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!
วัฏจักร
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.
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.
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
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.
Indicator 102#M3indicator based on Daily and weekly fib Level. Initial Breakout and breakdowns have been denoted as well
Muzyorae - RTH Anchored Quarters CyclesRTH Anchored Quarters Cycles — Model Overview
The RTH Anchored Quarters Cycles model is designed to divide the Regular Trading Hours (RTH) session of U.S. equities (typically 09:30 – 16:00 New York time) into four structured “quarters” plus a closing marker. It provides a consistent framework for analyzing intraday market behavior by aligning time-based partitions with the actual trading day.
Key Features
Anchored to RTH
The model starts each cycle at 09:30 NY time (the official cash open).
It ignores overnight or extended-hours data, focusing strictly on the RTH session, where the majority of institutional order flow takes place.
After 18:00 NY time, the model still references the same trading date, preventing false signals from session rollovers.
Quarterly Time Blocks
The trading day is split into five reference points:
Q1: 09:30 – 10:00
Q2: 10:00 – 11:30
Q3: 11:30 – 13:30
Q4: 13:30 – 16:00
End: Closing marker at 16:00
Each boundary is drawn as a vertical line on the chart, clearly separating the quarters.
Customization
Users can adjust the start/end times of each quarter.
So if you would like to wish to use ICT timing Macro, intraday, daily and even weekly
The line style, color, and width are configurable (solid/dotted/dashed).
A label is placed at each quarter boundary (Q1, Q2, Q3, Q4, End) for quick visual reference.
Days Back Control
The model can display the cycles for multiple past trading days (user-defined).
Weekend days are automatically skipped, so “2 days back” means today and the previous trading day.
Why It’s Useful
Intraday Structure: Traders can quickly identify where the market is within the daily RTH cycle.
Consistency: Since the model is anchored to RTH, it avoids confusion caused by overnight Globex activity.
Clarity: Vertical markers and labels provide a clean framework for aligning trade setups, volume analysis, or order flow studies with specific time windows.
Flexibility: The customizable settings allow adaptation across instruments and strategies.
Trend Following CryptoSmartTrend Following CryptoSmart is a hybrid trend-following system designed for traders who value visual precision, structured logic, and clean confirmations.
This indicator combines a hybrid main line (EMA + trailing stop behavior) with a parallel secondary line, both offset from price by customizable distance. The logic resets on MACD crossovers and behaves like a dynamic visual stop, never repainting against trend.
Features include:
Modular lines with professional-grade smoothing
Shadow between price and trend, with separate color and opacity for bullish and bearish conditions
Displaced Long/Short labels with customizable style
Visual markers over native candles, without replacing them
Ideal for Smart Money flows, visual entry systems, and multi-timeframe confirmations.
This script is optimized for clarity, accessibility, and full customization. Every parameter is adjustable from the settings panel, allowing traders to tailor both visual and logical behavior to their strategy.
JoseangelFX Trader Mecanico Vol 1🔥 Tired of emotional trading? Transform yourself in 7 days with a 100% mechanical system!
Hi, I'm José Ángel FX, the Mechanical Trader. Forget long, theoretical courses. Here I give you a proven method to master the indices in record time. No subjective analysis, no emotions, just clear rules that work.
This code is responsible for indicating a trading range for a 100% mechanical system.
🚀 What will you achieve with this system?
✅ Trade like a pro in 7 days: You don't need years of study.
✅ Objective and repeatable signals: Eliminate doubts forever.
✅ Backtesting: Concrete results of the strategy.
✅ Discipline of Steel: Psychotrading armored against fear and greed.
📢 "In a week with this system, you are no longer the same trader."
Investment: Profitability really has no value, you'll achieve it (remote assistance with management system installation included, for MT4, MT5, and TradingView).
Requirement: Obedience...
👉 Schedule your FREE diagnosis:
WhatsApp: wa.me/584122928262
Telegram: @tradermecanicoJAFX
t.me
[GrandAlgo] Moving Averages Cross LevelsMoving Averages Cross Levels
Many traders watch for moving average crossovers – such as the golden cross (50 MA crossing above 200 MA) or death cross – as signals of changing trends. However, once a crossover happens, the exact price level where it occurred often fades from view, even though that level can be an important reference point. Moving Averages Cross Levels is an indicator that keeps those crossover price levels visible on your chart, helping you track where momentum shifts occurred and how price behaves relative to those key levels.
This tool plots horizontal line segments at the price where each pair of selected moving averages crossed within a recent window of bars. Each level is labeled with the moving average lengths (for example, “21×50” for a 21/50 MA cross) and is color-coded – green for bullish crossovers (short-term MA crossing above long-term MA) and red for bearish crossunders (short-term crossing below). By visualizing these crossover levels, you can quickly identify past trend change points and use them as potential support/resistance or decision levels in your trading. Importantly, this indicator is non-repainting – once a crossover level is plotted, it remains fixed at the historical price where the cross occurred, allowing you to continually monitor that level going forward. (As with any moving average-based analysis, crossover signals are lagging, so use these levels in conjunction with other tools for confirmation.)
Key Features:
✅ Multiple Moving Averages: Track up to 7 different MAs (e.g. 5, 8, 21, 50, 64, 83, 200 by default) simultaneously. You can enable/disable each MA and set its length, allowing flexible combinations of short-term and long-term averages.
✅ Selectable MA Type: Each average can be calculated as a Simple (SMA), Exponential (EMA), Volume-Weighted (VWMA), or Smoothed (RMA) moving average, giving you flexibility to match your preferred method.
✅ Auto Crossover Detection: The script automatically detects all crosses between any enabled MA pairs, so you don’t have to specify pairs manually. Whether it’s a fast cross (5×8) or a long-term cross (50×200), every crossover within the lookback period will be identified and marked.
✅ Horizontal Level Markers: For each detected crossover, a horizontal line segment is drawn at the exact price where the crossover occurred. This makes it easy to glance at your chart and see precisely where two moving averages intersected in the recent past.
✅ Labeled and Color-Coded: Each crossover line is labeled with the two MA lengths that crossed (e.g. “50×200”) for clear identification. Colors indicate crossover direction – by default green for bullish (positive) crossovers and red for bearish (negative) crossovers – so you can tell at a glance which way the trend shifted. (You can customize these colors in the settings.)
✅ Adjustable Lookback: A “Crosses with X candles” input lets you control how far back the script looks for crossovers to plot. This prevents your chart from getting cluttered with too many old levels – for example, set X = 100 to show crossovers from roughly the last 100 bars. Older crossover lines beyond this lookback window will automatically clear off the chart.
✅ Optional MA Plots: You can toggle the display of each moving average line on the chart. This means you can either view just the crossover levels alone for a clean look, or also overlay the MA curves themselves for additional context (to see how price and MAs were moving around the crossover).
✅ No Repainting or Hindsight Bias: Once a crossover level is plotted, it stays at that fixed price. The indicator doesn’t move levels around after the fact – each line is a true historical event marker. This allows you to backtest visually: see how price acted after the crossover by observing if it retested or respected that level later.
How It Works:
1️⃣ Add to Chart & Configure – Simply add the indicator to your chart. In the settings, choose which moving averages you want to include and set their lengths. For example, you might enable 21, 50, 200 to focus on medium and long-term crosses (including the golden cross), or turn on shorter MAs like 5 and 8 for quick momentum shifts. Adjust the lookback (number of bars to scan for crosses) if needed.
2️⃣ Visualization – The script continuously checks the latest X bars for any points where one MA crossed above or below another. Whenever a crossover is found, it calculates the exact price level at which the two moving averages intersected. On the last bar of your chart, it will draw a horizontal line segment extending from the crossover bar to the current bar at that price level, and place a label to the right of the line with the MA lengths. Green lines/labels signify bullish crossovers (where the first MA crossed above the second), and red lines indicate bearish crossunders.
3️⃣ On Your Chart – You will see these labeled levels aligned with the price scale. For example, if a 50 MA crossed above a 200 MA (bullish) 50 bars ago at price $100, there will be a green “50×200” line at $100 extending to the present, showing you exactly where that golden cross happened. You might notice price pulling back near that level and bouncing, or if price falls back through it, it could signal a failed crossover. The indicator updates in real-time: if a new crossover happens on the latest bar, a new line and label will instantly appear, and if any old cross moves out of the lookback range, its line is removed to keep the chart focused.
4️⃣ Customization – You can fine-tune the appearance: toggle any MA’s visibility, change line colors or label styles, and modify the lookback length to suit different timeframes. For instance, on a 1-hour chart you might use a lookback of 500 bars to see a few weeks of cross history, whereas on a daily chart 100 bars (about 4–5 months) may be sufficient. Adjust these settings based on how many crossover levels you find useful to display.
Ideal for Traders Who:
Use MA Crossovers in Strategy: If your strategy involves moving average crossovers (for trend confirmation or entry/exit signals), this indicator provides an extra layer of insight by keeping the price of those crossover events in sight. For example, trend-followers can watch if price stays above a bullish crossover level as a sign of trend strength, or falls below it as a sign of weakness.
Identify Support/Resistance from MA Events: Crossover levels often coincide with pivot points in market sentiment. A crossover can act like a regime change – the level where it happened may turn into support or resistance. This tool helps you mark those potential S/R levels automatically. Rather than manually noting where a golden cross occurred, you’ll have it highlighted, which can be useful for setting stop-losses (e.g. below the crossover price in a bullish scenario) or profit targets.
Track Multiple Averages at Once: Instead of focusing on just one pair of moving averages, you might be interested in the interaction of several (short, medium, and long-term trends). This indicator caters to that by plotting all relevant crossovers among your chosen MAs. It’s great for multi-timeframe thinkers as well – e.g. you could apply it on a higher timeframe chart to mark major cross levels, then drill down to lower timeframes knowing those key prices.
Value Clean Visualization: There are no flashing signals or arrows – just simple lines and labels that enhance your chart’s storytelling. It’s ideal if you prefer to make trading decisions based on understanding price interaction with technical levels rather than following automatic trade calls. Moving Averages Cross Levels gives you information to act on, without imposing any bias or strategy – you interpret the crossover levels in the context of your own trading system.
MomentumScriptThis is Momentum Tracker based on Richard Driehaus' research:
1) 12–1 momentum (return from t-12 months to t-1 month
2) FIP / path efficiency (many small up days > one big gap)
3) Proximity to 52-week high/low
Capiba RSI + Ichimoku + VolatilidadeThe "Capiba RSI + Ichimoku + Volatility" indicator is a powerful, all-in-one technical analysis tool designed to provide traders with a comprehensive view of market dynamics directly on their price chart. This multi-layered indicator combines a custom Relative Strength Index (RSI), the trend-following Custom Ichimoku Cloud, and dynamic volatility lines to help identify high-probability trading setups.
How It Works
This indicator functions by overlaying three distinct, yet complementary, analysis systems onto a single chart, offering a clear and actionable perspective on a wide range of market conditions, from strong trends to periods of consolidation.
1. Custom RSI & Momentum Signals
The core of this indicator is a refined version of the Relative Strength Index (RSI). It calculates a custom Ultimate RSI that is more sensitive to price movements, offering a quicker response to potential shifts in momentum. The indicator also plots a moving average of this RSI, allowing for the generation of clear trading signals. Use RMAs.
Bar Coloring: The color of the price bars on your chart dynamically changes to reflect the underlying RSI momentum.
Blue bars indicate overbought conditions, suggesting trend and a potential short-term reversal.
Yellow bars indicate oversold conditions, hinting at a potential bounce.
Green bars signal bullish momentum, where the Custom RSI is above both 50 and its own moving average.
Red bars indicate bearish momentum, as the Custom RSI is below both 50 and its moving average.
Trading Signals: The indicator plots visual signals directly on the chart in the form of triangles to highlight key entry and exit points. A green triangle appears when the Custom RSI crosses above its moving average (a buy signal), while a red triangle marks a bearish crossunder (a sell signal).
2. Custom Ichimoku Cloud for Trend Confirmation
This component plots a standard Ichimoku Cloud directly on the chart, providing a forward-looking view of trend direction, momentum, and dynamic support and resistance levels.
The cloud’s color serves as a strong visual cue for the prevailing trend: a green cloud indicates a bullish trend, while a red cloud signals a bearish trend.
The cloud itself acts as a dynamic support or resistance zone. For example, in an uptrend, prices are expected to hold above the cloud, which provides a strong support level for the market.
3. Dynamic Volatility Lines
This final layer is a dynamic volatility channel that automatically plots the highest high and lowest low from a user-defined period. These lines create a visual representation of the recent price range, helping traders understand the current market volatility.
Volatility Ratio: A label is displayed on the chart showing a volatility ratio, which compares the current price range to a historical average. A high ratio indicates increasing volatility, while a low ratio suggests a period of price consolidation or lateral movement, a valuable insight for day traders.
The indicator is highly customizable, allowing you to adjust parameters like RSI length, overbought/oversold levels, Ichimoku periods, and volatility lookback periods to suit your personal trading strategy. It is an ideal tool for traders who rely on a combination of momentum, trend, and volatility to make well-informed decisions.
Muzyorae - Quarterly CyclesQuarterly Theory — NY Session Macro Model
The Quarterly Theory is a time-based framework for analyzing intraday market behavior during the New York session. It divides the session into four sequential quarters (Q1–Q4), each reflecting institutional activity, liquidity accumulation, and directional bias.
Q1 – Accumulation (9:30–10:00 AM): Early positioning, initial liquidity sweeps, and potential early breakouts (AMDX - XAMD patterns).
Q2 – Manipulation/Expansion (10:00–11:30 AM): Main directional move with structure breaks, fair value gaps, and liquidity sweeps.
Q3 – Distribution/Retracement (11:30 AM–1:30 PM): Consolidation, profit-taking, and market chop.
Q4 – Final Expansion/Repricing (1:30–4:00 PM): Trend continuation, reversals, and session high/low formation.
Key Features:
Fractal-based cycles scalable across intraday or multi-day timeframes.
Supports AMDX (Accumulation → Manipulation → Distribution → Expansion) and XAMD reversal sequences.
Highlights early Q1 expansions, Q2 open reference, and critical liquidity zones.
Fully synchronized to NY time and compatible with ICT concepts (SMT, FVGs, OBs, BOS).
Professional visualization with optional labels and vertical markers.
Purpose:
Provides traders a systematic framework to align with institutional flow, anticipate liquidity accumulation, identify optimal entry/exit zones, and structure trades around high-probability intraday cycles.
🐋 Radar de Ballenas v3 + PanelEvaluate areas of high interest by gathering information based on the fluctuation of the bar graph + information panel for decision-making
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🐋 Radar de Ballenas v3 (final)evalua zonas de gran interes recopilando informacion basada en la fluctuazion del grafico de barras
Student Wyckoff Paunch v.3 Adx
Look trend background
Look at the trend combined with the volatility bands
RSI Cross Alerts with Vertical Lines (9:30 AM - 2:45 PM)RSI Cross Alerts - Indicates Vertical Lines on previous times the RSI Indicator Crosses Overbought or Oversold parameters set by user.
NY Sessions Boxes (Live Drawing)//@version=5
indicator("NY Sessions Boxes (Live Drawing)", overlay=true)
ny_tz = "America/New_York"
t = time(timeframe.period, ny_tz)
hour_ny = hour(t)
minute_ny = minute(t)
// سشن ۱: 02:00 – 05:00
session1_active = (hour_ny >= 2 and hour_ny < 5)
session1_start = (hour_ny == 2 and minute_ny == 0)
// سشن ۲: 09:30 – 11:00
session2_active = ((hour_ny == 9 and minute_ny >= 30) or (hour_ny > 9 and hour_ny < 11))
session2_start = (hour_ny == 9 and minute_ny == 30)
var box box1 = na
var float hi1 = na
var float lo1 = na
if session1_start
hi1 := high
lo1 := low
box1 := box.new(left = time, right = time, top = high, bottom = low, bgcolor=color.new(color.blue, 85), border_color=color.blue)
if session1_active and not na(box1)
hi1 := math.max(hi1, high)
lo1 := math.min(lo1, low)
box.set_right(box1, time)
box.set_top(box1, hi1)
box.set_bottom(box1, lo1)
if not session1_active and not na(box1)
box1 := na
hi1 := na
lo1 := na
var box box2 = na
var float hi2 = na
var float lo2 = na
if session2_start
hi2 := high
lo2 := low
box2 := box.new(left = time, right = time, top = high, bottom = low, bgcolor=color.new(color.purple, 85), border_color=color.purple)
if session2_active and not na(box2)
hi2 := math.max(hi2, high)
lo2 := math.min(lo2, low)
box.set_right(box2, time)
box.set_top(box2, hi2)
box.set_bottom(box2, lo2)
if not session2_active and not na(box2)
box2 := na
hi2 := na
lo2 := na
Dynamic Fibonacci MTF Zones v1🔹 Overview
This indicator automatically detects Fibonacci retracement levels across multiple timeframes (MTF) and highlights the most relevant zones around the current price.
Instead of cluttering the chart with too many lines, it only shows the 3 nearest levels above and below the current price, with clear labels and lines.
🔹 Key Features
Multi-Timeframe Support
Up to 7 custom timeframes can be analyzed simultaneously
Example: 5m, 15m, 1H, 4H, 1D, 1W, 1M
Dynamic Fibonacci Levels
Based on recent high/low within N bars
Uses extended set of 25 ratios (0.045 ~ 0.955)
Golden Pocket (0.382–0.618) zones are auto-highlighted
Nearest 3 Levels Display
Picks the 3 closest levels above and below current price
Labels and lines are plotted for clarity
Identical levels across TFs are merged automatically for clean display
Labels with Details
Direction (▲ / ▼)
Timeframe
Fibonacci ratio
Exact price
Visual Customization
Above levels in blue tones, below levels in red tones
Transparency darkens gradually from TF1 → TF7
Line style: solid / dashed / dotted
Zone fills with adjustable colors
🔹 How to Use
Identify strong support/resistance zones where multiple TF Fibonacci levels overlap
Scalpers: Combine short TFs (5m, 15m, 1H)
Swing traders: Use higher TFs (4H, 1D, 1W)
Investors: Track broader zones (1D, 1W, 1M)
🔹 Settings
Recent Range Bars (R): lookback period for Fibonacci highs/lows
Golden Pocket Highlight: toggle 0.382–0.618 shading
Line Style: switch between line/circle visualization
MTF Control: enable/disable TF1~TF7 with custom timeframe selection
✅ Core Idea:
This tool doesn’t just draw Fibonacci lines — it dynamically selects the most relevant MTF levels, merges duplicates, and highlights only the critical zones you need for real trading decisions.
