Time-based Alerts for Trading Windows🌟 Time-based Alerts for Trading Windows 🌐📈
This is a re-uploaded script as the previous one got hidden.
This Time-based Alerts for Trading Windows script is a highly customizable and reliable tool designed to assist traders in managing automated strategies or manually monitoring specific market conditions. Inspired by CrossTrade's Time-based Alert, this script is tailored for those who rely on precise time windows to trigger actions, such as sending webhook signals or managing Expert Advisors (EAs).
Whether you are a scalper, day trader, or algorithmic trader, this script empowers you to stay on top of your trades with fully customizable time-based alerts.
🛠️ Customizable Time Alerts
This indicator allows you to create up to 12 unique time windows by specifying the exact hour and minute for each alert. Each time window corresponds to an individual alert condition, making it perfect for managing trades during specific market sessions or key time periods.
For example:
Alert 1 can be set at 9:30 AM (market open).
Alert 2 can be set at 3:55 PM (just before market close).
Each alert can be toggled on or off in the indicator settings, allowing you to manage alerts without having to reconfigure your script.
You can adjust the colours to fit any colour scheme you like!
🕒 Odd and Even Time Alerts
The script comes with three built-in alert type categories:
Odd Alerts (marked with a green triangle on the chart): These correspond to odd-numbered inputs like Alert 1, Alert 3, Alert 5, and so on.
Even Alerts (marked with a red triangle on the chart): These correspond to even-numbered inputs like Alert 2, Alert 4, Alert 6, and so on.
You can also customize all 12 alerts individually to include a custom alert message
These alerts serve as a convenient way to differentiate between multiple trading strategies or market conditions. You can customize alert messages for odd and even alerts directly from TradingView’s alert panel.
🔗 Webhook Integration for Automation
This script is fully compatible with webhook-based automation. By configuring your alerts in TradingView, you can send signals to trading bots, EAs, or any third-party system. For example, you can:
Turn off an EA at a specific time (e.g., 3:55 PM EST).
Send buy/sell signals to your bot during predefined trading windows.
Simply use TradingView’s alert message editor to format webhook payloads for your automation system.
🌐 Timezone Flexibility
Trading happens across multiple time zones, and this script accounts for that. You can toggle between:
Eastern Time (New York): Ideal for most US-based markets.
Central Time (Exchange): Useful for futures and commodities traders.
This ensures your alerts are always in sync with your preferred time zone, eliminating confusion.
🎨 Visual Indicators
The script plots visual markers directly on your chart to indicate active alerts:
Up Facing Triangles: Represent odd-numbered alerts, providing a quick reference for these time windows.
Down Facing Triangles: Represent even-numbered alerts, helping you track different strategies or conditions.
These visual markers make it easy to see when alerts are triggered, even at a glance.
📈 Practical Use Case
Let’s say you’re trading the USTEC index on a 1-minute chart. You want to:
Turn off your trading bot at 16:55 EST to avoid after-market volatility.
Trigger a re-entry signal at 17:30 EST to capture moves during the Asian session.
Visually monitor these actions on your chart for easy reference.
This script makes it possible with precision alerts and webhook integration. Simply configure the time windows in the settings and set up your alerts in TradingView.
🚨 How to Set Up Alerts
Enable or Disable Alerts: Use the script’s settings to toggle specific alerts on or off as needed.
Set Custom Time Windows: Define the hour and minute for each alert in the settings panel.
Create Alerts in TradingView:
Go to the TradingView alert panel.
Select the condition (e.g., "Odd Time-based Alert (Green)" or "Even Time-based Alert (Red)").
Customize the alert message for webhook integration or personal notification.
Choose the trigger type: Once Per Bar or Once Per Bar Close to keep the alert active.
Integrate with Webhooks: Use the alert message field to format payloads for automation systems like MT4, MT5, or third-party bots.
📋 Key Notes
Alerts can trigger indefinitely if set to "Once Per Bar" or "Once Per Bar Close".
Always ensure the expiration date is set far in the future to avoid unexpected alert deactivation.
Test webhook messages and alert configurations thoroughly before using them in live trading.
This script is a powerful addition to your trading toolbox, offering precision, flexibility, and automation capabilities. Whether you’re turning off an EA, managing trades during market sessions, or automating strategies via webhooks, this script is here to support you.
Start using the Time-based Alerts for Trading Windows today and trade with confidence! 🚀✨
Signals
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.
[COG]StochRSI Zenith📊 StochRSI Zenith
This indicator combines the traditional Stochastic RSI with enhanced visualization features and multi-timeframe analysis capabilities. It's designed to provide traders with a comprehensive view of market conditions through various technical components.
🔑 Key Features:
• Advanced StochRSI Implementation
- Customizable RSI and Stochastic calculation periods
- Multiple moving average type options (SMA, EMA, SMMA, LWMA)
- Adjustable signal line parameters
• Visual Enhancement System
- Dynamic wave effect visualization
- Energy field display for momentum visualization
- Customizable color schemes for bullish and bearish signals
- Adaptive transparency settings
• Multi-Timeframe Analysis
- Higher timeframe confirmation
- Synchronized market structure analysis
- Cross-timeframe signal validation
• Divergence Detection
- Automated bullish and bearish divergence identification
- Customizable lookback period
- Clear visual signals for confirmed divergences
• Signal Generation Framework
- Price action confirmation
- SMA-based trend filtering
- Multiple confirmation levels for reduced noise
- Clear entry signals with customizable display options
📈 Technical Components:
1. Core Oscillator
- Base calculation: 13-period RSI (adjustable)
- Stochastic calculation: 8-period (adjustable)
- Signal lines: 5,3 smoothing (adjustable)
2. Visual Systems
- Wave effect with three layers of visualization
- Energy field display with dynamic intensity
- Reference bands at 20/30/50/70/80 levels
3. Confirmation Mechanisms
- SMA trend filter
- Higher timeframe alignment
- Price action validation
- Divergence confirmation
⚙️ Customization Options:
• Visual Parameters
- Wave effect intensity and speed
- Energy field sensitivity
- Color schemes for bullish/bearish signals
- Signal display preferences
• Technical Parameters
- All core calculation periods
- Moving average types
- Divergence detection settings
- Signal confirmation criteria
• Display Settings
- Chart and indicator signal placement
- SMA line visualization
- Background highlighting options
- Label positioning and size
🔍 Technical Implementation:
The indicator combines several advanced techniques to generate signals. Here are key components with code examples:
1. Core StochRSI Calculation:
// Base RSI calculation
rsi = ta.rsi(close, rsi_length)
// StochRSI transformation
stochRSI = ((ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) != 0) ?
(100 * (rsi - ta.lowest(rsi, stoch_length))) /
(ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) : 0
2. Signal Generation System:
// Core signal conditions
crossover_buy = crossOver(sk, sd, cross_threshold)
valid_buy_zone = sk < 30 and sd < 30
price_within_sma_bands = close <= sma_high and close >= sma_low
// Enhanced signal generation
if crossover_buy and valid_buy_zone and price_within_sma_bands and htf_allows_long
if is_bullish_candle
long_signal := true
else
awaiting_bull_confirmation := true
3. Multi-Timeframe Analysis:
= request.security(syminfo.tickerid, mtf_period,
)
The HTF filter looks at a higher timeframe (default: 4H) to confirm the trend
It only allows:
Long trades when the higher timeframe is bullish
Short trades when the higher timeframe is bearish
📈 Trading Application Guide:
1. Signal Identification
• Oversold Opportunities (< 30 level)
- Look for bullish crosses of K-line above D-line
- Confirm with higher timeframe alignment
- Wait for price action confirmation (bullish candle)
• Overbought Conditions (> 70 level)
- Watch for bearish crosses of K-line below D-line
- Verify higher timeframe condition
- Confirm with bearish price action
2. Divergence Trading
• Bullish Divergence
- Price makes lower lows while indicator makes higher lows
- Most effective when occurring in oversold territory
- Use with support levels for entry timing
• Bearish Divergence
- Price makes higher highs while indicator shows lower highs
- Most reliable in overbought conditions
- Combine with resistance levels
3. Wave Effect Analysis
• Strong Waves
- Multiple wave lines moving in same direction indicate momentum
- Wider wave spread suggests increased volatility
- Use for trend strength confirmation
• Energy Field
- Higher intensity in trading zones suggests stronger moves
- Use for momentum confirmation
- Watch for energy field convergence with price action
The energy field is like a heat map that shows momentum strength
It gets stronger (more visible) when:
Price is in oversold (<30) or overbought (>70) zones
The indicator lines are moving apart quickly
A strong signal is forming
Think of it as a "strength meter" - the more visible the energy field, the stronger the potential move
4. Risk Management Integration
• Entry Confirmation
- Wait for all signal components to align
- Use higher timeframe for trend direction
- Confirm with price action and SMA positions
• Stop Loss Placement
- Consider placing stops beyond recent swing points
- Use ATR for dynamic stop calculation
- Account for market volatility
5. Position Management
• Partial Profit Taking
- Consider scaling out at overbought/oversold levels
- Use wave effect intensity for exit timing
- Monitor energy field for momentum shifts
• Trade Duration
- Short-term: Use primary signals in trading zones
- Swing trades: Focus on divergence signals
- Position trades: Utilize higher timeframe signals
⚠️ Important Usage Notes:
• Avoid:
- Trading against strong trends
- Relying solely on single signals
- Ignoring higher timeframe context
- Over-leveraging based on signals
Remember: This tool is designed to assist in analysis but should never be used as the sole decision-maker for trades. Always maintain proper risk management and combine with other forms of analysis.
[SHORT ONLY] 10 Bar Low Pullback█ STRATEGY DESCRIPTION
The "10 Bar Low Pullback" strategy is a contrarian short trading system designed to capture pullbacks after a new 10‐bar low is made. it identifies a potential short opportunity when the current bar’s low breaks below the lowest low of the previous 10 bars, provided that the bar exhibits strong internal momentum as measured by its IBS value. An optional trend filter further refines entries by requiring that the close is below a 200-period EMA.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
ibs = (close - low) / (high - low)
- Low IBS (≤ 0.2): Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8): Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current bar’s low is below the lowest low of the past X bars (default: 10).
The bar’s IBS is greater than the specified threshold (default: 0.85).
The signal occurs within the defined trading window (between Start Time and End Time).
If the EMA Filter is enabled, the close must be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
Lookback Period: Defines the number of bars (default is 10) over which the lowest low is calculated.
IBS Threshold: Sets the minimum required IBS value (default is 0.85) to qualify as a pullback.
Trading Window: Trades are only executed between the user-defined Start Time and End Time.
EMA Filter (Optional): When enabled, short entries are only considered if the current close is below the 200-period EMA, with the EMA period being adjustable (default is 200).
█ PERFORMANCE OVERVIEW
Designed for shorting opportunities, this strategy aims to capture pullbacks following an aggressive 10-bar low break.
It leverages a combination of a lookback low and IBS measurement to identify overextended bullish moves that may revert.
The optional EMA filter helps confirm a bearish market environment by ensuring the price remains under the trend line.
Suitable for use on various assets, including stocks and ETFs, on daily or similar timeframes.
Backtesting and parameter optimization are recommended to tailor the strategy to specific market conditions.
[SHORT ONLY] ATR Sell the Rip Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "ATR Sell the Rip Mean Reversion Strategy" is a contrarian system that targets overextended price moves on stocks and ETFs. It calculates an ATR‐based trigger level to identify shorting opportunities. When the current close exceeds this smoothed ATR trigger, and if the close is below a 200-period EMA (if enabled), the strategy initiates a short entry, aiming to profit from an anticipated corrective pullback.
█ HOW IS THE ATR SIGNAL BAND CALCULATED?
This strategy computes an ATR-based signal trigger as follows:
Calculate the ATR
The strategy computes the Average True Range (ATR) using a configurable period provided by the user:
atrValue = ta.atr(atrPeriod)
Determine the Threshold
Multiply the ATR by a predefined multiplier and add it to the current close:
atrThreshold = close + atrValue * atrMultInput
Smooth the Threshold
Apply a Simple Moving Average over a specified period to smooth out the threshold, reducing noise:
signalTrigger = ta.sma(atrThreshold, smoothPeriodInput)
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current close is above the smoothed ATR signal trigger.
The trade occurs within the specified trading window (between Start Time and End Time).
If the EMA filter is enabled, the close must also be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
ATR Period: The period used to calculate the ATR, allowing for adaptability to different volatility conditions (default is 20).
ATR Multiplier: The multiplier applied to the ATR to determine the raw threshold (default is 1.0).
Smoothing Period: The period over which the raw ATR threshold is smoothed using an SMA (default is 10).
Start Time and End Time: Defines the time window during which trades are allowed.
EMA Filter (Optional): When enabled, short entries are only executed if the current close is below the 200-period EMA, confirming a bearish trend.
█ PERFORMANCE OVERVIEW
This strategy is designed for use on the Daily timeframe, targeting stocks and ETFs by capitalizing on overextended price moves.
It utilizes a dynamic, ATR-based trigger to identify when prices have potentially peaked, setting the stage for a mean reversion short entry.
The optional EMA filter helps align trades with broader market trends, potentially reducing false signals.
Backtesting is recommended to fine-tune the ATR multiplier, smoothing period, and EMA settings to match the volatility and behavior of specific markets.
[SHORT ONLY] Consecutive Bars Above MA Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above MA Strategy" is a contrarian trading system aimed at exploiting overextended bullish moves in stocks and ETFs. It monitors the number of consecutive bars that close above a chosen short-term moving average (which can be either a Simple Moving Average or an Exponential Moving Average). Once the count reaches a preset threshold and the current bar’s close exceeds the previous bar’s high within a designated trading window, a short entry is initiated. An optional EMA filter further refines entries by requiring that the current close is below the 200-period EMA, helping to ensure that trades are taken in a bearish environment.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy utilizes a counter variable, `bullCount`, to track consecutive bullish bars based on their relation to the short-term moving average. Here’s how the count is determined:
Initialize the Counter
The counter is initialized at the start:
var int bullCount = na
Bullish Bar Detection
For each bar, if the close is above the selected moving average (either SMA or EMA, based on user input), the counter is incremented:
bullCount := close > signalMa ? (na(bullCount) ? 1 : bullCount + 1) : 0
Reset on Non-Bullish Condition
If the close does not exceed the moving average, the counter resets to zero, indicating a break in the consecutive bullish streak.
█ SIGNAL GENERATION
1. SHORT ENTRY
A short signal is generated when:
The number of consecutive bullish bars (i.e., bars closing above the short-term MA) meets or exceeds the defined threshold (default: 3).
The current bar’s close is higher than the previous bar’s high.
The signal occurs within the specified trading window (between Start Time and End Time).
Additionally, if the EMA filter is enabled, the entry is only executed when the current close is below the 200-period EMA.
2. EXIT CONDITION
An exit signal is triggered when the current close falls below the previous bar’s low, prompting the strategy to close the short position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish bars required to trigger a short entry (default is 3).
Trading Window: The Start Time and End Time inputs define when the strategy is active.
Moving Average Settings: Choose between SMA and EMA, and set the MA length (default is 5), which is used to assess each bar’s bullish condition.
EMA Filter (Optional): When enabled, this filter requires that the current close is below the 200-period EMA, supporting entries in a downtrend.
█ PERFORMANCE OVERVIEW
This strategy is designed for stocks and ETFs and can be applied across various timeframes.
It seeks to capture mean reversion by shorting after a series of bullish bars suggests an overextended move.
The approach employs a contrarian short entry by waiting for a breakout (close > previous high) following consecutive bullish bars.
The adjustable moving average settings and optional EMA filter allow for further optimization based on market conditions.
Comprehensive backtesting is recommended to fine-tune the threshold, moving average parameters, and filter settings for optimal performance.
[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.
[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- Low IBS (≤ 0.2) : Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8) : Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The IBS value rises to or above the Upper Threshold (default: 0.9).
The Closing price is greater than the previous bars High (close>high ).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
The strategy can be optimized further using additional conditions such as using volume or volatility filters.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
Range Filtered Trend Signals [AlgoAlpha]Introducing the Range Filtered Trend Signals , a cutting-edge trading indicator designed to detect market trends and ranging conditions with high accuracy. This indicator leverages a combination of Kalman filtering and Supertrend analysis to smooth out price fluctuations while maintaining responsiveness to trend shifts. By incorporating volatility-based range filtering, it ensures traders can differentiate between trending and ranging conditions effectively, reducing false signals and enhancing trade decision-making.
:key: Key Features
:white_check_mark: Kalman Filter Smoothing – Minimizes market noise while preserving trend clarity.
:bar_chart: Supertrend Integration – A dynamic trend-following mechanism for spotting reversals.
:fire: Volatility-Based Range Detection – Detects trending vs. ranging conditions with precision.
:art: Color-Coded Trend Signals – Instantly recognize bullish, bearish, and ranging market states.
:gear: Customizable Inputs – Fine-tune Kalman parameters, Supertrend settings, and color themes to match your strategy.
:bell: Alerts for Trend Shifts – Get real-time notifications when market conditions change!
:tools: How to Use
Add the Indicator – Click the star icon to add it to your TradingView favorites.
Analyze Market Conditions – Observe the color-coded signals and range boundaries to identify trend strength and direction.
Use Alerts for Trade Execution – Set alerts for trend shifts and market conditions to stay ahead without constantly monitoring charts.
:mag: How It Works
The Kalman filter smooths price fluctuations by dynamically adjusting its weighting based on market volatility. It helps remove noise while keeping the signal reactive to trend changes. The Supertrend calculation is then applied to the filtered price data, providing a robust trend-following mechanism. To enhance signal accuracy, a volatility-weighted range filter is incorporated, creating upper and lower boundaries that define trend conditions. When price breaks out of these boundaries, the indicator confirms trend continuation, while signals within the range indicate market consolidation. Traders can leverage this tool to enhance trade timing, filter false breakouts, and identify optimal entry/exit zones.
ZenAlgo - WavesZenAlgo - Waves is an advanced technical analysis indicator designed to refine trading decisions through a unique combination of multiple methodologies. By integrating Wave-like oscilator, RSI+MFI, and a dynamic Extra Moving Average (MA), it provides a structured approach to trend analysis and momentum detection. Unlike standalone indicators, this tool synchronizes multiple perspectives to provide holistic view and reduce noise.
Purpose and Justification for Integration
ZenAlgo - Waves strategically integrates multiple methodologies to provide trend validation. This indicator goes beyond standalone calculations by layering:
Original Wave Oscillator: Used to detect market momentum shifts and overbought/oversold conditions, further filtered by additional trend confirmation layers.
RSI + MFI Fusion: Introduces price-volume relationship validation, reducing misleading momentum reading.
Dynamic Extra Moving Average (MA): Acts as an adaptive trend filter, ensuring signals align with prevailing market direction rather than reacting to noise.
Divergence Detection: Contextualized divergence detection for both Wave and RSI+MFI.
Multi-Timeframe Trend Table: Facilitates confirmation across different timeframes, helping traders validate trade setups.
Attribution & Originality
ZenAlgo - Waves is an independently developed indicator that builds upon well-known technical analysis techniques while introducing significant enhancements. Unlike traditional WaveTrend indicator, it replaces the fixed constants of the original WaveTrend approach with a dynamic formula based on standard deviation , allowing for more adaptive and responsive calculations.
Additionally, this script integrates Ehlers' Super Smoother Filter , a highly regarded smoothing technique pioneered by John F. Ehlers and freely available for public use. Beyond these foundations, ZenAlgo - Waves incorporates proprietary logic and unique enhancements, setting it apart from conventional alternatives.
If you're seeking an exact replication of WaveTrend, please note that this indicator follows a distinct methodology, producing different calculations and outputs.
How to Use
Identify Key Zones: Observe Wave oscillator values to detect potential overbought and oversold conditions, which may vary based on settings.
Check RSI+MFI Histogram: Confirm momentum strength—bullish (increasing green bars) or bearish (increasing red bars).
Assess Trend via Extra MA: Use the Extra Moving Average to determine overall trend direction.
Look for Divergences: Identify divergences between price action and Wave/RSI+MFI for potential reversals.
Monitor Multi-Timeframe Trend Table: Check for alignment across timeframes for additional confirmation.
Set Alerts for Key Conditions: Configure alerts for Wave crossovers, divergences, and Extra MA state changes.
Analyze Conditions Before Making Decisions: The indicator does not execute trades. Traders should use it as a confirmation tool alongside a broader strategy.
Detailed Explanation of Calculation Logic
ZenAlgo - Waves builds on established wave-based oscillator principles, fine-tuning them for greater adaptability:
Baseline & Difference: Computes a smoothed average of the price source (e.g., HLC3) and measures the difference (or "deviation") between the current price and this baseline.
Volatility Scaling: Uses standard deviation to capture market volatility instead of relying on a static multiplier.
Normalization & Smoothing: Processes the resulting ratio into an oscillator, helping identify overbought and oversold zones. Optionally applies a secondary smoothing pass (including Ehlers' Super Smoother - SMMA) to reduce noise while preserving trend structure.
RSI + MFI Integration: Fuses RSI and MFI into a single composite metric, weighting RSI momentum with volume-adjusted MFI values for a clearer representation of momentum strength.
Extra Moving Average Filtering: A variety of moving average types (EMA, Hull, ZEMA, etc.) smooth the underlying trend, with sensitivity to trend changes customizable.
Divergence Detection: Identifies both regular and hidden divergences by comparing oscillator movements against price action, adjusting dynamically based on historical volatility.
Multi-Timeframe Trend Confirmation: Aggregates data across multiple timeframes (e.g., 1m, 5m, 15m, 1h) to provide a broader market context.
Alerts and Key Conditions: Alerts can be configured for specific conditions such as Wave crossovers, RSI+MFI confirmation, or Extra MA transitions. These alerts serve as notifications, not as automatic trading signals.
Why It’s Worth Paying For
ZenAlgo - Waves differentiates itself from free indicators by providing:
Contextual Signal Filtering: Integrates price-volume analysis and trend alignment checks.
Adaptive Trend Classification: Dynamically adjusts to market conditions.
Multi-Layer Confirmation: Requires momentum, volume, and trend agreement before providing insights.
Advanced Divergence Detection: Filters out noise-based divergences, highlighting only significant price-action-driven reversals.
Multi-Timeframe Validation: Helps ensure that observed trends are consistent across different timeframes.
Considerations for Use:
During periods of low trading volume, as price action lacks conviction.
In highly volatile market conditions, rapid price swings can introduce uncertainty.
Fundamental news events can override technical patterns.
If trends contradict across multiple timeframes, additional confirmation is recommended before making decisions.
Important Notes
This indicator is a tool for technical analysis and does not guarantee trading success.
Best Practices: Use ZenAlgo - Waves in conjunction with other indicators and fundamental analysis for a well-rounded approach.
Price Step Channel [BigBeluga]Price Step Channel is designed to provide a structured look at price trends through a dynamic step line channel, highlighting trend direction and volatility boundaries.
🔵 Key Features:
Step Line with Boundaries: The central step line adjusts with price movements, creating upper and lower boundaries based on price volatility. The channel is green during uptrends and red during downtrends, visually signaling the trend’s direction.
Fakeout Markers: "✖" markers identify potential fakeouts—moments when the price breaches the channel boundary without confirming a trend change. These markers help you spot possible mean reversion points.
Dynamic Boundary Labels: Labels at the end of the channel show the price levels of the upper and lower boundaries. In uptrends, the upper label turns green; in downtrends, the lower label turns red, providing an instant read on the trend's direction.
Customizable Display: You can toggle off the boundaries and labels for a cleaner view, focusing only on the step line and its color-coded trend signals.
🔵 When to Use:
Price Step Channel is ideal for traders looking to follow structured trends with defined volatility boundaries. The step line and color-coded channel provide clear trend insights, while the fakeout markers and customizable display options enhance flexibility in different market conditions. Whether you’re focusing on clean trend signals or detailed boundary interactions, this tool adapts to your style.
[COG] Adaptive Squeeze Intensity 📊 Adaptive Squeeze Intensity (ASI) Indicator
🎯 Overview
The Adaptive Squeeze Intensity (ASI) indicator is an advanced technical analysis tool that combines the power of volatility compression analysis with momentum, volume, and trend confirmation to identify high-probability trading opportunities. It quantifies the degree of price compression using a sophisticated scoring system and provides clear entry signals for both long and short positions.
⭐ Key Features
- 📈 Comprehensive squeeze intensity scoring system (0-100)
- 📏 Multiple Keltner Channel compression zones
- 📊 Volume analysis integration
- 🎯 EMA-based trend confirmation
- 🎨 Proximity-based entry validation
- 📱 Visual status monitoring
- 🎨 Customizable color schemes
- ⚡ Clear entry signals with directional indicators
🔧 Components
1. 📐 Squeeze Intensity Score (0-100)
The indicator calculates a total squeeze intensity score based on four components:
- 📊 Band Convergence (0-40 points): Measures the relationship between Bollinger Bands and Keltner Channels
- 📍 Price Position (0-20 points): Evaluates price location relative to the base channels
- 📈 Volume Intensity (0-20 points): Analyzes volume patterns and thresholds
- ⚡ Momentum (0-20 points): Assesses price momentum and direction
2. 🎨 Compression Zones
Visual representation of squeeze intensity levels:
- 🔴 Extreme Squeeze (80-100): Red zone
- 🟠 Strong Squeeze (60-80): Orange zone
- 🟡 Moderate Squeeze (40-60): Yellow zone
- 🟢 Light Squeeze (20-40): Green zone
- ⚪ No Squeeze (0-20): Base zone
3. 🎯 Entry Signals
The indicator generates entry signals based on:
- ✨ Squeeze release confirmation
- ➡️ Momentum direction
- 📊 Candlestick pattern confirmation
- 📈 Optional EMA trend alignment
- 🎯 Customizable EMA proximity validation
⚙️ Settings
🔧 Main Settings
- Base Length: Determines the calculation period for main indicators
- BB Multiplier: Sets the Bollinger Bands deviation multiplier
- Keltner Channel Multipliers: Three separate multipliers for different compression zones
📈 Trend Confirmation
- Four customizable EMA periods (default: 21, 34, 55, 89)
- Optional trend requirement for entry signals
- Adjustable EMA proximity threshold
📊 Volume Analysis
- Customizable volume MA length
- Adjustable volume threshold for signal confirmation
- Option to enable/disable volume analysis
🎨 Visualization
- Customizable bullish/bearish colors
- Optional intensity zones display
- Status monitor with real-time score and state information
- Clear entry arrows and background highlights
💻 Technical Code Breakdown
1. Core Calculations
// Base calculations for EMAs
ema_1 = ta.ema(close, ema_length_1)
ema_2 = ta.ema(close, ema_length_2)
ema_3 = ta.ema(close, ema_length_3)
ema_4 = ta.ema(close, ema_length_4)
// Proximity calculation for entry validation
ema_prox_raw = math.abs(close - ema_1) / ema_1 * 100
is_close_to_ema_long = close > ema_1 and ema_prox_raw <= prox_percent
```
### 2. Squeeze Detection System
```pine
// Bollinger Bands setup
BB_basis = ta.sma(close, length)
BB_dev = ta.stdev(close, length)
BB_upper = BB_basis + BB_mult * BB_dev
BB_lower = BB_basis - BB_mult * BB_dev
// Keltner Channels setup
KC_basis = ta.sma(close, length)
KC_range = ta.sma(ta.tr, length)
KC_upper_high = KC_basis + KC_range * KC_mult_high
KC_lower_high = KC_basis - KC_range * KC_mult_high
```
### 3. Scoring System Implementation
```pine
// Band Convergence Score
band_ratio = BB_width / KC_width
convergence_score = math.max(0, 40 * (1 - band_ratio))
// Price Position Score
price_range = math.abs(close - KC_basis) / (KC_upper_low - KC_lower_low)
position_score = 20 * (1 - price_range)
// Final Score Calculation
squeeze_score = convergence_score + position_score + vol_score + mom_score
```
### 4. Signal Generation
```pine
// Entry Signal Logic
long_signal = squeeze_release and
is_momentum_positive and
(not use_ema_trend or (bullish_trend and is_close_to_ema_long)) and
is_bullish_candle
short_signal = squeeze_release and
is_momentum_negative and
(not use_ema_trend or (bearish_trend and is_close_to_ema_short)) and
is_bearish_candle
```
📈 Trading Signals
🚀 Long Entry Conditions
- Squeeze release detected
- Positive momentum
- Bullish candlestick
- Price above relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
🔻 Short Entry Conditions
- Squeeze release detected
- Negative momentum
- Bearish candlestick
- Price below relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
⚠️ Alert Conditions
- 🔔 Extreme squeeze level reached (score crosses above 80)
- 🚀 Long squeeze release signal
- 🔻 Short squeeze release signal
💡 Tips for Usage
1. 📱 Use the status monitor to track real-time squeeze intensity and state
2. 🎨 Pay attention to the color gradient for trend direction and strength
3. ⏰ Consider using multiple timeframes for confirmation
4. ⚙️ Adjust EMA and proximity settings based on your trading style
5. 📊 Use volume analysis for additional confirmation in liquid markets
📝 Notes
- 🔧 The indicator combines multiple technical analysis concepts for robust signal generation
- 📈 Suitable for all tradable markets and timeframes
- ⭐ Best results typically achieved in trending markets with clear volatility cycles
- 🎯 Consider using in conjunction with other technical analysis tools for confirmation
⚠️ Disclaimer
This technical indicator is designed to assist in analysis but should not be considered as financial advice. Always perform your own analysis and risk management when trading.
Adaptive Resonance Oscillator [AlgoAlpha]Introducing the Adaptive Resonance Oscillator , an advanced momentum-based oscillator designed to dynamically adjust to changing market conditions. This innovative indicator detects market frequency through a Hilbert Transform approach, adapting in real-time to identify overbought and oversold conditions with improved accuracy. With built-in divergence detection, trend analysis, and customizable smoothing, this tool is perfect for traders looking to refine their entries and exits based on adaptive oscillation mechanics.
🚀 Key Features :
🔹 Adaptive Frequency Detection – Uses Hilbert Transform principles to dynamically determine market cycle length for precise oscillator calculation.
⚙️ Customizable Smoothing – Option to apply a Hull Moving Average (HMA) for enhanced signal clarity.
📈 Divergence Detection – Identifies bullish and bearish divergences with visual markers, helping traders spot early trend reversals.
🟢 Overbought & Oversold Signals – Highlights extreme momentum conditions with adjustable thresholds.
🔔 Real-Time Alerts – Get notified for crossovers, divergences, and strong trend shifts directly on your TradingView chart.
🎨 Fully Customizable Appearance – Modify colors, divergence sensitivity, and smoothing options to fit your trading style.
🛠 How to Use :
Add the Adaptive Resonance Oscillator to your TradingView chart by clicking the ★ to favorite it.
Monitor the Charts , switch between smoothed and I smoothed modes to identify trend and price swings, use divergences and reversal signals for potential entry/exits.
Set alerts for bullish/bearish crossovers and divergence signals to stay ahead of market moves.
⚙ How It Works :
The indicator begins by applying a Hilbert Transform frequency estimation to the price series, identifying the dominant market cycle length. This is used to calculate a period for the RSI that matches its resonant frequency with the dominant market frequency, dynamically adjusting the Oscillator. The oscillator then applies an optional Hull Moving Average (HMA) smoothing for signal refinement. Additionally, the indicator scans for bullish and bearish divergences by comparing oscillator movements against price action, plotting signals accordingly. When overbought/oversold conditions or divergence events occur, alerts are triggered to notify the trader in real time.
Dynamic Weighted Price Flow [QuantAlgo]Experience a brand new way of analyzing price movement with Dynamic Weighted Price Flow , an advanced technical tool that utilizes the uniqueness of weighted price and dynamic momentum analysis to evaluate trends and deliver high-probability signals. Whether you're a long-term investor seeking major trend confirmation or an active trader looking for precise entries and exits, this indicator's sophisticated and innovative approach to price flow analysis offers invaluable market insights you can only find at QuantAlgo !
🟢 Core Architecture
The Dynamic Weighted Price Flow's foundation rests on its innovative weighted price calculation and momentum-based trend scoring system. By implementing a unique price weighting algorithm alongside Hull Moving Average smoothing, each market move is evaluated within a dynamic context while maintaining exceptional responsiveness to price action. This refined approach helps identify genuine trend transitions while filtering out market noise across multiple timeframes and instruments.
🟢 Technical Foundation
Three key components of this indicator are:
Weighted Price Analysis: Utilizes a sophisticated weighting system that prioritizes recent price action
Momentum Range Processing: A comprehensive scoring system that evaluates price momentum across multiple periods
Dynamic Trend State Management: A normalized system that tracks and validates trend transitions
🟢 Practical Usage Tips
Here's how to maximize your use of the Dynamic Weighted Price Flow :
1/ Setup:
Add the indicator to your favorites ⭐️
Start with the default baseline period for balanced analysis
Use the recommended momentum range for optimal signal generation
Keep signal markers enabled for clear trend transitions
Customize accent colors to match your preferences
Enable dynamic price bars for complete visual feedback
2/ Reading Signals:
Monitor for triangle markers indicating trend transitions
Watch the main trend line color for direction confirmation
Observe the gradient fills for trend strength visualization
Use the built-in alert system to catch potential setups
🟢 Pro Tips
Adjust Baseline Period based on your trading style:
→ Lower values (1-5) for more responsive signals
→ Higher values (5-10) for more stable trend identification
Fine-tune Momentum Range based on market conditions:
→ Lower values (20-35) for shorter-term signals
→ Higher values (35-50) for longer-term trend following
Optimize Visual Settings for your strategy:
→ Enable signal markers for clear entry/exit points
→ Use dynamic price bars for enhanced trend visualization
Combine with:
→ Volume indicators for trade confirmation
→ Support/resistance levels for entry refinement
→ Multiple timeframe analysis for strategic context
ZenAlgo - Aggregated DeltaZenAlgo - Aggregated Delta is an advanced market analysis tool designed to provide traders with a holistic view of market sentiment by leveraging multi-exchange volume aggregation, cumulative delta analysis, and divergence detection. Unlike traditional indicators that rely on a single data source, this tool aggregates order flow data from multiple exchanges, reducing the impact of exchange-specific anomalies and liquidity disparities.
This indicator is ideal for traders looking to enhance their understanding of market dynamics, trend confirmations, and order flow patterns. By intelligently combining multiple analytical components, it eliminates the need for manually interpreting separate indicators and offers traders a streamlined approach to market analysis.
This indicator was inspired by aggregated volume analysis techniques. Independently developed with a focus on cumulative delta and divergence detection.
Key Features & Their Interaction
Multi-Exchange Volume Aggregation: Aggregates buy and sell volumes from up to nine major exchanges, including Binance, Bybit, Coinbase, and Kraken. Unlike traditional single-source indicators, this ensures a robust, diversified measure of market sentiment and smooths out exchange-specific volume fluctuations.
Cumulative Delta Analysis: Tracks the net difference between buy and sell volumes across all aggregated exchanges, helping traders identify true buying/selling pressure rather than misleading short-term volume spikes.
Advanced Divergence Detection: Unlike basic divergence indicators, this tool detects divergences not only between price and cumulative delta but also across multiple analytical layers, including moving averages and temperature zones, offering deeper confirmation signals.
Dynamic Market Temperature Zones: Unlike fixed overbought/oversold indicators, this feature applies adaptive standard deviation-based filtering to classify market conditions dynamically as "Extreme Hot," "Hot," "Neutral," "Cold," and "Extreme Cold."
Intelligent Market State Classification: Determines whether the market is in a Full Bull, Bearish, or Neutral state by analyzing multi-exchange volume flow, cumulative delta positioning, and market-wide liquidity trends.
Real-Time Alerts & Adaptive Visualization: Provides fully configurable real-time alerts for trend shifts, divergences, and market conditions, allowing traders to act immediately on high-confidence signals.
What Makes ZenAlgo - Aggregated Delta Unique?
Unlike free or open-source alternatives, ZenAlgo - Aggregated Delta applies a multi-layered data processing approach to smooth inconsistencies and improve signal reliability. Instead of using raw exchange feeds, the system incorporates adaptive volume aggregation and standard deviation-based market classification to ensure accuracy and reduce noise. These enhancements lead to more precise trend signals and a clearer representation of market sentiment.
Multi-Exchange Order Flow Validation: Unlike single-source indicators that rely on individual exchange feeds, this tool ensures cross-market consistency by aggregating volume data dynamically.
Fractal-Based Divergence Detection: Detects divergences using fractal logic rather than contextual volume trends, reducing false-positive divergence signals while maintaining accuracy.
Automated Sentiment Analysis: Classifies market sentiment into structured phases (Full Bull, Bearish, etc.), reducing the manual effort needed to interpret order flow trends.
How It Works (Technical Breakdown)
Multi-Exchange Volume Aggregation: The system fetches and validates buy/sell volume data from multiple exchanges, applying volume aggregation techniques to smooth out inconsistencies. It ensures that data from low-liquidity exchanges does not disproportionately influence the analysis.
Cumulative Delta Computation: Cumulative delta is computed as the net difference between buy and sell volumes over a given period. By summing up these values across multiple exchanges, traders can identify real accumulation or distribution zones, reducing false signals from isolated exchange anomalies.
Divergence Detection Methodology: The tool uses a fractal-based logic approach to detect high-confidence divergences across price, volume, and delta trends. This allows for a more structured detection process compared to simple peak/trough analysis, reducing noise in the signals.
Temperature Zones Filtering: Market conditions are dynamically classified using a rolling standard deviation model, ensuring that hot/cold states adjust automatically based on recent volatility levels. This means that instead of using arbitrary fixed thresholds, the tool adapts based on historical data behavior.
Market Sentiment State Calculation: The tool evaluates liquidity conditions, volume trends, and cumulative delta flow, categorizing the market into predefined states (Bullish, Bearish, Neutral). This helps traders assess the broader context of price movements rather than reacting to isolated signals.
Real-Time Adaptive Alerts: The system provides fully configurable alerts that notify traders about key trend shifts, high-confidence divergences, and changes in market conditions as they occur. This ensures that traders can make timely and well-informed decisions.
Why This Approach Works
By aggregating data from multiple exchanges, it reduces the impact of exchange-specific liquidity disparities and anomalies, leading to a more holistic view of order flow.
The cumulative delta analysis ensures that price movements are validated by actual buying/selling pressure, filtering out misleading short-term spikes.
Dynamic market classification adapts to current conditions rather than using outdated fixed thresholds, making it more relevant in different market regimes.
Fractal-based divergence detection avoids common pitfalls of traditional divergence analysis, reducing false signals while maintaining accuracy.
Combining real-time adaptive alerts with well-structured classification improves traders’ ability to respond to market shifts efficiently.
Practical Use Cases
Identifying High-Probability Trend Reversals: If cumulative delta shows bullish divergence while the market is in an Extreme Cold zone, it signals a strong potential for reversal.
Confirming Trend Continuation: When bullish moving average crossovers align with a rising cumulative delta, traders can enter positions with higher confidence.
Detecting Exhaustion in Market Moves: If price enters an "Extreme Hot" zone but cumulative delta starts declining, this suggests trend exhaustion and a possible reversal.
Filtering False Breakouts: If price breaks a resistance level but aggregated buy volume fails to increase, this invalidates the breakout, helping traders avoid bad trades.
Cross-Exchange Sentiment Confirmation: If cumulative delta on aggregated exchanges contradicts price action on an individual exchange, traders can identify localized exchange-based distortions.
Customization & Settings Overview
Exchange Selection: Traders can fine-tune exchange sources for aggregation, allowing for custom market-specific insights.
Adaptive Divergence Settings: Configure detection thresholds, lookback periods, and divergence filtering options to reduce noise and focus on high-confidence signals.
Moving Average Adjustments: Select custom MA types, lengths, and visualization preferences to match different trading styles.
Market Temperature Thresholds: Adjust hot/cold sensitivity to align with preferred risk levels and volatility expectations.
Configurable Alerts & Theme Customization: Full control over notification triggers, color themes, and label formatting to enhance user experience.
Important Considerations
Market Context Dependency: This tool provides order flow analysis, which should be used in conjunction with broader market context and risk management.
Data Source Variability: While multi-exchange aggregation improves reliability, some exchanges may report inaccurate or delayed data.
Extreme Volatility Handling: Large price swings can temporarily distort delta readings, so traders should always validate with additional context.
Liquidity Limitations: In low-liquidity conditions, order flow signals may be less reliable due to fragmented market participation.
[COG] WeatherForecaster🌤️ Just like a weather forecast that adjusts as new data emerges, this TMA Pivot Points Forecaster adapts to evolving market conditions!
Description:
This indicator combines the power of a Triple Moving Average (TMA) with pivot point analysis to identify potential market turning points and trend directions. Like a meteorologist using various atmospheric data to predict weather patterns, this tool analyzes price action through multiple lenses to forecast potential market movements.
Key Features:
- Dynamic TMA Line: Acts as our "atmospheric pressure system," showing the underlying market direction
- Adaptive Pivot Points: Like weather stations, these pivots identify key market levels where the "climate" might change
- Smart Entry Signals: ☀️ and 🌧️ icons appear when conditions align for potential trades
- Timeframe-Adaptive: Automatically adjusts sensitivity across different timeframes
- Customizable Visuals: Adjust colors and styles to match your trading environment
Settings Include:
✓ TMA Length and Slope Sensitivity
✓ Pivot Point Parameters
✓ Visual Customization Options
✓ Toggle Entry Signals
✓ Toggle Pivot Lines
Note: Like weather forecasts that update with new data, this indicator recalculates as market conditions evolve. Past signals may adjust as more price action develops. Always use proper risk management and combine with other analysis tools.
Usage Guide:
The indicator works best when used as part of a complete trading system. Here's how to interpret the signals:
📈 Bullish Conditions:
- TMA Line turns green: Indicates upward momentum
- "Buy above 🌋" level appears: Potential resistance turned support level
- ☀️ Signal: Indicates favorable buying conditions
📉 Bearish Conditions:
- TMA Line turns red: Indicates downward momentum
- "Sell below 🌋" level appears: Potential support turned resistance level
- 🌧️ Signal: Indicates favorable selling conditions
⏺️ Ranging Conditions:
- TMA Line turns yellow: Market in consolidation
- 💤 Signal: Suggests waiting for clearer direction
Best Practices:
1. Higher timeframes (4H, Daily) tend to produce more reliable signals
2. Use the pivot lines as potential entry/exit reference points
3. Adjust the TMA length based on your trading style:
• Shorter lengths (20-30) for more active trading
• Longer lengths (50-60) for trend following
Settings Explained:
TMA Settings:
- TMA Length: Determines the smoothing period (default: 30)
- Slope Threshold: Controls trend sensitivity (default: 0.015)
Pivot Settings:
- Left/Right Bars: Controls pivot point calculation
- Line Length: Adjusts the visual length of pivot lines
- Line Style & Colors: Customize the visual appearance
Disclaimer:
Past performance does not guarantee future results. This indicator, like any technical tool, provides possibilities rather than certainties. Please test thoroughly on your preferred timeframes and markets before using with real capital.
Drawdown Visualisation█ OVERVIEW
The Drawdown Visualisation indicator calculates and displays the instrument’s drawdown (in percent) relative to its all‐time high (ATH) from a user‐defined start date. It provides customisable options for label appearance, threshold lines (0%, –50%, –100%), and can plot historic drawdown levels via pivot detection.
█ USAGE
This indicator should be used with the Percentage Retracement from ATH indicator.
█ KEY FEATURES
Custom Date Settings — Use a custom start date so that only specified price action is considered.
Retracement Level Calculation — Determines ATH and computes multiple retracement levels using percentages from 0% to –100%.
Visual Signals and Customisation — Plots configurable horizontal lines and labels that display retracement percentages and prices.
Time Filtering — Bases calculations on data from the desired time period.
Historic Drawdowns — Display historical drawdowns
█ PURPOSE
Assist traders in visualising the depth of price retracements from recent or historical peaks.
Identify critical zones where the market may find support or resistance after reaching an ATH.
Facilitate more informed entry and exit decisions by clearly demarcating retracement levels on the chart.
█ IDEAL USERS
Swing Traders — Looking to exploit pullbacks following strong upward moves.
Technical Analysts — Interested in pinpointing key retracement levels as potential reversal or continuation points.
Price Action Traders — Focused on the nuances of market peaks and subsequent corrections.
Strategy Developers — Keen to backtest and refine approaches centred on retracement dynamics.
Percentage Retracement from ATH█ OVERVIEW
The Percentage Retracement from ATH indicator is a dynamic trading utility designed to help traders gauge market pullbacks from the peak price. By calculating key retracement levels based on the All-Time High (ATH) and user‑defined percentage inputs, it offers clear visual cues to assist in identifying potential support and resistance zones.
█ KEY FEATURES
Custom Date — Use a custom start date so the indicator only considers specified price action.
Retracement Calculation — Determines ATH and calculates levels based on user‑defined percentages (0% to –100%).
Visual Customisation — Plots configurable horizontal lines and labels showing retracement percentages and prices.
Time Filtering — Uses time filtering to base levels on the desired data period.
█ PURPOSE
Assist traders in visualising the depth of price retracements from recent or historical peaks.
Identify critical zones where the market may find support or resistance after reaching an ATH.
Facilitate more informed entry and exit decisions by clearly demarcating retracement levels on the chart.
█ IDEAL USERS
Swing Traders — Looking to exploit pullbacks following strong upward moves.
Technical Analysts — Interested in pinpointing key retracement levels as potential reversal or continuation points.
Price Action Traders — Focused on the nuances of market peaks and subsequent corrections.
Strategy Developers — Keen to backtest and refine approaches centred on retracement dynamics.
Triple Trend Indicator [BigBeluga]Triple Trend Indicator is a versatile trend-following tool designed to help traders identify trend strength and potential pullback levels using a three-band system. Each band represents a varying degree of price deviation from the mean, providing progressively stronger trend signals.
🔵 Key Features:
Three Adaptive Bands:
The indicator dynamically calculates three bands (1, 2, and 3) based on moving averages (SMA, EMA, WMA) and ATR multipliers.
Bands are positioned below the price in an uptrend and above the price in a downtrend, offering clear trend direction visualization.
Signal System:
Signals are generated when price interacts with the bands:
Signal 1: Triggered when the price touches Band 1, indicating a minor pullback within the trend.
Signal 2: Triggered at Band 2, showing a stronger price deviation and trend confirmation.
Signal 3: Triggered at Band 3, representing the most significant price deviation and strongest trend signal.
The further the price deviates from the mean, the stronger the trend signal, with Signal 3 being the most robust.
Color-Coded Bands:
Bands dynamically change color based on the trend direction:
Green bands signify an uptrend.
Brown bands signify a downtrend.
Dynamic Trend Line Changes:
Dashed lines highlight trend changes, helping traders visualize key turning points in the market.
🔵 Usage:
Use the bands to identify trend direction and strength.
Monitor the signal system to assess the level of price deviation and potential pullback strength.
Combine Signal 1, 2, and 3 to confirm trend momentum:
Signal 1 suggests a weaker pullback and continuation.
Signal 2 indicates a stronger trend confirmation.
Signal 3 highlights the strongest momentum and potential exhaustion points.
Utilize the color-coded bands for an intuitive understanding of current market conditions.
The Triple Trend Indicator is an ideal tool for trend traders looking for structured signals and dynamic support and resistance levels to optimize entries and exits.
VWAP Bands with ML [CryptoSea]VWAP Machine Learning Bands is an advanced indicator designed to enhance trading analysis by integrating VWAP with a machine learning-inspired adaptive smoothing approach. This tool helps traders identify trend-based support and resistance zones, predict potential price movements, and generate dynamic trade signals.
Key Features
Adaptive ML VWAP Calculation: Uses a dynamically adjusted SMA-based VWAP model with volatility sensitivity for improved trend analysis.
Forecasting Mechanism: The 'Forecast' parameter shifts the ML output forward, providing predictive insights into potential price movements.
Volatility-Based Band Adjustments: The 'Sigma' parameter fine-tunes the impact of volatility on ML smoothing, adapting to market conditions.
Multi-Tier Standard Deviation Bands: Includes two levels of bands to define potential breakout or mean-reversion zones.
Dynamic Trend-Based Colouring: The VWAP and ML lines change colour based on their relative positions, visually indicating bullish and bearish conditions.
Custom Signal Detection Modes: Allows traders to choose between signals from Band 1, Band 2, or both, for more tailored trade setups.
In the image below, you can see an example of the bands on higher timeframe showing good mean reversion signal opportunities, these tend to work better in ranging markets rather than strong trending ones.
How It Works
VWAP & ML Integration: The script computes VWAP and applies a machine learning-inspired adjustment using SMA smoothing and volatility-based adaptation.
Forecasting Impact: The 'Forecast' setting shifts the ML output forward in time, allowing for anticipatory trend analysis.
Volatility Scaling (Sigma): Adjusts the ML smoothing sensitivity based on market volatility, providing more responsive or stable trend lines.
Trend Confirmation via Colouring: The VWAP line dynamically switches colour depending on whether it is above or below the ML output.
Multi-Level Band Analysis: Two standard deviation-based bands provide a framework for identifying breakouts, trend reversals, or continuation patterns.
In the example below, we can see some of the most reliable signals where we have mean reversion signals from the band whilst the price is also pulling back into the VWAP, these signals have the additional confluence which can give you a higher probabilty move.
Alerts
Bullish Signal Band 1: Alerts when the price crosses above the lower ML Band 1.
Bearish Signal Band 1: Alerts when the price crosses below the upper ML Band 1.
Bullish Signal Band 2: Alerts when the price crosses above the lower ML Band 2.
Bearish Signal Band 2: Alerts when the price crosses below the upper ML Band 2.
Filtered Bullish Signal: Alerts when a bullish signal is triggered based on the selected signal detection mode.
Filtered Bearish Signal: Alerts when a bearish signal is triggered based on the selected signal detection mode.
Application
Trend & Momentum Analysis: Helps traders identify key market trends and potential momentum shifts.
Dynamic Support & Resistance: Standard deviation bands serve as adaptive price zones for potential breakouts or reversals.
Enhanced Trade Signal Confirmation: The integration of ML smoothing with VWAP provides clearer entry and exit signals.
Customizable Risk Management: Allows users to adjust parameters for fine-tuned signal detection, aligning with their trading strategy.
The VWAP Machine Learning Bands indicator offers traders an innovative tool to improve market entries, recognize potential reversals, and enhance trend analysis with intelligent data-driven signals.
SD Trend with SignalsSD Trend Indicator
The SD Trend Indicator is a trend-following tool designed to help traders identify potential buy and sell signals based on a combination of technical indicators: MACD, RSI, and Stochastic Oscillator. It visually enhances price action by color-coding candles and plotting signals when a trend shift occurs.
How It Works:
MACD (12, 26, 9): Measures momentum and trend direction.
RSI (7): Identifies overbought and oversold conditions.
Stochastic Oscillator (14, 3, 3): Confirms trend strength and reversals.
Candle Color Coding:
Green → Bullish (Buy Condition)
Red → Bearish (Sell Condition)
Black → Neutral (No Trade)
Signal Generation:
A Buy Signal (B) is plotted below the first green candle after a neutral (black) phase.
A Sell Signal (S) is plotted above the first red candle after a neutral (black) phase.
This helps traders capture early trend reversals with clear visual confirmation.
Key Features:
✔️ Trend Confirmation using three proven indicators.
✔️ Clear Candle Coloring for easy trend visualization.
✔️ Buy/Sell Labels (B/S) for quick decision-making.
✔️ Works on any timeframe and asset class (stocks, forex, crypto, etc.).
This indicator is ideal for traders looking to follow trends, identify potential reversals, and improve entry/exit timing with a systematic approach
Two-Pole Oscillator [BigBeluga]
The Two-Pole Oscillator is an advanced smoothing oscillator designed to provide traders with precise market signals by leveraging deviation-based calculations combined with a unique two-pole filtering technique. It offers clear visual representation and actionable signals for smart trading decisions.
🔵Key Features:
Two-Pole Filtering: Smooths out the main oscillator signal to reduce noise, providing a cleaner and more reliable view of market momentum and trend strength.
// Two-pole smooth filter function
f_two_pole_filter(source, length) =>
var float smooth1 = na
var float smooth2 = na
alpha = 2.0 / (length + 1)
if na(smooth1)
smooth1 := source
else
smooth1 := (1 - alpha) * smooth1 + alpha * source
if na(smooth2)
smooth2 := smooth1
else
smooth2 := (1 - alpha) * smooth2 + alpha * smooth1
Deviation-Based Oscillator: Utilizes price deviations from the mean to generate dynamic signals, making it ideal for detecting overbought and oversold conditions.
float sma1 = ta.sma(close, 25)
float sma_n1 = ((close - sma1) - ta.sma(close - sma1, 25)) / ta.stdev(close - sma1, 25)
Signal Gradient Strength: Signals on the main oscillator line feature gradient coloring based on their proximity to the 0 level:
➔ Closer to 0: More transparent, indicating weaker signals.
➔ Closer to 1 or -1: Less transparent, highlighting stronger signals.
Level-Based Signal Validation: Parallel levels are plotted on the chart for each signal:
➔ If a level is crossed by price, the signal is invalidated, marked by an "X" at the invalidation point.
Trend Continuation
Invalidation Levels: Serve as potential stop-loss or trade-reversal zones, enabling traders to make more informed and disciplined trading decisions.
Dynamic Chart Plotting: Signals are plotted directly on the chart with corresponding levels, providing a comprehensive visual representation for easy interpretation.
🔵How It Works:
The oscillator calculates price deviation from a mean value and applies two-pole filtering to smooth the resulting signal.
Gradient-colored signals reflect their strength, with transparency indicating proximity to the 0 level on the oscillator scale.
Buy and sell signals are generated based on crossovers and crossunders of the oscillator line with a signal line.
If a level is crossed, the corresponding signal is marked with a "X" plotted on the chart at the crossover point.
🔵Use Cases:
Detecting overbought or oversold market conditions with a smoother, noise-free oscillator.
Using invalidation levels to set clear stop-loss or trade exit points.
Identifying strong momentum signals and filtering out weaker, less reliable ones.
Combining oscillator signals with price action for more precise trade entries and exits.
This indicator is perfect for traders seeking a refined approach to oscillator analysis, combining signal strength visualization with actionable invalidation levels to enhance trading precision and strategy.
Monthly DividerThis Trading View indicator visually marks the beginning of each month starting from January 2024. It draws vertical lines on the chart at the start of each month and labels them with the corresponding month abbreviation (e.g., "Jan", "Feb"). Users can customize the color and thickness of the lines through the indicator settings, allowing for personalized chart aesthetics. This tool is ideal for traders and analysts who want to easily identify month transitions and enhance their technical analysis.
