MACD StrategyOverview
The "MACD Strategy" is a straightforward trading strategy tested for BTCUSDT Futures on the 1-minute timeframe, leveraging the Moving Average Convergence Divergence (MACD) indicator to identify momentum-based buy and sell opportunities. Developed with input from expert trading analyst insights, this strategy combines technical precision with risk management, making it suitable for traders of all levels on platforms like TradingView. It focuses on capturing trend reversals and momentum shifts, with clear visual cues and automated alerts for seamless integration with trading bots (e.g., Bitget webhooks).
#### How It Works
This strategy uses the MACD indicator to generate trading signals based on momentum and trend direction:
- **Buy Signal**: Triggered when the MACD line crosses above the signal line, and the MACD histogram turns positive (above zero). This suggests increasing bullish momentum.
- **Sell Signal**: Triggered when the MACD line crosses below the signal line, and the MACD histogram turns negative (below zero), indicating growing bearish momentum.
Once a signal is detected, the strategy opens a position (long for buy, short for sell) with a position size calculated based on your risk tolerance. It includes a stop-loss to limit losses and a take-profit to lock in gains, both dynamically adjusted using the Average True Range (ATR) for adaptability to market volatility.
#### Key Features
- **MACD-Based Signals**: Relies solely on MACD for entry points, plotted in a separate pane for clear momentum analysis.
- **Risk Management**: Automatically calculates position size based on a percentage of your account balance and sets stop-loss and take-profit levels using ATR multipliers and a risk:reward ratio.
- **Visual Feedback**: Plots entry, stop-loss, and take-profit lines on the chart with labeled markers for easy tracking.
- **Alerts**: Includes Bitget webhook-compatible alerts for automated trading, notifying you of buy and sell signals in real-time.
#### Input Parameters
- **Account Balance**: Default 10000 – Set your initial trading capital to determine position sizing.
- **MACD Fast Length**: Default 12 – The short-term EMA period for MACD sensitivity.
- **MACD Slow Length**: Default 26 – The long-term EMA period for MACD calculation.
- **MACD Signal Length**: Default 9 – The smoothing period for the signal line.
- **Risk Per Trade (%)**: Default 3.0 – The percentage of your account balance risked per trade (e.g., 3% of 10000 = 300).
- **Risk:Reward Ratio**: Default 3.0 – The ratio of potential profit to risk (e.g., 3:1 means risking 1 to gain 3).
- **SL Multiplier**: Default 1.0 – Multiplies ATR to set the stop-loss distance (e.g., 1.0 x ATR).
- **TP Multiplier**: Default 3.0 – Multiplies ATR to set the take-profit distance, adjusted by the risk:reward ratio.
- **Line Length (bars)**: Default 25 – Duration in bars for displaying trade lines on the chart.
- **Label Position**: Default 'left' – Position of text labels (left or right) relative to trade lines.
- **ATR Period**: Default 14 – The number of periods for calculating ATR to measure volatility.
#### How to Use
1. **Add to Chart**: Load the "MACD Strategy" as a strategy and the "MACD Indicator" as a separate indicator on your TradingView chart (recommended for BTCUSDT Futures on the 1-minute timeframe).
2. **Customize Settings**: Adjust the input parameters based on your risk tolerance and market conditions. For BTCUSDT Futures, consider reducing `Risk Per Trade (%)` during high volatility (e.g., 1%) or increasing `SL Multiplier` for wider stops.
3. **Visual Analysis**: Watch the main chart for trade entry lines (green for buy, red for sell), stop-loss (red), and take-profit (green) lines with labels. Use the MACD pane below to confirm momentum shifts.
4. **Set Alerts**: Create alerts in TradingView for "Buy Signal" and "Sell Signal" to automate trades via Bitget webhooks.
5. **Backtest and Optimize**: Test the strategy on historical BTCUSDT Futures 1-minute data to fine-tune parameters. The short timeframe requires quick execution, so monitor closely for slippage or latency.
#### Tips for Success
- **Market Conditions**: This strategy performs best in trending markets on the 1-minute timeframe. Avoid choppy conditions where MACD crossovers may produce false signals.
- **Risk Management**: Start with the default 3% risk per trade and adjust downward (e.g., 1%) during volatile periods like BTCUSDT news events. The 3:1 risk:reward ratio targets consistent profitability.
- **Timeframe**: Optimized for 1-minute charts; switch to 5-minute or 15-minute for less noise if needed.
- **Confirmation**: Cross-check MACD signals with price action or support/resistance levels for higher accuracy on BTCUSDT Futures.
#### Limitations
- This strategy relies solely on MACD, so it may lag in fast-moving or sideways markets. Consider adding a secondary filter (e.g., RSI) if needed.
- Stop-loss and take-profit are ATR-based and may need adjustment for BTCUSDT Futures’ high volatility, especially during leverage trading.
#### Conclusion
The "MACD Strategy" offers a simple yet effective way to trade momentum shifts using the MACD indicator, tested for BTCUSDT Futures on the 1-minute timeframe, with robust risk management and visual tools. Whether you’re scalping crypto futures or exploring short-term trends, this strategy provides a solid foundation for automated or manual trading. Share your feedback or customizations in the comments, and happy trading!
Komut dosyalarını "scalping" için ara
Fair Value Gaps BOOSTED [LuxAlgo & mqsxn] Fair Value Gaps BOOSTED
This enhanced version of LuxAlgo’s Fair Value Gap indicator takes market imbalance detection to the next level. Built on the trusted foundation of the original, this extension introduces powerful new features designed for traders who want deeper insight and more control:
Extended Visualization – Fair Value Gaps now stretch farther into the past with customizable bar extensions, so you can easily track unmitigated gaps over longer distances of time.
Intersection Highlights – Automatically identify and shade overlapping bullish/bearish FVGs, giving instant visual clarity on high-confluence zones.
Center Lines & Mitigation Tracking – Optional center lines improve precision, while mitigation markers help confirm when gaps are filled.
Advanced Filtering – Control visibility with minimum gap sizes, custom start dates for gap formations, and per-direction display limits.
Dashboard Stats – On-chart metrics show the number of detected and mitigated gaps, plus percentages, at a glance.
Alerts Ready – Set up alerts for fresh FVG formation or mitigation events, so you never miss a key signal.
Whether you’re scalping, day trading, or swing trading, Fair Value Gaps BOOSTED helps you pinpoint institutional price imbalances and trade around them with confidence.
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Inputs & Settings
Threshold % / Auto
Defines the minimum gap size as a percentage of price. Enable Auto to let the script automatically adapt thresholding based on volatility.
Unmitigated Lines (combined)
Draws guide lines for a set number of the most recent unmitigated gaps.
Mitigation Levels
Shows dashed lines where gaps have been fully mitigated (filled).
Timeframe
Lets you calculate Fair Value Gaps on a higher or lower timeframe than the chart you’re viewing.
Style
Dynamic Mode
Keeps the most recent gap area actively updating with price as long as it remains unmitigated.
Extend Right (bars)
Controls how many bars into the future each gap visualization will project.
Bullish / Bearish Colors
Customize the fill colors of bullish and bearish gaps.
Center Line & Width
Adds a dotted line through the midpoint of each gap for visual precision.
Filter
Min Gap Size (ticks)
Only display gaps greater than or equal to this size.
Min Formation Date (days ago)
Show gaps formed within a given lookback window (e.g., only last 4 days).
Display
Show Last Bullish / Bearish (unmitigated)
Limit how many recent bullish or bearish gaps appear at once (set to 0 for unlimited).
Intersections
Show Intersections
Highlight overlapping bullish and bearish gaps as shaded zones.
Show Intersections Only
Hide individual gaps and show only the overlapping regions.
Intersection Color
Customize the fill for overlap areas.
Intersection Center Line / Width
Optionally plot a midpoint line through the overlap zone.
Dashboard
Show Dashboard
Display a compact on-chart table of bullish vs bearish counts and mitigation percentages.
Location
Choose where the dashboard sits (top right, bottom right, bottom left).
Size
Adjust text size (Tiny, Small, Normal).
Frozen 4H VWAP – Precision AnchoredFrozen 4H VWAP – Precision Anchored Like Ice
The Frozen 4H VWAP – Precision Anchored delivers a clean, stable, and reliable view of the 4-hour Volume Weighted Average Price, designed for traders who want higher timeframe insights without intrabar noise or repainting.
🔹 Key Features:
Non-Repainting: VWAP value is “frozen” at the close of each 4H candle — no mid-bar updates or flickering.
4H Timeframe Anchoring: Seamlessly pulls 4-hour VWAP values into any timeframe you’re trading on.
Clear Trend Reference: Updates only when a new 4H candle begins, acting as a trustworthy anchor for support/resistance.
Custom Source Option: Choose from different price sources (default: HLC3) to fit your strategy.
Whether you're scalping, day trading, or swing trading, this indicator gives you a powerful edge by grounding your decisions in higher timeframe VWAP data — clear, calm, and frozen in time.
Estrategy EURUSD M3 Scalping Estrategia para operar el EURUSD en temp de 3 min, indica sl y tp 6 pips sl y 10 pips tp
MK_OSFT-Multi-Timeframe MA Dashboard & Smart Alerts-v2📊 Multi-Timeframe MA Dashboard & Smart Alerts v2.0
Transform your trading with the ultimate moving average monitoring system that tracks up to 8 different MA configurations across multiple timeframes simultaneously.
🎯 What This Indicator Does
This advanced dashboard eliminates the need to constantly switch between timeframes by displaying all your critical moving averages on a single chart. Whether you're scalping on 5-minute charts or swing trading on daily timeframes, you'll instantly see the big picture.
⭐ Key Features
📈 Multi-Timeframe Moving Averages
Monitor up to **8 different MA configurations** simultaneously
Support for **SMA and EMA** across 6 timeframes (5m, 15m, 1h, 4h, Daily, Weekly)
Each MA fully customizable: length, color, alert settings, and visibility
Smart visual representation with labeled horizontal lines and connecting plots
🚨 Intelligent Alert System
Cross-over/Cross-under alerts for price vs MA interactions
Three alert modes : No alerts, Once only, or Once per bar close
Smart batching system prevents alert spam during volatile periods
Queue management with 3-second delays between alerts for optimal performance
Easy alert reset functionality for "once only" alerts
📊 Real-Time Information Dashboard
Live countdown timers showing time remaining until each timeframe closes
Color-coded progress bars with gradient visualization (green → yellow → orange → red)
Instant cross-over detection with up/down arrow indicators
Price vs MA relationship clearly displayed (above/below coloring)
🎨 Professional Visualization
Anti-overlap technology prevents labels from clustering
Customizable label positioning and sizing options
Drawing order control (larger timeframes first/last)
Connecting lines link current price to MA values
Status line integration for quick value reference
💡 Perfect For
Multi-timeframe traders [/b who need complete market context
Trend followers monitoring key MA levels across timeframes
Breakout traders waiting for price to cross critical moving averages
Risk managers using MAs as dynamic support/resistance levels
Anyone wanting organized, clutter-free MA monitoring
⚙️ Highly Configurable
Moving Average Settings
Individual enable/disable for each of 8 MA slots
Flexible timeframe selection : 5m, 15m, 1h, 4h, Daily, Weekly
MA type choice : SMA or EMA for each configuration
Custom lengths from 1 to any desired period
Color customization for each MA line and label
Alert Management
Per-MA alert configuration : Choose which MAs trigger alerts
Source selection : Current bar vs last confirmed bar calculations
Frequency control : Prevent over-alerting with smart queuing
Reset functionality : Easily reactivate "fired" once-only alerts
Display Options
Table positioning : Top-right, bottom-left, or bottom-right
Label styling : Size, offset, and gap control
Line customization : Width and extension options
Timezone adjustment : Align timestamps with your local time
🔧 Technical Excellence
Optimized performance with efficient array management and single-pass calculations
Real-time vs historical mode handling for accurate backtesting
Memory-efficient label and line management prevents accumulation
Robust error handling and edge case management
Clean, well-documented code following Pine Script best practices
📋 How to Use
Add to chart and configure your desired MA combinations
Set alert preferences for each MA (none/once/per bar)
Create TradingView alert using "Any alert() function calls"
Monitor the dashboard for cross-over signals and timeframe progress
Use the info table to track all MA values and alert statuses at a glance
🎓 Educational Value
This indicator serves as an excellent educational tool for understanding:
Multi-timeframe analysis principles
Moving average confluence and divergence
Alert system design and management
Professional indicator development techniques
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Transform your trading workflow with this professional-grade multi-timeframe MA monitoring system. No more chart hopping - get the complete moving average picture in one powerful dashboard!
© MK_OSF_TRADING | Pine Script v6 | Mozilla Public License 2.0
TIKOLE SVM Sentiment Combo Oscillator MACD"This one has MACD and RSI. Accuracy is very good. Best for 5-minute and 15-minute timeframes."
The script combines MACD-style histogram with RSI logic.
It gives high accuracy signals.
Works best on 5-minute and 15-minute charts (scalping + intraday).
⚡MACD (fast EMA / slow EMA) into the same script along with your RSI sentiment oscillator, so you’ll get a dual-confirmation system (RSI sentiment + MACD crossover + histogram).
TIKOLE SVM Sentiment Combo Oscillator MACD"This one has MACD and RSI. Accuracy is very good. Best for 5-minute and 15-minute timeframes."
So basically, you mean:
The script combines MACD-style histogram with RSI logic.
It gives high accuracy signals.
Works best on 5-minute and 15-minute charts (scalping + intraday).
⚡ If you want, I can also add MACD (fast EMA / slow EMA) into the same script along with your RSI sentiment oscillator, so you’ll get a dual-confirmation system (RSI sentiment + MACD crossover + histogram).
Regime Radar — Trend vs Volatile [AlphaGroup.Live]⚡ Regime Radar — Trend vs Volatile
Markets switch personalities. Some weeks they trend relentlessly. Other times they chop, fake out, and punish breakout traders.
This tool tells you — at a glance — whether an asset is in TREND , VOLATILE , or MIXED mode across multiple timeframes.
🔑 How it works
The engine scores every timeframe on two dimensions:
Trend Score (directional persistence):
• Efficiency Ratio (straight vs noisy moves)
• Normalized ADX (directional movement strength)
• Positive autocorrelation (persistence of returns)
Volatile Score (chop / mean reversion):
• 1 − Efficiency Ratio (lack of direction)
• Frequency of outside bars (indecision candles)
• Negative autocorrelation (flip-flop behavior)
Then it compares the difference:
• TREND if Trend − Volatile > thWeak
• VOLATILE if Trend − Volatile < −thWeak
• MIXED if the difference is inside
Strength comes from how far apart the scores are:
• Strong if |diff| ≥ thStrong
• Weak if thWeak ≤ |diff| < thStrong
• Neutral if |diff| < thWeak
🖼️ What you see
• Yellow candles mark outside bars (both high & low broken) → “non-decision” events.
• A dashboard table prints your chosen timeframes with verdicts like:
5m VOLATILE Strong
15m VOLATILE Weak
1h TREND Neutral
4h TREND Weak
D VOLATILE Neutral
W TREND Strong
M TREND Strong
• Optional Bias column shows the numeric difference (Trend − Volatile).
💡 Why use it
• Spot when trend-following systems (crossovers, inside bar breakouts) are favored.
• Spot when reversal systems (RSI2, MinMax, Bollinger plays) are favored.
• Check regime alignment across intraday, swing, and macro frames.
• Avoid trading a TREND system in a VOLATILE regime (and vice versa).
⚡ Want more setups?
Get 100 battle-tested trading strategies FREE here:
👉 alphagroup.live
No excuses. No guesswork. The market tells you its regime. Listen — and adapt.
📌 Tags
trenddetection, volatility, regimefilter, trendfilter, rangetrading, meanreversion, priceaction, chartpatterns, riskmanagement, tradingdashboard, forex, crypto, stocks, scalping, swingtrading
VWAP Executor — v6 (VWAP fix)tarek helishPractical scalping plan with high-rate (sometimes reaching 70–85% in a quiet market)
Concept: “VWAP bounce with a clear trend.”
Tools: 1–3-minute chart for entry, 5-minute trend filter, VWAP, EMA(50) on 5M, ATR(14) on 1M, volume.
When to trade: London session or early New York session; avoid 10–15 minutes before/after high-impact news.
Entry rules (buy for example):
Trend: Price is above the EMA(50) on 5M and has an upward trend.
Entry zone: First bounce to VWAP (or a ±1 standard deviation channel around it).
Signal: Bullish rejection/engulfing candle on 1M with increasing volume, and RSI(2) has exited oversold territory (optional).
Order: Entry after the confirmation candle closes or a limit close to VWAP.
Trade Management:
Stop: Below the bounce low or 0.6xATR(1M) (strongest).
Target: 0.4–0.7xATR(1M) or the previous micro-high (small return to increase success rate).
Trigger: Move the stop to breakeven after +0.25R; close manually if the 1M candle closes strongly against you.
Filter: Do not trade if the spread widens, or the price "saws" around VWAP without a trend.
Sell against the rules in a downtrend.
Why this plan raises the heat-rate? You buy a "small discount" within an existing trend and near the institutional average price (VWAP), with a small target price.
مواقعي شركة الماسة للخدمات المنزلية
شركة تنظيف بالرياض
نقل عفش بالرياض
Rolling Correlation BTC vs Hedge AssetsRolling Correlation BTC vs Hedge Assets
Overview
This indicator calculates and plots the rolling correlation between Bitcoin (BTC) returns and several key hedge assets:
• XAUUSD (Gold)
• EURUSD (proxy for DXY, U.S. Dollar Index)
• VIX (Volatility Index)
• TLT (20y U.S. Treasury Bonds ETF)
By monitoring these dynamic correlations, traders can identify whether BTC is moving in sync with risk assets or decoupling as a hedge, and adjust their trading strategy accordingly.
How it works
1. Computes returns for BTC and each asset using percentage change.
2. Uses the rolling correlation function (ta.correlation) over a configurable window length (default = 12 bars).
3. Plots each correlation as a separate colored line (Gold = Yellow, EURUSD = Blue, VIX = Red, TLT = Green).
4. Adds threshold levels at +0.3 and -0.3 to help classify correlation regimes.
How to use it
• High positive correlation (> +0.3): BTC is moving together with the asset (risk-on behavior).
• Near zero (-0.3 to +0.3): BTC is showing little to no correlation — neutral/independent moves.
• Negative correlation (< -0.3): BTC is moving in the opposite direction — potential hedge opportunity.
Practical strategies:
• Watch BTC vs VIX: a spike in volatility (VIX ↑) usually coincides with BTC selling pressure.
• Track BTC vs EURUSD: stronger USD often puts downside pressure on BTC.
• Observe BTC vs Gold: during “flight to safety” events, gold rises while BTC weakens.
• Monitor BTC vs TLT: rising yields (falling TLT) often align with BTC weakness.
Inputs
• Window Length (bars): Number of bars used to calculate rolling correlations (default = 12).
• Comparison Timeframe: Default = 5m. Can be changed to align with your intraday or swing trading style.
Notes
• Works best on intraday charts (1m, 5m, 15m) for scalping and short-term setups.
• Use correlations as context, not standalone signals — combine with volume, VWAP, and price action.
• Correlations are dynamic; they can switch regimes quickly during macro events (CPI, NFP, FOMC).
This tool is designed for traders who want to manage risk exposure by monitoring whether BTC is behaving as a risk-on asset or hedge, and to exploit opportunities during decoupling phases.
VWAP with period (rajib127)VWAP with Adjustable Period (rajib127)
This advanced VWAP (Volume Weighted Average Price) indicator offers enhanced functionality with customizable anchor periods and multiple standard deviation bands.
Key Features:
Adjustable Anchor Period: Unlike standard VWAP that resets daily, this indicator allows you to set custom anchor timeframes (Daily, Weekly, Monthly) to match your trading strategy
Multiple Deviation Bands: Display up to 3 sets of bands with customizable multipliers for better support/resistance identification
Dual Calculation Modes: Choose between Standard Deviation or Percentage-based band calculations
Flexible Price Sources: Select from 7 different price calculation methods (Typical, Close, High, Low, Median, Weighted, Open)
Timeframe Visibility Control: Option to hide VWAP on higher timeframes (Daily and above) for cleaner charts
Visual Enhancements: Color-coded bands with fill areas and real-time value display table
Trading Applications:
Identify dynamic support and resistance levels
Spot mean reversion opportunities when price deviates from bands
Use different anchor periods for swing trading vs day trading strategies
Combine with other indicators for confluence-based entries
Unique Advantage:
The ability to adjust the VWAP reset period makes this indicator versatile for various trading styles - from intraday scalping with hourly resets to swing trading with weekly anchors.
Perfect for traders who want more control over their VWAP analysis beyond the standard daily reset limitation.
FUMO 200 MagnetWhat it does
FUMO Magnet measures how far price has stretched away from its long-term “magnet” — a blended EMA/SMA moving average (200 by default).
It plots a logarithmic deviation (optionally normalized) as an oscillator around zero.
Above 0** → price is above the magnet (stretched up)
Below 0** → price is below the magnet (stretched down)
Guide levels** highlight potential overbought/oversold zones
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Why log deviation?
Log returns make extremes comparable across cycles and compress exponential trends — especially useful for BTC and other crypto assets.
Normalization modes further adjust the scale, keeping the oscillator readable on any chart.
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Inputs
**Base**
* Source (default: Close)
* Base Length (default: 200 EMA/SMA)
* EMA vs SMA weight (%) — 0% = pure SMA, 100% = pure EMA, 50% = blended
* EMA smoothing of deviation — acts as a noise filter
**Normalization**
* None (Log Deviation) — raw log stretch in % terms
* Z-score — deviation in standard deviations (σ)
* Robust Z (MAD) — deviation vs median absolute deviation, resistant to outliers
* Tanh squash — smooth nonlinear squash of extremes for compact scale
* Normalization window (for Z / MAD)
* Tanh scale (lower = stronger squash)
* Clamp after normalization — hard cap at ±X
**Levels**
* Guide levels (Upper / Lower) — visual thresholds (default ±12)
* Zero line toggle
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### How to read it
* **Trend bias**: sustained time above 0 = uptrend, below 0 = downtrend
* **Stretch / mean reversion**: the farther from 0, the higher the reversion risk
* **Cross-checks**: combine with structure (HH/HL, LH/LL), volume, or momentum (RSI, MACD)
---
### Recommended settings by timeframe
**Long-term (1D / 1W)**
* Normalization: None (Log Deviation)
* Base Length: 200
* EMA vs SMA weight: 50% (adjust 35–65% for faster/slower magnet)
* Deviation smoothing: 20 (10–30 range)
* Guide levels: ±12 to ±20
* Use case: cycle extremes, portfolio rebalancing, trim/add logic
**Swing (4H – 1D)**
* Normalization: Z-score
* Window: 200 (100–250)
* Smoothing: 14–20
* Guide levels: ±2σ to ±3σ
* Use case: stretched conditions across regimes; ±3σ is rare, often mean-reverts
**Intraday / Active swing (1H – 4H)**
* Normalization: Robust Z (MAD)
* Window: 200 (150 for faster response)
* Smoothing: 10–16
* Guide levels: ±3 to ±4 (robust units)
* Use case: handles spikes better than σ, fewer false overbought/oversold signals
**Scalping / Universal readability (15m – 1H)**
* Normalization: Tanh squash
* Tanh scale: 6–10 (start with 8)
* Smoothing: 8–12
* Guide levels: ±8 to ±12
* Use case: compact panel across assets and timeframes; not % or σ, but visually consistent
---
### Optional
* Clamp: enable ±20 (or ±25) for strict bounded range (useful for public charts)
---
### Quick setups
**BTC Daily (“cycle view”)**
* Normalization: None
* Blend: 50%
* Smooth: 20
* Levels: ±12–15
**BTC 4H (“swing”)**
* Normalization: Z-score
* Window: 200
* Smooth: 16
* Levels: ±2.5σ to ±3σ
**Alts 1H (“volatile”)**
* Normalization: Robust Z (MAD)
* Window: 200
* Smooth: 12
* Levels: ±3.5 to ±4.5
**Mixed assets 15m (“compact panel”)**
* Normalization: Tanh squash
* Scale: 8
* Smooth: 10
* Levels: ±8–12
* Clamp: ±20
Sabina's TRAMA Crossover MTF📊 Sabina's TRAMA Crossover MTF
Trend Regularity Adaptive Moving Average (TRAMA) is a dynamic smoothing algorithm that adjusts based on trend consistency. Unlike traditional moving averages like EMA or SMA, TRAMA speeds up in strong trends and slows down during consolidation, reducing noise and lag.
This script plots two TRAMA lines (short and long) and dynamically colors them based on crossover direction:
🟢 Green: Bullish crossover (short TRAMA crosses above long TRAMA)
🔴 Red: Bearish crossover (short TRAMA crosses below long TRAMA)
✅ Multi-Timeframe Enabled
You can run the indicator on your current chart while calculating TRAMA from any higher or lower timeframe. This gives you flexibility to track trend strength across different contexts.
Use cases:
Trend-following entries with adaptive confirmation
Scalping with higher-timeframe filters
Visual clarity of market regime (consolidation vs expansion)
T-Virus Sentiment [hapharmonic]🧬 T-Virus Sentiment: Visualize the Market's DNA
Remember the iconic T-Virus vial from the first Resident Evil? That powerful, swirling helix of potential has always fascinated me. It sparked an idea: what if we could visualize the market's underlying health in a similar way? What if we could capture the "genetic code" of market sentiment and contain it within a dynamic, 3D indicator? This project is the result of that idea, brought to life with Pine Script.
The indicator's main goal is to measure the strength and direction of market sentiment by analyzing the "genetic code" of price action through a variety of trusted indicators. The result is displayed as a liquid level within a DNA helix, a bubble density representing buying pressure, and a T-Virus mascot that reflects the overall mood.
🧐 Core Concept: How It Works
The primary output of the indicator is the "Active %" gauge you see on the right side of the vial. This percentage represents the overall sentiment score, calculated as an average from 7 different technical analysis tools. Each tool is analyzed on every bar and assigned a score from 1 (strong bearish pressure) to 5 (strong bullish potential).
In this indicator, we re-imagine market dynamics through the lens of a viral outbreak. A strong bear market is like a virus taking hold, pulling all technical signals down into a state of weakness. Conversely, a powerful bull market is like an antiviral serum ; positive signals rise and spread toward the top of the vial, indicating that the system is being injected with strength.
This is not just another line on a chart. It's a comprehensive sentiment dashboard designed to give an immediate, at-a-glance understanding of the confluence between 7 classic technical indicators. The incredible 3D model of the vial itself was inspired by a design concept found here .
⚛️ The 4 Core Elements of T-Virus Sentiment
These four elements work in harmony to give a complete, multi-faceted picture of market sentiment. Each component tells a different part of the story.
The Virus Mascot: An instant emotional cue. This character provides the quickest possible read on the overall market mood, combining sentiment with volume pressure.
The Antiviral Serum Level: The main quantitative output. This is the liquid level in the DNA helix and the percentage gauge on the right, representing the average sentiment score from all 7 indicators.
Buy Pressure & Bubble Density: This visualizes volume flow. The density of bubbles represents the intensity of accumulation (buying) versus distribution (selling). It's the "power" behind the move.
The Signal Distribution: This shows the confluence (or dispersion) of sentiment. Are all signals bullish and clustered at the top, or are they scattered, indicating a conflicted market? The position of the indicator labels is crucial, as each is assigned to one of five distinct zones:
Base Bottom: The market is at its weakest. Signals here suggest strong bearish control and distribution.
Lower Zone: The market is still bearish, but signals may be showing early signs of accumulation or bottoming.
Neutral Core (Center): A state of balance or sideways consolidation. The market is waiting for a new direction.
Upper Zone: Bullish momentum is becoming clear. Signals are strengthening and showing bullish control.
Top Cap: The market is "heating up" with strong bullish sentiment, potentially nearing overbought conditions.
🐂🐻 The Virus Mascot: The At-a-Glance Indicator
This character acts as a shortcut to confirm market health. It combines the sentiment score with volume, preventing false confidence in a low-volume rally.
Its state is determined by a dual-check: the overall "Antiviral Serum Level" and the "Buy Pressure" must both be above 50%.
Green & Smiling: The 'all clear' signal. This means that not only is the overall technical sentiment bullish, but it's also being supported by real buying pressure. This is a sign of a healthy bull market.
Red & Angry: A warning sign. This appears if either the sentiment is weak, or a bullish sentiment is not being confirmed by buying volume. The latter could indicate a potential "bull trap" or an exhaustive move.
This mascot can be disabled from the settings page under "Virus Mascot Styling" if a cleaner look is preferred.
🫧 Bubble Density: Gauging Buy vs. Sell Pressure
The bubbles visualize the battle between buyers and sellers. There are two modes to control how this is calculated:
Mode 1: Visible Range (The 'Big Picture' View)
This default mode is best for getting a broad, contextual understanding of the current session. It dynamically analyzes the volume of every single candlestick currently visible on the screen to calculate the buy/sell pressure ratio. It answers the question: "Over the entire period I'm looking at, who is in control?" As you zoom in or out, the calculation adapts.
Mode 2: Custom Lookback (The 'Precision' View)
This mode is for traders who need to analyze short-term pressure. You can define a fixed number of recent bars to analyze, which is perfect for scalping or understanding the volume dynamics leading into a key level. It answers the question: "What is happening right now ?" In the example above, a lookback of 2 focuses only on the most recent action, clearly showing intense, immediate selling pressure (few bubbles) and a corresponding drop in the sentiment score to 29%.
ℹ️ Interactive Tooltips: Dive Deeper
We believe in transparency, not 'black box' indicators. This feature transforms the indicator from a visual aid into an active learning tool.
Simply hover the mouse over any indicator label (like EMA, OBV, etc.) to get a detailed tooltip. It will explain the specific data points and thresholds that signal met to be placed in its current zone. This helps build trust in the signals and allows users to fine-tune the indicator settings to better match their own trading style.
🎯 The Scoring Logic Breakdown
The "Antiviral Serum Level" gauge is the average score from 7 technical analysis tools. Each is graded on a 5-point scale (1=Strong Bearish to 5=Strong Bullish). Here’s a detailed, transparent look at how each "gene" is evaluated:
Relative Strength Index (RSI)
Measures momentum and overbought/oversold conditions.
Group 1 (Strong Bearish): RSI > 80 (Extreme Overbought)
Group 2 (Bearish): 70 < RSI ≤ 80 (Overbought)
Group 3 (Neutral): 30 ≤ RSI ≤ 70
Group 4 (Bullish): 20 ≤ RSI < 30 (Oversold)
Group 5 (Strong Bullish): RSI < 20 (Extreme Oversold)
Exponential Moving Averages (EMA)
Evaluates the trend's strength and structure based on the alignment of multiple EMAs (9, 21, 50, 100, 200, 250).
Group 1 (Strong Bearish): A perfect bearish sequence (9 < 21 < 50 < ...)
Group 2 (Bearish Transition): Early signs of a potential reversal (e.g., 9 > 21 but still below 50)
Group 3 (Neutral / Mixed): MAs are intertwined or showing a partial bullish sequence.
Group 4 (Bullish): A strong bullish sequence is forming (e.g., 9 > 21 > 50 > 100)
Group 5 (Strong Bullish): A perfect bullish sequence (9 > 21 > 50 > 100 > 200 > 250)
Moving Average Convergence Divergence (MACD)
Analyzes the relationship between two moving averages to gauge momentum.
Group 1 (Strong Bearish): MACD & Histogram are negative and momentum is falling.
Group 2 (Weakening Bearish): MACD is negative but the histogram is rising or positive.
Group 3 (Neutral / Crossover): A crossover event is occurring near the zero line.
Group 4 (Bullish): MACD & Histogram are positive.
Group 5 (Strong Bullish): MACD & Histogram are positive, rising strongly, and accelerating.
Average Directional Index (ADX)
Measures trend strength, not direction. The score is based on both ADX value and the dominance of DI+ vs DI-.
Group 1 (Bearish / No Trend): ADX < 20 and DI- is dominant.
Group 2 (Developing Bearish Trend): 20 ≤ ADX < 25 and DI- is dominant.
Group 3 (Neutral / Indecision): Trend is weak or DI+ and DI- are nearly equal.
Group 4 (Developing Bullish Trend): 25 ≤ ADX ≤ 40 and DI+ is dominant.
Group 5 (Strong Bullish Trend): ADX > 40 and DI+ is dominant.
Ichimoku Cloud (IKH)
A comprehensive indicator that defines support/resistance, momentum, and trend direction.
Group 1 (Strong Bearish): Price is below the Kumo, Tenkan < Kijun, and Chikou is below price.
Group 2 (Bearish): Price is inside or below the Kumo, with mixed secondary signals.
Group 3 (Neutral / Ranging): Price is inside the Kumo, often with a Tenkan/Kijun cross.
Group 4 (Bullish): Price is above the Kumo with strong primary signals.
Group 5 (Strong Bullish): All signals are aligned bullishly: price above Kumo, bullish Tenkan/Kijun cross, bullish future Kumo, and Chikou above price.
Bollinger Bands (BB)
Measures volatility and relative price levels.
Group 1 (Strong Bearish): Price is below the lower band.
Group 2 (Bearish Territory): Price is between the lower band and the basis line.
Group 3 (Neutral): Price is hovering around the basis line.
Group 4 (Bullish Territory): Price is between the basis line and the upper band.
Group 5 (Strong Bullish): Price is above the upper band.
On-Balance Volume (OBV)
Uses volume flow to predict price changes. The score is based on OBV's trend and its position relative to its moving average.
Group 1 (Strong Bearish): OBV is below its MA and falling.
Group 2 (Weakening Bearish): OBV is below its MA but showing signs of rising.
Group 3 (Neutral): OBV is very close to its MA.
Group 4 (Bullish): OBV is above its MA and rising.
Group 5 (Strong Bullish): OBV is above its MA, rising strongly, and showing signs of a volume spike.
🧭 How to Use the T-Virus Sentiment Indicator
IMPORTANT: This indicator is a sentiment dashboard , not a direct buy/sell signal generator. Its strength lies in showing confluence and providing a quick, holistic view of the market's technical health.
Confirmation Tool: Use the "Active %" gauge to confirm a trade setup from your primary strategy. For example, if you see a bullish chart pattern, a high and rising sentiment score can add confidence to your trade.
Momentum & Trend Gauge: A consistently high score (e.g., > 75%) suggests strong, established bullish momentum. A consistently low score (< 25%) suggests strong bearish control. A score hovering around 50% often indicates a ranging or indecisive market.
Divergence & Warning System: Pay attention to divergences. If the price is making new highs but the sentiment score is failing to follow or is actively decreasing, it could be an early warning sign that the underlying momentum is weakening.
⚙️ Settings & Customization
The indicator is highly customizable to fit any trading style.
Position & Anchor: Control where the vial appears on the chart.
Styling (Vial, Helix, etc.): Nearly every visual element can be color-customized.
Signals: This is where the real power is. All underlying indicator parameters (RSI length, MACD settings, etc.) can be fine-tuned to match a personal strategy. The text labels can also be disabled if the chart feels cluttered.
Enjoy visualizing the market's DNA with the T-Virus Sentiment indicator
FUMO MA Cross Matrix 9/21/50/100/200 FUMO MA Cross Matrix is a flexible and advanced indicator designed for traders who rely on moving average crossovers as part of their strategy.
🔹 Key Features:
Supports 5 types of Moving Averages: EMA, SMA, SMMA (RMA), WMA, HMA.
Includes 5 standard MAs: 9, 21, 50, 100, 200 (toggle on/off individually).
Choose which MA crosses to monitor (9×21, 21×50, 50×100, 100×200, and 6 extended combinations).
On-chart signals (labels) when crosses occur.
Alerts system for every selected cross and also summary alerts (“Any Cross Up/Down”).
Option to trigger signals only on confirmed bars (no repaint).
Fully adjustable label visibility and signal style.
🔹 Use Cases:
Detect trend shifts (short-term vs long-term).
Build scalping, swing, or position trading strategies.
Combine with price action or volume analysis for stronger setups.
Quickly react to Golden Cross and Death Cross events.
🔹 How to Use:
Select your preferred MA type (EMA, SMA, etc.).
Enable the MAs (9, 21, 50, 100, 200) you want to plot.
Choose which crossovers to track in the settings.
Enable/disable on-chart labels for better visualization.
Set up alerts:
“CROSS UP/DOWN X>Y” for specific pairs.
“ANY CROSS UP/DOWN” for aggregated signals.
📌 Example Alerts
MA Cross UP 9>21 on BTCUSDT 15m @ 65432
Any selected MA cross DOWN on AAPL 1D @ 195.2
Market Sessions [odnac]
This indicator highlights the three main global market sessions (USA, Europe, Asia) and their overlaps directly on the chart.
It helps traders quickly identify active trading periods and potential high-liquidity overlaps.
Features:
Customizable start and end times for each session
Optional daily dividers with weekday labels
Session markers displayed as circles above the candles
Overlap sessions displayed in distinct colors
Adjustable opacity for better chart visibility
Option to hide weekends
Sessions included:
USA Market Session (default 13:30–20:00 UTC)
Europe Market Session (default 07:00–16:00 UTC)
Asia Market Session (default 00:00–09:00 UTC)
Overlaps: USA + Europe, USA + Asia, Europe + Asia
This tool is designed for intraday timeframes (1m–60m) and can be useful for scalping, day trading, or session-based strategies.
KAMA Trend Flip - SightLing LabsBuckle up, traders—this open-source KAMA Trend Flip indicator is your ticket to sniping trend reversals with a Kaufman Adaptive Moving Average (KAMA) that’s sharper than a Wall Street shark’s tooth. No voodoo, no fluff—just raw, volatility-adaptive math that dances with the market’s rhythm. It zips through trending rockets and chills in choppy waters, slashing false signals like a samurai. Not laggy like the others - this thing is the real deal!
Core Mechanics:
• Efficiency Ratio (ER): Reads the market’s pulse (0-1). High ER = turbo-charged MA, low ER = smooth operator.
• Adaptive Smoothing: Mixes fast (default power 2) and slow (default 30) constants to match market mood swings.
• Trend Signals: KAMA climbs = blue uptrend (bulls run wild). KAMA dips = yellow downtrend (bears take over). Flat = gray snooze-fest.
• Alerts: Instant pings on flips—“Trend Flip Up” for long plays, “Down” for shorts. Plug into bots for set-and-forget domination.
Why It Crushes:
• Smokes static MAs in volatile arenas (crypto, stocks, you name it). Backtests show 20-30% fewer fakeouts than SMA50.
• Visual Pop: Overlays price with bold blue/yellow signals. Slap it on BTC 1D to see trends light up like Times Square.
• Tweakable: Dial ER length (default 50) to your timeframe. Short for scalps, long for swing trades.
Example Settings in Action:
• 10s Chart (Hyper-Scalping): Set Source: Close, ER Length: 100, Fast Power: 1, Slow Power: 6. Catches micro-trends in crypto like a heat-seeking missile. Blue/yellow flips scream entry/exit on fast moves.
• 2m Chart (Quick Trades): Set Source: Close, ER Length: 14, Fast Power: 1, Slow Power: 6. Perfect for rapid trend shifts in stocks or forex. Signals align with momentum bursts—check historical flips for proof.
Deployment:
• Drop it on any chart. Backtest settings to match your asset’s volatility—tweak until it sings.
• Pair with RSI or volume spikes for killer confirmation. Pro move: Enter on flip + volume pop, exit on reverse.
• Strategy-Ready: Slap long/short logic on alerts to build a lean, mean trading machine.
Open source from SightLing Labs—grab it, hack it, profit from it. Share your tweaks in the comments and let’s outsmart the market together. Trade hard, win big!
FluidFlow OscillatorFluidFlow Oscillator: Study Material for Traders
Overview
The FluidFlow Oscillator is a custom technical indicator designed to measure price momentum and market flow dynamics by simulating fluid motion concepts such as velocity, viscosity, and turbulence. It helps traders identify potential buy and sell signals along with trend strength, momentum direction, and volatility conditions.
This study explains the underlying calculation concepts, signal logic, visual cues, and how to interpret the professional dashboard table that summarizes key indicator readings.
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How the FluidFlow Oscillator Works
Core Mechanisms
1. Price Flow Velocity
o Measures the rate of change of price over a specified flow length (default 40 bars).
o Calculated as a percentage change of closing price: roc=close−closelen_flowcloselen_flow×100\text{roc} = \frac{\text{close} - \text{close}_{len\_flow}}{\text{close}_{len\_flow}} \times 100roc=closelen_flowclose−closelen_flow×100
o Smoothed by an EMA (Exponential Moving Average) to reduce noise, generating a "flow velocity" value.
2. Viscosity Factor
o Analogous to fluid viscosity, it adjusts the flow velocity based on recent price volatility.
o Volatility is computed as the standard deviation of close prices over the flow length.
o The viscosity acts as a damping factor to slow down the flow velocity in highly volatile conditions.
o This results in a "flow with viscosity" value, that smooths out the velocity considering market turbulence.
3. Turbulence Burst
o Captures sudden changes or bursts in the flow by measuring changes between successive viscosity-adjusted flows.
o The turbulence value is a smoothed absolute change in flow.
o A burst boost factor is added to the oscillator to incorporate this rapid change component, amplifying signals during sudden shifts.
4. Oscillator Calculation
o The raw oscillator value is the sum of flow with viscosity plus burst boost, scaled by 10.
o Clamped between -100 and +100 to limit extremes.
o Finally, smoothed again by EMA for cleaner visualization.
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Signal Logic
The oscillator works with complementary components to produce actionable signals:
• Signal Line: An EMA-smoothed version of the oscillator for generating crossover-based signals.
• Momentum: The rate of change of the oscillator itself, smoothed by EMA.
• Trend: Uses fast (21-period EMA) and slow (50-period EMA) moving averages of price to identify market trend direction (uptrend, downtrend, or sideways).
Signal Conditions
• Bullish Signal (Buy): Oscillator crosses above the oversold threshold with positive momentum.
• Bearish Signal (Sell): Oscillator crosses below the overbought threshold with negative momentum.
Statuses
The oscillator provides descriptive market states based on level and momentum:
• Overbought
• Oversold
• Buy Signal
• Sell Signal
• Bullish / Bearish (momentum-driven)
• Neutral (no clear trend)
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Color System and Visualization
The oscillator uses a sophisticated HSV color model adapting hues according to:
• Oscillator value magnitude and sign (positive or negative)
• Acceleration of oscillator changes
• Smooth color gradients to facilitate intuitive understanding of trend strength and momentum shifts
Background colors highlight overbought (red tint) and oversold (green tint) zones with transparency.
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How to Understand the Professional Dashboard Table
The FluidFlow Oscillator offers an integrated table at the bottom center of the chart. This dashboard summarizes critical indicator readings in 8 columns across 3 rows:
Column Description
SIGNAL Current signal status (e.g., Buy, Sell, Overbought) with color coding
OSCILLATOR Current oscillator value (-100 to +100) with color reflecting intensity and direction
MOMENTUM Momentum bias indicating strength/direction of oscillator changes (Strong Up, Up, Sideways, Down, Strong Down)
TREND Current trend status based on EMAs (Strong Uptrend, Uptrend, Sideways, Downtrend, Strong Downtrend)
VOLATILITY Volatility percentage relative to average, indicating market activity level
FLOW Flow velocity value describing price momentum magnitude and direction
TURBULENCE Turbulence level indicating sudden bursts or spikes in price movement
PROGRESS Oscillator's position mapped as a percentage (0% to 100%) showing proximity to extreme levels
Rows Explained
• Row 1 (Header): Labels for each metric.
• Row 2 (Values): Current numerical or descriptive values color-coded along a professional scheme:
o Green or lime tones indicate positive or bullish conditions.
o Red or orange tones indicate caution, sell signals, or bearish conditions.
o Blue tones indicate neutral or stable conditions.
• Row 3 (Status Indicators): Emoji-like icons and bars provide a quick visual gauge of each metric's intensity or signal strength:
o For example, "🟢🟢🟢" suggests very strong bullish momentum, while "🔴🔴🔴" suggests strong bearish momentum.
o Progress bar visually demonstrates oscillator movement toward oversold or overbought extremes.
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Practical Interpretation Tips
• A Buy signal with green colors and strong momentum usually precedes upward price moves.
• An Overbought status with red background and red table colors warns of potential price corrections or reversals.
• Watch the Turbulence to gauge market instability; spikes may precede price shocks or volatility bursts.
• Confirm signals with the Trend and Momentum columns to avoid false entries.
• Use the Progress bar to anticipate oscillations approaching key threshold levels for timing trades.
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Alerts
The oscillator supports alerts for:
• Buy and sell signals based on oscillator crossovers.
• Overbought and oversold levels reached.
These help traders automate awareness of important market conditions.
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Disclaimer
The FluidFlow Oscillator and its signals are for educational and informational purposes only. They do not guarantee profits and should not be considered as financial advice. Always conduct your own research and use proper risk management when trading. Past performance is not indicative of future results.
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This detailed explanation should help you understand the workings of the FluidFlow Oscillator, its components, signal logic, and how to analyze its professional dashboard for informed trading decisions.
FlowShift OscillatorFlowShift Oscillator
Overview
The FlowShift Oscillator is a sophisticated momentum indicator designed to capture short-term shifts in market strength, identify trend acceleration, and highlight potential reversals. Combining baseline trend analysis with normalized momentum displacement and volatility-adjusted thresholds, FlowShift provides traders with a responsive, adaptive, and visually intuitive tool suitable for multiple timeframes and asset classes. Whether used for intraday scalping or longer-term trend following, FlowShift helps traders make informed decisions with precision and confidence.
Features
Customizable Baseline Moving Average : Select from SMA, EMA, SMMA (RMA), WMA, or VWMA to define the underlying trend. Adjustable length allows for tuning to specific market conditions.
Normalized Momentum Calculation : Measures price displacement relative to the baseline MA, removing minor fluctuations while preserving meaningful momentum shifts.
Volatility-Adjusted Thresholds : Dynamic upper and lower bounds adapt to market volatility, helping identify overextended bullish or bearish conditions.
Optional Signal Markers : Buy/Sell triangles indicate potential turning points when momentum reaches critical levels, aiding trade timing and decision-making.
Visual Enhancements : Customizable area fills, line colors, and optional candle tinting allow traders to quickly interpret momentum, bias, and trend direction.
Flexible Timeframe Compatibility : Effective across all timeframes, from 1-minute intraday charts to daily and weekly analysis.
How It Works
FlowShift calculates the displacement of price from a baseline moving average to identify deviations from the prevailing trend. This displacement is normalized and smoothed using exponential moving averages, producing a clean oscillator line that highlights genuine momentum changes. The oscillator’s dynamic thresholds are determined by a percentile of recent absolute values, providing an adaptive reference for extreme conditions in both bullish and bearish markets.
Signals
Buy Signal : Triggered when the oscillator crosses above prior lows in an oversold region, suggesting potential upward momentum.
Sell Signal : Triggered when the oscillator crosses below prior highs in an overbought region, indicating potential downward momentum.
Signals are optional and can be displayed as triangles on the chart to clearly mark potential entry and exit points.
Visual Interpretation
FlowShift Line & Area : The oscillator line and area highlight momentum direction and intensity. Upward momentum is shown in green tones, downward momentum in red.
Baseline MA & Glow : Displays the selected baseline moving average with optional glow for trend reference.
Candle Tinting : Optionally tints bars based on the baseline MA bias, providing an at-a-glance view of market sentiment.
Usage Notes
FlowShift is best used in conjunction with other trend confirmation tools or support/resistance analysis.
Dynamic thresholds help identify potential reversal points, but traders should consider overall market context and not rely solely on signals.
Customize the baseline MA type and length to fit your trading style; shorter lengths increase sensitivity, while longer lengths provide smoother trend representation.
Use the optional signal markers as guidance for trade timing, combining with risk management strategies for optimal results.
Conclusion
FlowShift Oscillator delivers a powerful, adaptive, and visually intuitive approach to momentum analysis. By combining baseline trend assessment, normalized momentum, and dynamic volatility scaling, it enables traders to anticipate market shifts, spot trend accelerations, and make timely trading decisions across a wide range of markets and timeframes.
Market Outlook Score (MOS)Overview
The "Market Outlook Score (MOS)" is a custom technical indicator designed for TradingView, written in Pine Script version 6. It provides a quantitative assessment of market conditions by aggregating multiple factors, including trend strength across different timeframes, directional movement (via ADX), momentum (via RSI changes), volume dynamics, and volatility stability (via ATR). The MOS is calculated as a weighted score that ranges typically between -1 and +1 (though it can exceed these bounds in extreme conditions), where positive values suggest bullish (long) opportunities, negative values indicate bearish (short) setups, and values near zero imply neutral or indecisive markets.
This indicator is particularly useful for traders seeking a holistic "outlook" score to gauge potential entry points or market bias. It overlays on a separate pane (non-overlay mode) and visualizes the score through horizontal threshold lines and dynamic labels showing the numeric MOS value along with a simple trading decision ("Long", "Short", or "Neutral"). The script avoids using the plot function for compatibility reasons (e.g., potential TradingView bugs) and instead relies on hline for static lines and label.new for per-bar annotations.
Key features:
Multi-Timeframe Analysis: Incorporates slope data from 5-minute, 15-minute, and 30-minute charts to capture short-term trends.
Trend and Strength Integration: Uses ADX to weight trend bias, ensuring stronger signals in trending markets.
Momentum and Volume: Includes RSI momentum impulses and volume deviations for added confirmation.
Volatility Adjustment: Factors in ATR changes to assess market stability.
Customizable Inputs: Allows users to tweak periods for lookback, ADX, and ATR.
Decision Labels: Automatically classifies the MOS into actionable categories with visual labels.
This indicator is best suited for intraday or swing trading on volatile assets like stocks, forex, or cryptocurrencies. It does not generate buy/sell signals directly but can be combined with other tools (e.g., moving averages or oscillators) for comprehensive strategies.
Inputs
The script provides three user-configurable inputs via TradingView's input panel:
Lookback Period (lookback):
Type: Integer
Default: 20
Range: Minimum 10, Maximum 50
Purpose: Defines the number of bars used in slope calculations for trend analysis. A shorter lookback makes the indicator more sensitive to recent price action, while a longer one smooths out noise for longer-term trends.
ADX Period (adxPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Sets the smoothing period for the Average Directional Index (ADX) and its components (DI+ and DI-). Standard value is 14, but shorter periods increase responsiveness, and longer ones reduce false signals.
ATR Period (atrPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Determines the period for the Average True Range (ATR) calculation, which measures volatility. Adjust this to match your trading timeframe—shorter for scalping, longer for positional trading.
These inputs allow customization without editing the code, making the indicator adaptable to different market conditions or user preferences.
Core Calculations
The MOS is computed through a series of steps, blending trend, momentum, volume, and volatility metrics. Here's a breakdown:
Multi-Timeframe Slopes:
The script fetches data from higher timeframes (5m, 15m, 30m) using request.security.
Slope calculation: For each timeframe, it computes the linear regression slope of price over the lookback period using the formula:
textslope = correlation(close, bar_index, lookback) * stdev(close, lookback) / stdev(bar_index, lookback)
This measures the rate of price change, where positive slopes indicate uptrends and negative slopes indicate downtrends.
Variables: slope5m, slope15m, slope30m.
ATR (Average True Range):
Calculated using ta.atr(atrPeriod).
Represents average volatility over the specified period. Used later to derive volatility stability.
ADX (Average Directional Index):
A detailed, manual implementation (not using built-in ta.adx for customization):
Computes upward movement (upMove = high - high ) and downward movement (downMove = low - low).
Derives +DM (Plus Directional Movement) and -DM (Minus Directional Movement) by filtering non-relevant moves.
Smooths true range (trur = ta.rma(ta.tr(true), adxPeriod)).
Calculates +DI and -DI: plusDI = 100 * ta.rma(plusDM, adxPeriod) / trur, similarly for minusDI.
DX: dx = 100 * abs(plusDI - minusDI) / max(plusDI + minusDI, 0.0001).
ADX: adx = ta.rma(dx, adxPeriod).
ADX values above 25 typically indicate strong trends; here, it's normalized (divided by 50) to influence the trend bias.
Volume Delta (5m Timeframe):
Fetches 5m volume: volume_5m = request.security(syminfo.tickerid, "5", volume, lookahead=barmerge.lookahead_on).
Computes a 12-period SMA of volume: avgVolume = ta.sma(volume_5m, 12).
Delta: (volume_5m - avgVolume) / avgVolume (or 0 if avgVolume is zero).
This measures relative volume spikes, where positive deltas suggest increased interest (bullish) and negative suggest waning activity (bearish).
MOS Components and Final Calculation:
Trend Bias: Average of the three slopes, normalized by close price and scaled by 100, then weighted by ADX influence: (slope5m + slope15m + slope30m) / 3 / close * 100 * (adx / 50).
Emphasizes trends in strong ADX conditions.
Momentum Impulse: Change in 5m RSI(14) over 1 bar, divided by 50: ta.change(request.security(syminfo.tickerid, "5", ta.rsi(close, 14), lookahead=barmerge.lookahead_on), 1) / 50.
Captures short-term momentum shifts.
Volatility Clarity: 1 - ta.change(atr, 1) / max(atr, 0.0001).
Measures ATR stability; values near 1 indicate low volatility changes (clearer trends), while lower values suggest erratic markets.
MOS Formula: Weighted average:
textmos = (0.35 * trendBias + 0.25 * momentumImpulse + 0.2 * volumeDelta + 0.2 * volatilityClarity)
Weights prioritize trend (35%) and momentum (25%), with volume and volatility at 20% each. These can be adjusted in code for experimentation.
Trading Decision:
A variable mosDecision starts as "Neutral".
If mos > 0.15, set to "Long".
If mos < -0.15, set to "Short".
Thresholds (0.15 and -0.15) are hardcoded but can be modified.
Visualization and Outputs
Threshold Lines (using hline):
Long Threshold: Horizontal dashed green line at +0.15.
Short Threshold: Horizontal dashed red line at -0.15.
Neutral Line: Horizontal dashed gray line at 0.
These provide visual reference points for MOS interpretation.
Dynamic Labels (using label.new):
Placed at each bar's index and MOS value.
Text: Formatted MOS value (e.g., "0.2345") followed by a newline and the decision (e.g., "Long").
Style: Downward-pointing label with gray background and white text for readability.
This replaces a traditional plot line, showing exact values and decisions per bar without cluttering the chart.
The indicator appears in a separate pane below the main price chart, making it easy to monitor alongside price action.
Usage Instructions
Adding to TradingView:
Copy the script into TradingView's Pine Script editor.
Save and add to your chart via the "Indicators" menu.
Select a symbol and timeframe (e.g., 1-minute for intraday).
Interpretation:
Long Signal: MOS > 0.15 – Consider bullish positions if supported by other indicators.
Short Signal: MOS < -0.15 – Potential bearish setups.
Neutral: Between -0.15 and 0.15 – Avoid trades or wait for confirmation.
Watch for MOS crossings of thresholds for momentum shifts.
Combine with price patterns, support/resistance, or volume for better accuracy.
Limitations and Considerations:
Lookahead Bias: Uses barmerge.lookahead_on for multi-timeframe data, which may introduce minor forward-looking bias in backtesting (use with caution).
No Alerts Built-In: Add custom alerts via TradingView's alert system based on MOS conditions.
Performance: Tested for compatibility; may require adjustments for illiquid assets or extreme volatility.
Backtesting: Use TradingView's strategy tester to evaluate historical performance, but remember past results don't guarantee future outcomes.
Customization: Edit weights in the MOS formula or thresholds to fit your strategy.
This indicator distills complex market data into a single score, aiding decision-making while encouraging users to verify signals with additional analysis. If you need modifications, such as restoring plot functionality or adding features, provide details for further refinement.
samc's - Keltner OscillatorThe KELTNER CHANNEL is a widely used technical indicator developed in the 60's by Chester W. Keltner who described it in his 1960 book How To Make Money in Commodities.
so i took the logic, simplified the code and made into an oscillator.
to add a flavor of modern times you can choose among 10 different colorways themes in the settings. (so traders can adjust it for dark or light charts)
Although the initial idea was developed for stocks and commodities, I've carefully back tested this as an oscillator across FX MAJORS , MINORS and high liquidity stocks for the use case of scalping and Medium term trade ideas.
now, this indicator works successfully over all time frames, custom time frames and all assets.
This script builds on the same approach as my earlier session tool — keeping things clean, visual, and easy to read.
I intend to publish more of my work as i develop them from Beta ideas into stable scripts, and i welcome feedback.
samc's FX SESSIONS - on candles So, based on my 8 yrs of experience and over a 2 decade worth of back testing on FX majors pairs one thing i can univocally affirm to the fact that Timing is everything especially in the currency markets.
so i made this indicator to help reduce the noise and focus on signals which is coded by time,
now i made this as GMT+8 in focus but you can adjust based on your requirements.
I classified my indicator colors according to the inter-SESSION High Impact areas only as following :
Primary session colors:
ASIAN - YELLOW
EU - BLUE
US - Magenta (light)
and every first 10 mins of the hour (Great for scalping)
i marked them in a shade of grey.
secondary sessions i marked them as minor sessions.
PRE-EU 1hr of expected trend i marked in color green
and
after hours in a shade of color violet.
so i usually make my candles into light grey by default and remove the body and wicks to minimize the visual stimulus so that this indicator will work great with both dark and light themes and does not obstruct other indicators.
also i made an option to uncheck my naming scheme of session on the top right.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
