RSI Open-Source IndicatorA simple open-source RSI indicator
using default settings.
No signals.
No predictions.
Bitcoin (Kryptowaluta)
high-frequency scalping strategy by Alphaomega18Alphaomega18 – High-Frequency Scalping Engine (1m)
Institutional Logic | Explosive Momentum | Session-Based Precision
🔬 Strategy Overview
Alphaomega18 is a next-generation high-frequency scalping strategy engineered exclusively for the 1-minute timeframe (1m).
It is built around a proprietary Source Shift Algorithm, comparing:
SMA 3 (Close-based)
SMA 5 (Open-based)
Unlike traditional moving average crossovers, Alphaomega18 measures instantaneous momentum displacement between candle opens and real-time price action. This allows the strategy to detect and exploit impulsive moves at their inception, before lagging indicators can react.
⚙️ Core Technical Edge
Proprietary Open vs Close SMA displacement logic
Ultra-fast signal generation optimized for scalping environments
Designed to operate efficiently in high-volatility conditions
Minimal indicator lag – price leads the signal
This structure makes Alphaomega18 particularly effective during liquidity injections such as market opens and session transitions.
🚀 Verified Performance Highlights
Backtested Period: December 22, 2025 – January 18, 2026
Nasdaq Futures (NQ) – New York Open
With an optimized 50-point Stop Loss, Alphaomega18 delivered institutional-grade performance:
Net Profit: +$21,035.00
Total Return: +2,103.50%
Profit Factor: 1.34 (high consistency)
Additional Results – New York Session
ES (S&P 500): +$5,350.00 (+267.50%) | PF: 1.181
BTC/USD: +$2,921.67 (+146.08%) | PF: 1.61+
24/7 Mode – Crypto & Metals
Bitcoin (BTC): +$10,932.00 (+547.53%)
Gold (XAU/USD): +$474.73 (+21.74%)
🕒 Smart Session Filter (Key Feature)
Alphaomega18 integrates a multi-session trading filter, allowing traders to focus exclusively on high-probability market windows:
New York Open (09:30–11:45 NY time)
The “Phenomenal Window” where the +2103% NQ performance was achieved.
European Session (08:00–17:00 Paris time)
Optimized for EUR/USD and DAX scalping.
Full-Time Mode (24/7)
Recommended for cryptocurrencies and gold.
This feature significantly reduces market noise and overtrading.
📊 Trading Rules (Clear & Objective)
Recommended Assets:
Nasdaq (NQ), S&P 500 (ES), Bitcoin (BTC)
Timeframe:
1 minute (1m) — mandatory
Risk Settings:
NQ: 50-point Stop Loss
Other assets: 40-point Stop Loss
Signal Logic:
BUY: SMA 3 (green) crosses above SMA 5 (red)
SELL: SMA 3 (green) crosses below SMA 5 (red)
🧠 Who Is This Strategy For?
✔ Active scalpers
✔ Futures & crypto traders
✔ Traders seeking session-based precision
✔ Users with low-spread / fast-execution brokers
⚠️ Risk Disclaimer
Scalping involves substantial risk and requires disciplined risk management.
Alphaomega18 is a high-frequency strategy and performs best with low spreads, minimal slippage, and proper execution conditions. Past performance does not guarantee future results.
IcebergCryptoX - Week Data Gap📊 BTC WEEKEND DATA COLLECTION
This indicator analyzes Bitcoin movements during weekends when traditional US markets are closed.
🎯 DATA COLLECTED:
- Gap from Friday close → Monday open (%)
- Maximum upward/downward movements during the weekend
- Total weekend range
- Mean reversion rate (return to Friday closing price)
- Movement direction (positive/negative/neutral)
- Historical records (biggest gaps and ranges)
📈 FEATURES:
✓ Colored zones to visually identify weekends
✓ Detailed labels on each weekend with key metrics
✓ Real-time statistics table
✓ Tracking of extremes and averages
✓ 100% data collection (no trading signals)
⚙️ PARAMETERS:
- Display weekend zones (on/off)
- Display labels (on/off)
- Statistics table (on/off)
- Significant movement threshold (customizable)
📉 USAGE:
Ideal for analyzing BTC volatility patterns outside US trading hours and identifying recurring opportunities.
Recommended timeframe: 15min to 1H
[Algoros] Bitcoin Risk Heat MapBitcoin Risk Heat Map v2.0 — How to use
Purpose: A BTC daily risk “temperature” overlay that colors price from colder blue (lower risk) to hotter red (higher risk), plus an optional on-chart thermometer barometer.
1) Required setup (important)
Symbol : Best results on BITSTAMP:BTCUSD . Also supports BTCUSD, BTCEUR, BTCCHF, BTCGBP, BTCAUD, BTCJPY.
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you pick the wrong symbol/timeframe/type, the script can show an on-chart warning message.
2) What the colors mean
Colder (blue/aqua/teal) : lower risk conditions (cooler market “temperature”).
Neutral (lime) : mid / balanced conditions.
Hotter (yellow/orange/red/maroon) : higher risk conditions (hot market “temperature”).
3) Visuals
Colored BTC price overlay : the BTC price line is colored by the current risk level.
Heat band : a colored band around price. Control thickness via Heatmap width .
Thermometer / Barometer table : enable/disable via Show Heatmap Barometer .
4) Settings
Heatmap width : controls how wide the colored band is drawn around price.
Show Heatmap Barometer : toggles the thermometer-style table at the bottom.
Component weights : you can change the weight of each sub-component to adjust the risk model emphasis.
5) Using it together with Bitcoin Profit Scout (recommended)
This combination makes perfect sense:
- Buy signals from Bitcoin Profit Scout in red/hot areas of the Bitcoin Risk Heat Map may be riskier than buy signals in colder blue areas.
- Vice versa, sell signals in red/hot areas might be stronger than sell signals in colder blue areas.
Example screenshot (Bitcoin Profit Scout + Bitcoin Risk Heat Map)
Free video walkthrough + deeper explanations
If you want a step-by-step video walkthrough and additional explanations/examples for Bitcoin Risk Heat Map, you can access them on our website (free): algoros.ai
Notes / expectations
This is not financial advice; always use risk management and position sizing.
The heat map is designed for daily BTC charts . Other symbols/timeframes will degrade results.
[Algoros] Bitcoin Profit ScoutBitcoin Profit Scout v4.3.1 — How to use
Purpose: a BTC daily “buy the dips / sell the rips” guide using Buy/Sell Trigger Lines + confirmed signal shapes + optional Signal Barometer.
1) Required setup (important)
Symbol : Best results on BITSTAMP:BTCUSD . Also supports BTCUSD, BTCEUR, BTCCHF, BTCGBP, BTCAUD, BTCJPY.
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you pick the wrong symbol/timeframe/type, BPS will show an on-chart error message and hide signals/lines.
2) What the lines mean
Buy Trigger Line : prices below this line are the “Buy Zone”.
Sell Trigger Line : prices above this line are the “Sell Zone”.
3) Market modes (visual cues)
Bull Market Mode (green emphasis): “Buy Zone” is less strict.
Bear Market Mode (teal/aqua emphasis): “Buy Zone” is stricter (deeper downside needed).
Hype Market Mode (red emphasis): sell logic can become stricter; special “blow-off” logic can apply.
4) Signals (shapes) and how to act
Buy signals (below candles)
Small Buy (green triangle, tiny): early/smaller dip buy.
Buy (green triangle, small): stronger dip buy.
Strong Buy (aqua/teal triangle): bear-market style buy (typically deeper undervaluation).
Golden Buy (yellow triangle): rare, deep-cycle accumulation style signal.
Blow-Off Buy (green diamond): buy signal during hype/blow-off conditions when a dip is attractive.
Sell signals (above candles)
Sell (red triangle, tiny): regular sell / take-profit signal.
Sell (Blow-Off) (red triangle, larger): blow-off top style sell signal.
BM Sell (red X-cross): bear-market “soft sell” / risk-off sell signal.
Practical usage idea (simple and robust)
Context first : use the trigger lines to see whether price is in Buy Zone or Sell Zone.
Wait for confirmation : act on the signal shapes (not just touching a line).
Scale in/out : consider multiple entries on buy signals and partial exits on sell signals (instead of all-in/all-out).
5) “Show Signals…” (reducing repaint surprises)
when they appear : signals can appear intraday and may vanish before the daily candle closes.
on the day of action : signals are shown after the daily candle closes (confirmed; plotted 1 day later).
Tip: If you want the cleanest, least-surprising signals, use on the day of action .
6) Signal Barometer (optional)
Show Signal Barometer : displays Buy and Sell likelihood for the current daily candle from 0–10.
How to interpret : 0 = unlikely, 10 = very likely / a signal is present.
Highlight historical barometer : visually highlights candles when the barometer is above your chosen threshold (commonly 8–10).
7) Alerts (TradingView)
Buy
Strong Buy
Golden Buy
Sell (includes bull sells, blow-off sells, and BM sells)
Altcoins
BPS is BTC-focused. If you want similar signal-style analysis on altcoin charts, use the separate Altcoin Profit Scout indicator (where available to you).
Free video walkthrough + deeper explanations
If you want a step-by-step video walkthrough and additional explanations/examples for Bitcoin Profit Scout, you can access them on our website (free): algoros.ai
Notes / expectations
BPS is designed for daily BTC charts . Using other timeframes or non-BTC symbols will degrade results and may hide signals.
Signals are based on multiple data sources (e.g., funding proxies and on-chain SOPR). Occasional data delays from providers can shift timing.
This is not financial advice; use risk management and position sizing.
Sentiment Trader v4.1 StrategySentiment Trader v4.1 Strategy — How to use
Purpose: A rules-based BTC/ETH daily strategy that combines multiple market regime inputs (trend zones, funding conditions, SOPR, and BPS-style signals) to plot clear Long / Short entries and trailing-stop based exits.
1) Required setup (important)
Preset : Select your market via the Strategy input:
BTC 1D → requires BITSTAMP:BTCUSD
ETH 1D → requires BITSTAMP:ETHUSD
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you select the wrong symbol / timeframe / chart type, the script shows an on-chart warning message and signals may be missing.
2) What you see on the chart
Long : blue triangle below the candle.
Short : pink/red triangle above the candle.
Long Close : X marker (exit) after a long position.
Short Close : X marker (exit) after a short position.
Trailing Stop lines :
TSL Long (aqua): trailing stop reference for long positions
TSL Short (red): trailing stop reference for short positions
3) Practical usage (simple)
Start with the correct setup (symbol + Daily + standard chart).
Treat signals as a system : avoid mixing entries/exits with unrelated intraday signals (this is designed for daily regimes).
Use risk management : position sizing, max drawdown rules, and (if trading manually) your own execution discipline.
4) Backtesting period (built-in)
Customize strategy tool for a specific time period : limits entries to your chosen start/end dates.
Tip : Avoid TradingView “deep backtesting” for this script — it can cut off previously collected data and distort signal calculation.
5) Data dependencies
This strategy references external series such as GLASSNODE:* and CRYPTOCAP:USDT.D . If your TradingView plan/exchange access does not provide these series, results may differ or parts may not work.
6) Alerts + automation note (important)
TradingView’s Terms of Use state that TradingView market data (including charts, alerts, and webhooks) is licensed for display-only use and prohibits non-display usage , including automated trading / automated order generation and similar machine-driven processing. Please review the current policy text before using alerts with any third-party tooling: tradingview.com/policies .
If you want a free walkthrough on understanding the signals and setting up alerts/notifications, you can visit our website: algoros.ai
Notes / expectations
This is not financial advice.
Past performance is not indicative of future results.
DurdenBTCs Dual Signal Trend SentinelA Bitcoin-Specific Strategy that Beats Buy and Hold
This is a Volatility Adjusted Momentum (VAMS) strategy tuned specifically for Bitcoin. Unlike standard Moving Average crossovers that get chopped up in sideways markets, this script uses Z-Score logic to normalize price distance from the trend, helping you stay in major moves and exit before deep drawdowns.
How It Works: Markets move in cycles. This strategy focuses on the Quarterly Cycle (approx. 3 months) to determine the dominant trend.
The Baseline: It calculates a 63-period trend baseline.
Volatility Adjustment: It measures the standard deviation of price around that baseline to assess real volatility.
The VAMS Score (Z-Score): It calculates exactly how many standard deviations price is away from the mean using the formula: (Close - Baseline) / Volatility .
The Signal Logic: The strategy classifies the market into three clear regimes using a color-coded background:
🟢BULLISH (Green Background): Price is > 0.5 Standard Deviations above the baseline. This indicates a strong momentum breakout. The strategy enters a Long position here.
🔴BEARISH (Red Background): Price is < -0.5 Standard Deviations below the baseline. This indicates trend failure. The strategy Closes All positions to preserve capital.
🟠NEUTRAL (Gray/Orange Background): Price is chopping between -0.5 and 0.5. This is the "noise" zone where trends are undefined. You can customize how you want the strategy to work at this point.
Why Use This?
Visual Clarity: The background color tells you the regime instantly, no need to guess.
Objective Entries/Exits : Removes emotion by using math-based volatility thresholds rather than arbitrary price levels.
Tuned for BTC: The 63-length lookback is specifically chosen to capture Bitcoin's quarterly flows.
🚀 Want More Precision? This script is the "Core" version of my trading framework. If you like this logic but want to reduce lag and capture moves even earlier, check out my private script: Bitcoin Gaussian Volatility Trend Signal . Access is granted to Substack subscribers.
The private version includes advanced Gaussian smoothing to filter out fake-outs that standard moving averages miss, offering a sharper edge for active investors.
Disclaimer: Past performance is not indicative of future results.
HMA Trend Scalper V1[wjdtks255]
Overview
This indicator is a high-performance trend-following system optimized for crypto futures trading. It provides clear entry signals and dynamic, real-time risk management tools to help traders stay on the right side of the market.
Key Features
Dynamic Trend Tracking: Uses a specialized HMA (Hull Moving Average) to filter market noise and identify the core trend.
Real-time TP/SL Extension: Unlike static indicators, the Take Profit (TP) and Stop Loss (SL) lines extend candle-by-candle along with the price action.
Clean Chart UI: Lines only exist from the entry point to the current candle, preventing chart clutter.
Automatic Completion: Once the price hits a target, the line stops extending and marks the result (Target Hit or Stop Out).
Trading Strategy (How to Trade)
1. Long Entry (🚀 LONG)
Condition: The price must be above the trend line, and a breakout of the recent 5-candle high must occur with significant volume.
Action: Enter a Long position when the "🚀 LONG" label appears.
Exit: Hold until the price reaches the Cyan (Aqua) TP line or hits the Yellow SL line.
2. Short Entry (💀 SHORT)
Condition: The price must be below the trend line, and a breakdown of the recent 5-candle low must occur with significant volume.
Action: Enter a Short position when the "💀 SHORT" label appears.
Exit: Hold until the price reaches the Cyan (Aqua) TP line or hits the Yellow SL line.
3. Risk Management
Stop Loss: The indicator automatically calculates the optimal SL based on recent volatility (ATR) and swing points.
Take Profit: The TP is set at a calculated ratio to ensure a positive risk-to-reward setup.
Settings
Trend Sensitivity: Adjust the HMA length to match your preferred timeframe (Scalping vs. Swing).
Volume Multiplier: Filter out weak moves by increasing the volume breakout requirement.
Custom Styles: Fully customize line colors, widths, and styles (Solid, Dashed, Dotted) in the settings menu.
Chaban Fibonacci Precision: BTC & ETH 5m Engine Chaban Fibonacci Precision: BTC & ETH 5m Engine
Chaban Fibonacci Precision is a professional-grade trading engine meticulously engineered for the high-velocity volatility of BTC & ETH 5-minute charts. This system goes beyond standard indicators by integrating Institutional Trend Anchoring with Proprietary Fibonacci Volatility Bands, filtering out market noise to capture reversals with surgical precision.
Trend Anchor: Defines the primary market bias, ensuring you trade in sync with the "Smart Money" (Institutional flow).
Fibonacci Precision Zones: Utilizes dynamic volatility thresholds based on Fibonacci sequences to pinpoint exact exhaustion points without manual drawing.
Structural Confirmation: Integrates cloud-based structural filters to verify trend stability before issuing any signal.
Professional Interface: Designed for maximum clarity, reducing chart clutter and allowing you to focus entirely on execution.
Trend Identification: The engine establishes a clear market bias, preventing users from making the mistake of trading against the major flow.
Precision Entry: Buy/Sell signals (Triangles) are generated exactly when the price reaches our proprietary Fibonacci boundaries, indicating market exhaustion.
Dynamic Rotation: The engine immediately adjusts its bias as market structures evolve, identifying new opportunities in real-time.
Leverage: It is strongly recommended to use leverage of 5x or lower.
Position Sizing: Always utilize a layered (scaled) entry approach.
Entry Strategy: Initiate trades based on the Trend-aligned Buy/Sell signals. For additional entries, add to your position near the band boundaries in the direction of the trend.
Example: In an Uptrend, only look for entries near the Lower Band. In a Downtrend, only look for entries near the Upper Band.
Take-Profit (TP) Strategy: Once in profit, use a scaled exit strategy:
Long Positions: Scale out near the Upper Band in the direction of the trend.
Short Positions: Scale out near the Lower Band in the direction of the trend.
By following the setup shown in the provided screenshots, you will receive three types of alerts: Trend Shift, Long Signal, and Short Signal.
Note: Long and Short alerts serve as "Preliminary Entry Alerts." Therefore, they may not always coincide exactly with the appearance of the triangle icons. Always use them as a preparation signal.
Dual-Asset Optimization: Specifically tuned for the unique liquidity and volatility of BTC and ETH.
Timeframe Focused: Engineered and tested for optimal performance on the 5-minute chart for scalpers and day traders.
Invite-Only Access: A premium tool designed for disciplined traders.
To request access to the Chaban Fibonacci Precision engine or for any setup inquiries, please send a Private Message (PM) on TradingView.
Global Money Flow & Liquidity [Inter-market]This script helps you define the current smart money (institutional) flow between most important assets in the world. Metal (Gold, Silver), USD assets (U.S. Treasuries/Bond) and Cryptocurrencies (BTC).
The Y-Axis: Z-Score (Standard Deviation)
Instead of showing Price (where Gold is $2000 and S&P is $4000), this script converts everything into "Sigma" or Z-Score.
+2.0 (High): This means the price is 2 standard deviations above its average. This is statistically "expensive" or "overextended." A reversal usually happens here.
0.0 (The Zero Line): This is the Mean (Average). If a line is at 0, the asset is trading exactly at its average value for the lookback period (20 days in your settings). It is "fair value."
-2.0 (Low): This means the price is 2 standard deviations below its average. This is statistically "cheap" or "oversold."
The Correlation shows how relevant those assets are related to the current chart, e.g., if you are looking at Gold, then the Corr. should be 0.99 or close to 1.
BTC Valuation ZonesBTC Valuation – Distance From 200 MA
This indicator provides a simple but powerful Bitcoin valuation framework based on how far price is from the 200-period Moving Average, a level that has historically acted as Bitcoin’s long-term equilibrium.
Instead of predicting tops or bottoms, this tool focuses on mean-reversion behavior:
When price deviates too far above the 200 MA → risk increases
When price deviates deeply below the 200 MA → long-term opportunity increases
Adoptive Conditional range High/Low MA Crossover StrategyDeveloped from the doctoral research of Abu-Kadunagra at ****** University's in Australia, this strategy implements a "Campaign-Based Adaptive Execution" framework. It moves beyond simple entries and exits by treating each market engagement as a multi-phase campaign with distinct operational states. The system intelligently identifies cyclical turning points, then employs a feedback-driven approach to capital allocation—reinforcing successful momentum with pyramiding while deploying controlled defensive averaging during temporary setbacks. By anchoring its exit mechanism to dynamically updated market structure rather than static profit targets, the algorithm seeks to capture cyclical momentum while maintaining disciplined risk parameters. This research-driven approach represents an evolution toward state-aware algorithmic systems that adapt their tactics in real-time based on market phase recognition.
Conditional-range High/Low adoptive-MA Crossover StrategyDeveloped from the doctoral research of Abu-Kadunagra at ****** University on topic of Digital Finance and Crypto in Australia, this strategy implements a "Campaign-Based Adaptive Execution" framework. It moves beyond simple entries and exits by treating each market engagement as a multi-phase campaign with distinct operational states. The system intelligently identifies cyclical turning points, then employs a feedback-driven approach to capital allocation—reinforcing successful momentum with pyramiding while deploying controlled defensive averaging during temporary setbacks. By anchoring its exit mechanism to dynamically updated market structure rather than static profit targets, the algorithm seeks to capture cyclical momentum while maintaining disciplined risk parameters. This research-driven approach represents an evolution toward state-aware algorithmic systems that adapt their tactics in real-time based on market phase recognition.
Vel-SIGThis pine script will give you an idea about the markets are in trending or rangebound. based on this you can take your decision whether you can buy or sell or right option.
BTC ETF Average Inflow Cost BasisConcept
Since the historic launch of Bitcoin Spot ETFs on January 11, 2024, institutional flows have become a major driver of price action. This indicator aims to visualize the aggregate Cost Basis (average entry price) of the major Bitcoin ETFs relative to the underlying asset.
It serves as an on-chain proxy for institutional positioning, helping traders identify critical support levels where ETF inflows have historically concentrated.
How it Works
The script aggregates daily volume data from the top Bitcoin ETFs (IBIT, FBTC, ARKB, GBTC, BITB) and compares it against the Bitcoin price (BTCUSDT).
ETF Cost Basis (Pink Line):
This is calculated as a Cumulative Volume-Weighted Average Price (VWAP), anchored specifically to the ETF launch date (Jan 11, 2024).
Formula: It accumulates (BTC Price * Total ETF Volume) and divides it by the Cumulative Total ETF Volume.
This creates a dynamic level representing the "breakeven" price for the aggregate volume traded through these funds.
True Market Mean (Gray Line):
This represents the simple cumulative average of the Bitcoin price since the ETF launch date. It acts as a neutral baseline for the post-ETF market era.
How to Use
Institutional Support: The Cost Basis line often acts as a strong dynamic support level during corrections. When price revisits this level, it suggests the market is returning to the average institutional entry price.
Trend Filter:
Price > Cost Basis: The market is in a net profit state relative to ETF flows (Bullish/Trend continuation).
Price < Cost Basis: The market is in a net loss state (Bearish/Capitulation risk).
Confluence: The intersection of the Cost Basis and the True Market Mean can signal pivotal moments of trend reset.
Features
Data Aggregation: Pulls data from 5 major ETFs via request.security without repainting (using closed bars).
Dashboard: Includes a table in the top-right corner displaying real-time values for Price, Cost Basis, and Market Mean.
Customization: You can toggle individual ETF Moving Averages in the settings (disabled by default due to price scale differences between BTC and ETF shares).
Disclaimer
This tool is for educational purposes only and attempts to estimate institutional cost basis using volume proxies. It does not represent financial advice.
Vega Convexity Regime Filter [Institutional Lite]STOP TRADING THE NOISE.
90% of retail trading losses occur during "Chop"—sideways markets where standard trend-following bots bleed capital through slippage and fees. Institutional desks know that the secret to high returns isn't just winning trades; it's knowing when to sit in cash.
The Vega V6 Regime Filter is the "Gatekeeper" layer of our proprietary Hierarchical Machine Learning engine (developed by a 25-year TradFi Risk Quant). It calculates a composite volatility score to answer one simple question: Is this asset tradeable right now?
THE VISUAL LOGIC
This indicator visually filters market conditions into two distinct Regimes based on our institutional backtests:
🌫️ GREY BARS (Noise / Chop)
The State: Volatility is compressing. The trend is undefined or weak.
The Trap: This is where MACD/RSI give false signals.
Institutional Action: Sit in Cash. Preserve Capital. Wait.
🟢 🔴 COLORED BARS (Impulse)
The State: Volatility is expanding. Momentum is statistically significant.
The Opportunity: A "Fat-Tail" move is likely beginning.
Institutional Action: Deploy Risk. Look for entries.
HOW IT WORKS (The Math)
Unlike simple moving average crossovers, the Vega Gatekeeper analyzes 4 distinct market dimensions simultaneously to generate a Tradeability Score (0-10) :
Trend Strength (ADX): Is there a vector?
Momentum (RSI/MACD): Is the move accelerating?
Volatility (Bollinger Bands): Is the range expanding?
Volume Flow: Is there institutional participation?
The Rule: If the composite score is < 4 , the market is Noise. The bars turn Grey. You do nothing.
BEST PRACTICES
For Swing Trading (Daily): Use Medium sensitivity. Only look for entries when the background turns Green/Red.
For Day Trading (4H/1H): Use Low sensitivity (more conservative). Use the Grey zones to tighten stops or exit positions.
THE PHILOSOPHY: "CASH IS A POSITION"
Most traders feel the need to be in a trade 24/7. The Vega V6 Engine (the system this tool is based on) achieved a +3,849% backtested return (18 months) largely by sitting in cash during chop. This tool visualizes that discipline.
🔒 WANT THE DIRECTIONAL SIGNALS?
This Lite version provides the Regime (When to trade).
To get the specific Entry Signals , Intraday Stop-Losses , and Probability Matrix (Stage 2 of our model), you need the Vega V6 Convexity Engine .
The Pro Version includes:
🚀 Specific Direction: Classification of "Explosion," "Rally," or "Crash."
🛡️ Dynamic Risk: Plots the exact Stop Loss levels used in our institutional backtests.
🌊 Macro Data: Integration of M2 Liquidity flow alerts.
👉 ACCESS INSTRUCTIONS:
Links to the Pro System , our Live Dashboard , and the 18-Month Performance Audit can be found in the Author Profile below or in the script settings.
Disclaimer: This tool is for educational purposes only. Past performance is not indicative of future results. Trading cryptocurrencies involves significant risk.
AlphaGen ME V.15.12AlphaGen ME V.15.10 is an ATR-based trend-following strategy with dynamic trailing stops and EMA filter, designed for automated Crypto perpetual trading.
Core Logic:
• ATR Trailing Stops: Dynamically adjusts stop-loss using ATR(10) × 3.0 multiplier
• 200 EMA Trend Filter: Optional Only takes longs above EMA, shorts below EMA
• Reversal System: Flips positions when trend changes (filter-aware)
• MACD Acceleration Exit: Optional momentum-based profit taking
Position Sizing Modes:
• Simple % of Equity (default 90%) - Safe leverage control
• Risk % of Equity - Fixed risk per trade
• Fixed Contract Size - Consistent lot sizing
Webhook Integration:
Routes signals directly to AlphaGen-AI for execution on:
• Hyperliquid DEX
• AsterDEX
Requirements:
• AlphaGen-AI Pro subscription for webhook routing
• Hyperliquid or AsterDEX Wallets
• TradingView alerts configured with passphrase
Risk Disclosure: Trading involves substantial risk. Past performance does not guarantee future results. Only trade with capital you can afford to lose.
Structure Break ModelMAIN FEATURES
Supported Assets & Timeframe
This indicator is specifically designed and calibrated for 30 USDT trading pairs on the H4 timeframe, all of which have been actively traded for over 1,000 days, including:
BTCUSDT, ETHUSDT, XRPUSDT, BNBUSDT, SOLUSDT, TRXUSDT, DOGEUSDT, ADAUSDT, XLMUSDT, BCHUSDT,
ZECUSDT, LINKUSDT, HBARUSDT, UNIUSDT, LTCUSDT, AVAXUSDT, SHIBUSDT, DOTUSDT, AAVEUSDT, NEARUSDT,
ETCUSDT, ICPUSDT, FILUSDT, APTUSDT, ENSUSDT, ATOMUSDT, VETUSDT, QNTUSDT, CRVUSDT, INJUSDT
Using the script on other pairs or timeframes will trigger an automatic warning to prevent incorrect usage.
1. Structural Weakening Model (Core Logic)
At the heart of the system lies the Structural Weakening Model (SWM) — a multi-layered market-structure engine that identifies momentum exhaustion and confirms genuine reversals using pivot-based swing architecture.
Pivot Structure Mapping
The indicator continuously analyzes Pivot Highs and Pivot Lows (length = 5) to establish clean, stable swing structure.
Weakening Pattern Detection
The model evaluates directional fatigue by detecting pivot sequences:
2–6 Higher Lows → Weakening buyers → Potential SELL setup
2–6 Lower Highs → Weakening sellers → Potential BUY setup
This mechanism identifies “compression zones” where market pressure fades before a structural shift.
Breakout Confirmation Layer
A signal is only triggered when price breaks the final structural anchor of the pivot chain.
This ensures:
Optional Trend Filter (MA Alignment)
Users may select EMA, SMA, WMA, HMA and more.
Price above MA → BUY-only mode
Price below MA → SELL-only mode
This keeps signals aligned with broader market flow.
Visual Example – SELL Signal (TP Hit)
2. Signal Conditions (How the System Works)
SELL Setups
Triggered when:
Price forms 2–6 higher lows, signaling weakening buyers
Price breaks below the structural pivot anchor
(Optional) Price is below the MA filter
BUY Setups
Triggered when:
Price forms 2–6 lower highs, signaling weakening sellers
Price breaks above the structural pivot anchor
(Optional) Price is above the MA filter
Visual Example – SELL Signal (SL Hit)
3. Automatic Capital Management
The script integrates full risk-management utilities:
Starting capital (default 10,000 USDT)
Risk % per trade
Leverage (x10 → x100)
Automatic position sizing
Margin requirements
Real-time TP/SL calculations
This turns the indicator into not just a signal tool, but a complete trading assistant.
4. Flexible Stop-Loss System
Users may choose:
Swing-based SL (nearest structural pivot)
Fixed SL %
Custom TP based on R:R (1:1.5 → 1:5)
Default R:R = 1:2
SL/TP levels update instantly whenever settings change.
Input Settings Menu
5. Visual Interface
The chart displays:
Entry, TP, SL (extended 20 candles)
BUY/SELL labels
Real-time TP/SL hit status
Full info panel:
Latest signal
Entry price
TP/SL
Leverage
Risk %
Required margin
Win/loss & R statistics
Days on chart: The total number of trading days calculated from your chart’s visible data
All signals follow the exact same logic in historical and real-time charts.
Zero repainting.
6. Internal Backtest Engine (Not Official TradingView Backtesting)
The script includes an internal backtest calculator that evaluates:
SL methods
TP R:R settings
Signal quality
Aggregate R performance
⚠ This is an internal calculation tool, not the official TradingView Strategy Tester.
Its purpose is to help users understand how different settings behave when applied to past data.
7. 1-Day Free Trial
Users may message the author on TradingView to request:
1-day trial access
Ability to test signals in real-time
Compare different SL/RR settings
Verify that the indicator does not repaint
Inspect how the engine behaves on the supported 30-coin dataset
This allows users to evaluate the tool transparently before subscribing.
8. Market Coverage & Deep Backtest Basis This indicator is calibrated on the 30 largest USDT pairs, providing a deep historical dataset with stable liquidity and clearer structural swings. The long backtest range and high signal density help reduce noise and ensure more consistent behavior across different market conditions.
⚠ Disclaimer
This indicator is a quantitative analysis tool created for educational purposes only.
All “optimal settings” are derived from historical market behavior and do not guarantee future performance.
Market conditions change, and every trader must apply independent risk management.
Trading involves risk.
Use responsibly.
BTC DCA Risk Metric StrategyBTC DCA Risk Strategy - Automated Dollar Cost Averaging with 3Commas Integration
Overview
This strategy combines the proven Oakley Wood Risk Metric with an intelligent tiered Dollar Cost Averaging (DCA) system, designed to help traders systematically accumulate Bitcoin during periods of low risk and take profits during high-risk conditions.
Key Features
📊 Multi-Component Risk Assessment
4-Year SMA Deviation: Measures Bitcoin's distance from its long-term mean
20-Week MA Analysis: Tracks medium-term momentum shifts
50-Day/50-Week MA Ratio: Captures short-to-medium term trend strength
All metrics are normalized by time to account for Bitcoin's maturing market dynamics
💰 3-Tier DCA Buy System
Level 1 (Low Risk): Conservative entry with base allocation
Level 2 (Lower Risk): Increased allocation as opportunity improves
Level 3 (Extreme Low Risk): Maximum allocation during rare buying opportunities
Buys execute every bar while risk remains below thresholds, enabling true DCA accumulation
📈 Progressive Profit Taking
Sell Level 1: Take initial profits as risk increases
Sell Level 2: Scale out further positions during elevated risk
Sell Level 3: Final exit during extreme market conditions
Sell levels automatically reset when new buy signals occur, allowing flexible re-entry
🤖 3Commas Integration
Fully automated webhook alerts for Custom Signal Bots
JSON payloads formatted per 3Commas API specifications
Supports multiple exchanges (Binance, Coinbase, Kraken, Gemini, Bybit)
Configurable quote currency (USD, USDT, BUSD)
How It Works
The strategy calculates a composite risk metric (0-1 scale):
0.0-0.2: Extreme buying opportunity (green zone)
0.2-0.5: Favorable accumulation range (yellow zone)
0.5-0.8: Neutral to cautious territory (orange zone)
0.8-1.0+: High risk, profit-taking zone (red zone)
Buy Logic: As risk decreases, position sizes increase automatically. If risk drops from L1 to L3 threshold, the strategy combines all three tier allocations for maximum exposure.
Sell Logic: Sequential profit-taking ensures you capture gains progressively. The system won't advance to Sell L2 until L1 completes, preventing premature full exits.
Configuration
Risk Metric Parameters:
All calculations use Bitcoin price data (any BTC chart works)
Time-normalized formulas adapt to market maturity
No manual parameter tuning required
Buy Settings:
Set risk thresholds for each tier (default: 0.20, 0.10, 0.00)
Define dollar amounts per tier (default: $10, $15, $20)
Fully customizable to your risk tolerance and capital
Sell Settings:
Configure risk thresholds for profit-taking (default: 1.00, 1.50, 2.00)
Set percentage of position to sell at each level (default: 25%, 35%, 40%)
3Commas Setup:
Create a Custom Signal Bot in 3Commas
Copy Bot UUID and Secret Token into strategy inputs
Enable 3Commas Alerts checkbox
Create TradingView alert: Condition → "alert() function calls only", Webhook → api.3commas.io
Backtesting Results
Strengths:
Systematically buys dips without emotion
Averages down during extended bear markets
Captures explosive bull run profits through tiered exits
Pyramiding (1000 max orders) allows true DCA behavior
Considerations:
Requires sufficient capital for multiple buys during prolonged downtrends
Backtest on Daily timeframe for most reliable signals
Past performance does not guarantee future results
Visual Design
The indicator pane displays:
Color-coded risk metric line: Changes from white→red→orange→yellow→green as risk decreases
Background zones: Green (buy), yellow (hold), red (sell) areas
Dashed threshold lines: Clear visual markers for each buy/sell level
Entry/Exit labels: Green buy labels and orange/red sell labels mark all trades
Credits
Original Risk Metric: Oakley Wood
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Modifications: pommesUNDwurst
Disclaimer
This strategy is for educational and informational purposes only. Cryptocurrency trading carries substantial risk of loss. Always conduct your own research and never invest more than you can afford to lose. The authors are not financial advisors and assume no responsibility for trading decisions made using this tool.
Bitcoin Multibook v1.0 [Apollo Algo]Bitcoin Multibook v1.0 by Apollo Algo is an advanced market depth and order flow visualization tool that brings professional-grade multi-exchange order book analysis to TradingView. Inspired by Bookmap's multibook functionality and built upon LucF's original single "Tape" indicator concept, this tool aggregates real-time trading data from multiple Bitcoin exchanges into a unified tape display.
Credits & Attribution
This indicator is an evolution of the original "Tape" indicator created by LucF (TradingView: @LucF). The multibook enhancement and Bitcoin-specific optimizations were developed by Apollo Algo to provide traders with institutional-grade market microstructure visibility across major Bitcoin trading venues.
Purpose & Philosophy
Bitcoin leads the entire cryptocurrency market. By monitoring order flow across the primary Bitcoin exchanges simultaneously, traders gain crucial insights into:
Cross-exchange arbitrage opportunities
Institutional order flow patterns
Market maker positioning
True market sentiment beyond single-exchange data
Key Features
📊 Multi-Exchange Data Aggregation
Real-time tape from 3 major exchanges:
Binance (BTCUSDT)
Coinbase (BTCUSD)
Kraken (BTCUSD)
Customizable source inputs for any trading pair
Synchronized price and volume tracking
Exchange name identification in tape display
📈 Advanced Tape Display
Dynamic tape visualization with configurable line quantity (0-50 lines)
Directional flow indicators (＋/－ symbols for price changes)
Exchange identification for each trade
Volume precision control (0-16 decimal places)
Flexible positioning (9 screen positions available)
Real-time only operation for accurate order flow
🎯 Volume Delta Analysis
Real-time cumulative volume delta calculation
Divergence detection (price vs. volume direction)
Colored visual feedback for market sentiment
Total session delta displayed in footer
Cross-exchange delta aggregation
🚨 Smart Alert System
Marker 1: Volume Delta Bumps (⬆⬇)
Triggers on consecutive volume delta increases
Identifies momentum acceleration points
Filters out divergent movements
Marker 2: Volume Delta Thresholds (⇑⇓)
Fires when delta exceeds user-defined thresholds
Catches significant order imbalances
Excludes divergence conditions
Marker 3: Large Volume Detection (⤊⤋)
Highlights unusually large individual trades
Spots potential institutional activity
Direction-specific triggers
Configure Data Sources
Adjust exchange pairs if needed (e.g., for altcoin analysis)
Leave blank to disable specific exchanges
Use format: EXCHANGE:SYMBOL
Customize Display
Set tape line quantity based on screen size
Position the table for optimal visibility
Choose color scheme (text or background)
Adjust text size for readability
Configure Alerts
Enable desired markers (1, 2, or 3)
Set volume thresholds appropriate for your timeframe
Choose direction (Longs, Shorts, or Both)
Create TradingView alerts on marker signals
Trading Applications
Scalping (1-5 min)
Monitor tape speed for momentum shifts
Watch for cross-exchange divergences
Track large volume clusters
Use Marker 1 for quick momentum trades
Day Trading (5-60 min)
Identify accumulation/distribution phases
Spot institutional positioning
Confirm breakout validity with volume delta
Use Marker 2 for significant imbalances
Swing Trading (1H+)
Analyze volume delta trends
Detect smart money rotation
Time entries with order flow confirmation
Use Marker 3 for institutional footprints
Advanced Techniques
Cross-Exchange Arbitrage Detection
When price disparities appear between exchanges:
Immediate Opportunity: Price differences > 0.1%
Bot Activity: Rapid convergence patterns
Liquidity Vacuum: One exchange leading others
Divergence Trading Strategies
Volume delta diverging from price direction:
Absorption: Strong hands entering (price down, delta up)
Distribution: Smart money exiting (price up, delta down)
Reversal Setup: Sustained divergence over multiple bars
Institutional Footprint Recognition
Large volume characteristics:
Simultaneous Spikes: Same timestamp across exchanges
TWAP Patterns: Consistent volume over time
Iceberg Orders: Repeated same-size trades
Pine Script v6 Enhancements
Type Safety Improvements
Strict boolean type handling
Explicit type declarations
Enhanced error checking
Performance Optimizations
Improved request.security() function
Better memory management with arrays
Optimized table rendering
Modern Syntax Updates
indicator() instead of study()
Namespaced math functions (math.round())
Typed input functions (input.int(), input.float())
Performance Considerations
System Requirements
Real-time Data: Essential for tape operation
Multiple Security Calls: May impact performance
Array Operations: Memory intensive with high line counts
Table Rendering: CPU usage increases with tape size
Optimization Tips
Reduce tape lines for better performance
Increase volume filter to reduce noise
Disable unused markers
Use text-only coloring for faster rendering
Moon Boys LineWe have the 44 and 125 day moving averages. When they cross, the trend is bullish or bearish.
V-CORE Engine Free v1V-CORE Engine Free v1 — Public Release
This is a simplified trend-state visualiser from the V-CORE suite, designed for clean directional bias on crypto markets using 1H+ timeframes.
The engine runs fixed, non-editable internal logic with multi-stage trend confirmation.
No optimisation, no signals, no settings — just locked-in regime detection for educational and research use.
This free edition is a lightweight derivative of our internal V-CORE Engine architecture.
It includes only the essential background-state display while keeping all proprietary components sealed.
For additional V-CORE tools, future releases, or extended versions, please visit our TradingView profile.
MACD Forecast Colorful [DiFlip]MACD Forecast Colorful
The Future of Predictive MACD — is one of the most advanced and customizable MACD indicators ever published on TradingView. Built on the classic MACD foundation, this upgraded version integrates statistical forecasting through linear regression to anticipate future movements — not just react to the past.
With a total of 22 fully configurable long and short entry conditions, visual enhancements, and full automation support, this indicator is designed for serious traders seeking an analytical edge.
⯁ Real-Time MACD Forecasting
For the first time, a public MACD script combines the classic structure of MACD with predictive analytics powered by linear regression. Instead of simply responding to current values, this tool projects the MACD line, signal line, and histogram n bars into the future, allowing you to trade with foresight rather than hindsight.
⯁ Fully Customizable
This indicator is built for flexibility. It includes 22 entry conditions, all of which are fully configurable. Each condition can be turned on/off, chained using AND/OR logic, and adapted to your trading model.
Whether you're building a rules-based quant system, automating alerts, or refining discretionary signals, MACD Forecast Colorful gives you full control over how signals are generated, displayed, and triggered.
⯁ With MACD Forecast Colorful, you can:
• Detect MACD crossovers before they happen.
• Anticipate trend reversals with greater precision.
• React earlier than traditional indicators.
• Gain a powerful edge in both discretionary and automated strategies.
• This isn’t just smarter MACD — it’s predictive momentum intelligence.
⯁ Scientifically Powered by Linear Regression
MACD Forecast Colorful is the first public MACD indicator to apply least-squares predictive modeling to MACD behavior — effectively introducing machine learning logic into a time-tested tool.
It uses statistical regression to analyze historical behavior of the MACD and project future trajectories. The result is a forward-shifted MACD forecast that can detect upcoming crossovers and divergences before they appear on the chart.
⯁ Linear Regression: Technical Foundation
Linear regression is a statistical method that models the relationship between a dependent variable (y) and one or more independent variables (x). The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted variable (e.g., future MACD value)
x = independent variable (e.g., bar index)
β₀ = intercept
β₁ = slope
ε = random error (residual)
The regression model calculates β₀ and β₁ using the least squares method, minimizing the sum of squared prediction errors to produce the best-fit line through historical values. This line is then extended forward, generating a forecast based on recent price momentum.
⯁ Least Squares Estimation
The regression coefficients are computed with the following formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Regression in Machine Learning
Linear regression is a foundational model in supervised learning. Its ability to provide precise, explainable, and fast forecasts makes it critical in AI systems and quantitative analysis.
Applying linear regression to MACD forecasting is the equivalent of injecting artificial intelligence into one of the most widely used momentum tools in trading.
⯁ Visual Interpretation
Picture the MACD values over time like this:
Time →
MACD →
A regression line is fitted to recent MACD values, then projected forward n periods. The result is a predictive trajectory that can cross over the real MACD or signal line — offering an early-warning system for trend shifts and momentum changes.
The indicator plots both current MACD and forecasted MACD, allowing you to visually compare short-term future behavior against historical movement.
⯁ Scientific Concepts Used
Linear Regression: models the relationship between variables using a straight line.
Least Squares Method: minimizes squared prediction errors for best-fit.
Time-Series Forecasting: projects future data based on past patterns.
Supervised Learning: predictive modeling using labeled inputs.
Statistical Smoothing: filters noise to highlight trends.
⯁ Why This Indicator Is Revolutionary
First open-source MACD with real-time predictive modeling.
Scientifically grounded with linear regression logic.
Automatable through TradingView alerts and bots.
Smart signal generation using forecasted crossovers.
Highly customizable with 22 buy/sell conditions.
Enhanced visuals with background (bgcolor) and area fill (fill) support.
This isn’t just an update — it’s the next evolution of MACD forecasting.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the MACD?
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ How to use the MACD?
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
• Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
• Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
• Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
• Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ How to use MACD forecast?
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
📈 BUY
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
📉 SELL
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
