Guppy MMA 3, 5, 8, 10, 12, 15 and 30, 35, 40, 45, 50, 60Guppy Multiple Moving Average
Short Term EMA 3, 5, 8, 10, 12, 15
Long Term EMA 30, 35, 40, 45, 50, 60
Use for SFTS Class
在腳本中搜尋"12月4号是什么星座"
12&50 RSI + %R2/50 RSI+ %R is a PineScript indicator that combines two popular technical indicators, the Relative Strength Index (RSI) and the Williams %R. The indicator plots two lines, K and D, which represent the smoothed moving averages of the RSI. It also plots the RSI with a 60-period length and the Williams %R with a 21-period length. The indicator can be used to identify overbought and oversold conditions, as well as potential reversals.
Here are some of the key features of the script:
It uses two different RSI lengths to provide a more comprehensive view of the market.
It plots the Williams %R, which can be used to identify overbought and oversold conditions.
It includes overbought and oversold levels to help traders identify potential entry and exit points.
Real Trading Hours - Vertical Lines - Mark RTH for Futures 12/Jan/2021 09:15 AM AUTHOR: Brandon Gum
--
Updated script to plot vertical lines for open and close of futures.
Not sure why the 8:30 and 15:00 times had to be used over 9:30 or 16:00
Only plots for products of type futures. - Could be easily expanded to work with cryptos as well if you wanted.
======================
NY ORB - Full Dynamic SystemNY ORB - Full Dynamic Strategy Summary
1. Opening Range and Session Timing
Opening Range (ORB) Calculation: The strategy identifies the ORB High and ORB Low by tracking the highest high and lowest low during the specified New York pre-market window, which is set by default from 8:30 to 8:45 (New York time).
Entry Window: Trading activity is restricted to a specific entry period, typically starting shortly after the ORB is established (default: 8:50 to 12:00).
Hard Exit Time: Any remaining open positions are automatically closed at a fixed exit time (default: 13:25).
2. Trade Entry Logic and Filters
An entry (Long or Short) is generated when the price breaks out of the established ORB, provided it passes a series of optional filters:
Direction Control: The user can restrict the strategy to trade Long Only, Short Only, or Both.
Second Breakout Logic: An optional filter that requires the price to break out, reverse back into the range, and then break out again, confirming momentum after a consolidation.
Confirmation Candle Count: An optional filter that checks the close of a previous candle (e.g., 1 or 2 candles ago) to ensure the price was still inside the range, preventing premature entry.
Technical Filters (Optional): The entry is only executed if it aligns with selected indicators:
RSI: Filters for non-overbought (Long) or non-oversold (Short) conditions.
MACD: Requires the MACD line to be above/below the Signal line for alignment.
VWAP: Requires the price to be above/below the Volume-Weighted Average Price.
Trend Filter (SMMA): Requires the price to be above/below a 50-period Simple Moving Average.
3. Dynamic Risk and Exit Management
This strategy features highly configurable stop-loss and profit-taking mechanics:
Primary Stop Loss Methods: The Stop Loss distance can be dynamically chosen from four types:
Fixed: A fixed number of ticks.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR-based, but with a hard maximum tick limit.
OR-Based: Based on a multiple of the actual ORB High-to-Low range.
Dynamic Profit Target: The Take Profit level is calculated dynamically based on a multiplier of either the ATR or the ORB Range.
Breakeven Stop:
If enabled, the Stop Loss automatically moves to the entry price (Breakeven) once the price moves a predetermined distance in the profitable direction.
An Adaptive Breakeven option allows the trigger distance to be calculated as a percentage of the overall ATR Profit Target.
Trailing Stop: The strategy uses a trailing stop, which can be custom-set (fixed ticks) or dynamically tied to the ATR. An optional feature Auto Tighten Trailing reduces the trailing multiplier once the breakeven level is hit.
MA Cross Exit: An alternative, counter-trend exit mechanism that closes the trade if the price crosses back over the chosen Moving Average (either SMMA or VWAP), overriding the pending profit target.
4. Daily Account Management
The strategy includes crucial daily risk controls to protect capital and lock in profits:
Daily Profit Limit: If the total daily PnL (realized and unrealized) hits a predefined maximum profit threshold (in ticks), all trades are closed, and new entries are blocked for the remainder of the trading day.
Daily Loss Limit: Conversely, if the total daily PnL hits a predefined maximum loss threshold, all trades are closed, and new entries are blocked for the remainder of the day.
Trailing 12M % Gain/Lossthis script shows profit or loss for training 12 months, works only on daily time frame
LA - EMA Bands with MTF DashboardDetailed Explanation of the LA - EMA Bands with MTF Dashboard Indicator
This custom Pine Script v6 indicator, designed for Trading View, overlays EMA-based price channels on the chart while incorporating a multi-timeframe (MTF) dashboard for broader market context. It focuses on visualizing trend direction and momentum through three sets of EMA bands, each representing different time horizons, and extends this with a tabular dashboard that summarizes signals across user-selected timeframes. The bands help identify support, resistance, and trend shifts, while the dashboard provides at-a-glance alignment across multiple periods, aiding in confirming trades or spotting divergences. Unlike volatility-based channels (e.g., Bollinger or Keltner), it relies solely on EMAs for simplicity and lag-reduced responsiveness.
Inputs Section
The script begins with user-configurable options grouped for ease. A timeframe input allows specifying a resolution for the EMA bands' data fetching, defaulting to the chart's timeframe if left empty—this enables higher-timeframe overlays on lower charts for context.
Next, a shared source input defines the price data for all midlines, defaulting to the midpoint of high and low (hl2) but customizable to close, open, or others.
The EMA bands have dedicated toggles and length inputs for each of the three sets: the first (long-term) defaults to 144 periods, the second (medium-term) to 72, and the third (short-term) to 12. These are inlined for compact settings panels, with minimum lengths of 1 to prevent errors.
A boolean toggle controls the visibility of the MTF dashboard. Following this are nine pairs of inputs for dashboard timeframes: each pair includes a show/hide toggle and an editable timeframe string (e.g., '1' for 1-minute, 'D' for daily). Defaults progress from short (1, 3, 5 minutes) to longer (15, 30, 60 minutes, daily, weekly, monthly), grouped in inlines for organization. Only enabled and non-empty timeframes appear in the dashboard.
Helpers Section
Two utility functions are defined here. The first computes an EMA on any source series over a specified length using Trading View's built-in function, reused throughout for midlines and bands.
The second function generates a signal string ("B" for buy/bullish, "S" for sell/bearish, or "-" for neutral) based on the direction of an EMA applied to high prices. It compares the current EMA value to the previous one, mirroring the band fill logic for consistency in the dashboard.
Core Components per Band Set:
Midline: An EMA calculated on a user-selectable source price (default: hl2, which is the midpoint between high and low prices). This acts as the central trend line.
Upper Band: An EMA applied directly to the high prices of each bar.
Lower Band: An EMA applied to the low prices of each bar.
These form a channel that captures the smoothed range of price action, highlighting potential support (lower band), resistance (upper band), and overall trend direction (midline).
Multiple Band Sets: The indicator includes three independent EMA band sets, each with its own length parameter for customization:
EMA1 (default length: 144) – Focuses on long-term trends.
EMA2 (default length: 72) – Targets medium-term trends.
EMA3 (default length: 12) – Emphasizes short-term momentum.
Each set can be toggled on or off via input checkboxes, allowing users to reduce chart clutter if needed.
Visual Elements:
Midline Plot: Displayed as a line colored based on its direction compared to the previous bar: green for rising (bullish), red for falling (bearish), and black for neutral (flat).
Band Fill: The area between the upper and lower bands is filled with a semi-transparent color indicating the trend of the upper band: light green for rising (suggesting expanding highs/upward momentum) and light pink for falling (contracting highs/downward pressure). The bands themselves are plotted in blue with a thin linewidth.
Multi-Timeframe Support: Users can input a custom timeframe (e.g., 'D' for daily), and the indicator fetches data from that resolution. This enables higher-timeframe context on lower-timeframe charts, such as viewing daily EMA bands on a 1-hour chart.
Calculation Mechanics:
All EMAs are computed using Trading View's built-in ta.ema() function.
Data is retrieved in a single request.security() call for efficiency, with lookahead enabled to avoid repainting.
No multipliers or volatility adjustments are included, making it a simple EMA-based envelope rather than a true volatility channel.
In practice, this indicator helps traders identify trend strength, potential breakouts (price crossing bands), or mean-reversion opportunities (price bouncing within bands). It's particularly useful for swing or position trading where multi-period alignment (e.g., all midlines green) signals conviction.
Pros
Multi-Period Insight: By combining short (12), medium (72), and long (144) periods, it offers a layered view of trends across time horizons, helping confirm alignments or divergences without needing multiple separate indicators.
Visual Clarity: Color-coded trends and fills make it easy to spot bullish/bearish shifts at a glance, reducing analysis time.
Flexibility: Custom timeframe input allows for multi-timeframe analysis, while shared source and toggles provide user control.
Simplicity and Efficiency: Purely EMA-based, it's computationally light and avoids overcomplication, making it accessible for beginners while still useful for spotting channel-based setups like squeezes or expansions.
No Repainting: With lookahead, plots are stable once bars close.
Cons
Lagging Nature: EMAs inherently lag price action, especially longer ones like 144-period, which may cause delayed signals in fast-moving or ranging markets.
Lack of Volatility Adjustment: Unlike Keltner Channels or Bollinger Bands, it doesn't incorporate ATR or standard deviation, so bands may not accurately reflect true volatility—potentially leading to false breakouts in high-volatility environments.
Chart Clutter: Displaying all three band sets simultaneously can overcrowd the chart, particularly on lower timeframes or volatile assets.
Subjective Interpretation: Color changes and band interactions require trader discretion; there's no built-in alerting or quantitative signals, which might lead to inconsistent results.
Market Dependency: Defaults may not suit all assets (e.g., stocks vs. crypto); shorter periods like 12 could whipsaw in noisy markets, while 144 might be too slow for intraday trading.
Justification for Default Values (12, 72, and 144)
The default lengths of 12, 72, and 144 are not arbitrary but draw from established trading principles, particularly W.D. Gann's geometric and numerical theories, as well as Fibonacci sequences, to create a harmonic progression for short-, medium-, and long-term analysis. Here's the rationale:
12 (Short-Term): This is a common period for capturing recent momentum in technical indicators, often seen in setups like the MACD (which uses 12- and 26-day EMAs). It aligns with natural cycles, such as the 12 months in a year, and in Gann theory, 12 serves as a base unit for squaring price and time (e.g., in the "Square of 12" where multiples like 12, 24, etc., measure cycles in days, weeks, or months). At 12 periods, the EMA reacts quickly to price changes without excessive noise, making it ideal for short-term trend detection.
72 (Medium-Term): This acts as an intermediate bridge, derived from Gann's divisions of the 360-degree circle (a key Gann concept representing a full cycle). Specifically, 72 is 360/5 (relating to pentagonal geometry and natural harmonics) and appears in Gann's time cycle measurements (e.g., as a multiple in the Square of 12: 12×6=72). It's roughly half of 144, providing a balanced midpoint for medium-term trends without overlapping too closely with the others. In practice, 72 periods smooth out short-term fluctuations while still responding to developing trends.
144 (Long-Term): This is a powerhouse number in trading lore, being both 12 squared (12×12=144, central to Gann's "Square of 144" for monthly charts and major cycle turns, as there are 12 months in a year) and a Fibonacci sequence value (1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144...). Fibonacci periods are popular in moving averages for their alignment with natural growth patterns in markets, and 144 is often used for long-term regime definition (e.g., confirming trends over 144 bars). It helps identify major support/resistance in extended cycles.
Overall, these values form a geometric/harmonic series (12, 72=12×6, 144=12×12), promoting alignment with market cycles as per Gann and Fibonacci principles, rather than generic lengths like 50 or 200. They can be adjusted based on the asset or timeframe, but the defaults provide a starting point rooted in time-tested trading numerology for balanced multi-period analysis.
Please use this along with other indicators (eg. Pivot, MACD, etc) for better results.
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
My exponential moving averages - Suri's EMAs
It's not an indication of anything here, it's just part of my operating in a simple and summarized way, I hope it helps someone.
Suri's EMA's indicator is nothing more than a set of exponential moving averages (EMA). They are 12, 26, 50 and 200.
Attention to the use of the indicator, it is just an INDICATOR, it should not be taken as the main point of your entry, but to guide you in your entries in favor of the trend, whether intra-day or swing.
Created for clear, monochrome screens. Make your adjustments.
Color condition, candles turn green when their close is above EMA 12 and 26.
Color condition, candles turn red when their close is below EMA 12 and 26.
Condition for colors, MME12,26,50 and 200 will turn green with price working above it.
Condition for colors, MME12, 26, 50 and 200 will turn red with price working below it.
Indication for use in time-frames = 5m, 15m, 60m, 240m. (higher hit rates)
How to use the indicator, MME 12 and 26, are the most important and led you to more entries, but we should not only consider them, we have to analyze the whole context to then make a decision.
Indicator was nicknamed by me by "Pullback Pick", it works in a simple way:
In an uptrend or downtrend, the price usually tends to return in the averages or the averages go up to the price, that being said, it is easy to observe that where the price returns would be a pullback from the last movement, so when returning to the averages, the candle that shows strength in favor of this trend, in the EMA's region, becomes a possible entry, with its stop below or above this "pullback" formed, because the stop goes there, because usually when the price returns on the EMAs they tend to to hold and replay the price in favor of the trend.
My observations:
I like to enter when the price returns to the averages smoothly, without much movement, when it touches the average 12 or 26 it is an entry, but an entry without confirmation, the gain is greater, but the chance of being stopped is higher, I like it when the price is close to the 12 and 26 averages and leaves a small candle or doji on this pullback, my entry goes to the breakout of this candle and the stop behind the candle.
THERE IS NO MIRACLE, THERE IS NO 100% HIT RATE, SO USE STOP.
Aaaaaaaaaa I was forgetting.... and the target???
As it is a trend following setup, it is cool to leave a trailing stop or update the stop as new bottoms or tops are formed.
Targeting in 1v1 is good, setup pays a lot!
Targeting in 2x1 is too good, setup pays well!
Making a target in 3x1 is more than good, setup pays sometimes, then from now on, it depends on where you are entering this "PULLBACK", if it is in the first wave, in the second, if you are going to lateralize, the market is SOVEREIGN, put in the pocket that is no longer on the market, oh it's yours!
That's it, doubts, send it there, suggestion, opinion, whatever you want.
Added a symbol at the crossing of the 12 and 26 moving averages.
I am so sorry, but i dont speak english, use google translate.
Português.
Não se trata de indicação de nada aqui, é apenas parte do meu operacional de maneira simples e resumida, espero que ajude alguém.
Indicador Suri's EMA's, nada mais é do que um conjunto de médias móveis exponenciais(MME). São elas 12, 26, 50 e 200.
Atenção para o uso do indicador, ele é apenas um INDICADOR, não deve ser tomado como o ponto principal de sua entrada, mas sim de te balizar nas suas entradas a favor da tendência, seja ela intra-day ou swing.
Criado para telas claras e monocromáticas. Façam seus ajustes.
Condição para as cores, candles ficam verdes quando o fechamento dele é acima das MME 12 e 26.
Condição para as cores, candles ficam vermelhos quando o fechamento dele é abaixo das MME 12 e 26.
Condição para as cores, MME12,26,50 e 200 ficará verde com preço trabalhando acima dela.
Condição para as cores, MME12, 26, 50 e 200 ficará vermelho com preço trabalhando abaixo dela.
Indicação para uso nos time-frame = 5m, 15m, 60m, 240m.(taxas de acerto maior)
Como utilizar o indicador, MME 12 e 26, são as mais importantes e te levaram a mais entradas, porém não devemos levar apenas elas em consideração, temos que analisar todo o contexto para então tomar decisão.
Indicador foi apelidado por mim por " Pega Pullback", ele funciona de uma maneira simples:
Em tendência de alta ou de baixa, o preço geralmente tende a retornar nas médias ou as médias irem até o preço, dito isso é fácil de se observar que onde o preço retorna seria um pullback do último movimento, portanto ao retornar nas médias, o candle que mostra força a favor dessa tendência, na região das EMA's, se torna uma possível entrada, com o seu stop abaixo ou acima desse "pullback" formado, porque o stop vai nesse local, porque geralmente quando o preço retorna nas EMAs elas tendem a segurar e voltar a jogar o preço a favor da tendência.
Minhas observações:
Eu gosto de entrar quando o preço retorna nas médias de maneira suave, sem muito movimento, quando toca na média 12 ou 26 é uma entrada, porém uma entrada sem confirmação, o ganho é maior, porém a chance de ser stopado é mais alta, eu gosto quando o preço fica perto das médias 12 e 26 e deixa um candle pequeno ou doji nesse pullback, minha entrada vai no rompimento desse candle e o stop atrás do candle.
Não existe MILAGRE, NÃO EXISTE TAXA DE ACERTO DE 100%, POR ISSO USE STOP.
Aaaaaaaaaa ia me esquecendo.... e o alvo???
Por ser um setup seguidor de tendência, o legal é deixar um trailing stop ou ir atualizando o stop conforme novos fundos ou topos são formados.
Realizar alvo no 1x1 é bom, setup paga muito!
Realizar alvo no 2x1 é bom de mais, setup paga bem!
Realizar alvo no 3x1 é mais do que bom, setup paga as vezes, ai daqui pra frente, depende de onde você está entrando nesse "PULLBACK", se é na primeira onda, na segunda, se vai lateralizar, o mercado é SOBERANO, põe no bolso que não é mais do mercado, ai é teu!
É isso, dúvidas, manda ai, sugestão, opinião, o que quiser.
Adicionado um símbolo no cruzamento das médias móveis 12 e 26.
Ripster Labels + Air Gaps (v6)What it shows (on one chart)
EMA Clouds (current timeframe)
Plots EMA 8/12/21/34/50/200 with three cloud fills:
12–21 = “fast” cloud
34–50 = “mid” cloud
50–200 = “base” cloud
Cloud color: green when the faster EMA is above the slower (bullish), red/maroon/orange when below (bearish).
Toggle lines vs. clouds via A) EMA Clouds settings.
MTF Rails (higher-TF EMAs)
For three higher timeframes (defaults 30m / 60m / 240m), draws two EMAs each (defaults 34 & 50).
These are stepline-like rails you can visually use as higher-TF supports/resistances.
Configure in B) MTF Rails (turn on/off, change TFs/lengths/colors).
Relative Volume Box (RVol)
Small table (top-center) showing:
Candle Vol (formatted K/M/B if enabled)
RVol = current bar volume / SMA 20 of volume (as a %)
Color scale: blue (<100%), yellow (100–150%), red (>150%).
Settings in C) RVol Box.
DTR vs ATR Box
Daily True Range (DTR = day high − day low) vs ATR(14) on the daily timeframe, with DTR as % of ATR.
Placed at top-right; toggle in D) DTR/ATR Box.
Ripster Trend Label (10m 12/50)
Looks at a separate timeframe (default 10m): EMA 12 vs EMA 50.
Bottom-right table cell shows “10m Trend ↑/↓/Sideways” (green/red/gray).
Configure in E) Ripster Trend Labels (TF and lengths).
Air Gaps (single EMA per TF)
Three horizontal, auto-extending lines showing an EMA from 30m / 60m / 240m (default length 12).
“Air gaps” are the price spaces between these lines—often lighter-resistance zones for price.
Start point logic:
All Bars = draw from the chart’s left
Start of Day = draw from today’s first bar
Bars Offset = draw from N bars back (default 100)
Settings in F) Air Gaps (TFs, length, draw-from, bars-back).
Inputs & where to tweak
A) EMA Clouds
Show EMA Clouds: master toggle
Source: close (default)
Lengths: 8/12/21/34/50/200
Show EMA lines: toggle plotted lines (clouds remain)
B) MTF Rails
Show MTF Rails
TF1/TF2/TF3 (defaults 30/60/240)
EMA A/B (defaults 34/50)
C) RVol Box
Show box
Format as K/M/B: K=1e3, M=1e6, B=1e9
D) DTR/ATR Box
Show DTR/ATR
ATR len: default 14 (daily)
E) Ripster Trend Labels
Show labels
Trend TF: default 10 (10-minute)
Trend EMA Fast/Slow: default 12/50
F) Air Gaps
Show Air Gap lines
TF1/TF2/TF3 (30/60/240)
EMA length: default 12
Draw from: All Bars | Start of Day | Bars Offset
Bars back: used if Draw from = Bars Offset
How it makes decisions
Cloud bias = sign of (faster EMA − slower EMA) for each cloud pair.
Example: 12>21 → fast cloud is bullish (green); 34>50 → mid cloud bullish (teal).
10m trend label = sign of (EMA12−EMA50) on the Trend TF (default 10m).
RVol = volume / sma(volume, 20); formatted as a percent and color-coded.
Practical read of the screen
Fast cloud flips (12/21) often mark short-term momentum changes; mid cloud flips (34/50) reflect swing bias.
Air Gap lines from higher TFs frequently act as support/resistance. Larger spaces between lines = “air gaps” where price can move with less friction.
RVol color tells you how “real” a move is: red/yellow often confirms momentum; blue warns of thin/liquidy bars.
DTR vs ATR shows if today’s range is stretched vs recent norm.
Design choices (why your prior errors are gone)
Removed multiline ?: chains → replaced by if/else (Pine v6 is picky about line continuations).
Moved fill() calls outside of local if blocks (Pine limitation).
ta.change(time("D")) != 0 makes the if condition boolean.
Declared G_drawFrom / G_barsBack before startX() so identifiers exist.
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Range Bar Gaps DetectorRange Bar Gaps Detector
Overview
The Range Bar Gaps Detector identifies price gaps across multiple range bar sizes (12, 24, 60, and 120) on any trading instrument, helping traders spot potential support/resistance zones or breakout opportunities. Designed for Pine Script v6, this indicator detects gaps on range bars and exports data for use in companion scripts like Range Bar Gaps Overlap, making it ideal for multi-timeframe gap analysis.
Key Features
Multi-Range Gap Detection: Identifies gaps on 12, 24, 60, and 120-range bars, capturing both bullish (gap up) and bearish (gap down) price movements.
Customizable Sensitivity: Includes a user-defined minimum deviation (default: 10% of 14-period SMA) for 12-range gaps to filter out noise.
7-Day Lookback: Automatically prunes gaps older than 7 days to focus on recent, relevant price levels.
Data Export: Serializes up to 10 gaps per range (tops, bottoms, start bars, highest/lowest prices, and age) for seamless integration with overlap analysis scripts.
Debugging Support: Plots gap counts and aggregation data in the Data Window for easy verification of detected gaps.
How It Works
The indicator aggregates price movements to simulate higher range bars (24, 60, 120) from a base range bar chart. It detects gaps when the price jumps significantly between bars, ensuring gaps meet the minimum deviation threshold for 12-range bars. Gaps are stored in arrays, serialized for external use, and pruned after 7 days to maintain efficiency.
Usage
Add to your range bar chart (e.g., 12-range) to detect gaps across multiple ranges.
Use alongside the Range Bar Gaps Overlap indicator to visualize gaps and their overlaps as boxes on the chart.
Check the Data Window to confirm gap counts and sizes for each range (12, 24, 60, 120).
Adjust the "Minimal Deviation (%) for 12-Range" input to control gap detection sensitivity.
Settings
Minimal Deviation (%) for 12-Range: Set the minimum gap size for 12-range bars (default: 10% of 14-period SMA).
Range Sizes: Fixed at 24, 60, and 120 for higher range bar aggregation.
Notes
Ensure the script is published under your TradingView username (e.g., GreenArrow2005) for use with companion scripts.
Best used on range bar charts to maintain consistent gap detection.
For advanced overlap analysis, pair with the Range Bar Gaps Overlap indicator to highlight zones where gaps from different ranges align.
Ideal For
Traders seeking to identify key price levels for support/resistance or breakout strategies.
Multi-timeframe analysts combining gap data across various range bar sizes.
Developers building custom indicators that leverage gap data for advanced charting.
2:30 [LuciTech]this is a technical analysis tool designed to highlight key price levels and patterns during a specific trading window, based on UK time (Europe/London). It overlays visual elements on the chart, including a 12 PM reference line, Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) levels, a highlighted 2:30 PM candle, and Engulfing Fair Value Gaps (FVGs). This indicator is intended for traders who focus on intraday price action and liquidity zones.
Features
The 12 PM Line displays a vertical line at 12:00 PM (UK time) to mark the start of the session. It’s customizable, allowing you to enable or disable it and adjust its color.
BSL/SSL Lines track the highest high (BSL) and lowest low (SSL) from 12:00 PM to 2:00 PM (UK time). These lines extend horizontally until 3:30 PM, after which they remain static at their last recorded levels. You can customize them by enabling or disabling visibility, adjusting colors, choosing a line style (solid, dashed, or dotted), and setting the width.
The 2:30 PM Candle highlights the candle at 2:30 PM (UK time) with a distinct color. It’s customizable, with options to enable or disable it and change its color.
Engulfing FVG (Fair Value Gap) identifies bullish and bearish engulfing patterns with a gap from the prior candle’s range. It draws a shaded box over the FVG area, and you can customize it by enabling or disabling it and adjusting the box color.
How It Works
The indicator operates within a session starting at 12:00 PM (UK time). BSL/SSL levels update between 12:00 PM and 2:00 PM, with lines extending until 3:30 PM. After 3:30 PM, these lines freeze.
BSL/SSL lines show the highest price (BSL) and lowest price (SSL) reached during the 12:00 PM to 2:00 PM window. After 3:30 PM, they remain static, marking the final range boundaries.
The 2:30 PM candle emphasizes a key timestamp, often of interest to intraday traders.
Engulfing FVGs detect significant price gaps created by engulfing candles, which may indicate potential reversal or continuation zones.
Settings
12 PM Line Settings let you toggle visibility and set the line color.
BSL/SSL Line Settings allow you to toggle visibility, set BSL and SSL colors, choose a line style (Solid, Dashed, Dotted), and adjust width (1-4).
2:30 Candle Settings let you toggle visibility and set the candle color.
Engulfing FVG Settings allow you to toggle visibility and set the box color.
Interpretation
The 12 PM Line serves as a reference for the session start.
BSL/SSL Lines may act as potential support or resistance zones or highlight liquidity areas. After 3:30 PM, they remain static, showing the session’s final range.
The 2:30 PM Candle can be monitored for price action signals, such as reversals or breakouts.
Engulfing FVGs shaded areas may indicate imbalances in supply and demand, useful for identifying trade opportunities or stop-loss placement.
Notes
The timezone is set to Europe/London (UK time). Ensure your chart’s timezone aligns for accurate results.
This indicator is best used on intraday timeframes, such as 1-minute or 5-minute charts.
It provides visual aids for analysis and does not generate buy or sell signals on its own.
Universal Global SessionUniversal Global Session
This Script combines the world sessions of: Stocks, Forex, Bitcoin Kill Zones, strategic points, all configurable, in a single Script, to capitalize the opening and closing times of global exchanges as investment assets, becoming an Universal Global Session .
It is based on the great work of @oscarvs ( BITCOIN KILL ZONES v2 ) and the scripts of @ChrisMoody. Thank you Oscar and Chris for your excellent judgment and great work.
At the end of this writing you can find all the internet references of the extensive documentation that I present here. To maximize your benefits in the use of this Script, I recommend that you read the entire document to create an objective and practical criterion.
All the hours of the different exchanges are presented at GMT -6. In Market24hClock you can adjust it to your preferences.
After a deep investigation I have been able to show that the different world sessions reveal underlying investment cycles, where it is possible to find sustained changes in the nominal behavior of the trend before the passage from one session to another and in the natural overlaps between the sessions. These underlying movements generally occur 15 minutes before the start, close or overlap of the session, when the session properly starts and also 15 minutes after respectively. Therefore, this script is designed to highlight these particular trending behaviors. Try it, discover your own conclusions and let me know in the notes, thank you.
Foreign Exchange Market Hours
It is the schedule by which currency market participants can buy, sell, trade and speculate on currencies all over the world. It is open 24 hours a day during working days and closes on weekends, thanks to the fact that operations are carried out through a network of information systems, instead of physical exchanges that close at a certain time. It opens Monday morning at 8 am local time in Sydney —Australia— (which is equivalent to Sunday night at 7 pm, in New York City —United States—, according to Eastern Standard Time), and It closes at 5pm local time in New York City (which is equivalent to 6am Saturday morning in Sydney).
The Forex market is decentralized and driven by local sessions, where the hours of Forex trading are based on the opening range of each active country, becoming an efficient transfer mechanism for all participants. Four territories in particular stand out: Sydney, Tokyo, London and New York, where the highest volume of operations occurs when the sessions in London and New York overlap. Furthermore, Europe is complemented by major financial centers such as Paris, Frankfurt and Zurich. Each day of forex trading begins with the opening of Australia, then Asia, followed by Europe, and finally North America. As markets in one region close, another opens - or has already opened - and continues to trade in the currency market. The seven most traded currencies in the world are: the US dollar, the euro, the Japanese yen, the British pound, the Australian dollar, the Canadian dollar, and the New Zealand dollar.
Currencies are needed around the world for international trade, this means that operations are not dominated by a single exchange market, but rather involve a global network of brokers from around the world, such as banks, commercial companies, central banks, companies investment management, hedge funds, as well as retail forex brokers and global investors. Because this market operates in multiple time zones, it can be accessed at any time except during the weekend, therefore, there is continuously at least one open market and there are some hours of overlap between the closing of the market of one region and the opening of another. The international scope of currency trading means that there are always traders around the world making and satisfying demands for a particular currency.
The market involves a global network of exchanges and brokers from around the world, although time zones overlap, the generally accepted time zone for each region is as follows:
Sydney 5pm to 2am EST (10pm to 7am UTC)
London 3am to 12 noon EST (8pm to 5pm UTC)
New York 8am to 5pm EST (1pm to 10pm UTC)
Tokyo 7pm to 4am EST (12am to 9am UTC)
Trading Session
A financial asset trading session refers to a period of time that coincides with the daytime trading hours for a given location, it is a business day in the local financial market. This may vary according to the asset class and the country, therefore operators must know the hours of trading sessions for the securities and derivatives in which they are interested in trading. If investors can understand market hours and set proper targets, they will have a much greater chance of making a profit within a workable schedule.
Kill Zones
Kill zones are highly liquid events. Many different market participants often come together and perform around these events. The activity itself can be event-driven (margin calls or option exercise-related activity), portfolio management-driven (asset allocation rebalancing orders and closing buy-in), or institutionally driven (larger players needing liquidity to complete the size) or a combination of any of the three. This intense cross-current of activity at a very specific point in time often occurs near significant technical levels and the established trends emerging from these events often persist until the next Death Zone approaches or enters.
Kill Zones are evolving with time and the course of world history. Since the end of World War II, New York has slowly invaded London's place as the world center for commercial banking. So much so that during the latter part of the 20th century, New York was considered the new center of the financial universe. With the end of the cold war, that leadership appears to have shifted towards Europe and away from the United States. Furthermore, Japan has slowly lost its former dominance in the global economic landscape, while Beijing's has increased dramatically. Only time will tell how these death zones will evolve given the ever-changing political, economic, and socioeconomic influences of each region.
Financial Markets
New York
New York (NYSE Chicago, NASDAQ)
7:30 am - 2:00 pm
It is the second largest currency platform in the world, followed largely by foreign investors as it participates in 90% of all operations, where movements on the New York Stock Exchange (NYSE) can have an immediate effect (powerful) on the dollar, for example, when companies merge and acquisitions are finalized, the dollar can instantly gain or lose value.
A. Complementary Stock Exchanges
Brazil (BOVESPA - Brazilian Stock Exchange)
07:00 am - 02:55 pm
Canada (TSX - Toronto Stock Exchange)
07:30 am - 02:00 pm
New York (NYSE - New York Stock Exchange)
08:30 am - 03:00 pm
B. North American Trading Session
07:00 am - 03:00 pm
(from the beginning of the business day on NYSE and NASDAQ, until the end of the New York session)
New York, Chicago and Toronto (Canada) open the North American session. Characterized by the most aggressive trading within the markets, currency pairs show high volatility. As the US markets open, trading is still active in Europe, however trading volume generally decreases with the end of the European session and the overlap between the US and Europe.
C. Strategic Points
US main session starts in 1 hour
07:30 am
The euro tends to drop before the US session. The NYSE, CHX and TSX (Canada) trading sessions begin 1 hour after this strategic point. The North American session begins trading Forex at 07:00 am.
This constitutes the beginning of the overlap of the United States and the European market that spans from 07:00 am to 10:35 am, often called the best time to trade EUR / USD, it is the period of greatest liquidity for the main European currencies since it is where they have their widest daily ranges.
When New York opens at 07:00 am the most intense trading begins in both the US and European markets. The overlap of European and American trading sessions has 80% of the total average trading range for all currency pairs during US business hours and 70% of the total average trading range for all currency pairs during European business hours. The intersection of the US and European sessions are the most volatile overlapping hours of all.
Influential news and data for the USD are released between 07:30 am and 09:00 am and play the biggest role in the North American Session. These are the strategically most important moments of this activity period: 07:00 am, 08:00 am and 08:30 am.
The main session of operations in the United States and Canada begins
08:30 am
Start of main trading sessions in New York, Chicago and Toronto. The European session still overlaps the North American session and this is the time for large-scale unpredictable trading. The United States leads the market. It is difficult to interpret the news due to speculation. Trends develop very quickly and it is difficult to identify them, however trends (especially for the euro), which have developed during the overlap, often turn the other way when Europe exits the market.
Second hour of the US session and last hour of the European session
09:30 am
End of the European session
10:35 am
The trend of the euro will change rapidly after the end of the European session.
Last hour of the United States session
02:00 pm
Institutional clients and very large funds are very active during the first and last working hours of almost all stock exchanges, knowing this allows to better predict price movements in the opening and closing of large markets. Within the last trading hours of the secondary market session, a pullback can often be seen in the EUR / USD that continues until the opening of the Tokyo session. Generally it happens if there was an upward price movement before 04:00 pm - 05:00 pm.
End of the trade session in the United States
03:00 pm
D. Kill Zones
11:30 am - 1:30 pm
New York Kill Zone. The United States is still the world's largest economy, so by default, the New York opening carries a lot of weight and often comes with a huge injection of liquidity. In fact, most of the world's marketable assets are priced in US dollars, making political and economic activity within this region even more important. Because it is relatively late in the world's trading day, this Death Zone often sees violent price swings within its first hour, leading to the proven adage "never trust the first hour of trading in America. North.
---------------
London
London (LSE - London Stock Exchange)
02:00 am - 10:35 am
Britain dominates the currency markets around the world, and London is its main component. London, a central trading capital of the world, accounts for about 43% of world trade, many Forex trends often originate from London.
A. Complementary Stock Exchange
Dubai (DFM - Dubai Financial Market)
12:00 am - 03:50 am
Moscow (MOEX - Moscow Exchange)
12:30 am - 10:00 am
Germany (FWB - Frankfurt Stock Exchange)
01:00 am - 10:30 am
Afríca (JSE - Johannesburg Stock Exchange)
01:00 am - 09:00 am
Saudi Arabia (TADAWUL - Saudi Stock Exchange)
01:00 am - 06:00 am
Switzerland (SIX - Swiss Stock Exchange)
02:00 am - 10:30 am
B. European Trading Session
02:00 am - 11:00 am
(from the opening of the Frankfurt session to the close of the Order Book on the London Stock Exchange / Euronext)
It is a very liquid trading session, where trends are set that start during the first trading hours in Europe and generally continue until the beginning of the US session.
C. Middle East Trading Session
12:00 am - 06:00 am
(from the opening of the Dubai session to the end of the Riyadh session)
D. Strategic Points
European session begins
02:00 am
London, Frankfurt and Zurich Stock Exchange enter the market, overlap between Europe and Asia begins.
End of the Singapore and Asia sessions
03:00 am
The euro rises almost immediately or an hour after Singapore exits the market.
Middle East Oil Markets Completion Process
05:00 am
Operations are ending in the European-Asian market, at which time Dubai, Qatar and in another hour in Riyadh, which constitute the Middle East oil markets, are closing. Because oil trading is done in US dollars, and the region with the trading day coming to an end no longer needs the dollar, consequently, the euro tends to grow more frequently.
End of the Middle East trading session
06:00 am
E. Kill Zones
5:00 am - 7:00 am
London Kill Zone. Considered the center of the financial universe for more than 500 years, Europe still has a lot of influence in the banking world. Many older players use the European session to establish their positions. As such, the London Open often sees the most significant trend-setting activity on any trading day. In fact, it has been suggested that 80% of all weekly trends are set through the London Kill Zone on Tuesday.
F. Kill Zones (close)
2:00 pm - 4:00 pm
London Kill Zone (close).
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Tokyo
Tokyo (JPX - Tokyo Stock Exchange)
06:00 pm - 12:00 am
It is the first Asian market to open, receiving most of the Asian trade, just ahead of Hong Kong and Singapore.
A. Complementary Stock Exchange
Singapore (SGX - Singapore Exchange)
07:00 pm - 03:00 am
Hong Kong (HKEx - Hong Kong Stock Exchange)
07:30 pm - 02:00 am
Shanghai (SSE - Shanghai Stock Exchange)
07:30 pm - 01:00 am
India (NSE - India National Stock Exchange)
09:45 pm - 04:00 am
B. Asian Trading Session
06:00 pm - 03:00 am
From the opening of the Tokyo session to the end of the Singapore session
The first major Asian market to open is Tokyo which has the largest market share and is the third largest Forex trading center in the world. Singapore opens in an hour, and then the Chinese markets: Shanghai and Hong Kong open 30 minutes later. With them, the trading volume increases and begins a large-scale operation in the Asia-Pacific region, offering more liquidity for the Asian-Pacific currencies and their crosses. When European countries open their doors, more liquidity will be offered to Asian and European crossings.
C. Strategic Points
Second hour of the Tokyo session
07:00 pm
This session also opens the Singapore market. The commercial dynamics grows in anticipation of the opening of the two largest Chinese markets in 30 minutes: Shanghai and Hong Kong, within these 30 minutes or just before the China session begins, the euro usually falls until the same moment of the opening of Shanghai and Hong Kong.
Second hour of the China session
08:30 pm
Hong Kong and Shanghai start trading and the euro usually grows for more than an hour. The EUR / USD pair mixes up as Asian exporters convert part of their earnings into both US dollars and euros.
Last hour of the Tokyo session
11:00 pm
End of the Tokyo session
12:00 am
If the euro has been actively declining up to this time, China will raise the euro after the Tokyo shutdown. Hong Kong, Shanghai and Singapore remain open and take matters into their own hands causing the growth of the euro. Asia is a huge commercial and industrial region with a large number of high-quality economic products and gigantic financial turnover, making the number of transactions on the stock exchanges huge during the Asian session. That is why traders, who entered the trade at the opening of the London session, should pay attention to their terminals when Asia exits the market.
End of the Shanghai session
01:00 am
The trade ends in Shanghai. This is the last trading hour of the Hong Kong session, during which market activity peaks.
D. Kill Zones
10:00 pm - 2:00 am
Asian Kill Zone. Considered the "Institutional" Zone, this zone represents both the launch pad for new trends as well as a recharge area for the post-American session. It is the beginning of a new day (or week) for the world and as such it makes sense that this zone often sets the tone for the remainder of the global business day. It is ideal to pay attention to the opening of Tokyo, Beijing and Sydney.
--------------
Sidney
Sydney (ASX - Australia Stock Exchange)
06:00 pm - 12:00 am
A. Complementary Stock Exchange
New Zealand (NZX - New Zealand Stock Exchange)
04:00 pm - 10:45 pm
It's where the global trading day officially begins. While it is the smallest of the megamarkets, it sees a lot of initial action when markets reopen Sunday afternoon as individual traders and financial institutions are trying to regroup after the long hiatus since Friday afternoon. On weekdays it constitutes the end of the current trading day where the change in the settlement date occurs.
B. Pacific Trading Session
04:00 pm - 12:00 am
(from the opening of the Wellington session to the end of the Sydney session)
Forex begins its business hours when Wellington (New Zealand Exchange) opens local time on Monday. Sydney (Australian Stock Exchange) opens in 2 hours. It is a session with a fairly low volatility, configuring itself as the calmest session of all. Strong movements appear when influential news is published and when the Pacific session overlaps the Asian Session.
C. Strategic Points
End of the Sydney session
12:00 am
---------------
Conclusions
The best time to trade is during overlaps in trading times between open markets. Overlaps equate to higher price ranges, creating greater opportunities.
Regarding press releases (news), it should be noted that these in the currency markets have the power to improve a normally slow trading period. When a major announcement is made regarding economic data, especially when it goes against the predicted forecast, the coin can lose or gain value in a matter of seconds. In general, the more economic growth a country produces, the more positive the economy is for international investors. Investment capital tends to flow to countries that are believed to have good growth prospects and subsequently good investment opportunities, leading to the strengthening of the country's exchange rate. Also, a country that has higher interest rates through its government bonds tends to attract investment capital as foreign investors seek high-yield opportunities. However, stable economic growth and attractive yields or interest rates are inextricably intertwined. It's important to take advantage of market overlaps and keep an eye out for press releases when setting up a trading schedule.
References:
www.investopedia.com
www.investopedia.com
www.investopedia.com
www.investopedia.com
market24hclock.com
market24hclock.com
RSI Full Forecast [Titans_Invest]RSI Full Forecast
Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast
Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market.
AI-Powered RSI Forecasting:
Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy.
But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis.
You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements.
See the Future, Now:
• Track upcoming RSI & RSI MA crossovers in advance.
• Identify potential reversal zones before price reacts.
• Uncover statistical behavior patterns that would normally go unnoticed.
40+ Intelligent Conditions:
The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic.
Full Customization:
All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions.
Innovative, Accurate, Unique:
This isn’t just an upgrade. It’s a quantum leap in technical analysis.
RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
_________________________________________________
Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
______________________________________________________
______________________________________________________
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔹 RSI (Crossover) MA Forecast
🔹 RSI (Crossunder) MA Forecast
🔹 RSI Forecast 1 > MA Forecast 1
🔹 RSI Forecast 1 < MA Forecast 1
🔹 RSI Forecast 2 > MA Forecast 2
🔹 RSI Forecast 2 < MA Forecast 2
🔹 RSI Forecast 3 > MA Forecast 3
🔹 RSI Forecast 3 < MA Forecast 3
🔹 RSI Forecast 4 > MA Forecast 4
🔹 RSI Forecast 4 < MA Forecast 4
🔹 RSI Forecast 5 > MA Forecast 5
🔹 RSI Forecast 5 < MA Forecast 5
🔹 RSI Forecast 6 > MA Forecast 6
🔹 RSI Forecast 6 < MA Forecast 6
🔹 RSI Forecast 7 > MA Forecast 7
🔹 RSI Forecast 7 < MA Forecast 7
🔹 RSI Forecast 8 > MA Forecast 8
🔹 RSI Forecast 8 < MA Forecast 8
🔹 RSI Forecast 9 > MA Forecast 9
🔹 RSI Forecast 9 < MA Forecast 9
🔹 RSI Forecast 10 > MA Forecast 10
🔹 RSI Forecast 10 < MA Forecast 10
🔹 RSI Forecast 11 > MA Forecast 11
🔹 RSI Forecast 11 < MA Forecast 11
🔹 RSI Forecast 12 > MA Forecast 12
🔹 RSI Forecast 12 < MA Forecast 12
🔹 RSI Forecast 13 > MA Forecast 13
🔹 RSI Forecast 13 < MA Forecast 13
🔹 RSI Forecast 14 > MA Forecast 14
🔹 RSI Forecast 14 < MA Forecast 14
🔹 RSI Forecast 15 > MA Forecast 15
🔹 RSI Forecast 15 < MA Forecast 15
🔹 RSI Forecast 16 > MA Forecast 16
🔹 RSI Forecast 16 < MA Forecast 16
🔹 RSI Forecast 17 > MA Forecast 17
🔹 RSI Forecast 17 < MA Forecast 17
🔹 RSI Forecast 18 > MA Forecast 18
🔹 RSI Forecast 18 < MA Forecast 18
🔹 RSI Forecast 19 > MA Forecast 19
🔹 RSI Forecast 19 < MA Forecast 19
🔹 RSI Forecast 20 > MA Forecast 20
🔹 RSI Forecast 20 < MA Forecast 20
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🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔸 RSI (Crossover) MA Forecast
🔸 RSI (Crossunder) MA Forecast
🔸 RSI Forecast 1 > MA Forecast 1
🔸 RSI Forecast 1 < MA Forecast 1
🔸 RSI Forecast 2 > MA Forecast 2
🔸 RSI Forecast 2 < MA Forecast 2
🔸 RSI Forecast 3 > MA Forecast 3
🔸 RSI Forecast 3 < MA Forecast 3
🔸 RSI Forecast 4 > MA Forecast 4
🔸 RSI Forecast 4 < MA Forecast 4
🔸 RSI Forecast 5 > MA Forecast 5
🔸 RSI Forecast 5 < MA Forecast 5
🔸 RSI Forecast 6 > MA Forecast 6
🔸 RSI Forecast 6 < MA Forecast 6
🔸 RSI Forecast 7 > MA Forecast 7
🔸 RSI Forecast 7 < MA Forecast 7
🔸 RSI Forecast 8 > MA Forecast 8
🔸 RSI Forecast 8 < MA Forecast 8
🔸 RSI Forecast 9 > MA Forecast 9
🔸 RSI Forecast 9 < MA Forecast 9
🔸 RSI Forecast 10 > MA Forecast 10
🔸 RSI Forecast 10 < MA Forecast 10
🔸 RSI Forecast 11 > MA Forecast 11
🔸 RSI Forecast 11 < MA Forecast 11
🔸 RSI Forecast 12 > MA Forecast 12
🔸 RSI Forecast 12 < MA Forecast 12
🔸 RSI Forecast 13 > MA Forecast 13
🔸 RSI Forecast 13 < MA Forecast 13
🔸 RSI Forecast 14 > MA Forecast 14
🔸 RSI Forecast 14 < MA Forecast 14
🔸 RSI Forecast 15 > MA Forecast 15
🔸 RSI Forecast 15 < MA Forecast 15
🔸 RSI Forecast 16 > MA Forecast 16
🔸 RSI Forecast 16 < MA Forecast 16
🔸 RSI Forecast 17 > MA Forecast 17
🔸 RSI Forecast 17 < MA Forecast 17
🔸 RSI Forecast 18 > MA Forecast 18
🔸 RSI Forecast 18 < MA Forecast 18
🔸 RSI Forecast 19 > MA Forecast 19
🔸 RSI Forecast 19 < MA Forecast 19
🔸 RSI Forecast 20 > MA Forecast 20
🔸 RSI Forecast 20 < MA Forecast 20
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
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Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
PubLibCandleTrendLibrary "PubLibCandleTrend"
candle trend, multi-part candle trend, multi-part green/red candle trend, double candle trend and multi-part double candle trend conditions for indicator and strategy development
chh()
candle higher high condition
Returns: bool
chl()
candle higher low condition
Returns: bool
clh()
candle lower high condition
Returns: bool
cll()
candle lower low condition
Returns: bool
cdt()
candle double top condition
Returns: bool
cdb()
candle double bottom condition
Returns: bool
gc()
green candle condition
Returns: bool
gchh()
green candle higher high condition
Returns: bool
gchl()
green candle higher low condition
Returns: bool
gclh()
green candle lower high condition
Returns: bool
gcll()
green candle lower low condition
Returns: bool
gcdt()
green candle double top condition
Returns: bool
gcdb()
green candle double bottom condition
Returns: bool
rc()
red candle condition
Returns: bool
rchh()
red candle higher high condition
Returns: bool
rchl()
red candle higher low condition
Returns: bool
rclh()
red candle lower high condition
Returns: bool
rcll()
red candle lower low condition
Returns: bool
rcdt()
red candle double top condition
Returns: bool
rcdb()
red candle double bottom condition
Returns: bool
chh_1p()
1-part candle higher high condition
Returns: bool
chh_2p()
2-part candle higher high condition
Returns: bool
chh_3p()
3-part candle higher high condition
Returns: bool
chh_4p()
4-part candle higher high condition
Returns: bool
chh_5p()
5-part candle higher high condition
Returns: bool
chh_6p()
6-part candle higher high condition
Returns: bool
chh_7p()
7-part candle higher high condition
Returns: bool
chh_8p()
8-part candle higher high condition
Returns: bool
chh_9p()
9-part candle higher high condition
Returns: bool
chh_10p()
10-part candle higher high condition
Returns: bool
chh_11p()
11-part candle higher high condition
Returns: bool
chh_12p()
12-part candle higher high condition
Returns: bool
chh_13p()
13-part candle higher high condition
Returns: bool
chh_14p()
14-part candle higher high condition
Returns: bool
chh_15p()
15-part candle higher high condition
Returns: bool
chh_16p()
16-part candle higher high condition
Returns: bool
chh_17p()
17-part candle higher high condition
Returns: bool
chh_18p()
18-part candle higher high condition
Returns: bool
chh_19p()
19-part candle higher high condition
Returns: bool
chh_20p()
20-part candle higher high condition
Returns: bool
chh_21p()
21-part candle higher high condition
Returns: bool
chh_22p()
22-part candle higher high condition
Returns: bool
chh_23p()
23-part candle higher high condition
Returns: bool
chh_24p()
24-part candle higher high condition
Returns: bool
chh_25p()
25-part candle higher high condition
Returns: bool
chh_26p()
26-part candle higher high condition
Returns: bool
chh_27p()
27-part candle higher high condition
Returns: bool
chh_28p()
28-part candle higher high condition
Returns: bool
chh_29p()
29-part candle higher high condition
Returns: bool
chh_30p()
30-part candle higher high condition
Returns: bool
chl_1p()
1-part candle higher low condition
Returns: bool
chl_2p()
2-part candle higher low condition
Returns: bool
chl_3p()
3-part candle higher low condition
Returns: bool
chl_4p()
4-part candle higher low condition
Returns: bool
chl_5p()
5-part candle higher low condition
Returns: bool
chl_6p()
6-part candle higher low condition
Returns: bool
chl_7p()
7-part candle higher low condition
Returns: bool
chl_8p()
8-part candle higher low condition
Returns: bool
chl_9p()
9-part candle higher low condition
Returns: bool
chl_10p()
10-part candle higher low condition
Returns: bool
chl_11p()
11-part candle higher low condition
Returns: bool
chl_12p()
12-part candle higher low condition
Returns: bool
chl_13p()
13-part candle higher low condition
Returns: bool
chl_14p()
14-part candle higher low condition
Returns: bool
chl_15p()
15-part candle higher low condition
Returns: bool
chl_16p()
16-part candle higher low condition
Returns: bool
chl_17p()
17-part candle higher low condition
Returns: bool
chl_18p()
18-part candle higher low condition
Returns: bool
chl_19p()
19-part candle higher low condition
Returns: bool
chl_20p()
20-part candle higher low condition
Returns: bool
chl_21p()
21-part candle higher low condition
Returns: bool
chl_22p()
22-part candle higher low condition
Returns: bool
chl_23p()
23-part candle higher low condition
Returns: bool
chl_24p()
24-part candle higher low condition
Returns: bool
chl_25p()
25-part candle higher low condition
Returns: bool
chl_26p()
26-part candle higher low condition
Returns: bool
chl_27p()
27-part candle higher low condition
Returns: bool
chl_28p()
28-part candle higher low condition
Returns: bool
chl_29p()
29-part candle higher low condition
Returns: bool
chl_30p()
30-part candle higher low condition
Returns: bool
clh_1p()
1-part candle lower high condition
Returns: bool
clh_2p()
2-part candle lower high condition
Returns: bool
clh_3p()
3-part candle lower high condition
Returns: bool
clh_4p()
4-part candle lower high condition
Returns: bool
clh_5p()
5-part candle lower high condition
Returns: bool
clh_6p()
6-part candle lower high condition
Returns: bool
clh_7p()
7-part candle lower high condition
Returns: bool
clh_8p()
8-part candle lower high condition
Returns: bool
clh_9p()
9-part candle lower high condition
Returns: bool
clh_10p()
10-part candle lower high condition
Returns: bool
clh_11p()
11-part candle lower high condition
Returns: bool
clh_12p()
12-part candle lower high condition
Returns: bool
clh_13p()
13-part candle lower high condition
Returns: bool
clh_14p()
14-part candle lower high condition
Returns: bool
clh_15p()
15-part candle lower high condition
Returns: bool
clh_16p()
16-part candle lower high condition
Returns: bool
clh_17p()
17-part candle lower high condition
Returns: bool
clh_18p()
18-part candle lower high condition
Returns: bool
clh_19p()
19-part candle lower high condition
Returns: bool
clh_20p()
20-part candle lower high condition
Returns: bool
clh_21p()
21-part candle lower high condition
Returns: bool
clh_22p()
22-part candle lower high condition
Returns: bool
clh_23p()
23-part candle lower high condition
Returns: bool
clh_24p()
24-part candle lower high condition
Returns: bool
clh_25p()
25-part candle lower high condition
Returns: bool
clh_26p()
26-part candle lower high condition
Returns: bool
clh_27p()
27-part candle lower high condition
Returns: bool
clh_28p()
28-part candle lower high condition
Returns: bool
clh_29p()
29-part candle lower high condition
Returns: bool
clh_30p()
30-part candle lower high condition
Returns: bool
cll_1p()
1-part candle lower low condition
Returns: bool
cll_2p()
2-part candle lower low condition
Returns: bool
cll_3p()
3-part candle lower low condition
Returns: bool
cll_4p()
4-part candle lower low condition
Returns: bool
cll_5p()
5-part candle lower low condition
Returns: bool
cll_6p()
6-part candle lower low condition
Returns: bool
cll_7p()
7-part candle lower low condition
Returns: bool
cll_8p()
8-part candle lower low condition
Returns: bool
cll_9p()
9-part candle lower low condition
Returns: bool
cll_10p()
10-part candle lower low condition
Returns: bool
cll_11p()
11-part candle lower low condition
Returns: bool
cll_12p()
12-part candle lower low condition
Returns: bool
cll_13p()
13-part candle lower low condition
Returns: bool
cll_14p()
14-part candle lower low condition
Returns: bool
cll_15p()
15-part candle lower low condition
Returns: bool
cll_16p()
16-part candle lower low condition
Returns: bool
cll_17p()
17-part candle lower low condition
Returns: bool
cll_18p()
18-part candle lower low condition
Returns: bool
cll_19p()
19-part candle lower low condition
Returns: bool
cll_20p()
20-part candle lower low condition
Returns: bool
cll_21p()
21-part candle lower low condition
Returns: bool
cll_22p()
22-part candle lower low condition
Returns: bool
cll_23p()
23-part candle lower low condition
Returns: bool
cll_24p()
24-part candle lower low condition
Returns: bool
cll_25p()
25-part candle lower low condition
Returns: bool
cll_26p()
26-part candle lower low condition
Returns: bool
cll_27p()
27-part candle lower low condition
Returns: bool
cll_28p()
28-part candle lower low condition
Returns: bool
cll_29p()
29-part candle lower low condition
Returns: bool
cll_30p()
30-part candle lower low condition
Returns: bool
gc_1p()
1-part green candle condition
Returns: bool
gc_2p()
2-part green candle condition
Returns: bool
gc_3p()
3-part green candle condition
Returns: bool
gc_4p()
4-part green candle condition
Returns: bool
gc_5p()
5-part green candle condition
Returns: bool
gc_6p()
6-part green candle condition
Returns: bool
gc_7p()
7-part green candle condition
Returns: bool
gc_8p()
8-part green candle condition
Returns: bool
gc_9p()
9-part green candle condition
Returns: bool
gc_10p()
10-part green candle condition
Returns: bool
gc_11p()
11-part green candle condition
Returns: bool
gc_12p()
12-part green candle condition
Returns: bool
gc_13p()
13-part green candle condition
Returns: bool
gc_14p()
14-part green candle condition
Returns: bool
gc_15p()
15-part green candle condition
Returns: bool
gc_16p()
16-part green candle condition
Returns: bool
gc_17p()
17-part green candle condition
Returns: bool
gc_18p()
18-part green candle condition
Returns: bool
gc_19p()
19-part green candle condition
Returns: bool
gc_20p()
20-part green candle condition
Returns: bool
gc_21p()
21-part green candle condition
Returns: bool
gc_22p()
22-part green candle condition
Returns: bool
gc_23p()
23-part green candle condition
Returns: bool
gc_24p()
24-part green candle condition
Returns: bool
gc_25p()
25-part green candle condition
Returns: bool
gc_26p()
26-part green candle condition
Returns: bool
gc_27p()
27-part green candle condition
Returns: bool
gc_28p()
28-part green candle condition
Returns: bool
gc_29p()
29-part green candle condition
Returns: bool
gc_30p()
30-part green candle condition
Returns: bool
rc_1p()
1-part red candle condition
Returns: bool
rc_2p()
2-part red candle condition
Returns: bool
rc_3p()
3-part red candle condition
Returns: bool
rc_4p()
4-part red candle condition
Returns: bool
rc_5p()
5-part red candle condition
Returns: bool
rc_6p()
6-part red candle condition
Returns: bool
rc_7p()
7-part red candle condition
Returns: bool
rc_8p()
8-part red candle condition
Returns: bool
rc_9p()
9-part red candle condition
Returns: bool
rc_10p()
10-part red candle condition
Returns: bool
rc_11p()
11-part red candle condition
Returns: bool
rc_12p()
12-part red candle condition
Returns: bool
rc_13p()
13-part red candle condition
Returns: bool
rc_14p()
14-part red candle condition
Returns: bool
rc_15p()
15-part red candle condition
Returns: bool
rc_16p()
16-part red candle condition
Returns: bool
rc_17p()
17-part red candle condition
Returns: bool
rc_18p()
18-part red candle condition
Returns: bool
rc_19p()
19-part red candle condition
Returns: bool
rc_20p()
20-part red candle condition
Returns: bool
rc_21p()
21-part red candle condition
Returns: bool
rc_22p()
22-part red candle condition
Returns: bool
rc_23p()
23-part red candle condition
Returns: bool
rc_24p()
24-part red candle condition
Returns: bool
rc_25p()
25-part red candle condition
Returns: bool
rc_26p()
26-part red candle condition
Returns: bool
rc_27p()
27-part red candle condition
Returns: bool
rc_28p()
28-part red candle condition
Returns: bool
rc_29p()
29-part red candle condition
Returns: bool
rc_30p()
30-part red candle condition
Returns: bool
cdut()
candle double uptrend condition
Returns: bool
cddt()
candle double downtrend condition
Returns: bool
cdut_1p()
1-part candle double uptrend condition
Returns: bool
cdut_2p()
2-part candle double uptrend condition
Returns: bool
cdut_3p()
3-part candle double uptrend condition
Returns: bool
cdut_4p()
4-part candle double uptrend condition
Returns: bool
cdut_5p()
5-part candle double uptrend condition
Returns: bool
cdut_6p()
6-part candle double uptrend condition
Returns: bool
cdut_7p()
7-part candle double uptrend condition
Returns: bool
cdut_8p()
8-part candle double uptrend condition
Returns: bool
cdut_9p()
9-part candle double uptrend condition
Returns: bool
cdut_10p()
10-part candle double uptrend condition
Returns: bool
cdut_11p()
11-part candle double uptrend condition
Returns: bool
cdut_12p()
12-part candle double uptrend condition
Returns: bool
cdut_13p()
13-part candle double uptrend condition
Returns: bool
cdut_14p()
14-part candle double uptrend condition
Returns: bool
cdut_15p()
15-part candle double uptrend condition
Returns: bool
cdut_16p()
16-part candle double uptrend condition
Returns: bool
cdut_17p()
17-part candle double uptrend condition
Returns: bool
cdut_18p()
18-part candle double uptrend condition
Returns: bool
cdut_19p()
19-part candle double uptrend condition
Returns: bool
cdut_20p()
20-part candle double uptrend condition
Returns: bool
cdut_21p()
21-part candle double uptrend condition
Returns: bool
cdut_22p()
22-part candle double uptrend condition
Returns: bool
cdut_23p()
23-part candle double uptrend condition
Returns: bool
cdut_24p()
24-part candle double uptrend condition
Returns: bool
cdut_25p()
25-part candle double uptrend condition
Returns: bool
cdut_26p()
26-part candle double uptrend condition
Returns: bool
cdut_27p()
27-part candle double uptrend condition
Returns: bool
cdut_28p()
28-part candle double uptrend condition
Returns: bool
cdut_29p()
29-part candle double uptrend condition
Returns: bool
cdut_30p()
30-part candle double uptrend condition
Returns: bool
cddt_1p()
1-part candle double downtrend condition
Returns: bool
cddt_2p()
2-part candle double downtrend condition
Returns: bool
cddt_3p()
3-part candle double downtrend condition
Returns: bool
cddt_4p()
4-part candle double downtrend condition
Returns: bool
cddt_5p()
5-part candle double downtrend condition
Returns: bool
cddt_6p()
6-part candle double downtrend condition
Returns: bool
cddt_7p()
7-part candle double downtrend condition
Returns: bool
cddt_8p()
8-part candle double downtrend condition
Returns: bool
cddt_9p()
9-part candle double downtrend condition
Returns: bool
cddt_10p()
10-part candle double downtrend condition
Returns: bool
cddt_11p()
11-part candle double downtrend condition
Returns: bool
cddt_12p()
12-part candle double downtrend condition
Returns: bool
cddt_13p()
13-part candle double downtrend condition
Returns: bool
cddt_14p()
14-part candle double downtrend condition
Returns: bool
cddt_15p()
15-part candle double downtrend condition
Returns: bool
cddt_16p()
16-part candle double downtrend condition
Returns: bool
cddt_17p()
17-part candle double downtrend condition
Returns: bool
cddt_18p()
18-part candle double downtrend condition
Returns: bool
cddt_19p()
19-part candle double downtrend condition
Returns: bool
cddt_20p()
20-part candle double downtrend condition
Returns: bool
cddt_21p()
21-part candle double downtrend condition
Returns: bool
cddt_22p()
22-part candle double downtrend condition
Returns: bool
cddt_23p()
23-part candle double downtrend condition
Returns: bool
cddt_24p()
24-part candle double downtrend condition
Returns: bool
cddt_25p()
25-part candle double downtrend condition
Returns: bool
cddt_26p()
26-part candle double downtrend condition
Returns: bool
cddt_27p()
27-part candle double downtrend condition
Returns: bool
cddt_28p()
28-part candle double downtrend condition
Returns: bool
cddt_29p()
29-part candle double downtrend condition
Returns: bool
cddt_30p()
30-part candle double downtrend condition
Returns: bool
Technical Ratings on Multi-frames / Assets█ OVERVIEW
This indicator is a modified version of TECHNICAL RATING v1.0 available in the public library to provide a quick overview of consolidated technical ratings performed on 12 assets in 3 timeframes.The purpose of the indicator is to provide a quick overview of the current status of the custom 12 (24) assets and to help focus on the appropriate asset.
█ MODIFICATIONS
- Markers, visualizations and alerts have been deleted
- Due to the limitation on maximum number of security (40), the results of 12 assets evaluated in 3 different time frames can be shown at the same time.
- An additional 12 assets can be configured in the settings so that you do not have to choose each ticker one by one to facilitate a quick change, but can switch between the 12 -12 assets with a single click on "Second sets?".
- The position, colors and parameters of the table can be widely customized in the settings.
- The 12 assets can be arranged in rows 3, 4, 6 and 12 with Table Rows options, which can also be used to create a simple mobile view.
- The default gradient color setting has been changed to red/yellow/green traffic lights
ORIGINAL DESCRIPTION ABOUT TECHNICAL RATING v1.0
█ OVERVIEW
This indicator calculates TradingView's well-known "Strong Buy", "Buy", "Neutral", "Sell" or "Strong Sell" states using the aggregate biases of 26 different technical indicators.
█ WARNING
This version is similar, but not identical, to our recently published "Technical Ratings" built-in, which reproduces our "Technicals" ratings displayed as a gauge in the right panel of charts, or in the "Rating" indicator available in the TradingView Screener. This is a fork and refactoring of the code base used in the "Technical Ratings" built-in. Its calculations will not always match those of the built-in, but it provides options not available in the built-in. Up to you to decide which one you prefer to use.
█ FEATURES
Differences with the built-in version
• The built-in version produces values matching the states displayed in the "Technicals" ratings gauge; this one does not always.
• A strategy version is also available as a built-in; this script is an indicator—not a strategy.
• This indicator will show a slightly different vertical scale, as it does not use a fixed scale like the built-in.
• This version allows control over repainting of the signal when you do not use a higher timeframe. Higher timeframe (HTF) information from this version does not repaint.
• You can adjust the weight of the Oscillators and MAs components of the rating here.
• You can configure markers on signal breaches of configurable levels, or on advances declines of the signal.
The indicator's settings allow you to:
• Choose the timeframe you want calculations to be made on.
• When not using a HTF, you can select a repainting or non-repainting signal.
• When using both MAs and Oscillators groups to calculate the rating, you can vary the weight of each group in the calculation. The default is 50/50.
Because the MAs group uses longer periods for some of its components, its value is not as jumpy as the Oscillators value.
Increasing the weight of the MAs group will thus have a calming effect on the signal.
• Alerts can be created on the indicator using the conditions configured to control the display of markers.
Display
The calculated rating is displayed as columns, but you can change the style in the inputs. The color of the signal can be one of three colors: bull, bear, or neutral. You can choose from a few presets, or check one and edit its color. The color is determined from the rating's value. Between 0.1 and -0.1 it is in the neutral color. Above/below 0.1/-0.1 it will appear in the bull/bear color. The intensity of the bull/bear color is determined by cumulative advances/declines in the rating. It is capped to 5, so there are five intensities for each of the bull/bear colors.
The "Strong Buy", "Buy", "Neutral", "Sell" or "Strong Sell" state of the last calculated value is displayed to the right of the last bar for each of the three groups: All, MAs and Oscillators. The first value always reflects your selection in the "Rating uses" field and is the one used to display the signal. A "Strong Buy" or "Strong Sell" state appears when the signal is above/below the 0.5/-0.5 level. A "Buy" or "Sell" state appears when the signal is above/below the 0.1/-0.1 level. The "Neutral" state appears when the signal is between 0.1 and -0.1 inclusively.
Five levels are always displayed: 0.5 and 0.1 in the bull color, zero in the neutral color, and -0.1 and - 0.5 in the bull color.
█ CALCULATIONS
The indicator calculates the aggregate value of two groups of indicators: moving averages and oscillators.
The "MAs" group is comprised of 15 different components:
• Six Simple Moving Averages of periods 10, 20, 30, 50, 100 and 200
• Six Exponential Moving Averages of the same periods
• A Hull Moving Average of period 9
• A Volume-weighed Moving Average of period 20
• Ichimoku
The "Oscillators" group includes 11 components:
• RSI
• Stochastic
• CCI
• ADX
• Awesome Oscillator
• Momentum
• MACD
• Stochastic RSI
• Wiliams %R
• Bull Bear Power
• Ultimate Oscillator
LA - MACD EMA BandsOverview of the "LA - MACD EMA Bands" Indicator
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
The "LA - MACD EMA Bands" is a custom technical indicator written in Pine Script v6 for TradingView. It builds on the traditional Moving Average Convergence Divergence (MACD) oscillator by incorporating additional smoothing via Exponential Moving Averages (EMAs) and Bollinger Bands (BB) applied directly to the MACD line. This creates a multi-layered momentum and volatility tool displayed in a separate pane below the price chart (not overlaid on the price itself).
The indicator allows for customization, such as selecting a different timeframe (for multi-timeframe analysis) and adjusting period lengths. It fetches data from the specified timeframe using request.security with lookahead enabled to avoid repainting issues. The core idea is to provide insights into momentum trends, crossovers, and volatility expansions/contractions in the MACD's behavior, making it suitable for identifying potential trend reversals, continuations, or ranging markets.
Unlike a standard MACD, which focuses primarily on momentum via a single line, signal line, and histogram, this version emphasizes longer-term smoothing and volatility boundaries. It uses visual fills between lines to highlight bullish/bearish conditions, aiding quick interpretation. Below, I'll break down each component, its calculation, visual representation, and practical uses.
Detailed Breakdown of Each Component and Its Uses
MACD Line (Blue Line, Labeled 'MACD Line')
Calculation: This is the core MACD value, computed as the difference between a fast EMA (default length 12) and a slow EMA (default length 144) of the input source (default: close price). The EMAs are calculated on data from the selected timeframe.
Visuals: Plotted as a solid blue line.
Uses:
Measures momentum: When above zero, it indicates bullish momentum (prices rising faster in the short term); below zero, bearish momentum.
Trend identification: Rising MACD suggests strengthening uptrends; falling suggests downtrends.
Divergence spotting: Compare with price action—e.g., if price makes higher highs but MACD makes lower highs, it signals potential bearish reversal (and vice versa for bullish divergence).
In trading: Often used for entry/exit signals when crossing the zero line or other lines in the indicator.
MACD EMA (Red Line, Labeled 'MACD EMA')
Calculation: A 12-period EMA applied to the MACD Line itself.
Visuals: Plotted as a solid red line.
Uses:
Acts as a signal line for the MACD, smoothing out short-term noise.
Crossover signals: When the MACD Line crosses above the MACD EMA, it can signal a bullish buy opportunity; crossing below suggests a bearish sell.
Trend confirmation: Helps filter false signals in choppy markets by requiring confirmation from this slower-moving average.
In trading: Useful for momentum-based strategies, like entering trades on crossovers in alignment with the overall trend.
Fill Between MACD Line and MACD EMA (Green/Red Shaded Area, Titled 'MACD Fill')
Calculation: The area between the MACD Line and MACD EMA is filled with color based on their relative positions.
Color Logic: Green (with 57% transparency) if MACD Line > MACD EMA (bullish); red if MACD Line < MACD EMA (bearish).
Visuals: Semi-transparent fill for easy visibility without overwhelming the lines.
Uses:
Quick visual cue for momentum shifts: Green areas highlight bullish phases; red for bearish.
Enhances readability: Makes crossovers more apparent at a glance, especially in fast-moving markets.
In trading: Can be used to time entries/exits or as a filter (e.g., only take long trades in green zones).
Bollinger Bands on MACD (BB Upper: Black Dotted, BB Basis: Maroon Dotted, BB Lower: Black Dotted)
Calculation: Bollinger Bands applied to the MACD Line.
BB Basis: 144-period EMA of the MACD Line.
BB Standard Deviation: 144-period stdev of the MACD Line.
BB Upper: BB Basis + (2.0 * BB Stdev)
BB Lower: BB Basis - (2.0 * BB Stdev)
Visuals: Upper and lower bands as black dotted lines; basis as maroon dotted
Uses:
Volatility measurement: Bands expand during high momentum volatility (strong trends) and contract during low volatility (ranging or consolidation).
Mean reversion: When MACD Line touches or exceeds the upper band, it may signal overbought conditions (potential sell); lower band for oversold (potential buy).
Squeeze detection: Narrow bands (squeeze) often precede big moves—watch for breakouts.
In trading: Combines momentum with volatility; e.g., a MACD Line breakout above the upper band could confirm a strong uptrend.
BB Basis EMA (Green Line, Labeled 'BB Basis EMA')
Calculation: A 72-period EMA applied to the BB Basis (which is already a 144-period EMA of the MACD Line).
Visuals: Solid green line.
Uses:
Further smoothing: Provides a longer-term view of the MACD's average behavior, reducing noise from the BB Basis.
Trend direction: Acts as a baseline for the BB system—above it suggests bullish bias in momentum volatility; below, bearish.
Crossover with BB Basis: Can signal shifts in volatility trends (e.g., BB Basis crossing above BB Basis EMA indicates increasing bullish volatility).
In trading: Useful for confirming longer-term trends or as a filter for BB-based signals.
Fill Between BB Basis and BB Basis EMA (Gray Shaded Area, Titled 'BB Basis Fill')
Calculation: The area between BB Basis and BB Basis EMA is filled.
Color Logic: Currently set to a constant semi-transparent gray regardless of position.
Visuals: Semi-transparent gray fill.
Uses:
Highlights divergence: Shows when the shorter-term BB Basis deviates from its longer-term EMA, indicating potential volatility shifts.
Visual aid for crossovers: Makes it easier to spot when BB Basis crosses its EMA.
In trading: Could be used to identify overextensions in volatility (e.g., wide gray areas might signal impending mean reversion).
Zero Line (Black Horizontal Line)
Calculation: A simple horizontal line at y=0.
Visuals: Solid black line.
Uses:
Reference point: Divides bullish (above) from bearish (below) territory for all MACD-related lines.
In trading: Crossovers of the zero line by the MACD Line or BB Basis can signal major trend changes.
How It Differs from a Normal MACD
A standard MACD (e.g., the built-in TradingView MACD with defaults 12/26/9) consists of:
MACD Line: EMA(12) - EMA(26).
Signal Line: EMA(MACD Line, 9).
Histogram: MACD Line - Signal Line (bars showing convergence/divergence).
Key differences in "LA - MACD EMA Bands":
Periods: Uses a much longer slow EMA (144 vs. 26), making it more sensitive to long-term trends but less reactive to short-term price action. The MACD EMA is 12 periods (vs. 9), further emphasizing smoothing.
No Histogram: Replaces the histogram with fills and bands for visual emphasis on crossovers and volatility.
Added Bollinger Bands: Applies BB directly to the MACD Line (with a long 144-period basis), introducing volatility analysis absent in standard MACD. This helps detect "squeezes" or expansions in momentum.
Additional EMA Layer: The BB Basis EMA (72-period) adds a secondary smoothing level to the BB system, providing a hierarchical view of momentum (short-term MACD → mid-term BB → long-term EMA).
Multi-Timeframe Support: Built-in option for higher timeframes, unlike basic MACD.
Focus: Standard MACD is purely momentum-focused; this version integrates volatility (via BB) and multi-layer smoothing, making it better for trend-following in volatile markets but potentially overwhelming for beginners.
Overall, this indicator transforms the MACD from a simple oscillator into a comprehensive momentum-volatility hybrid, reducing false signals in trending markets but introducing lag.
Overall Pros and Cons
Pros:
Enhanced Visualization: Fills and bands make trends, crossovers, and volatility easier to spot without needing multiple indicators.
Reduced Noise: Longer periods (144, 72) smooth out whipsaws, ideal for swing or position trading in trending assets like stocks or forex.
Volatility Integration: BB adds a dimension not in standard MACD, helping identify breakouts or consolidations.
Customizable: Inputs for timeframes and lengths allow adaptation to different assets/timeframes.
Multi-Layered Insights: Combines short-term signals (MACD crossovers) with long-term confirmation (BB EMA), improving signal reliability.
Cons:
Lagging Nature: Long periods (e.g., 144) delay signals, missing early entries in fast markets or leading to late exits.
Complexity: Multiple lines and fills can clutter the pane, requiring experience to interpret; beginners might misread it.
Potential Overfitting: Custom periods (12/144/12/144/72) may work well on historical data but underperform in live trading without backtesting.
No Built-in Alerts/Signals: Relies on visual interpretation; users must manually set alerts for crossovers.
Resource Intensive: On lower timeframes or with lookahead, it might slow chart loading on Trading View.
This indicator shines in strategies combining momentum and volatility, like trend-following with BB squeezes, but test it on your assets (e.g., via backtesting) to ensure it fits your style.
For Better view, use this indicator along with "LA - EMA Bands with MTF Dashboard"
Swing Guardrail — 30-sec Midterm Check (EBITDA Margin & EV/EBITDWhat it does
Before a short-term swing entry, this indicator right-sizes positions by a quick midterm (3–12m) durability screen using two fundamentals:
EBITDA Margin (TTM) → earning power / operational resilience
EV/EBITDA (TTM) → price tag vs earning capacity (payback feel)
A high-contrast table (top-right) shows both metrics and a verdict:
PASS — both meet thresholds → normal size
HALF — only one meets → reduce size
FAIL — neither meets → avoid
Why check “midterm” for a short-term trade?
Short swings still face earnings/news gaps, failed breakouts, and regime shifts. Names with weak margins or stretched valuation tend to break faster and deeper. A 30-sec durability check helps you:
Filter fragile setups (avoid expensive + weakening names)
Stabilize drawdowns (size down when quality/price don’t align)
Keep timing unchanged while improving risk-adjusted returns
Inputs (defaults)
Min EBITDA Margin % (TTM): 8%
Max EV/EBITDA (TTM): 12
Dark chart? High-contrast colors
How to use with a swing system
Get your entry from price/volume (e.g., Ichimoku cloud break, Kijun reclaim, Tenkan>Kijun; or your A/B/C rules).
Run this check only to set size (not timing).
Optional alerts: Once per bar close for PASS / HALF / FAIL.
Size mapping & event guard
PASS → 100% of your planned size
HALF → ~50% size / tighter stops
FAIL → watchlist only
If earnings < ~10 JP business days, drop one tier; ≤3 days → avoid.
Sector guides (tweak as needed)
Software/Internet: Margin ≥ 15%, EV/EBITDA ≤ 18
Industrials/Consumer: Margin ≥ 8%, EV/EBITDA ≤ 12
Retail: Margin ≥ 5–7%, EV/EBITDA ≤ 10–12
Edge cases / substitutions
Banks/Insurers/REITs or net-cash/negative EBITDA: EV/EBITDA may mislead → consider Net Debt/EBITDA or sector metrics (CET1/LTV/DSCR).
Sparse data / fresh listings: numbers may be NA until updates.
Notes & limitations
Data via request.financial() (TTM/most-recent). Some tickers/regions can show NA until fundamentals refresh.
This is a risk-screen / sizing tool, not a buy/sell signal.
Disclaimer
Educational use only. Not investment advice.
日本語
タイトル
スイング用ガードレール―中期“壊れにくさ”30秒チェック（EBITDAマージン & EV/EBITDA, TTM）
概要
短期スイングのエントリー前に、中期（3〜12か月）の耐久性を2指標で素早く確認し、ポジションサイズを決めるためのツールです。
EBITDAマージン（TTM）：事業の稼ぐ力・体力
EV/EBITDA（TTM）：その体力に対する“値札”（回収年数の感覚）
右上の高コントラスト表に数値と判定を表示：
PASS：両方クリア → 通常サイズ
HALF：片方のみ → サイズ半分
FAIL：両方NG → 見送り
なぜ短期でも“中期”を確認？
短期でも決算・ニュースのギャップ、ブレイク失敗、地合い転換は起きます。マージンが弱い／割高すぎる銘柄は崩れやすく、戻りも鈍い傾向。30秒の耐久性チェックで
脆いセットアップを回避
ドローダウンを平準化（サイズで吸収）
タイミングは変えずに、リスク調整後リターンの改善を狙えます。
入力（既定）
最低EBITDAマージン：8%
最大EV/EBITDA：12
黒背景向け：高コントラスト表示
使い方（スイング手法と併用）
まずは価格シグナル（一目の雲上抜け／基準線回復／転換線>基準線、またはA/B/Cルール）。
本インジの判定でサイズのみ決定（エントリーのタイミングは出しません）。
任意でバー確定アラート（PASS/HALF/FAIL）を設定。
サイズ目安 & イベント抑制
PASS：計画サイズ100%
HALF：約50%（ストップもタイトに）
FAIL：見送り
決算まで≦10営業日なら1段階サイズダウン、≦3営業日は原則見送り。
セクター目安（調整推奨）
ソフト/ネット：マージン 15%以上、EV/EBITDA 18以下
工業/一般消費：マージン 8%以上、EV/EBITDA 12以下
小売：マージン 5〜7%以上、EV/EBITDA 10〜12以下
例外・代替
銀行・保険・REIT／ネットキャッシュ・EBITDAマイナス：EV/EBITDAは適さない場合 → Net Debt/EBITDAやCET1/LTV/DSCR等で補助。
新規上場・データ薄：更新までNAのことあり。
注意
データは request.financial() を使用。更新前はNAの可能性。
本ツールはリスク確認／サイズ調整用で、売買シグナルではありません。
免責
情報提供のみ。投資判断は自己責任で。
FUMO 200 MagnetWhat it does
FUMO Magnet measures how far price has stretched away from its long-term “magnet” — a blended EMA/SMA moving average (200 by default).
It plots a logarithmic deviation (optionally normalized) as an oscillator around zero.
Above 0** → price is above the magnet (stretched up)
Below 0** → price is below the magnet (stretched down)
Guide levels** highlight potential overbought/oversold zones
---
Why log deviation?
Log returns make extremes comparable across cycles and compress exponential trends — especially useful for BTC and other crypto assets.
Normalization modes further adjust the scale, keeping the oscillator readable on any chart.
---
Inputs
**Base**
* Source (default: Close)
* Base Length (default: 200 EMA/SMA)
* EMA vs SMA weight (%) — 0% = pure SMA, 100% = pure EMA, 50% = blended
* EMA smoothing of deviation — acts as a noise filter
**Normalization**
* None (Log Deviation) — raw log stretch in % terms
* Z-score — deviation in standard deviations (σ)
* Robust Z (MAD) — deviation vs median absolute deviation, resistant to outliers
* Tanh squash — smooth nonlinear squash of extremes for compact scale
* Normalization window (for Z / MAD)
* Tanh scale (lower = stronger squash)
* Clamp after normalization — hard cap at ±X
**Levels**
* Guide levels (Upper / Lower) — visual thresholds (default ±12)
* Zero line toggle
---
### How to read it
* **Trend bias**: sustained time above 0 = uptrend, below 0 = downtrend
* **Stretch / mean reversion**: the farther from 0, the higher the reversion risk
* **Cross-checks**: combine with structure (HH/HL, LH/LL), volume, or momentum (RSI, MACD)
---
### Recommended settings by timeframe
**Long-term (1D / 1W)**
* Normalization: None (Log Deviation)
* Base Length: 200
* EMA vs SMA weight: 50% (adjust 35–65% for faster/slower magnet)
* Deviation smoothing: 20 (10–30 range)
* Guide levels: ±12 to ±20
* Use case: cycle extremes, portfolio rebalancing, trim/add logic
**Swing (4H – 1D)**
* Normalization: Z-score
* Window: 200 (100–250)
* Smoothing: 14–20
* Guide levels: ±2σ to ±3σ
* Use case: stretched conditions across regimes; ±3σ is rare, often mean-reverts
**Intraday / Active swing (1H – 4H)**
* Normalization: Robust Z (MAD)
* Window: 200 (150 for faster response)
* Smoothing: 10–16
* Guide levels: ±3 to ±4 (robust units)
* Use case: handles spikes better than σ, fewer false overbought/oversold signals
**Scalping / Universal readability (15m – 1H)**
* Normalization: Tanh squash
* Tanh scale: 6–10 (start with 8)
* Smoothing: 8–12
* Guide levels: ±8 to ±12
* Use case: compact panel across assets and timeframes; not % or σ, but visually consistent
---
### Optional
* Clamp: enable ±20 (or ±25) for strict bounded range (useful for public charts)
---
### Quick setups
**BTC Daily (“cycle view”)**
* Normalization: None
* Blend: 50%
* Smooth: 20
* Levels: ±12–15
**BTC 4H (“swing”)**
* Normalization: Z-score
* Window: 200
* Smooth: 16
* Levels: ±2.5σ to ±3σ
**Alts 1H (“volatile”)**
* Normalization: Robust Z (MAD)
* Window: 200
* Smooth: 12
* Levels: ±3.5 to ±4.5
**Mixed assets 15m (“compact panel”)**
* Normalization: Tanh squash
* Scale: 8
* Smooth: 10
* Levels: ±8–12
* Clamp: ±20
