Forex Fire EMA/MA/RSI StrategyEURUSD
The entry method in the Forex Fire EMA/MA/RSI Strategy combines several conditions across two timeframes. Here's a breakdown of how entries are determined:
Long Entry Conditions:
15-Minute Timeframe Conditions:
EMA 13 > EMA 62 (short-term momentum is bullish)
Price > MA 200 (trading above the major trend indicator)
Fast RSI (7) > Slow RSI (28) (momentum is increasing)
Fast RSI > 50 (showing bullish momentum)
Volume is increasing compared to 20-period average
4-Hour Timeframe Confluence:
EMA 13 > EMA 62 (larger timeframe confirms bullish trend)
Price > MA 200 (confirming overall uptrend)
Slow RSI (28) > 40 (showing bullish bias)
Fast RSI > Slow RSI (momentum is supporting the move)
Additional Precision Requirement:
Either EMA 13 has just crossed above EMA 62 (crossover)
OR price has just crossed above MA 200
Short Entry Conditions:
15-Minute Timeframe Conditions:
EMA 13 < EMA 62 (short-term momentum is bearish)
Price < MA 200 (trading below the major trend indicator)
Fast RSI (7) < Slow RSI (28) (momentum is decreasing)
Fast RSI < 50 (showing bearish momentum)
Volume is increasing compared to 20-period average
4-Hour Timeframe Confluence:
EMA 13 < EMA 62 (larger timeframe confirms bearish trend)
Price < MA 200 (confirming overall downtrend)
Slow RSI (28) < 60 (showing bearish bias)
Fast RSI < Slow RSI (momentum is supporting the move)
Additional Precision Requirement:
Either EMA 13 has just crossed under EMA 62 (crossunder)
OR price has just crossed under MA 200
The key aspect of this strategy is that it requires alignment between the shorter timeframe (15m) and the larger timeframe (4h), which helps filter out false signals and focuses on trades that have strong multi-timeframe support. The crossover/crossunder requirement further refines entries by looking for actual changes in direction rather than just conditions that might have been in place for a long time.
Komut dosyalarını "市值60亿的股票" için ara
HALO Oracle - CoffeeKillerHALO Oracle - CoffeeKiller Indicator Guide
Hello traders! Today I'm going to walk you through how to use the HALO Oracle indicator, which is a powerful tool for identifying market trends and potential reversal points.
Basic Overview
The HALO Oracle is a trend-following indicator that combines Heiken Ashi candles with golden ratio calculations to help you identify market direction and key price levels.
Main Features
1. Time Settings
- You have two modes for time analysis:
- Normal Mode: The indicator analyzes each individual candle on your chart
- Custom Resolution Mode: You can use a different timeframe for calculations than what's shown on your chart
* For example, you could view a 5-minute chart but have the indicator calculate based on 1-hour data
* Available timeframes include Monthly (M), Weekly (W), Daily (D), 4 Hours (240), 1 Hour (60), etc.
2. Visual Components
Bands and Fill
- Two main bands: green and red
- The space between these bands is filled with colors:
- Green fill indicates a bullish trend
- Red fill indicates a bearish trend
- You can adjust the thickness of the bands and the transparency of the fill colors
Marker Lines
- High Marker Line (magenta): Tracks the highest opening price during bullish trends
- Low Marker Line (cyan): Tracks the lowest opening price during bearish trends
- These lines create a "zone" that helps identify potential support and resistance levels
- Diamond markers appear when the trend resets
Background Fill
- Optional full-chart background coloring
- Green background for bullish trends
- Red background for bearish trends
How to Read the Indicator
1. **Trend Identification**
- Green fill/background indicates a bullish trend
- Red fill/background indicates a bearish trend
- Watch for color changes as they signal potential trend changes
2. **Support and Resistance Levels**
- The bands create dynamic support and resistance zones
- Price tends to respect these levels during strong trends
- Watch for price reactions when it touches either band
3. **Marker Lines**
- These act as historical support/resistance levels
- The space between marker lines creates a "zone" where price might find support or resistance
- Diamond shapes appear when these levels reset, indicating potential trend changes
Trading Tips
1. **Trend Trading**
- Trade in the direction of the background color
- Look for pullbacks to the support/resistance bands in the trend direction
- Use marker lines as potential entry/exit points
2. **Reversal Signals**
- Watch for diamond markers as they indicate trend resets
- Confirm reversals with price action and other indicators
- Pay attention to how price reacts around marker lines
3. **Timeframe Analysis**
- Use custom resolution for a broader market perspective
- Higher timeframes for overall trend
- Lower timeframes for entry/exit timing
Customization Options
1. **Display Settings**
- Toggle bands and fill visibility
- Adjust line thickness
- Customize colors for all components
2. **Background Options**
- Toggle full-chart background
- Adjust background transparency
3. **Marker Line Settings**
- Toggle visibility of marker lines
- Toggle reset diamonds
- Customize marker line colors
Best Practices
1. Start with the default settings to understand how the indicator behaves
2. Gradually customize colors and settings to match your trading style
3. Use multiple timeframes to confirm trends
4. Don't trade solely based on the indicator - combine it with price action and other tools
5. Pay special attention to areas where marker lines and bands converge
6. Watch for diamond markers as they often precede significant moves
Remember, this indicator works best when used as part of a complete trading strategy, not in isolation.
The information and signals provided by this indicator are intended solely for educational and informational purposes. They do not constitute financial, legal, or any other professional advice. Past performance is not indicative of future results. Trading and investing involve significant risk, and it is strongly recommended that you use this indicator in conjunction with other analysis tools and indicators. Always consult with a qualified financial advisor or professional before making any investment decisions. The creators and distributors of this indicator expressly disclaim any liability for any losses incurred through the use of the indicator or reliance on the information provided. Use at your own risk.
Inside Bar with High/LowInside Bar with High/Low
The indicator plots horizontal mid line between two Inside bars with High / Low with Multi Time Frame Selection by the user which can be traded in trending markets in the direction of the trend, when traded this way they are typically referred to as a ‘Breakout Play’ or an inside bar ‘Price Action Breakout Pattern’ They can also be traded counter-trend, typically from ‘Key Chart Levels’ , when traded this way they are often referred to as ‘Inside Bar Reversals’ .
The classic entry for an inside bar signal is to place a buy stop or sell stop at the high or low of the mother bar, and then when price breakouts above or below the mother bar, your entry order is filled with best time frame preferably more than 1 hour.
Stop loss placement is typically at the opposite end of the mother bar, or it can be placed near the mother bar halfway point (50% level), typically if the mother bar is larger than average.
It’s worth noting that these are the ‘classic’ or standard entry and stop loss placements for an inside bar setup is a useful tool for traders looking to identify potential reversals using the 20/50 EMA and candlestick patterns. However, like any trading tool, it should be used in conjunction with other indicators and analysis techniques for better accuracy
And also this tool is especially useful for day traders who want to track price action during specific times of the day and make informed decisions based on market behavior with more than 60 minutes period
As always, back testing and customization are recommended to optimize performance across different market conditions
In the end, experienced traders may decide on other entries or stop loss placements as they see fit.
Please remember that this indicator is provided for educational purposes only and does not constitute financial advice
Multi-Period Rolling VWAPMulti-Period Rolling VWAP (MP-RVWAP)
This indicator plots multiple Rolling Volume-Weighted Average Price (RVWAP) lines over different time periods (7, 14, 30, 60, 90, 180, and 360 days) on a single chart. Each RVWAP is calculated using a user-defined timeframe and source (default: HLC3), ensuring consistency across chart resolutions.
Key Features:
Customizable Periods: Toggle visibility for each period (7d, 14d, 30d, 60d, 90d, 180d, 360d) and adjust their colors.
Labels: Each RVWAP line is labeled at the end (e.g., "7d", "360d") for easy identification.
Standard Deviation Bands: Optional bands can be added above and below each RVWAP, with customizable multipliers (set to 0 to hide).
Flexible Timeframe: Define a single timeframe (default: 1D) for all RVWAP calculations, independent of the chart’s timeframe.
Minimum Bars: Set a minimum number of bars (default: 10) to ensure reliable calculations.
Usage:
Ideal for traders analyzing price trends across multiple time horizons. Enable/disable specific RVWAPs, tweak colors, and add bands to suit your strategy.
Rolling Pivot PointsThe "Rolling Pivot Points" indicator, built in Pine Script (version 6) for TradingView, overlays dynamic pivot levels on a price chart. It calculates a 24-hour lookback period (length = 1440 / (timeframe.in_seconds() / 60)) using the prior period’s high, low, and close to determine a Pivot Point (vPP) and three resistance (vR1, vR2, vR3) and support (vS1, vS2, vS3) levels. Plotted lines include vPP (yellow), vR1 (red), and vS1 (blue) in a cross style, with a customizable reset time (default: 8 AM) to refresh levels daily.
The indicator updates at the specified resetTime (minute = 0), otherwise retaining prior levels, making it ideal for intraday traders. The averageDays input (default: 5) is present but unclear in function. Suited for identifying key price zones, it adapts across timeframes, offering a concise, color-coded tool for technical analysis on TradingView.
Volume Profile [ActiveQuants]The Volume Profile indicator visualizes the distribution of trading volume across price levels over a user-defined historical period. It identifies key liquidity zones, including the Point of Control (POC) (price level with the highest volume) and the Value Area (price range containing a specified percentage of total volume). This tool is ideal for traders analyzing support/resistance levels, market sentiment , and potential price reversals .
█ CORE METHODOLOGY
Vertical Price Rows: Divides the price range of the selected lookback period into equal-height rows.
Volume Aggregation: Accumulates bullish/bearish or total volume within each price row.
POC: The row with the highest total volume.
Value Area: Expands from the POC until cumulative volume meets the user-defined threshold (e.g., 70%).
Dynamic Visualization: Rows are plotted as horizontal boxes with widths proportional to their volume.
█ KEY FEATURES
- Customizable Lookback & Resolution
Adjust the historical period ( Lookback ) and granularity ( Number of Rows ) for precise analysis.
- Configurable Profile Width & Horizontal Offset
Control the relative horizontal length of the profile rows, and set the distance from the current bar to the POC row’s anchor.
Important: Do not set the horizontal offset too high. Indicators cannot be plotted more than 500 bars into the future.
- Value Area & POC Highlighting
Set the percentage of total volume required to form the Value Area , ensuring that key volume levels are clearly identified.
Value Area rows are colored distinctly, while the POC is marked with a bold line.
- Flexible Display Options
Show bullish/bearish volume splits or total volume.
Place the profile on the right or left of the chart.
- Gradient Coloring
Rows fade in color intensity based on their relative volume strength .
- Real-Time Adjustments
Modify horizontal offset, profile width, and appearance without reloading.
█ USAGE EXAMPLES
Example 1: Basic Volume Profile with Value Area
Settings:
Lookback: 500 bars
Number of Rows: 100
Value Area: 70%
Display Type: Up/Down
Placement: Right
Image Context:
The profile appears on the right side of the chart. The POC (orange line) marks the highest volume row. Value Area rows (green/red) extend above/below the POC, containing 70% of total volume.
Example 2: Total Volume with Gradient Colors
Settings:
Lookback: 800 bars
Number of Rows: 100
Profile Width: 60
Horizontal Offset: 20
Display Type: Total
Gradient Colors: Enabled
Image Context:
Rows display total volume in a single color with gradient transparency. Darker rows indicate higher volume concentration.
Example 3: Left-Aligned Profile with Narrow Value Area
Settings:
Lookback: 600 bars
Number of Rows: 100
Profile Width: 45
Horizontal Offset: 500
Value Area: 50%
Profile Placement: Left
Image Context:
The profile shifts to the left, with a tighter Value Area (50%).
█ USER INPUTS
Calculation Settings
Lookback: Historical bars analyzed (default: 500).
Number of Rows: Vertical resolution of the profile (default: 100).
Profile Width: Horizontal length of rows (default: 50).
Horizontal Offset: Distance from the current bar to the POC (default: 50).
Value Area (%): Cumulative volume threshold for the Value Area (default: 70%).
Volume Display: Toggle between Up/Down (bullish/bearish) or Total volume.
Profile Placement: Align profile to the Right or Left of the chart.
Appearance
Rows Border: Customize border width/color.
Gradient Colors: Enable fading color effects.
Value Area Colors: Set distinct colors for bullish and bearish Value Area rows.
POC Line: Adjust color, width, and visibility.
█ CONCLUSION
The Volume Profile indicator provides a dynamic, customizable view of market liquidity. By highlighting the POC and Value Area, traders can identify high-probability reversal zones, gauge market sentiment, and align entries/exits with key volume levels.
█ IMPORTANT NOTES
⚠ Lookback Period: Shorter lookbacks prioritize recent activity but may omit critical levels.
⚠ Horizontal Offset Limitation: Avoid excessively high offsets (e.g., close to ±300). TradingView restricts plotting indicators more than 500 bars into the future, which may truncate or hide the profile.
⚠ Risk Management: While the indicator highlights areas of concentrated volume, always use it in combination with other technical analysis tools and proper risk management techniques.
█ RISK DISCLAIMER
Trading involves substantial risk. The Volume Profile highlights historical liquidity but does not predict future price movements. Always use stop-loss orders and confirm signals with additional analysis. Past performance is not indicative of future results.
📊 Happy trading! 🚀
Multi-Timeframe RPM Gauges with Custom Timeframes by DiGetIntroducing the **Multi-Timeframe RPM Gauges with Custom Timeframes + RSI Combos (mod) by DiGet** – a cutting-edge TradingView indicator meticulously crafted to revolutionize your market analysis.
Imagine having a dynamic dashboard right on your chart that consolidates the power of nine essential technical indicators—RSI, CCI, Stochastic, Williams %R, EMA crossover, Bollinger Bands, ATR, MACD, and Ichimoku Cloud—across multiple timeframes. This indicator not only displays each indicator’s score through an intuitive gauge system but also computes a combined metric to provide you with an at-a-glance understanding of market momentum and potential trend shifts.
**Key Features:**
- **Multi-Timeframe Insight:**
Configure up to four custom timeframes (e.g., 1, 5, 15, 60 minutes) to capture both short-term fluctuations and long-term trends, ensuring you never miss critical market moves.
- **Comprehensive Signal Suite:**
Benefit from a harmonious blend of signals. Whether you rely on momentum indicators like RSI and CCI, volatility measures like Bollinger Bands and ATR, or trend confirmations via EMA, MACD, and Ichimoku, every metric is normalized into actionable percentages.
- **Dynamic, Color-Coded Gauge Display:**
A built-in table presents all your data in a clear, color-coded format—green for bullish, red for bearish, and gray for neutral conditions. This visual representation allows you to quickly gauge market sentiment without sifting through complex charts.
- **Customizable Layout:**
Tailor your experience by toggling individual table columns. Whether you want to focus solely on RSI or dive deep into combined metrics like RSI & CCI or RSI & MACD, the choice is yours.
- **Optimized Utility Functions:**
Proprietary functions standardize indicator values into percentage scores, making it simpler than ever to compare different signals and spot opportunities in real time.
- **User-Friendly Interface:**
Designed for both beginners and seasoned traders, the straightforward input settings let you easily adjust technical parameters and timeframes to suit your personal trading strategy.
This indicator is not just a tool—it’s your new trading companion. It equips you with a multi-dimensional view of the market, enabling faster, more informed decision-making. Whether you’re scanning across various assets or drilling down on a single chart, the Multi-Timeframe RPM Gauges empower you to interpret market data with unprecedented clarity.
Add this indicator to your TradingView chart today and experience a smarter, more efficient way to navigate the markets. Join the community of traders who have elevated their analysis—and be ready to receive countless thanks as you transform your trading strategy!
real_time_candlesIntroduction
The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold.
This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches.
Key Features
The library supports two primary candle generation approaches:
Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars.
Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe.
Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data.
Configuration Requirements
For optimal performance with this library:
Set max_bars_back = 5000 in your script settings
When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500
These settings ensure that you will be able to draw correctly and will avoid any runtime errors.
Usage Examples
Basic Chart-Time Candle Visualization
// Create real-time candles for RSI
float rsi = ta.rsi(close, 14)
Candle rsi_candle = candle_series(rsi, CandleType.candlestick)
// Plot the candles using Pine's built-in function
plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close,
"RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color)
Multiple Access Patterns
The library provides three ways to access candle data, accommodating different programming styles:
// 1. Array-based access for collection operations
Candle candles = candle_array(source)
// 2. Object-oriented access for single entity manipulation
Candle candle = candle_series(source)
float value = candle.source(Source.HLC3)
// 3. Tuple-based access for functional programming styles
= candle_tuple(source)
Custom Timeframe Examples
// Create 20-second candles with EMA overlay
plot_ctf_candles(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 20,
timezone = -5,
tied_open = true,
ema_period = 9,
enable_ema = true
)
// Create tick-based candles (new candle every 15 ticks)
plot_ctf_tick_candles(
source = close,
candle_type = CandleType.heikin_ashi,
number_of_ticks = 15,
timezone = -5,
tied_open = true
)
Advanced Usage with Custom Visualization
// Get custom timeframe candles without automatic plotting
CandleCTF my_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 30
)
// Apply custom logic to the candles
float ema_values = my_candles.ctf_ema(14)
// Draw candles and EMA using time-based coordinates
my_candles.draw_ctf_candles_time()
ema_values.draw_ctf_line_time(line_color = #FF6D00)
Library Components
Data Types
Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties
CandleCTF: Extended candle structure with additional time metadata for custom timeframes
TickData: Structure for individual price updates with time deltas
Enumerations
CandleType: Specifies visualization style (candlestick or Heikin-Ashi)
Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.)
SampleType: Sets sampling method (Time-based or Tick-based)
Core Functions
get_tick(): Captures current price as a tick data point
candle_array(): Creates an array of candles from price updates
candle_series(): Provides a single candle based on latest data
candle_tuple(): Returns OHLC values as a tuple
ctf_candles_array(): Creates custom timeframe candles without rendering
Visualization Functions
source(): Extracts specific price components from candles
candle_ctf_to_float(): Converts candle data to float arrays
ctf_ema(): Calculates exponential moving averages for candle arrays
draw_ctf_candles_time(): Renders candles using time coordinates
draw_ctf_candles_index(): Renders candles using bar index coordinates
draw_ctf_line_time(): Renders lines using time coordinates
draw_ctf_line_index(): Renders lines using bar index coordinates
Technical Implementation Notes
This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes:
Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas
Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+
Temporal synchronization: Manages two time domains (chart time and custom timeframe)
The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe.
Limitations
Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data
Real-time visualization is only available during live chart updates
Maximum history is constrained by Pine Script's array size limits
Applications
Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time
Volume analysis: Create custom volume profiles independent of chart timeframe
Scalping strategies: Identify short-term patterns with precisely defined time windows
Volatility measurement: Track price movement characteristics within bars
Custom signal generation: Create entry/exit signals based on custom timeframe patterns
Conclusion
The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities.
Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script.
Implementation Details & Advanced Guide
Core Implementation Concepts
The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams.
Tick Processing System
The foundation of the library is the get_tick() function, which captures price updates as they occur:
export get_tick(series float source = close, series float na_replace = na)=>
varip float price = na
varip int series_index = -1
varip int old_time = 0
varip int new_time = na
varip float time_delta = 0
// ...
This function:
Samples the current price
Calculates time elapsed since last update
Maintains a sequential index to track updates
The resulting TickData structure serves as the fundamental building block for all candle generation.
State Management Architecture
The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model.
For chart-time candles, the core state transition logic is:
// Real-time update of current candle
candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color)
candles.set(0, candle_data)
// When a new bar starts, preserve the previous candle
if clear_state
candles.insert(1, candle_data)
price.clear()
// Reset state for new candle
Open := Close
price.push(Open)
series_index += 1
This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data.
Custom Timeframe Implementation
The custom timeframe system manages its own time boundaries independent of chart bars:
bool clear_state = switch settings.sample_type
SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks
SampleType.Time => cumulative_time_delta >= settings.number_of_seconds
This dual-clock system synchronizes two time domains:
Pine's execution clock (bar-by-bar processing)
The custom timeframe clock (tick or time-based)
The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps.
Advanced Usage Techniques
1. Creating Custom Indicators with Real-Time Candles
To develop indicators that process real-time data within the current bar:
// Get real-time candles for your data
Candle rsi_candles = candle_array(ta.rsi(close, 14))
// Calculate indicator values based on candle properties
float signal = ta.ema(rsi_candles.first().source(Source.Close), 9)
// Detect patterns that occur within the bar
bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close
2. Working with Custom Timeframes and Plotting
For maximum flexibility when visualizing custom timeframe data:
// Create custom timeframe candles
CandleCTF volume_candles = ctf_candles_array(
source = volume,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 60
)
// Convert specific candle properties to float arrays
float volume_closes = volume_candles.candle_ctf_to_float(Source.Close)
// Calculate derived values
float volume_ema = volume_candles.ctf_ema(14)
// Create custom visualization
volume_candles.draw_ctf_candles_time()
volume_ema.draw_ctf_line_time(line_color = color.orange)
3. Creating Hybrid Timeframe Analysis
One powerful application is comparing indicators across multiple timeframes:
// Standard chart timeframe RSI
float chart_rsi = ta.rsi(close, 14)
// Custom 5-second timeframe RSI
CandleCTF ctf_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 5
)
float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close)
float fast_rsi = fast_rsi_array.first()
// Generate signals based on divergence between timeframes
bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1)
Final Notes
This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms.
The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application.
------------------------
Library "real_time_candles"
A comprehensive library for creating real-time candles with customizable timeframes and sampling methods.
Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization.
Allows for tick-based or time-based sampling with moving average overlay capabilities.
get_tick(source, na_replace)
Captures the current price as a tick data point
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
na_replace (float) : Optional - Value to use when source is na
Returns: TickData structure containing price, time since last update, and sequential index
candle_array(source, candle_type, sync_start, bullish_color, bearish_color)
Creates an array of candles based on price updates
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of Candle objects ordered with most recent at index 0
candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides a single candle based on the latest price data
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: A single Candle object representing the current state
candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides candle data as a tuple of OHLC values
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Tuple representing current candle values
method source(self, source, na_replace)
Extracts a specific price component from a Candle
Namespace types: Candle
Parameters:
self (Candle)
source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
na_replace (float) : Optional - Value to use when source value is na
Returns: The requested price value from the candle
method source(self, source)
Extracts a specific price component from a CandleCTF
Namespace types: CandleCTF
Parameters:
self (CandleCTF)
source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
Returns: The requested price value from the candle as a varip
method candle_ctf_to_float(self, source)
Converts a specific price component from each CandleCTF to a float array
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
Returns: Array of float values extracted from the candles, ordered with most recent at index 0
method ctf_ema(self, ema_period)
Calculates an Exponential Moving Average for a CandleCTF array
Namespace types: array
Parameters:
self (array)
ema_period (simple float) : Period for the EMA calculation
Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0
method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar time coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using time-based x-coordinates
method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar index coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using index-based x-coordinates
method draw_ctf_line_time(self, source, line_size, line_color)
Renders a line representing a price component from the candles using time coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_time(self, line_size, line_color)
Renders a line from a varip float array using time coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_index(self, source, line_size, line_color)
Renders a line representing a price component from the candles using index coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
method draw_ctf_line_index(self, line_size, line_color)
Renders a line from a varip float array using index coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots tick-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots tick-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots time-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots time-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)
Unified function for plotting candles with comprehensive options
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Optional - Type of candle chart to display
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
ema_period (simple float) : Optional - Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
enable_ema (bool) : Optional - Whether to display the EMA overlay
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with optional EMA overlay
ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)
Creates an array of custom timeframe candles without rendering them
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)
sample_type (simple SampleType) : Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of CandleCTF objects ordered with most recent at index 0
Candle
Structure representing a complete candle with price data and display properties
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
candle_color (series color) : Color to use when rendering the candle
ready (series bool) : Boolean indicating if candle data is valid and ready for use
TickData
Structure for storing individual price updates
Fields:
price (series float) : The price value at this tick
time_delta (series float) : Time elapsed since the previous tick in milliseconds
series_index (series int) : Sequential index identifying this tick
CandleCTF
Structure representing a custom timeframe candle with additional time metadata
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
open_time (series int) : Timestamp marking when the candle was opened (in Unix time)
time_delta (series float) : Duration of the candle in milliseconds
candle_color (series color) : Color to use when rendering the candle
Global M2 Money Supply (USD) GrowthThe Global M2 Growth indicator evaluates the total liquid money supply, including cash, checking deposits, and assets that can be easily converted to cash. It reflects changes in global liquidity by tracking year-on-year (YoY) changes in the Global M2 money supply rather than its absolute value. This approach highlights the velocity of liquidity expansion or contraction, offering a clearer understanding of its correlation with asset performance, such as Bitcoin.
How It Works
When the Global M2 money supply expands, it reflects an increase in available liquidity. This often leads to an influx of capital into higher-yielding and riskier assets like Bitcoin, equities, and commodities. Conversely, when M2 contracts, liquidity tightens, leading to declines in the values of these assets.
An essential insight is that Bitcoin's price is not immediately affected by changes in M2. Research shows a lag of approximately 56-60 days (around two months) between liquidity changes and Bitcoin's price movements. Shifting the liquidity data forward by this period improves the correlation between Global M2 and Bitcoin performance.
How to Use
Track Global M2 YoY Change: Focus on liquidity's yearly change to identify trends. Rapid increases in liquidity often signify favorable conditions for Bitcoin and other risk assets to rise, while contractions often predict price declines or consolidation phases.
Account for the Lag Effect: Incorporate the two-month lag into your analysis to predict Bitcoin's potential moves more accurately. For instance, a recent resurgence in liquidity growth could signal a Bitcoin rally within the next two months.
Use as a Macro Indicator: Monitor liquidity trends alongside other economic indicators and asset performance metrics to build a more comprehensive investment framework.
By tracking these dynamics, traders and investors can better anticipate Bitcoin's trajectory and make informed decisions.
Auto Fib Retracement with Buy/SellKey Features of the Advanced Script:
Multi-Timeframe (MTF) Analysis:
We added an input for the higher timeframe (higher_tf), where the trend is checked on a higher timeframe to confirm the primary trend direction.
Complex Trend Detection:
The trend is determined not only by the current timeframe but also by the trend on the higher timeframe, giving a more comprehensive and reliable signal.
Dynamic Fibonacci Levels:
Fibonacci lines are plotted dynamically, extending them based on price movement, with the Fibonacci retracement drawn only when a trend is identified.
Background Color & Labels:
A background color is added to give a clear indication of the trend direction. Green for uptrend, red for downtrend. It makes it visually easier to understand the current market structure.
"Buy" or "Sell" labels are shown directly on the chart to mark possible entry points.
Strategy and Backtesting:
The script includes strategy commands (strategy.entry and strategy.exit), which allow for backtesting the strategy in TradingView.
Stop loss and take profit conditions are added (loss=100, profit=200), which can be adjusted according to your preferences.
Next Steps:
Test with different timeframes: Try changing the higher_tf to different timeframes (like "60" or "240") and see how it affects the trend detection.
Adjust Fibonacci settings: Modify how the Fibonacci levels are calculated or add more Fibonacci levels like 38.2%, 61.8%, etc.
Optimize Strategy Parameters: Fine-tune the entry/exit logic by adjusting stop loss, take profit, and other strategy parameters.
This should give you a robust foundation for creating advanced trend detection strategies
Ragi's 24h volumeThis script is a TradingView Pine Script indicator that displays the 24-hour trading volume for a given asset. It provides both the native volume of the asset and, if the asset is not already listed on Binance, also displays the 24-hour volume from Binance (if applicable). Here's a breakdown of the key components:
Volume Calculation:
It sums the volume data over different time frames: 1-minute, 5-minute (for daily charts), or 60-minute intervals.
The volume is calculated based on the asset's volume type (either "quote" volume or a calculated value of close * volume).
For crypto assets, if the volume data is unavailable, it raises an error.
Binance Volume:
If the asset is not from Binance, the script fetches 24-hour volume data from Binance for that symbol, ensuring it is using the correct currency rate.
Display:
The indicator displays a table with the 24-hour volume in the chosen position on the chart (top, middle, or bottom).
The table displays the current exchange's volume, and if applicable, the Binance volume.
The volume is color-coded based on predefined thresholds:
Attention: Displays a warning color for volumes exceeding the attention level.
Warning: Shows an alert color for volumes above the warning threshold.
Normal: Displays in standard color when the volume is lower than the warning level.
The text and background color are customizable, and users can adjust the text size and position of the table.
User Inputs:
The script allows customization of table text size, position, background color, and volume thresholds for attention and warning.
In summary, this indicator is designed to track and display 24-hour volume on a chart, with additional volume information from Binance if necessary, and provides visual cues based on volume levels to help traders quickly assess trading activity.
VIDYA For-Loop | QuantEdgeB Introducing VIDYA For-Loop by QuantEdgeB
Overview
The VIDYA For-Loop indicator by QuantEdgeB is a dynamic trend-following tool that leverages Variable Index Dynamic Average (VIDYA) along with a rolling loop function to assess trend strength and direction. By utilizing adaptive smoothing and a recursive loop for threshold evaluation, this indicator provides a more responsive and robust signal framework for traders.
______
Key Components & Features
📌 VIDYA (Variable Index Dynamic Average)
- Adaptive Moving Average that adjusts its responsiveness based on market volatility.
- Uses a dynamic smoothing constant based on standard deviations.
- Allows for better trend detection compared to static moving averages.
📌 Loop Function (Rolling Calculation)
- A for-loop algorithm continuously compares VIDYA values over a defined lookback range.
- Measures the number of times price trends higher or lower within the rolling window.
- Generates a momentum-based score that helps quantify trend persistence.
📌 Trend Signal Calculation
- A long signal is triggered when the loop score exceeds the upper threshold.
- A short signal is triggered when the loop score falls below the lower threshold.
- The result is a clear directional bias that adapts to changing market conditions.
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How It Works in Trading
✅ Detects Trend Strength – By measuring cumulative movements within a window.
✅ Filters Noise – Uses adaptive smoothing to avoid whipsaws.
✅ Dynamic Thresholds – Enables customized entry & exit conditions.
✅ Color-Coded Candles – Provides visual clarity for traders.
______
Visual Representation
Trend Signals:
🔵 Blue Candles – Strong Uptrend
🔴 Red Candles – Strong Downtrend
Thresholds:
📈 Long Threshold – Upper bound for bullish confirmation.
📉 Short Threshold – Lower bound for bearish confirmation.
Labels & Annotations (Optional):
✅ Long & Short Labels can be turned on or off for trade signal clarity.
📊 Display of entry & exit points based on loop calculations.
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Settings:
VIDYA Length: 2 → Number of bars for VIDYA calculation.
SD Length: 5 → Standard deviation length for VIDYA calculation.
Source: Close → Defines the input data source (Close price).
Start Loop: 1 → Initial lookback period for the loop function.
End Loop: 60 → Maximum lookback range for trend scoring.
Long Threshold: 40 → Upper bound for a long signal.
Short Threshold: 10 → Lower bound for a short signal.
Extra Plots: True → Enables additional moving averages for visualization.
______
Conclusion
The VIDYA For-Loop by QuantEdgeB is a next-gen adaptive trend filter that combines dynamic smoothing with recursive trend evaluation, making it an invaluable tool for traders seeking precision and consistency in their strategies.
🔹 Who should use VIDYA For Loop :
📊 Trend-Following Traders – Helps identify sustained trends.
⚡ Momentum Traders – Captures strong price swings.
🚀 Algorithmic & Systematic Trading – Ideal for automated entries & exits.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
PriceCatch - Previous Hour RangeHi Tradingview community,
Recently I stumbled upon a video on Youtube where the Youtuber was talking about Intraday trading based on 1 hour price range.
Anyone requesting the code was asked to contact over email for the code. So, I thought, this is such a simple script and has no special complex coding involved and why such a show off instead of just sharing it.
So, I decided to write the code myself and it took me under 10 minutes to do it. So, here's the PriceCatch - Previous Hour Range script. It is open source, so you can check it and apply it in your trading strategy.
Remember, this is just a simple range plotter and does not give any signals.
If you want 2 hours range, then simply change 60 to 120. Simple.
So, all the best with your trades.
PriceCatch
Dynamic Pivot PointsDynamic Pivot Point Indicator
The Dynamic Pivot Point is an indicator used on the TradingView platform that dynamically calculates pivot points and displays them on the chart. This indicator provides automatically adjustable support and resistance levels for different timeframes. By visualizing dynamic levels that match current market conditions, traders can plan their strategies more effectively.
Features
Adapts to Timeframes
The indicator automatically selects the appropriate pivot calculation method based on the user's current timeframe. For example:
For short timeframes such as 1, 3, or 5 minutes, it uses daily (1D) data.
For medium timeframes like 15, 30, or 60 minutes, it uses weekly (1W) data.
For longer timeframes such as 120, 180, or 240 minutes, it uses monthly (1M) data.
For very long timeframes like 360, 480 minutes, daily (D), or weekly (1W), it uses 12-month (12M) data.
Dynamic Pivot Levels
The indicator automatically calculates pivot levels based on the specified high and low values.
Flexible Line Style Options
Users can choose different line styles (Dashed, Dotted, Solid) to improve visual clarity on the chart.
Clean and Clear Visualization
The indicator automatically removes previous lines and displays the latest levels clearly on the chart, preventing clutter and allowing traders to focus more efficiently.
How It Works
Identifying High and Low Levels
The indicator retrieves previous and current high and low levels based on the selected timeframe.
New high and low levels are updated by comparing them with previous levels.
Calculating Pivot Levels
Pivot points are calculated using Fibonacci ratios between high and low levels.
These levels represent dynamic support and resistance zones.
Drawing Lines
The calculated levels are displayed as lines on the chart, each represented with different colors and styles.
Use Cases
Support and Resistance Levels
The indicator dynamically calculates and displays support and resistance levels, serving as reference points for buy and sell decisions.
Trend Analysis
Fibonacci levels help identify trend strength and potential reversal points.
Risk Management
Pivot points assist in setting stop-loss and take-profit levels.
Multi-Timeframe Analysis
Since the indicator adapts to different timeframes, it can be used for both short-term and long-term analysis.
Advantages
✅ Automatic Calculation: No manual calculations are required, as it updates dynamically.
✅ Flexible Timeframe Support: Adapts to different timeframes.
✅ Visual Clarity: Line styles and colors make it easy to distinguish levels on the chart.
✅ Fibonacci Integration: Adds depth to technical analysis.
Conclusion
The Dynamic Pivot Point indicator is a useful tool for both beginners and experienced traders. By dynamically calculating pivot points and Fibonacci levels, it simplifies market analysis and aids in strategy development. With its flexible structure and clear visualization, it can be effectively used across all timeframes.
6 dakika önce
Sürüm Notları
This indicator is written for Support Resistance Traders
RSI Divergence[UgurTash] – Real-Time📈 RSI Divergence – Real-Time, Adaptive, and Intelligent RSI Divergence Detection
🚀 What Does This Indicator Do?
RSI Divergence is a real-time divergence detection tool that helps traders identify bullish and bearish divergences between price and the Relative Strength Index (RSI). Unlike traditional RSI-based indicators, this script offers:
✅ Real-time detection – No need to wait for bar closes or repainting.
✅ Dynamic time-frame adaptation – The script automatically adjusts RSI settings based on the selected chart time frame.
✅ Multi-layered divergence analysis – Supports short-term, medium-term, and long-term divergence detection with an optional all-term mode that dynamically selects the best configuration.
🛠 How Does It Work?
Pivot-Based Divergence Detection:
The script analyzes pivot points on both price and RSI to determine valid divergences.
Bullish divergence occurs when price forms a lower low but RSI trends higher, indicating potential upward momentum.
Bearish divergence occurs when price forms a higher high but RSI trends lower, signaling possible weakness.
Adaptive RSI Calculation:
The RSI length is dynamically adjusted based on the chosen time frame:
Short-Term: RSI (7) for 1-5 min charts.
Medium-Term: RSI (14) for 15-60 min charts.
Long-Term: RSI (28) for 4H+ charts.
In All-Term Mode, the script automatically determines the best RSI length based on the active chart timeframe.
Smart Visualization & Alerts:
Bullish divergences are marked with green lines & labels.
Bearish divergences are highlighted in red.
Users can customize symbol size, divergence labels, and colors.
Instant alerts notify traders as soon as a divergence is detected.
🎯 How to Use This Indicator?
📌 For Trend Reversals: Look for bullish divergences at key support levels and bearish divergences at resistance zones.
📌 For Trend Continuation: Combine divergence signals with moving averages, volume analysis, or price action strategies to confirm trades.
📌 For Scalping & Swing Trading: Adjust the time-frame settings to match your trading style.
🏆 What Makes This Indicator Original?
🔹 Unlike standard RSI divergence indicators, this script features real-time analysis with no repainting, allowing for instant trading decisions.
🔹 The time-frame adaptive RSI makes it dynamic and suitable for any market condition.
🔹 The multi-term divergence detection offers flexibility, giving traders a precise view of both short-term & long-term market structure.
⚠ Note: No indicator guarantees 100% accuracy. Always use additional confirmations and sound risk management strategies.
If you find this tool useful, don’t forget to support & share! 🚀
Candle Bias ForecastCandle Bias Forecast Indicator
Description:
The Candle Bias Forecast Indicator is an original multi‐timeframe analysis tool that generates price forecast levels based on the difference between candle biases on two different timeframes. It uses innovative calculations to provide potential forecast levels that align with current price action.
How It Works:
1. Candle Bias Calculation:
For each candle, the indicator computes a “candle bias” using the formula:
candleBias = (((open + close)/2 - (high + low)/2) + ((close - open)/(high - low)))/2
This measure captures both the positioning of the candle’s body within its range and the normalized move from open to close.
2. Multi-Timeframe Analysis:
The script uses multiple timeframe pairs (e.g., 5-minute vs. 30-minute, 10-minute vs. 60-minute, etc.). For each pair, the bias is computed on the lower timeframe and on the higher timeframe.
3. Normalization with ATR:
To translate the dimensionless bias difference into price terms, the indicator multiplies the difference by the lower timeframe’s Average True Range (ATR). This scales the forecast adjustment to current market volatility.
4. Forecast Computation:
The forecast level for each pair is then calculated as:
forecast = close + (lowerTF_ATR * (lowerTF_bias - higherTF_bias))
This yields forecast levels that are plotted on the chart and connected by lines for a visual guide.
How to Use:
- Visual Confirmation: Add the indicator to your 1 to 15 minute chart to see forecast levels overlaid on the price.
- Supplementary Analysis: Use these forecast levels as an additional tool alongside your other analysis methods. They can help indicate potential support/resistance areas or directional bias.
Important Notes:
- Not a Standalone Signal: This indicator is intended to supplement your analysis. Always combine it with other tools and sound risk management practices.
- For Educational & Research Use: The indicator is provided “as is” without any guarantee of performance. It is designed to illustrate an innovative approach to multi-timeframe analysis.
- Disclaimer: Past performance is not indicative of future results. Use this tool at your own risk.
By combining candle bias with ATR-based normalization and multi-timeframe analysis, this indicator offers a unique perspective on market dynamics that can enrich your trading strategy.
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*This is an original script designed to add value to the TradingView community. Please test and validate its outputs thoroughly before using it in live trading.*
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
IronCondor 10am 30TF by RMThe IronCondor 10am 30TF indicator shows Iron Condor trades win rate over a large number of days.
The default ETFs in this indicators are "QQQ", "SPY", "RUT" , "CBTX" and "SPX", other entries have not been tested.
Iron Condor quick explanation:
- Iron Condors trades have four options, generally, are based around a Midpoint price (Current Market Price Strike) and
- Two equally distances Strikes for the SELL components (called the Body of the Iron Condor)
- Further away from the two SELLs, another Two BUYs for protection (not considered in this indicator)
- Iron Condors are used for Passive Income based on small gains most of the time.
The IronCondor 10am 30TF has its logic created based on the premises that:
- Most days the market prices stay within a range.
- As example the S&P market prices would stay within 1% on about 80% of the time
- The moving markets (bullish or bearish) occur about 20% of the time
- The biggest market price volatility generally occurs before market opens and then around the first hour or so of trade in the day.
- After the first hour or so of the market the prices would be most likely to stay within a range.
The operation is simple:
- At the Trade Star time in the day (say 10:30 Hrs.) draws a vertical yellow line, then
- Creates two blue horizontal lines for the SELL limits in the Iron Condor Body, at +/- 1% price boundary (check Ticker list below for values)
- At the Trade End time (say 16:00 Hrs.) checks that none of the SELL limits have been broken by highs or lows during the trade day
(The check is done calculating at Trade End time the high/lows 10 bars back for 30 min TF - timeframe)
- There is a label at each Trade End time with Win/Loss and Body value.
- There is one final label with overall calculated past performance in Win percentage out of 'n' trades
Defaults and User Entries:
- The User can modify the Midpoint price called 'IronCondor Midpoint STRIKE' (default is the Candle Close at the selected time)
- The User can modify the Body value called 'IronCondor Body' (default is the Ticker's selected value as per list below)
"QQQ" or "SPY" Body = 5
"RUT" or "CBTX" Body = 20
"SPX" Body = 60
* Disclaimer: This is not a Financial tool, it cannot used as any kind of advice to invest or risk moneys in any market,
Markets are volatile in nature - with little or no warning - and will drain your account if you are not careful.
Use only as an academic demonstrator => * Use at your own risk *
Grouped EMAsThis indicator displays grouped EMAs across multiple timeframes (5m, 15m, 30m, and 60m) on a single chart. It allows traders to easily track key EMA levels across different timeframes for better trend analysis and decision-making.
Key Features:
Adjustable EMA Length: Change the EMA period once, and it updates across all timeframes simultaneously.
Multi-Timeframe Support: Displays 365 EMA High and Low for 5-minute, 15-minute, 30-minute, and 60-minute intervals.
Clear Color Coding: Each timeframe is color-coded for quick visual recognition.
How to Use:
Adjust the EMA length using the input option to set your preferred period.
Observe the EMAs across different timeframes to identify support, resistance, and trend directions.
Combine with other indicators or price action strategies for enhanced trading insights.
This tool is ideal for traders looking to simplify multi-timeframe analysis while maintaining flexibility with the EMA period.
Enjoy more informed trading and enhanced trend analysis with Grouped EMAs!
Adaptive Supply and Demand [EdgeTerminal]Adaptive Supply and Demand is a dynamic supply and demand indicator with a few unique twists. It considers volume pressure, volatility-based adjustments and multi-time frame momentum for confidence scoring (multi-step confirmation) to generate dynamic lines that adjust based on the market and also to generate dynamic support/resistance levels for the supply and demand lines.
The dynamic support and resistance lines shown gives you a better situational awareness of the current state of the market and add more context to why the market is moving into a certain direction.
> Trading Scenarios
When the confidence score is over 80%, strong volume pressure in trend direction (up or down), volatility is low and momentum is aligned across timeframes, there is an indication of a strong upward or downward trend.
When the supply and demand line crossover, the confidence score is over 75% and the volume pressure is shifting, this can be an indicator of trend reversal. Use tight initial stops, scale into position as trend develops, monitor the volume pressure for continuation and wait for confidence confirmation.
When the confiance score is below 60%, the volume pressure is choppy, volatility is high, you want to avoid trading or reduce position size, wait for confidence improvements, use support and resistance for entries/exits and use tighter stops due to market conditions. This is an indication of a ranging market.
Another scenario is when there is a sudden volume pressure increase, and a raising confidence score, the volatility is expanding and the bar momentum is aligning the volatility direction. This can indicate a breakout scenario.
> How it Works
1. Volume Pressure Analysis
Volume Pressure Analysis is a key component that measures the true buying and selling force in the market. Here's a detailed breakdown. The idea is to standardize volume to prevent large spikes from skewing results.
The indicator employs an adaptive volume normalization technique to detect genuine buying and selling pressure.
It takes current volume and divides it by average volume.
If normVol > 1: Current volume is above average
If normVol < 1: Current volume is below average
An example if this would be If current volume is 1500 and average is 1000, normVol = 1.5 (50% above average)
Another component of the volume pressure analysis is the Price Change Calculation sub-module. The purpose of this is to measure price movement relative to recent average.
It works by subtracting the average price from the current price. If the value is positive, price is average and if negative, price is below average.
Finally, the volume pressure is calculated to combine volume and price for true pressure reading.
2. Savitzky-Golay Filtering
SG filtering implements advanced signal smoothing while preserving important trend features. It uses weighted moving average approximation, preserves higher moments of data and reduces noise while maintaining signal integrity.
This results in smoother signal lines, reduced false crossovers and better trend identification. Traditional moving averages tend to lag and smooth out important features. Additionally, simple moving averages can miss critical turning points and regular smoothing can delay signal generation.
SG filtering preserves higher moments such as peaks, valleys and trends, reduces noise while maintaining signal sharpness.
It works by creating a symmetric weighting scheme. This way center points get the highest weights while edge points get the lowest weight.
3. Parkinson's Volatility
Parkinson's Volatility is an advanced volatility measurement formula using high-low range data. It uses high-low range for volatility calculation, incorporates logarithmic returns and annualized the volatility measure.
This results in more accurate volatility measurement, better risk assessment and dynamic signal sensitivity.
4. Multi-timeframe Momentum
This combines signals from each module for each timeframe to calculate momentum across three timeframes. It also applies weighted importance to each timeframe and generates a composite momentum signal.
This results in a more comprehensive trend analysis, reduced timeframe bias and better trend confirmation.
> Indicator Settings
Short-term Period:
Lower values makes it more sensitive, meaning it will generate more signals. Higher values makes it less sensitive, resulting in fewer signals. We recommend a 5 to 15 range for day trading, and 10 to 20 for swing trading
Medium-term Period:
Lower values result in faster trend confirmation and higher values show slower and more reliable confirmation. We recommend a range of 15-25 for day trading and 20-30 for swing trading.
Long-term Period:
Lower values makes it more responsive to trend changes and higher values are better for major trend identification. We recommend a range of 40-60 for day trading and 50-100 for swing trading.
Volume Analysis Window:
Lower values result in more sensitivity to volume changes and higher values result in smoother volume analysis. The optimal range is 15-25 for most trading styles.
Confidence Threshold:
Lower values generate more signals but quality decreases. Higher values generate fewer signals but accuracy increases.The optimal range is 0.65-0.8 for most trading conditions.
ICT NY Kill Zone Auto Trading### **ICT NY Kill Zone Auto Trading Strategy (5-Min Chart)**
#### **Overview:**
This strategy is based on Inner Circle Trader (ICT) concepts, focusing on the **New York Kill Zone**. It is designed for trading GBP/USD exclusively on the **5-minute chart**, automatically entering and exiting trades during the US session.
#### **Key Components:**
1. **Time Filter**
- The strategy only operates during the **New York Kill Zone (9:30 AM - 11:00 AM NY Time)**.
- It ensures execution only on the **5-minute timeframe**.
2. **Fair Value Gaps (FVGs) Detection**
- The script identifies areas where price action left an imbalance, known as Fair Value Gaps (FVGs).
- These gaps indicate potential liquidity zones where price may return before continuing in the original direction.
3. **Order Blocks (OBs) Identification**
- **Bullish Order Block:** Occurs when price forms a strong bullish pattern, suggesting further upside movement.
- **Bearish Order Block:** Identified when a strong bearish formation signals potential downside continuation.
4. **Trade Execution**
- **Long Trade:** Entered when a bullish order block forms within the NY Kill Zone and aligns with an FVG.
- **Short Trade:** Entered when a bearish order block forms within the Kill Zone and aligns with an FVG.
5. **Risk Management**
- **Stop Loss:** Fixed at **30 pips** to limit downside risk.
- **Take Profit:** Set at **60 pips**, providing a **2:1 risk-reward ratio**.
6. **Visual Aids**
- The **Kill Zone is highlighted in blue** to help traders visually confirm the active session.
**Objective:**
This script aims to **capitalize on institutional price movements** within the New York session by leveraging ICT concepts such as FVGs and Order Blocks. By automating trade entries and exits, it eliminates emotions and ensures a disciplined trading approach.
Auto-Length Moving Average + Trend Signals (Zeiierman)█ Overview
The Auto-Length Moving Average + Trend Signals (Zeiierman) is an easy-to-use indicator designed to help traders dynamically adjust their moving average length based on market conditions. This tool adapts in real-time, expanding and contracting the moving average based on trend strength and momentum shifts.
The indicator smooths out price fluctuations by modifying its length while ensuring responsiveness to new trends. In addition to its adaptive length algorithm, it incorporates trend confirmation signals, helping traders identify potential trend reversals and continuations with greater confidence.
This indicator suits scalpers, swing traders, and trend-following investors who want a self-adjusting moving average that adapts to volatility, momentum, and price action dynamics.
█ How It Works
⚪ Dynamic Moving Average Length
The core feature of this indicator is its ability to automatically adjust the length of the moving average based on trend persistence and market conditions:
Expands in strong trends to reduce noise.
Contracts in choppy or reversing markets for faster reaction.
This allows for a more accurate moving average that aligns with current price dynamics.
⚪ Trend Confirmation & Signals
The indicator includes built-in trend detection logic, classifying trends based on market structure. It evaluates trend strength based on consecutive bars and smooths out transitions between bullish, bearish, and neutral conditions.
Uptrend: Price is persistently above the adjusted moving average.
Downtrend: Price remains below the adjusted moving average.
Neutral: Price fluctuates around the moving average, indicating possible consolidation.
⚪ Adaptive Trend Smoothing
A smoothing factor is applied to enhance trend readability while minimizing excessive lag. This balances reactivity with stability, making it easier to follow longer-term trends while avoiding false signals.
█ How to Use
⚪ Trend Identification
Bullish Trend: The indicator confirms an uptrend when the price consistently stays above the dynamically adjusted moving average.
Bearish Trend: A downtrend is recognized when the price remains below the moving average.
⚪ Trade Entry & Exit
Enter long when the dynamic moving average is green and a trend signal occurs. Exit when the price crosses below the dynamic moving average.
Enter short when the dynamic moving average is red and a trend signal occurs. Exit when the price crosses above the dynamic moving average.
█ Slope-Based Reset
This mode resets the trend counter when the moving average slope changes direction.
⚪ Interpretation & Insights
Best for trend-following traders who want to filter out noise and only reset when a clear shift in momentum occurs.
Higher slope length (N): More stable trends, fewer resets.
Lower slope length (N): More reactive to small price swings, frequent resets.
Useful in swing trading to track significant trend reversals.
█ RSI-Based Reset
The counter resets when the Relative Strength Index (RSI) crosses predefined overbought or oversold levels.
⚪ Interpretation & Insights
Best for reversal traders who look for extreme overbought/oversold conditions.
High RSI threshold (e.g., 80/20): Fewer resets, only extreme conditions trigger adjustments.
Lower RSI threshold (e.g., 60/40): More frequent resets, detecting smaller corrections.
Great for detecting exhaustion in trends before potential reversals.
█ Volume-Based Reset
A reset occurs when current volume significantly exceeds its moving average, signaling a shift in market participation.
⚪ Interpretation & Insights
Best for traders who follow institutional activity (high volume often means large players are active).
Higher volume SMA length: More stable trends, only resets on massive volume spikes.
Lower volume SMA length: More reactive to short-term volume shifts.
Useful in identifying breakout conditions and trend acceleration points.
█ Bollinger Band-Based Reset
A reset occurs when price closes above the upper Bollinger Band or below the lower Bollinger Band, signaling potential overextension.
⚪ Interpretation & Insights
Best for traders looking for volatility-based trend shifts.
Higher Bollinger Band multiplier (k = 2.5+): Captures only major price extremes.
Lower Bollinger Band multiplier (k = 1.5): Resets on moderate volatility changes.
Useful for detecting overextensions in strong trends before potential retracements.
█ MACD-Based Reset
A reset occurs when the MACD line crosses the signal line, indicating a momentum shift.
⚪ Interpretation & Insights
Best for momentum traders looking for trend continuation vs. exhaustion signals.
Longer MACD lengths (260, 120, 90): Captures major trend shifts.
Shorter MACD lengths (10, 5, 3): Reacts quickly to momentum changes.
Useful for detecting strong divergences and market shifts.
█ Stochastic-Based Reset
A reset occurs when Stochastic %K crosses overbought or oversold levels.
⚪ Interpretation & Insights
Best for short-term traders looking for fast momentum shifts.
Longer Stochastic length: Filters out false signals.
Shorter Stochastic length: Captures quick intraday shifts.
█ CCI-Based Reset
A reset occurs when the Commodity Channel Index (CCI) crosses predefined overbought or oversold levels. The CCI measures the price deviation from its statistical mean, making it a useful tool for detecting overextensions in price action.
⚪ Interpretation & Insights
Best for cycle traders who aim to identify overextended price deviations in trending or ranging markets.
Higher CCI threshold (e.g., ±200): Detects extreme overbought/oversold conditions before reversals.
Lower CCI threshold (e.g., ±10): More sensitive to trend shifts, useful for early signal detection.
Ideal for detecting momentum shifts before price reverts to its mean or continues trending strongly.
█ Momentum-Based Reset
A reset occurs when Momentum (Rate of Change) crosses zero, indicating a potential shift in price direction.
⚪ Interpretation & Insights
Best for trend-following traders who want to track acceleration vs. deceleration.
Higher momentum length: Captures longer-term shifts.
Lower momentum length: More responsive to short-term trend changes.
█ How to Interpret the Trend Strength Table
The Trend Strength Table provides valuable insights into the current market conditions by tracking how the dynamic moving average is adjusting based on trend persistence. Each metric in the table plays a role in understanding the strength, longevity, and stability of a trend.
⚪ Counter Value
Represents the current length of trend persistence before a reset occurs.
The higher the counter, the longer the current trend has been in place without resetting.
When this value reaches the Counter Break Threshold, the moving average resets and contracts to become more reactive.
Example:
A low counter value (e.g., 10) suggests a recent trend reset, meaning the market might be changing directions frequently.
A high counter value (e.g., 495) means the trend has been ongoing for a long time, indicating strong trend persistence.
⚪ Trend Strength
Measures how strong the current trend is based on the trend confirmation logic.
Higher values indicate stronger trends, while lower values suggest weaker trends or consolidations.
This value is dynamic and updates based on price action.
Example:
Trend Strength of 760 → Indicates a high-confidence trend.
Trend Strength of 50 → Suggests weak price action, possibly a choppy market.
⚪ Highest Trend Score
Tracks the strongest trend score recorded during the session.
Helps traders identify the most dominant trend observed in the timeframe.
This metric is useful for analyzing historical trend strength and comparing it with current conditions.
Example:
Highest Trend Score = 760 → Suggests that at some point, there was a strong trend in play.
If the current trend strength is much lower than this value, it could indicate trend exhaustion.
⚪ Average Trend Score
This is a rolling average of trend strength across the session.
Provides a bigger picture of how the trend strength fluctuates over time.
If the average trend score is high, the market has had persistent trends.
If it's low, the market may have been choppy or sideways.
Example:
Average Trend Score of 147 vs. Current Trend Strength of 760 → Indicates that the current trend is significantly stronger than the historical average, meaning a breakout might be occurring.
Average Trend Score of 700+ → Suggests a strong trending market overall.
█ Settings
⚪ Dynamic MA Controls
Base MA Length – Sets the starting length of the moving average before dynamic adjustments.
Max Dynamic Length – Defines the upper limit for how much the moving average can expand.
Trend Confirmation Length – The number of bars required to validate an uptrend or downtrend.
⚪ Reset & Adaptive Conditions
Reset Condition Type – Choose what triggers the moving average reset (Slope, RSI, Volume, MACD, etc.).
Trend Smoothing Factor – Adjusts how smoothly the moving average responds to price changes.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
[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.
