Pivot S/R with Volatility Filter## *📌 Indicator Purpose*
This indicator identifies *key support/resistance levels* using pivot points while also:
✅ Detecting *high-volume liquidity traps* (stop hunts)
✅ Filtering insignificant pivots via *ATR (Average True Range) volatility*
✅ Tracking *test counts and breakouts* to measure level strength
---
## *⚙ SETTINGS – Detailed Breakdown*
### *1️⃣ ◆ General Settings*
#### *🔹 Pivot Length*
- *Purpose:* Determines how many bars to analyze when identifying pivots.
- *Usage:*
- *Low values (5-20):* More pivots, better for scalping.
- *High values (50-200):* Fewer but stronger levels for swing trading.
- *Example:*
- Pivot Length = 50 → Only the most significant highs/lows over 50 bars are marked.
#### *🔹 Test Threshold (Max Test Count)*
- *Purpose:* Sets how many times a level can be tested before being invalidated.
- *Example:*
- Test Threshold = 3 → After 3 tests, the level is ignored (likely to break).
#### *🔹 Zone Range*
- *Purpose:* Creates a price buffer around pivots (±0.001 by default).
- *Why?* Markets often respect "zones" rather than exact prices.
---
### *2️⃣ ◆ Volatility Filter (ATR)*
#### *🔹 ATR Period*
- *Purpose:* Smoothing period for Average True Range calculation.
- *Default:* 14 (standard for volatility measurement).
#### *🔹 ATR Multiplier (Min Move)*
- *Purpose:* Requires pivots to show *meaningful price movement*.
- *Formula:* Min Move = ATR × Multiplier
- *Example:*
- ATR = 10 pips, Multiplier = 1.5 → Only pivots with *15+ pip swings* are valid.
#### *🔹 Show ATR Filter Info*
- Displays current ATR and minimum move requirements on the chart.
---
### *3️⃣ ◆ Volume Analysis*
#### *🔹 Volume Change Threshold (%)*
- *Purpose:* Filters for *unusual volume spikes* (institutional activity).
- *Example:*
- Threshold = 1.2 → Requires *120% of average volume* to confirm signals.
#### *🔹 Volume MA Period*
- *Purpose:* Lookback period for "normal" volume calculation.
---
### *4️⃣ ◆ Wick Analysis*
#### *🔹 Wick Length Threshold (Ratio)*
- *Purpose:* Ensures rejection candles have *long wicks* (strong reversals).
- *Formula:* Wick Ratio = (Upper Wick + Lower Wick) / Candle Range
- *Example:*
- Threshold = 0.6 → 60% of the candle must be wicks.
#### *🔹 Min Wick Size (ATR %)*
- *Purpose:* Filters out small wicks in volatile markets.
- *Example:*
- ATR = 20 pips, MinWickSize = 1% → Wicks under *0.2 pips* are ignored.
---
### *5️⃣ ◆ Display Settings*
- *Show Zones:* Toggles support/resistance shaded areas.
- *Show Traps:* Highlights liquidity traps (▲/▼ symbols).
- *Show Tests:* Displays how many times levels were tested.
- *Zone Transparency:* Adjusts opacity of zones.
---
## *🎯 Practical Use Cases*
### *1️⃣ Liquidity Trap Detection*
- *Scenario:* Price spikes *above resistance* then reverses sharply.
- *Requirements:*
- Long wick (Wick Ratio > 0.6)
- High volume (Volume > Threshold)
- *Outcome:* *Short Trap* signal (▼) appears.
### *2️⃣ Strong Support Level*
- *Scenario:* Price bounces *3 times* from the same level.
- *Indicator Action:*
- Labels the level with test count (3/5 = 3 tests out of max 5).
- Turns *red* if broken (Break Count > 0).
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
## *📊 Parameter Encyclopedia (Expanded)*
### *1️⃣ Pivot Engine Settings*
#### *Pivot Length (50)*
- *What It Does:*
Determines how many bars to analyze when searching for swing highs/lows.
- *Professional Adjustment Guide:*
| Trading Style | Recommended Value | Why? |
|--------------|------------------|------|
| Scalping | 10-20 | Captures short-term levels |
| Day Trading | 30-50 | Balanced approach |
| Swing Trading| 50-200 | Focuses on major levels |
- *Real Market Example:*
On NASDAQ 5-minute chart:
- Length=20: Identifies levels holding for ~2 hours
- Length=50: Finds levels respected for entire trading day
#### *Test Threshold (5)*
- *Advanced Insight:*
Institutions often test levels 3-5 times before breaking them. This setting mimics the "probe and push" strategy used by smart money.
- *Psychology Behind It:*
Retail traders typically give up after 2-3 tests, while institutions keep testing until stops are run.
---
### *2️⃣ Volatility Filter System*
#### *ATR Multiplier (1.0)*
- *Professional Formula:*
Minimum Valid Swing = ATR(14) × Multiplier
- *Market-Specific Recommendations:*
| Market Type | Optimal Multiplier |
|------------------|--------------------|
| Forex Majors | 0.8-1.2 |
| Crypto (BTC/ETH) | 1.5-2.5 |
| SP500 Stocks | 1.0-1.5 |
- *Why It Matters:*
In EUR/USD (ATR=10 pips):
- Multiplier=1.0 → Requires 10 pip swings
- Multiplier=1.5 → Requires 15 pip swings (fewer but higher quality levels)
---
### *3️⃣ Volume Confirmation System*
#### *Volume Threshold (1.2)*
- *Institutional Benchmark:*
- 1.2x = Moderate institutional interest
- 1.5x+ = Strong smart money activity
- *Volume Spike Case Study:*
*Before Apple Earnings:*
- Normal volume: 2M shares
- Spike threshold (1.2): 2.4M shares
- Actual volume: 3.1M shares → STRONG confirmation
---
### *4️⃣ Liquidity Trap Detection*
#### *Wick Analysis System*
- *Two-Filter Verification:*
1. *Wick Ratio (0.6):*
- Ensures majority of candle shows rejection
- Formula: (UpperWick + LowerWick) / Total Range > 0.6
2. *Min Wick Size (1% ATR):*
- Prevents false signals in flat markets
- Example: ATR=20 pips → Min wick=0.2 pips
- *Trap Identification Flowchart:*
Price Enters Zone →
Spikes Beyond Level →
Shows Long Wick →
Volume > Threshold →
TRAP CONFIRMED
---
## *💡 Master-Level Usage Techniques*
### *Institutional Order Flow Analysis*
1. *Step 1:* Identify pivot levels with ≥3 tests
2. *Step 2:* Watch for volume contraction near levels
3. *Step 3:* Enter when trap signal appears with:
- Wick > 2×ATR
- Volume > 1.5× average
### *Multi-Timeframe Confirmation*
1. *Higher TF:* Find weekly/monthly pivots
2. *Lower TF:* Use this indicator for precise entries
3. *Example:*
- Weekly pivot at $180
- 4H shows liquidity trap → High-probability reversal
---
## *⚠ Critical Mistakes to Avoid*
1. *Using Default Settings Everywhere*
- Crude oil needs higher ATR multiplier than bonds
2. *Ignoring Trap Context*
- Traps work best at:
- All-time highs/lows
- Major psychological numbers (00/50 levels)
3. *Overlooking Cumulative Volume*
- Check if volume is building over multiple tests
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Master Litecoin Miner Sell PressureBrief Description:
Purpose: The indicator overlays on a chart to highlight periods of high miner sell pressure for Litecoin.
Data Sources:
miner_out: Fetches daily Litecoin miner outflows (amount of LTC moved out by miners) using the INTOTHEBLOCK:LTC_MINEROUTFLOWS dataset.
miner_res: Fetches daily Litecoin miner reserves (amount of LTC held by miners) using the INTOTHEBLOCK:LTC_MINERRESERVES dataset.
Calculation:
Computes a ratio m by taking the 14-day sum of miner outflows and dividing it by the 14-day simple moving average (SMA) of miner reserves.
Calculates Bollinger Bands around m:
bbl: Lower band (200-day SMA of m minus 1 standard deviation).
bbu: Upper band (200-day SMA of m plus 1 standard deviation).
Visualization:
If the ratio m exceeds the upper Bollinger Band (bbu), the background is colored blue with 30% opacity, indicating potential high sell pressure from miners.
Forex Pips Tracker PinescriptlabsThis algorithm is exclusively designed for the Forex market 🌐 and serves as a tool to measure volatility, helping to determine on average how many pips positions move per hour. With this information, a trader can place take profit and stop loss orders with greater certainty, since they know the average pip movement range during each hour of the day.
What does it do and how does it work?
• Volatility measurement in pips 📊:
The algorithm calculates the size of the movement (or range) of each candle expressed in pips. To do this, it takes the difference between the highest and lowest price of each candle and converts it into pips.
👉
• Time zone adjustment ⏰:
It allows you to configure the time zone so that the data aligns with your desired schedule. This is especially useful for comparing movements at different times based on the trader's location.
• Analysis by time intervals 🕒:
The algorithm’s logic organizes the information for each hour of the day. It stores data for the current day, the previous day, weekly, and historically (200 candles). This allows you to see how volatility varies across different periods, providing a dynamic view of market behavior.
👉
• Directionality of movement 🔄:
In addition to averaging the pip range, the algorithm determines the predominant direction of each candle (bullish or bearish). This translates into visual indicators (like arrows) that help identify whether, on average, the movement during that hour tends to go up or down.
• Table visualization 📈:
Finally, the information is presented in an integrated table on the chart. Each row corresponds to an hour of the day and shows the average number of pips and the direction (bullish, bearish, or neutral) for each analyzed period. This table makes it easy to quickly and practically interpret the volatility data.
By combining these features, the algorithm becomes an essential tool for traders looking to better understand market dynamics and optimize their trading strategies! 💼✨
Español:
Este algoritmo está diseñado exclusivamente para el mercado Forex 🌐 y sirve como una herramienta para medir la volatilidad, ayudando a determinar en promedio cuántos pips se mueven las posiciones por hora. Con esta información, un trader puede colocar el take profit y el stop loss con mayor certeza, ya que conoce el rango promedio de movimiento en pips durante cada hora del día.
¿Qué hace y cómo funciona?
• Medición de volatilidad en pips 📊:
El algoritmo calcula el tamaño del movimiento (o rango) de cada vela expresado en pips. Para ello, toma la diferencia entre el precio máximo y el mínimo de cada vela y la convierte a pips.
👉
• Ajuste de zona horaria ⏰:
Permite configurar la zona horaria para que los datos se ajusten al horario deseado. Esto es especialmente útil para comparar movimientos durante distintas horas en función de la localización del trader.
• Análisis por intervalos de tiempo 🕒:
La lógica del algoritmo organiza la información por cada hora del día. Guarda datos para el día actual, el día anterior, a nivel semanal e histórico (200 velas). Esto permite ver cómo varía la volatilidad en diferentes periodos, proporcionando una visión dinámica del comportamiento del mercado.
👉
• Direccionalidad del movimiento 🔄:
Además de promediar el rango en pips, el algoritmo determina la dirección predominante de cada vela (alcista o bajista). Esto se traduce en indicadores visuales (como flechas) que permiten identificar si, en promedio, el movimiento en esa hora tiende a subir o bajar.
• Visualización en tabla 📈:
Finalmente, la información se presenta en una tabla integrada en el gráfico. Cada fila corresponde a una hora del día y muestra el promedio de pips y la dirección (alcista, bajista o neutral) para cada uno de los periodos analizados. Esta tabla facilita la interpretación rápida y práctica de los datos de volatilidad.
Al combinar estas funciones, el algoritmo se convierte en una herramienta esencial para traders que buscan entender mejor la dinámica del mercado y optimizar sus estrategias de trading! 💼✨
Risk MeterRisk Meter Indicator for TradingView
The Risk Meter is a powerful market risk assessment tool designed to help traders evaluate the current risk environment using a simple, data-driven score. By analyzing four critical market factors—VIX (volatility index), market breadth, trailing volatility, and credit spreads—the indicator generates a risk score between 0 and 4. This score empowers traders to make informed decisions about hedging, exiting positions, or re-entering the market, with clear visual cues and alerts for intraday monitoring.
What It Does
Calculates a Risk Score: Assigns a score from 0 to 4, where each point reflects an active risk condition based on four market indicators.
Identifies Risk Levels:
A score of 3 or higher indicates a high-risk environment, suggesting traders consider hedging or reducing exposure.
A score of 2 or lower for at least two consecutive days signals a potential opportunity to re-enter the market.
Provides Visual Feedback: Uses color-coded Columns, threshold markers, and a component table for quick interpretation.
Supports Decision-Making: Offers a structured approach to managing risk and timing trades.
How It Works
The Risk Meter aggregates four key risk conditions, each contributing 1 point to the total score when triggered:
Elevated and Rising VIX (Risk 1)
Condition: The VIX is above 18 and higher than it was 20 days ago.
Purpose: Detects increasing market fear or uncertainty.
Market Breadth Dropping (Risk 2)
Condition: Either:
Fewer than 50% of S&P 500 stocks are above their 200-day moving average and fewer than 70% are above their 50-day moving average, or
The 3-day EMA of the 200-day breadth falls below 80% of its 20-day SMA.
Purpose: Identifies weakening participation across the market.
Trailing Volatility (Risk 3)
Condition: The 30-day annualized volatility of the equal-weight S&P 500 (RSP) exceeds 35%.
Purpose: Highlights periods of heightened price instability.
Credit Spreads (Risk 4)
Condition: The price ratio of high-yield bonds (HYG) to Treasuries (TLT or IEF) is lower than it was 20 days ago, indicating widening credit spreads.
Purpose: Signals potential stress in credit markets.
The total risk score is the sum of these conditions (0 to 4). Additionally, the indicator tracks consecutive days with a score of 2 or lower to generate re-entry signals.
How to Read It Intraday
The Risk Meter is built on daily data but can be monitored intraday for real-time insights. Here’s how traders can interpret it:
Risk Score Plot:
Displayed as a step line ranging from 0 to 4.
Colors:
Red: High risk (score ≥ 3) – caution advised.
Green: Re-entry signal – score ≤ 2 for at least two consecutive days (triggered when the count increments from 1 to 2).
Blue: Neutral or low risk (score < 3 without a re-entry signal).
Threshold Lines:
Dashed Gray Line at 3: Marks the high-risk threshold.
Dotted Gray Line at 2: Indicates the low-risk threshold for re-entry signals.
Risk Component Table:
Located in the top-right corner, it lists:
VIX, Breadth, Volatility, and Credit Spreads.
Status: Shows "" (warning, red) if the risk condition is met, or "✓" (safe, blue) if not.
Helps traders pinpoint which factors are driving the score.
Alerts:
High Risk Alert: Triggers when the score moves from < 3 to ≥ 3.
Re-entry Signal Alert: Triggers when the score ≤ 2 for two consecutive days.
Intraday Usage Tips
Check the indicator throughout the day for early signs of risk shifts, especially if the score is near a threshold (e.g., 2 or 3).
Combine with other intraday tools (e.g., price action, volume) since the Risk Meter updates daily but reflects broader market conditions.
How Traders Can Use It
High-Risk Signal (Score ≥ 3):
Consider hedging positions (e.g., with options) or reducing equity exposure to protect against potential downturns.
Re-entry Signal (Score ≤ 2 for 2+ Days):
Look to re-enter the market or increase exposure, as it suggests stabilizing conditions.
Daily Risk Management:
Use the score and table to assess overall market health and adjust strategies accordingly.
Alert-Driven Trading:
Set up alerts to stay notified of critical risk changes without constant monitoring.
Why Use the Risk Meter?
This indicator offers a systematic, multi-factor approach to risk assessment, blending volatility, breadth, and credit market data into an easy-to-read score. Whether you’re an intraday trader or a longer-term investor, the Risk Meter helps you stay proactive, avoid surprises, and time your trades with greater confidence.
Financial Risk Disclaimer for the Risk Meter Tool
Important Notice: The Risk Meter is a market risk assessment tool designed to provide insights into current market conditions based on historical data and predefined indicators. It is intended for informational and educational purposes only and should not be considered financial advice, a recommendation to buy or sell any securities, or a guarantee of future market performance.
Key Considerations
No Guarantee of Accuracy: While the Risk Meter utilizes reliable data sources and established financial metrics, the creators do not guarantee the accuracy, completeness, or timeliness of the information provided. Financial markets are complex and subject to rapid, unpredictable changes, and the tool’s output may not fully reflect all market dynamics.
Market Risks: Trading and investing in financial markets carry significant risks, including the potential loss of principal. Market volatility, economic shifts, and other factors can lead to unexpected outcomes. Past performance is not a reliable indicator of future results, and the Risk Meter’s assessments are based on historical data, not future predictions.
Not a Substitute for Professional Advice: The Risk Meter is not intended to replace personalized financial guidance. Users are strongly encouraged to consult a qualified financial advisor, perform their own research, and evaluate their personal financial situation, risk tolerance, and investment objectives before making any trading or investment decisions.
Limitation of Liability: The creators of the Risk Meter, including any affiliates, developers, or contributors, are not liable for any direct, indirect, incidental, or consequential losses or damages arising from the use of this tool. This includes, but is not limited to, financial losses, missed opportunities, or decisions based on the tool’s output.
User Responsibility: By using the Risk Meter, you accept full responsibility for your trading and investment decisions. You acknowledge that you use the tool at your own risk and that the creators bear no responsibility for any outcomes resulting from its use.
Final Note
The Risk Meter is a supplementary tool designed to enhance your understanding of market risk. It is not a comprehensive solution for investment management. Approach trading and investing with caution, ensuring your decisions align with your personal financial strategy.
OrangeCandle 4EMA 55 + Fib Bands + SignalsThe script is a TradingView indicator that combines three popular technical analysis tools: Exponential Moving Averages (EMAs), Fibonacci bands, and buy/sell signals based on these indicators. Here’s a breakdown of its features:
1. EMA Settings and Calculation:
The script calculates and plots several Exponential Moving Averages (EMAs) on the chart with different lengths:
Short-term EMAs: EMA 9, EMA 13, EMA 21, and EMA 55 (used for tracking short-term price trends).
Long-term EMAs: EMA 100 and EMA 200 (used to analyze longer-term trends).
These EMAs are plotted with different colors to visually distinguish between the short-term and long-term trends.
2. Fibonacci Bands:
The script calculates Fibonacci Bands based on the Average True Range (ATR) and a Simple Moving Average (SMA).
Fibonacci factors (1.618, 2.618, 4.236, 6.854, and 11.090) are used to determine the upper and lower bounds of five Fibonacci bands.
Upper Fibonacci Bands (e.g., fib1u, fib2u) represent resistance levels.
Lower Fibonacci Bands (e.g., fib1l, fib2l) represent support levels.
These bands are plotted with different colors for each level, helping traders identify potential price reversal zones.
3. Buy and Sell Signals:
Long Condition: A buy signal occurs when the price crosses above the EMA 55 (long-term trend indicator) and is above the lower Fibonacci band (support zone).
Short Condition: A sell signal occurs when the price crosses below the EMA 55 and is below the upper Fibonacci band (resistance zone).
These conditions trigger visual signals on the chart (green arrow for long, red arrow for short).
4. Alerts:
The script includes alert conditions to notify the trader when a long or short signal is triggered based on the crossover of price and EMA 55 near the Fibonacci support or resistance levels.
Long Entry Alert: Triggers when the price crosses above the EMA 55 and is near a Fibonacci support level.
Short Entry Alert: Triggers when the price crosses below the EMA 55 and is near a Fibonacci resistance level.
5. Visualization:
EMAs are plotted with distinct colors:
EMA 9 is aqua,
EMA 13 is purple,
EMA 21 is orange,
EMA 55 is blue (with thicker line width for emphasis),
EMA 100 is gray,
EMA 200 is black.
Fibonacci bands are plotted with different colors for each level:
Fib Band 1 (upper and lower) in white,
Fib Band 2 in green (upper) and red (lower),
Fib Band 3 in green (upper) and red (lower),
Fib Band 4 in blue (upper) and orange (lower),
Fib Band 5 in purple (upper) and yellow (lower).
Summary:
This script provides a comprehensive strategy for analyzing the market with multiple EMAs for trend detection, Fibonacci bands for support/resistance, and signals based on price action in relation to these indicators. The combination of these tools can assist traders in making more informed decisions by providing potential entry and exit points on the chart.
VWAP Horizon Suite Optimized - CoffeeKillerVWAP Horizon Suite Optimized - User Guide
Overview
The VWAP Horizon Suite Optimized is a comprehensive technical analysis tool for TradingView designed to enhance your trading strategy with Volume Weighted Average Price (VWAP) analysis, standard deviation bands, and customizable Exponential Moving Averages (EMAs). This indicator provides a robust framework for identifying potential support and resistance levels, price momentum, and market trends.
Key Features
- **Daily VWAP with Session Reset**: Automatically resets at 17:00 (5:00 PM) each day
- **Customizable Standard Deviation/Percentage Bands**: Up to 3 bands above and below VWAP
- **High/Low Point Detection**: Visual markers for significant price levels
- **Multiple Customizable EMAs**: 8 different EMAs that can be individually toggled and styled
- **Visual Customization**: Adjustable colors, fills, and styles for all elements
VWAP Settings
- **Source**: Determines the price data used to calculate VWAP (default: HLC3 - High, Low, Close average)
Bands Settings
- **Bands Calculation Mode**: Choose between "Standard Deviation" or "Percentage" methods
- **Show Band #1, #2, #3**: Toggle visibility for each band
- **Band Multiplier #1, #2, #3**: Adjust the distance from VWAP (in standard deviations or percentage)
- **Show Fills**: Enable colored fills between bands for better visualization
Visualization Settings
- **Show High/Low Markers**: Display diamond markers for local high and low points relative to VWAP, these reset based on the price crossing the VWAP Line.
EMA Settings
The indicator provides 8 customizable EMAs (8, 13, 21, 26, 48, 50, 100, and 200) with individual controls:
- **Show EMA X**: Toggle visibility for each EMA
- **EMA X Period**: Adjust the period length for calculation
- **EMA X Color**: Customize the color of each EMA
- **EMA Line Width**: Set the width for all EMA lines
How to Use
Basic VWAP Analysis
The core VWAP line (blue) represents the average price weighted by volume since the start of the session (17:00 daily reset). This serves as a dynamic support/resistance level and reference point for intraday trading.
1. **Price above VWAP**: Generally bullish short-term sentiment
2. **Price below VWAP**: Generally bearish short-term sentiment
3. **Crosses of VWAP**: Potential shift in short-term momentum
Standard Deviation Bands
The bands surrounding VWAP help identify potential support, resistance, and volatility levels:
- **Band #1 (±1σ)**: Price often reverts to VWAP when reaching these levels
- **Band #2 (±2σ)**: Stronger support/resistance areas, possible reversal zones
- **Band #3 (±3σ)**: Extreme price levels, often indicating overbought/oversold conditions
High/Low Point Detection
Purple and yellow diamond markers identify significant swing highs and lows relative to VWAP, helping you recognize potential reversal points or continuation patterns. (These repaint in a effort to find the max high/low point from the VWAP Line)
EMA Strategy
The customizable EMAs can be used to:
- Find potential support/resistance levels
- Create crossover systems
- Analyze market structure
Common EMA combinations include:
- 8 & 21 for short-term trends
- 50 & 200 for long-term trends and the "Golden Cross/Death Cross"
- 13 & 48 for the "New Golden Cross" - a modern alternative gaining popularity among traders
- 8, 13, 21 for complex short-term momentum analysis
Advanced Usage Tips
For Day Traders
1. **Opening Range Analysis**: Watch how price reacts to VWAP in the first hour of trading
2. **VWAP Reversions**: Look for trades when price touches outer bands and reverses toward VWAP
3. **Band Breakouts**: Strong moves beyond Band #2 may indicate momentum for continuation
For Swing Traders
1. **Use alongside daily/weekly support-resistance levels**
2. **Combine with EMA crossovers for trend confirmation**
3. **Identify potential reversal zones where price reaches Band #3**
Combined Strategies
- **EMA + VWAP Confluence**: Strong signals occur when EMA lines and VWAP/bands align at the same price level
- **High/Low + Band Touch**: When a high/low marker appears near a band, it may indicate a stronger support/resistance level
Conclusion
The VWAP Horizon Suite Optimized provides a comprehensive set of tools for price analysis based on volume-weighted data and exponential averages. By understanding and properly configuring the various components, you can create a powerful visual framework for identifying potential trading opportunities across multiple timeframes.
Remember that no indicator provides perfect signals, and the VWAP Horizon Suite works best when used as part of a complete trading strategy that includes risk management, multiple confirmation tools, and proper analysis of market conditions.
DISCLAIMER
**DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.**
EMA Cross CounterEMA Cross Counter – Trend & Crossover Analyzer
🔥 Description
The EMA Cross Counter is an advanced indicator designed to detect price crossovers with the EMA 200 and provide insightful trend analysis. It highlights valid signals and displays success statistics directly on the chart.
🎯 Key Features
✅ Crossover Detection: Identifies moments when the price crosses the EMA 200 upward or downward.
✅ Signal Filtering: Valid signals (leading to sustained trends) are shown in blue, while invalid signals are faded.
✅ Performance Analysis: A statistics table shows the number of crossovers and their success rate.
✅ Dynamic EMA Coloring:
🟢 Green when the trend is bullish
🔴 Red when the trend is bearish
⚪ Gray when the market is in a range
✅ Range Detection: If the price remains within a narrow range for 30 candles, the EMA turns gray to indicate trend uncertainty.
✅ Stop-Loss (SL) Display: A dashed red line appears below sell signals and above buy signals (adjustable in pips).
✅ Automatic Alerts: Get notified when a significant crossover occurs.
📈 How to Use It?
1️⃣ Look for blue signals as potential trade entries.
2️⃣ Avoid trading when the EMA is gray (ranging market).
3️⃣ Use success rate statistics to evaluate crossover reliability.
4️⃣ Adjust SL distance in the settings to match your risk management strategy.
🛠 Customization Options
Adjustable EMA period
Configurable range threshold
SL distance customizable in pips
Enable/Disable alerts
💡 Ideal for scalping and swing trading, this indicator offers clear trend insights to enhance your decision-making process!
💬 Try it out and share your feedback! 🚀
Mayer Multiple ZonesMayer Multiple Zones
The Mayer Multiple Zones indicator is a powerful market valuation tool that helps traders identify key price zones based on multiples of the 200-period moving average. Originally inspired by the Bitcoin Mayer Multiple concept, this versatile indicator works across all markets and timeframes to visualize the relative valuation of any asset.
Key Features:
Color-coded valuation zones: Instantly recognize if the current price represents a strong buy opportunity, fair value, or potential bubble territory
Customizable multiplier levels: Adjust all zone thresholds to suit specific markets or trading strategies
Real-time status indicator: Clear market status display showing current valuation zone
Comprehensive information table: View all critical price levels and current multiple at a glance
Multi-timeframe compatible: Works seamlessly across all timeframes while maintaining accurate MA200 reference
Visual zone labeling: Clear labels for each price zone directly on the chart
How to Use:
The indicator divides price action into six distinct zones based on the MA200:
Strong Buy Zone (default: below 0.6x MA200): Extreme undervaluation, historically excellent buying opportunities
Value Buy Zone (default: 0.6x-0.8x MA200): Attractive buying range for long-term value
Accumulation Zone (default: 0.8x-1.0x MA200): Price building strength below the MA200
Fair Value Zone (default: 1.0x-2.0x MA200): Reasonable valuation range
Take Profit Zone (default: 2.0x-2.5x MA200): Overvaluation suggesting partial profit taking
Bubble Zone (default: above 2.5x MA200): Extreme overvaluation, historically unsustainable levels
This indicator serves as both a strategic planning tool for long-term investors and a tactical guide for shorter-term traders, helping identify potential reversal zones and price targets based on historical valuation patterns.
Settings:
MA Length: Adjust the moving average period (default: 200)
Multipliers: Customize each zone threshold to adapt to specific market characteristics
Perfect for all traders seeking to understand relative market valuation across any timeframe.
DynamicMALibrary "DynamicMA"
Dynamic Moving Averages Library
Introduction
The Dynamic Moving Averages Library is a specialized collection of custom built functions designed to calculate moving averages dynamically, beginning from the first available bar. Unlike standard moving averages, which rely on fixed length lookbacks, this library ensures that indicators remain fully functional from the very first data point, making it an essential tool for analysing assets with short time series or limited historical data.
This approach allows traders and developers to build robust indicators that do not require a preset amount of historical data before generating meaningful outputs. It is particularly advantageous for:
Newly listed assets with minimal price history.
High-timeframe trading, where large lookback periods can lead to delayed or missing data.
By eliminating the constraints of fixed lookback periods, this library enables the seamless construction of trend indicators, smoothing functions, and hybrid models that adapt instantly to market conditions.
Comprehensive Set of Custom Moving Averages
The library includes a wide range of custom dynamic moving averages, each designed for specific analytical use cases:
SMA (Simple Moving Average) – The fundamental moving average, dynamically computed.
EMA (Exponential Moving Average) – Adaptive smoothing for better trend tracking.
DEMA (Double Exponential Moving Average) – Faster trend detection with reduced lag.
TEMA (Triple Exponential Moving Average) – Even more responsive than DEMA.
WMA (Weighted Moving Average) – Emphasizes recent price action while reducing noise.
VWMA (Volume Weighted Moving Average) – Accounts for volume to give more weight to high-volume periods.
HMA (Hull Moving Average) – A superior smoothing method with low lag.
SMMA (Smoothed Moving Average) – A hybrid approach between SMA and EMA.
LSMA (Least Squares Moving Average) – Uses linear regression for trend detection.
RMA (Relative Moving Average) – Used in RSI-based calculations for smooth momentum readings.
ALMA (Arnaud Legoux Moving Average) – A Gaussian-weighted MA for superior signal clarity.
Hyperbolic MA (HyperMA) – A mathematically optimized averaging method with dynamic weighting.
Each function dynamically adjusts its calculation length to match the available bar count, ensuring instant functionality on all assets.
Fully Optimized for Pine Script v6
This library is built on Pine Script v6, ensuring compatibility with modern TradingView indicators and scripts. It includes exportable functions for seamless integration into custom indicators, making it easy to develop trend-following models, volatility filters, and adaptive risk-management systems.
Why Use Dynamic Moving Averages?
Traditional moving averages suffer from a common limitation: they require a fixed historical window to generate meaningful values. This poses several problems:
New Assets Have No Historical Data - If an asset has only been trading for a short period, traditional moving averages may not be able to generate valid signals.
High Timeframes Require Massive Lookbacks - On 1W or 1M charts, a 200-period SMA would require 200 weeks or months of data, making it unusable on newer assets.
Delayed Signal Initialization - Standard indicators often take dozens of bars to stabilize, reducing effectiveness when trading new trends.
The Dynamic Moving Averages Library eliminates these issues by ensuring that every function:
Starts calculation from bar one, using available data instead of waiting for a lookback period.
Adapts dynamically across timeframes, making it equally effective on low or high timeframes.
Allows smoother, more responsive trend tracking, particularly useful for volatile or low-liquidity assets.
This flexibility makes it indispensable for custom script developers, quantitative analysts, and discretionary traders looking to build more adaptive and resilient indicators.
Final Summary
The Dynamic Moving Averages Library is a versatile and powerful set of functions designed to overcome the limitations of fixed-lookback indicators. By dynamically adjusting the calculation length from the first bar, this library ensures that moving averages remain fully functional across all timeframes and asset types, making it an essential tool for traders and developers alike.
With built-in adaptability, low-lag smoothing, and support for multiple moving average types, this library unlocks new possibilities for quantitative trading and strategy development - especially for assets with short price histories or those traded on higher timeframes.
For traders looking to enhance signal reliability, minimize lag, and build adaptable trading systems, the Dynamic Moving Averages Library provides an efficient and flexible solution.
SMA(sourceData, maxLength)
Dynamic SMA
Parameters:
sourceData (float)
maxLength (int)
EMA(src, length)
Dynamic EMA
Parameters:
src (float)
length (int)
DEMA(src, length)
Dynamic DEMA
Parameters:
src (float)
length (int)
TEMA(src, length)
Dynamic TEMA
Parameters:
src (float)
length (int)
WMA(src, length)
Dynamic WMA
Parameters:
src (float)
length (int)
HMA(src, length)
Dynamic HMA
Parameters:
src (float)
length (int)
VWMA(src, volsrc, length)
Dynamic VWMA
Parameters:
src (float)
volsrc (float)
length (int)
SMMA(src, length)
Dynamic SMMA
Parameters:
src (float)
length (int)
LSMA(src, length, offset)
Dynamic LSMA
Parameters:
src (float)
length (int)
offset (int)
RMA(src, length)
Dynamic RMA
Parameters:
src (float)
length (int)
ALMA(src, length, offset_sigma, sigma)
Dynamic ALMA
Parameters:
src (float)
length (int)
offset_sigma (float)
sigma (float)
HyperMA(src, length)
Dynamic HyperbolicMA
Parameters:
src (float)
length (int)
NSE Index Strategy with Entry/Exit MarkersExplanation of the Code
Trend Filter (200 SMA):
The line trendSMA = ta.sma(close, smaPeriod) calculates the 200‑period simple moving average. By trading only when the current price is above this SMA (inUptrend = close > trendSMA), we aim to trade in the direction of the dominant trend.
RSI Entry Signal:
The RSI is calculated with rsiValue = ta.rsi(close, rsiPeriod). The script checks for an RSI crossover above the oversold threshold using ta.crossover(rsiValue, rsiOversold). This helps capture a potential reversal from a minor pullback in an uptrend.
ATR-Based Exits:
ATR is computed by atrValue = ta.atr(atrPeriod) and is used to set the stop loss and take profit levels:
Stop Loss: stopLossPrice = close - atrMultiplier * atrValue
Take Profit: takeProfitPrice = close + atrMultiplier * atrValue
This dynamic approach allows the exit levels to adjust according to the current market volatility.
Risk and Money Management:
The strategy uses a fixed percentage of equity (10% by default) for each trade. The built‑in commission parameter helps simulate real-world trading costs.
TradFi Fundamentals: Enhanced Macroeconomic Momentum Trading Introduction
The "Enhanced Momentum with Advanced Normalization and Smoothing" indicator is a tool that combines traditional price momentum with a broad range of macroeconomic factors. I introduced the basic version from a research paper in my last script. This one leverages not only the price action of a security but also incorporates key economic data—such as GDP, inflation, unemployment, interest rates, consumer confidence, industrial production, and market volatility (VIX)—to create a comprehensive, normalized momentum score.
Previous indicator
Explanation
In plain terms, the indicator calculates a raw momentum value based on the change in price over a defined lookback period. It then normalizes this momentum, along with several economic indicators, using a method chosen by the user (options include simple, exponential, or weighted moving averages, as well as a median absolute deviation (MAD) approach). Each normalized component is assigned a weight reflecting its relative importance, and these weighted values are summed to produce an overall momentum score.
To reduce noise, the combined momentum score can be further smoothed using a user-selected method.
Signals
For generating trade signals, the indicator offers two modes:
Zero Cross Mode: Signals occur when the smoothed momentum line crosses the zero threshold.
Zone Mode: Overbought and oversold boundaries (which are user defined) provide signals when the momentum line crosses these preset limits.
Definition of the Settings
Price Momentum Settings:
Price Momentum Lookback: The number of days used to compute the percentage change in price (default 50 days).
Normalization Period (Price Momentum): The period over which the price momentum is normalized (default 200 days).
Economic Data Settings:
Normalization Period (Economic Data): The period used to normalize all economic indicators (default 200 days).
Normalization Method: Choose among SMA, EMA, WMA, or MAD to standardize both price and economic data. If MAD is chosen, a multiplier factor is applied (default is 1.4826).
Smoothing Options:
Apply Smoothing: A toggle to enable further smoothing of the combined momentum score.
Smoothing Period & Method: Define the period and type (SMA, EMA, or WMA) used to smooth the final momentum score.
Signal Generation Settings:
Signal Mode: Select whether signals are based on a zero-line crossover or by crossing user-defined overbought/oversold (OB/OS) zones.
OB/OS Zones: Define the upper and lower boundaries (default upper zones at 1.0 and 2.0, lower zones at -1.0 and -2.0) for zone-based signals.
Weights:
Each component (price momentum, GDP, inflation, unemployment, interest rates, consumer confidence, industrial production, and VIX) has an associated weight that determines its contribution to the overall score. These can be adjusted to reflect different market views or risk preferences.
Visual Aspects
The indicator plots the smoothed combined momentum score as a continuous blue line against a dotted zero-line reference. If the Zone signal mode is selected, the indicator also displays the upper and lower OB/OS boundaries as horizontal lines (red for overbought and green for oversold). Buy and sell signals are marked by small labels ("B" for buy and "S" for sell) that appear at the bottom or top of the chart when the score crosses the defined thresholds, allowing traders to quickly identify potential entry or exit points.
Conclusion
This enhanced indicator provides traders with a robust approach to momentum trading by integrating traditional price-based signals with a suite of macroeconomic indicators. Its normalization and smoothing techniques help reduce noise and mitigate the effects of outliers, while the flexible signal generation modes offer multiple ways to interpret market conditions. Overall, this tool is designed to deliver a more nuanced perspective on market momentum.
Stock ETF Tracker 2.0The Stock Sector ETF tracker with Indicators is a versatile tool designed to track the performance of sector-specific ETFs relative to the current asset. It automatically identifies the sector of the underlying symbol and displays the corresponding ETF’s price action alongside key technical indicators. This helps traders analyze sector trends and correlations in real time.
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Key Features
Automatic Sector Detection:
Fetches the sector of the current asset (e.g., "Technology" for AAPL).
Maps the sector to a user-defined ETF (default: SPDR sector ETFs) .
Technical Indicators:
Simple Moving Average (SMA): Tracks the ETF’s trend.
Bollinger Bands: Highlights volatility and potential reversals.
Donchian High (52-Week High): Identifies long-term resistance levels.
SPY Regime Filter: Red background color if SP500 is below 200 day SMA.
Customizable Inputs:
Adjust indicator parameters (length, visibility).
Override default ETFs for specific sectors.
Informative Table:
Displays the current sector and ETF symbol in the bottom-right corner.
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Input Settings
SMA Settings
SMA Length: Period for calculating the Simple Moving Average (default: 200).
Show SMA: Toggle visibility of the SMA line.
Bollinger Bands Settings
BB Length: Period for Bollinger Bands calculation (default: 20).
BB Multiplier: Standard deviation multiplier (default: 2.0).
Show Bollinger Bands: Toggle visibility of the bands.
Donchian High (52-Week High)
Daily High Length: Days used to calculate the high (default: 252, approx. 1 year).
Show High: Toggle visibility of the 52-week high line.
Sector Selections
Customize ETFs for each sector (e.g., replace XLU with another utilities ETF).
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Example Use Cases
Trend Analysis: Compare a stock’s price action to its sector ETF’s SMA for trend confirmation.
Volatility Signals: Use Bollinger Bands to spot ETF price squeezes or breakouts.
Sector Strength: Monitor if the ETF is approaching its 52-week high to gauge sector momentum.
Enjoy tracking sector trends with ease! 🚀
MA Deviation with Volatility ThresholdsPrice Deviation from MA with Dynamic Thresholds - TradingView Script Description
Overview
The Price Deviation from Moving Average (MA) with Dynamic Thresholds indicator is designed to measure and visualize how far the current price deviates from a chosen moving average (SMA or EMA) in percentage terms. It provides traders with valuable insights into whether the asset is significantly overbought or oversold relative to its historical mean.
One of the standout features of this indicator is its ability to dynamically adjust overbought and oversold thresholds based on historical volatility, making it more adaptable across different asset classes and market conditions.
Key Features
✅ Customizable Moving Average
Choose between Simple Moving Average (SMA) or Exponential Moving Average (EMA).
Adjustable MA period (default: 200).
Select the timeframe for the MA calculation (default: Daily).
✅ Percentage-Based Deviation Measurement
Measures how much the price has deviated from the selected moving average in percentage terms.
Helps to identify extreme price movements relative to historical trends.
✅ Static & Dynamic Overbought/Oversold Thresholds
Static Thresholds: Users can set fixed percentage levels for overbought and oversold conditions (default: ±20%).
Dynamic Thresholds (enabled by default): Automatically adjust based on historical volatility.
Uses standard deviation of price changes over a specified period (default: 200 candles).
Thresholds are calculated as volatility × a user-defined multiplier (default: 10).
✅ Visual Enhancements
Background Highlighting:
Red when the price exceeds the overbought threshold.
Green when the price drops below the oversold threshold.
Area Chart Representation: The deviation is plotted as a filled orange area (30% opacity) to enhance visual clarity.
Zero Line in Yellow: Helps in quickly identifying when the price is near the moving average.
How to Use
📌 Trend Confirmation & Mean Reversion Trading:
If the deviation is consistently positive, it indicates an uptrend, while negative values suggest a downtrend.
If the price significantly deviates from the MA and enters the overbought/oversold zone, a potential mean reversion opportunity may arise.
📌 Volatility-Adaptive Thresholds:
When enabled, dynamic thresholds help to adjust for different asset volatilities.
Suitable for traders dealing with assets that exhibit varying levels of price fluctuations.
📌 Combining with Other Indicators:
Works well with RSI, Bollinger Bands, and MACD to confirm trend strength or potential reversals.
Can be used in conjunction with support & resistance levels for added confirmation.
Customization Options
Moving Average Type: SMA or EMA.
Moving Average Period & Timeframe Selection.
Static Overbought/Oversold Levels.
Dynamic Thresholds:
Toggle ON/OFF.
Set the Lookback Period for volatility calculation.
Adjust the Volatility Multiplier for fine-tuning threshold sensitivity.
Why Use This Indicator?
🔹 Adaptive to Different Markets: Works with stocks, forex, crypto, commodities, and indices.
🔹 Useful for Both Trend-Following & Mean Reversion Strategies.
🔹 Volatility-Based Adjustments Ensure Market-Relevant Thresholds.
🔹 Enhances Market Awareness by Identifying Extreme Price Deviations.
Final Thoughts
The Price Deviation from MA with Dynamic Thresholds indicator is a powerful tool for traders who want to gauge price extremes and identify potential turning points in the market. With both static and dynamic threshold options, it can be tailored to different trading styles and asset behaviors.
💡 Tip: Experiment with different MA types, periods, and volatility multipliers to find settings that best suit your preferred trading strategy. 🚀
Support Resistance - Percentile LevelsKey Features:
1. Percentile Calculations:
The indicator calculates the 95th percentile (PercentilePlot100) and the 5th percentile (PercentilePlot5) of the high and low prices over specified lengths.
The lengths for these calculations are adjustable via input fields, allowing users to customize the periods used for percentile calculations.
2. Percentile Levels:
Resistance Levels (R1, R2, R3, R4): Plots resistance levels based on the 95th percentile of the high prices over different lengths (100, 200, 750, 4500).
Support Levels (S1, S2, S3, S4): Plots support levels based on the 5th percentile of the low prices over different lengths (100, 200, 750, 4500).
3. High-Timeframe Average:
Calculates and plots the average of the 750-period high and low percentiles (htfavg), which acts as a pivot point on the chart.
How to Use This Indicator:
1. Identify Key Support and Resistance Levels:
Use the plotted resistance (R1, R2, R3, R4) and support (S1, S2, S3, S4) levels to identify key areas where price may reverse or consolidate.
2. Pivot Point Analysis:
The plotted pivot point (htfavg) can be used to identify potential areas of trend change or consolidation. It represents the average price level based on higher timeframe percentiles.
3. Trend Analysis:
By observing how price interacts with these percentile levels, traders can gain insights into market trends and potential reversal points.
Customization:
The input fields allow you to customize the lengths of the percentiles and the percentile plot values according to your trading strategy and timeframe preference.
In summary, this indicator can help traders identify significant support and resistance levels, potential pivot points, and overall market trends based on percentile calculations of high and low prices over various periods. This can be valuable for making informed trading decisions and setting entry and exit points.
If you have any specific questions or need further customization, feel free to ask! 😊
TradFi Fundamentals: Momentum Trading with Macroeconomic DataIntroduction
This indicator combines traditional price momentum with key macroeconomic data. By retrieving GDP, inflation, unemployment, and interest rates using security calls, the script automatically adapts to the latest economic data. The goal is to blend technical analysis with fundamental insights to generate a more robust momentum signal.
Original Research Paper by Mohit Apte, B. Tech Scholar, Department of Computer Science and Engineering, COEP Technological University, Pune, India
Link to paper
Explanation
Price Momentum Calculation:
The indicator computes price momentum as the percentage change in price over a configurable lookback period (default is 50 days). This raw momentum is then normalized using a rolling simple moving average and standard deviation over a defined period (default 200 days) to ensure comparability with the economic indicators.
Fetching and Normalizing Economic Data:
Instead of manually inputting economic values, the script uses TradingView’s security function to retrieve:
GDP from ticker "GDP"
Inflation (CPI) from ticker "USCCPI"
Unemployment rate from ticker "UNRATE"
Interest rates from ticker "USINTR"
Each series is normalized over a configurable normalization period (default 200 days) by subtracting its moving average and dividing by its standard deviation. This standardization converts each economic indicator into a z-score for direct integration into the momentum score.
Combined Momentum Score:
The normalized price momentum and economic indicators are each multiplied by user-defined weights (default: 50% price momentum, 20% GDP, and 10% each for inflation, unemployment, and interest rates). The weighted components are then summed to form a comprehensive momentum score. A horizontal zero line is plotted for reference.
Trading Signals:
Buy signals are generated when the combined momentum score crosses above zero, and sell signals occur when it crosses below zero. Visual markers are added to the chart to assist with trade timing, and alert conditions are provided for automated notifications.
Settings
Price Momentum Lookback: Defines the period (in days) used to compute the raw price momentum.
Normalization Period for Price Momentum: Sets the window over which the price momentum is normalized.
Normalization Period for Economic Data: Sets the window over which each macroeconomic series is normalized.
Weights: Adjust the influence of each component (price momentum, GDP, inflation, unemployment, and interest rate) on the overall momentum score.
Conclusion
This implementation leverages TradingView’s economic data feeds to integrate real-time macroeconomic data into a momentum trading strategy. By normalizing and weighting both technical and economic inputs, the indicator offers traders a more holistic view of market conditions. The enhanced momentum signal provides additional context to traditional momentum analysis, potentially leading to more informed trading decisions and improved risk management.
The next script I release will be an improved version of this that I have added my own flavor to, improving the signals.
[SHORT ONLY] Consecutive Close>High[1] Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Consecutive Close > High " Mean Reversion Strategy is a contrarian daily trading system for stocks and ETFs. It identifies potential shorting opportunities by counting consecutive days where the closing price exceeds the previous day's high. When this consecutive day count reaches a predetermined threshold, and if the close is below a 200-period EMA (if enabled), a short entry is triggered, anticipating a corrective pullback.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy uses a counter variable called `bullCount` to track how many consecutive bars meet a bullish condition. Here’s a breakdown of the process:
Initialize the Counter
var int bullCount = 0
Bullish Bar Detection
Every time the close exceeds the previous bar's high, increment the counter:
if close > high
bullCount += 1
Reset on Bearish Bar
When there is a clear bearish reversal, the counter is reset to zero:
if close < low
bullCount := 0
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The count of consecutive bullish closes (where close > high ) reaches or exceeds the defined threshold (default: 3).
The signal occurs within the specified trading window (between Start Time and End Time).
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish closes required to trigger a short entry (default is 3).
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
EMA Filter (Optional): When enabled, short entries are only triggered if the current close is below the 200-period EMA.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs on the Daily timeframe and targets overextended bullish moves.
It aims to capture mean reversion by entering short after a series of consecutive bullish closes.
Further optimization is possible with additional filters (e.g., EMA, volume, or volatility).
Backtesting should be used to fine-tune the threshold and filter settings for specific market conditions.
Nearest EMA Levels (Multi-Timeframe)This indicator identifies the closest upper and lower EMA levels across multiple timeframes, helping traders spot trend direction and key support/resistance zones.
📌 Key Features:
✔ Multi-Timeframe Support: Works across 1min to 1W timeframes.
✔ Customizable EMAs:
1min & 5min: Only 200 EMA.
Other timeframes: 20, 50, 100, and 200 EMA.
✔ Auto Detection: Highlights the nearest EMA levels above and below price.
✔ Customizable Display: Adjustable line style, thickness, and colors.
✔ Clear Labels: Shows EMA value and timeframe for easy interpretation.
🛠 How to Use:
Enable preferred timeframes and adjust visual settings.
Nearest EMA levels are plotted automatically.
Labels indicate timeframe and EMA value.
⚠ Note:
For technical analysis only, not financial advice.
1M timeframe removed due to TradingView API limits.
Too many EMAs may clutter the chart—enable only needed timeframes.
🚀 Perfect for:
✔ Trend Identification
✔ Support & Resistance Analysis
✔ Short & Long-Term Market Tracking
RSI Bands with Volume and EMAThis script is a comprehensive technical analysis tool designed to help traders identify key market signals using RSI bands, volume, and multiple Exponential Moving Averages (EMAs). It overlays the following on the chart:
RSI Bands: The script calculates and plots two bands based on the Relative Strength Index (RSI), indicating overbought and oversold levels. These bands act as dynamic support and resistance zones:
Resistance Band (Upper Band): Plotted when the RSI exceeds the overbought level, typically indicating a potential sell signal.
Support Band (Lower Band): Plotted when the RSI falls below the oversold level, typically indicating a potential buy signal.
Midline: The average of the upper and lower bands, acting as a neutral reference.
Buy/Sell Labels: Labels are dynamically added to the chart when price reaches the overbought or oversold levels.
A "Buy" label appears when the price reaches the oversold (lower) band.
A "Sell" label appears when the price reaches the overbought (upper) band.
Volume Indicator: The script visualizes trading volume as histograms, with red or green bars representing decreasing or increasing volume, respectively. The volume height is visually reduced for better clarity and comparison.
Exponential Moving Averages (EMAs): The script calculates and plots four key EMAs (12, 26, 50, and 200) to highlight short-term, medium-term, and long-term trends:
EMA 12: Blue
EMA 26: Orange
EMA 50: Purple
EMA 200: Green
The combined use of RSI, volume, and EMAs offers traders a multi-faceted view of the market, assisting in making informed decisions about potential price reversals, trends, and volume analysis. The script is particularly useful for identifying entry and exit points on charts like BTC/USDT, although it can be applied to any asset.
3 Down, 3 Up Strategy█ STRATEGY DESCRIPTION
The "3 Down, 3 Up Strategy" is a mean-reversion strategy designed to capitalize on short-term price reversals. It enters a long position after consecutive bearish closes and exits after consecutive bullish closes. This strategy is NOT optimized and can be used on any timeframes.
█ WHAT ARE CONSECUTIVE DOWN/UP CLOSES?
- Consecutive Down Closes: A sequence of trading bars where each close is lower than the previous close.
- Consecutive Up Closes: A sequence of trading bars where each close is higher than the previous close.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The price closes lower than the previous close for Consecutive Down Closes for Entry (default: 3) consecutive bars.
The signal occurs within the specified time window (between Start Time and End Time).
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average).
2. EXIT CONDITION
A Sell Signal is generated when the price closes higher than the previous close for Consecutive Up Closes for Exit (default: 3) consecutive bars.
█ ADDITIONAL SETTINGS
Consecutive Down Closes for Entry: Number of consecutive lower closes required to trigger a buy. Default = 3.
Consecutive Up Closes for Exit: Number of consecutive higher closes required to exit. Default = 3.
EMA Filter: Optional 200-period EMA filter to confirm long entries in bullish trends. Default = disabled.
Start Time and End Time: Restrict trading to specific dates (default: 2014-2099).
█ PERFORMANCE OVERVIEW
Designed for volatile markets with frequent short-term reversals.
Performs best when price oscillates between clear support/resistance levels.
The EMA filter improves reliability in trending markets but may reduce trade frequency.
Backtest to optimize consecutive close thresholds and EMA period for specific instruments.
3-Bar Low Strategy█ STRATEGY DESCRIPTION
The "3-Bar Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous three bars. It enters a long position when specific conditions are met and exits when the price exceeds the highest high of the previous seven bars. This strategy is suitable for use on various timeframes.
█ WHAT IS THE 3-BAR LOW?
The 3-Bar Low is the lowest price observed over the last three bars. This level is used as a reference to identify potential oversold conditions and reversal points.
█ WHAT IS THE 7-BAR HIGH?
The 7-Bar High is the highest price observed over the last seven bars. This level is used as a reference to identify potential overbought conditions and exit points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous three bars (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
If the EMA Filter is enabled, the close price must also be above the 200-period Exponential Moving Average (EMA).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the highest high of the previous seven bars (`close > _highest `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
MA Period: The lookback period for the 200-period EMA used in the EMA Filter. Default is 200.
Use EMA Filter: Enables or disables the EMA Filter for long entries. Default is disabled.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support and resistance levels.
It is sensitive to oversold conditions, as indicated by the 3-Bar Low, and overbought conditions, as indicated by the 7-Bar High.
Backtesting results should be analyzed to optimize the MA Period and EMA Filter settings for specific instruments.
Turn around Tuesday on Steroids Strategy█ STRATEGY DESCRIPTION
The "Turn around Tuesday on Steroids Strategy" is a mean-reversion strategy designed to identify potential price reversals at the start of the trading week. It enters a long position when specific conditions are met and exits when the price shows strength by exceeding the previous bar's high. This strategy is optimized for ETFs, stocks, and other instruments on the daily timeframe.
█ WHAT IS THE STARTING DAY?
The Starting Day determines the first day of the trading week for the strategy. It can be set to either Sunday or Monday, depending on the instrument being traded. For ETFs and stocks, Monday is recommended. For other instruments, Sunday is recommended.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day is the first day of the trading week (either Sunday or Monday, depending on the Starting Day setting).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
If the MA Filter is enabled, the close price must also be above the 200-period Simple Moving Average (SMA).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Starting Day: Determines the first day of the trading week. Options are Sunday or Monday. Default is Sunday.
Use MA Filter: Enables or disables the 200-period SMA filter for long entries. Default is disabled.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for markets with frequent weekly reversals.
It performs best in volatile conditions where price movements are significant at the start of the trading week.
Backtesting results should be analysed to optimize the Starting Day and MA Filter settings for specific instruments.
Moving Average Crossover Strategy with Take Profit and Stop LossThe Moving Average Crossover Strategy is a popular trading technique that utilizes two moving averages (MAs) of different periods to identify potential buy and sell signals. By incorporating take profit and stop loss levels, traders can effectively manage their risk while maximizing potential returns. Here’s a detailed explanation of how this strategy works:
Overview of the Moving Average Crossover Strategy
Moving Averages:
A short-term moving average (e.g., 50-day MA) reacts more quickly to price changes, while a long-term moving average (e.g., 200-day MA) smooths out price fluctuations over a longer period.
The strategy generates trading signals based on the crossover of these two averages:
Buy Signal: When the short-term MA crosses above the long-term MA (often referred to as a "Golden Cross").
Sell Signal: When the short-term MA crosses below the long-term MA (known as a "Death Cross").
Implementing Take Profit and Stop Loss
1. Setting Take Profit Levels
Definition: A take profit order automatically closes a trade when it reaches a specified profit level.
Strategy:
Determine a realistic profit target based on historical price action, support and resistance levels, or a fixed risk-reward ratio (e.g., 2:1).
For instance, if you enter a buy position at $100, you might set a take profit at $110 if you anticipate that level will act as resistance.
2. Setting Stop Loss Levels
Definition: A stop loss order limits potential losses by closing a trade when the price reaches a specified level.
Strategy:
Place the stop loss just below the most recent swing low for buy orders or above the recent swing high for sell orders.
Alternatively, you can use a percentage-based method (e.g., 2-3% below the entry point) to define your stop loss.
For example, if you enter a buy position at $100 with a stop loss set at $95, your maximum loss would be limited to $5 per share.
Example of Using Moving Average Crossover with Take Profit and Stop Loss
Entry Signal:
You observe that the 50-day MA crosses above the 200-day MA at $100. You enter a buy position.
Setting Take Profit and Stop Loss:
You analyze historical price levels and set your take profit at $110.
You place your stop loss at $95 based on recent swing lows.
Trade Management:
If the price rises to $110, your take profit order is executed, securing your profit.
If the price falls to $95, your stop loss is triggered, limiting your losses.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
