Adaptive Score Pro - Trade Intelligence ⚠️ IMPORTANT RISK DISCLAIMER
This script, "Adaptive Score Pro - Trade Intelligence" is published for informational and educational purposes only. It is a technical analysis tool that automates calculations based on market data.
1. Not Investment Advice
The information generated by this script does not constitute financial, investment, or trading advice of any kind . It is not a recommendation to buy, sell, or hold any security or other financial product. You should not rely on this script as a substitute for independent research or professional financial advice .
2. Trading is High Risk
Trading financial instruments carries a high degree of risk. You can lose more than your initial investment, especially when using leverage . Past performance, including any hypothetical or backtested results shown, is not indicative of future results.
3. No Warranties or Liability
The script and its outputs are provided "as is" without any guarantees of accuracy, reliability, or profitability . By using this script, you agree that the author and TradingView, Inc. are not liable for any trading decisions you make, or for any losses or damages that may arise from your use of or reliance on this script .
4. Your Responsibility
You are solely and fully responsible for evaluating the risks of any trade and for your own trading decisions . Ensure you understand the risks involved and only trade with capital you can afford to lose .
By using this script, you acknowledge that you have read, understood, and agree to this disclaimer.
📈 Indicator Overview & Purpose
"Adaptive Score Pro - Trade Intelligence MFE_MAE4" is a comprehensive, all-in-one trading system designed for systematic traders. It goes beyond basic signal generation by integrating real-time trade management, detailed performance analytics, and advanced market regime detection into a single, visually intuitive dashboard.
The core philosophy is to provide trade intelligence—not just entry signals. It analyzes market conditions, assigns a quality grade to every signal, and actively monitors open positions to suggest management adjustments, helping traders move from guesswork to data-driven decisions.
🎯 Unique Selling Points & Key Features
Your script's depth sets it apart. Here are its standout features presented in a table for clarity:
Feature Category What It Does Why It's Valuable
Open Trade Intelligence Monitor Replaces simple signal panels with a dynamic dashboard for each open trade. It compares entry vs. current conditions (score, grade, confidence, regime) and suggests specific actions (HOLD, ADD, DEF, EXIT, TP) and adjustments to stops/targets. Provides actionable, real-time management suggestions, turning a static indicator into an active trading assistant.
Expanded MFE/MAE & High/Low Analysis Tracks the Maximum Favorable and Adverse Excursion in ATR terms and records price highs/lows at strategic intervals (Bars 1, 2, 3, 5, 7, 10, 15) after entry for both long and short trades. Offers deep, standardized post-trade analytics to evaluate entry quality and trade behavior, helping refine future strategy.
Adaptive Signal Engine Generates a composite score from trend, momentum, and volume components, with weights that adapt to market regime (e.g., STRONG TREND, ACTIVE RANGE). Each signal receives a quality grade (A+ to F) and confidence score. Filters out low-probability setups, ensuring you focus on high-quality, regime-appropriate trades.
Holistic Performance Suite Displays complete trade history and detailed statistics (Win Rate, Profit Factor, Sharpe/Sortino Ratios, Max Drawdown). Includes a Threshold Analysis table showing historical win rates for specific score bands. Enables continuous strategy validation and optimization based on your actual historical performance.
Integrated Risk & Portfolio Management Features multi-position risk control, position sizing (with optional Kelly Criterion), and tracks total portfolio equity and drawdown. It enforces maximum open positions and position-size limits. Manages portfolio-level risk, a critical feature often missing from standalone indicators.
🛠️ How to Use the Indicator
Signal Generation: The indicator plots signals on the chart. Focus on trades with a B- grade or higher and high confidence for best results.
Trade Management: Once in a trade, the Open Trade Monitor (top of the table) becomes your control center. Use the suggested "ACT" (action) and adjust stops/targets based on the "NewS" and "NewT" columns.
Post-Trade Analysis: Review the "Recent Trades" section and "Performance" statistics to understand what's working. Use the "Threshold Analysis" to see which score ranges are most profitable for your asset.
💡 Ideal User & Best Practices
This script is ideal for traders who employ a systematic, discretionary approach and want a unified tool for signal filtering, trade management, and performance tracking.
Recommended Timeframes: 1-hour charts and above for reliable regime detection and to avoid excessive noise.
Initial Setup: Start with the default settings. After 20-30 trades, use the Threshold Analysis to see if adjusting the buy/sell thresholds (default 56/44) could improve your edge.
Core Philosophy: Use the A/B-grade signals as high-probatility alerts, not automated orders. The intelligence is in the context it provides—always apply your own final judgment.
⚠️ Important Considerations
Learning Curve: The indicator is feature-rich and may be overwhelming for complete beginners.
Not a "Set-and-Forget" System: It is a sophisticated decision-support tool. Successful use requires understanding its outputs and integrating them into a complete trading plan.
Historical Data: The statistical models and threshold analysis become more reliable as more trade history is accumulated.
In summary, "Adaptive Score Pro" packages the tools of a professional trading desk—from signal generation and quality grading to active trade management and detailed analytics—into a single TradingView indicator. Its standout Open Trade Intelligence Monitor and expanded trade analytics make it a powerful platform for traders aiming to systematize and improve their process.
Statistics
USDT: Market cap changeUSDT: Market Cap Change
This indicator tracks the market capitalization changes of major stablecoins (USDT, USDC, and DAI) to help identify capital flows in the cryptocurrency market.
Features:
Monitor daily and custom period market cap changes for selected stablecoins
Configurable stablecoin selection (USDT, USDC, DAI)
Adjustable lookback period for measuring market cap changes
Multiple moving average types (SMA, EMA, HMA, WMA, RMA) for trend analysis
Visual representation with columns for daily changes and area fill for custom period changes
How to Use:
The indicator displays two main metrics: daily market cap change (shown as columns) and custom period change (shown as a line with area fill). Positive values indicate capital inflow into stablecoins, which may suggest accumulation or risk-off sentiment. Negative values indicate capital outflow, potentially signaling deployment into other crypto assets.
The moving average overlay helps identify trends in stablecoin market cap changes over time.
Settings:
Select which stablecoins to track
Adjust the lookback period (default: 60 days)
Toggle and configure the moving average overlay
Customize MA type and length
Data Source:
Uses Glassnode market capitalization data for USDT, USDC, and DAI on a daily timeframe.
Average Daily Range by EleventradesThe Average Daily Range (ADR) indicator helps traders measure how much of the current day’s range has already been completed and how much movement may still be available.
This tool calculates the average range of previous daily candles and compares it with the current day’s price action. It displays how many points of the ADR have been consumed, how much remains, and the percentage of the daily range already covered. This allows traders to better judge whether price is still expanding or approaching exhaustion.
Key Features:
ADR Consumption Tracking
Shows how much of the daily range has already been used in both points and percentage terms.
Reversal Threshold
A customizable threshold that highlights when price exceeds a defined ADR value, signaling potential exhaustion or reversal zones.
Mean Reversion Logic
When price reaches a user-defined percentage of the ADR, the indicator helps identify areas where price may revert back toward the daily range.
ADR Exceeded Alert
Displays a message when price exceeds 100% of the average daily range.
Information Table
A clean table that summarizes ADR values, consumed range, remaining range, and percentage data for quick reference.
ADR Projection Levels
Projected upper and lower ADR levels are plotted using visual guide lines, helping traders see where the daily range may extend before exceeding typical limits.
US Index Market Snapshot Cash, Futures & ETFsBrief Description
This study displays a real-time table of major U.S. equity indices—Dow Jones, S&P 500, Nasdaq, and Russell—across Cash, Futures, and ETF markets.
Each cell shows the current price along with the daily percentage change, with color-coded backgrounds for quick trend identification.
Designed as a compact market dashboard, it provides an at-a-glance view of cross-market alignment and relative performance.
Alternative Title Options
US Indices Dashboard (Cash • Futures • ETFs)
Index Market Matrix – Prices & Daily Change
Multi-Market US Index Table
FVG & OB [odnac]This indicator is a sophisticated tool designed for Smart Money Concepts (SMC) traders. It automates the detection of two critical institutional footprints: Order Blocks (OB) and Fair Value Gaps (FVG), with a focus on candle momentum and mitigation tracking.
Key Features
1. Advanced Momentum Filtering (3 Versions)
Unlike basic indicators, this script uses three different mathematical approaches to ensure the middle candle represents a "strong" move:
V1 (Body Focus): Compares the bodies of the surrounding candles to the middle candle.
V2 (Hybrid): Uses a mix of candle ranges and bodies to identify expansion.
V3 (Range Focus): The most aggressive filter; it ensures the total range of the middle candle dwarfs the surrounding candles.
2. Automatic Mitigation Tracking
The indicator doesn't just draw static boxes. It tracks price action in real-time:
Dynamic Extension: Boxes extend to the right automatically as long as price has not returned to "test" or "fill" the zone.
Smart Clean-up: Once the price touches the zone (Mitigation), the box stops extending or is removed. This keeps your chart clean and focused only on "fresh" (unmitigated) levels.
3. Smart Money Concept Integration
Order Blocks (White Boxes): Identifies where institutional buying or selling occurred before a strong move.
Fair Value Gaps (Yellow Boxes): Highlights price imbalances where the market moved too fast, leaving a gap that often acts as a magnet for future price action.
Technical Logic Breakdown
Detection Logic
The script looks at a 3-candle sequence:
Candle (The Origin): Defines the boundary of the OB or FVG.
Candle (The Expansion): Must be a "Strong Candle" based on your selected setting (V1, V2, or V3).
Candle (The Confirmation): Ensures that the "Tail Gap" condition is met (the wick of Candle 2 and Candle 0 do not touch).
Box Management
The script uses Pine Script Arrays to manage up to 500 boxes. It constantly loops through active boxes to check:
Time Limit: If a box exceeds the max_bars_extend limit, it is removed to save memory.
Price Touch: If low or high enters the box coordinates, the zone is considered "mitigated" and the extension stops.
INFO TIME BARInfo Time Bar by EternityWorld is a table-style overlay indicator that displays real-time, non-repainting information from the current chart.
Included Information
Asset ticker
Current chart timeframe
Candle countdown timer, formatted as HH:MM:SS
Key Features
✔ Fixed 3-row table for visual stability
✔ Auto-updates on the latest confirmed bar
✔ Independent enable/disable toggles per row
✔ Fully adjustable table position on chart
✔ Minimalist, clean, and functional design
Usage
This indicator is built exclusively for chart information display, without plotting signals, levels, drawings, or additional graphical elements.
Compatibility
Works on all TradingView assets that support overlay indicators, adapting automatically to any active chart timeframe.
Disclaimer ⚠️
This indicator is not financial advice nor a market-prediction tool. It solely displays current chart data. Options and derivatives trading involves risk. Use responsibly and execute based on your own trading decisions.
LQL Watchlist TableFollowing me on X - x.com
LQL Watchlist Table - A clean, customizable on-chart watchlist table that displays up to 10 symbols with real-time Last Price, daily Change, and Change % — styled like TradingView's official watchlist.
Key Features:
Fully configurable rows (enable/disable, custom color, any symbol)
Optional left color block for quick visual scanning
Toggle columns: Last Price, Change, Change %
Fixed decimal places for consistent, professional alignment
Real-time Last Price updates (1-minute resolution)
Change and Change % calculated from previous daily close (exactly like TradingView's built-in watchlist)
Clean header with subtle ⓘ hint (hover for explanation)
Transparent buffers and customizable position/size
Disclaimer – Important Note on Real-Time Updates:
This is an indicator script, so the table refreshes only when the chart receives new data (new bar or tick on the main chart symbol).
During market hours: updates live with every tick.
On weekends/holidays or when the main chart symbol is closed (e.g., stocks/futures): the table becomes static and shows the last available prices from Friday's close.
Crypto symbols (e.g., BTCUSDT) will only tick live if the main chart is receiving updates (e.g., if you're viewing a crypto chart or a low-timeframe stock chart during active hours).
This is a limitation of Pine Script indicators and cannot be fully overcome. For 24/7 crypto ticking on weekends, use a crypto symbol as your main chart.
AZ #1 RM (FX*10)Lot Size/Position Size/Risk Management Tool
All in trading view, making the process seamless.
BACT Bougie Assistant Context and TimingBACT — Candle Assistant | Context & Timing
BACT is not a signal indicator.
It does not try to predict the market.
It tells you when the market is ready… and when it is not.
🎯 What is BACT for?
Filtering bad trades before they even exist
Identifying market regimes in real time:
Range
Range breakout
Extension
Extreme risk zone
👉 Helping with timing, not direction
BACT acts directly on candles, with no lag and no anticipation.
🧠 Philosophy
No prediction
No imposed directional bias
No attempt to “guess the future”
👉 The market decides.
👉 BACT adapts in real time.
🔬 How BACT works
BACT uses an adaptive algorithm, specific to the traded instrument.
It does not rely on fixed, universal parameters
It dynamically adjusts to the current market behavior
Its logic is purely statistical, based on real candle structure and context
The indicator evolves continuously with the market,
with no external learning, no frozen historical model,
and no over-optimization.
👉 Every market has its own signature.
👉 BACT reads it, instead of forcing a model onto it.
📊 Who is it for?
Scalping / Day trading
Swing / Investing (depending on the selected mode)
Indices, Futures, Stocks
BACT works with your existing strategy.
It does not replace it — it enhances it.
⚙️ What BACT actually does
Colors candles according to the real market context
Highlights zones where doing nothing is the best decision
Allows trading only when statistical conditions are aligned
Protects against false starts, choppy ranges, and overtrading
🔒 What BACT does NOT do
It does not give buy or sell orders
It does not promise performance
It does not replace risk management
❓ Simple question
How many monthly losses could you avoid
if you only traded when the market is ready?
ℹ️ Important notes
BACT is designed to be used exclusively with Heikin Ashi candles
BACT will be offered as a subscription-based indicator
A limited-time free launch offer will be available
USDJPY Power DashboardUSDJPY Power Dashboard — Description
USDJPY Power Dashboard is an analytical dashboard designed to visualize
the underlying forces driving USD/JPY (US Dollar / Japanese Yen) by combining currency strength and market risk factors.
Instead of showing price direction alone, this indicator separates “cause” and “result”:
Why USD/JPY is being pushed up or down (pressure / structure)
What USD/JPY is actually doing (trend)
This makes it especially useful for identifying trend continuation, range conditions, and potential turning points.
Instruments Used
The dashboard evaluates USD/JPY using six key instruments:
USDJPY – the price itself (result)
EURUSD – relative USD strength vs EUR
DXY (US Dollar Index) – overall USD strength
JPY Index – overall JPY strength
Dow Jones Industrial Average – risk sentiment proxy (JPY factor)
Nikkei 225 – risk sentiment proxy (JPY factor)
These are grouped into:
USD-related factors
JPY-related factors
Risk-on / Risk-off factors (equities)
Direction Logic
For each instrument:
A simple moving average (SMA) slope is calculated.
The direction is classified as:
Up (+1)
Down (−1)
Neutral (0)
The direction is then converted into its contribution to USD/JPY:
+1 = upward pressure on USD/JPY
−1 = downward pressure on USD/JPY
0 = neutral
The moving average is used only for direction detection, not for chart display.
Table Overview (Bottom Right)
1. Individual Power per Instrument
Each instrument is listed with its current contribution to USD/JPY:
Up Power
Down Power
Neutral
Numeric score (+1 / −1 / 0)
This allows you to instantly see which components are pushing or pulling USD/JPY.
2. Summary 1 — Cause / Pressure (Hybrid Model)
Summary 1 describes the market structure behind USD/JPY by evaluating USD and JPY forces independently.
It explicitly shows real-world FX combinations such as:
USD Buy + JPY Sell (Classic Trend)
USD Sell + JPY Buy (Classic Reversal)
USD Buy + JPY Buy (Weak Direction / Tug of War)
USD Sell + JPY Sell (Risk-On Distortion)
On top of that, it adds a practical pressure label:
USDJPY Upward Pressure / Downward Pressure
USD-led / JPY-led / Mixed
This provides a concise explanation of what is driving the market right now.
3. Summary 2 — Result (Trend)
Summary 2 shows the actual USD/JPY trend based on USDJPY’s own direction:
UP
DOWN
FLAT
By comparing Summary 1 (cause) and Summary 2 (result), you can quickly identify:
Trend confirmation
Range conditions
Early signs of trend exhaustion or reversal
How to Use This Indicator
To understand why USD/JPY is moving, not just how
To distinguish trend continuation vs. structural divergence
As a bridge between technical analysis and macro / intermarket context
⚠️ When Summary 1 and Summary 2 diverge, the market is often ranging or approaching a turning point.
Notes
This is not a prediction tool, but a market structure and pressure analysis tool
Equity indices (Dow / Nikkei) are indirect factors and should be interpreted as context
Sudden news-driven spikes may not be immediately reflected
Asia & London Session High/Low Description:
This indicator plots the highest and lowest points of the Asian and London trading sessions based on Eastern Time (ET).
Features:
Draws horizontal rays for session highs and lows
Automatically resets for each session
Perfect for I CT-style liquidity analysis , range breaks , and session-based trading setups
Clean chart : no labels or clutter, just the key session levels
Use it to identify liquidity zones , plan entries , and anticipate potential session raids in your trading strategy.
CFD Position Sizing Tool (ATR-Based)A visual dashboard is included. This is an ATR Designed robust position sizing calculator for the on the fly traders.
SOFR - EFFR SpreadThis indicator calculates and visualizes the spread between SOFR (Secured Overnight Financing Rate) and EFFR (Effective Federal Funds Rate) on TradingView. It fetches data from FRED to compute the difference. 'Red' indicates a liquidity crunch (tightness) in the market, while 'green' indicates ample liquidity.
tanukitsune scoreJapanese factor-based investing
This is an indicator for analyzing Japanese stocks, which quantifies changes that can be read from financial statements on a scale of 10 points. Since it adopts year-on-year or year-on-year comparison changes, I believe it is suitable for momentum investing.
Liquidation Map [Alpha Extract]A sophisticated liquidity distribution visualization system that identifies potential liquidation zones through pivot-based detection and renders them as an interactive histogram with cumulative distance-to-liquidation curves. Utilizing multi-exchange volume aggregation and ATR-scaled pocket detection, this indicator delivers institutional-grade liquidity mapping with real-time histogram display showing relative concentration of long and short liquidation levels across configurable price ranges. The system's box-based rendering architecture combined with cumulative distribution overlays provides comprehensive visual assessment of asymmetric liquidity positioning for strategic trade planning.
🔶 Advanced Multi-Exchange Aggregation Framework
Implements intelligent ticker detection and multi-source volume aggregation across major exchanges including Binance, Bybit, KuCoin, OKX, and MEXC for accurate liquidity weight calculations. The system automatically identifies base currency (BTC, ETH, SOL) from chart ticker, retrieves volume data from matching perpetual contracts across multiple venues, and aggregates into composite volume metric for enhanced pocket weighting accuracy.
🔶 Pivot-Based Liquidation Pocket Detection
Features sophisticated swing point identification using configurable pivot width with ATR-scaled vertical zone construction for volatility-adaptive pocket sizing. The system detects pivot highs for short liquidation zones (placed above swing) and pivot lows for long liquidation zones (placed below swing), applying 200-period ATR with percentage multipliers to determine pocket heights that adjust to market volatility conditions.
🔶 Interactive Histogram Visualization Engine
Provides real-time box-based histogram rendering in indicator pane with configurable bin counts (up to 400 columns) and adjustable height, displaying liquidity concentration across fixed percentage range above and below current price. The system calculates bin sizes from view range, accumulates pocket weights into price bins, and renders vertical bars with gradient color intensity reflecting relative liquidity concentration at each price level.
🔶 Cumulative Distance Overlay System
Implements innovative cumulative distribution curves showing aggregate liquidity distance from current price for both long (left) and short (right) positions. The system calculates running totals of pocket weights from current price outward in both directions, normalizes against maximum span, and overlays line segments showing how much total liquidity exists at various distances, enabling instant assessment of liquidation cascade potential.
🔶 Dynamic Price Range Adaptation
Features fixed percentage-based view window that maintains consistent price range visualization across all timeframes and instruments, automatically centering histogram on current price with configurable +/- percentage bounds. The system recalculates histogram bins and pocket distributions on each bar close, ensuring visualization adapts to price movement while maintaining interpretable scale regardless of volatility regime.
🔶 Touch Detection and Weight Adjustment
Provides intelligent pocket state tracking that identifies when price trades through liquidation zones and applies configurable weight multipliers to touched pockets for historical context. The system monitors price interaction with pocket midpoints, marks pockets as "hit" when violated, and optionally increases their visual weight (default 5x) to emphasize historical liquidation levels while distinguishing from untouched future zones.
🔶 Gradient Intensity Color System
Implements sophisticated color gradient engine that modulates bar opacity from transparent to opaque based on relative liquidity concentration within each bin. The system normalizes bin values against maximum liquidity, applies color interpolation from faded to vivid hues, and distinguishes long liquidation zones (cyan) from short liquidation zones (yellow/gold) with current price column highlighted in red for instant orientation.
🔶 Performance-Optimized Rendering Architecture
Utilizes efficient box and line object management with dynamic allocation based on histogram configuration, implementing intelligent cleanup and reuse to maintain smooth performance. The system includes adaptive line budget calculations that adjust segment density for cumulative curves based on available object limits, ensuring consistent operation even with maximum histogram resolution settings.
🔶 Asymmetric Distribution Analysis
Calculates separate cumulative distributions for long and short liquidation zones split at current price, enabling identification of imbalanced liquidity positioning. The system normalizes distributions against respective maximums and overlays both curves on single histogram, allowing traders to instantly assess whether more liquidation risk exists above (shorts vulnerable) or below (longs vulnerable) current price levels.
🔶 Configurable Label and Scale System
Provides price axis labeling with adjustable frequency to reduce clutter while maintaining reference points, displaying price values at regular column intervals with configurable offset positioning. The system includes current price label showing exact value and percentile position within view range, offering both absolute price reference and relative positioning context for distribution interpretation.
🔶 Historical Pocket Persistence Framework
Maintains rolling window of liquidation pockets up to 3000 bars with automatic expiration management and optional preservation of touched zones for historical analysis. The system tracks pocket creation time, monitors age against lookback limits, and manages array cleanup to prevent memory overflow while retaining relevant historical liquidation levels for pattern recognition and support/resistance validation.
This indicator delivers sophisticated liquidity distribution analysis through histogram visualization and cumulative distance curves that reveal asymmetric positioning of potential liquidation levels. Unlike simple liquidation heatmaps that show absolute levels, the Liquidation Map's cumulative distribution overlays instantly communicate how much total liquidity exists at various distances from current price, enabling assessment of cascade potential. The system's multi-exchange volume aggregation, touch-weighted historical zones, and fixed-range visualization make it essential for traders seeking strategic positioning around institutional liquidity clusters in cryptocurrency futures markets. The histogram format enables instant identification of price levels where concentrated liquidations may trigger significant volatility or reversal events, while the asymmetric distribution curves reveal whether market structure favors upside or downside cascades.
Current Day Range DeltaDisplays the current trading day’s high, low, and range delta, with optional labels and intraday level tracking for futures and ETFs.
Weekend Trading Range - [EntryLab]ENTRYLAB WEEKEND RANGE
Trading the weekends often results in lower volume, consolidation, and flat price action. This indicator is built for the community to clearly mark the weekend range, allowing traders to gauge how price formed during the weekend before markets reopen on Monday.
Custom built by EntryLab for the trading community.
Breakeven LECAPs BONCAPsEN
Breakeven LECAPs & BONCAPs (ARS → USD) + Futures Curve
This indicator plots the breakeven USD/ARS exchange rate for Argentine fixed-rate Treasury instruments LECAPs (S tickers) and BONCAPs (T tickers), showing the USD/ARS level at each maturity where holding the peso instrument would match the performance of holding dollars.
What you get
• Breakeven labels at (Maturity Date, Breakeven Dollar)
• Automatic FX benchmarks:
• Dólar MEP: BCBA:AL30 / BCBA:AL30D
• Dólar Cable (CCL): BCBA:AL30 / BCBA:AL30C
• Optional Custom Dollar input (1000–10000 ARS)
• Optional MatbaRofex USD futures labels at their expiry dates
• Optional polynomial regression curves for LECAPs, BONCAPs, and Futures (degree 1–4), with independent toggles, colors, and smoothness points
Core calculations
• Direct Return = (Maturity Price / Last Price) - 1
• TNA (Annualized Rate) = Direct Return × 365 / Days to Maturity
• Breakeven Dollar = Current Dollar × (1 + Direct Return)
Tooltip (hover labels)
Ticker/type, maturity date, days to maturity, current price, maturity price (px_finish), direct return, TNA, and breakeven value.
⸻
ES
Breakeven LECAPs & BONCAPs (ARS → USD) + Curva de Futuros
Este indicador grafica el tipo de cambio USD/ARS de equilibrio (breakeven) para instrumentos de tasa fija del Tesoro argentino LECAPs (tickers S) y BONCAPs (tickers T). Te muestra a qué nivel de dólar, en cada vencimiento, una inversión en pesos igualaría el rendimiento de quedarse en dólares.
Qué muestra
• Etiquetas de breakeven en (Fecha de vencimiento, Dólar breakeven)
• Referencias automáticas de tipo de cambio:
• Dólar MEP: BCBA:AL30 / BCBA:AL30D
• Dólar Cable (CCL): BCBA:AL30 / BCBA:AL30C
• Opción de Dólar Custom (1000–10000 ARS)
• Opción de mostrar futuros de USD MatbaRofex en sus vencimientos
• Curvas de regresión polinómica opcionales para LECAPs, BONCAPs y Futuros (grado 1–4), con toggle, color y suavizado configurables por separado
Cálculos principales
• Retorno Directo = (Precio de vencimiento / Último precio) - 1
• TNA = Retorno Directo × 365 / Días al vencimiento
• Dólar Breakeven = Dólar actual × (1 + Retorno Directo)
Tooltip (pasar el mouse por las etiquetas)
Ticker/tipo, fecha de vencimiento, días restantes, precio actual, precio de vencimiento (px_finish), retorno directo, TNA y valor de breakeven.
==================== DISCLAIMER / AVISO LEGAL ====================
This indicator is for informational and educational purposes only.
Eco Valores S.A. does NOT provide investment advice or recommendations.
Consult a qualified financial advisor before making investment decisions.
Este indicador es solo para fines informativos y educativos.
Eco Valores S.A. NO brinda asesoramiento ni recomendaciones de inversion.
Consulte con un asesor financiero calificado antes de invertir.
===================================================================
LECAPS_BONCAP_LibraryLibrary "LECAPS_BONCAP_Library"
getInstrumentCount()
getTicker(index)
Parameters:
index (int)
getTickerShort(index)
Parameters:
index (int)
getMaturityPrice(index)
Parameters:
index (int)
getMaturityTimestamp(index)
Parameters:
index (int)
getMaturityYear(index)
Parameters:
index (int)
getMaturityMonth(index)
Parameters:
index (int)
getMaturityDay(index)
Parameters:
index (int)
isBoncap(index)
Parameters:
index (int)
isLecap(index)
Parameters:
index (int)
getInstrumentType(index)
Parameters:
index (int)
getDolarFuturesCount()
getDolarFuturesTicker(index)
Parameters:
index (int)
getDolarFuturesShort(index)
Parameters:
index (int)
getDolarFuturesExpiry(index)
Parameters:
index (int)
getDaysToMaturity(index)
Parameters:
index (int)
getDataSummary(index)
Parameters:
index (int)
YTD % / Visible Range % TableAUTHOR: Brandon Gum
DATE: 2026-01-03
// PURPOSE:
// Calculates price-range metrics based on the *currently visible*
// portion of the chart. Intended for table-based UI display where
// values must be stable and evaluated only on the last bar.
//
// Originally based on Jeff Sun's ADR price data table.
//
// METRICS RETURNED:
// - Visible High
// - Visible Low
// - Visible % Range = (Visible High - Visible Low) / Visible Low
// - Visible ATRs = (Visible High - Visible Low) / ATR
//
// IMPLEMENTATION NOTES:
// - Logic executes ONLY on barstate.islast to avoid state corruption.
// - Visible range is recomputed atomically using a backward loop
// bounded by chart.left_visible_bar_time.
// - Avoids var-based accumulation and bar-by-bar resets, which are
// unreliable when visible window changes.
// - ATR is evaluated at the current bar (not averaged over range).
//
// ASSUMPTIONS / LIMITATIONS:
// - Uses chart-visible time boundaries supplied by TradingView.
// - Loop upper bound must be sufficiently large to cover max
// expected visible bars.
// - Intended for display purposes, not signal generation.
//
// SIDE EFFECTS:
// - None. No plots, no drawings, no state persistence.
Z-Score Momentum Dashboard Z-Score Momentum Dashboard: A Comprehensive Technical Analysis Framework
Understanding the Z-Score Momentum Dashboard
The Z-Score Momentum Dashboard represents a sophisticated evolution in technical analysis indicators, designed to synthesize multiple analytical frameworks into a singular, coherent probabilistic assessment of market conditions. At its core, this indicator is a multi-dimensional analytical engine that processes price action, volume dynamics, cyclical patterns, and statistical anomalies to generate standardized z-scores that measure how far current market behavior deviates from established norms. Unlike traditional single-metric indicators that examine price through one lens, this dashboard constructs a comprehensive probabilistic model by weighting and combining six distinct analytical domains: Ehlers bandpass filtering for cycle detection, momentum calculations across multiple timeframes, mean reversion tendencies, trend strength measurements, volatility regime analysis, and volume confirmation signals.
The indicator operates by first calculating individual scores across each of these six domains, normalizing them into comparable z-score formats, then applying user-configurable weights to create a composite probability score that estimates the likelihood of upward price movement. This probability undergoes statistical transformation through hyperbolic tangent functions to ensure bounded outputs between zero and one, which are then compared against historical baselines to generate the final z-score reading. The z-score itself becomes the primary signal, indicating not just direction but the statistical significance of the current market state relative to recent history. When the z-score exceeds predefined thresholds, it suggests the market has entered a regime that statistically differs from the baseline, implying either strong momentum continuation or potential exhaustion depending on accompanying contextual indicators.
The dashboard visualization provides traders with immediate access to critical information through a comprehensive table display that shows historical z-scores over the past five days, current probability assessments, trend classification, momentum measurements, acceleration metrics, and distance from moving averages. This multi-temporal perspective allows traders to observe not just the current state but the trajectory of change, identifying whether momentum is building, plateauing, or reversing. The indicator also generates regime classifications such as "PARABOLIC EXT," "OVERSOLD," "STRONG MOM," and "NEUTRAL," which combine z-score readings with price extension metrics to characterize the current market environment. These classifications directly inform suggested actions, ranging from "Ride trend w/ stops" during strong momentum periods to "Watch for reversal" during oversold conditions with increasing momentum, providing traders with contextually appropriate strategic guidance.
The Special Nature of This Analytical Approach
What distinguishes the Z-Score Momentum Dashboard from conventional technical indicators is its fundamental philosophical approach to market analysis, which embraces probabilistic thinking rather than deterministic prediction. Most traditional indicators generate binary signals or directional recommendations based on threshold crossovers or pattern recognition, implicitly suggesting certainty about future price movement. This dashboard, in contrast, explicitly models uncertainty by generating probability distributions and measuring statistical significance, acknowledging that markets are stochastic systems where edge comes from systematic bias rather than predictive certainty. By converting diverse technical signals into standardized z-scores, the indicator creates a common language for comparing fundamentally different types of market information, whether that information comes from price momentum, volume patterns, or cyclical oscillations.
The pseudo-machine learning architecture embedded within the indicator represents another distinctive feature that elevates it beyond standard technical analysis tools. While Pine Script limitations prevent the implementation of actual neural networks or gradient-boosted decision trees, the indicator approximates ensemble learning principles by treating each analytical domain as a separate "model" whose outputs are weighted and combined. Users can adjust these weights based on their market beliefs or through backtesting optimization, effectively training the indicator to emphasize whichever analytical dimensions prove most predictive in their specific trading context. This flexibility means the same indicator can be configured for mean-reversion trading in range-bound markets by increasing mean reversion weights, or for momentum trading in trending markets by emphasizing trend and momentum components, making it adaptable across varying market regimes without requiring entirely different analytical tools.
The integration of John Ehlers' digital signal processing concepts, particularly the bandpass filtering and super smoother functions, introduces engineering-grade analytical precision to financial market analysis. Ehlers' work translates aerospace and telecommunications signal processing mathematics into trading applications, allowing the indicator to isolate specific cyclical frequencies within price action while filtering out noise. This is fundamentally different from simple moving averages or oscillators that indiscriminately smooth price data; bandpass filters can extract the 10-day cycle component separately from the 20-day cycle component, identifying when multiple cycles align or diverge. The inclusion of these sophisticated filters alongside more conventional tools creates a hybrid analytical framework that combines the mathematical rigor of quantitative finance with the practical market wisdom embedded in traditional technical analysis.
The dashboard's temporal analysis capabilities provide another layer of analytical depth rarely found in standalone indicators. By displaying five days of historical z-scores alongside current readings, the interface enables pattern recognition at the signal level rather than just the price level. Traders can observe whether z-scores are trending, oscillating, or demonstrating divergent behavior relative to price action. For instance, if price continues making new highs while z-scores decline, this suggests deteriorating statistical support for the advance despite superficial price strength, providing early warning of potential reversals. Similarly, rising z-scores during price consolidation indicate building statistical pressure that may soon manifest as directional movement. This meta-analytical capability transforms the indicator from a simple signal generator into a comprehensive framework for understanding the statistical character of market behavior.
Algorithmic Superiority and Technical Advantages
The algorithmic architecture of the Z-Score Momentum Dashboard demonstrates several technical advantages that contribute to its analytical power and practical utility. The normalization of disparate technical indicators into standardized z-scores solves a fundamental problem in multi-factor analysis: how to combine indicators with different scales and units into a coherent composite signal. A momentum reading measured in price points cannot be directly compared to an RSI reading measured on a 0-100 scale, nor to a volume ratio measured as a multiplier. By converting each measure into a z-score representing standard deviations from its respective mean, the indicator creates dimensional consistency, ensuring that each component contributes proportionally to the final composite score based on its statistical deviation rather than its nominal value.
The use of adaptive baselines through rolling statistical windows provides robustness against regime changes and non-stationary market behavior. Rather than comparing current readings against fixed historical values or statically defined overbought/oversold levels, the indicator continuously recalculates mean and standard deviation estimates over the user-defined baseline period. This approach automatically adjusts to changing volatility regimes, market cycles, and structural shifts in price behavior. During high-volatility periods, the standard deviation increases, requiring larger absolute deviations to generate extreme z-scores, appropriately raising the bar for signal generation. Conversely, during low-volatility periods, smaller absolute movements can generate significant z-scores, maintaining signal sensitivity across diverse market conditions.
The composite probability calculation employs mathematically sound transformation functions rather than arbitrary scaling. After weighting and combining individual z-scores into a composite score, the indicator applies hyperbolic tangent transformation to convert the unbounded composite score into a bounded probability estimate between zero and one. The tanh function was chosen specifically because its sigmoid-shaped curve smoothly compresses extreme values while maintaining sensitivity around the center, preventing outlier distortion while preserving information about moderate deviations. This is superior to linear scaling or simple threshold clamping, which can create artificial discontinuities or lose information about the magnitude of extreme readings. The subsequent z-score calculation on this probability distribution creates a second-order statistical metric that measures not just "is probability high?" but "is probability statistically significantly higher than typical?" This layered statistical approach provides more nuanced information than single-stage calculations.
The incorporation of acceleration metrics alongside momentum measurements adds a crucial dimension to the analytical framework. While momentum measures the first derivative of the z-score (rate of change), acceleration measures the second derivative (rate of change of the rate of change), identifying inflection points where momentum itself shifts. Markets often reverse not when momentum reaches zero but when acceleration reverses, as this indicates the rate of momentum decay is accelerating even while momentum remains positive. By explicitly calculating and displaying acceleration, the indicator provides early warning of potential trend exhaustion before momentum fully dissipates. This mathematical sophistication mirrors concepts from physics and calculus, applying them to financial market dynamics in ways that enhance predictive capability.
The multi-timeframe momentum analysis embedded within the indicator examines price changes over five, ten, and twenty periods, capturing different temporal scales of market behavior. Short-term momentum captures immediate price action and trading range dynamics, while longer-term momentum reflects sustained directional bias and major trend development. By combining these timeframes into a weighted average before calculating z-scores, the indicator synthesizes information across temporal scales, avoiding the myopia of single-timeframe analysis. This approach recognizes that market structure exists simultaneously at multiple frequencies, and robust signals often emerge when momentum aligns across timeframes, while divergences between timeframes can signal pending reversals or consolidations.
Predictive Power Through Cyclical Analysis
The integration of cyclical analysis into the Z-Score Momentum Dashboard represents one of its most powerful predictive capabilities, leveraging the empirical observation that financial markets exhibit periodic behavior driven by fundamental economic cycles, seasonal patterns, trader psychology, and technical feedback loops. The Ehlers bandpass filters implemented in the indicator specifically isolate cyclical components at 10, 15, and 20-day periods, frequencies that correspond to common trading cycles including bi-weekly, monthly, and quarterly rhythms in market activity. By extracting these specific frequency bands and measuring their slope, the indicator identifies when cycles are aligned in the same directional phase versus when they are diverging, with aligned cycles providing stronger predictive signals than single-frequency readings.
Cyclical analysis offers predictive power because cycles, by definition, have characteristic wavelengths that enable forecasting of future turning points based on the current phase. If the indicator detects that the 10-day cycle is in a trough phase while the 20-day cycle is also declining, it can anticipate that the shorter cycle should begin turning upward before the longer cycle, potentially creating a bullish divergence or early reversal signal. Conversely, when a shorter cycle reaches a peak while longer cycles continue rising, this suggests the current rally may consolidate before the longer-cycle momentum can drive new highs. This phase relationship analysis transforms cyclical information from descriptive to predictive, allowing traders to position ahead of probable turning points rather than merely reacting to them.
The bandpass filtering approach is particularly valuable because it separates signal from noise more effectively than conventional smoothing techniques. Traditional moving averages suppress both high-frequency noise and the actual signal being measured, creating lag and reducing responsiveness. Bandpass filters, in contrast, selectively attenuate frequencies outside the target band while preserving amplitude and phase information within the band, maintaining the timing and magnitude of the actual cyclical component. This means when the bandpass output changes, it reflects genuine change in the underlying cycle rather than random noise or smoothing artifacts. The z-score normalization of bandpass slopes then measures whether the current cyclical momentum is statistically unusual relative to recent history, identifying periods when cyclical forces are particularly strong or weak.
The integration of Fisher Transform calculations further enhances cyclical predictive power by converting price oscillations into a nearly Gaussian probability distribution. Financial price data typically exhibits non-normal distributions with fat tails and skewness, which violate the assumptions underlying many statistical techniques. The Fisher Transform specifically addresses this by mapping the price data onto a normal distribution where standard statistical inference tools work more reliably. When applied to cyclical data, this transformation makes it possible to accurately assess the statistical significance of cycle phases and turning points, distinguishing between normal cyclical oscillation and statistically significant deviations that may precede major price movements.
The Schaff Trend Cycle component adds another dimension to cyclical analysis by combining MACD calculations with stochastic smoothing to identify trending phases within broader cyclical structures. Markets often exhibit fractal behavior where trends exist within cycles which exist within larger trends. The Schaff indicator specifically addresses this nested structure by detecting when shorter-term trends are emerging within the dominant cycle, providing early identification of trend changes before they become apparent in price action. When the Schaff reading aligns with bandpass filter signals and overall z-score direction, it confirms that multiple analytical perspectives agree on current cyclical phase, increasing confidence in directional predictions.
The Detrended Price Oscillator (DPO) calculation removes trend components to isolate pure cyclical behavior, addressing a common challenge in cyclical analysis where strong trends can mask underlying cycles. By comparing current price to a centered moving average, the DPO reveals cyclical patterns that persist regardless of trend direction, allowing the indicator to maintain cyclical awareness in both trending and ranging markets. This is particularly valuable because cycles often continue operating during trends but become invisible to trend-following indicators, yet these cycles can predict pullbacks, consolidations, and acceleration phases within the larger trend. The incorporation of DPO signals into the composite z-score calculation ensures that cyclical information contributes to the final reading even when dominated by strong directional momentum.
Practical Trading Application and Strategic Implementation
Implementing the Z-Score Momentum Dashboard in practical trading requires understanding both its signal generation logic and the appropriate strategic frameworks for acting on its outputs. The primary trading signal comes from the overall z-score reading relative to the trigger and extreme thresholds, which by default are set at 1.25 and 2.0 respectively. When the z-score exceeds the trigger threshold, it indicates that current market behavior is more than 1.25 standard deviations above the recent baseline, suggesting statistically significant bullish momentum. Traders can interpret this as a regime shift from neutral to bullish conditions, warranting either initiation of long positions or continuation of existing long exposure with trailing stops. The strength of this signal increases when the z-score crosses the extreme threshold, indicating the market has entered a parabolic phase that, while statistically unusual, may represent either climactic buying or unsustainable conditions prone to mean reversion.
The regime classifications provide contextual interpretation that modifies how traders should approach z-score signals. A z-score above the trigger threshold combined with moderate price extension from the 20-period moving average generates a "STRONG MOM" regime classification with the recommended action "Ride trend w/ stops," suggesting that traders should maintain directional exposure while using trailing stop-loss orders to protect profits if momentum reverses. In contrast, a z-score above the trigger threshold but with extreme price extension generates a "PARABOLIC EXT" classification with the action "Mean rev UP expected," warning that despite strong statistical momentum, the price has deviated too far from its moving average and may soon consolidate or reverse toward the mean. This nuanced interpretation prevents traders from blindly chasing extended moves even when z-scores remain elevated.
The trend classification system—identifying RISING, FALLING, BOTTOMING, and TOPPING patterns—provides crucial information about the trajectory of statistical momentum rather than just its current level. A RISING classification indicates that not only is the z-score positive, but it has been consistently increasing over recent periods, suggesting accelerating momentum and increasing statistical support for directional movement. Traders can use this to distinguish between stable momentum that may continue and deteriorating momentum that may reverse, informing position sizing and stop-loss placement decisions. BOTTOMING and TOPPING classifications specifically identify potential inflection points where the direction of z-score movement is changing, generating early reversal signals before z-scores cross back through neutral territory.
For mean reversion traders, the indicator provides exceptional value when z-scores reach extreme negative levels (below -2.0) while showing BOTTOMING trend patterns and positive acceleration. This combination suggests that statistical momentum has reached an extreme oversold condition and is beginning to reverse, creating favorable risk-reward opportunities for counter-trend long positions. The extension metric provides additional confirmation, as extreme negative extension from the moving average creates mechanical pull toward the mean independent of momentum considerations. Traders can enter positions when these factors align, using the moving average as an initial profit target and the z-score returning to neutral as a signal for position closure or transition to trend-following mode.
For trend-following traders, the indicator is most valuable when z-scores remain elevated above the trigger threshold for extended periods with RISING or stable trend patterns and positive momentum readings. This indicates persistent statistical support for the trend rather than a temporary spike, justifying larger position sizes and wider stop-loss placement. The momentum and acceleration metrics help trend followers distinguish between healthy trends with sustained momentum and exhausted trends where momentum is decelerating, allowing for timely exit before reversals occur. When momentum and acceleration both turn negative while z-scores remain positive, it signals that the statistical foundation of the trend is eroding even though the trend nominally persists, prompting trend followers to tighten stops or take partial profits.
The component scores displayed in the dashboard enable advanced traders to perform qualitative analysis of what factors are driving the composite z-score reading. If the composite z-score is positive but the breakdown shows that bandpass and momentum scores are negative while mean reversion scores are strongly positive, this indicates that the bullish reading is driven primarily by oversold mean reversion potential rather than directional momentum. Traders can use this information to adjust their trading approach, perhaps favoring short-term reversal trades over longer-term trend follows. Conversely, if all components show aligned readings, it suggests broad-based agreement across analytical dimensions, increasing confidence in the signal and potentially warranting larger position sizes or longer holding periods.
Integration with broader trading systems can enhance the indicator's effectiveness. Traders might use the z-score as a filter for other strategies, taking long signals from separate systems only when the z-score is positive or trading reversal patterns only when z-scores are extreme. Alternatively, the indicator can serve as a portfolio allocation tool, increasing equity exposure when z-scores are positive and reducing exposure or shifting to defensive positions when z-scores turn negative. The probability estimates can be directly incorporated into Kelly Criterion or other position sizing formulas, scaling position sizes proportionally to the estimated probability of upward movement adjusted for risk-reward ratios of specific trade setups.
Alert conditions built into the indicator provide automated monitoring capabilities, notifying traders when z-scores cross critical thresholds or when trend patterns change from FALLING to BOTTOMING or RISING to TOPPING. These alerts enable traders to monitor multiple instruments without constant chart watching, maintaining awareness of regime changes across a diversified portfolio. The alerts for extreme z-scores specifically warn of potential climactic conditions that may require immediate attention, whether to take profits on existing positions or to prepare for reversal opportunities.
The customization options allow traders to optimize the indicator for specific instruments and market conditions. The baseline period parameter controls the lookback window for calculating statistical norms, with shorter periods making the indicator more responsive to recent conditions at the cost of increased noise, while longer periods provide stability but slower adaptation to regime changes. The weight parameters enable traders to emphasize whichever analytical dimensions prove most predictive in their specific markets, potentially increasing trend weights for strongly trending instruments like technology stocks while increasing mean reversion weights for range-bound commodities or currencies. Through systematic backtesting and forward validation, traders can develop instrument-specific configurations that maximize the indicator's predictive accuracy.
Ultimately, the Z-Score Momentum Dashboard functions most effectively as a comprehensive analytical framework rather than a standalone trading system, providing rich statistical context that enhances decision-making across diverse trading approaches. Whether used for discretionary trade timing, systematic signal generation, risk management, or portfolio allocation, the indicator's multi-dimensional analysis, cyclical awareness, and probabilistic framework offer traders a sophisticated tool for understanding and responding to statistical patterns in market behavior that persist across timeframes, instruments, and market regimes.
FX Rate Bias US vs EU 2YFX Rate Bias – US vs EU (2Y)
This indicator implements a rate-differential based macro bias model using the 2-year government bond yield spread between the United States and Germany.
The methodology focuses on the short end of the yield curve, which primarily reflects central bank expectations rather than long-term inflation or risk premiums.
By applying light smoothing and a zero-line regime framework, the script classifies market conditions into USD rate advantage or EUR rate advantage states.
Calculation logic:
Retrieves daily 2Y sovereign yields for the US and Germany
Computes the yield differential (US − DE)
Applies optional smoothing to reduce noise
Uses the zero line as a regime boundary to define relative monetary bias
Practical use:
This tool is designed to provide directional macro context for FX analysis, particularly for EURUSD.
It helps traders align technical setups with prevailing interest rate expectations, and is not intended as a standalone signal or timing indicator.
