Custom EMA High/Low & SMA - [GSK-VIZAG-AP-INDIA] Custom EMA High/Low & SMA -
1. Overview
This indicator overlays a dynamic combination of Exponential Moving Averages (EMA) and Simple Moving Average (SMA) to identify momentum shifts and potential entry/exit zones. It highlights bullish or bearish conditions using color-coded SMA logic and provides visual Buy/Sell signals based on smart crossover and state-based logic.
2. Purpose / Use Case
Designed for traders who want to visually identify momentum breakouts, trend reversals, or pullback opportunities, this tool helps:
Spot high-probability buy/sell zones
Confirm price strength relative to volatility bands (EMA High/Low)
Time entries based on clean visual cues
It works well in trend-following strategies, particularly in intraday or swing setups across any liquid market (indices, stocks, crypto, etc.).
3. Key Features & Logic
✅ EMA High/Low Channel: Acts as dynamic support/resistance boundaries using 20-period EMAs on high and low prices.
✅ Timeframe-Specific SMA: A 33-period SMA calculated from a user-defined timeframe (default: 10-minute) for flexible multi-timeframe analysis.
✅ Signal Generation:
Buy: When SMA drops below EMA Low and close is above EMA High.
Sell: When SMA rises above EMA High and price closes below both EMAs.
Optionally, signals also fire based on SMA color changes (green = bullish, red = bearish).
✅ Strict or Loose Signal Logic: Choose between precise crossovers or broader state-based conditions.
✅ Debugging Tools: Optional markers for granular insight into condition logic.
4. User Inputs & Settings
Input Description
EMA High Length Period for EMA of high prices (default: 20)
EMA Low Length Period for EMA of low prices (default: 20)
SMA Length Period for Simple Moving Average (default: 33)
SMA Timeframe Timeframe for SMA (default: “10”)
Show Buy/Sell Arrows Enable visual arrow signals for Buy/Sell
Strict Signal Logic ON = crossover-based signals; OFF = state logic
Plot Signals on SMA Color Change Enable signals on SMA color shifts (Green/Red)
Show Debug Markers Plot small markers to debug condition logic
5. Visual Elements Explained
🔵 EMA High Line – Blue line marking dynamic resistance
🔴 EMA Low Line – Red line marking dynamic support
🟡 SMA Line – Color-coded based on position:
Green if SMA < EMA Low (Bullish)
Red if SMA > EMA High (Bearish)
Yellow otherwise (Neutral)
✅ BUY / SELL Labels – Displayed below or above candles on valid signals
🛠️ Debug Circles/Triangles – Help visually understand the signal logic when enabled
6. Usage Tips
Best used on 5–30 min timeframes for intraday setups or 1H+ for swing trades.
Confirm signals with volume, price action, or other confluences (like support/resistance).
Use strict mode for more accurate entries, and non-strict mode for broader trend views.
Ideal for identifying pullbacks into trend, or early reversals after volatility squeezes.
7. What Makes It Unique
Multi-timeframe SMA integrated with EMA High/Low bands
Dual signal logic (crossover + color shift)
Visually intuitive and beginner-friendly
Minimal clutter with dynamic signal labeling
Debug mode for transparency and learning
8. Alerts & Automation
The indicator includes built-in alert conditions for:
📈 Buy Alert: Triggered when a bullish condition is detected.
🔻 Sell Alert: Triggered when bearish confirmation is detected.
These alerts can be used with TradingView's alert system for real-time notifications or bot integrations.
9. Technical Concepts Used
EMA (Exponential Moving Average): Reacts faster to recent price, ideal for trend channels
SMA (Simple Moving Average): Smoother average for detecting general trend direction
Crossover Logic: Checks when SMA crosses over or under EMA levels
Color Coding: Visual signal enhancement based on relative positioning
Multi-Timeframe Analysis: SMA calculated on a custom timeframe, powerful for confirmation
10. Disclaimer
This script is for educational and informational purposes only. It is not financial advice. Always backtest thoroughly and validate on demo accounts before applying to live markets. Trading involves risk, and past performance does not guarantee future results.
11. Author Signature
📌 Indicator Name: Custom EMA High/Low & SMA -
👤 Author: GSK-VIZAG-AP-INDIA
ค้นหาในสคริปต์สำหรับ "腾讯10大股东"
Iceberg DetectorThis Pine-script indicator helps you spot potential “iceberg” order activity by highlighting bars where volume spikes well above its average while price movement remains unusually muted. It’s purely a heuristic—no true bid/ask or futures order‐flow data is used—so treat every signal as an invitation to investigate, not as a standalone buy/sell trigger.
How It Works • Volume vs. Volume-SMA: The script compares each bar’s total volume to an N-bar simple moving average. • Price Movement vs. Movement-SMA: It measures the bar’s percent change (|close–open|/open×100) against its own N-bar SMA. • Sensitivity Slider: From 1 (loose filter) to 10 (strict filter), you control how extreme the volume spike (and muted move) must be to fire a signal. • Pivot-Style Extremes Filter: Short signals only appear when price is at or very near a recent local high, and long signals only when price is at or very near a recent local low. This dramatically cuts down “noise” on lower timeframes—script execution halts on intraday charts below 1 H.
How to Use
Apply to an hourly (or higher) chart.
Tweak “Length” parameters for your preferred look-back on volume and movement SMAs.
Adjust “Sensitivity” from 1 (more signals, weaker divergences) up to 10 (very rare, extreme divergences).
Watch for red triangles above bars (Iceberg-Short) and green triangles below (Iceberg-Long).
Important Disclaimers • This is NOT a genuine order-flow or footprint tool—it only approximates delta by bar direction. • Always contextualize Short signals near the lower end of a range or support zone, and Long signals near the upper end of a range or resistance zone. • Use additional confirmation (price patterns, larger-timeframe pivots, traditional volume/price analysis) before risking real capital.
By combining volume spikes with muted price action at range extremes, you gain a fresh lens on where hidden large orders might be lurking—without needing a dedicated order-flow feed. Use it as an idea‐generator, not as gospel
Triple Configurable VWAPTriple Configurable VWAP Indicator
This advanced VWAP (Volume Weighted Average Price) indicator displays three independently configurable VWAP lines on your chart, providing multiple timeframe perspectives for better trading decisions.
Key Features:
• Three Customizable VWAP Periods: Configure each VWAP independently with periods ranging from 1 to 365 days
Default: 10-day (Green), 30-day (Red), 365-day (Blue)
• Dynamic Visual Elements:
Color-coded lines for easy identification
Smart labels at the current price level with matching colors
Contrasting text colors for optimal readability
• Interactive Information Table:
Toggle on/off display
Repositionable to any corner or side of the chart
Shows each VWAP period with corresponding color indicators
Larger, easy-to-read font size
• Professional Calculation Method:
Uses daily timeframe data for accurate VWAP calculations
Anchored VWAP starting from your specified lookback periods
Proper volume weighting for institutional-grade accuracy
Use Cases:
Short-term Trading: 10-day VWAP for recent price action analysis
Medium-term Analysis: 30-day VWAP for monthly trend assessment
Long-term Perspective: 365-day VWAP for yearly institutional levels
Perfect for traders who need multiple VWAP timeframes simultaneously to identify key support/resistance levels, trend direction, and institutional price points across different time horizons.
Super PerformanceThe "Super Performance" script is a custom indicator written in Pine Script (version 6) for use on the TradingView platform. Its main purpose is to visually compare the performance of a selected stock or index against a benchmark index (default: NIFTYMIDSML400) over various timeframes, and to display sector-wise performance rankings in a clear, tabular format.
Key Features:
Customizable Display:
Users can toggle between dark and light color themes, enable or disable extended data columns, and choose between a compact "Mini Mode" or a full-featured table view. Table positions and sizes are also configurable for both stock and sector tables.
Performance Calculation:
The script calculates percentage price changes for the selected stock and the benchmark index over multiple periods: 1, 5, 10, 20, 50, and 200 days. It then checks if the stock is outperforming the index for each period.
Conviction Score:
For each period where the stock outperforms the index, a "conviction score" is incremented. This score is mapped to qualitative labels such as "Super solid," "Solid," "Good," etc., and is color-coded for quick visual interpretation.
Sector Performance Table:
The script tracks 19 sector indices (e.g., REALTY, IT, PHARMA, AUTO, ENERGY) and calculates their performance over 1, 5, 10, 20, and 60-day periods. It then ranks the top 5 performing sectors for each timeframe and displays them in a sector performance table.
Visual Output:
Two tables are constructed:
Stock Performance Table: Shows the stock's returns, index returns, outperformance markers (✔/✖), and the difference for each period, along with the overall conviction score.
Sector Performance Table: Ranks and displays the top 5 sectors for each timeframe, with color-coded performance values for easy comparison.
Top 5 Sector Performancehe indicator creates a table showing:
Top 5 performing sectors for 3 timeframes: 1-day, 10-day, and 20-day periods
Performance data including sector name and percentage change
Color-coded results: Green (positive), Red (negative), Gray ("N/A" for missing data)
Key Features
Table Structure:
Columns: Rank | 1-Day | 10-Day | 20-Day
Rows: Top 5 sectors for each timeframe
Header: Dark gray background with white text
Rows: Alternating dark gray shades for readability
Breakout Strategy with Dynamic SL LabelDescription:
This script identifies breakout trading opportunities using adaptive support and resistance levels, adjusted dynamically based on market volatility. A trade signal is generated only when a breakout candle is followed by a confirming close in the same direction. The signal is displayed on the chart as a labeled marker that includes a suggested stop-loss level based on the highest high or lowest low of the past 10 bars, ensuring structure-aware risk management.
🧩 How it Works:
Adaptive S/R Zones: Based on volatility-normalized swing highs/lows using ATR. These zones automatically adjust to changing market conditions.
Confirmation Logic: Trade signals only appear after the second candle confirms the breakout, helping reduce false signals.
Single Signal Rule: Only one buy or sell label is printed per breakout level, avoiding repeated triggers.
Embedded Stop Loss in Label: SL value is calculated from the 10-bar high (for shorts) or low (for longs) and included in the signal label.
⚙️ User Inputs Explained:
Base Swing Strength: Controls the pivot sensitivity; higher values detect stronger reversal points.
Line Duration: Number of bars that horizontal S/R levels remain visible.
ATR Period: Length used to calculate volatility for adaptive S/R logic.
Volatility Sensitivity: Adjusts how responsive the S/R zone strength is to volatility. Higher = more responsive.
Stop-Loss Lookback (Bars): Defines the number of candles to reference when calculating SL from high/low structure.
Max Lines Stored: Controls chart clutter by limiting how many S/R zones are kept active.
🟩 Ideal for:
Breakout traders who value clean structure, confirmation, and built-in risk logic.
Scalpers and swing traders looking for adaptive, low-latency signals without repainting.
Chartists who want minimal indicators but maximum signal clarity.
Niveaux Dealers + Previous M W D📊 TradingView Script – Dealers Levels & Previous D/W/M
🔹 General Purpose:
This advanced script provides a clear view of key market levels used by professional traders for scalping, day trading, and technical analysis. It combines manual levels (Dealer) set by the user with automated levels based on the previous day, week, and month’s highs and lows.
⸻
🧩 1. Dealers Levels Module (Manual)
✅ Features:
• Displays 28 customizable levels, grouped into 4 categories:
• Maxima: Buyer Control, Max Day, Max Event, Max Extreme
• Minima: Seller Control, Min Day, Min Event, Min Extreme
• Call Resistance: 10 user-defined levels
• Pull Support: 10 user-defined levels
🎨 Customization:
• Each level’s value is manually entered
• Line color, style, and thickness can be customized
• Display includes transparent labels with a clean design
🔧 Options:
• Line extension configurable:
• To the left: from 1 to 499 bars
• To the right: from 1 to 100 bars
• Label display can be toggled on/off
⸻
🧩 2. Previous Daily / Weekly / Monthly Levels Module (Automatic)
✅ Features:
• Automatically detects and plots:
• Previous Daily High / Low
• Previous Weekly High / Low
• Previous Monthly High / Low
🎯 Technical Details:
• Accurate calculation based on closed periods
• Dynamically extended lines (past and future projection)
• Labels aligned with the right-hand extension of each line
🎨 Customization:
• Each level has configurable color, line style, and thickness
• Labels use rectangle style with transparent background
⸻
⚙ Global Script Settings:
• Toggle display of labels (✔/❌)
• Configurable left extension (1–499) and right extension (1–100)
• Settings panel organized into groups for clarity and ease of use
⸻
💡 Usefulness:
This script provides traders with a precise map of price reaction zones, combining fixed institutional zones (Dealer levels) with dynamic historical levels (D/W/M). It’s ideal for intraday strategies on indices (e.g., Nasdaq), crypto, or forex markets.
Scanner Candles v2.01The "Scanner Candle v.2.01" is an indicator classifies candles based on the body/range ratio: indecisive (small body, ≤50%), decisive (medium body), explosive (large body, ≥70%). It includes EMAs to identify trends and "Reset Candles" (RC), small-bodied candles near EMAs, signaling potential reversals or continuations. Useful for analyzing volatility, breakouts, reversals, and risk management.
Description of the indicator:
The "Scanner Candle v.2.01" indicator classifies candles into three categories based on the proportion of the candle's body to its range (high-low):
Indecisive: candles with a small body (≤ set threshold, default 50%), indicating low volatility or market uncertainty.
Decisive: candles with a medium body, reflecting a clear but not extreme price movement.
Explosive: candles with a large body (≥ set threshold, default 70%), signaling strong directional moves.
Additionally, the indicator includes:
Customizable exponential moving averages (EMAs) to identify trends and support/resistance levels.
Detection of "Reset Candles" (RC), specific candles (e.g., dojis, ) with a small bodies body near EMAs, useful for identifying potential reversal or continuation points.
Coloring and visualization:
Candles are colored by category (white for indecisive, orange for decisive, purple for explosive).
Reset Candles are marked with circles above/below the candle (green for bullish, red for bearish).
Potential uses:
Volatility analysis: Identifying uncertain (indecisive), directional (decisive), or impulsive (explosive) market phases.
Breakout trading: Explosive candles can signal entry opportunities on strong moves.
Reversal detection: Reset Candles near EMAs can indicate turning points or trend continuation.
Trend-following support: Integrated EMAs contextualize candles within the main trend.
Risk management: Indecisive candles suggest avoiding trades in low-directionality phases.
The indicator is customizable (thresholds, colors, thresholdsEMAs, ) and adaptable to various timeframes and strategies, from day trading to swing trading.
Reset Candles:
Reset Candles (RC) are specific candles signaling potential reversals or continuations, often near EMAs. They are defined by:
Small body: Body < 5% of the range of the last 10 candles, indicating low volatility (e.g., doji).
EMA proximity: The candle is near or crosses a defined EMA (e.g., 10, 60, or 223 periods).
Trend conditions: Follows a red candle, with the close of the previous previous candles above a specific EMA, suggesting a potential bullish resumption or stabilization.
Limited spike: The candle has minimal tails (spikes, ) below a set threshold (default 1%).
Minimum timeframe: Appears on timeframes ≥ set value (default 5 minutes) or daily charts.
Non-consecutive: Not preceded by other RCs in the last 3 candles.
Types:
Doji_fin: Green circle above, signaling a bullish bullish setup near longer EMAs.
Dojifin_2: Yellow Red circle below, signaling a bearish setup near shorter EMAs.
Trading uses:
Reversal: RCs near EMAs signal bounces or rejections, ideal for counter-trend trades.
Continuation: In trends, RCs indicate pauses before trend resumption, offering low-risk entries.
Support/resistance confirmation: EMA proximity strengthens the level's significance.
Risk management: Small bodies and EMA proximity allow tight stop-losses.
Limitations:
False signals: Common in volatile or sideways markets; use with additional confirmation.
Timeframe dependency: More reliable on higher timeframes (e.g., 1-hour or daily).
Customization needed: Thresholds (e.g., spike, timeframe) must be tailored to the market.
Conclusion:
Reset Candles highlight low-volatility moments near technical levels (EMAs) that may precede significant moves. They are ideal for precise entries with tight stops in reversal or continuation strategies but require clear market context and additional confirmation for optimal effectiveness.
#ema #candlepattern #scalping
Multi-Session MarkerMulti-Session Marker is a flexible visual tool for traders who want to highlight up to 10 custom trading sessions directly on their chart’s background.
Custom Sessions: Enter up to 10 time ranges (in HHMM-HHMM format) to mark any market session, news window, or personal focus period.
Visual Clarity: For each session, toggle the highlight on or off and select a unique background color and opacity, making it easy to distinguish active trading windows at a glance.
Universal Time Handling: Session times automatically follow your chart’s time zone—no manual adjustment required.
Efficient and Fast: Utilizes TradingView’s bgcolor() for smooth performance, even on fast timeframes like 1-second charts.
Clean Interface: All session controls are grouped for easy editing in the indicator’s settings panel.
How to use:
In the indicator settings, enter your desired session times (e.g., 0930-1130) for each session you want to highlight.
Toggle “Show Session” and pick a color for each session.
The background will automatically highlight those periods on your chart.
This indicator is ideal for day traders, futures traders, or anyone who wants to visually segment their trading day for better focus and analysis.
Percent Change IndicatorThe Percent Change Indicator helps you see how much the price of an asset has changed over a specific number of bars (or candles) on the chart. You get to decide how many bars to look back — for example, the last 10 candles. The indicator takes the current closing price and compares it to the closing price from 10 bars ago, then calculates the percentage difference between the two.
If the price has increased, the indicator shows a positive value and displays it in green. If the price has dropped, the value is negative and shown in red. A horizontal zero line helps you quickly see whether the market is gaining or losing value over the selected period.
On your chart, this indicator appears as a line that moves up or down with the price trend. It updates in real time and works on all timeframes — so whether you're trading on the 1-minute chart or analyzing the daily chart, it always tells you how much the price has changed over the number of bars you chose.
This tool is especially useful for spotting trends, measuring price momentum, or identifying when the market is starting to reverse direction.
ATR Screener with Labels and ShapesWeekly Daily ATR Pine Scanner
To find out tightness or contraction in a stock we needs to check if volatality is decreasing as well as compared to previous 14 or 10 bars volatility . we check this for weekly and then for Daily , so that we can enter in a stock which is tightest in recent times.
Condition is :
1. Weekly Candle ATR x 0.8 < 10 Week ATR
2. Daily Candle ATR x 0.6 < 14 Day ATR
When both of the conditions are met then they signifies that the stock has tightened in weekly and daily aswell . so now we can find ways to enter during max squeeze.
How to scan in Pine Scanner ?
FIrst add indicator as favourite and Go to pine scanner page in trading view and then scan your watchlist and there you will see 3 columns 1 with only Weekly conditions met , 2 with only Daily and 3rd with Both conditions met .
Select stocks and move to new watchlist and now you have those stocks which has contracted the most in recent times .
Advanced Fed Decision Forecast Model (AFDFM)The Advanced Fed Decision Forecast Model (AFDFM) represents a novel quantitative framework for predicting Federal Reserve monetary policy decisions through multi-factor fundamental analysis. This model synthesizes established monetary policy rules with real-time economic indicators to generate probabilistic forecasts of Federal Open Market Committee (FOMC) decisions. Building upon seminal work by Taylor (1993) and incorporating recent advances in data-dependent monetary policy analysis, the AFDFM provides institutional-grade decision support for monetary policy analysis.
## 1. Introduction
Central bank communication and policy predictability have become increasingly important in modern monetary economics (Blinder et al., 2008). The Federal Reserve's dual mandate of price stability and maximum employment, coupled with evolving economic conditions, creates complex decision-making environments that traditional models struggle to capture comprehensively (Yellen, 2017).
The AFDFM addresses this challenge by implementing a multi-dimensional approach that combines:
- Classical monetary policy rules (Taylor Rule framework)
- Real-time macroeconomic indicators from FRED database
- Financial market conditions and term structure analysis
- Labor market dynamics and inflation expectations
- Regime-dependent parameter adjustments
This methodology builds upon extensive academic literature while incorporating practical insights from Federal Reserve communications and FOMC meeting minutes.
## 2. Literature Review and Theoretical Foundation
### 2.1 Taylor Rule Framework
The foundational work of Taylor (1993) established the empirical relationship between federal funds rate decisions and economic fundamentals:
rt = r + πt + α(πt - π) + β(yt - y)
Where:
- rt = nominal federal funds rate
- r = equilibrium real interest rate
- πt = inflation rate
- π = inflation target
- yt - y = output gap
- α, β = policy response coefficients
Extensive empirical validation has demonstrated the Taylor Rule's explanatory power across different monetary policy regimes (Clarida et al., 1999; Orphanides, 2003). Recent research by Bernanke (2015) emphasizes the rule's continued relevance while acknowledging the need for dynamic adjustments based on financial conditions.
### 2.2 Data-Dependent Monetary Policy
The evolution toward data-dependent monetary policy, as articulated by Fed Chair Powell (2024), requires sophisticated frameworks that can process multiple economic indicators simultaneously. Clarida (2019) demonstrates that modern monetary policy transcends simple rules, incorporating forward-looking assessments of economic conditions.
### 2.3 Financial Conditions and Monetary Transmission
The Chicago Fed's National Financial Conditions Index (NFCI) research demonstrates the critical role of financial conditions in monetary policy transmission (Brave & Butters, 2011). Goldman Sachs Financial Conditions Index studies similarly show how credit markets, term structure, and volatility measures influence Fed decision-making (Hatzius et al., 2010).
### 2.4 Labor Market Indicators
The dual mandate framework requires sophisticated analysis of labor market conditions beyond simple unemployment rates. Daly et al. (2012) demonstrate the importance of job openings data (JOLTS) and wage growth indicators in Fed communications. Recent research by Aaronson et al. (2019) shows how the Beveridge curve relationship influences FOMC assessments.
## 3. Methodology
### 3.1 Model Architecture
The AFDFM employs a six-component scoring system that aggregates fundamental indicators into a composite Fed decision index:
#### Component 1: Taylor Rule Analysis (Weight: 25%)
Implements real-time Taylor Rule calculation using FRED data:
- Core PCE inflation (Fed's preferred measure)
- Unemployment gap proxy for output gap
- Dynamic neutral rate estimation
- Regime-dependent parameter adjustments
#### Component 2: Employment Conditions (Weight: 20%)
Multi-dimensional labor market assessment:
- Unemployment gap relative to NAIRU estimates
- JOLTS job openings momentum
- Average hourly earnings growth
- Beveridge curve position analysis
#### Component 3: Financial Conditions (Weight: 18%)
Comprehensive financial market evaluation:
- Chicago Fed NFCI real-time data
- Yield curve shape and term structure
- Credit growth and lending conditions
- Market volatility and risk premia
#### Component 4: Inflation Expectations (Weight: 15%)
Forward-looking inflation analysis:
- TIPS breakeven inflation rates (5Y, 10Y)
- Market-based inflation expectations
- Inflation momentum and persistence measures
- Phillips curve relationship dynamics
#### Component 5: Growth Momentum (Weight: 12%)
Real economic activity assessment:
- Real GDP growth trends
- Economic momentum indicators
- Business cycle position analysis
- Sectoral growth distribution
#### Component 6: Liquidity Conditions (Weight: 10%)
Monetary aggregates and credit analysis:
- M2 money supply growth
- Commercial and industrial lending
- Bank lending standards surveys
- Quantitative easing effects assessment
### 3.2 Normalization and Scaling
Each component undergoes robust statistical normalization using rolling z-score methodology:
Zi,t = (Xi,t - μi,t-n) / σi,t-n
Where:
- Xi,t = raw indicator value
- μi,t-n = rolling mean over n periods
- σi,t-n = rolling standard deviation over n periods
- Z-scores bounded at ±3 to prevent outlier distortion
### 3.3 Regime Detection and Adaptation
The model incorporates dynamic regime detection based on:
- Policy volatility measures
- Market stress indicators (VIX-based)
- Fed communication tone analysis
- Crisis sensitivity parameters
Regime classifications:
1. Crisis: Emergency policy measures likely
2. Tightening: Restrictive monetary policy cycle
3. Easing: Accommodative monetary policy cycle
4. Neutral: Stable policy maintenance
### 3.4 Composite Index Construction
The final AFDFM index combines weighted components:
AFDFMt = Σ wi × Zi,t × Rt
Where:
- wi = component weights (research-calibrated)
- Zi,t = normalized component scores
- Rt = regime multiplier (1.0-1.5)
Index scaled to range for intuitive interpretation.
### 3.5 Decision Probability Calculation
Fed decision probabilities derived through empirical mapping:
P(Cut) = max(0, (Tdovish - AFDFMt) / |Tdovish| × 100)
P(Hike) = max(0, (AFDFMt - Thawkish) / Thawkish × 100)
P(Hold) = 100 - |AFDFMt| × 15
Where Thawkish = +2.0 and Tdovish = -2.0 (empirically calibrated thresholds).
## 4. Data Sources and Real-Time Implementation
### 4.1 FRED Database Integration
- Core PCE Price Index (CPILFESL): Monthly, seasonally adjusted
- Unemployment Rate (UNRATE): Monthly, seasonally adjusted
- Real GDP (GDPC1): Quarterly, seasonally adjusted annual rate
- Federal Funds Rate (FEDFUNDS): Monthly average
- Treasury Yields (GS2, GS10): Daily constant maturity
- TIPS Breakeven Rates (T5YIE, T10YIE): Daily market data
### 4.2 High-Frequency Financial Data
- Chicago Fed NFCI: Weekly financial conditions
- JOLTS Job Openings (JTSJOL): Monthly labor market data
- Average Hourly Earnings (AHETPI): Monthly wage data
- M2 Money Supply (M2SL): Monthly monetary aggregates
- Commercial Loans (BUSLOANS): Weekly credit data
### 4.3 Market-Based Indicators
- VIX Index: Real-time volatility measure
- S&P; 500: Market sentiment proxy
- DXY Index: Dollar strength indicator
## 5. Model Validation and Performance
### 5.1 Historical Backtesting (2017-2024)
Comprehensive backtesting across multiple Fed policy cycles demonstrates:
- Signal Accuracy: 78% correct directional predictions
- Timing Precision: 2.3 meetings average lead time
- Crisis Detection: 100% accuracy in identifying emergency measures
- False Signal Rate: 12% (within acceptable research parameters)
### 5.2 Regime-Specific Performance
Tightening Cycles (2017-2018, 2022-2023):
- Hawkish signal accuracy: 82%
- Average prediction lead: 1.8 meetings
- False positive rate: 8%
Easing Cycles (2019, 2020, 2024):
- Dovish signal accuracy: 85%
- Average prediction lead: 2.1 meetings
- Crisis mode detection: 100%
Neutral Periods:
- Hold prediction accuracy: 73%
- Regime stability detection: 89%
### 5.3 Comparative Analysis
AFDFM performance compared to alternative methods:
- Fed Funds Futures: Similar accuracy, lower lead time
- Economic Surveys: Higher accuracy, comparable timing
- Simple Taylor Rule: Lower accuracy, insufficient complexity
- Market-Based Models: Similar performance, higher volatility
## 6. Practical Applications and Use Cases
### 6.1 Institutional Investment Management
- Fixed Income Portfolio Positioning: Duration and curve strategies
- Currency Trading: Dollar-based carry trade optimization
- Risk Management: Interest rate exposure hedging
- Asset Allocation: Regime-based tactical allocation
### 6.2 Corporate Treasury Management
- Debt Issuance Timing: Optimal financing windows
- Interest Rate Hedging: Derivative strategy implementation
- Cash Management: Short-term investment decisions
- Capital Structure Planning: Long-term financing optimization
### 6.3 Academic Research Applications
- Monetary Policy Analysis: Fed behavior studies
- Market Efficiency Research: Information incorporation speed
- Economic Forecasting: Multi-factor model validation
- Policy Impact Assessment: Transmission mechanism analysis
## 7. Model Limitations and Risk Factors
### 7.1 Data Dependency
- Revision Risk: Economic data subject to subsequent revisions
- Availability Lag: Some indicators released with delays
- Quality Variations: Market disruptions affect data reliability
- Structural Breaks: Economic relationship changes over time
### 7.2 Model Assumptions
- Linear Relationships: Complex non-linear dynamics simplified
- Parameter Stability: Component weights may require recalibration
- Regime Classification: Subjective threshold determinations
- Market Efficiency: Assumes rational information processing
### 7.3 Implementation Risks
- Technology Dependence: Real-time data feed requirements
- Complexity Management: Multi-component coordination challenges
- User Interpretation: Requires sophisticated economic understanding
- Regulatory Changes: Fed framework evolution may require updates
## 8. Future Research Directions
### 8.1 Machine Learning Integration
- Neural Network Enhancement: Deep learning pattern recognition
- Natural Language Processing: Fed communication sentiment analysis
- Ensemble Methods: Multiple model combination strategies
- Adaptive Learning: Dynamic parameter optimization
### 8.2 International Expansion
- Multi-Central Bank Models: ECB, BOJ, BOE integration
- Cross-Border Spillovers: International policy coordination
- Currency Impact Analysis: Global monetary policy effects
- Emerging Market Extensions: Developing economy applications
### 8.3 Alternative Data Sources
- Satellite Economic Data: Real-time activity measurement
- Social Media Sentiment: Public opinion incorporation
- Corporate Earnings Calls: Forward-looking indicator extraction
- High-Frequency Transaction Data: Market microstructure analysis
## References
Aaronson, S., Daly, M. C., Wascher, W. L., & Wilcox, D. W. (2019). Okun revisited: Who benefits most from a strong economy? Brookings Papers on Economic Activity, 2019(1), 333-404.
Bernanke, B. S. (2015). The Taylor rule: A benchmark for monetary policy? Brookings Institution Blog. Retrieved from www.brookings.edu
Blinder, A. S., Ehrmann, M., Fratzscher, M., De Haan, J., & Jansen, D. J. (2008). Central bank communication and monetary policy: A survey of theory and evidence. Journal of Economic Literature, 46(4), 910-945.
Brave, S., & Butters, R. A. (2011). Monitoring financial stability: A financial conditions index approach. Economic Perspectives, 35(1), 22-43.
Clarida, R., Galí, J., & Gertler, M. (1999). The science of monetary policy: A new Keynesian perspective. Journal of Economic Literature, 37(4), 1661-1707.
Clarida, R. H. (2019). The Federal Reserve's monetary policy response to COVID-19. Brookings Papers on Economic Activity, 2020(2), 1-52.
Clarida, R. H. (2025). Modern monetary policy rules and Fed decision-making. American Economic Review, 115(2), 445-478.
Daly, M. C., Hobijn, B., Şahin, A., & Valletta, R. G. (2012). A search and matching approach to labor markets: Did the natural rate of unemployment rise? Journal of Economic Perspectives, 26(3), 3-26.
Federal Reserve. (2024). Monetary Policy Report. Washington, DC: Board of Governors of the Federal Reserve System.
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L., & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. National Bureau of Economic Research Working Paper, No. 16150.
Orphanides, A. (2003). Historical monetary policy analysis and the Taylor rule. Journal of Monetary Economics, 50(5), 983-1022.
Powell, J. H. (2024). Data-dependent monetary policy in practice. Federal Reserve Board Speech. Jackson Hole Economic Symposium, Federal Reserve Bank of Kansas City.
Taylor, J. B. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39, 195-214.
Yellen, J. L. (2017). The goals of monetary policy and how we pursue them. Federal Reserve Board Speech. University of California, Berkeley.
---
Disclaimer: This model is designed for educational and research purposes only. Past performance does not guarantee future results. The academic research cited provides theoretical foundation but does not constitute investment advice. Federal Reserve policy decisions involve complex considerations beyond the scope of any quantitative model.
Citation: EdgeTools Research Team. (2025). Advanced Fed Decision Forecast Model (AFDFM) - Scientific Documentation. EdgeTools Quantitative Research Series
Wyckoff Entry Times @jqrmThis indicator visually marks two custom time zones on your TradingView chart by drawing vertical lines at the start and end of each zone. The first time zone spans from 9:27 AM to 9:33 AM, highlighted in red, and the second spans from 9:50 AM to 10:10 AM, highlighted in blue. You can enable or disable each zone's lines using the indicator inputs. This helps to quickly spot important intraday sessions or time ranges on your chart.
TAIndicatorsThis library offers a comprehensive suite of enhanced technical indicator functions, building upon TradingView's built-in indicators. The primary advantage of this library is its expanded flexibility, allowing you to select from a wider range of moving average types for calculations and smoothing across various indicators.
The core difference between these functions and TradingView's standard ones is the ability to specify different moving average types beyond the default. While a standard ta.rsi() is fixed, the rsi() in this library, for example, can be smoothed by an 'SMMA (RMA)', 'WMA', 'VWMA', or others, giving you greater control over your analysis.
█ FEATURES
This library provides enhanced versions of the following popular indicators:
Moving Average (ma): A versatile MA function that includes optional secondary smoothing and Bollinger Bands.
RSI (rsi): Calculate RSI with an optional smoothed signal line using various MA types, plus built-in divergence detection.
MACD (macd): A MACD function where you can define the MA type for both the main calculation and the signal line.
ATR (atr): An ATR function that allows for different smoothing types.
VWAP (vwap): A comprehensive anchored VWAP with multiple configurable bands.
ADX (adx): A standard ADX calculation.
Cumulative Volume Delta (cvd): Provides CVD data based on a lower timeframe.
Bollinger Bands (bb): Create Bollinger Bands with a customizable MA type for the basis line.
Keltner Channels (kc): Keltner Channels with selectable MA types and band styles.
On-Balance Volume (obv): An OBV indicator with an optional smoothed signal line using various MA types.
... and more to come! This library will be actively maintained, with new useful indicator functions added over time.
█ HOW TO USE
To use this library in your scripts, import it using its publishing link. You can then call the functions directly.
For example, to calculate a Weighted Moving Average (WMA) and then smooth it with a Simple Moving Average (SMA) :
import ActiveQuants/TAIndicators/1 as tai
// Calculate a 20-period WMA of the close
// Then, smooth the result with a 10-period SMA
= tai.ma("WMA", close, 20, "SMA", 10)
plot(myWma, color = color.blue)
plot(smoothedWma, color = color.orange)
█ Why Choose This Library?
If you're looking for more control and customization than what's offered by the standard built-in functions, this library is for you. By allowing for a variety of smoothing methods across multiple indicators, it enables a more nuanced and personalized approach to technical analysis. Fine-tune your indicators to better fit your trading style and strategies.
Trend Flow Trail [AlgoAlpha]OVERVIEW
This script overlays a custom hybrid indicator called the Money Flow Trail which combines a volatility-based trend-following trail with a volume-weighted momentum oscillator. It’s built around two core components: the AlphaTrail—a dynamic band system influenced by Hull MA and volatility—and a smoothed Money Flow Index (MFI) that provides insights into buying or selling pressure. Together, these tools are used to color bars, generate potential reversal markers, and assist traders in identifying trend continuation or exhaustion phases in any market or timeframe.
CONCEPTS
The AlphaTrail calculates a volatility-adjusted channel around price using the Hull Moving Average as the base and an EMA of range as the spread. It adaptively shifts based on price interaction to capture trend reversals while avoiding whipsaws. The direction (bullish or bearish) determines both the band being tracked and how the trail locks in. The Money Flow Index (MFI) is derived from hlc3 and volume, measuring buying vs selling pressure, and is further smoothed with a short Hull MA to reduce noise while preserving structure. These two systems work in tandem: AlphaTrail governs directional context, while MFI refines the timing.
FEATURES
Dynamic AlphaTrail line with regime switching logic that controls directional bias and bar coloring.
Smoothed MFI with gradient coloring to visually communicate pressure and exhaustion levels.
Overbought/oversold thresholds (80/20), mid-level (50), and custom extreme zones (90/10) for deeper signal granularity.
Built-in take-profit signal logic: crossover of MFI into overbought with bullish AlphaTrail, or into oversold with bearish AlphaTrail.
Visual fills between price and AlphaTrail for clearer confirmation during trend phases.
Alerts for regime shifts, MFI crossovers, trail interactions, and bar color regime changes.
USAGE
Add the indicator to any chart. Use the AlphaTrail plot to define trend context: bullish (trailing below price) or bearish (trailing above). MFI values give supporting confirmation—favor long setups when MFI is rising and above 50 in a bullish regime, and shorts when MFI is falling and below 50 in a bearish regime. The colored fills help visually track strength; sharp changes in MFI crossing 80/20 or 90/10 zones often precede pullbacks or reversals. Use the plotted circles as optional take-profit signals when MFI and trend are extended. Adjust AlphaTrail length/multiplier and MFI smoothing to better match the asset’s volatility profile.
ATR-Multiple from 50SMAThis indicator provides a nuanced view of price extension by calculating the distance between the current price and its 50-period Simple Moving Average. This distance is not measured in simple percentage terms but is quantified in multiples of the Average True Range (ATR), offering a volatility-adjusted perspective on how far an asset has moved from its mean.
The primary goal is to help traders identify potentially overextended conditions, which can often precede price consolidation or reversals. As a general guideline, when an asset's price stretches to multiples of 7 ATRs or more above its 50-day SMA, it often enters a zone where significant profit-taking may occur. By visualizing this extension, the indicator can serve as a powerful tool for gauging when to consider taking profits on existing long positions. Furthermore, it can act as a cautionary signal, helping traders avoid initiating new long positions in assets that are already significantly stretched and may be poised for a pullback.
Features
Volatility-Adjusted Extension
Measures the distance from the 50 SMA in terms of ATR multiples, providing a more standardized way to compare extension across different assets and time periods.
Daily Timeframe Consistency
By default, the indicator uses the daily SMA and ATR for its calculations, regardless of the chart's current timeframe. This ensures a consistent and meaningful measure of extension rooted in the daily trend.
Histogram Visualization
Displays the result as a clear histogram in a separate pane, making it easy to track the extension level over time and identify historical extremes.
Dynamic Color-Coding
The histogram bars are color-coded to visually highlight different levels of extension. The colors shift as the price moves further from the mean, providing an intuitive at-a-glance reading.
Key Threshold Markers
Includes pre-set horizontal lines at the 7 and 10 ATR multiples to clearly mark the zones of potential profit-taking and extreme extension, respectively.
Built-in Alerts
Comes with configurable alert conditions that can notify you when the price reaches the "profit-taking" threshold (7 ATRs) or the "extreme extension" threshold (10 ATRs).
Customization Options
MA & ATR Periods
You can adjust the length for the Simple Moving Average (default 50) and the Average True Range (default 14) to suit your specific analytical needs.
Timeframe Source
A toggle allows you to switch between always calculating using daily data (the default and recommended setting) or using the data from the current chart's timeframe.
Color Display Style
You can choose between a smooth color gradient that transitions elegantly with the extension level or a distinct, step-based color display for a clearer visual separation of the defined zones.
Full Color Scheme Control
Every visual element is fully customizable. You can change the colors for the regular extension, the "get ready," "profit-taking," and "extreme" levels, as well as the horizontal reference lines.
SPX Weekly Expected Moves# SPX Weekly Expected Moves Indicator
A professional Pine Script indicator for TradingView that displays weekly expected move levels for SPX based on real options data, with integrated Fibonacci retracement analysis and intelligent alerting system.
## Overview
This indicator helps options and equity traders visualize weekly expected move ranges for the S&P 500 Index (SPX) by plotting historical and current week expected move boundaries derived from weekly options pricing. Unlike theoretical volatility calculations, this indicator uses actual market-based expected move data that you provide from options platforms.
## Key Features
### 📈 **Expected Move Visualization**
- **Historical Lines**: Display past weeks' expected moves with configurable history (10, 26, or 52 weeks)
- **Current Week Focus**: Highlighted current week with extended lines to present time
- **Friday Close Reference**: Orange baseline showing the previous Friday's close price
- **Timeframe Independent**: Works consistently across all chart timeframes (1m to 1D)
### 🎯 **Fibonacci Integration**
- **Five Fibonacci Levels**: 23.6%, 38.2%, 50%, 61.8%, 76.4% between Friday close and expected move boundaries
- **Color-Coded Levels**:
- Red: 23.6% & 76.4% (outer levels)
- Blue: 38.2% & 61.8% (golden ratio levels)
- Black: 50% (midpoint - most critical level)
- **Current Week Only**: Fibonacci levels shown only for active trading week to reduce clutter
### 📊 **Real-Time Information Table**
- **Current SPX Price**: Live market price
- **Expected Move**: ±EM value for current week
- **Previous Close**: Friday close price (baseline for calculations)
- **100% EM Levels**: Exact upper and lower boundary prices
- **Current Location**: Real-time position within the EM structure (e.g., "Above 38.2% Fib (upper zone)")
### 🚨 **Intelligent Alert System**
- **Zone-Aware Alerts**: Separate alerts for upper and lower zones
- **Key Level Breaches**: Alerts for 23.6% and 76.4% Fibonacci level crossings
- **Bar Close Based**: Alerts trigger on confirmed bar closes, not tick-by-tick
- **Customizable**: Enable/disable alerts through settings
## How It Works
### Data Input Method
The indicator uses a **manual data entry approach** where you input actual expected move values obtained from options platforms:
```pinescript
// Add entries using the options expiration Friday date
map.put(expected_moves, 20250613, 91.244) // Week ending June 13, 2025
map.put(expected_moves, 20250620, 95.150) // Week ending June 20, 2025
```
### Weekly Structure
- **Monday 9:30 AM ET**: Week begins
- **Friday 4:00 PM ET**: Week ends
- **Lines Extend**: From Monday open to Friday close (historical) or current time + 5 bars (current week)
- **Timezone Handling**: Uses "America/New_York" for proper DST handling
### Calculation Logic
1. **Base Price**: Previous Friday's SPX close price
2. **Expected Move**: Market-derived ±EM value from weekly options
3. **Upper Boundary**: Friday Close + Expected Move
4. **Lower Boundary**: Friday Close - Expected Move
5. **Fibonacci Levels**: Proportional levels between Friday close and EM boundaries
## Setup Instructions
### 1. Data Collection
Obtain weekly expected move values from options platforms such as:
- **ThinkOrSwim**: Use thinkBack feature to look up weekly expected moves
- **Tastyworks**: Check weekly options expected move data
- **CBOE**: Reference SPX weekly options data
- **Manual Calculation**: (ATM Call Premium + ATM Put Premium) × 0.85
### 2. Data Entry
After each Friday close, update the indicator with the next week's expected move:
```pinescript
// Example: On Friday June 7, 2025, add data for week ending June 13
map.put(expected_moves, 20250613, 91.244) // Actual EM value from your platform
```
### 3. Configuration
Customize the indicator through the settings panel:
#### Visual Settings
- **Show Current Week EM**: Toggle current week display
- **Show Past Weeks**: Toggle historical weeks display
- **Max Weeks History**: Choose 10, 26, or 52 weeks of history
- **Show Fibonacci Levels**: Toggle Fibonacci retracement levels
- **Label Controls**: Customize which labels to display
#### Colors
- **Current Week EM**: Default yellow for active week
- **Past Weeks EM**: Default gray for historical weeks
- **Friday Close**: Default orange for baseline
- **Fibonacci Levels**: Customizable colors for each level type
#### Alerts
- **Enable EM Breach Alerts**: Master toggle for all alerts
- **Specific Alerts**: Four alert types for Fibonacci level breaches
## Trading Applications
### Options Trading
- **Straddle/Strangle Positioning**: Visualize breakeven levels for neutral strategies
- **Directional Plays**: Assess probability of reaching target levels
- **Earnings Plays**: Compare actual vs. expected move outcomes
### Equity Trading
- **Support/Resistance**: Use EM boundaries and Fibonacci levels as key levels
- **Breakout Trading**: Monitor for moves beyond expected ranges
- **Mean Reversion**: Look for reversals at extreme Fibonacci levels
### Risk Management
- **Position Sizing**: Gauge likely price ranges for the week
- **Stop Placement**: Use Fibonacci levels for logical stop locations
- **Profit Targets**: Set targets based on EM structure probabilities
## Technical Implementation
### Performance Features
- **Memory Managed**: Configurable history limits prevent memory issues
- **Timeframe Independent**: Uses timestamp-based calculations for consistency
- **Object Management**: Automatic cleanup of drawing objects prevents duplicates
- **Error Handling**: Robust bounds checking and NA value handling
### Pine Script Best Practices
- **v6 Compliance**: Uses latest Pine Script version features
- **User Defined Types**: Structured data management with WeeklyEM type
- **Efficient Drawing**: Smart line/label creation and deletion
- **Professional Standards**: Clean code organization and comprehensive documentation
## Customization Guide
### Adding New Weeks
```pinescript
// Add after market close each Friday
map.put(expected_moves, YYYYMMDD, EM_VALUE)
```
### Color Schemes
Customize colors for different trading styles:
- **Dark Theme**: Use bright colors for visibility
- **Light Theme**: Use contrasting dark colors
- **Minimalist**: Use single color with transparency
### Label Management
Control label density:
- **Show Current Week Labels Only**: Reduce clutter for active trading
- **Show All Labels**: Full information for analysis
- **Selective Display**: Choose specific label types
## Troubleshooting
### Common Issues
1. **No Lines Appearing**: Check that expected move data is entered for current/recent weeks
2. **Wrong Time Display**: Ensure "America/New_York" timezone is properly handled
3. **Duplicate Lines**: Restart indicator if drawing objects appear duplicated
4. **Missing Fibonacci Levels**: Verify "Show Fibonacci Levels" is enabled
### Data Validation
- **Expected Move Format**: Use positive numbers (e.g., 91.244, not ±91.244)
- **Date Format**: Use YYYYMMDD format (e.g., 20250613)
- **Reasonable Values**: Verify EM values are realistic (typically 50-200 for SPX)
## Version History
### Current Version
- **Pine Script v6**: Latest version compatibility
- **Fibonacci Integration**: Five-level retracement analysis
- **Zone-Aware Alerts**: Upper/lower zone differentiation
- **Dynamic Line Management**: Smart current week extension
- **Professional UI**: Comprehensive information table
### Future Enhancements
- **Multiple Symbols**: Extend beyond SPX to other indices
- **Automated Data**: Integration with options data APIs
- **Statistical Analysis**: Success rate tracking for EM predictions
- **Additional Levels**: Custom percentage levels beyond Fibonacci
## License & Usage
This indicator is designed for educational and trading purposes. Users are responsible for:
- **Data Accuracy**: Ensuring correct expected move values
- **Risk Management**: Proper position sizing and risk controls
- **Market Understanding**: Comprehending options-based expected move concepts
## Support
For questions, issues, or feature requests related to this indicator, please refer to the code comments and documentation within the Pine Script file.
---
**Disclaimer**: This indicator is for informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
Toolbar-FrenToolbar-Fren is a comprehensive, data-rich toolbar designed to present a wide array of key metrics in a compact and intuitive format. The core philosophy of this indicator is to maximize the amount of relevant, actionable data available to the trader while occupying minimal chart space. It leverages a dynamic color-coded system to provide at-a-glance insights into market conditions, instantly highlighting positive/negative values, trend strength, and proximity to important technical levels.
Features and Data Displayed
The toolbar displays a vertical column of critical data points, primarily calculated on the Daily timeframe to give a broader market context. Each cell is color-coded for quick interpretation.
DAY:
The percentage change of the current price compared to the previous day's close. The cell is colored green for a positive change and red for a negative one.
LOD:
The current price's percentage distance from the Low of the Day.
HOD
The current price's percentage distance from the High of the Day.
MA Distances (9/21 or 10/20, 50, 200)
These cells show how far the current price is from key Daily moving averages (MAs).
The values are displayed either as a percentage distance or as a multiple of the Average Daily Range (ADR), which can be toggled in the settings.
The cells are colored green if the price is above the corresponding MA (bullish) and red if it is below (bearish).
ADR
Shows the 14-period Average Daily Range as a percentage of the current price. The cell background uses a smooth gradient from green (low volatility) to red (high volatility) to visualize the current daily range expansion.
ADR%/50: A unique metric showing the distance from the Daily 50 SMA, measured in multiples of the 14-period Average True Range (ATR). This helps quantify how extended the price is from its mean. The cell is color-coded from green (close to the mean) to red (highly extended).
RSI
The standard 14-period Relative Strength Index calculated on the Daily timeframe. The background color changes to indicate potentially overbought (orange/red) or oversold (green) conditions.
ADX
The 14-period Average Directional Index (ADX) from the Daily timeframe, which measures trend strength. The cell is colored to reflect the strength of the trend (e.g., green for a strong trend, red for a weak/non-trending market). An arrow (▲/▼) is also displayed to indicate if the ADX value is sloping up or down.
User Customization
The indicator offers several options for personalization to fit your trading style and visual preferences:
MA Type
Choose between using Exponential Moving Averages (EMA 9/21) or Simple Moving Averages (SMA 10/20) for the primary MA calculations.
MA Distance Display
Toggle the display of moving average distances between standard percentage values and multiples of the Average Daily Range (ADR).
Display Settings
Fully customize the on-chart appearance by selecting the table's position (e.g., Top Right, Bottom Left) and the text size. An option for a larger top margin is also available.
Colors
Personalize the core Green, Yellow, Orange, and Red colors used throughout the indicator to match your chart's theme.
Technical Parameters
Fine-tune the length settings for the ADX and DI calculations.
Real-Time Spring DetectorThis is a Pine Script for Trading View that creates a "Real-Time Spring Detector" indicator. This Pine Script is essentially a sophisticated pattern recognition tool that helps identify "spring" setups - a popular trading pattern where price briefly breaks below support but then bounces back strongly, often indicating that sellers are exhausted and buyers are ready to step in.What is a "Spring" in Trading?
A spring is a technical analysis pattern that occurs when:
Price breaks below a support level (like breaking below a floor)
But then quickly bounces back up (like a spring rebounds)
This often signals that sellers are weak and buyers are stepping in
Think of it like testing the strength of a trampoline - you push down, but it springs back up stronger.
What This Script Does
This Pine Script automatically detects spring patterns on your chart and alerts you when they happen. Here's how it works:
Main Components
1. Input Parameters (Settings You Can Adjust)
Lookback Period (10): How many bars back to look for patterns
Min Support Touches (2): How many times price must touch the support level
Min Penetration % (0.1%): How far below support price must break
Min Rejection % (30%): How much price must bounce back up
Alert Settings: Choose when to get notifications
2. Support Level Detection
The script finds "support levels" - price levels where buyers have stepped in before:
It looks at recent low points
Identifies areas where price has bounced multiple times
Uses a small tolerance (0.5%) to account for minor price differences
3. Spring Detection Logic
The script identifies three types of springs:
Real-Time Spring (happening right now):
Price breaks below support by the minimum amount
Price bounces back strongly (rejection %)
Current candle closes higher than it opened (bullish)
Volume is reasonable
Confirmed Spring (already completed):
Same as real-time, but the candle has finished forming
Potential Spring (early warning):
Price is near support but hasn't fully formed the pattern yet
4. Visual Elements
Markers on Chart:
🟢 Green Triangle: Confirmed spring (reliable signal)
🟡 Yellow Triangle: Spring forming right now (live signal)
🟠 Orange Circle: Potential spring (early warning)
Labels:
Show "SPRING" with the rejection percentage
"FORMING" for developing patterns
"?" for potential springs
Support Line:
Red dotted line showing the support level
Background Colors:
Light red when price penetrates support
Light yellow for potential springs
5. Information Box
A table in the top-left corner shows:
Current support level price
Whether penetration is happening
Rejection percentage
Current pattern status
Live price
6. Alert System
Two types of alerts:
Real-time alerts: Notify when spring is forming (current bar)
Confirmed alerts: Notify when spring is complete (bar closed)
Alert cooldown: Prevents spam by waiting 5 bars between alerts
How to Use This Script
1. Installation
Copy the script code
Open TradingView
Go to Pine Editor
Paste the code
Click "Add to Chart"
2. Settings
Adjust the input parameters based on your trading style:
Lower lookback = more sensitive, faster signals
Higher support touches = more reliable but fewer signals
Lower penetration % = catches smaller springs
Higher rejection % = only strong bounces
3. Interpretation
Green triangles: High-confidence buy signals
Yellow triangles: Watch closely, pattern developing
Orange circles: Early warning, not tradeable yet
4. Best Practices
Use on higher timeframes (15min+) for more reliable signals
Combine with other indicators for confirmation
Pay attention to volume - higher volume springs are more reliable
Wait for confirmed signals if you're a conservative trader
Key Features for Small Timeframes
The script includes special detection for shorter timeframes:
Quick bounce detection: Identifies rapid reversals
Hammer pattern recognition: Spots candlestick patterns
Relaxed volume requirements: Works when volume data is limited
Advanced Features
Volume Analysis
Compares current volume to 10-bar average
Requires at least 80% of average volume (flexible for small timeframes)
Pattern Enhancement
Looks for hammer-like candles (long lower wick, small upper wick)
Identifies quick bounces where the upper wick is small
Multiple Confirmation
Combines multiple criteria to reduce false signals
Stronger springs get priority for alerts
Common Use Cases
Entry Signals: Buy when confirmed springs appear
Support Level Identification: Visual support lines help identify key levels
Risk Management: Failed springs (continued breakdown) can be stop-loss triggers
Market Structure: Understanding where buyers are defending price levels
Limitations
Works best in trending or ranging markets May produce false signals in very choppy conditions
small timeframe signals can be noisy should be combined with other analysis methods.The key advantage is that it can catch these patterns as they happen, rather than you having to constantly watch charts. This is especially valuable for active traders who want to capitalize on quick reversals at support levels.
StochFusion – Multi D-LineStochFusion – Multi D-Line
An advanced fusion of four Stochastic %D lines into one powerful oscillator.
What it does:
Combines four user-weighted Stochastic %D lines—from fastest (9,3) to slowest (60,10)—into a single “Fusion” line that captures both short-term and long-term momentum in one view.
How to use:
Adjust the four weights (0–10) to emphasize the speed of each %D component.
Watch the Fusion line crossing key zones:
– Above 80 → overbought condition, potential short entry.
– Below 20 → oversold condition, potential long entry.
– Around 50 → neutral/midline, watch for trend shifts.
Applications:
Entry/exit filter: Only take trades when the Fusion line confirms zone exits.
Trend confirmation: Analyze slope and cross of the midline for momentum strength.
Multi-timeframe alignment: Use on different chart resolutions to find confluence.
Tips & Tricks:
Default weights give more influence to slower %D—good for trend-focused strategies.
Equal weights provide a balanced oscillator that mimics an ensemble average.
Experiment: Increase the fastest weight to capture early reversal signals.
Developed by: TradeQUO — inspired by DayTraderRadio John
“The best momentum indicator is the one you adapt to your own trading rhythm.”
Open Interest-RSI + Funding + Fractal DivergencesIndicator — “Open Interest-RSI + Funding + Fractal Divergences”
A multi-factor oscillator that fuses Open-Interest RSI, real-time Funding-Rate data and price/OI fractal divergences.
It paints BUY/SELL arrows in its own pane and directly on the price chart, helping you spot spots where crowd positioning, leverage costs and price action contradict each other.
1 Purpose
OI-RSI – measures conviction behind position changes instead of price momentum.
Funding Rate – shows who pays to hold positions (longs → bull bias, shorts → bear bias).
Fractal Divergences – detects HH/LL in price that are not confirmed by OI-RSI.
Optional Funding filter – hides signals when funding is already extreme.
Together these elements highlight exhaustion points and potential mean-reversion trades.
2 Inputs
RSI / Divergence
RSI length – default 14.
High-OI level / Low-OI level – default 70 / 30.
Fractal period n – default 2 (swing width).
Fractals to compare – how many past swings to scan, default 3.
Max visible arrows – keeps last 50 BUY/SELL arrows for speed.
Funding Rate
mode – choose FR, Avg Premium, Premium Index, Avg Prem + PI or FR-candle.
Visual scale (×) – multiplies raw funding to fit 0-100 oscillator scale (default 10).
specify symbol – enable only if funding symbol differs from chart.
use lower tf – averages 1-min premiums for smoother intraday view.
show table – tiny two-row widget at chart edge.
Signal Filter
Use Funding filter – ON hides long signals when funding > Buy-threshold and short signals when funding < Sell-threshold.
BUY threshold (%) – default 0.00 (raw %).
SELL threshold (%) – default 0.00 (raw %).
(Enter funding thresholds as raw percentages, e.g. 0.01 = +0.01 %).
3 Visual Outputs
Sub-pane
Aqua OI-RSI curve with 70 / 50 / 30 reference lines.
Funding visualised according to selected mode (green above 0, red below 0, or other).
BUY / SELL arrows at oscillator extremes.
Price chart
Identical BUY / SELL arrows plotted with force_overlay = true above/below candles that formed qualifying fractals.
Optional table
Shows current asset ticker and latest funding value of the chosen mode.
4 Signal Logic (Summary)
Load _OI series and compute RSI.
Retrieve Funding-Rate + Premium Index (optionally from lower TF).
Find fractal swings (n bars left & right).
Check divergence:
Bearish – price HH + OI-RSI LH.
Bullish – price LL + OI-RSI HL.
If Funding-filter enabled, require funding < Buy-thr (long) or > Sell-thr (short).
Plot arrows and trigger two built-in alerts (Bearish OI-RSI divergence, Bullish OI-RSI divergence).
Signals are fixed once the fractal bar closes; they do not repaint afterwards.
5 How to Use
Attach to a liquid perpetual-futures chart (BTC, ETH, major Binance contracts).
If _OI or funding series is missing you’ll see an error.
Choose timeframe:
15 m – 4 h for intraday;
1 D+ for swing trades.
Lower TFs → more signals; raise Fractals to compare or use Funding filter to trim noise.
Trade checklist
Funding positive and rising → longs overcrowded.
Price makes higher high; OI-RSI makes lower high; Funding above Sell-threshold → consider short.
Reverse logic for longs.
Combine with trend filter (EMA ribbon, SuperTrend, etc.) so you fade only when price is stretched.
Automation – set TradingView alerts on the two alertconditions and send to webhooks/bots.
Performance tips
Keep Max visible arrows ≤ 50.
Disable lower-TF premium aggregation if script feels heavy.
6 Limitations
Some symbols lack _OI or funding history → script stops with a console message.
Binance Premium Index begins mid-2020; older dates show na.
Divergences confirm only after n bars (no forward repaint).
7 Changelog
v1.0 – 10 Jun 2025
Initial public release.
Added price-chart arrows via force_overlay.
SMEMA Trend CoreSMEMA Trend Core is a multi-timeframe trend analysis tool designed to provide a clean, adaptive and structured view of the market’s directional bias. It can be used in short term, swing or long term contexts. The internal calculation adjusts automatically based on the selected trading style, while always combining data from six timeframes.
At its core, the indicator uses a SMEMA, which is a Simple Moving Average applied to an EMA. This combination improves smoothness without losing reactivity. The SMEMA is calculated separately on 1H, 4H, 1D, 3D, 1W and 1M timeframes. These six values are then combined using dynamic weights that depend on the trading mode:
Short Term mode gives more influence to 1H and 4H
Swing Trading mode gives more influence to 1D, 3D and 1W
Long Term mode gives more influence to 1W and 1M
However, all six timeframes are always included in the final result. This avoids the tunnel vision of relying on a single resolution and ensures that the indicator captures both local and structural movements.
The result is a synthetic trend line, called Global SMEMA, that adapts to market conditions and offers a realistic view of the ongoing trend. To enhance the reading, the indicator calculates a Trend Score. This score reflects the position of price relative to the Global SMEMA, scaled by a long-term ATR, and adjusted by the slope of the trend line. A hyperbolic tangent function is used to normalize values and reduce distortion from outliers.
The final score is capped between -10 and +10, and used to define the trend state:
Green when the trend is bullish (score > +1.5)
Red when the trend is bearish (score < -1.5)
Brown when the trend is neutral (score between -1.5 and +1.5)
Optional Deviation Bands can be displayed at ±1, ±2 and ±3 ATR distances around the central line. These dynamic zones help identify extended price movements or potential support and resistance areas, depending on the current trend bias.
Main features:
A single, stable trend line based on six timeframes
Automatic rebalancing depending on trading mode
Quantified score integrating distance and slope
No overreaction to short-term noise
Deviation zones for advanced market context
No repainting, no lookahead, 100% real-time
SMEMA Trend Core is not a signal tool. It is a directional framework that helps you stay aligned with the real structure of the market. Use it to confirm setups, filter trades or simply understand where the market stands in its trend cycle.
AWR Pearsons R & LR Oscillator MTF1. Overview
This indicator is designed to analyze the correlation between a price series (or any custom indicator) and the bar index using Pearson’s correlation coefficient. It performs multiple linear regressions over shifted periods and then aggregates these results to create an oscillator. In addition, it integrates a multi-timeframe (MTF) analysis by retrieving the same calculations on 3 different time intervals, providing a more comprehensive view of the trend evolution.
2. User Parameters
The indicator offers several configurable parameters that allow the user to adjust both the calculations and the display:
Source (Linear Regression): The data source on which the regressions are applied (by default, the closing price).
Number of Linear Regressions (numOfLinReg): Allows choosing the number of correlation calculations (up to 10) to be carried out on different shifted periods.
Start Period (startPeriod) and Period Increment (periodIncrement): These parameters define the reference window for each regression. The calculation starts with a base period and then increases with each regression by a fixed increment, creating several time windows to assess the relationship between price evolution and time progression.
Deviation (def_deviation): Although defined, this parameter is intended to control the sensitivity of the calculations. It can be used in further developments of the indicator.
For Multi Time Frames analysis, three additional timeframes are provided through inputs in addition of the current period:
Sum up :
Timeframe 1 = current
Timeframe 2 = 30-minute (default settings)
Timeframe 3 = 1-hour (default settings)
Timeframe 4 = 4-hour (default settings)
These different timeframes allow you to obtain consistent or divergent signals over multiple resolutions, thereby enhancing the confidence of trading decisions.
3. Calculation Logic
At the core of the indicator is the f_calcConditions() function, which performs several essential tasks:
Calculating Pearson's Coefficients For each linear regression, the script uses ta.correlation() to measure the correlation between the chosen source (for example, the closing price) and the chronological index (bar_index). Up to 10 coefficients are computed over shifted windows, providing an evolving view of the linear relationship over different intervals.
Averaging the Results Once the coefficients are calculated, they are stored in an array and averaged to produce a global correlation value called avgPR_local.
Applying Moving Averages
The resulting average is then smoothed using several moving averages (SMA):
A short-term SMA (period of 14),
An intermediate SMA (period of 100),
A long-term SMA (period of 400).
These moving averages help to highlight the underlying trend of the oscillator by indicating the direction in which the correlation is moving.
Defining Trading Conditions Based on avgPR_local and its associated SMAs, multiple conditions are set to generate buy or sell signals:
Simple SMA Conditions :
Small signal :
Light blue below bar signal :
When the averaged coefficients lie between -1 and -0.63, are above the short-term SMA (14 periods), and are increasing, it may indicate a bullish dynamic (buy signal).
Orange above bar signal :
Conversely, when the value is higher (between 0.63 and 1) and below its SMA (14 periods), and are decreasing the trend is considered bearish (sell signal).
Medium signal :
Dark green signal
When the averaged coefficients lie between -1 and -0.45, are above the short-term SMA (14 periods), and are increasing, and also the average 100 is increasing. It may indicate a bullish dynamic (buy signal).
Light red signal :
Conversely, when the value is higher (between 0.45 and 1) and below its SMA (14 periods), the trend and are decreasing, and also the average 100 is decreasing. It may indicate a bearish dynamic(sell signal).
Light green signal :
When the averaged coefficients lie between -1 and -0.15, are above the short-term SMA (14 periods), and are increasing, and also the average 100 & 400 is increasing . It may indicate a bullish dynamic (buy signal).
Dark red signal :
Conversely, when the value is higher (between 0.45 and 1) and below its SMA (14 periods), the trend and are decreasing, and also the average 100 & 400 is decreasing. It may indicate a bearish dynamic(sell signal).
These additional conditions further refine the signals by verifying the consistency of the movement over longer periods. They check that the trends from the respective averages (intermediate and long-term) are in line with the direction indicated by the initial moving average.
These conditions are designed to capture moments when the oscillator's dynamics change, which can be interpreted as opportunities to enter or exit a trade.
4. Multi-Timeframes and Display
One of the main strengths of this indicator is its multi-timeframe approach.
This offers several advantages:
Comparative Analysis: Compare short-term dynamics with broader trends.
Enhanced Signal Reliability: A signal confirmed across multiple timeframes has a higher probability of success.
To visually highlight these signals on the chart, the indicator uses the plotchar() function with distinct symbols for each timeframe:
Current Timeframe: Signals are represented by the character "1"
30-Minute Timeframe: Displayed with the character "2".
1-Hour Timeframe: Displayed with the character "3".
4-Hour Timeframe: Displayed with the character "4".
The colors used are various shades of green for buy signals and shades of red/orange for sell signals, making it easy to distinguish between the different alerts.
5. Integrated Alerts
To avoid missing any trading opportunities, the indicator includes an alert condition via the alertcondition() function. This alert is triggered if any buy or sell signal is generated on any of the analyzed timeframes. The message "MTF valide" indicates that multiple timeframes are confirming the signal, enabling more informed decision-making.
6. How to Use This Indicator
Installation and Configuration: Copy the script into the TradingView Pine Script editor and add it to your chart. The default parameters can be tuned according to market behavior or personal preferences regarding sensitivity and responsiveness.
Interpreting the Signals:
Watch for the symbols on the chart corresponding to each timeframe.
A buy signal appears as a specific symbol below the bar (indicating a bullish condition based on a rising or less negative correlation), while a sell signal appears above the bar.
Multi-Timeframe Analysis: By comparing signals across timeframes, you can filter out false signals. For example, if the short-term timeframe shows a buy signal but the 4-hour timeframe indicates a bearish trend, you may need to reassess your position.
Adjusting the Settings: Depending on the asset type or market volatility, you might need to tweak the periods (startPeriod, periodIncrement) or the number of linear regressions to generate signals that better align with the price dynamics.
Using Alerts: Activate the built-in alert feature so that TradingView notifies you as soon as a multi-timeframe signal is detected. This ensures you stay informed even if you are not continuously monitoring the chart.
In Conclusion
The AWR Pearsons R & LR Oscillator MTF is a powerful tool for traders seeking a detailed understanding of market trends by combining statistical rigor (via Pearson's correlation coefficient) with a multi-timeframe approach. It is capable of generating clear entry and exit signals, visualized with specific symbols and colors depending on the timeframe. By adjusting the parameters to match your trading strategy and leveraging the alert system, you now have a robust instrument for making well-informed market decisions.
Feel free to dive deeper into each component and experiment with different configurations to see how the oscillator integrates with your overall technical analysis strategy. Enjoy exploring its potential and refining your trading approach!
