EMA Trend Cloud with HH/LL Counter [RanAlgo]Indicator Overview:
This indicator combines EMA-based trend analysis with pivot point detection to identify market trends and potential reversal points. It features:
EMA Cloud System: Dual cloud layers (8/22 EMA and 21/49 EMA) for trend visualization
Pivot Analysis: Identifies Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL)
Counter System: Tracks daily and session counts of HH/LL patterns
Key Components:
EMA Configuration:
Fast EMAs: 8, 21, 22
Medium EMAs: 49, 50
Slow EMA: 100
Cloud formations between EMAs (8/22 and 21/49) with adjustable opacity
Trend Signals:
Buy signals when EMA8 crosses above EMA22 (green cloud)
Sell signals when EMA8 crosses below EMA22 (red cloud)
Additional confirmation from 21/49 EMA cloud
Pivot Point System:
Customizable lookback period (default 16 bars)
Four pivot types with customizable visuals:
HH (Higher High) - Green
HL (Higher Low) - Blue
LH (Lower High) - Red
LL (Lower Low) - Orange
Extended lines with adjustable length
Counter Table:
Displays daily counts of HH and LL patterns
Six position options for table placement
Color-coded to match pivot line colors
Trading Rules:
Trend Following:
Go long when both clouds are green (EMA8 > EMA22 AND EMA21 > EMA49)
Go short when both clouds are red (EMA8 < EMA22 AND EMA21 < EMA49)
Pivot Confirmation:
Strong uptrend confirmed by consecutive HH and HL patterns
Strong downtrend confirmed by consecutive LH and LL patterns
Potential reversals when pattern sequences break
Counter Interpretation:
Increasing HH count suggests strong bullish momentum
Increasing LL count suggests strong bearish momentum
Divergences between price and counts may signal weakening trends
Customization Options:
Adjustable EMA lengths (hardcoded but can be modified)
Cloud opacity controls
Pivot line colors, styles, and thickness
Lookback period for pivot detection
Line extension length
Table visibility and positioning
Display Features:
Clean visual design that doesn't obscure price action
Non-repainting elements (uses confirmed pivots only)
Minimal screen space usage with optional table
This indicator complies with TradingView's guidelines by:
Using non-repainting calculations (confirmed pivots only)
Providing clear source code with comments
Offering comprehensive customization without overcrowding
Including proper input validation
Maintaining readable visuals at all zoom levels
The tool is designed for trend identification and confirmation, suitable for various timeframes and instruments. Users should combine it with other analysis techniques for best results.
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CCI Divergence Detector
A technical analysis tool that identifies divergences between price action and the Commodity Channel Index (CCI) oscillator. Unlike standard divergence indicators, this system employs advanced gradient visualization, multi-layer wave effects, and comprehensive customization options to provide traders with crystal-clear divergence signals and market momentum insights.
Core Detection Mechanism
CCI-Based Analysis: The indicator utilizes the Commodity Channel Index as its primary oscillator, calculated from user-configurable source data (default: HLC3) with adjustable length parameters. The CCI provides reliable momentum readings that effectively highlight price-momentum divergences.
Dynamic Pivot Detection: The system employs adaptive pivot detection with three sensitivity levels (High/Normal/Low) to identify significant highs and lows in both price and CCI values. This dynamic approach ensures optimal divergence detection across different market conditions and timeframes.
Dual Divergence Analysis:
Regular Bullish Divergences: Detected when price makes lower lows while CCI makes higher lows, indicating potential upward reversal
Regular Bearish Divergences: Identified when price makes higher highs while CCI makes lower highs, signaling potential downward reversal
Strength Classification System: Each detected divergence is automatically classified into three strength categories (Weak/Moderate/Strong) based on:
-Price differential magnitude
-CCI differential magnitude
-Time duration between pivot points
-User-configurable strength multiplier
Advanced Visual System
Multi-Layer Wave Effects: The indicator features a revolutionary wave visualization system that creates depth through multiple gradient layers around the CCI line. The wave width dynamically adjusts based on ATR volatility, providing intuitive visual feedback about market conditions.
Professional Color Gradient System: Nine independent color inputs control every visual aspect:
Bullish Colors (Light/Medium/Dark): Control oversold areas, wave effects, and strong bullish signals
Bearish Colors (Light/Medium/Dark): Manage overbought zones, wave fills, and strong bearish signals
Neutral Colors (Light/Medium/Dark): Handle table elements, zero line, and transitional states
Intelligent Color Mapping: Colors automatically adapt based on CCI values:
Overbought territory (>100): Bearish color gradients with increasing intensity
Neutral positive (0 to 100): Blend from neutral to bearish tones
Oversold territory (<-100): Bullish color gradients with increasing intensity
Neutral negative (-100 to 0): Transition from neutral to bullish tones
Key Features & Components
Advanced Configuration System: Eight organized input groups provide granular control:
General Settings: System enable, pivot length, confidence thresholds
Oscillator Selection: CCI parameters, overbought/oversold levels, normalization options
Detection Parameters: Divergence types, minimum strength requirements
Sensitivity Tuning: Pivot sensitivity, divergence threshold, confirmation bars
Visual System: Line thickness, labels, backgrounds, table display
Wave Effects: Dynamic width, volatility response, layer count, glow effects
Transparency Controls: Independent transparency for all visual elements
Smoothing & Filtering: CCI smoothing types, noise filtering, wave smoothing
Professional Alert System: Comprehensive alert functionality with dynamic messages including:
-Divergence type and strength classification
-Current CCI value and confidence percentage
-Customizable alert frequency and conditions
Enhanced Information Table: Real-time display showing:
-Current CCI length and value
-Market status (Overbought/Normal/Oversold)
-Active sensitivity setting
Configurable table positioning (4 corner options)
Visual Elements Explained
Primary CCI Line: Main oscillator plot with gradient coloring that reflects market momentum and CCI intensity. Line thickness is user-configurable (1-8 pixels).
Wave Effect Layers: Multi-layer gradient fills creating a dynamic wave around the
CCI line:
-Outer layers provide broad market context
-Inner layers highlight immediate momentum
-Core layers show precise CCI movement
-All layers respond to volatility and momentum changes
Divergence Lines & Labels:
-Solid lines connecting divergence pivot points
-Color-coded based on divergence type and strength
-Labels displaying divergence type and strength classification
-Customizable transparency and size options
Reference Lines:
-Zero line with neutral color coding
-Overbought level (default: 100) with bearish coloring
-Oversold level (default: -100) with bullish coloring
Background Gradient: Optional background coloring that reflects CCI intensity and market conditions with user-controlled transparency (80-99%).
Configuration Options
Sensitivity Controls:
Pivot sensitivity: High/Normal/Low detection levels
Divergence threshold: 0.1-2.0 sensitivity range
Confirmation bars: 1-5 bar confirmation requirement
Strength multiplier: 0.1-3.0 calculation adjustment
Visual Customization:
Line transparency: 0-90% for main elements
Wave transparency: 0-95% for fill effects
Background transparency: 80-99% for subtle background
Label transparency: 0-50% for text elements
Glow transparency: 50-95% for glow effects
Advanced Processing:
Five smoothing types: None/SMA/EMA/RMA/WMA
Noise filtering with adjustable threshold (0.1-10.0)
CCI normalization for enhanced gradient scaling
Dynamic wave width with ATR-based volatility response
Interpretation Guidelines
Divergence Signals:
Strong divergences: High-confidence reversal signals requiring immediate attention
Moderate divergences: Reliable signals suitable for most trading strategies
Weak divergences: Early warning signals best combined with additional confirmation
Wave Intensity: Wave width and color intensity provide real-time volatility and momentum feedback. Wider, more intense waves indicate higher market volatility and stronger momentum.
Color Transitions: Smooth color transitions between bullish, neutral, and bearish states help identify market regime changes and momentum shifts.
CCI Levels: Traditional overbought (>100) and oversold (<-100) levels remain relevant, but the gradient system provides more nuanced momentum reading between these extremes.
Technical Specifications
Compatible Timeframes: All timeframes supported
Maximum Labels: 500 (for divergence marking)
Maximum Lines: 500 (for divergence drawing)
Pine Script Version: v5 (latest optimization)
Overlay Mode: False (separate pane indicator)
Usage Recommendations
This indicator works best when:
-Combined with price action analysis and support/resistance levels
-Used across multiple timeframes for confirmation
-Integrated with proper risk management protocols
-Applied in trending markets for divergence-based reversal signals
-Utilized with other technical indicators for comprehensive analysis
Risk Disclaimer: Trading involves substantial risk of loss. This indicator is provided for analytical purposes only and does not constitute financial advice. Divergence signals, while powerful, are not guaranteed to predict future price movements. Past performance is not indicative of future results. Always use proper risk management and never trade with capital you cannot afford to lose.
Adaptive Freedom Machine w/labelsAdaptive Freedom Machine w/ Labels
Overview
The Adaptive Freedom Machine w/ Labels is a versatile Pine Script indicator designed to assist traders in identifying buy and sell opportunities across various market conditions (trending, ranging, or volatile). It combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), Average True Range (ATR), and customizable time filters to generate actionable signals. The indicator overlays on the price chart, displaying EMAs, a dynamic cloud, scaled RSI levels, buy/sell signals, and market condition labels, making it suitable for swing trading, day trading, or scalping.
What It Does
This indicator generates buy and sell signals based on the interaction of two EMAs, filtered by RSI thresholds, ATR-based volatility, and user-defined time windows. It adapts to the selected market condition by adjusting EMA lengths, RSI thresholds, and trading hours. A dynamic cloud highlights trend direction or neutral zones, and candlestick bodies are colored in neutral conditions for clarity. A table displays real-time trend and volatility status.
How It Works
The indicator uses the following components:
EMAs: Two EMAs (short and long) are calculated on a user-selected timeframe (1, 5, 15, 30, or 60 minutes). Their crossover or crossunder generates potential buy/sell signals, with lengths adjusted based on the market condition (e.g., longer EMAs for trending markets, shorter for ranging).
Dynamic Cloud: The area between the EMAs forms a cloud, colored green for uptrends, red for downtrends, or a user-defined color (default yellow) for neutral zones (when EMAs are close, determined by an ATR-based threshold). Users can widen the cloud for visibility.
RSI Filter: RSI is scaled to price levels and plotted on the chart (optional). Signals are filtered to ensure RSI is within user-defined buy/sell thresholds and not in overbought/oversold zones, with thresholds tailored to the market condition.
ATR Volatility Filter: An optional filter ensures signals occur during sufficient volatility (ATR(14) > SMA(ATR, 20)).
Time Filter: Signals are restricted to a user-defined or market-specific time window (e.g., 10:00–15:00 UTC for volatile markets), with an option for custom hours.
Visual Aids: Buy/sell signals appear as green triangles (buy) or red triangles (sell). Candlesticks in neutral zones are colored (default yellow). A table in the top-right corner shows the current trend (Uptrend, Downtrend, Neutral) and volatility (High or Low).
The indicator ensures compatibility with standard chart types (e.g., candlestick charts) to produce realistic signals, avoiding non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Timeframe: Choose a timeframe (1, 5, 15, 30, or 60 minutes) to align with your trading style.
Market Condition: Select one market condition (Trending, Ranging, or Volatile). Volatile is the default if none is selected. Only one condition can be active.
Filters:
Enable/disable the ATR volatility filter to trade only in high-volatility periods.
Enable the time filter and choose default hours (specific to the market condition) or set custom UTC hours.
Cloud Settings: Adjust the cloud width, neutral zone threshold, and color. Enable/disable the neutral cloud.
RSI Display: Toggle the scaled RSI and its thresholds on the chart.
Interpret Signals:
Buy Signal: A green triangle below the bar indicates a potential long entry (EMA crossover, RSI above buy threshold, within time window, and passing volatility filter).
Sell Signal: A red triangle above the bar indicates a potential short entry (EMA crossunder, RSI below sell threshold, within time window, and passing volatility filter).
Neutral Zone: Yellow candlesticks and cloud (if enabled) suggest a lack of clear trend; avoid trading or use for range-bound strategies.
Monitor the Table: Check the top-right table for real-time trend (Uptrend, Downtrend, Neutral) and volatility (High or Low) to confirm market context.
Unique Features
Adaptive Parameters: Automatically adjusts EMA lengths, RSI thresholds, and trading hours based on the selected market condition, reducing manual tweaking.
Neutral Zone Detection: Uses an ATR-based threshold to identify low-trend periods, helping traders avoid choppy markets.
Scaled RSI Visualization: Plots RSI and thresholds directly on the price chart, making it easier to assess momentum relative to price action.
Flexible Time Filtering: Supports both default and custom UTC-based trading windows, ideal for day traders targeting specific sessions.
Dynamic Cloud: Enhances trend visualization with customizable width and neutral zone coloring, improving readability.
Notes
Use on standard candlestick or bar charts to ensure realistic signals.
Test the indicator on a demo account to understand its behavior in your chosen market and timeframe.
Adjust settings to match your trading strategy, but avoid over-optimizing for past data.
The indicator is not a standalone system; combine it with other analysis (e.g., support/resistance, news events) for better results.
Limitations
Signals may lag in fast-moving markets due to EMA-based calculations.
Neutral zone detection may vary in extremely volatile or illiquid markets.
Time filters are UTC-based; ensure your platform’s timezone settings align.
This indicator is designed for traders seeking a customizable, trend-following tool that adapts to different market environments while providing clear visual cues and robust filtering.
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
---
### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
---
### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
---
**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
BTC Daily DCA CalculatorThe BTC Daily DCA Calculator is an indicator that calculates how much Bitcoin (BTC) you would own today by investing a fixed dollar amount daily (Dollar-Cost Averaging) over a user-defined period. Simply input your start date, end date, and daily investment amount, and the indicator will display a table on the last candle showing your total BTC, total invested, portfolio value, and unrealized yield (in USD and percentage).
Features
Customizable Inputs: Set the start date, end date, and daily dollar amount to simulate your DCA strategy.
Results Table: Displays on the last candle (top-right of the chart) with:
Total BTC: The accumulated Bitcoin from daily purchases.
Total Invested ($): The total dollars invested.
Portfolio Value ($): The current value of your BTC holdings.
Unrealized Yield ($): Your profit/loss in USD.
Unrealized Yield (%): Your profit/loss as a percentage.
Visual Markers: Green triangles below the chart mark each daily investment.
Overlay on Chart: The table and markers appear directly on the BTCUSD price chart for easy reference.
Daily Timeframe: Designed for Daily (1D) charts to ensure accurate calculations.
How to Use
Add the Indicator: Apply the indicator to a BTCUSD chart (e.g., Coinbase:BTCUSD, Binance:BTCUSDT).
Set Daily Timeframe: Ensure your chart is on the Daily (1D) timeframe, or the script will display an error.
Configure Inputs: Open the indicator’s Settings > Inputs tab and set:
Start Date: When to begin the DCA strategy (e.g., 2024-01-01).
End Date: When to end the strategy (e.g., 2025-04-27 or earlier).
Daily Investment ($): The fixed dollar amount to invest daily (e.g., $100).
View Results: Scroll to the last candle in your date range to see the results table in the top-right corner of the chart. Green triangles below the bars indicate investment days.
Settings
Start Date: Choose the start date for your DCA strategy (default: 2024-01-01).
End Date: Choose the end date (default: 2025-04-27). Must be after the start date and within available chart data.
Daily Investment ($): Set the daily investment amount (default: $100). Minimum is $0.01.
Notes
Timeframe: The indicator requires a Daily (1D) chart. Other timeframes will trigger an error.
Data: Ensure your BTCUSD chart has historical data for the selected date range. Use reliable pairs like Coinbase:BTCUSD or Binance:BTCUSDT.
Limitations: Does not account for trading fees or slippage. Future dates (beyond the current date) will not display results.
Performance: Works best with historical data. Free TradingView accounts may have limited historical data; consider premium for longer ranges.
Cot DeltaCOT Delta by Jacopo
Designed to visualize and analyze data related to the Commitment of Traders (COT) report, which is published by the Commodity Futures Trading Commission (CFTC) in the United States. Its primary purpose is to display the long and short positions of traders on futures contracts, divided by categories like Commercial, Noncommercial, and Nonreportable.
Main Features:
Selection Mode: The user can choose from several modes to display COT data, such as "Auto", "Root", "Base currency", or "Currency". This determines which currency will be shown on the chart.
Contract Type: It is possible to select whether to display data for Futures, Options, or both (Futures + Options).
COT Category: The user can choose one of the trader categories like Commercial Positions, Noncommercial Positions, or Nonreportable Positions to analyze positions based on the type of market participant.
Data Visualization: The chart shows long, short, and net positions (long - short) with separate lines, using different colors for each type of position:
Long positions in green.
Short positions in red.
Net difference (long - short) in white.
Data Table: A table is displayed to present the data clearly, with the following columns:
Long: Long positions.
Short: Short positions.
Total: The net sum of positions (long - short).
Changes: The difference between current and previous data (delta) in both absolute and percentage terms.
Variation Visualization: The table also shows the variations from the previous period (both in absolute and percentage terms), with conditional background colors to highlight positive or negative changes.
Optional CFTC Code: The user can input a custom CFTC code to analyze specific data, if necessary.
In Summary:
This indicator provides a clear and precise visualization of trader positions (long and short) on futures and options contracts, making it easier to analyze market dynamics related to commercial and non-commercial traders. The combination of a chart and table allows for real-time tracking of position changes.
3CRGANG - Histogram (Basic)This indicator provides traders with a unified view of momentum by combining multiple classic oscillators into a single histogram. By aggregating momentum signals into one visual output, it simplifies trend analysis, helping traders identify momentum shifts without managing multiple indicators separately.
What It Does
The 3CRGANG - Histogram (Basic) calculates a momentum-based histogram using a user-selected oscillator (e.g., RSI, MACD, MFI, RVI, Stochastic, Stochastic RSI, or TMASlope). The histogram is plotted with color-coded bars to indicate bullish, bearish, or neutral momentum, alongside predefined alert levels and a trend status table for quick reference.
Why It’s Useful
This script addresses the challenge of monitoring multiple momentum indicators by consolidating them into a single histogram. Each oscillator measures momentum differently (e.g., RSI tracks price strength, MACD focuses on moving average convergence, MFI incorporates volume), but the script normalizes these signals into a unified output. This reduces chart clutter and provides a clear, actionable signal for identifying trend direction, making it easier for traders to focus on key momentum shifts across various market conditions.
How It Works
The script follows these steps to generate the histogram:
Oscillator Selection: Traders choose one oscillator to base the histogram on. For example: RSI measures the speed and change of price movements, MACD tracks the relationship between two exponential moving averages, and MFI combines price and volume to measure buying/selling pressure. The choice of oscillator affects the histogram’s sensitivity to price movements.
Fast Oscillator Calculation: A fast-moving oscillator is computed using the selected method over a user-defined period (default: 8 bars). For instance, RSI calculates the relative strength of price gains versus losses, while MACD computes the difference between short and long EMAs. The result is normalized to a range centered around zero.
Histogram Plotting: The oscillator’s output is adjusted by a modification factor (default: 1) for sensitivity tuning and plotted as a histogram. Positive values indicate bullish momentum, negative values indicate bearish momentum, and values near zero suggest a lack of clear trend.
Color Coding: Bars are colored based on momentum and price direction: green for bullish momentum (price moving upward, histogram value typically positive), red for bearish momentum (price moving downward, histogram value typically negative), and grey for neutral momentum (ranging conditions or unclear trend).
Alert Levels: Predefined buy and sell levels are plotted as dotted lines to mark significant momentum thresholds. For most oscillators, levels are set at 20 (buy) and -20 (sell), representing overbought/oversold conditions based on historical performance. For TMASlope, levels are adjusted to 0.04 and -0.04, as it measures the slope of a triangular moving average relative to the average true range (ATR).
Trend Table: A table in the top-right corner displays the current timeframe’s trend status ("Buy Only," "Sell Only," or "Ranging") based on the histogram value, price direction, and alert levels, along with the histogram’s numerical value.
Underlying Concepts
The script is built on the concept of momentum aggregation, aiming to capture short-term price dynamics while filtering noise. By using a fast-moving oscillator, it emphasizes recent price action, and the histogram format provides a visual summary of momentum strength. The alert levels are derived from typical overbought/oversold thresholds for each oscillator, adjusted to ensure consistency across different methods. The trend table adds a layer of interpretation, helping traders quickly assess whether the momentum aligns with the broader trend.
Use Case
Trending Markets: In a bullish trend, green bars above the buy alert level (e.g., 20) indicate strong upward momentum, suggesting potential long entries. In a bearish trend, red bars below the sell alert level (e.g., -20) suggest short opportunities.
Ranging Markets: Grey bars or values between alert levels indicate a lack of clear momentum, prompting caution or scalping strategies.
Confirmation Tool: Use the histogram to confirm price action signals, such as breakouts or reversals, by ensuring momentum aligns with the direction of the move. For example, a breakout with green bars above the buy level may signal a stronger trend.
Settings
Choose Type: Select the oscillator to use (default: RSI - CLASSIC).
Source: Choose between Close or HL2 price data (default: Close).
Histogram Length: Set the period for oscillator calculation (options: 5, 8, 13; default: 8).
Modification Factor: Adjust the sensitivity of the histogram (default: 1).
Notes
The script supports classic oscillators only and operates on the current timeframe.
If volume data is unavailable for your ticker, MFI calculations may not work; select another oscillator to continue plotting.
Disclaimer
This indicator is a tool for analyzing market trends and does not guarantee trading success. Trading involves risk, and past performance is not indicative of future results. Always use proper risk management.
DoloresOverview
The "Dolores Trading Assistant" is a sleek and intuitive indicator designed to empower traders during the high-volatile New York trading session. This tool overlays a customizable table on your chart, presenting real-time insights from key market internals—NYSE and Nasdaq Advance/Decline (A/D), Volume Difference (VOLD), and TICK—in a clear, color-coded format. Its streamlined design focuses on delivering essential market data with trend states, making it a practical companion for assessing momentum and sentiment at a glance.
Purpose and Usefulness
Tailored for intraday traders, the Dolores Trading Assistant goes beyond price-based analysis by tapping into broad market internals to uncover the underlying forces driving the New York session. Whether you’re scalping, day trading, or monitoring short-term trends, this indicator helps you quickly gauge market direction, confirm momentum, and identify potential shifts—all from a single, visually accessible table. Its simplicity and focus on real-time data make it a valuable tool for traders seeking clarity in fast-moving markets.
How It Works
The indicator fetches live data from six vital market internals using a 1-second timeframe:
NYSE Advance/Decline (A/D) - Tracks the net balance of advancing versus declining NYSE stocks.
Nasdaq Advance/Decline (A/D) - Monitors the same for Nasdaq stocks.
NYSE VOLD - Measures the net volume difference between buying and selling on the NYSE.
Nasdaq VOLD - Captures the equivalent for Nasdaq.
NYSE TICK - Reflects the net number of NYSE stocks ticking up versus down.
Nasdaq TICK - Provides the same for Nasdaq.
These internals are processed to determine their trend states—such as bullish, bearish, or neutral—displayed in colors and emojis for instant recognition. The table organizes this data into three columns: the condition (e.g., "NYSE A/D"), its current reading (formatted for readability, like "1.2m" or "500k"), and its trend state (e.g., "Trending Bullish" or "Neutral"). This setup offers a snapshot of market health without overwhelming the user with excessive details.
Internal Signals and Their Role
Each internal signal contributes to understanding the market’s current state and the conditions you’re trading into:
NYSE and Nasdaq A/D: Reveals market breadth. Strong positive values suggest widespread buying, while negative readings indicate broad selling, helping you confirm if a move has robust participation.
NYSE and Nasdaq VOLD: Tracks volume momentum. High positive figures point to aggressive buying pressure, while deep negatives signal heavy selling, validating whether price moves are backed by volume.
NYSE and Nasdaq TICK: Captures short-term sentiment. Extreme readings highlight overbought or oversold conditions, offering clues about momentum strength or potential exhaustion.
How Signals Confirm Conditions
Trend States: Each internal’s trend state (e.g., "Bullish," "Bearish," "Trending Bearish") reflects its current momentum. Consistent bullish states across multiple internals confirm a strong upward trend, while bearish alignments suggest selling pressure. Neutral or mixed states indicate indecision or choppiness, guiding you to adjust expectations accordingly.
Visual Cues: Color-coded backgrounds (e.g., green for bullish, red for bearish) and emojis (e.g., 🐂for bullish, 🐻for bearish) make it easy to spot dominant conditions or emerging shifts, enhancing your ability to react quickly.
How to Use It
Add to Chart: Apply the indicator to any symbol (Best W/ SPY, QQQ, IWM and correlated futures securities) on a 1-second or higher timeframe. The table appears in your chosen position (default: bottom right).
Monitor Internals: Check the table for real-time readings and trend states. For example, "NYSE TICK: 800, Strong Overbought Rally" signals short-term bullish momentum.
Assess Conditions: Look for alignment across internals—e.g., multiple "Bullish" states suggest buying strength, while "Neutral" dominance warns of choppy action.
Adapt Your Strategy: Use the trend states to confirm entries, exits, or hold-off decisions. Pair with price tools (e.g., candlestick patterns) for a fuller picture.
Customize: Adjust table position, orientation (vertical/horizontal), text size, colors, and transparency via inputs to match your setup.
Customization
Tailor the experience with options for table placement (e.g., "Top Left"), text size (e.g., "Small" to "Huge"), orientation, and color schemes. Adjust transparency settings to keep the table unobtrusive yet readable.
Limitations
Requires real-time NYSE/Nasdaq data access, which may depend on your TradingView subscription.
Displays current conditions only, not predictive signals—use it as a real-time snapshot, not a crystal ball.
Best paired with price analysis for comprehensive trading decisions.
Requires a TradingView Subscription that supports the 1s Time Frame
Why It’s Original
The Dolores Trading Assistant stands out with its elegant, yet simple table-based presentation of NYSE and Nasdaq internals, distilled into an intuitive format with trend states and visual cues. Unlike cluttered dashboards or generic mashups, it offers a focused, trader-centric view of market momentum, avoiding unnecessary complexity while delivering actionable insights—making it a fresh and practical tool for the New York session.
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Market Sessions [APIDEVs]Description
The 🐸 Market Sessions 👑 indicator is an advanced and highly customizable tool designed for traders who want to visualize and manage market sessions directly on their TradingView charts. With support for up to four configurable sessions (by default: Sydney, Tokyo, London, and New York), this indicator allows you to adjust times, time zones, day filters, and display styles to suit your trading strategy.
In addition to displaying active sessions on the chart using dotted lines or colored backgrounds, it includes an interactive table that provides a quick overview of each session's status, active hours, and the current date adjusted to your time zone. Ideal for intraday traders, forex traders, or anyone needing precise control over market periods.
Main Features
Customizable Sessions: Define up to four sessions with unique names, times (HHMM-HHMM format), and colors.
Time Zone Adjustment: Select your time zone (UTC-12 to UTC+12) to align the sessions with your local time.
Day Filter: Enable or disable sessions by day of the week (Monday to Sunday).
Flexible Visualization: Choose between dotted lines ("Line"), colored background ("Background"), or no visual representation ("None").
Information Table: Displays session status (🟢 active / 🔴 inactive), active hours, and the current date in a compact and configurable format (adjustable size and position).
Daily Dividers: Optionally, add vertical lines and labels to mark the change of day (useful on timeframes ≤ 4 hours).
How to Use
Add the indicator to your chart.
Configure the sessions in the settings menu:
Enable/disable sessions and define their names, times, and colors.
Select your time zone to synchronize the times.
Choose the days of the week you want the sessions to be visible.
Customize the display:
Decide if you prefer lines, background, or no representation on the chart.
Adjust the size and position of the table according to your needs.
Analyze the sessions in real-time using the table and the chart.
Stoch RSI Multi-Timeframe Cross Indicator
Stoch RSI Multi-Timeframe Cross Indicator
Overview
This Pine Script v6 indicator is designed to monitor Stochastic RSI crossovers across multiple timeframes (1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, and daily) and provide visual and alert-based signals for trading decisions. It overlays on the chart, displaying:
A table showing the bullish (green) or bearish (red) state of each timeframe.
Triangles and labels ("Long" or "Short") to indicate entry points when all enabled timeframes align in a bullish or bearish direction.
Alerts for when all enabled timeframes turn bullish or bearish.
The indicator tracks crossovers between the Stochastic RSI %K and %D lines, persisting the state (bullish or bearish) until the next crossover occurs, mimicking the behavior of the original RSI-based script but adapted for Stochastic RSI.
Inputs
RSI Length (rsiLength): Length of the RSI calculation (default: 14).
Stochastic Length (stochLength): Lookback period for the Stochastic RSI calculation (default: 14).
Smooth K (smoothK): Smoothing period for the %K line (default: 3).
Smooth D (smoothD): Smoothing period for the %D line (default: 3).
Use in Logic (use1m, use5m, etc.): Boolean toggles to include or exclude each timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D) in the entry signal logic (default: all true).
Timeframes
The indicator monitors the following timeframes, defined as strings compatible with Pine Script v6:
1-minute ("1")
5-minute ("5")
15-minute ("15")
30-minute ("30")
1-hour ("60")
4-hour ("240")
Daily ("D")
Core Logic
Stochastic RSI Calculation:
For each timeframe, the indicator:
Computes RSI using ta.rsi(close, rsiLength).
Applies the stochastic formula to RSI with ta.stoch(rsi, rsi, rsi, stochLength) to get the raw Stochastic RSI.
Smooths the result with ta.sma() to calculate %K (using smoothK) and %D (using smoothD).
This is done within a stochRsiState function, which is called via request.security() to ensure calculations align with each timeframe’s data.
Crossover Detection:
Detects crossovers using ta.crossover(k, d) (bullish) and ta.crossunder(k, d) (bearish).
Maintains a persistent state (var bool isBullish) for each timeframe, updated only when a crossover occurs:
true (bullish) when %K crosses above %D.
false (bearish) when %K crosses below %D.
Multi-Timeframe States:
Each timeframe’s %K, %D, and isBullish state is fetched independently using request.security(), ensuring accurate crossover detection regardless of the chart’s timeframe.
Visual Outputs
Table:
A static table in the bottom-left corner displays the state of each timeframe:
Columns: "1M", "5M", "15M", "30M", "1H", "4H", "1D".
Background color: Green (color.green) for bullish, Red (color.red) for bearish.
Updates on the last confirmed bar (barstate.islast).
Triangles:
Green upward triangle below the bar when all enabled timeframes are bullish (allBullish).
Red downward triangle above the bar when all enabled timeframes are bearish (allBearish).
Labels:
"Long" label (green) below the bar when allBullish is true.
"Short" label (red) below the bar when allBearish is true.
Displayed only on the last confirmed historical bar (barstate.islastconfirmedhistory).
Alerts
All Timeframes Bullish: Triggers when all enabled timeframes are bullish, with the message: "All Stoch RSI timeframes are bullish (green)!"
All Timeframes Bearish: Triggers when all enabled timeframes are bearish, with the message: "All Stoch RSI timeframes are bearish (red)!"
Conditions for Signals
Bullish Condition (allBullish):
True when all enabled timeframes (use1m ? isBullish1m : true, etc.) are bullish, and at least one timeframe is enabled.
Bearish Condition (allBearish):
True when all enabled timeframes are bearish, and at least one timeframe is enabled.
Disabled timeframes are treated as neutral (always true) in the logic, ensuring they don’t block signals.
Usage
Add the indicator to your TradingView chart.
Adjust input parameters (e.g., rsiLength, stochLength, smoothK, smoothD) to match your trading strategy.
Enable/disable timeframes via the input settings to focus on specific ones.
Watch the table for individual timeframe states and the chart for entry signals ("Long"/"Short") when all enabled timeframes align.
Set up alerts to be notified of full alignment.
Notes
The indicator is designed to persist the crossover state until the next crossover, similar to the original RSI-based script, ensuring stability across chart timeframe switches.
It uses request.security() to fetch data, making it robust for multi-timeframe analysis, though performance may depend on the chart’s data availability.
Stoch RSI Multi-Timeframe Cross Индикатор
Обзор
Этот индикатор Pine Script v6 предназначен для мониторинга пересечений Stochastic RSI на нескольких таймфреймах (1-минутный, 5-минутный, 15-минутный, 30-минутный, 1-часовой, 4-часовой и дневной) и предоставления визуальных и основанных на оповещениях сигналов для принятия торговых решений. Он накладывается на график, отображая:
Таблица, показывающая бычье (зеленый) или медвежье (красный) состояние каждого таймфрейма.
Треугольники и метки («Длинный» или «Короткий») для обозначения точек входа, когда все включенные таймфреймы совпадают в бычьем или медвежьем направлении.
Оповещения о том, когда все включенные таймфреймы становятся бычьими или медвежьими.
Индикатор отслеживает пересечения линий %K и %D стохастического RSI , сохраняя состояние (бычье или медвежье) до тех пор, пока не произойдет следующее пересечение, имитируя поведение исходного скрипта на основе RSI, но адаптированного для стохастического RSI.
Входы
Длина RSI ( rsiLength ): длина расчета RSI (по умолчанию: 14).
Длина стохастика ( stochLength ): период ретроспективного анализа для расчета стохастического RSI (по умолчанию: 14).
Сглаживание K ( smoothK ): период сглаживания для линии %K (по умолчанию: 3).
Smooth D ( smoothD ): период сглаживания для линии %D (по умолчанию: 3).
Использовать в логике ( use1m , use5m и т. д.): логические переключатели для включения или исключения каждого таймфрейма (1M, 5M, 15M, 30M, 1H, 4H, 1D) в логику входного сигнала (по умолчанию: все true).
Временные рамки
Индикатор отслеживает следующие таймфреймы, определенные как строки, совместимые с Pine Script v6:
1 минута ( "1" )
5-минутный ( "5" )
15-минутный ( "15" )
30-минутный ( "30" )
1 час ( "60" )
4-часовой ( "240" )
Ежедневно ( "Д" )
Основная логика
Расчет стохастического RSI :
Для каждого таймфрейма индикатор:
Вычисляет RSI с помощью ta.rsi(close, rsiLength) .
Применяет стохастическую формулу к RSI с ta.stoch(rsi, rsi, rsi, stochLength) для получения необработанного стохастического RSI.
Сглаживает результат с помощью ta.sma() для вычисления %K (используя smoothK ) и %D (используя smoothD ).
Это делается в функции stochRsiState , которая вызывается через request.security(), чтобы гарантировать соответствие расчетов данным каждого таймфрейма.
Обнаружение кроссовера :
Обнаруживает пересечения с помощью ta.crossover(k, d) (бычий) и ta.crossunder(k, d) (медвежий).
Поддерживает постоянное состояние ( var bool isBullish ) для каждого таймфрейма, обновляется только при возникновении пересечения:
истина (бычий тренд), когда %K пересекает %D снизу вверх .
ложно (медвежье), когда %K пересекает %D снизу .
Состояния с несколькими таймфреймами :
Состояние %K , %D и isBullish каждого таймфрейма извлекается независимо с помощью request.security() , что обеспечивает точное обнаружение пересечений независимо от таймфрейма графика.
Визуальные результаты
Стол :
Статическая таблица в нижнем левом углу отображает состояние каждого таймфрейма:
Столбцы: «1M», «5M», «15M», «30M», «1H», «4H», «1D».
Цвет фона: зеленый ( color.green ) для бычьего тренда, красный ( color.red ) для медвежьего тренда.
Обновления по последнему подтвержденному бару ( barstate.islast ).
Треугольники :
Зеленый восходящий треугольник под полосой, когда все включенные таймфреймы являются бычьими ( allBullish ).
Красный нисходящий треугольник над баром, когда все включенные таймфреймы медвежьи ( allBearish ).
Метки :
Метка «Длинная» (зеленая) под полосой, когда allBullish имеет значение true.
Метка «Короткая» (красная) под полосой, когда allBearish имеет значение true.
Отображается только на последнем подтвержденном историческом баре ( barstate.islastconfirmedhistory ).
Оповещения
Все таймфреймы бычьи : срабатывает, когда все включенные таймфреймы бычьи, с сообщением: «Все таймфреймы Stoch RSI бычьи (зеленые)!»
Все таймфреймы медвежьи : срабатывает, когда все включенные таймфреймы медвежьи, с сообщением: «Все таймфреймы Stoch RSI медвежьи (красные)!»
Условия для сигналов
Бычье состояние ( всеБычье ) :
Истинно, когда все включенные таймфреймы ( use1m ? isBullish1m : true и т. д.) являются бычьими и включен хотя бы один таймфрейм.
Медвежьи условия ( всемедвежьи ) :
Истинно, когда все включенные таймфреймы являются медвежьими и включен хотя бы один таймфрейм.
Отключенные таймфреймы рассматриваются в логике как нейтральные (всегда истинные ), что гарантирует, что они не блокируют сигналы.
Использование
Добавьте индикатор на свой график TradingView.
Отрегулируйте входные параметры (например, rsiLength , stochLength , smoothK , smoothD ) в соответствии с вашей торговой стратегией.
Включите/отключите таймфреймы с помощью настроек ввода, чтобы сосредоточиться на определенных из них.
Следите за таблицей для определения состояний отдельных таймфреймов и графиком для определения сигналов на вход («Длинный»/«Короткий»), когда все включенные таймфреймы совпадают.
Настройте оповещения, чтобы получать уведомления о полном выравнивании.
Примечания
Индикатор разработан таким образом, чтобы сохранять состояние пересечения до следующего пересечения, аналогично оригинальному скрипту на основе RSI, обеспечивая стабильность при переключении таймфреймов графика.
Для извлечения данных используется request.security() , что делает его надежным для многовременного анализа, хотя производительность может зависеть от доступности данных графика.
Journal Trade By TradeINskiThis indicator, "Journal Trade By TradeINski" (JT), is designed to assist traders in maintaining a comprehensive trade journal directly on their TradingView charts. It provides a customizable table overlay that displays key trade metrics for analysis and record-keeping purposes.
Key Features and Functionality:
Trade Journaling Table:
Displays user-inputted and calculated trade data in a structured table format.
Facilitates the recording of essential trade details, including entry price, stop-loss, position size, and risk parameters.
Risk Management Calculations:
Calculates and displays risk-related information, such as risk percentage, risk amount, and risk per share, to aid in risk management.
Calculates the dollar and percentage distance from entry to stop loss.
Position Sizing Assistance:
Calculates and displays position size as a percentage of account capital.
Displays the quantity of shares/units.
Calculates the quantity based on a half stop loss.
R-Multiple Visualization:
Calculates and displays R-multiples to assess risk-reward ratios.
Offers customizable color coding for R-multiples to visually represent different risk-reward levels.
Trade Management Tools:
Displays information to assist in part selling, and selling into strength strategies.
Displays part numbers, part quantities, and remainders.
User Customization:
Provides various customization options, including table position, size, and color, to suit individual preferences.
This indicator is intended to be a tool for traders to:
Maintain a detailed record of their trades.
Analyze trade performance.
Improve risk management practices.
Enhance trade planning and execution.
Open Interest and Liquidity [by Alpha_Precision_Charts]Indicator Description: Open Interest and Liquidity
Introduction:
The "Open Interest and Liquidity" indicator is an advanced tool designed for traders seeking to analyze aggregated Open Interest (OI) flow and liquidity in the cryptocurrency market, with a special focus on Bitcoin. It combines high-quality Open Interest data, a detailed liquidity table, and a visual longs vs shorts gauge, providing a comprehensive real-time view of market dynamics. Ideal for scalpers, swing traders, and volume analysts, this indicator is highly customizable and optimized for 1-minute charts, though it works across other timeframes as well.
Key Features:
Aggregated Open Interest and Delta: Leverages Binance data for accuracy, allowing traders to switch between displaying absolute OI or OI Delta, with value conversion to base currency or USD.
Liquidity Table: Displays the analyzed period, active liquidity, shorts, and longs with visual proportion bars, functioning for various cryptocurrencies as long as Open Interest data is available.
Longs vs Shorts Gauge: A semicircle visual that shows real-time market sentiment, adjustable for chart positioning, helping identify imbalances, optimized and exclusive for Bitcoin on 1-minute charts.
Utilities:
Sentiment Analysis: Quickly detect whether the market is accumulating positions (longs/shorts) or liquidating (OI exits).
Pivot Identification: Highlight key moments of high buying or selling pressure, ideal for trade entries or exits.
Liquidity Monitoring: The table and gauge provide a clear view of active liquidity, helping assess a move’s strength.
Scalping and Day Trading: Perfect for short-term traders operating on 1-minute charts, offering fast and precise visual insights.
How to Use:
Initial Setup: Choose between "Open Interest" (candles) or "Open Interest Delta" (columns) in the "Display" field. The indicator defaults to Binance data for enhanced accuracy.
Customization: Enable/disable the table and gauge as needed and position them on the chart.
Interpretation: Combine OI Delta and gauge data with price movement to anticipate breakouts or reversals.
Technical Notes
The indicator uses a 500-period VWMA to calculate significant OI Delta thresholds and is optimized for Bitcoin (BTCUSDT.P) on high-liquidity charts.
Disclaimer
This indicator relies on the availability of Open Interest data on TradingView. For best results, use on Bitcoin charts with high liquidity, such as BTCUSDT.P. Accuracy may vary with lower-volume assets or exchanges.
Quarterly Theory ICT 01 [TradingFinder] XAMD + Q1-Q4 Sessions🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system based on the concepts of ICT (Inner Circle Trader) and fractal time. It divides time into quarterly periods and accurately determines entry and exit points for trades by using the True Open as the starting point of each cycle. This system is applicable across various time frames including annual, monthly, weekly, daily, and even 90-minute sessions.
Time is divided into four quarters: in the first quarter (Q1), which is dedicated to the Accumulation phase, the market is in a consolidation state, laying the groundwork for a new trend; in the second quarter (Q2), allocated to the Manipulation phase (also known as Judas Swing), sudden price changes and false moves occur, marking the true starting point of a trend change; the third quarter (Q3) is dedicated to the Distribution phase, during which prices are broadly distributed and price volatility peaks; and the fourth quarter (Q4), corresponding to the Continuation/Reversal phase, either continues or reverses the previous trend.
By leveraging smart algorithms and technical analysis, this system identifies optimal price patterns and trading positions through the precise detection of stop-run and liquidity zones.
With the division of time into Q1 through Q4 and by incorporating key terms such as Quarterly Theory ICT, True Open, Accumulation, Manipulation (Judas Swing), Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, this system enables traders to identify market trends and make informed trading decisions using real data and precise analysis.
♦ Important Note :
This indicator and the "Quarterly Theory ICT" concept have been developed based on material published in primary sources, notably the articles on Daye( traderdaye ) and Joshuuu . All copyright rights are reserved.
🔵 How to Use
The Quarterly Theory ICT strategy is built on dividing time into four distinct periods across various time frames such as annual, monthly, weekly, daily, and even 90-minute sessions. In this approach, time is segmented into four quarters, during which the phases of Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal appear in a systematic and recurring manner.
The first segment (Q1) functions as the Accumulation phase, where the market consolidates and lays the foundation for future movement; the second segment (Q2) represents the Manipulation phase, during which prices experience sudden initial changes, and with the aid of the True Open concept, the real starting point of the market’s movement is determined; in the third segment (Q3), the Distribution phase takes place, where prices are widely dispersed and price volatility reaches its peak; and finally, the fourth segment (Q4) is recognized as the Continuation/Reversal phase, in which the previous trend either continues or reverses.
This strategy, by harnessing the concepts of fractal time and smart algorithms, enables precise analysis of price patterns across multiple time frames and, through the identification of key points such as stop-run and liquidity zones, assists traders in optimizing their trading positions. Utilizing real market data and dividing time into Q1 through Q4 allows for a comprehensive and multi-level technical analysis in which optimal entry and exit points are identified by comparing prices to the True Open.
Thus, by focusing on keywords like Quarterly Theory ICT, True Open, Accumulation, Manipulation, Distribution, Continuation/Reversal, ICT, fractal time, smart algorithms, technical analysis, price patterns, trading positions, stop-run, and liquidity, the Quarterly Theory ICT strategy acts as a coherent framework for predicting market trends and developing trading strategies.
🔵b]Settings
Cycle Display Mode: Determines whether the cycle is displayed on the chart or on the indicator panel.
Show Cycle: Enables or disables the display of the ranges corresponding to each quarter within the micro cycles (e.g., Q1/1, Q1/2, Q1/3, Q1/4, etc.).
Show Cycle Label: Toggles the display of textual labels for identifying the micro cycle phases (for example, Q1/1 or Q2/2).
Table Display Mode: Enables or disables the ability to display cycle information in a tabular format.
Show Table: Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info: Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
Quarterly Theory ICT provides a fractal and recurring approach to analyzing price behavior by dividing time into four quarters (Q1, Q2, Q3, and Q4) and defining the True Open at the beginning of the second phase.
The Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal phases repeat in each cycle, allowing traders to identify price patterns with greater precision across annual, monthly, weekly, daily, and even micro-level time frames.
Focusing on the True Open as the primary reference point enables faster recognition of potential trend changes and facilitates optimal management of trading positions. In summary, this strategy, based on ICT principles and fractal time concepts, offers a powerful framework for predicting future market movements, identifying optimal entry and exit points, and managing risk in various trading conditions.
DCSessionStatsOHLC_v1.0DCSessionStatsOHLC_v1.0
© dc_77 | Pine Script™ v6 | Licensed under Mozilla Public License 2.0
This indicator overlays customizable session-based OHLC (Open, High, Low, Close) statistics on your TradingView chart. It tracks price action within user-defined sessions, calculates average manipulation and distribution levels based on historical data, and visually projects these levels with lines and labels. Additionally, it provides a session count table to monitor bullish and bearish sessions.
Key Features:
Session Customization: Define session time (e.g., "0000-1600") and time zone (e.g., UTC, America/New_York). Analyze up to 20 historical sessions.
Anchor Line: Displays a vertical line at session start with customizable style, color, and optional label.
Session Open Line: Plots a horizontal line at the session’s opening price with adjustable appearance and label.
Manipulation Levels: Calculates and projects average price extensions (high/low relative to open) for manipulative moves, shown as horizontal lines with labels.
Distribution Levels: Displays average price ranges (high/low beyond open) for distribution phases, with customizable lines and labels.
Visual Flexibility: Adjust line styles (solid, dashed, dotted), colors, widths, label sizes, and projection offsets (bars beyond session start).
Session Stats Table: Optional table showing counts of bullish (close > open) and bearish (close < open) sessions, with configurable position and size.
How It Works:
Tracks OHLC data within each session and identifies session start/end based on the specified time range.
Computes averages for manipulation (e.g., low below open in bullish sessions) and distribution (e.g., high above open) levels from past sessions.
Projects these levels forward as horizontal lines, extending them by a user-defined offset for easy reference.
Updates a table with real-time bullish/bearish session counts.
Use Case:
Ideal for traders analyzing intraday or custom session behavior, identifying key price levels, and gauging market sentiment over time.
Toggle individual elements on/off and fine-tune visuals to suit your trading style.
Retrograde Periods (Multi-Planet)**Retrograde Periods (Multi-Planet) Indicator**
This TradingView script overlays your chart with a dynamic visualization of planetary retrograde periods. Built in Pine Script v6, it computes and displays the retrograde status of eight planets—Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto—using hard-coded retrograde intervals from 2009 to 2026.
**Key Features:**
- Dynamic Background Coloring:
The indicator changes the chart’s background color based on the current retrograde status of the planets. The colors follow a priority order (Mercury > Venus > Mars > Jupiter > Saturn > Uranus > Neptune > Pluto) so that if multiple planets are retrograde simultaneously, the highest-priority planet’s color is displayed.
- Interactive Planet Selection:
User-friendly checkboxes allow you to choose which planets to list in the table’s “Selected” row. Note that while these checkboxes control the display of the planet names in the table, the retrograde calculations remain independent of these selections.
- Real-Time Retrograde Status Table:
A table in the top-right corner displays each planet’s retrograde status in real time. “Yes” is shown in red for a planet in retrograde and “No” in green when it isn’t. This offers an at-a-glance view of the cosmic conditions influencing your charts.
- Astrological & Astronomical Insights:
Whether you’re into sidereal astrology or simply fascinated by celestial mechanics, this script lets you visualize those retrograde cycles. In astrology, retrograde periods are often seen as times for reflection and re-evaluation, while in astronomy they reflect the natural orbital motions seen from our perspective on Earth.
Enhance your trading setup by integrating cosmic cycles into your technical analysis. Happy trading and cosmic exploring!
Display MB on BarsDescription
The "Display MB on Bars" Pine Script indicator is designed to visually represent Market Breadth values and R4.5 scores on trading charts. This script enables traders to highlight and analyze key market behavior using pre-defined thresholds for MB scores and dynamically calculated R4.5 values. Additionally, it includes a moving average status table to assess price levels relative to the 10-day and 20-day moving averages.
Features:
1. COB Date Matching: Displays data corresponding to specific "COB dates" provided by the user.
2. MB Value Visualization:
o Highlights bars with a background color based on MB values:
Red if MB ≤ MB_Red (default: -1).
Green if MB ≥ MB_Green (default: 3).
3. R4.5 Scores Display:
o Creates a label on the chart with the MB and R4.5 values when conditions are met (e.g., R4.5 > 200 or specific MB thresholds).
4. Index Moving Average Comparison:
o Calculates 10-day and 20-day moving averages for the selected symbol (default: NSE:NIFTYMIDSML400).
o Shows the price position relative to these moving averages in a table.
How to Use:
1. Configure Inputs:
o COB Dates: Enter a comma-separated list of dates in the format DD-MM-YYYY.
o MB Values: Provide the corresponding MB scores for the COB dates.
o R4.5 Values: Provide the R4.5 scores for the COB dates.
o Set the thresholds for MB values (MB Red<= and MB Green>=).
o Toggle features like MB, RS (R4.5), and the moving average status table.
2. Interpret the Output:
o Observe background colors on the bars:
Red: Indicates MB is less than or equal to the lower threshold.
Green: Indicates MB exceeds the upper threshold.
o Check labels above bars for R4.5 and MB values when conditions are met.
o Refer to the status table on the top-right corner to understand price positions relative to 10-day and 20-day moving averages.
This script is especially useful for traders seeking insights into custom metrics like MB and R4.5, enabling quick identification of key patterns and trends in the market.
MTF Fractal Bias Confluence DetectorMTF Fractal Bias Confluence Detector
This indicator, the MTF Fractal Bias Confluence Detector, is based on the idea that the market exhibits fractal behaviour. The origin of the idea traces back to 1963, when Benoit Mandelbrot analyzed the fluctuations in cotton prices over a time series starting in 1900, discovering that price changes exhibited scale-invariant patterns. This means that the curve representing daily price changes mirrored the shape of monthly price changes, highlighting the fractal nature of market behaviour. When applied to swing points across multiple timeframes (MTF), this concept suggests that swing points demonstrate similar patterns regardless of the timeframe being analyzed. These self-similar fractal structures provide traders with insights into market reversals and trends, making them a powerful tool for multi-timeframe analysis.
A Swing Point is made up of three main parts: a move away from the last Break level; forming a peak (pivot point) with a Fakeout of the peak (explained through an example later); and a subsequent move away from it. These swing points recur across all timeframes as part of cyclical momentum patterns, meaning each swing point gives rise to a new cycle of market movement. Due to the fractal nature of the market, larger cycles encompass multiple smaller ones.
The theory behind the Fractal Bias Confluence Detector utilizes the idea that the market movements are fractal in nature and illustrates how such swing points can be identified across MTFs. To do so, we examine the Peak Fakeouts within these cycles, as they form. It is not possible to know in advance how long each of these moves will last, but a Swing Point will often occur with a Peak Fakeout. Therefore, the most critical element is to identify the Peak Fakeout.
The snapshot below captures a Peak Fakeout, as discussed earlier.
Similarly, the following snapshot shows various possible breakdowns of Higher Time Frame (HTF) cycles into smaller Lower Time Frame (LTF) movements. The chart contains a white table(not part of the indicator and shown for illustration purposes only).
To further illustrate. Consider the combination of Time Frames (TF) from the 2nd row (from the above snapshot). Cycle TF (1M), Setup TF (1W), Momentum TF (1D) etc.
Price movements in the 1M TF highlight the direction in which HTF traders are pushing the market. Often, when markets have broken out of a level, they tend to form a peak and can then pull back towards the prior breakout level. Once the pullback is beyond the last breakout level, in the opposite direction, we may say the peak formation is created, and directional bias has changed. This is also called Peak Fakeout. Due to the fractal nature of the market, Swing Points on the HTF will often constitute multiple Swing Points on the LTF, though they are not always in sync. However, after such peak formation, there is a high probability that the price might move away from the peak for at least 1 candle (in the cycle TF). This theory illustrates that once a new cycle is in play, we can then look at 1W (Setup TF) to look for possible in-sync movements, at least within that 1 candle of the HTF. Repeating the same for further lower TFs, we may arrive at a confluence of Fractal Bias and see how the movements in LTF are driven by the HTF momentum.
Another example within the chart:
Note: The above examples are just for illustration purposes, and other permutations and combinations of movements across multiple TFs are also possible.
This indicator aims to help users identify such fractal-bias-confluences, so that they can leverage the fractal nature of the market to get a holistic view. To do so, the indicator displays how the market has moved across multiple time frames, with respect to different historical levels.
Features:
1. The bias summary table
The following snapshot depicts the bias summary table at the bottom right of the chart.
1.1. Workings: The table will display, for various TFs, in the first four (starting from "current" to Prev ) rows, one of the following.
"F/H" , " Acronym for the failed break of the previous high",
"F/L" , " Acronym for the failed break of the previous low",
"B/H" , " Acronym for the break of the previous high",
"B/L" , " Acronym for the break of the previous low",
"IN" , " Acronym for an inside candle (never broke high or low of perv candle)",
"OT" , " Acronym for an outside candle (broke both high and low of previous candle and closing price is in between previous high and low)".
Note: these acronyms are customizable according to the user's choice of terminology in any language, as shown in the snapshot below.
1.1.1 In the above snapshot, the 1st row, called "Current", shows how the current candle is evolving with respect to the previous one. The "previous" row shows how the previous candle closed with respect to the pre-previous one. The next two rows represent the bias of the pre-previous and pre-pre-previous in a similar manner. By default, the bias is updated in real-time, even for the already closed historical candles. For example, if the previous 4H candle closed as a B/H and the current price then comes below the pre-previous 4H candle high, then the bias of the previous candle will get updated to F/H. This informs the user that the break above the pre-previous high has failed. However, the user has the option to turn this off. The information in these four rows shows the user how the market is moving currently and how it evolved before reaching the current price levels.
Note: The calculation done by the indicator is to keep track of how the price is moving with respect to the last candle levels in real-time. This means if the price first goes above the previous high and then goes below the previous low, the indicator is equipped to display what happened in the most recent time. The snapshot below shows the option to turn on/off such updates in the bias summary table.
Note: While the bias summary table is turned on, the user also has the option to turn off Prev and Prev rows, as shown in the snapshot below.
1.1.2 The 2nd to last row, called CL/CS(Consecutive Long/Short), shows whether consecutive (2+) breaks of high/low happened or not in one direction without taking out the previous candle's range in the opposite direction. When conditions are met, it will show the number of times the price has been pushed in one direction (in the above manner), followed by "L" for long and "S" for short, for each TF, for example, "4L". It gets updated in real-time for each push in the same direction. Furthermore, a good analogy of "4L" on an HTF is 4 consecutive Break of Structure (BOS) (in the same direction) on LTF, without a Change of Character (CHoCH). Another example would be Stacey Burke's 3 consecutive rises that can be mapped in the indicator, if the conditions are met for "3L" for a given TF.
1.1.3 The last row, FRC/FGC, stands for the first red/green candle. It shows whether the last candle of a TF has closed as green (i.e., close>open) after posting two red candles (i.e., close
Multi Indicator SummaryPurpose: It calculates and displays bullish and bearish order blocks, key levels derived from recent price movements, which traders use to identify potential support and resistance areas.
Inputs: Users can customize the order block length, defining the range of price data used for calculations.
Logic: The script uses ta.lowest and ta.highest functions to compute order blocks based on specified periods for bullish and bearish trends.
Additional Levels: It identifies extra order blocks (bullish_below and bearish_above) to provide more context for deeper support or higher resistance.
Price Table: A visual table is created on the chart, showing the current price, bullish and bearish order blocks, and additional bearish levels above the current price.
Alerts: Alerts are triggered when the price crosses key order block levels, helping traders react to significant price movements.
Flexibility: The table dynamically updates based on the chart’s ticker and timeframe, ensuring it always reflects the latest data.
Bearish Above Price: Highlights the most recent bearish order block above the current price to inform traders about potential resistance areas.
Visualization: The clear table format aids quick decision-making by summarizing key levels in an accessible way.
Usability: This script is especially useful for intraday and swing traders seeking to integrate order block analysis into their strategies.
Index Trend MapThe Index Trend Map is a versatile and powerful tool designed to provide a sentiment heatmap for major market indices. This indicator tracks the average trend direction across multiple indices data points, including a default setting for S&P 500 Futures ( NYSE:ES ), Nasdaq 100 Futures ( SEED_ALEXDRAYM_SHORTINTEREST2:NQ ), Dow Jones Futures ( SEED_CRYPTOSLATE_VANTAGEPOINT:YM ), Russell 2000 Futures ( CAPITALCOM:RTY ) and traditionally inverse data points like the VIX– allowing traders to quickly assess overall market sentiment and make more informed trading decisions.
Key Features:
Sentiment Heatmap: Displays a color-coded heatmap for indices, with green indicating bullish sentiment and red indicating bearish sentiment. Each index’s sentiment is calculated on a scale from 0 to 100, with 50 as the neutral point.
Bullish/Bearish Percentages: Real-time calculations of the percentage of indices in bullish or bearish territory are displayed in a dynamic table for easy reference.
Tracks Major Indices: Monitors popular indices or their related futures contracts with the option to include custom tickers.
Inverse Sentiment Options: Allows users to invert sentiment calculations for specific symbols (e.g., VIX or DXY) to reflect their inverse relationship to broader market trends.
Customizable Moving Averages: Choose from SMA, EMA, WMA, or DEMA to tailor the trend calculation to your trading strategy.
Overlay Sentiment Colors on Candles: Option to display sentiment as green (bullish) or red (bearish) directly on price chart candles, enhancing market trend visibility.
Heatmap Visualization:
The heatmap assigns each index a sentiment score based on its calculated average.
Sentiment values above the 50 midline indicate bullish sentiment, while those below 50 indicate bearish sentiment.
Dynamic Table:
Located in the bottom right corner, this table displays real-time percentages of indices that are bullish and bearish. Example: If 4 out of 6 index data points are bullish, the table will show 66.6% bullish and 33.3% bearish.
Best Used For:
Intraday Traders: Assess real-time index sentiment during active market hours to make data-driven trading decisions.
Swing Traders: Monitor index trends over time to identify shifts in market sentiment and positioning opportunities.
Market Breadth Analysis: Identify broader market strength or weakness by analyzing multiple indices simultaneously.
Employee Portfolio Generator [By MUQWISHI]▋ INTRODUCTION :
The “Employee Portfolio Generator” simplifies the process of building a long-term investment portfolio tailored for employees seeking to build wealth through investments rather than traditional bank savings. The tool empowers employees to set up recurring deposits at customizable intervals, enabling to make additional purchases in a list of preferred holdings, with the ability to define the purchasing investment weight for each security. The tool serves as a comprehensive solution for tracking portfolio performance, conducting research, and analyzing specific aspects of portfolio investments. The output includes an index value, a table of holdings, and chart plots, providing a deeper understanding of the portfolio's historical movements.
_______________________
▋ OVERVIEW:
● Scenario (The chart above can be taken as an example) :
Let say, in 2010, a newly employed individual committed to saving $1,000 each month. Rather than relying on a traditional savings account, chose to invest the majority of monthly savings in stable well-established stocks. Allocating 30% of monthly saving to AMEX:SPY and another 30% to NASDAQ:QQQ , recognizing these as reliable options for steady growth. Additionally, there was an admired toward innovative business models of NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:AMZN , and NASDAQ:EBAY , leading to invest 10% in each of those companies. By the end of 2024, after 15 years, the total monthly deposits amounted to $179,000, which would have been the result of traditional saving alone. However, by sticking into long term invest, the value of the portfolio assets grew, reaching nearly $900,000.
_______________________
▋ OUTPUTS:
The table can be displayed in three formats:
1. Portfolio Index Title: displays the index name at the top, and at the bottom, it shows the index value, along with the chart timeframe, e.g., daily change in points and percentage.
2. Specifications: displays the essential information on portfolio performance, including the investment date range, total deposits, free cash, returns, and assets.
3. Holdings: a list of the holding securities inside a table that contains the ticker, last price, entry price, return percentage of the portfolio's total deposits, and latest weighted percentage of the portfolio. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
4. Indication of New Deposit: An indication of a new deposit added to the portfolio for additional purchasing.
5. Chart: The portfolio's historical movements can be visualized in a plot, displayed as a bar chart, candlestick chart, or line chart, depending on the preferred format, as shown below.
_______________________
▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Naming the index.
(2) Table location on the chart and cell size.
(3) Sorting Holdings Table. By securities’ {Return(%) Portfolio, Weight(%) Portfolio, or Ticker Alphabetical} order.
(4) Choose the type of index: {Assets, Return, or Return (%)}, and the plot type for the portfolio index: {Candle, Bar, or Line}.
(5) Positive/Negative colors.
(6) Table Colors (Title, Cell, and Text).
(7) To show/hide any of selected indicator’s components.
Section(2): Recurring Deposit Settings
(1) From DateTime of starting the investment.
(2) To DateTime of ending the investment
(3) The amount of recurring deposit into portfolio and currency.
(4) The frequency of recurring deposits into the portfolio {Weekly, 2-Weeks, Monthly, Quarterly, Yearly}
(5) The Depositing Model:
● Fixed: The amount for recurring deposits remains constant throughout the entire investment period.
● Increased %: The recurring deposit amount increases at the selected frequency and percentage throughout the entire investment period.
(5B) If the user selects “ Depositing Model: Increased % ”, specify the growth model (linear or exponential) and define the rate of increase.
Section(3): Portfolio Holdings
(1) Enable a ticker in the investment portfolio.
(2) The selected deposit frequency weight for a ticker. For example, if the monthly deposit is $1,000 and the selected weight for XYZ stock is 30%, $300 will be used to purchase shares of XYZ stock.
(3) Select up to 6 tickers that the investor is interested in for long-term investment.
Please let me know if you have any questions
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
DTS- Dynamic Trend SignalDynamic Trend Signal
The Dynamic Trend Signal indicator is a powerful and highly customizable tool designed for traders who want clear and actionable signals to guide their trading decisions. This indicator leverages the relationship between two moving averages and the current price to provide concise buy/sell recommendations while visually enhancing your chart with professional-grade features.
Key Features:
Actionable Trading Signals:
STRONG BUY / NO SELL: When the price is above both moving averages.
BUY / NO SELL: When the price is above the longer moving average but below the shorter moving average.
NO BUY / SELL: When the price is below the longer moving average but above the shorter moving average.
STRONG SELL / NO BUY: When the price is below both moving averages.
Dynamic Signal Table:
Displays real-time trading signals in a convenient table format.
Automatically updates based on market conditions.
Customizable table position (top-left, top-right, bottom-left, or bottom-right).
Dynamic background and text colors for improved visibility:
Green shades for bullish signals.
Red shades for bearish signals.
Customizable Moving Averages:
Configure each moving average independently:
Choose between Simple Moving Average (SMA) and Exponential Moving Average (EMA).
Set unique lengths, colors, and line thickness for each average.
Default settings:
MA1: Short-term (8-period) with thickness 1.
MA2: Long-term (20-period) with thickness 2.
Optional Crossover Alerts:
Visual and textual alerts for moving average crossovers:
BUY: When the shorter moving average crosses above the longer moving average.
SELL: When the shorter moving average crosses below the longer moving average.
Crossover alerts are disabled by default but can be easily enabled in settings.
Ease of Use:
Intuitive interface with clean and professional visuals.
Fully customizable to fit any trading strategy or chart style.
How It Helps Traders:
The Dynamic Trend Signal simplifies market analysis by removing guesswork and focusing on clear, data-driven signals. Whether you're a beginner looking for straightforward guidance or an experienced trader seeking to enhance your strategy, this indicator provides:
Confidence in decision-making with clear buy/sell signals.
Customization to align with your unique trading approach.
Clarity through visually appealing, color-coded signals and alerts.
Ideal For:
Swing Traders
Day Traders
Trend Followers
Traders looking to integrate a dynamic, rule-based approach to their analysis.
How to Use:
Add the Dynamic Trend Signal indicator to your chart.
Adjust the moving average lengths, types, colors, and thickness to suit your trading strategy.
Monitor the signal table for actionable recommendations.
Optionally enable crossover alerts for real-time buy/sell notifications.
Unlock the power of clear and actionable trading signals with the Dynamic Trend Signal! Add it to your TradingView chart today and take your trading strategy to the next level.
