Magical Thirteen Turns - The Greedy SnakeThe number 9 appears:
Meaning: Warning signal. The rise may encounter resistance and a cautious pullback is about to begin.
Operation: Consider reducing your holdings (selling a portion) to lock in profits and avoid experiencing wild fluctuations.
The number 13 appears:
Meaning: Strong sell signal. The upward momentum is likely to be exhausted, which is also known as "bull exhaustion".
Operation: It is recommended to liquidate your positions or significantly reduce them. Short sell (if you are trading contracts).
Indikatoren und Strategien
VEGA (Velocity of Efficient Gain Adaptation)VEGA (Velocity of Efficient Gain Adaptation)
VEGA is a momentum oscillator that measures the velocity of an efficiency-weighted adaptive moving average. Unlike traditional momentum indicators that react uniformly to all price movements, VEGA intelligently adapts its sensitivity based on market conditions—responding quickly during trending periods and filtering noise during consolidation.
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What Makes VEGA Different
Efficiency-Driven Adaptation
At its core, VEGA uses the Efficiency Ratio (ER) to distinguish between trending and choppy markets. When price moves efficiently in one direction, VEGA's underlying adaptive MA speeds up to capture the move. When price chops sideways, it slows down to avoid whipsaws. This creates a momentum reading that's inherently cleaner than fixed-period alternatives.
Linear Regression Smoothed Source
VEGA offers an optional LinReg-smoothed price source that blends regular candles with linear regression values. This pre-smoothing reduces noise before it ever enters the calculation, resulting in a histogram that's easier to read without sacrificing responsiveness. The mix ratio lets you dial in exactly how much smoothing you want.
Z-Score Normalization with Dead Zone
Rather than arbitrary oscillator bounds, VEGA normalizes output as standard deviations from the mean. This gives statistically meaningful levels: readings above +2σ or below -2σ represent genuinely extreme momentum. The configurable dead zone (with Snap, Soft Fade, or None modes) filters out insignificant movements near zero, keeping you focused on signals that matter.
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How It Works
1. Source Preparation — Price is smoothed via a LinReg/regular candle blend
2. Efficiency Ratio — Measures directional movement vs total movement over the lookback period
3. Adaptive MA — Applies variable smoothing based on efficiency (fast during trends, slow during chop)
4. Velocity — Calculates the rate of change of the adaptive MA
5. Normalization — Converts to Z-Score (standard deviations) or ATR-normalized percentage
6. Dead Zone — Optionally filters near-zero values to reduce noise
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How To Read VEGA
Signal and Interpretation
Histogram above zero | Bullish momentum
Histogram below zero | Bearish momentum
Bright color | Momentum accelerating
Faded color | Momentum decelerating
Beyond ±1σ bands | Above-average momentum
Beyond ±2σ bands | Extreme momentum (potential reversal zone)
Zero line cross*| Momentum shift
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Key Settings
ER Length — Lookback for efficiency ratio calculation. Higher = smoother, slower adaptation.
Fast/Slow Smoothing — Controls the adaptive MA's responsiveness range. The MA blends between these based on efficiency.
LinReg Settings — Enable smoothed candles and adjust the blend ratio (0 = regular candles, 1 = full LinReg, 0.5 = 50/50 mix).
Z-Score Lookback — Period for calculating mean and standard deviation. Shorter = more reactive normalization.
Dead Zone Type — How to handle near-zero values:
Snap — Hard cutoff to zero
Soft Fade — Gradual reduction toward zero
None — No filtering
Dead Zone Threshold — Values within this Z-Score range are affected by the dead zone setting.
VEGA works on any timeframe and any market. For best results, adjust the ER Length and LinReg settings to match your trading style and the volatility characteristics of your instrument.
Volatility Targeting: Single Asset [BackQuant]Volatility Targeting: Single Asset
An educational example that demonstrates how volatility targeting can scale exposure up or down on one symbol, then applies a simple EMA cross for long or short direction and a higher timeframe style regime filter to gate risk. It builds a synthetic equity curve and compares it to buy and hold and a benchmark.
Important disclaimer
This script is a concept and education example only . It is not a complete trading system and it is not meant for live execution. It does not model many real world constraints, and its equity curve is only a simplified simulation. If you want to trade any idea like this, you need a proper strategy() implementation, realistic execution assumptions, and robust backtesting with out of sample validation.
Single asset vs the full portfolio concept
This indicator is the single asset, long short version of the broader volatility targeted momentum portfolio concept. The original multi asset concept and full portfolio implementation is here:
That portfolio script is about allocating across multiple assets with a portfolio view. This script is intentionally simpler and focuses on one symbol so you can clearly see how volatility targeting behaves, how the scaling interacts with trend direction, and what an equity curve comparison looks like.
What this indicator is trying to demonstrate
Volatility targeting is a risk scaling framework. The core idea is simple:
If realized volatility is low relative to a target, you can scale position size up so the strategy behaves like it has a stable risk budget.
If realized volatility is high relative to a target, you scale down to avoid getting blown around by the market.
Instead of always being 1x long or 1x short, exposure becomes dynamic. This is often used in risk parity style systems, trend following overlays, and volatility controlled products.
This script combines that risk scaling with a simple trend direction model:
Fast and slow EMA cross determines whether the strategy is long or short.
A second, longer EMA cross acts as a regime filter that decides whether the system is ACTIVE or effectively in CASH.
An equity curve is built from the scaled returns so you can visualize how the framework behaves across regimes.
How the logic works step by step
1) Returns and simple momentum
The script uses log returns for the base return stream:
ret = log(price / price )
It also computes a simple momentum value:
mom = price / price - 1
In this version, momentum is mainly informational since the directional signal is the EMA cross. The lookback input is shared with volatility estimation to keep the concept compact.
2) Realized volatility estimation
Realized volatility is estimated as the standard deviation of returns over the lookback window, then annualized:
vol = stdev(ret, lookback) * sqrt(tradingdays)
The Trading Days/Year input controls annualization:
252 is typical for traditional markets.
365 is typical for crypto since it trades daily.
3) Volatility targeting multiplier
Once realized vol is estimated, the script computes a scaling factor that tries to push realized volatility toward the target:
volMult = targetVol / vol
This is then clamped into a reasonable range:
Minimum 0.1 so exposure never goes to zero just because vol spikes.
Maximum 5.0 so exposure is not allowed to lever infinitely during ultra low volatility periods.
This clamp is one of the most important “sanity rails” in any volatility targeted system. Without it, very low volatility regimes can create unrealistic leverage.
4) Scaled return stream
The per bar return used for the equity curve is the raw return multiplied by the volatility multiplier:
sr = ret * volMult
Think of this as the return you would have earned if you scaled exposure to match the volatility budget.
5) Long short direction via EMA cross
Direction is determined by a fast and slow EMA cross on price:
If fast EMA is above slow EMA, direction is long.
If fast EMA is below slow EMA, direction is short.
This produces dir as either +1 or -1. The scaled return stream is then signed by direction:
avgRet = dir * sr
So the strategy return is volatility targeted and directionally flipped depending on trend.
6) Regime filter: ACTIVE vs CASH
A second EMA pair acts as a top level regime filter:
If fast regime EMA is above slow regime EMA, the system is ACTIVE.
If fast regime EMA is below slow regime EMA, the system is considered CASH, meaning it does not compound equity.
This is designed to reduce participation in long bear phases or low quality environments, depending on how you set the regime lengths. By default it is a classic 50 and 200 EMA cross structure.
Important detail, the script applies regime_filter when compounding equity, meaning it uses the prior bar regime state to avoid ambiguous same bar updates.
7) Equity curve construction
The script builds a synthetic equity curve starting from Initial Capital after Start Date . Each bar:
If regime was ACTIVE on the previous bar, equity compounds by (1 + netRet).
If regime was CASH, equity stays flat.
Fees are modeled very simply as a per bar penalty on returns:
netRet = avgRet - (fee_rate * avgRet)
This is not realistic execution modeling, it is just a simple turnover penalty knob to show how friction can reduce compounded performance. Real backtesting should model trade based costs, spreads, funding, and slippage.
Benchmark and buy and hold comparison
The script pulls a benchmark symbol via request.security and builds a buy and hold equity curve starting from the same date and initial capital. The buy and hold curve is based on benchmark price appreciation, not the strategy’s asset price, so you can compare:
Strategy equity on the chart symbol.
Buy and hold equity for the selected benchmark instrument.
By default the benchmark is TVC:SPX, but you can set it to anything, for crypto you might set it to BTC, or a sector index, or a dominance proxy depending on your study.
What it plots
If enabled, the indicator plots:
Strategy Equity as a line, colored by recent direction of equity change, using Positive Equity Color and Negative Equity Color .
Buy and Hold Equity for the chosen benchmark as a line.
Optional labels that tag each curve on the right side of the chart.
This makes it easy to visually see when volatility targeting and regime gating change the shape of the equity curve relative to a simple passive hold.
Metrics table explained
If Show Metrics Table is enabled, a table is built and populated with common performance statistics based on the simulated daily returns of the strategy equity curve after the start date. These include:
Net Profit (%) total return relative to initial capital.
Max DD (%) maximum drawdown computed from equity peaks, stored over time.
Win Rate percent of positive return bars.
Annual Mean Returns (% p/y) mean daily return annualized.
Annual Stdev Returns (% p/y) volatility of daily returns annualized.
Variance of annualized returns.
Sortino Ratio annualized return divided by downside deviation, using negative return stdev.
Sharpe Ratio risk adjusted return using the risk free rate input.
Omega Ratio positive return sum divided by negative return sum.
Gain to Pain total return sum divided by absolute loss sum.
CAGR (% p/y) compounded annual growth rate based on time since start date.
Portfolio Alpha (% p/y) alpha versus benchmark using beta and the benchmark mean.
Portfolio Beta covariance of strategy returns with benchmark returns divided by benchmark variance.
Skewness of Returns actually the script computes a conditional value based on the lower 5 percent tail of returns, so it behaves more like a simple CVaR style tail loss estimate than classic skewness.
Important note, these are calculated from the synthetic equity stream in an indicator context. They are useful for concept exploration, but they are not a substitute for professional backtesting where trade timing, fills, funding, and leverage constraints are accurately represented.
How to interpret the system conceptually
Vol targeting effect
When volatility rises, volMult falls, so the strategy de risks and the equity curve typically becomes smoother. When volatility compresses, volMult rises, so the system takes more exposure and tries to maintain a stable risk budget.
This is why volatility targeting is often used as a “risk equalizer”, it can reduce the “biggest drawdowns happen only because vol expanded” problem, at the cost of potentially under participating in explosive upside if volatility rises during a trend.
Long short directional effect
Because direction is an EMA cross:
In strong trends, the direction stays stable and the scaled return stream compounds in that trend direction.
In choppy ranges, the EMA cross can flip and create whipsaws, which is where fees and regime filtering matter most.
Regime filter effect
The 50 and 200 style filter tries to:
Keep the system active in sustained up regimes.
Reduce exposure during long down regimes or extended weakness.
It will always be late at turning points, by design. It is a slow filter meant to reduce deep participation, not to catch bottoms.
Common applications
This script is mainly for understanding and research, but conceptually, volatility targeting overlays are used for:
Risk budgeting normalize risk so your exposure is not accidentally huge in high vol regimes.
System comparison see how a simple trend model behaves with and without vol scaling.
Parameter exploration test how target volatility, lookback length, and regime lengths change the shape of equity and drawdowns.
Framework building as a reference blueprint before implementing a proper strategy() version with trade based execution logic.
Tuning guidance
Lookback lower values react faster to vol shifts but can create unstable scaling, higher values smooth scaling but react slower to regime changes.
Target volatility higher targets increase exposure and drawdown potential, lower targets reduce exposure and usually lower drawdowns, but can under perform in strong trends.
Signal EMAs tighter EMAs increase trade frequency, wider EMAs reduce churn but react slower.
Regime EMAs slower regime filters reduce false toggles but will miss early trend transitions.
Fees if you crank this up you will see how sensitive higher turnover parameter sets are to friction.
Final note
This is a compact educational demonstration of a volatility targeted, long short single asset framework with a regime gate and a synthetic equity curve. If you want a production ready implementation, the correct next step is to convert this concept into a strategy() script, add realistic execution and cost modeling, test across multiple timeframes and market regimes, and validate out of sample before making any decision based on the results.
5-Period Average of Returns (Close)This indicator calculates the 5-period average of returns of the closing price, providing a detrended, zero-centered oscillator ideal for cycle analysis and timing.
Key Features:
Detrended: Centers around zero to clearly reveal cyclical patterns.
Cycle-friendly: Highlights peaks and troughs for measuring dominant cycles.
Flexible: Can be applied to multiple timeframes (daily, weekly, intraday).
Zero Line Reference: Quickly identify directional shifts in average returns.
Foundation for Advanced Analysis: Can be combined with RSI, statistical bands, or multi-timeframe studies.
Use this indicator to:
Identify dominant cycles and their phase
Measure cycle length and rhythm
Assist in entry and exit timing based on average-return oscillations
Detrend price data for more precise technical and cyclical analysis
Sideways Zone Breakout 📘 Sideways Zone Breakout – Indicator Description
Sideways Zone Breakout is a visual market-structure indicator designed to identify low-volatility consolidation zones and highlight potential breakout opportunities when price exits these zones.
This indicator focuses on detecting periods where price trades within a tight range, often referred to as sideways or consolidation phases, and visually marks these zones directly on the chart for clarity.
🔍 Core Concept
Markets often spend time moving sideways before making a directional move.
This indicator aims to:
Detect price compression
Visually highlight the sideways zone
Signal when price breaks above or below the zone boundaries
Instead of predicting direction, it simply reacts to range expansion after consolidation.
⚙️ How the Indicator Works
1️⃣ Sideways Zone Detection
The indicator looks back over a user-defined number of candles
It calculates the highest high and lowest low within that window
If the total price range remains within a defined percentage of the current price, the market is considered sideways
This helps filter out trending and highly volatile conditions.
2️⃣ Visual Zone Representation
When a sideways condition is detected:
A clear price zone is drawn between the recent high and low
The zone is displayed using a soft gradient fill for better visibility
Outer borders are added to enhance zone clarity without cluttering the chart
This makes consolidation areas easy to spot at a glance.
3️⃣ Breakout Identification
Once a sideways zone is active:
A bullish breakout is marked when price closes above the upper boundary
A bearish breakout is marked when price closes below the lower boundary
Directional arrows and labels are plotted directly on the chart to indicate these events.
📊 Visual Elements Included
Sideways consolidation zones with gradient fill
Upper and lower zone boundaries
Buy and Sell arrows on breakout
Optional text labels for clear interpretation
All visuals are designed to remain lightweight and readable on any chart theme.
🔧 User Inputs
Sideways Lookback (candles): Controls how many past candles are used to define the range
Max Range % (tightness): Determines how tight the range must be to qualify as sideways
Adjusting these inputs allows users to adapt the indicator to different instruments and timeframes.
📈 Usage Guidelines
Can be applied to any market or timeframe
Works well as a context or confirmation tool
Best used alongside volume, trend, or risk management tools
Signals should be validated with proper trade planning
⚠️ Disclaimer
This indicator is provided as open-source for educational and analytical purposes only.
It does not generate trade recommendations or guarantee outcomes.
Market conditions vary, and users are responsible for their own trading decisions.
MNQ Quant Oscillator Lab v2.1MNQ Quant Oscillator Lab v2.1 — Clean Namespaces
Adaptive LinReg Oscillator + Auto Regime Switching + MTF Confirmation + MOEP Gate + Research Harness
MNQ Quant Oscillator Lab is a research-grade oscillator framework designed for MNQ/NQ (and other liquid futures/indices) on 1-minute and intraday timeframes. It combines a linear-regression-based detrended oscillator with quant-style normalization, adaptive parameterization, regime switching, multi-timeframe confirmation, and an optional MOEP (Minimum Optimal Entry Point) gate. The goal is to provide a customizable signal laboratory that is stable in real time, non-repainting by default, and suitable for systematic experimentation.
What this indicator does
1) Core oscillator (quant-normalized)
The indicator computes a linear regression (LinReg) detrended signal and expresses it as a z-scored oscillator for portability across volatility regimes and assets. You can switch the oscillator “transform family” via Oscillator type:
LinReg Residual / Residual Z: detrended residual (mean-reversion sensitive)
LinReg Slope Z: regression slope (trend-derivative sensitive)
LogReturn Z: log-return oscillator (momentum-style)
VolNorm Return Z: volatility-normalized returns (risk-scaled)
This yields a single oscillator that is comparable over time, not tied to raw point values.
2) Adaptive length (dynamic calibration)
When enabled, the regression length is automatically adapted using a volatility-regime proxy (ATR% z-scored → logistic mapping). High volatility typically shortens the effective lookback; low volatility allows longer lookbacks. This helps the oscillator remain responsive during expansions while staying stable in compressions.
Important: the adaptive logic is implemented with safe warmup behavior, so it will not throw NaN errors on early bars.
3) Adaptive thresholds (dynamic bands)
Instead of static overbought/oversold levels, the indicator can compute dynamic upper/lower bands from the oscillator’s own distribution (rolling mean + sigma). This creates thresholds that adjust automatically to regime changes.
4) Auto regime switching (Trend vs Mean Reversion)
With Auto regime switch enabled, the indicator selects whether to behave as a Trend system or a Mean Reversion system using an interpretable heuristic:
Trend regime when EMA-spread is strong relative to ATR and ATR is rising
Otherwise defaults to Mean Reversion
This prevents running mean-reversion logic in trend breakouts and reduces “mode mismatch.”
5) Multi-timeframe (MTF) confirmation (optional)
MTF confirmation can be enabled to require that the higher timeframe oscillator sign aligns with the direction of the signal. This is useful for reducing noise on MNQ 1m by requiring higher-timeframe structure agreement (e.g., 5m or 15m).
6) MOEP Gate (optional “institutional” filter)
The MOEP gate is a confluence score filter intended to reduce low-quality signals. It aggregates multiple components into a 0–100 score:
BB/KC squeeze condition
Expansion proxy
Trend proxy
Momentum proxy (RSI-based)
Volume catalyst (volume z-score)
Structure break (highest/lowest break)
You can set:
Score threshold (minimum score required)
Minimum components required (forces diversity of evidence)
When enabled, a signal must satisfy both oscillator logic and MOEP confluence conditions.
7) Research harness (NON-CAUSAL, OFF by default)
A built-in research mode evaluates signals using future bars to compute basic forward excursion statistics:
MFE (max favorable excursion)
MAE (max adverse excursion)
Simple win-rate proxy based on MFE vs MAE
This feature is strictly for offline analysis and tuning. It is disabled by default and should not be considered “live-safe” because it uses future information for evaluation.
Signals and interpretation
Mean Reversion regime
Long: oscillator is below the lower band and turns back upward across it
Short: oscillator is above the upper band and turns back downward across it
Trend regime
Long: oscillator crosses above zero (optionally requires structure break confirmation)
Short: oscillator crosses below zero (optionally requires structure break confirmation)
Hybrid
When Hybrid is selected (manual mode), the indicator allows both trend and mean-reversion triggers, but still respects the filters and gates you enable.
Recommended starting configuration (MNQ 1m)
If you want stable, high-quality signals first, then expand into research:
Use RTH only: ON
Auto regime switch: ON
Adaptive length: ON
Adaptive bands: ON
MTF confirmation: OFF initially (turn ON later with 5m)
MOEP Gate: OFF initially (turn ON after you confirm base behavior)
Research harness: OFF (only enable for tuning studies)
Practical notes / transparency
The indicator is designed to be stable on live bars (optional confirmed-bar behavior reduces flicker).
No repainting logic is used for signals.
Any “performance” numbers shown under Research harness are not tradable metrics; they are forward-looking evaluation outputs intended strictly for experimentation.
Disclaimer
This script is provided for educational and research purposes only and does not constitute financial advice. Futures trading involves substantial risk, including the possibility of loss exceeding initial investment.
Session Highlighter with Kill Zones [Exponential-X]Session Highlighter with Kill Zones
Overview
This indicator provides comprehensive visualization of major forex trading sessions (Asian, London, and New York) with integrated kill zone detection and real-time session analytics. It helps traders identify optimal trading times by highlighting high-volatility periods and tracking session-specific price ranges.
What Makes This Original
While session indicators are common, this script uniquely combines several features that work together:
Kill Zone Integration: Highlights specific high-volatility windows within sessions (London: 02:00-05:00 EST, NY: 08:30-11:00 EST) when institutional activity typically peaks
Session Overlap Detection: Automatically detects and highlights when major sessions overlap (London-NY, Asian-London) with distinct visual cues
Real-Time Range Tracking: Calculates and displays percentage-based session ranges as they develop, not just historical data
Dynamic Statistics Dashboard: Live table showing current active session, session times, and comparative range percentages
Customizable Visual System: Flexible styling options including background shading, box overlays, and configurable line styles for session boundaries
How It Works
Session Detection Logic
The script uses timezone-normalized session detection based on EST/EDT times. It converts the current bar's timestamp to New York time and determines which session(s) are active using minute-based calculations. This approach ensures accurate session detection regardless of your chart's timezone settings.
Kill Zones
Kill zones represent periods within sessions when institutional traders are most active. The London kill zone (02:00-05:00 EST) captures pre-London open volatility, while the NY kill zone (08:30-11:00 EST) aligns with US economic data releases and market open activity.
Range Calculations
Session highs, lows, and opens are tracked from the first bar of each session and updated in real-time. Range percentages are calculated as: ((High - Low) / Low) × 100 , providing a volatility measure that's comparable across different instruments and price levels.
Visual System
Background shading: Color-coded zones for each session
Session boxes: Outline entire session ranges
H/L lines: Dynamic lines showing current session extremes
Open lines: Reference levels from session start
Overlap highlighting: Distinct colors when multiple sessions are active simultaneously
How to Use
Intraday Trading: Use kill zones to time entries during high-liquidity periods
Session Breakouts: Monitor for price breaks above/below session highs/lows
Range Trading: Trade between session boundaries during consolidation
Session Continuity: Observe how price behaves as sessions transition
Volatility Assessment: Compare current session ranges to typical values
Recommended Timeframes: Works on any timeframe, but most useful on 1m to 1H charts for intraday trading.
Settings Explained
Sessions Group
Toggle each major session on/off independently
Customize colors for visual clarity
Enable/disable overlap highlighting
Levels Group
Show/hide session high/low lines
Show/hide session open levels
Choose line styles (Solid/Dashed/Dotted)
Kill Zones Group
Toggle kill zone highlighting
Select which kill zones to display
Customize kill zone color intensity
Display Group
Show/hide statistics table
Show/hide session labels on chart
Important Notes
All times are displayed in EST/EDT
Session ranges reset at the start of each new session
Kill zones are session sub-periods, not separate sessions
Overlap colors override individual session colors when multiple sessions are active
The statistics table updates in real-time and shows percentage-based ranges for cross-instrument comparison
Session Times Reference
Asian Session: 19:00 - 04:00 EST (Tokyo open through early Sydney close)
London Session: 03:00 - 12:00 EST (Full European trading hours)
New York Session: 08:00 - 17:00 EST (US market hours)
London Kill Zone: 02:00 - 05:00 EST (Pre-London volatility spike)
NY Kill Zone: 08:30 - 11:00 EST (US open and news releases)
Alerts Available
The script includes six pre-configured alert conditions:
London Kill Zone start
NY Kill Zone start
London-NY Overlap start
Asian Session open
London Session open
NY Session open
Create alerts through TradingView's alert system to get notified when specific sessions or kill zones begin.
Disclaimer: This indicator is for informational purposes only. Session times and kill zones are based on typical market patterns but do not guarantee specific trading outcomes. Always use proper risk management.
SB-VDEMA + PivotsBest use - Intraday Scalping ( 1 Mt, 3 Mts, 5 Mts )
Uses Volatility weighted DEMA for smoother and reliable signals.
One can use dynamic colour coding of VWDEMA for entering call or puts. VWAP and Henkin ashi Supertrend is also there but, i think VWDEMA is quite enogh for decision making.
First 5-Min Candle DetectorHighlights the high and low of the first 5-minute candle of the regular trading session, beginning at 9:30am EST.
MACD Trend Count ScoreThis indicator aims to confirm trends in an asset's price. This confirmation is achieved by counting the MACD bars in a calculation using the chosen timeframe. Positive and negative bars are considered in the calculation of the strength index, which indicates the current trend of that asset.
This Delta index summarizes the predominance of positive or negative bars in the MACD histogram over weekly, bi-weekly, monthly, bi-monthly, and quarterly periods, and, depending on the timeframe used, its result allows one to indicate the intensity of the current trend, according to the results it shows within the following ranges:
Acima de +60 → Strong Raise.
Entre +20 e +60 → Moderate High.
Entre -20 e +20 → Neutral.
Entre -60 e -20 → Moderate Low.
Abaixo de -60 → Strong Low.
Session Levels (Daily & Weekly Targets)This indicator provides market structure and contextual reference only. It does not generate trade signals, entries, or trading advice.
Plots rolling previous daily and weekly highs/lows as potential target levels. Levels automatically remove once touched (including wicks). Default visibility is NY session with optional toggles for London and Asia. Designed for intraday structure, confluence, and target identification.
MA 50/150 Status Light לקראת שנת 2026. בודק האם אנחנו נמצאים מעל ממוצע 150 ו 50 האם בין והאם מתחת
במידה ואנחנו מעל אז מצב המניה חזק
במידה ובין אז סימן אזהרה, החלשות המניה
במידה ומתחת אז מניה חלשה
“Heading into 2026, we check whether the price is above the 50-day and 150-day moving averages, between them, or below them.
If the price is above both, the stock is in a strong condition.
If the price is between them, it is a warning sign — the stock is weakening.
If the price is below both, the stock is weak.”
Trading Dashboard + Daily SMAsThis indicator is an all-in-one workspace overlay designed for futures and intraday traders. It consolidates critical market internals, session statistics, and daily technical levels into a single, highly customizable dashboard.
The goal of this script is to reduce chart clutter by placing essential data into a clean table while overlaying key Daily Moving Averages onto your intraday timeframe.
Key Features:
1. Comprehensive Market Internals Dashboard Monitor the health of the broad market directly from your chart. The dashboard includes real-time data for:
VIX: Volatility Index.
TICK & TRIN: Sentiment and volume flow indicators.
Breadth Data: ADD, ADV, and DECL (Advance/Decline lines and volume).
Multi-Ticker Watch: Monitor 3 additional assets (Defaults: NQ, RTY, YM) with real-time price and % change.
2. Session Statistics & Probabilities Automated calculation of intraday statistics based on a user-defined lookback period (default 100 days):
RTH Data: Tracks Regular Trading Hours Open, Close, and Range.
Contextual ATR: Compares current RTH range to the 14-day ATR.
Probabilities: Displays historical probabilities for "Gap Fill," "Break of Yesterday's High," and "Break of Yesterday's Low."
3. Daily SMAs on Intraday Charts Plot key Daily Simple Moving Averages (21, 50, 200) directly on your lower timeframe charts (1m, 5m, etc.) without switching views.
Fully Customizable: Toggle each SMA on/off individually.
Color Control: Users can change the color of every SMA line to fit their theme.
4. "Dark Mode" Optimized The dashboard features a specific "Very Dark Grey" (#121212) background by default, designed to reduce eye strain and blend seamlessly with dark-themed trading setups.
Settings & Customization:
Session Times: Define your specific RTH start and end times.
Symbols: All ticker symbols (VIX, ADD, NQ, etc.) can be customized in the settings menu to match your data provider.
Visibility: Every element in the table and every SMA line has a toggle switch. You only see what you need.
Visuals: Change table position, text size, and line colors.
Author's Instructions: Configuration Guide
This script relies on specific ticker symbols to pull data for Market Internals (TICK, TRIN, ADD) and the Watchlist. Depending on your data subscription plan (CME, CBOE, etc.), you may need to adjust the default symbols to match what you have access to.
1. How to Change Symbols
Add the indicator to your chart.
Hover over the indicator name in the top-left corner and click the Settings (Gear Icon).
Scroll to the "Symbols" section.
Click inside the text box for the symbol you want to change.
2. Common Symbol Formats If the default symbols show "N/A" or "Error," try these alternatives based on your data feed:
TICK (NYSE Tick)
Default: USI:TICK (Requires specific data)
Alternative: TVC:TICK (General TradingView feed)
Alternative: TICK (Generic)
TRIN (Arms Index)
Default: USI:TRIN
Alternative: TVC:TRIN
Alternative: TRIN
Breadth (ADD/ADV/DECL)
ADD (Advance-Decline Line): Try USI:ADD, TVC:ADD, or ADD
ADV (Advancing Volume): Try USI:ADV, TVC:ADV, or UVOL (Up Volume)
DECL (Declining Volume): Try USI:DECL, TVC:DECL, or DVOL (Down Volume)
VIX
Standard: CBOE:VIX or TVC:VIX
3. Setting Up the Ticker Watchlist (Ticker 1, 2, 3) The script defaults to "Continuous Contracts" (indicated by the 1!), which automatically rolls to the front month.
Nasdaq: CME_MINI:NQ1!
S&P 500: CME_MINI:ES1!
Russell 2000: CME_MINI:RTY1!
Dow Jones: CBOT_MINI:YM1!
Note: If you want to watch a specific contract month (e.g., December 2025), enter the specific code like NQZ2025.
4. Troubleshooting "N/A" Data If a cell in the table is empty or says "N/A":
Verify you are not viewing the chart on a timeframe that excludes the data (though dynamic_requests=true usually handles this).
Ensure you have the correct data permission for that specific symbol.
Market Closed: Some internal data points only populate during the active NYSE session (09:30 - 16:00 ET).
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Past probabilities do not guarantee future results.
3 EMA with Alerts 2025This indicator plots three key EMAs (20, 50, and 200) directly on the chart, making it easy to track short-, medium-, and long-term trends. A color-coded table is displayed in the top-right corner for quick reference.
The script also includes smart alerts that trigger only when the state changes:
• 🔵 EMA 20 crossing above EMA 50 & EMA 200 → Bullish signal
• 🔴 EMA 20 crossing below EMA 50 & EMA 200 → Bearish signal
This tool is designed for traders who want clean visuals, reliable alerts, and simplified trend recognition in 2025 markets.
Volatility High/Low Projection (PHOD / PLOD)AP Capital – Volatility + High/Low Projection
This indicator is designed to identify high-probability intraday turning points by combining daily range statistics, session behaviour, and volatility context into a single clean framework.
It is built for index, forex, and metals traders who want structure, not noise.
🔹 Core Features
1️⃣ Potential High of Day (PHOD) & Potential Low of Day (PLOD)
The indicator highlights likely intraday extremes based on:
Session timing (Asia, London, New York)
Current day volatility vs historical averages
Prior day expansion or compression behaviour
Each level is displayed with:
A clear label (PHOD / PLOD)
A forward-extending box acting as a live Point of Interest (POI)
Automatic invalidation when price breaks the zone
2️⃣ Volatility & Range Context (Info Panel)
A compact information panel in the top-right corner provides real-time context without cluttering the chart:
20-Day Average Range
% of the average range already used today
Range status (NORMAL / EXHAUSTED)
Average session ranges for:
Asia
London
New York
This allows traders to immediately assess whether price is:
Early in the day with room to trend
Statistically stretched and prone to reversal
Over-extended where breakout chasing is risky
3️⃣ Session-Aware Logic
The model respects how markets behave across the trading day:
Asia favours accumulation and potential lows
London provides expansion
New York often delivers distribution or exhaustion
This prevents random high/low marking and focuses only on structurally meaningful levels.
🧠 How to Use
Use PHOD / PLOD boxes as reaction zones, not blind entries
Combine with your own confirmation (structure break, momentum, volume, EMA reclaim, etc.)
Avoid chasing trades when the Range Status = EXHAUSTED
Particularly effective on 15m – 1h timeframes
⚠️ Important Notes
This indicator does not repaint
It is contextual, not a buy/sell signal generator
Best used as part of a complete trading plan
📈 Suitable Markets
XAUUSD (Gold)
Indices (NASDAQ, S&P 500, DAX)
Major FX pairs
📌 Disclaimer
This indicator is for educational and analytical purposes only.
It does not constitute financial advice. Trading involves risk.
CRS (2 symbols: Ratio or Normalized) + InverseMade for Crosrate comparison By Leo Hanhart
This script is made to do a comparison between two assets under your current chart.
For example if you want to compare SPX over Growth ETF's Below a current asset to find momentum in your stock trading above it
SuperTrend Basit v5 - Agresif//@version=5
indicator("SuperTrend Basit v5 - Agresif", overlay=true)
// === Girdi ayarları ===
factor = input.float(3.0, "ATR Katsayısı")
atrPeriod = input.int(10, "ATR Periyodu")
// === Hesaplamalar ===
= ta.supertrend(factor, atrPeriod)
// === Çizim ===
bodyColor = direction == 1 ? color.new(color.lime, 0) : color.new(color.red, 0)
bgcolor(direction == 1 ? color.new(color.lime, 85) : color.new(color.red, 85))
plot(supertrend, color=bodyColor, linewidth=4, title="SuperTrend Çizgisi") // Kalın çizgi
// === Al/Sat sinyali ===
buySignal = ta.crossover(close, supertrend)
sellSignal = ta.crossunder(close, supertrend)
plotshape(buySignal, title="AL", location=location.belowbar, color=color.lime, style=shape.triangleup, size=size.large, text="AL")
plotshape(sellSignal, title="SAT", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.large, text="SAT")
Renkli EMA_MA CROSS
indicator("Renkli MA Kesişimi + Oklar", overlay=true, precision=2
fastLen = input.int(20, "Hızlı MA (Fast)")
slowLen = input.int(50, "Yavaş MA (Slow)")
maType = input.string("EMA", "MA Tipi", options= )
showArrows = input.bool(true, "Okları Göster")
fastMA = maType == "EMA" ? ta.ema(close, fastLen) : ta.sma(close, fastLen)
slowMA = maType == "EMA" ? ta.ema(close, slowLen) : ta.sma(close, slowLen)
barcolor(fastMA > slowMA ? color.new(color.green, 0) : color.new(color.red, 0))
longSignal = ta.crossover(fastMA, slowMA)
shortSignal = ta.crossunder(fastMA, slowMA)
plotshape(showArrows and longSignal, title="Al", style=shape.labelup, location=location.belowbar, color=color.green, size=size.large, text="AL")
plotshape(showArrows and shortSignal, title="Sat", style=shape.labeldown, location=location.abovebar, color=color.red, size=size.large, text="SAT")
plot(fastMA, color=color.blue, title="Hızlı MA")
plot(slowMA, color=color.orange, title="Yavaş MA")
ZLSMA Trend + Al/Sat Sinyali/@version=6
indicator("ZLSMA Trend + Al/Sat Sinyali", overlay=true, max_labels_count=500)
length = input.int(25, "ZLSMA Periyodu")
src = input.source(close, "Kaynak")
thickness = input.int(4, "Çizgi Kalınlığı")
colorUp = input.color(color.new(color.lime, 0), "Yükselen Renk")
colorDown = input.color(color.new(color.red, 0), "Düşen Renk")
ema1 = ta.ema(src, length)
ema2 = ta.ema(ema1, length)
zlsma = 2 * ema1 - ema2
trendUp = zlsma > zlsma
trendDown = zlsma < zlsma
zlsmaColor = trendUp ? colorUp : colorDown
plot(zlsma, title="ZLSMA", color=zlsmaColor, linewidth=thickness)
buySignal = ta.crossover(close, zlsma)
sellSignal = ta.crossunder(close, zlsma)
plotshape(buySignal, title="Al", location=location.belowbar, color=color.new(color.lime, 0), style=shape.triangleup, size=size.large, text="AL")
plotshape(sellSignal, title="Sat", location=location.abovebar, color=color.new(color.red, 0), style=shape.triangledown, size=size.large, text="SAT")
bgcolor(trendUp ? color.new(color.lime, 90) : color.new(color.red, 90))
Pops Dividend 7-Day RadarHow traders use it as a strategy anyway 🧠
In real life, this becomes a manual or semi-systematic strategy:
Strategy logic (human-driven):
Scan for highest yield stocks
Filter for ex-date within 7 days
Apply technical rules (trend, EMAs, support)
Enter before ex-date
Exit:
Before ex-date (momentum run-up)
On ex-date
Or after dividend (reversion play)
Indicator’s role:
“Tell me when a stock qualifies so I can decide how to trade it.”
That’s exactly what this tool does.
How we could turn this into a strategy-style framework
Even though Pine won’t let us backtest dividends properly, we can:
Build a rules-based checklist (entry/exit rules)
Create alerts that behave like strategy triggers
Combine with:
EMA trend filters
Volume conditions
ATR-based exits
Label it as:
“Pops Dividend Capture Playbook” (manual execution)
This keeps it honest, legal, and reliable.
Bottom line
🧩 Indicator = what we built
📘 Strategy = how you trade it using the indicator
⚠️ TradingView limitations prevent a true dividend strategy backtest
RSI Divergence & Momentum Color//@version=5
// هذا مؤشر موحد يحدد الدايفرجنس (العادي والمخفي) ويقوم بتلوين الشموع حسب زخم RSI.
indicator(title="RSI Divergence & Momentum Color", shorttitle="RSI Divergence & MOM", overlay=true)
// --- 1. الإعدادات والمتغيرات (Inputs) ---
// إعدادات RSI
rsiLength = input.int(14, title="RSI Length", minval=1)
// إعدادات تحديد القمم والقيعان (Pivots)
pivotLeft = input.int(5, title="Pivot Lookback Left", minval=1)
pivotRight = input.int(5, title="Pivot Lookback Right", minval=1)
// --- 2. حساب مؤشر القوة النسبية (RSI Calculation) ---
rsi = ta.rsi(close, rsiLength)
// --- 3. تلوين الشموع حسب الزخم (RSI Momentum Color) ---
// فحص: هل RSI الحالي أكبر من RSI السابق؟
isRSIUp = rsi > rsi
// تحديد اللون بناءً على الشرط
var color colorRSI = na
// تلوين الشمعة باللون الأخضر إذا كان RSI صاعداً، وبالأحمر إذا كان هابطاً
if isRSIUp
colorRSI := color.new(color.green, 60) // أخضر فاتح
else
colorRSI := color.new(color.red, 60) // أحمر فاتح
// تطبيق تلوين الشمعة على الشارت الرئيسي
barcolor(colorRSI)
// --- 4. تحديد الدايفرجنس (Divergence Detection) ---
// تحديد القمم والقيعان على السعر
price_high_pivot = ta.pivothigh(high, pivotLeft, pivotRight)
price_low_pivot = ta.pivotlow(low, pivotLeft, pivotRight)
// تحديد القمم والقيعان على RSI
rsi_high_pivot = ta.pivothigh(rsi, pivotLeft, pivotRight)
rsi_low_pivot = ta.pivotlow(rsi, pivotLeft, pivotRight)
// *** المنطق المباشر للدايفرجنس (تظهر الإشارة عند القمة/القاع المكتملة) ***
// 🔵 الدايفرجنس العادي الصعودي (Regular Bullish Div)
isRegBull = price_low_pivot and rsi_low_pivot and low < low and rsi > rsi
// 🔴 الدايفرجنس العادي الهبوطي (Regular Bearish Div)
isRegBear = price_high_pivot and rsi_high_pivot and high > high and rsi < rsi
// 🟪 الدايفرجنس المخفي الصعودي (Hidden Bullish Div)
isHiddenBull = price_low_pivot and rsi_low_pivot and low > low and rsi < rsi
// 🟧 الدايفرجنس المخفي الهبوطي (Hidden Bearish Div)
isHiddenBear = price_high_pivot and rsi_high_pivot and high < high and rsi > rsi
// --- 5. رسم إشارات الدايفرجنس على السعر (Plotting Shapes) ---
// رسم الإشارات على الشارت الرئيسي (لتحديد مناطق الانعكاس/الاستمرار)
// 1. عادي صعودي (انعكاس)
plotshape(isRegBull, title="Regular Bullish Div", location=location.belowbar, style=shape.triangleup, color=color.green, size=size.small)
// 2. عادي هبوطي (انعكاس)
plotshape(isRegBear, title="Regular Bearish Div", location=location.abovebar, style=shape.triangledown, color=color.red, size=size.small)
// 3. مخفي صعودي (استمرار)
plotshape(isHiddenBull, title="Hidden Bullish Div", location=location.belowbar, style=shape.diamond, color=color.blue, size=size.small)
// 4. مخفي هبوطي (استمرار)
plotshape(isHiddenBear, title="Hidden Bearish Div", location=location.abovebar, style=shape.diamond, color=color.orange, size=size.small)
// --- 6. عرض مؤشر RSI في نافذة فرعية (Sub-Window) ---
// يجب إضافة مؤشر RSI بشكل منفصل لترى الدايفرجنس على منحنى RSI
// لكي تظهر الخطوط على منحنى RSI، يجب عليك إضافة كود المؤشر السابق (RSI Divergence Detector (Full))
// على نافذة RSI، ولكن هذا يتعارض مع طلبك دمج كل شيء.
// أفضل طريقة هي: قم بإضافة هذا المؤشر إلى الشارت، ثم أضف مؤشر RSI الافتراضي إلى نافذة جديدة.
// أو يمكنك إنشاء مؤشر RSI منفصل خاص بك في نافذة فرعية:
plot(rsi, title="RSI Value", color=color.rgb(100, 150, 200), display=display.none) // لا تعرض في الشارت الرئيسي
// لعرض RSI في نافذة فرعية، قم بإنشاء مؤشر جديد واضبط overlay=false
// أو استخدم المؤشر التالي (بما أن هذا المؤشر يحتوي على overlay=true، لن يرسم RSI أسفل الشارت).
// --- ملاحظة أخيرة: لرسم الخطوط على RSI أسفل الشارت ---
// لتحقيق ذلك بالضبط، يجب كتابة مؤشر ثانٍ بـ (overlay=false)
// يحتوي على نفس منطق الدايفرجنس. لتجنب ذلك، يكتفي هذا الكود برسم الإشارات
// على السعر (overlay=true) وتلوين الشموع.
Swing Trading Indicator: RSI + EMA + MACD + BB Signals**Swing Trading Indicator: Multi-Indicator Confluence Signals**
This indicator identifies high-probability swing trading setups using RSI pullbacks, EMA trend filter, MACD momentum confirmation, and Bollinger Bands for volatility-based entries. Perfect for daily/4H charts on stocks like TSLA or SPY.
**Key Features:**
- **Long Signal (Green ↑ Arrow)**: Uptrend (above 200 EMA) + RSI crosses above oversold (default 30) + MACD bullish crossover + Price at/near BB lower band + Optional squeeze filter.
- **Short Signal (Red ↓ Arrow)**: Mirror for downtrends.
- **Real-Time Dashboard**: Top-right table shows condition status (✓/✗) and "LONG/SHORT READY" alerts.
- **Customizable**: Adjust RSI levels, BB multiplier, enable/disable shorts/squeeze/arrows.
- **Alerts**: Built-in for entry notifications.
**How to Use:**
1. Add to chart (daily timeframe recommended).
2. Watch for arrows + "READY" in dashboard.
3. Manual entry: Risk 1% per trade, target 1:2 reward (e.g., trail stops).
**Backtest Note**: Based on similar setups, ~55-65% win rate in trending markets (test yourself). Not financial advice—trading involves risk. Fork and improve!
#swingtrading #RSI #MACD #BollingerBands #PineScript
