Muzyorae - ICT Quarter Cycle (Once)ICT Quarterly Theory — 06:00 to 12:00 (NY) Micro-Quarters
This tool focuses on the 06:00–12:00 New York time window and subdivides it into four equal “micro-quarters,” each 90 minutes long. In many ICT layouts this block is treated as a single higher-level quarter; here we break it into a finer structure to help you frame intraday narratives, liquidity runs, and session shifts with consistent time anchors.
How it’s partitioned
q1: 06:00 → 07:30 (NY)
q2: 07:30 → 09:00 (NY)
q3: 09:00 → 10:30 (NY)
q4: 10:30 → 12:00 (NY)
Each boundary is plotted at the exact start time, so you can see where one 90-minute cycle ends and the next begins. Labels can be placed above or below price, and colors/styles are configurable to match your chart.
Why it’s useful
Provides fixed time scaffolding for building AM session bias, execution windows, and narrative transitions.
Helps distinguish pre-cash open, cash open, and late-AM distribution/accumulation phases without guessing.
Standardizes replay and journaling: the same 90-minute checkpoints every day.
Key features
NY-time anchored (handles DST automatically through TradingView’s exchange time).
Four precise 90-minute segments inside the 06:00–12:00 block.
Customizable line styles, colors, and label placement (above/below).
Optional visibility controls to keep charts clean.
Note: Some ICT mappings name the 06:00–12:00 block differently (e.g., Q2 vs. Q3). This indicator uses the same time bounds regardless of the label you prefer; you can rename the macro label in settings if desired.
Disclaimer: Time framing does not guarantee outcomes. Use alongside your own analysis, risk management, and execution plan.
Ciclos
Muzyorae - ICT Quarterly Theory (Intraday)ICT Quarterly Theory — Intraday
What it is
ICT’s Quarterly Theory models the intraday session as repeating cycles of four “quarters.” On NY time, a trading day is split into four macro quarters of 6 hours each:
Q1: 00:00–06:00 NY (Asia / pre-London)
Q2: 06:00–12:00 NY (London–NY overlap, AM session)
Q3: 12:00–18:00 NY (Midday / PM session)
Q4: 18:00–24:00 NY (Asia re-open / late session)
Each macro quarter can be further subdivided into micro quarters of 90 minutes (q1–q4). This fractal view helps traders frame accumulation → expansion → distribution → liquidation phases and align executions with time-of-day liquidity.
Why it matters
Orderflow, liquidity raids, and displacement are highly time-dependent. Marking the quarters makes it easier to:
Anticipate when the market is likely to deliver the day’s expansion (often Q2) versus retracement/distribution (often Q3) or late liquidity runs (often Q4).
Compare today’s behavior to prior days within the same quarter windows.
Anchor bias, entries, and risk management to session-specific highs/lows rather than arbitrary clock times.
What this indicator shows
Macro quarters (6h): Vertical lines and optional labels (Q1–Q4) on NY time.
Micro quarters (90m): Optional finer verticals inside each macro quarter (q1–q4) for precise timing.
True Open (Q2 AM): Optional line at the AM session’s true open (default 06:00 NY) to study premium/discount development from the intraday benchmark.
Futures Sunday handling: Optional treatment of Sunday 18:00 NY as Q4 (useful for FX/futures).
Label controls: Choose above/below placement, offset, size, and colors; micro labels can be toggled independently.
Performance-friendly: De-duplicated labels and a look-back “days to show” setting keep charts clean.
How to use
Timeframe: Works on intraday charts (1–60m). 5–15m is a common balance of signal vs. noise.
Bias framing:
Map Asia (Q1), AM expansion (Q2), midday distribution (Q3), late session runs (Q4).
Compare where the daily range forms versus the True Open to gauge premium/discount and likely continuations.
Execution: Look for standard ICT tools (liquidity sweeps, FVGs, displacement, PD arrays) inside the active quarter to avoid fighting time-of-day flow.
Review: Scroll back multiple days and evaluate where the day’s high/low typically forms relative to Q2–Q3; adapt expectations.
Settings (high level)
Show Macro Labels / Micro Lines / Micro Labels
Label position (above/below), X-shift, colors, sizes
Days to show, de-dup window (prevents label overlaps)
Q2 True Open toggle and extension (doesn't work)
Include Sunday as Q4 (18:00 NY)
Notes
Quarter boundaries are fixed to America/New York session logic to match ICT timing.
This is a context tool; it does not generate buy/sell signals. Combine with your existing execution model.
Past behavior does not guarantee future results. Use proper risk management.
National - Daily Kill Zone LinesDaily Kill Zone Lines
This indicator helps traders mark and visualize their daily "kill zone" with precision.
Plots two vertical lines at your chosen session start and end time.
Adjustable line color, style (solid/dashed/dotted), and width.
Optional shading between the lines for easy zone tracking.
Works on intraday charts and automatically updates for each new day.
Ideal for session-based trading strategies such as London open, New York open, or any custom time window you rely on.
Ultimate Fundamental FortressScript Overview
This script provides a comprehensive Fundamental Health Scorecard for stocks, calculating a normalized score out of 100 based on key financial metrics fetched from TradingView's fundamental data. It displays the results in an elegant table with customizable colors, a dynamic plot for visualization, and a scorecard label for quick insights. The scorecard helps users assess a stock's value, profitability, and financial strength at a glance.
Purpose
The primary goal is to simplify fundamental analysis by aggregating essential ratios into a single, easy-to-interpret score. Inspired by value investing principles (e.g., low P/E and P/B for undervalued stocks, high ROE for efficiency), it empowers traders and investors to identify strong fundamentals quickly. It's especially useful for screening undervalued opportunities or comparing stocks within sectors.
Principles
Metrics Selection: Focuses on core fundamentals: Price-to-Book (P/B), Price-to-Earnings (P/E), Return on Equity (ROE), Debt-to-Equity (D/E), Free Cash Flow (FCF normalized by market cap), EBITDA (normalized by market cap), and Net Profit Margin. These are chosen for their balance of valuation, profitability, and risk assessment.
Scoring Philosophy: Each metric is scored based on thresholds (e.g., low ratios for valuation metrics indicate better value). If manual sector averages are provided, scoring becomes relative (e.g., stock P/B below sector average gets higher points), reducing subjectivity and adapting to industry norms. Without averages, absolute thresholds apply.
Normalization: Scores are summed and scaled to 100, ignoring missing data to ensure robustness. This allows fair comparison across stocks with varying data availability.
Customization: Users can adjust thresholds, colors, and sector averages for personalized analysis, making it flexible for different markets or strategies.
Calculation Methodology
Data Fetching: Uses request.financial() to pull quarterly (FQ) or trailing twelve months (TTM) data for metrics like BVPS, EPS, ROE, etc.
Ratio Computations:
P/B = Close Price / BVPS
P/E = Close Price / EPS
ROE = Directly fetched
D/E = Total Liabilities / Equity
Net Margin = Net Income / Revenue
Normalized FCF = FCF / Market Cap (as percentage)
Normalized EBITDA = EBITDA / Market Cap (as percentage)
Scoring:
For each metric, compare to thresholds or relative to sector averages (if provided >0).
Example for P/B: If relative (sector avg >0), stock P/B < avg * high factor → 15 pts; < avg * med factor → 10 pts; etc.
For ROE/Net Margin (higher is better): Reverse logic (stock > avg / factor).
FCF/EBITDA: Always absolute (normalized thresholds).
Minimum score per metric: 2-5 pts if poor.
Total Score: Sum valid scores, divide by max possible for those metrics, multiply by 100.
Output: Table shows components, values, scores, and sector avgs.
Plot visualizes score with color-coding.
Label categorizes (e.g., "Buffett Approved" for 85+).
User Inputs and Benefits
Thresholds (Absolute/Relative Factors): Customize scoring rules (e.g., change P/E low threshold from 10 to 12).
Benefit: Adapt to personal strategy or market conditions – e.g., stricter for growth stocks.
Manual Sector Averages: Enter averages (e.g., sector P/B = 2.5).
Benefit: Makes scoring industry-specific, reducing bias (e.g., tech's high P/E normal, banking's low ROE risky). If not entered (≤0), falls back to absolute for simplicity.
Color Customizations: Adjust table colors (header, scores).
Benefit: Personalize visuals for dark/light themes, improving readability and user experience.
Normalized FCF/EBITDA Thresholds: Set as % of market cap. Benefit: Size-independent comparison – small caps won't be disadvantaged.
Usage Notes Add to chart via Indicators menu.
Data relies on TradingView fundamentals – may be limited for some exchanges (e.g., BIST, international). Use manual averages for accuracy.
For screener: High request count (10) may exceed limits; use reduced version if needed.
Not financial advice – always verify with external sources.
Feedback welcome – let's improve together!
HTFAnother HTF script, also super simple, also integrating fibs.
Uses 4W as opposed to Monthly bars to show a non-Roman Overlord perspective.
Option to add notes in the top right if that's your fancy.
Elliott Wave / NeoWave Rule Engine – v6.9This script functions as a "rule engine" that automatically identifies significant price swings and then tests them against a comprehensive set of Elliott Wave rules and guidelines.
The goal is to filter out low-probability setups and identify valid motive (impulse and diagonal) waves by applying user-defined tolerances. The script plots swings on the chart and can display a real-time dashboard that shows which rules are passing or failing. When a valid motive wave is detected, it can generate buy or sell signals.
User Settings
The script's behavior is controlled by a set of user inputs, organized into four main groups.
Swing / ZigZag Detection
These settings control how the script identifies the price swings that form the basis of the wave patterns.
Pivot Left Bars & Pivot Right Bars: These two values determine the sensitivity of the swing detection. A pivot point (a high or low) is only identified if it is the highest or lowest price within the specified number of bars to its left and right. Increasing these numbers will result in fewer, larger swings.
Minimum swing % (filter micro noise): This is a crucial filter. It ignores swings that are too small to be considered significant, helping to clean up the chart and prevent the engine from analyzing "noise." For example, a value of 0.3 means any swing that is less than 0.3% of the price range will be ignored.
Rule Engine Tolerances
This group allows you to define how strict the validation rules are.
Fibonacci tolerance (±%): This sets the acceptable margin of error for Fibonacci relationships (e.g., a 0.618 retracement). A value of 0.001 means a retracement between 0.617 and 0.619 will be considered a valid match.
Same-degree TIME proportion max (x): This sets the maximum time difference allowed between waves of the same degree (e.g., Wave 1 and Wave 3) to still be considered "proportional." A value of 1 means Wave 3's duration can be up to 1 time longer than Wave 1's duration, and vice-versa.
Same-degree PRICE proportion max (x): Similar to the time tolerance, this sets the maximum price difference allowed between waves of the same degree to still be considered proportional.
Alternation slope ratio threshold: This is a key NeoWave guideline. It checks if Wave 2 and Wave 4 have different "sharpness" (price change per bar). A higher value makes the alternation rule stricter.
Min guideline passes for motive validation (0–7): This is the gating feature. Even if a pattern passes all the hard Elliott Wave rules (e.g., no overlap, Wave 3 isn't the shortest), you can still require it to pass a minimum number of guidelines (like Fibonacci relationships, alternation, etc.) before a signal is generated. A value of 7 means every guideline must be met.
Momentum / Volume Guidelines
These are additional checks for pattern validation.
Momentum length: This setting controls a proxy for momentum, which is calculated based on the speed of price movement.
Use volume checks: This is a placeholder for future functionality. It does not currently affect the script's behavior.
UI / Debug
These settings control the visual aspects of the script on your chart.
Max swings to keep/evaluate: This determines how far back the script looks to find and analyze swings. A larger number will analyze more historical patterns but may impact performance.
Show detected labels: Toggles the display of numerical (1-2-3-4-5) and letter (A-B-C) labels on the detected waves.
Show rule PASS/FAIL dashboard: Toggles the on-chart table that provides a detailed breakdown of which rules and guidelines are met.
Table Position: Controls where the rule dashboard is located on your chart.
Print debug info to Data Window: If you are a developer or want to see the underlying data, this will print information to TradingView's Data Window.
Show Buy/Sell Signals: Toggles the display of Buy/Sell signals. These signals are only generated when a pattern passes all the hard rules and your minimum guideline pass requirement.
3*n 1.0IPDA Range display
ICT Hidden levels
give you special levels to trade from.
Supper support and resistance levels
BTC Power-Law Decay Channel Oscillator (0–100)🟠 BTC Power-Law Decay Channel Oscillator (0–100)
This indicator calculates Bitcoin’s position inside its long-term power-law decay channel and normalizes it into an easy-to-read 0–100 oscillator.
🔎 Concept
Bitcoin’s long-term price trajectory can be modeled by a log-log power-law channel.
A baseline is fitted, then an upper band (excess/euphoria) and a lower band (capitulation/fear).
The oscillator shows where the current price sits between those bands:
0 = near the lower band (historical bottoms)
100 = near the upper band (historical tops)
📊 How to Read
Oscillator > 80 → euphoric excess, often cycle tops
Oscillator < 20 → capitulation, often cycle bottoms
Works best on weekly or bi-weekly timeframes.
⚙️ Adjustable Parameters
Anchor date: starting point for the power-law fit (default: 2011).
Smoothing days: moving average applied to log-price (default: 365 days).
Upper / Lower multipliers: scale the bands to align with historical highs and lows.
✅ Best Use
Combine with other cycle signals (dominance ratios, macro indicators, sentiment).
Designed for long-term cycle analysis, not intraday trading.
Liquidity Box By "heman7knows"Code Description
This Pine Script Indicator Draws Custom Boxes On A Chart To Highlight Specific Trading Hours. It Allows You To Select A Timezone And Configure Up To Five Different Sessions. Each Box Automatically Adjusts To Show The Highest And Lowest Prices Reached During Its Respective Session. Users Can Customize The Time, Color, And Visibility Of Each Individual Session Box Through The Indicator's Settings.
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
" Date: " + date_str + " " + time_str +
" Trade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
" Rank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
" Percentile: " + str.tostring(percentile, "#.#") + "%" +
" Magnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
VCMB Levels v1.6c - MAs + VWAP + Key Levels Map + Last HighVCMB Levels v1.6c - MAs + VWAP + Key Levels Map + Last High
Custom Timed Boxes With TimezoneThis Pine Script Is A TradingView Indicator That Visually Marks Trading Sessions On Your Chart. It Is Designed To Help You Identify Key Price Areas And Track Market Behavior During Specific Timeframes.
Key Features Explained
Plotting Timed Boxes: The Script Draws Rectangular Boxes Around Price Action. Each Box Represents A Specific Time Period, Such As The Overnight Or Liquidity Hunt Sessions. The Box's Top And Bottom Automatically Adjust To The Highest And Lowest Price Within That Session.
Customizable Time Periods: You Can Define The Start And End Times For Up To 24 Different Sessions. This Allows You To Mark Any Timeframe You Want, Whether It's 15 Minutes Or Several Hours Long.
Color And Visibility Options: Each Of The 24 Boxes Has Its Own On/Off Switch And Color Selection. This Gives You Full Control Over What You See On Your Chart, Letting You Focus Only On The Sessions You Care About.
Timezone Support: There Is A Timezone Selector At The Top Of The Indicator's Settings. You Can Switch Between Different Timezones, And The Boxes Will Automatically Adjust To The Correct Local Time, Ensuring The Sessions Are Accurately Placed For Your Specific Market.
In Simple Terms, This Is A Powerful Tool For Traders Who Use Timed Sessions As A Core Part Of Their Strategy. It Automates The Process Of Drawing Boxes Manually, Making Your Chart Analysis Much Faster And More Efficient.
Daily High/Low Alerts MJO✅ Alert you when price hits daily highs and lows
✅ Work with any timeframe
✅ Support both stocks and crypto
✅ Include customizable colors for all visual elements
✅ Show optional table with current daily levels
✅ Provide flexible alert options
Zonas de Demanda e Oferta - Mais Sinais em Topos e FundosFX:EURUSD This script is a test script. Let me know if you like it. It's a model that sets us apart from other scripts. It's best to use it on Forex. It's available for an indefinite period, and we're always looking to update it for improvement.
If you have any questions, please contact us.
TMG V5This indicator is a trend indicator system. It is called a trendmeter. Its function is to show you the trend in which you are located (bullish, neutral, bearish) based on the displayed color.
Crypto Rate of ChangeThe indicator measures the percentage change in price over each month or quarter and displays those changes separately, so you can see how much the asset gained or lost in each distinct time period.
Bande de HullThis indicator works like a moving average whose thickness can be adjusted, varying depending on the asset and time frame.
I use it as a dynamic support/resistance zone.
Interest Rates CBs % Cutting📌 Description
This indicator tracks how many central banks around the world are currently cutting their policy rates. It aggregates policy rate changes from more than 30 central banks (including the Federal Reserve, ECB, BoE, BoJ, PBoC, Banco Central do Brasil, and many others) and normalizes the count to show the global percentage of banks easing monetary policy at any given time.
The calculation is simple:
A rate cut is counted as +1
A rate hike is counted as -1
No change = 0
The results are normalized by the number of banks with available data
The output is a smoothed line showing the share of central banks currently cutting rates. This helps highlight shifts in the global monetary cycle, which can be useful for macro-oriented analysis, risk-on/off regimes, or as a background filter for other strategies.
⚖️ Attribution
This script is inspired by and based on the “Global Central Banks Cutting Rates” indicator developed by Julien Bittel (MIT / RealVision). This version expands the coverage to a broader set of central banks and provides additional flexibility for signal smoothing.
🛑 Disclaimer
This indicator is for educational and analytical purposes only. It does not constitute financial advice or a trading signal. Please do your own research before making any investment decisions.
Auto Fibonacci TP/SL Area (DCMS)Auto Fibonacci TP/SL Area (BY Moura_DCMS)
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EMA Slopes Table (10/20/50/200)Gives you a box of 10,20,50 and 200 ema and indicates its sloping nature. If its in uptrend or downtrend.
1. Look for reversals when 200 is flat. Applies for both bearishness and bullishness
2. Look for 10,20 and 50 to be in sync always for powerful moves
MCL - Real Price (KRW/USD) - PUBLICThis indicator was developed by the chart analysis specialist team at the YouTube channel Money Copy Lab.
This indicator reflects the exchange rate between the US dollar and the South Korean won, enabling you to view domestic stock and domestic stock index charts correctly from an American investor's perspective.
As foreign investors, particularly American investors, participate heavily in domestic stocks, such exchange rate-reflected charts are highly significant.
