range midpoint (equilibrium).
Dots on CE lines = midpoints of the latest bullish/bearish FVG.
🔔 Alerts
ICT Buy → Triggers when a bullish setup confirms.
ICT Sell → Triggers when a bearish setup confirms.
You can connect these alerts to:
TradingView notifications.
Webhooks (for brokers or bots like MetaTrader, NinjaTrader, or Discord).
⚙️ Settings
Swing length – how many bars to use when detecting swing highs/lows for the dealing range.
Use PD filter – toggle ON/OFF for requiring discount/premium alignment.
Displacement ATR multiple – how strong the candle body must be compared to ATR to count as a displacement.
ATR length – used for displacement filter.
📈 Supported Markets
Works on all symbols and timeframes.
Commonly applied to:
NASDAQ (NQ, QQQ)
S&P500 (ES, SPX, SPY)
Forex pairs
Crypto (BTC, ETH, etc.)
⚠️ Disclaimer
This bot is for educational purposes only. It does not guarantee profits and should be tested on demo accounts first.
Always apply proper risk management before trading live.
Aggregated Multi-Exchange Delta Volume Histogram (w ADMF)This indicator is multi-exchange aggregated volume with additional ATR-based length ADMF EMA (orange/green line).
It has pre-defined ticker list for BTC, ETH and SOL but feel free to use settings to add a multi-exchange ticker list for any other ticker.
Sinyal Dominasi Volatilitas (dengan Alarm)sinyal perbandingan btc dan total3 perbedaan yang signifikan di candle TF15 menit
Maiko Range Scalper (Sideways BB + RSI) – v4 cleanPurpose
It’s a range scalping strategy for crypto. It tries to take small, repeatable trades inside a sideways market: buy near the bottom of the range, sell near the middle/top (and the reverse for shorts).
Core idea (two timeframes)
Define the trading range on a higher timeframe (HTF)
You choose the HTF (e.g., 15m or 1h).
The script finds the highest high and lowest low over a lookback window (e.g., last 96 HTF candles) → these become HTF Resistance and HTF Support.
It also calculates the midline (average of support/resistance).
Trade signals on your lower timeframe (LTF)
You run the strategy on a fast chart (e.g., 1m or 5m).
Entries are only allowed inside the HTF range.
Entry logic (mean reversion)
Indicators on the LTF:
Bollinger Bands (length & std dev configurable).
RSI (length & thresholds configurable).
Optional VWAP proximity filter (price must be within X% of VWAP).
Long setup:
Price touches/under-cuts the lower Bollinger band AND RSI ≤ threshold (default 30) AND price is inside the HTF range (and passes VWAP filter if enabled).
Short setup:
Price touches/exceeds the upper Bollinger band AND RSI ≥ threshold (default 70) AND price is inside the HTF range (and passes VWAP filter if enabled).
Exits and risk
Stop-loss: placed just outside the HTF range with a configurable buffer %:
Long SL = HTF Support × (1 − buffer).
Short SL = HTF Resistance × (1 + buffer).
Take-profit (selectable):
Mid band (the Bollinger basis) → conservative, faster exits.
Opposite band / HTF boundary → more aggressive, higher RR but more give-backs.
Position sizing
A simple cap: maximum position size = percent of account equity (e.g., 20%).
The script calculates quantity from that cap and current price.
Plots you’ll see on the chart
HTF Resistance (red) and HTF Support (green) via plot().
HTF Midline (gray dashed) drawn with a line.new() object (because plot() cannot do dashed).
Bollinger basis/upper/lower on the LTF.
Optional VWAP line (only shown if you enable the filter).
Signal markers (green triangle up for Long setups, red triangle down for Short setups).
Alerts
Two alertconditions:
“Long Setup” – when a long entry condition appears.
“Short Setup” – when a short entry condition appears.
Create alerts from these to get notified in real time.
How to use it (quick start)
Add to a 1m or 5m chart of a liquid coin (BTC, ETH, SOL).
Set HTF timeframe (start with 1h) and lookback (e.g., 96 = ~4 days on 1h).
Keep default Bollinger/RSI first; tune later.
Choose TP mode:
“Mid band” for quick scalps.
“Opposite band/Range” if the range is very clean and you want bigger targets.
Set SL buffer (0.15–0.30% is common; adjust for volatility).
Set Max position % to control size (e.g., 20%).
(Optional) Enable VWAP filter to skip stretched moves.
When it works best
Clearly sideways markets with visible support/resistance on the HTF.
High-liquidity pairs where spreads/fees are small relative to your scalp target.
Limitations & safety notes
True breakouts will invalidate mean-reversion logic—your SL outside the range is there to cut losses fast.
Fees can eat into small scalps—prefer limit orders, rebates, and liquid pairs.
Backtest results vary by exchange data; always forward-test on small size.
If you want, I can:
Add an ATR-based stop/target option.
Provide a study-only version (signals/alerts, no trading engine).
Pre-set risk to your €5,000 plan (e.g., ~0.5% max loss/trade) with calculated qty.
Swing Z | Zillennial Technologies Inc.Swing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Swing Z – Crypto Trading Algorithm | Zillennial Technologies IncSwing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Justin's Bitcoin Power Law PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. Using the formula Price = A * (daysSinceGenesis)^B, it calculates fair, upper, and floor prices with constants A_fair = 1.16e-17, A_floor = 0.42e-17, and B = 5.82, starting from Bitcoin’s genesis (January 3, 2009). The script plots these prices, displays values in a table.
Source: www.ccn.com
Justin's MSTR Powerlaw Price PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. The price prediction is based on the the formula published in this article:
www.ccn.com
AltCoin & MemeCoin Index Correlation [Eddie_Bitcoin]🧠 Philosophy of the Strategy
The AltCoin & MemeCoin Index Correlation Strategy by Eddie_Bitcoin is a carefully engineered trend-following system built specifically for the highly volatile and sentiment-driven world of altcoins and memecoins.
This strategy recognizes that crypto markets—especially niche sectors like memecoins—are not only influenced by individual price action but also by the relative strength or weakness of their broader sector. Hence, it attempts to improve the reliability of trading signals by requiring alignment between a specific coin’s trend and its sector-wide index trend.
Rather than treating each crypto asset in isolation, this strategy dynamically incorporates real-time dominance metrics from custom indices (OTHERS.D and MEME.D) and combines them with local price action through dual exponential moving average (EMA) crossovers. Only when both the asset and its sector are moving in the same direction does it allow for trade entries—making it a confluence-based system rather than a single-signal strategy.
It supports risk-aware capital allocation, partial exits, configurable stop loss and take profit levels, and a scalable equity-compounding model.
✅ Why did I choose OTHERS.D and MEME.D as reference indices?
I selected OTHERS.D and MEME.D because they offer a sector-focused view of crypto market dynamics, especially relevant when trading altcoins and memecoins.
🔹 OTHERS.D tracks the market dominance of all cryptocurrencies outside the top 10 by market cap.
This excludes not only BTC and ETH, but also major stablecoins like USDT and USDC, making it a cleaner indicator of risk appetite across true altcoins.
🔹 This is particularly useful for detecting "Altcoin Season"—periods where capital rotates away from Bitcoin and flows into smaller-cap coins.
A rising OTHERS.D often signals the start of broader altcoin rallies.
🔹 MEME.D, on the other hand, captures the speculative behavior of memecoin segments, which are often driven by retail hype and social media activity.
It's perfect for timing momentum shifts in high-risk, high-reward tokens.
By using these indices, the strategy aligns entries with broader sector trends, filtering out noise and increasing the probability of catching true directional moves, especially in phases of capital rotation and altcoin risk-on behavior.
📐 How It Works — Core Logic and Execution Model
At its heart, this strategy employs dual EMA crossover detection—one pair for the asset being traded and one pair for the selected market index.
A trade is only executed when both EMA crossovers agree on the direction. For example:
Long Entry: Coin's fast EMA > slow EMA and Index's fast EMA > slow EMA
Short Entry: Coin's fast EMA < slow EMA and Index's fast EMA < slow EMA
You can disable the index filter and trade solely based on the asset’s trend just to make a comparison and see if improves a classic EMA crossover strategy.
Additionally, the strategy includes:
- Adaptive position sizing, based on fixed capital or current equity (compound mode)
- Take Profit and Stop Loss in percentage terms
- Smart partial exits when trend momentum fades
- Date filtering for precise backtesting over specific timeframes
- Real-time performance stats, equity tracking, and visual cues on chart
⚙️ Parameters & Customization
🔁 EMA Settings
Each EMA pair is customizable:
Coin Fast EMA: Default = 47
Coin Slow EMA: Default = 50
Index Fast EMA: Default = 47
Index Slow EMA: Default = 50
These control the sensitivity of the trend detection. A wider spread gives smoother, slower entries; a narrower spread makes it more responsive.
🧭 Index Reference
The correlation mechanism uses CryptoCap sector dominance indexes:
OTHERS.D: Dominance of all coins EXCLUDING Top 10 ones
MEME.D: Dominance of all Meme coins
These are dynamically calculated using:
OTHERS_D = OTHERS_cap / TOTAL_cap * 100
MEME_D = MEME_cap / TOTAL_cap * 100
You can select:
Reference Index: OTHERS.D or MEME.D
Or disable the index reference completely (Don't Use Index Reference)
💰 Position Sizing & Risk Management
Two capital allocation models are supported:
- Fixed % of initial capital (default)
- Compound profits, which scales positions as equity grows
Settings:
- Compound profits?: true/false
- % of equity: Between 1% and 200% (default = 10%)
This is critical for users who want to balance growth with risk.
🎯 Take Profit / Stop Loss
Customizable thresholds determine automatic exits:
- TakeProfit: Default = 99999 (disabled)
- StopLoss: Default = 5 (%)
These exits are percentage-based and operate off the entry price vs. current close.
📉 Trend Weakening Exit (Scale Out)
If the position is in profit but the trend weakens (e.g., EMA color signals trend loss), the strategy can partially close a configurable portion of the position:
- Scale Position on Weak Trend?: true/false
- Scaled Percentage: % to close (default = 65%)
This feature is useful for preserving profits without exiting completely.
📆 Date Filter
Useful for segmenting performance over specific timeframes (e.g., bull vs bear markets):
- Filter Date Range of Backtest: ON/OFF
- Start Date and End Date: Custom time range
OTHER PARAMETERS EXPLANATION (Strategy "Properties" Tab):
- Initial Capital is set to 100 USD
- Commission is set to 0.055% (The ones I have on Bybit)
- Slippage is set to 3 ticks
- Margin (short and long) are set to 0.001% to avoid "overspending" your initial capital allocation
📊 Visual Feedback and Debug Tools
📈 EMA Trend Visualization
The slow EMA line is dynamically color-coded to visually display the alignment between the asset trend and the index trend:
Lime: Coin and index both bullish
Teal: Only coin bullish
Maroon: Only index bullish
Red: Both bearish
This allows for immediate visual confirmation of current trend strength.
💬 Real-Time PnL Labels
When a trade closes, a label shows:
Previous trade return in % (first value is the effective PL)
Green background for profit, Red for losses.
📑 Summary Table Overlay
This table appears in a corner of the chart (user-defined) and shows live performance data including:
Trade direction (yellow long, purple short)
Emojis: 💚 for current profit, 😡 for current loss
Total number of trades
Win rate
Max drawdown
Duration in days
Current trade profit/loss (absolute and %)
Cumulative PnL (absolute and %)
APR (Annualized Percentage Return)
Each metric is color-coded:
Green for strong results
Yellow/orange for average
Red/maroon for poor performance
You can select where this appears:
Top Left
Top Right
Bottom Left
Bottom Right (default)
📚 Interpretation of Key Metrics
Equity Multiplier: How many times initial capital has grown (e.g., “1.75x”)
Net Profit: Total gains including open positions
Max Drawdown: Largest peak-to-valley drop in strategy equity
APR: Annualized return calculated based on equity growth and days elapsed
Win Rate: % of profitable trades
PnL %: Percentage profit on the most recent trade
🧠 Advanced Logic & Safety Features
🛑 “Don’t Re-Enter” Filter
If a trade is closed due to StopLoss without a confirmed reversal, the strategy avoids re-entering in that same direction until conditions improve. This prevents false reversals and repetitive losses in sideways markets.
🧷 Equity Protection
No new trades are initiated if equity falls below initial_capital / 30. This avoids overleveraging or continuing to trade when capital preservation is critical.
Keep in mind that past results in no way guarantee future performance.
Eddie Bitcoin
Simple Liquidity Zones [Supertrade]🔎 What this indicator does
This indicator is designed to highlight liquidity sweep zones on the chart.
• A liquidity sweep occurs when price briefly breaks above a recent swing high or below a recent swing low, but fails to close beyond it.
• Such behavior often indicates that price has taken liquidity (stop orders resting above highs or below lows) and may reverse.
The indicator marks these events as bullish or bearish liquidity zones:
• Bullish Zone (green) → Price swept a swing low and closed back above it (possible bullish reversal area).
• Bearish Zone (red) → Price swept a swing high and closed back below it (possible bearish reversal area).
These zones are drawn as shaded horizontal bands that extend forward in time, providing visual areas where liquidity grabs occurred.
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⚙️ How calculations are made
The indicator does not use moving averages or smoothing.
Instead, it works with raw price action:
1. Swing Detection → It checks the highest high and lowest low of the past N bars (swing length).
2. Sweep Logic →
o A bearish sweep happens if the high breaks above the previous swing high, but the close returns below that level.
o A bullish sweep happens if the low breaks below the previous swing low, but the close returns above that level.
3. Zone Creation → When a sweep is detected, a shaded zone is drawn just above/below the swing level.
4. Persistence → Zones extend into the future until replaced by new ones (or optionally until price fully trades through them).
This makes the calculations simple, transparent, and responsive to actual market structure without lag.
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📈 How it helps traders
This tool helps traders by:
• Visualizing liquidity areas → Shows where price previously swept liquidity and may act as support/resistance.
• Identifying reversals → Helps spot potential turning points after liquidity grabs.
• Risk management → Zones highlight areas where stops may be targeted, useful for positioning stop-loss orders.
• Confluence tool → Works best when combined with other strategies such as order blocks, trendlines, or volume analysis.
⚠️ Note: Like all indicators, this should not be used in isolation. It provides context, not guaranteed trade signals.
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🏦 Markets & Timeframes
• Works across all markets (crypto, forex, stocks, indices, commodities).
• Particularly effective in high-liquidity environments where stop-hunting is common (e.g., forex majors, BTC/ETH, S&P500).
• Timeframes:
o Lower timeframes (1m–15m) → Scalpers can spot intraday liquidity sweeps.
o Higher timeframes (1H–1D) → Swing traders can identify major liquidity pools.
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Justin's Bitcoin Power Law Predictor (Santostasi Model)This indicator uses the Powerlaw to predict the BTC price.
EMA Oscillator [Alpha Extract]A precision mean reversion analysis tool that combines advanced Z-score methodology with dual threshold systems to identify extreme price deviations from trend equilibrium. Utilizing sophisticated statistical normalization and adaptive percentage-based thresholds, this indicator provides high-probability reversal signals based on standard deviation analysis and dynamic range calculations with institutional-grade accuracy for systematic counter-trend trading opportunities.
🔶 Advanced Statistical Normalization
Calculates normalized distance between price and exponential moving average using rolling standard deviation methodology for consistent interpretation across timeframes. The system applies Z-score transformation to quantify price displacement significance, ensuring statistical validity regardless of market volatility conditions.
// Core EMA and Oscillator Calculation
ema_values = ta.ema(close, ema_period)
oscillator_values = close - ema_values
rolling_std = ta.stdev(oscillator_values, ema_period)
z_score = oscillator_values / rolling_std
🔶 Dual Threshold System
Implements both statistical significance thresholds (±1σ, ±2σ, ±3σ) and percentage-based dynamic thresholds calculated from recent oscillator range extremes. This hybrid approach ensures consistent probability-based signals while adapting to varying market volatility regimes and maintaining signal relevance during structural market changes.
// Statistical Thresholds
mild_threshold = 1.0 // ±1σ (68% confidence)
moderate_threshold = 2.0 // ±2σ (95% confidence)
extreme_threshold = 3.0 // ±3σ (99.7% confidence)
// Percentage-Based Dynamic Thresholds
osc_high = ta.highest(math.abs(z_score), lookback_period)
mild_pct_thresh = osc_high * (mild_pct / 100.0)
moderate_pct_thresh = osc_high * (moderate_pct / 100.0)
extreme_pct_thresh = osc_high * (extreme_pct / 100.0)
🔶 Signal Generation Framework
Triggers buy/sell alerts when Z-score crosses extreme threshold boundaries, indicating statistically significant price deviations with high mean reversion probability. The system generates continuation signals at moderate levels and reversal signals at extreme boundaries with comprehensive alert integration.
// Extreme Signal Detection
sell_signal = ta.crossover(z_score, selected_extreme)
buy_signal = ta.crossunder(z_score, -selected_extreme)
// Dynamic Color Coding
signal_color = z_score >= selected_extreme ? #ff0303 : // Extremely Overbought
z_score >= selected_moderate ? #ff6a6a : // Overbought
z_score >= selected_mild ? #b86456 : // Mildly Overbought
z_score > -selected_mild ? #a1a1a1 : // Neutral
z_score > -selected_moderate ? #01b844 : // Mildly Oversold
z_score > -selected_extreme ? #00ff66 : // Oversold
#00ff66 // Extremely Oversold
🔶 Visual Structure Analysis
Provides a six-tier color gradient system with dynamic background zones indicating mild, moderate, and extreme conditions. The histogram visualization displays Z-score intensity with threshold reference lines and zero-line equilibrium context for precise mean reversion timing.
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4H
1D
🔶 Adaptive Threshold Selection
Features intelligent threshold switching between statistical significance levels and percentage-based dynamic ranges. The percentage system automatically adjusts to current volatility conditions using configurable lookback periods, while statistical thresholds maintain consistent probability-based signal generation across market cycles.
🔶 Performance Optimization
Utilizes efficient rolling calculations with configurable EMA periods and threshold parameters for optimal performance across all timeframes. The system includes comprehensive alert functionality with customizable notification preferences and visual signal overlay options.
🔶 Market Oscillator Interpretation
Z-score > +3σ indicates statistically significant overbought conditions with high reversal probability, while Z-score < -3σ signals extreme oversold levels suitable for counter-trend entries. Moderate thresholds (±2σ) capture 95% of normal price distributions, making breaches statistically significant for systematic trading approaches.
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🔶 Intelligent Signal Management
Automatic signal filtering prevents false alerts through extreme threshold crossover requirements, while maintaining sensitivity to genuine statistical deviations. The dual threshold system provides both conservative statistical approaches and adaptive market condition responses for varying trading styles.
Why Choose EMA Oscillator ?
This indicator provides traders with statistically-grounded mean reversion analysis through sophisticated Z-score normalization methodology. By combining traditional statistical significance thresholds with adaptive percentage-based extremes, it maintains effectiveness across varying market conditions while delivering high-probability reversal signals based on quantifiable price displacement from trend equilibrium, enabling systematic counter-trend trading approaches with defined statistical confidence levels and comprehensive risk management parameters.
Trojan Cycle: Dip & Profit Hunter📉 Crypto is changing. Your signals should too.
This script doesn’t try to outguess price — it helps you track capital rotation and flow behavior in alignment with the evolving macro structure of the digital asset market.
Trojan Cycle: Dip & Profit Hunter is a signal engine built to support and validate the capital rotation models outlined in the Trojan Cycle and Synthetic Rotation theses — available via RWCS_LTD’s published charts
It is not a classic “buy low, sell high” tool. It is a structural filter that uses price/volume statistics to surface accumulation zones, synthetic traps, and macro context shifts — all aligned with the institutionalization of crypto post-2024.
🧠 Purpose & Value
Crypto no longer follows the retail-led, halving-driven pattern of 2017 or 2021.
Instead, institutional infrastructure, regulatory filters, and equity-market Trojan horses define the new path of capital.
This tool helps you visualize that path by interpreting behavior through statistical imbalances and real-time momentum signals.
Use it to:
Track where capital is accumulating or exiting
Identify signals consistent with true cycle rotation (vs. synthetic traps)
Validate your macro view with real-time statistical context
🔍 How It Works
The engine combines four signal layers:
1. Z-Score Logic
- Measures how far price and volume have deviated from their mean
- Detects dips, blowoffs, and exhaustion zones
2. Percentile Logic
- Compares current price and volume to historical rank distribution
- Flags statistically rare conditions (e.g. bottom 10% price, top 90% volume)
3. Combined Context Engine
- Integrates both models to generate one of 36 unique output states
- Each state provides a labeled market context (e.g., 🟢 Confluent Buy, 🔴 Confluent Sell, 🧨 Synthetic Trap )
4. Momentum Spread & Divergence
- Measures whether price is leading volume (trap risk) or volume is leading price (accumulation)
- Outputs intuitive momentum context with emoji-coded alerts
📋 What You See
🧠 Contextual Table UI with key Z-Scores, percentiles, signals, and market commentary
🎯 Emoji-coded signals to quickly grasp high-probability setups or risk zones
🌊 Optional overlays: price/volume divergence, momentum spread
🎨 Visual table customization (size, position) and chart highlights for signal clarity
🔔 Alert System
✅ Single dynamic alert using alert() that only fires when signal context changes
Prevents alert fatigue and allows clean webhook/automation integration
🧭 Use Cases
For macro cycle traders: Track where we are in the Trojan Cycle using statistical context
For thesis explorers: Use the 36-output signal map to match against your rotation thesis
For capital rotation watchers: Identify structural setups consistent with ETF-driven or compliance-filtered flow
For narrative skeptics: Avoid synthetic altseason traps where volume lags or flow dries up
🧪 Suggested Pairing for Thesis Validation
To use this tool as part of a thesis-confirmation framework , pair it with:
BTC.D — Bitcoin Dominance
ETH/BTC — Ethereum strength vs. Bitcoin
TOTALE100/ETH — Altcoin strength relative to ETH
RWCS_LTD’s published charts and macro cycle models
🏁 Final Note
Crypto has matured. So should your signals.
This tool doesn’t try to game the next 2 candles. It helps you understand the current phase in a compliance-filtered, institutionalized rotation model.
It’s not built for hype — it’s built for conviction.
Explore the thesis → Validate the structure → Trade with clarity.
🚨 Disclaimer
This script is not financial advice. It is an analytical tool designed to support market structure research and rotation thesis validation. Use this as part of a broader framework including technical structure, dominance charts, and macro data.
LazyScalp (Multi-Exchanges)This indicator is based on the LazyScalp Board by Aleksandr400 and enhances it with multi-exchange functionality. It displays 24-hour trading volumes and BTC correlations across multiple exchanges, with optional features to sort by the current exchange and hide exchange names in the table
TOTAL3ES/ETH Mean Reversion
Total market capitalization of altcoins excluding ETH and BTC divided by ETH
Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.