XTE+ Optimized Trend Tracker📊 XTE+ Optimized Trend Tracker (OTT)
XTE+ OTT is a powerful, trend-following indicator designed for traders who value clarity, precision, and advanced analytics. It offers not only accurate entry and exit signals but also visual zones, historical signal analysis, and real-time trend monitoring.
🧠 How It Works
XTE+ OTT is based on an improved version of the Optimized Trend Tracker. It utilizes multiple customizable moving average types (VAR, EMA, SMA, WMA, and more) combined with volatility filtering (ATR logic) to generate cleaner, more reliable trend-following signals.
✅ Features
Trend Direction Detection with automatic switch logic
Buy/Sell Signal Icons with distinct large markers
Entry/Exit Zones drawn visually on chart
Custom Take-Profit / Stop-Loss settings for Buy and Sell signals
Statistical Panel showing:
Current Trend (Up/Down)
Number of total signals
Number of winning trades
Win percentage
Configurable Display Options:
Show/hide signals
Show/hide trend zones
Show/hide OTT and MA lines
Supports multiple MA types including EMA, SMA, VAR, ZLEMA, TSF and more
Non-repainting logic — signals are confirmed at bar close
⚙️ Inputs and Customization
OTT Period & Sensitivity (%)
MA Type Selection (VAR, EMA, etc.)
Entry Zone Visualization On/Off
Trend Panel Display On/Off
TP/SL % per direction (Buy/Sell separately)
Option to disable MA or OTT line display
📈 Visuals
Signal icons: BUY (Green Up Label), SELL (Red Down Label)
Entry zones: circles near breakout levels
Trendlines change color dynamically (green for uptrend, red for downtrend)
Trend Panel is pinned in the top-right corner for quick reference
💡 Usage Tips
Best used on higher timeframes (15min, 1H, 4H+) for more meaningful trend signals
Combine with volume/volatility indicators or support/resistance zones for enhanced decision making
Use TP/SL logic to track signal success over time and optimize strategies
📌 Disclaimer
This script is for educational and informational purposes only. It is not financial advice. Always test and validate your strategy before applying it in live markets.
Search in scripts for "Up down"
ZigZag█ Overview
This Pine Script™ library provides a comprehensive implementation of the ZigZag indicator using advanced object-oriented programming techniques. It serves as a developer resource rather than a standalone indicator, enabling Pine Script™ programmers to incorporate sophisticated ZigZag calculations into their own scripts.
Pine Script™ libraries contain reusable code that can be imported into indicators, strategies, and other libraries. For more information, consult the Libraries section of the Pine Script™ User Manual.
█ About the Original
This library is based on TradingView's official ZigZag implementation .
The original code provides a solid foundation with user-defined types and methods for calculating ZigZag pivot points.
█ What is ZigZag?
The ZigZag indicator filters out minor price movements to highlight significant market trends.
It works by:
1. Identifying significant pivot points (local highs and lows)
2. Connecting these points with straight lines
3. Ignoring smaller price movements that fall below a specified threshold
Traders typically use ZigZag for:
- Trend confirmation
- Identifying support and resistance levels
- Pattern recognition (such as Elliott Waves)
- Filtering out market noise
The algorithm identifies pivot points by analyzing price action over a specified number of bars, then only changes direction when price movement exceeds a user-defined percentage threshold.
█ My Enhancements
This modified version extends the original library with several key improvements:
1. Support and Resistance Visualization
- Adds horizontal lines at pivot points
- Customizable line length (offset from pivot)
- Adjustable line width and color
- Option to extend lines to the right edge of the chart
2. Support and Resistance Zones
- Creates semi-transparent zone areas around pivot points
- Customizable width for better visibility of important price levels
- Separate colors for support (lows) and resistance (highs)
- Visual representation of price areas rather than just single lines
3. Zig Zag Lines
- Separate colors for upward and downward ZigZag movements
- Visually distinguishes between bullish and bearish price swings
- Customizable colors for text
- Width customization
4. Enhanced Settings Structure
- Added new fields to the Settings type to support the additional features
- Extended Pivot type with supportResistance and supportResistanceZone fields
- Comprehensive configuration options for visual elements
These enhancements make the ZigZag more useful for technical analysis by clearly highlighting support/resistance levels and zones, and providing clearer visual cues about market direction.
█ Technical Implementation
This library leverages Pine Script™'s user-defined types (UDTs) to create a robust object-oriented architecture:
- Settings : Stores configuration parameters for calculation and display
- Pivot : Represents pivot points with their visual elements and properties
- ZigZag : Manages the overall state and behavior of the indicator
The implementation follows best practices from the Pine Script™ User Manual's Style Guide and uses advanced language features like methods and object references. These UDTs represent Pine Script™'s most advanced feature set, enabling sophisticated data structures and improved code organization.
For newcomers to Pine Script™, it's recommended to understand the language fundamentals before working with the UDT implementation in this library.
█ Usage Example
//@version=6
indicator("ZigZag Example", overlay = true, shorttitle = 'ZZA', max_bars_back = 5000, max_lines_count = 500, max_labels_count = 500, max_boxes_count = 500)
import andre_007/ZigZag/1 as ZIG
var group_1 = "ZigZag Settings"
//@variable Draw Zig Zag on the chart.
bool showZigZag = input.bool(true, "Show Zig-Zag Lines", group = group_1, tooltip = "If checked, the Zig Zag will be drawn on the chart.", inline = "1")
// @variable The deviation percentage from the last local high or low required to form a new Zig Zag point.
float deviationInput = input.float(5.0, "Deviation (%)", minval = 0.00001, maxval = 100.0,
tooltip = "The minimum percentage deviation from a previous pivot point required to change the Zig Zag's direction.", group = group_1, inline = "2")
// @variable The number of bars required for pivot detection.
int depthInput = input.int(10, "Depth", minval = 1, tooltip = "The number of bars required for pivot point detection.", group = group_1, inline = "3")
// @variable registerPivot (series bool) Optional. If `true`, the function compares a detected pivot
// point's coordinates to the latest `Pivot` object's `end` chart point, then
// updates the latest `Pivot` instance or adds a new instance to the `ZigZag`
// object's `pivots` array. If `false`, it does not modify the `ZigZag` object's
// data. The default is `true`.
bool allowZigZagOnOneBarInput = input.bool(true, "Allow Zig Zag on One Bar", tooltip = "If checked, the Zig Zag calculation can register a pivot high and pivot low on the same bar.",
group = group_1, inline = "allowZigZagOnOneBar")
var group_2 = "Display Settings"
// @variable The color of the Zig Zag's lines (up).
color lineColorUpInput = input.color(color.green, "Line Colors for Up/Down", group = group_2, inline = "4")
// @variable The color of the Zig Zag's lines (down).
color lineColorDownInput = input.color(color.red, "", group = group_2, inline = "4",
tooltip = "The color of the Zig Zag's lines")
// @variable The width of the Zig Zag's lines.
int lineWidthInput = input.int(1, "Line Width", minval = 1, tooltip = "The width of the Zig Zag's lines.", group = group_2, inline = "w")
// @variable If `true`, the Zig Zag will also display a line connecting the last known pivot to the current `close`.
bool extendInput = input.bool(true, "Extend to Last Bar", tooltip = "If checked, the last pivot will be connected to the current close.",
group = group_1, inline = "5")
// @variable If `true`, the pivot labels will display their price values.
bool showPriceInput = input.bool(true, "Display Reversal Price",
tooltip = "If checked, the pivot labels will display their price values.", group = group_2, inline = "6")
// @variable If `true`, each pivot label will display the volume accumulated since the previous pivot.
bool showVolInput = input.bool(true, "Display Cumulative Volume",
tooltip = "If checked, the pivot labels will display the volume accumulated since the previous pivot.", group = group_2, inline = "7")
// @variable If `true`, each pivot label will display the change in price from the previous pivot.
bool showChgInput = input.bool(true, "Display Reversal Price Change",
tooltip = "If checked, the pivot labels will display the change in price from the previous pivot.", group = group_2, inline = "8")
// @variable Controls whether the labels show price changes as raw values or percentages when `showChgInput` is `true`.
string priceDiffInput = input.string("Absolute", "", options = ,
tooltip = "Controls whether the labels show price changes as raw values or percentages when 'Display Reversal Price Change' is checked.",
group = group_2, inline = "8")
// @variable If `true`, the Zig Zag will display support and resistance lines.
bool showSupportResistanceInput = input.bool(true, "Show Support/Resistance Lines",
tooltip = "If checked, the Zig Zag will display support and resistance lines.", group = group_2, inline = "9")
// @variable The number of bars to extend the support and resistance lines from the last pivot point.
int supportResistanceOffsetInput = input.int(50, "Support/Resistance Offset", minval = 0,
tooltip = "The number of bars to extend the support and resistance lines from the last pivot point.", group = group_2, inline = "10")
// @variable The width of the support and resistance lines.
int supportResistanceWidthInput = input.int(1, "Support/Resistance Width", minval = 1,
tooltip = "The width of the support and resistance lines.", group = group_2, inline = "11")
// @variable The color of the support lines.
color supportColorInput = input.color(color.red, "Support/Resistance Color", group = group_2, inline = "12")
// @variable The color of the resistance lines.
color resistanceColorInput = input.color(color.green, "", group = group_2, inline = "12",
tooltip = "The color of the support/resistance lines.")
// @variable If `true`, the support and resistance lines will be drawn as zones.
bool showSupportResistanceZoneInput = input.bool(true, "Show Support/Resistance Zones",
tooltip = "If checked, the support and resistance lines will be drawn as zones.", group = group_2, inline = "12-1")
// @variable The color of the support zones.
color supportZoneColorInput = input.color(color.new(color.red, 70), "Support Zone Color", group = group_2, inline = "12-2")
// @variable The color of the resistance zones.
color resistanceZoneColorInput = input.color(color.new(color.green, 70), "", group = group_2, inline = "12-2",
tooltip = "The color of the support/resistance zones.")
// @variable The width of the support and resistance zones.
int supportResistanceZoneWidthInput = input.int(10, "Support/Resistance Zone Width", minval = 1,
tooltip = "The width of the support and resistance zones.", group = group_2, inline = "12-3")
// @variable If `true`, the support and resistance lines will extend to the right of the chart.
bool supportResistanceExtendInput = input.bool(false, "Extend to Right",
tooltip = "If checked, the lines will extend to the right of the chart.", group = group_2, inline = "13")
// @variable References a `Settings` instance that defines the `ZigZag` object's calculation and display properties.
var ZIG.Settings settings =
ZIG.Settings.new(
devThreshold = deviationInput,
depth = depthInput,
lineColorUp = lineColorUpInput,
lineColorDown = lineColorDownInput,
textUpColor = lineColorUpInput,
textDownColor = lineColorDownInput,
lineWidth = lineWidthInput,
extendLast = extendInput,
displayReversalPrice = showPriceInput,
displayCumulativeVolume = showVolInput,
displayReversalPriceChange = showChgInput,
differencePriceMode = priceDiffInput,
draw = showZigZag,
allowZigZagOnOneBar = allowZigZagOnOneBarInput,
drawSupportResistance = showSupportResistanceInput,
supportResistanceOffset = supportResistanceOffsetInput,
supportResistanceWidth = supportResistanceWidthInput,
supportColor = supportColorInput,
resistanceColor = resistanceColorInput,
supportResistanceExtend = supportResistanceExtendInput,
supportResistanceZoneWidth = supportResistanceZoneWidthInput,
drawSupportResistanceZone = showSupportResistanceZoneInput,
supportZoneColor = supportZoneColorInput,
resistanceZoneColor = resistanceZoneColorInput
)
// @variable References a `ZigZag` object created using the `settings`.
var ZIG.ZigZag zigZag = ZIG.newInstance(settings)
// Update the `zigZag` on every bar.
zigZag.update()
//#endregion
The example code demonstrates how to create a ZigZag indicator with customizable settings. It:
1. Creates a Settings object with user-defined parameters
2. Instantiates a ZigZag object using these settings
3. Updates the ZigZag on each bar to detect new pivot points
4. Automatically draws lines and labels when pivots are detected
This approach provides maximum flexibility while maintaining readability and ease of use.
Auto TrendLines [TradingFinder] Support Resistance Signal Alerts🔵 Introduction
The trendline is one of the most essential tools in technical analysis, widely used in financial markets such as Forex, cryptocurrency, and stocks. A trendline is a straight line that connects swing highs or swing lows and visually indicates the market’s trend direction.
Traders use trendlines to identify price structure, the strength of buyers and sellers, dynamic support and resistance zones, and optimal entry and exit points.
In technical analysis, trendlines are typically classified into three categories: uptrend lines (drawn by connecting higher lows), downtrend lines (formed by connecting lower highs), and sideways trends (moving horizontally). A valid trendline usually requires at least three confirmed touchpoints to be considered reliable for trading decisions.
Trendlines can serve as the foundation for a variety of trading strategies, such as the trendline bounce strategy, valid breakout setups, and confluence-based analysis with other tools like candlestick patterns, divergences, moving averages, and Fibonacci levels.
Additionally, trendlines are categorized into internal and external, and further into major and minor levels, each serving unique roles in market structure analysis.
🔵 How to Use
Trendlines are a key component in technical analysis, used to identify market direction, define dynamic support and resistance zones, highlight strategic entry and exit points, and manage risk. For a trendline to be reliable, it must be drawn based on structural principles—not by simply connecting two arbitrary points.
🟣 Selecting Pivot Types Based on Trend Direction
The first step is to determine the market trend: uptrend, downtrend, or sideways.
Then, choose pivot points that match the trend type :
In an uptrend, trendlines are drawn by connecting low pivots, especially higher lows.
In a downtrend, trendlines are formed by connecting high pivots, specifically lower highs.
It is crucial to connect pivots of the same type and structure to ensure the trendline is valid and analytically sound.
🟣 Pivot Classification
This indicator automatically classifies pivot points into two categories :
Major Pivots :
MLL : Major Lower Low
MHL : Major Higher Low
MHH : Major Higher High
MLH : Major Lower High
These define the primary structure of the market and are typically used in broader structural analysis.
Minor Pivots :
mLL: minor Lower Low
mHL: minor Higher Low
mHH: minor Higher High
mLH: minor Lower High
These are used for drawing more precise trendlines within corrective waves or internal price movements.
Example : In a downtrend, drawing a trendline from an MHH to an mHH creates structural inconsistency and introduces noise. Instead, connect points like MHL to MHL or mLH to mLH for a valid trendline.
🟣 Drawing High-Precision Trendlines
To ensure a reliable trendline :
Use pivots of the same classification (Major with Major or Minor with Minor).
Ensure at least three valid contact points (three touches = structural confirmation).
Draw through candles with the least deviation (choose wicks or bodies based on confluence).
Preferably draw from right to left for better alignment with current market behavior.
Use parallel lines to turn a single trendline into a trendline zone, if needed.
🟣 Using Trendlines for Trade Entries
Bounce Entry: When price approaches the trendline and shows signs of reversal (e.g., a reversal candle, divergence, or support/resistance), enter in the direction of the trend with a logical stop-loss.
Breakout Entry: When price breaks through the trendline with strong momentum and a confirmation (such as a retest or break of structure), consider trading in the direction of the breakout.
🟣 Trendline-Based Risk Management
For bounce entries, the stop-loss is placed below the trendline or the last pivot low (in an uptrend).
For breakout entries, the stop-loss is set behind the breakout candle or the last structural level.
A broken trendline can also act as an exit signal from a trade.
🟣 Combining Trendlines with Other Tools (Confluence)
Trendlines gain much more strength when used alongside other analytical tools :
Horizontal support and resistance levels
Moving averages (such as EMA 50 or EMA 200)
Fibonacci retracement zones
Candlestick patterns (e.g., Engulfing, Pin Bar)
RSI or MACD divergences
Market structure breaks (BoS / ChoCH)
🔵 Settings
Pivot Period : This defines how sensitive the pivot detection is. A higher number means the algorithm will identify more significant pivot points, resulting in longer-term trendlines.
Alerts
Alert :
Enable or disable the entire alert system
Set a custom alert name
Choose how often alerts trigger (every time, once per bar, or on bar close)
Select the time zone for alert timestamps (e.g., UTC)
Each trendline type supports two alert types :
Break Alert : Triggered when price breaks the trendline
React Alert : Triggered when price reacts or bounces off the trendline
These alerts can be independently enabled or disabled for all trendline categories (Major/Minor, Internal/External, Up/Down).
Display :
For each of the eight trendline types, you can control :
Whether to show or hide the line
Whether to delete the previous line when a new one is drawn
Color, line style (solid, dashed, dotted), extension direction (e.g., right only), and width
Major lines are typically thicker and more opaque, while minor lines appear thinner and more transparent.
All settings are designed to give the user full control over the appearance, behavior, and alert system of the indicator, without requiring manual drawing or adjustments.
🔵 Conclusion
A trendline is more than just a line on the chart—it is a structural, strategic, and flexible tool in technical analysis that can serve as the foundation for understanding price behavior and making trading decisions. Whether in trending markets or during corrections, trendlines help traders identify market direction, key zones, and high-potential entry and exit points with precision.
The accuracy and effectiveness of a trendline depend on using structurally valid pivot points and adhering to proper market logic, rather than relying on guesswork or personal bias.
This indicator is built to solve that exact problem. It automatically detects and draws multiple types of trendlines based on actual price structure, separating them into Major/Minor and Internal/External categories, and respecting professional analytical principles such as pivot type, trend direction, and structural location.
iD EMARSI on ChartSCRIPT OVERVIEW
The EMARSI indicator is an advanced technical analysis tool that maps RSI values directly onto price charts. With adaptive scaling capabilities, it provides a unique visualization of momentum that flows naturally with price action, making it particularly valuable for FOREX and low-priced securities trading.
KEY FEATURES
1 PRICE MAPPED RSI VISUALIZATION
Unlike traditional RSI that displays in a separate window, EMARSI plots the RSI directly on the price chart, creating a flowing line that identifies momentum shifts within the context of price action:
// Map RSI to price chart with better scaling
mappedRsi = useAdaptiveScaling ?
median + ((rsi - 50) / 50 * (pQH - pQL) / 2 * math.min(1.0, 1/scalingFactor)) :
down == pQL ? pQH : up == pQL ? pQL : median - (median / (1 + up / down))
2 ADAPTIVE SCALING SYSTEM
The script features an intelligent scaling system that automatically adjusts to different market conditions and price levels:
// Calculate adaptive scaling factor based on selected method
scalingFactor = if scalingMethod == "ATR-Based"
math.min(maxScalingFactor, math.max(1.0, minTickSize / (atrValue/avgPrice)))
else if scalingMethod == "Price-Based"
math.min(maxScalingFactor, math.max(1.0, math.sqrt(100 / math.max(avgPrice, 0.01))))
else // Volume-Based
math.min(maxScalingFactor, math.max(1.0, math.sqrt(1000000 / math.max(volume, 100))))
3 MODIFIED RSI CALCULATION
EMARSI uses a specially formulated RSI calculation that works with an adaptive base value to maintain consistency across different price ranges:
// Adaptive RSI Base based on price levels to improve flow
adaptiveRsiBase = useAdaptiveScaling ? rsiBase * scalingFactor : rsiBase
// Calculate RSI components with adaptivity
up = ta.rma(math.max(ta.change(rsiSourceInput), adaptiveRsiBase), emaSlowLength)
down = ta.rma(-math.min(ta.change(rsiSourceInput), adaptiveRsiBase), rsiLengthInput)
// Improved RSI calculation with value constraint
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
4 MOVING AVERAGE CROSSOVER SYSTEM
The indicator creates a smooth moving average of the RSI line, enabling a crossover system that generates trading signals:
// Calculate MA of mapped RSI
rsiMA = ma(mappedRsi, emaSlowLength, maTypeInput)
// Strategy entries
if ta.crossover(mappedRsi, rsiMA)
strategy.entry("RSI Long", strategy.long)
if ta.crossunder(mappedRsi, rsiMA)
strategy.entry("RSI Short", strategy.short)
5 VISUAL REFERENCE FRAMEWORK
The script includes visual guides that help interpret the RSI movement within the context of recent price action:
// Calculate pivot high and low
pQH = ta.highest(high, hlLen)
pQL = ta.lowest(low, hlLen)
median = (pQH + pQL) / 2
// Plotting
plot(pQH, "Pivot High", color=color.rgb(82, 228, 102, 90))
plot(pQL, "Pivot Low", color=color.rgb(231, 65, 65, 90))
med = plot(median, style=plot.style_steplinebr, linewidth=1, color=color.rgb(238, 101, 59, 90))
6 DYNAMIC COLOR SYSTEM
The indicator uses color fills to clearly visualize the relationship between the RSI and its moving average:
// Color fills based on RSI vs MA
colUp = mappedRsi > rsiMA ? input.color(color.rgb(128, 255, 0), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(240, 9, 9, 95), '', group= 'RSI < EMA', inline= 'dn')
colDn = mappedRsi > rsiMA ? input.color(color.rgb(0, 230, 35, 95), '', group= 'RSI > EMA', inline= 'up') :
input.color(color.rgb(255, 47, 0), '', group= 'RSI < EMA', inline= 'dn')
fill(rsiPlot, emarsi, mappedRsi > rsiMA ? pQH : rsiMA, mappedRsi > rsiMA ? rsiMA : pQL, colUp, colDn)
7 REAL TIME PARAMETER MONITORING
A transparent information panel provides real-time feedback on the adaptive parameters being applied:
// Information display
var table infoPanel = table.new(position.top_right, 2, 3, bgcolor=color.rgb(0, 0, 0, 80))
if barstate.islast
table.cell(infoPanel, 0, 0, "Current Scaling Factor", text_color=color.white)
table.cell(infoPanel, 1, 0, str.tostring(scalingFactor, "#.###"), text_color=color.white)
table.cell(infoPanel, 0, 1, "Adaptive RSI Base", text_color=color.white)
table.cell(infoPanel, 1, 1, str.tostring(adaptiveRsiBase, "#.####"), text_color=color.white)
BENEFITS FOR TRADERS
INTUITIVE MOMENTUM VISUALIZATION
By mapping RSI directly onto the price chart, traders can immediately see the relationship between momentum and price without switching between different indicator windows.
ADAPTIVE TO ANY MARKET CONDITION
The three scaling methods (ATR-Based, Price-Based, and Volume-Based) ensure the indicator performs consistently across different market conditions, volatility regimes, and price levels.
PREVENTS EXTREME VALUES
The adaptive scaling system prevents the RSI from generating extreme values that exceed chart boundaries when trading low-priced securities or during high volatility periods.
CLEAR TRADING SIGNALS
The RSI and moving average crossover system provides clear entry signals that are visually reinforced through color changes, making it easy to identify potential trading opportunities.
SUITABLE FOR MULTIPLE TIMEFRAMES
The indicator works effectively across multiple timeframes, from intraday to daily charts, making it versatile for different trading styles and strategies.
TRANSPARENT PARAMETER ADJUSTMENT
The information panel provides real-time feedback on how the adaptive system is adjusting to current market conditions, helping traders understand why the indicator is behaving as it is.
CUSTOMIZABLE VISUALIZATION
Multiple visualization options including Bollinger Bands, different moving average types, and customizable colors allow traders to adapt the indicator to their personal preferences.
CONCLUSION
The EMARSI indicator represents a significant advancement in RSI visualization by directly mapping momentum onto price charts with adaptive scaling. This approach makes momentum shifts more intuitive to identify and helps prevent the scaling issues that commonly affect RSI-based indicators when applied to low-priced securities or volatile markets.
Liquidity Hunt SwiftEdgeThe "Liquidity Hunt Dashboard By SwiftEdge" indicator is designed to assist traders in identifying potential liquidity zones by placing a dynamic target line based on swing points and weighted liquidity. It leverages technical analysis tools such as SMA (Simple Moving Average), pivot points, and volume to predict market movements and provides daily statistics on hits and success rate. The target line updates automatically when the price hits it, adapting to the market trend (up, down, or neutral). A dashboard displays the current price, target level, prediction, and trend, making it easy to make informed trading decisions.
Features:
Target Line: A yellow dashed line marks the next expected liquidity level (up to approximately 20 pips away on 1m).
Prediction: Displays "Up (Chasing Sell Liquidity)," "Down (Chasing Buy Liquidity)," or "Neutral" based on trend and liquidity.
Daily Statistics: Tracks hits and success rate, resetting daily.
Trend Indicator: Shows market direction ("Up," "Down," or "Neutral") in the dashboard.
Dynamic Updates: The line moves to a new target level when the price hits the current target.
Recommended Settings for 1-Minute Timeframe:
For Indices (e.g., S&P 500):
Lookback Period: 180 (3 hours to capture more stable swing points).
Max Distance (%): 0.015 (approximately 15 pips, suitable for indices).
Cooldown Period: 5 (stabilizes after hits).
Line Duration: 60 (displays the line for 1 hour).
For Crypto (e.g., BTC/USD):
Lookback Period: 120 (2 hours to capture short-term swing points).
Max Distance (%): 0.024 (approximately 20 pips, suitable for volatile crypto markets).
Cooldown Period: 5.
Line Duration: 60.
For Forex (e.g., EUR/USD):
Lookback Period: 180 (3 hours for greater data density in less volatile markets).
Max Distance (%): 0.012 (approximately 10-12 pips, suitable for forex).
Cooldown Period: 5.
Line Duration: 60.
Guide for Higher Timeframes:
This indicator can be adapted for higher timeframes (e.g., 5m, 15m, 1H) by adjusting the settings to account for larger price movements and slower market dynamics. Follow these steps:
Select Your Timeframe: Switch your chart to the desired timeframe (e.g., 5m, 15m, or 1H).
Adjust Lookback Period: Increase the "Lookback Period" to cover a longer historical period. For example:
5m: Set to 360 (equivalent to 6 hours).
15m: Set to 480 (equivalent to 8 hours).
1H: Set to 720 (equivalent to 12 hours).
Adjust Max Distance (%): Higher timeframes require larger targets to account for bigger price swings. For example:
5m: Increase to 0.05 (approximately 50 pips).
15m: Increase to 0.1 (approximately 100 pips).
1H: Increase to 0.2 (approximately 200 pips).
Adjust Cooldown Period: On higher timeframes, you may want a longer cooldown to avoid frequent updates. For example:
5m: Set to 10.
15m: Set to 15.
1H: Set to 20.
Adjust Line Duration: Extend the duration the line is displayed to match the timeframe. For example:
5m: Set to 120 (equivalent to 10 hours).
15m: Set to 240 (equivalent to 60 hours).
1H: Set to 480 (equivalent to 20 days).
Monitor the Dashboard: The dashboard will still show the target level, prediction, and trend, but the values will now reflect the larger timeframe's dynamics.
Usage Instructions:
Set your chart to a 1-minute timeframe (or follow the higher timeframe guide).
Adjust the settings based on the market and timeframe (see recommendations above).
Monitor the dashboard for the current price, target level, and prediction.
Use the yellow line as a potential entry or exit level, and adjust your strategy based on the trend and statistics.
Notes:
This indicator is intended solely for educational and analytical purposes and should not be considered financial advice.
Test the indicator on a demo account before using it with real funds.
The indicator complies with TradingView guidelines by not providing trading advice, automated trading signals, or guarantees of profit.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Bayesian TrendEnglish Description (primary)
1. Overview
This script implements a Naive Bayesian classifier to estimate the probability of an upcoming bullish, bearish, or neutral move. It combines multiple indicators—RSI, MACD histogram, EMA price difference in ATR units, ATR level vs. its average, and Volume vs. its average—to calculate likelihoods for each market direction. Each indicator is “binned” (categorized into discrete zones) and assigned conditional probabilities for bullish/bearish/neutral scenarios. The script then normalizes these probabilities and paints bars in green if bullish is most likely, red if bearish is most likely, or blue if neutral is most likely. A small table is also displayed in the top-right corner of the chart, showing real-time probabilities.
2. How it works
Indicator Calculations: The script calculates RSI, MACD (line and histogram), EMA, ATR, and Volume metrics.
Binning: Each metric is converted into a discrete category (e.g., low, medium, high). For example, RSI < 30 is binned as “low,” while RSI > 70 is binned as “high.”
Conditional Probabilities: User-defined tables specify the conditional probabilities of each bin under three hypotheses (Up, Down, Neutral).
Naive Bayesian Formula: The script multiplies the relevant conditional probabilities, normalizes them, and derives the final probabilities (Up, Down, or Neutral).
Visualization:
Bar Colors: Bars are green when the Up probability exceeds 50%, red for Down, and blue otherwise.
Table: Displays numeric probabilities of Up, Down, and Neutral in percentage terms.
3. How to use it
Add the script to your chart.
Observe the colored bars:
Green suggests a higher probability for bullish movement.
Red suggests a higher probability for bearish movement.
Blue indicates a higher probability of sideways or uncertain conditions.
Check the table in the top-right corner to see exact probabilities (Up/Down/Neutral).
Use the input settings to adjust thresholds (RSI, MACD, Volume, etc.), define alert conditions (e.g., when Up probability crosses 50%), and decide whether to trigger alerts on bar close or in real-time.
4. Originality and usefulness
Originality: This script uniquely applies a Naive Bayesian approach to a blend of classic and volume-based indicators. It demonstrates how different indicator “zones” can be combined to produce probabilistic insights.
Usefulness: Traders can interpret the probability breakdown to gauge the script’s bias. Unlike single indicators, this approach synthesizes several signals, potentially offering a more holistic perspective on market conditions.
5. Limitations
The conditional probabilities are manually assigned and may not reflect actual market behavior across all instruments or timeframes.
Results depend on the user’s choice of thresholds and indicator settings.
Like any indicator, past performance does not guarantee future results. Always confirm signals with additional analysis.
6. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice. Trading involves significant risk, and you should make decisions based on your own analysis. Neither the script’s author nor TradingView is liable for any financial losses.
Русское описание (Russian translation, optional)
Этот индикатор реализует наивный Байесовский классификатор для оценки вероятности предстоящего роста (Up), падения (Down) или бокового движения (Neutral). Он комбинирует несколько индикаторов—RSI, гистограмму MACD, разницу цены и EMA в единицах ATR, уровень ATR относительно своего среднего значения и объём относительно своего среднего—чтобы вычислить вероятности для каждого направления рынка. Каждый индикатор делится на «зоны» (low, mid, high), которым приписаны условные вероятности для бычьего/медвежьего/нейтрального исхода. Скрипт нормирует эти вероятности и раскрашивает бары в зелёный, красный или синий цвет в зависимости от того, какая вероятность выше. Также в правом верхнем углу отображается таблица с текущими значениями вероятностей.
Inside/Outside Bar Direction Highlighter
Here’s a trading indicator in Pine Script (v6) that combines the essence of the Inside Bar, Outside Bar, and directional patterns inspired by TT3 Theory. This indicator highlights bars based on their classification as inside, outside, or directional and provides potential trade signals.
Inside Outside Indicator
Explanation:
Bar Classification:
Inside Bar: Current high is less than the previous high, and the low is greater than the previous low.
Outside Bar: Current high exceeds the previous high, and the low breaks below the previous low.
Up/Down Bars: Closing prices relative to the previous high/low.
Visual Highlights:
Bars are visually highlighted with colors for easy identification.
Trade Signals:
Long Signal: When the close crosses above the previous high and it's a directional up bar.
Short Signal: When the close crosses below the previous low and it's a directional down bar.
Customizable Inputs:
Colors for inside, outside, up, and down bars can be modified.
You can copy and paste this script into the Pine Editor on TradingView to see it in action. Adjust the logic to fit your trading strategy as needed.
You said:
summary of how to use this indicator without buy/sell signal
ChatGPT said:
ChatGPT
How to Use the Inside/Outside Bar Direction Highlighter Indicator (Without Buy/Sell Signals)
Understand the Bar Classifications:
Inside Bars: Highlighted in blue (default). These indicate periods of market consolidation. Look for potential breakouts in either direction.
Outside Bars: Highlighted in orange (default). These represent increased volatility, where both higher highs and lower lows are made. Watch for reversals or continuations based on broader trends.
Directional Up Bars: Highlighted in green (default). These occur when the current close is above the previous high, signaling bullish momentum.
Directional Down Bars: Highlighted in red (default). These occur when the current close is below the previous low, indicating bearish momentum.
Identify Key Patterns:
Use the highlighted bars to spot price action setups, such as:
Breakouts from inside bars.
Reversal signals following outside bars.
Continuation patterns when directional bars align with the trend.
Combine with Your Analysis:
Trend Analysis: Match bar classifications with trend direction on larger timeframes (e.g., daily, 4-hour).
Support/Resistance: Use inside and outside bars near key levels for confirmation or reversal signals.
Volume: Higher volume on directional bars strengthens the momentum signal.
Customize the Colors:
Adjust the bar highlight colors to fit your chart theme for better visibility.
No Automatic Signals:
This indicator doesn’t provide explicit buy/sell recommendations. Instead, use the visual highlights to make informed decisions based on your trading strategy.
By interpreting these bar patterns, you can better gauge market behavior and make more confident decisions without relying on preset signals.
Kalman PredictorThe **Kalman Predictor** indicator is a powerful tool designed for traders looking to enhance their market analysis by smoothing price data and projecting future price movements. This script implements a Kalman filter, a statistical method for noise reduction, to dynamically estimate price trends and velocity. Combined with ATR-based confidence bands, it provides actionable insights into potential price movement, while offering clear trend and momentum visualization.
---
#### **Key Features**:
1. **Kalman Filter Smoothing**:
- Dynamically estimates the current price state and velocity to filter out market noise.
- Projects three future price levels (`Next Bar`, `Next +2`, `Next +3`) based on velocity.
2. **Dynamic Confidence Bands**:
- Confidence bands are calculated using ATR (Average True Range) to reflect market volatility.
- Visualizes potential price deviation from projected levels.
3. **Trend Visualization**:
- Color-coded prediction dots:
- **Green**: Indicates an upward trend (positive velocity).
- **Red**: Indicates a downward trend (negative velocity).
- Dynamically updated label displaying the current trend and velocity value.
4. **User Customization**:
- Inputs to adjust the process and measurement noise for the Kalman filter (`q` and `r`).
- Configurable ATR multiplier for confidence bands.
- Toggleable trend label with adjustable positioning.
---
#### **How It Works**:
1. **Kalman Filter Core**:
- The Kalman filter continuously updates the estimated price state and velocity based on real-time price changes.
- Projections are based on the current price trend (velocity) and extend into the future (Next Bar, +2, +3).
2. **Confidence Bands**:
- Calculated using ATR to provide a dynamic range around the projected future prices.
- Indicates potential volatility and helps traders assess risk-reward scenarios.
3. **Trend Label**:
- Updates dynamically on the last bar to show:
- Current trend direction (Up/Down).
- Velocity value, providing insight into the expected magnitude of the price movement.
---
#### **How to Use**:
- **Trend Analysis**:
- Observe the direction and spacing of the prediction dots relative to current candles.
- Larger spacing indicates a potential strong move, while clustering suggests consolidation.
- **Risk Management**:
- Use the confidence bands to gauge potential price volatility and set stop-loss or take-profit levels accordingly.
- **Pullback Detection**:
- Look for flattening or clustering of dots during trends as a signal of potential pullbacks or reversals.
---
#### **Customizable Inputs**:
- **Kalman Filter Parameters**:
- `lookback`: Adjusts the smoothing window.
- `q`: Process noise (higher values make the filter more reactive to changes).
- `r`: Measurement noise (controls sensitivity to price deviations).
- **Confidence Bands**:
- `band_multiplier`: Multiplies ATR to define the range of confidence bands.
- **Visualization**:
- `show_label`: Option to toggle the trend label.
- `label_offset`: Adjusts the label’s distance from the price for better visibility.
---
#### **Examples of Use**:
- **Scalping**: Use on lower timeframes (e.g., 1-minute, 5-minute) to detect short-term price trends and reversals.
- **Swing Trading**: Identify pullbacks or continuations on higher timeframes (e.g., 4-hour, daily) by observing the prediction dots and confidence bands.
- **Risk Assessment**: Confidence bands help visualize potential price volatility, aiding in the placement of stops and targets.
---
#### **Notes for Traders**:
- The **Kalman Predictor** does not predict the future with certainty but provides a statistically informed estimate of price movement.
- Confidence bands are based on historical volatility and should be used as guidelines, not guarantees.
- Always combine this tool with other analysis techniques for optimal results.
---
This script is open-source, and the Kalman filter logic has been implemented uniquely to integrate noise reduction with dynamic confidence band visualization. If you find this indicator useful, feel free to share your feedback and experiences!
---
#### **Credits**:
This script was developed leveraging the statistical principles of Kalman filtering and is entirely original. It incorporates ATR for dynamic confidence band calculations to enhance trader usability and market adaptability.
lib_momentumLibrary "lib_momentum"
This library calculates the momentum, derived from a sample range of prior candles. Depending on set MomentumType it either deduces the momentum from the price, volume, or a product of both. If price/product are selected, you can choose from SampleType if only candle body, full range from high to low or a combination of both (body counts full, wicks half for each direction) should be used. Optional: You can choose to normalize the results, dividing each value by its average (normalization_ma_length, normalization_ma). This will allow comparison between different instruments. For the normalization Moving Average you can choose any currently supported in my lib_no_delay.
get_momentum(momentum_type, sample_type, sample_length, normalization_ma_length, normalization_ma)
Parameters:
momentum_type (series MomentumType) : select one of MomentumType. to sample the price, volume or a product of both
sample_type (series SampleType) : select one of SampleType. to sample the body, total range from high to low or a combination of both (body count full, wicks half for each direction)
sample_length (simple int) : how many candles should be sampled (including the current)
normalization_ma_length (simple int) : if you want to normalize results (momentum / momentum average) this sets the period for the average. (default = 0 => no normalization)
normalization_ma (simple MovingAverage enum from robbatt/lib_no_delay/9) : is the type of moving average to normalize / compare with
Returns: returns the current momentum where the total line is not just (up - down) but also sampled over the sample_length and can therefore be used as trend indicator. If up/down fail to reach total's level it's a sign of decreasing momentum, if up/down exceed total the trend it's a sign of increasing momentum.
TrigWave Suite [InvestorUnknown]The TrigWave Suite combines Sine-weighted, Cosine-weighted, and Hyperbolic Tangent moving averages (HTMA) with a Directional Movement System (DMS) and a Relative Strength System (RSS).
Hyperbolic Tangent Moving Average (HTMA)
The HTMA smooths the price by applying a hyperbolic tangent transformation to the difference between the price and a simple moving average. It also adjusts this value by multiplying it by a standard deviation to create a more stable signal.
// Function to calculate Hyperbolic Tangent
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
// Function to calculate Hyperbolic Tangent Moving Average
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Sine-Weighted Moving Average (SWMA)
The SWMA applies sine-based weights to historical prices. This gives more weight to the central data points, making it responsive yet less prone to noise.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * src
swma
Cosine-Weighted Moving Average (CWMA)
The CWMA uses cosine-based weights for data points, which produces a more stable trend-following behavior, especially in low-volatility markets.
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * src
cwma
Directional Movement System (DMS)
DMS is used to identify trend direction and strength based on directional movement. It uses ADX to gauge trend strength and combines +DI and -DI for directional bias.
// Function to calculate Directional Movement System
f_DMS(simple int dmi_len, simple int adx_len) =>
up = ta.change(high)
down = -ta.change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
trur = ta.rma(ta.tr, dmi_len)
plus = fixnan(100 * ta.rma(plusDM, dmi_len) / trur)
minus = fixnan(100 * ta.rma(minusDM, dmi_len) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adx_len)
dms_up = plus > minus and adx > minus
dms_down = plus < minus and adx > plus
dms_neutral = not (dms_up or dms_down)
signal = dms_up ? 1 : dms_down ? -1 : 0
Relative Strength System (RSS)
RSS employs RSI and an adjustable moving average type (SMA, EMA, or HMA) to evaluate whether the market is in a bullish or bearish state.
// Function to calculate Relative Strength System
f_RSS(rsi_src, rsi_len, ma_type, ma_len) =>
rsi = ta.rsi(rsi_src, rsi_len)
ma = switch ma_type
"SMA" => ta.sma(rsi, ma_len)
"EMA" => ta.ema(rsi, ma_len)
"HMA" => ta.hma(rsi, ma_len)
signal = (rsi > ma and rsi > 50) ? 1 : (rsi < ma and rsi < 50) ? -1 : 0
ATR Adjustments
To minimize false signals, the HTMA, SWMA, and CWMA signals are adjusted with an Average True Range (ATR) filter:
// Calculate ATR adjusted components for HTMA, CWMA and SWMA
float atr = ta.atr(atr_len)
float htma_up = htma + (atr * atr_mult)
float htma_dn = htma - (atr * atr_mult)
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
This adjustment allows for better adaptation to varying market volatility, making the signal more reliable.
Signals and Trend Calculation
The indicator generates a Trend Signal by aggregating the output from each component. Each component provides a directional signal that is combined to form a unified trend reading. The trend value is then converted into a long (1), short (-1), or neutral (0) state.
Backtesting Mode and Performance Metrics
The Backtesting Mode includes a performance metrics table that compares the Buy and Hold strategy with the TrigWave Suite strategy. Key statistics like Sharpe Ratio, Sortino Ratio, and Omega Ratio are displayed to help users assess performance. Note that due to labels and plotchar use, automatic scaling may not function ideally in backtest mode.
Alerts and Visualization
Trend Direction Alerts: Set up alerts for long and short signals
Color Bars and Gradient Option: Bars are colored based on the trend direction, with an optional gradient for smoother visual feedback.
Important Notes
Customization: Default settings are experimental and not intended for trading/investing purposes. Users are encouraged to adjust and calibrate the settings to optimize results according to their trading style.
Backtest Results Disclaimer: Please note that backtest results are not indicative of future performance, and no strategy guarantees success.
Breakout LevelsBreakout Levels Indicator
The Breakout Levels indicator is a tool designed to help traders identify potential breakout points based on a specified time range and market volatility. By combining user-defined time frames with Average True Range (ATR) calculations, it provides actionable entry and stop-loss levels for both upward and downward breakouts. Additionally, it includes risk management features to calculate appropriate position sizes based on your account capital and risk tolerance.
Key Features
Custom Time Range Selection: Define a specific period during which the indicator calculates the highest high and lowest low to establish breakout levels.
ATR-Based Calculations: Use the ATR to adjust entry and stop-loss levels according to market volatility.
Risk Management: Automatically calculate position sizes based on your account capital and desired risk per trade.
Indicator Inputs
Start Time : The beginning of the time range for calculating the highest high and lowest low.
End Time : The end of the time range.
Entry Multiplier: A factor that determines how far the entry level is from the breakout level, scaled by the ATR.
Stop-Loss Multiplier: A factor that determines the distance of the stop-loss from the entry level, scaled by the ATR.
Risk per Trade (%) : The percentage of your account capital you're willing to risk on each trade.
Account Capital : Your total trading capital used for position size calculations.
ATR Length : The number of periods over which the ATR is calculated.
Position Size Up / Down : Shows you Lot size to maintain no loss more than allowed percentage at that entry
Volumetric Volatility Blocks [UAlgo]The Volumetric Volatility Blocks indicator is designed to identify significant volatility blocks based on price and volume data. It utilizes a combination of the Average True Range (ATR) and Simple Moving Average (SMA) to determine the volatility level and identify periods of heightened market activity. The indicator highlights these volatility blocks, providing traders with visual cues for potential trading opportunities. It differentiates between bullish and bearish volatility by analyzing price movement and volume, offering a nuanced view of market sentiment. This tool is particularly useful for traders looking to capitalize on periods of high volatility and momentum shifts.
🔶 Key Features
Volatility Measurement Length: Controls the period used to calculate the ATR.
Smooth Length of Volatility: Defines the period for the SMA used to smooth the ATR.
Multiplier of SMA: Sets the minimum threshold for the ATR to be considered a "high volatility" block.
Show Last X Volatility Blocks: Determines how many of the most recent volatility blocks are displayed on the chart.
Mitigation Method: Choose between "Close" or "Wick" price to filter volatility blocks based on price action. This helps avoid highlighting blocks broken by the chosen price level.
Volume Info: Displaying the volume associated with each block.
Up/Down Block Color: Sets the color for bullish and bearish volatility blocks.
🔶 Usage
The Volumetric Volatility Blocks indicator visually represents periods of high volatility with blocks on the chart. Green blocks indicate bullish volatility, while red blocks indicate bearish volatility.
Bullish Volatility Blocks: When the ATR surpasses the smoothed ATR multiplied by the set multiplier, and the price closes higher than it opened, a bullish block is formed. These blocks are generally used to identify potential buying opportunities as they indicate upward momentum.
Bearish Volatility Blocks: Conversely, bearish blocks form under the same conditions, but when the price closes lower than it opened. These blocks can signal potential selling opportunities as they highlight downward momentum.
Volume Information: Each block can display volume data, providing insight into the strength of the market movement. The percentage shown on the block indicates the relative volume contribution of that block, helping traders assess the significance of the volatility.
The volume percentages in the Volumetric Volatility Blocks indicator are calculated based on the total volume of the most recent volatility blocks. For each of the most recent volatility blocks, the percentage of the total volume is calculated by dividing the block's volume by the total volume:
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Multi-Timeframe Trend IndicatorMulti-Timeframe Trend Indicator
The “Multi-Timeframe Trend Indicator” is a versatile tool designed to help traders identify trends across multiple timeframes using Exponential Moving Averages (EMAs). This indicator is suitable for both novice and experienced traders. It allows users to customize the lengths of the short and long EMAs, providing a clear visualization of the trend direction (UP, DOWN, SIDE) for various intervals including 1 minute, 5 minutes, 15 minutes, 30 minutes, 1 hour, and 4 hours. The indicator offers extensive customization options, enabling adjustments for table position, colors, and more to suit individual trading preferences.
How the Calculation Works
The Multi-Timeframe Trend Indicator uses EMAs to calculate trends. EMAs give more weight to recent prices, making them responsive to new information. The short EMA, calculated over a shorter period, reacts quickly to price changes, while the long EMA, calculated over a longer period, smooths out fluctuations to show the overall trend.
For each timeframe, the indicator calculates both the short EMA and the long EMA. If the short EMA is above the long EMA, the trend is considered “UP”. If the short EMA is below the long EMA, the trend is “DOWN”. If the absolute difference between the short and long EMAs is within a user-defined threshold, the trend is classified as “SIDE” (sideways).
This calculation is repeated for multiple timeframes: 1 minute, 5 minutes, 15 minutes, 30 minutes, 1 hour, and 4 hours. The results are displayed in a table, providing a comprehensive view of the trend direction across different timeframes.
How the Code Works
Input Parameters: Users can input the lengths of the short and long EMAs and the threshold for identifying sideways trends. These inputs allow for a high degree of customization to match individual trading strategies.
Trend Calculation Function: The trend function calculates the trend direction based on the EMAs. It uses the math.abs function to find the absolute difference between the EMAs and determines if the trend is “UP”, “DOWN”, or “SIDE” based on the threshold.
Requesting Data for Multiple Timeframes: The script uses the request.security function to fetch price data and calculate the EMAs for different timeframes independently of the current chart timeframe. This ensures consistency in trend analysis regardless of the displayed timeframe.
Creating and Updating the Table: A table is created to display the trend directions for each timeframe. The table’s position and appearance can be customized. The trend data for each timeframe is color-coded (green for UP, red for DOWN, gray for SIDE) and displayed in the table.
Customization Options: Users can customize the colors, table position, and EMA lengths through the indicator settings, providing flexibility to adapt the indicator to their trading style.
Disclaimer
This indicator is for informational purposes only and should not be considered financial advice. It does not predict future price movements and does not guarantee accurate trend calculations, as market conditions can vary. Trading involves substantial risk and is not suitable for everyone. Always conduct your own research before making any trading decisions.
Perfect Order Alert USDJPY/BTCUSD/XAUUSDPerfect Order Alert USDJPY/BTCUSD/XAUUSD 日本語解説は下記
This indicator detects the perfect order of three moving averages and displays on the Panel in an easy-to-understand visual manner whether there is an uptrend, downtrend, or non-trend for each time leg.
This indicator detects perfect orders for the three currency pairs USDJPY/BTCUSD/XAUUSD on the 5-minute, 15-minute, 1-hour, and 4-hour time frames, and displays them on the Panel on the chart, with “▲” for up, “▼” for down, and “ー” for non-trend, so that you can quickly determine the trend. The panel is displayed on the chart.
In order to check for perfect orders without missing them, it is also possible to set up alerts that notify you of all the time frames and currency pairs as well.
Functions
Displaying 4H, 1H, 15M, 5M, up (▲), down (▼), other (-), of USDJPY/BTCUSD/XAUUSD on the panel.
*(By default, 20EMA, 75EMA, and 200EMA are hidden.)
Display position setting of the panel (You can choose from upper left, upper top, upper right, lower left, lower bottom, or lower right).
Panel color and text color change function
The moving average line can be hidden by default.
Moving average period change
Moving average color and thickness can be changed.
EMA/SMA switchable
Alert function - One alert can be set for each currency pair and time frame ▲▼, which is very useful.
Perfect Order Alert
You can use it even if you have a free account with only one alert setting.
To use the alert function, go to the Tradingview default alert settings, select “USDJPY/BTCUSD/XAUUSD” for the top item of conditions, and select “Call Alert() function” in the frame just below it!
_* Supplementary explanation: ＿＿＿＿＿＿＿＿＿＿＿＿
Please note that due to the limitation of the script, only 3 currency pairs and 4 time frames are displayed with 12 items (Panels for currency pairs other than USDJPY/BTCUSD/XAUUSD are also created, but they are indicators for other scripts, so if you are interested in other currency pairs, please use those. If you are interested in other currency pairs, please use them.)
Please note that we may change the functions or delete the indicator itself without prior notice.
Translated with DeepL.com (free version)
Reference image of the setting screenReference image of the setting screen
設定画面参考画像
3本の移動平均線のパーフェクトオーダーを検知し、時間足ごとに上昇トレンドか下降トレンドかノントレンドかを視覚的にわかりやすくPanelに表示するインジゲーターです。
このインジゲーターは、USDJPY/BTCUSD/XAUUSDの３通貨ペアの５分足、15分足、１時間足、４時間足のパーフェクトオーダーを検知して、チャートに表示されるPanelに、上昇は「▲」下降は「▼」ノントレンドは「ー」と、すぐに判断できる表示にしてあります。
パーフェクトオーダーを逃さずチェックできるように、それぞれの時間足や通貨ペアも全てを通知してくれるアラート設定が可能なのも特徴です。
機能紹介
・USDJPY/BTCUSD/XAUUSDの4H,1H,15M,5M,の上昇(▲),下降(▼),その他(-),をパネルに表示
※(デフォルトでは20EMA,75EMA,200EMAの３本で非表示にしてあります）
・パネルの表示位置設定（左上、上、右上、左下、下、右下、から選択できます。）
・パネルの色とテキスト色変更機能
・移動平均線表示非表示機能（デフォルトでは表示OFFにしてあります。）
・移動平均線期間変更
・移動平均線色と太さ変更
・EMA/SMA切り替え可能
・アラート機能ー１つのアラート設定で通貨ペアと時間足▲▼一つ一つを細かく教えてくれるので便利。
※パーフェクト オーダーアラート
無料アカウントで１つしかアラート設定できなくても使えます。
アラート機能はTradingviewデフォルトのアラート設定から、条件の一番上の項目を「USDJPY/BTCUSD/XAUUSD」選択、そのすぐ下の枠に「Alert()関数の呼び出し」を選択でOK！
＿※ 補足説明＿＿＿＿＿＿＿＿＿＿＿＿
・スクリプトの制限の為、３通貨ペアと４つの時間足の１２項目で表示させていますのでご了承ください
(USDJPY/BTCUSD/XAUUSD以外の通貨ペアのPanelも作成していますが別スクリプトのインジゲーターになりますので他の通貨ペアも興味がある方はそちらをお使いください）
・予告なしで機能の変更やインジゲーター自体の削除等行う事もあるかもなのでご了承ください。
DMI ForLoop [InvestorUnknown]Overview
This indicator utilizes the Directional Movement Index (DMI) combined with a for-loop to provide a robust trend analysis (ADX is not a part of this indicator).
Settings
DMI ForLoop Settings:
Start Length (a): The initial length for DMI calculation (inclusive).
End Length (b): The final length for DMI calculation (inclusive).
EMA Length (c): The length for the Exponential Moving Average applied to the DMI values, in order so smoothen the signal.
Signal Settings:
Signal Mode: Determines the mode of signal calculation. Options are "Fast", "Slow", "Thresholds Crossing", and "Fast Threshold". Default is "Fast".
1. Slow: is a simple crossing of the midline (0).
2. Fast: positive signal depends if the current "DMIema" is above "DMIema " or above 0.99, otherwise the signal is negative.
3. Thresholds Crossing: simple ta.crossover and ta.crossunder of the user defined threshold for Long and Short.
4. Fast Threshold: signal changes if the value of "DMIema" changes by more than user defined threshold against the current signal.
// Slow
dmicol1 = DMIema > 0 ? colup : coldn
// Fast
dmicol2 = DMIema > DMIema or DMIema > 0.99 ? colup : coldn
// Thresholds Crossing
var color dmicol3 = na
if ta.crossover(DMIema,longth)
dmicol3 := colup
if ta.crossunder(DMIema,shortth)
dmicol3 := coldn
// Fast Threshold
var color dmicol4 = na
if (DMIema > DMIema + fastth)
dmicol4 := colup
if (DMIema < DMIema - fastth)
dmicol4 := coldn
color dmicol = na
if sigmode == "Slow"
dmicol := dmicol1
if sigmode == "Fast"
dmicol := dmicol2
if sigmode == "Thresholds Crossing"
dmicol := dmicol3
if sigmode == "Fast Threshold"
dmicol := dmicol4
else
na
Functionality
The DMI ForLoop indicator calculates an array of DMI values over a specified range of lengths, then averages these values and applies an EMA for smoothing. The result is a dynamic trend indicator that adapts to market conditions.
DMI Calculation:
The indicator iterates through lengths from Start Length to End Length, calculating the positive and negative directional movement (DM) for each period and calculates the average of all the signals at the end. A custom function version of the DMI is used here in order to use DMI with "series" inputs.
// Function to calculate an array of DMI values over a range of lengths
DMIArray(a, b, c) =>
// Initialize an array to store DMI values, with size based on the range (b - a + 1)
var dmiArray = array.new_float(b - a + 1, 0.0)
// Loop through each length from a to b
for x = 0 to (b - a)
// Calculate the smoothing factor alpha for the current length
alpha = 1.0 / (a + x)
// Initialize variables for positive and negative DM
float plus = na
float minus = na
// Calculate the up and down movements
up = ta.change(high)
down = -ta.change(low)
// Determine the positive DM (plusDM)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
// Determine the negative DM (minusDM)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
// Calculate the smoothed positive DM using either SMA or EMA
plus := na(plus ) ? ta.sma(plusDM, (a + x)) : alpha * plusDM + (1 - alpha) * nz(plus )
// Calculate the smoothed negative DM using either SMA or EMA
minus := na(minus ) ? ta.sma(minusDM, (a + x)) : alpha * minusDM + (1 - alpha) * nz(minus )
// Determine the trend direction: 1 for positive trend, -1 for negative trend, 0 for no trend
trend = plus > minus ? 1 : plus < minus ? -1 : 0
// Store the trend value in the DMI array
array.set(dmiArray, x, trend)
// Calculate the average of the DMI array
dmiAvg = array.avg(dmiArray)
// Apply an EMA to the average DMI value
DMIema = ta.ema(dmiAvg, c)
// Return the DMI array, its average, and the EMA of the average
// Call the DMIArray function with the input parameters and assign the results to variables
= DMIArray(a, b, c)
This indicator is versatile and can be tailored to fit various trading/investing strategies by adjusting the input parameters and signal modes.
Buy-Sell Volume Bar Gauge [By MUQWISHI]▋ INTRODUCTION :
The Buy-Sell Volume Bar Gauge is developed to provide traders with a detailed analysis of volume in bars using a low timeframe, such as a 1-second interval, to measure the dominance of buy and sell for each bar. By highlighting the balance between buying and selling activities, the Buy-Sell Volume Bar Gauge helps traders identify potential volume momentum of a bar; aimed at being a useful tool for day traders and scalpers.
_______________________
▋ OVERVIEW:
_______________________
▋ METHODOLOGY:
The concept is based on bars from a lower timeframe within the current chart timeframe bar, where volume is categorized into Up, Down, and Neutral Volume, with each one displayed as a portion of a column plot. Up Volume is recorded when the price experiences a positive change, Down Volume occurs when the price experiences a negative change, and Neutral Volume is observed when the price shows no significant change.
_______________________
▋ INDICATOR SETTINGS:
(1) Fetch data from the selected lower timeframe. Note: If the selected timeframe is invalid (higher than chart), the indicator will automatically switch to 1 second.
(2) Price Source.
(3) Treating Neutral Data (Price Source) as
Neutral: In a lower timeframe, when the bar has no change in its price, the volume is counted as Neutral Volume.
Previous Move: In a lower timeframe, when the bar has no change in its price, the volume is counted as the previous change; “Up Volume” if the previous change was positive, and “Down Volume” if the previous change was negative.
Opposite Previous Move: In a lower timeframe, when the bar has no change in its price, the volume is counted as the opposite previous change; “Up Volume” if the previous change was negative, and “Down Volume” if the previous change was positive.
(4) Average Volume Length, it's used for lighting/darkening columns in a plot.
(5) Enable Alert.
(7) Total bought (%) Level.
(8) Total Sold (%) Level.
_____________________
▋ COMMENT:
The Buy-Sell Volume Bar Gauge can be taken as confirmation for predicting the next move, but it should not be considered a major factor in making a trading decision.
Enhanced Volume by SR7SiddharthaRay007's Enhanced Volume Indicator works on any Timeframe
⦿ Volume Labels:
1. Current Volume, Volume Change%, Average Volume, Average Doller Volume, Up/Down Ratio, ADR%.
=>Average value can be changed using 'Lookback Length' (Default: 20)
⦿ Simple Moving Average: MA (Default: 50). Color of MA changes based on the up down volume ratio.
1. Up/Down Ratio > 1: Blue
2. Up/Down Ratio < 1: Orange
⦿ Volume Bar Colors:
1. High Relative Volume Positive Candle: Lime Green .
2. High Relative Volume Negative Candle: Red .
3. Normal Volume Positive Candle: Blue .
4. Normal Volume Negative Candle: Fuchsia .
5. Low Relative Volume Positive/Negative Candle: Orange .
=>High Relative Volume > 300% of Average Volume; Low Relative Volume < 30% of Average Volume
⦿ Pocket Pivot (A pocket pivot is an up day with volume greater than any of the down days volume in the past 10 days)
1. 10 day Pocket Pivots: Lime Green Diamond below volume bar
2. 5 day Pocket Pivots: Blue Diamond below volume bar
⦿ 'Highest Volume (HV) ' on top of the Volume Bar:
1. Highest Volume Ever (HVE)
2. Highest Volume in Over a Year (HVY)
⦿ Projected Volume Bar: Aqua
⦿ Plot a line at 2x and 3x Average Volume and set Alerts
Statistics • Chi Square • P-value • SignificanceThe Statistics • Chi Square • P-value • Significance publication aims to provide a tool for combining different conditions and checking whether the outcome is significant using the Chi-Square Test and P-value.
🔶 USAGE
The basic principle is to compare two or more groups and check the results of a query test, such as asking men and women whether they want to see a romantic or non-romantic movie.
–––––––––––––––––––––––––––––––––––––––––––––
| | ROMANTIC | NON-ROMANTIC | ⬅︎ MOVIE |
–––––––––––––––––––––––––––––––––––––––––––––
| MEN | 2 | 8 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
| WOMEN | 7 | 3 | 10 |
–––––––––––––––––––––––––––––––––––––––––––––
|⬆︎ SEX | 10 | 10 | 20 |
–––––––––––––––––––––––––––––––––––––––––––––
We calculate the Chi-Square Formula, which is:
Χ² = Σ ( (Observed Value − Expected Value)² / Expected Value )
In this publication, this is:
chiSquare = 0.
for i = 0 to rows -1
for j = 0 to colums -1
observedValue = aBin.get(i).aFloat.get(j)
expectedValue = math.max(1e-12, aBin.get(i).aFloat.get(colums) * aBin.get(rows).aFloat.get(j) / sumT) //Division by 0 protection
chiSquare += math.pow(observedValue - expectedValue, 2) / expectedValue
Together with the 'Degree of Freedom', which is (rows − 1) × (columns − 1) , the P-value can be calculated.
In this case it is P-value: 0.02462
A P-value lower than 0.05 is considered to be significant. Statistically, women tend to choose a romantic movie more, while men prefer a non-romantic one.
Users have the option to choose a P-value, calculated from a standard table or through a math.ucla.edu - Javascript-based function (see references below).
Note that the population (10 men + 10 women = 20) is small, something to consider.
Either way, this principle is applied in the script, where conditions can be chosen like rsi, close, high, ...
🔹 CONDITION
Conditions are added to the left column ('CONDITION')
For example, previous rsi values (rsi ) between 0-100, divided in separate groups
🔹 CLOSE
Then, the movement of the last close is evaluated
UP when close is higher then previous close (close )
DOWN when close is lower then previous close
EQUAL when close is equal then previous close
It is also possible to use only 2 columns by adding EQUAL to UP or DOWN
UP
DOWN/EQUAL
or
UP/EQUAL
DOWN
In other words, when previous rsi value was between 80 and 90, this resulted in:
19 times a current close higher than previous close
14 times a current close lower than previous close
0 times a current close equal than previous close
However, the P-value tells us it is not statistical significant.
NOTE: Always keep in mind that past behaviour gives no certainty about future behaviour.
A vertical line is drawn at the beginning of the chosen population (max 4990)
Here, the results seem significant.
🔹 GROUPS
It is important to ensure that the groups are formed correctly. All possibilities should be present, and conditions should only be part of 1 group.
In the example above, the two top situations are acceptable; close against close can only be higher, lower or equal.
The two examples at the bottom, however, are very poorly constructed.
Several conditions can be placed in more than 1 group, and some conditions are not integrated into a group. Even if the results are significant, they are useless because of the group formation.
A population count is added as an aid to spot errors in group formation.
In this example, there is a discrepancy between the population and total count due to the absence of a condition.
The results when rsi was between 5-25 are not included, resulting in unreliable results.
🔹 PRACTICAL EXAMPLES
In this example, we have specific groups where the condition only applies to that group.
For example, the condition rsi > 55 and rsi <= 65 isn't true in another group.
Also, every possible rsi value (0 - 100) is present in 1 of the groups.
rsi > 15 and rsi <= 25 28 times UP, 19 times DOWN and 2 times EQUAL. P-value: 0.01171
When looking in detail and examining the area 15-25 RSI, we see this:
The population is now not representative (only checking for RSI between 15-25; all other RSI values are not included), so we can ignore the P-value in this case. It is merely to check in detail. In this case, the RSI values 23 and 24 seem promising.
NOTE: We should check what the close price did without any condition.
If, for example, the close price had risen 100 times out of 100, this would make things very relative.
In this case (at least two conditions need to be present), we set 1 condition at 'always true' and another at 'always false' so we'll get only the close values without any condition:
Changing the population or the conditions will change the P-value.
In the following example, the outcome is evaluated when:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is lower/equal than the close value from 2 bars back
Or:
close value from 1 bar back is higher than the close value from 2 bars back
close value from 1 bar back is equal than the close value from 2 bars back
close value from 1 bar back is lower than the close value from 2 bars back
In both examples, all possibilities of close against close are included in the calculations. close can only by higher, equal or lower than close
Both examples have the results without a condition included (5 = 5 and 5 < 5) so one can compare the direction of current close.
🔶 NOTES
• Always keep in mind that:
Past behaviour gives no certainty about future behaviour.
Everything depends on time, cycles, events, fundamentals, technicals, ...
• This test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Red, Yellow, Green, Blue} etc., but not numerical data such as height or weight. One might argue that such tests shouldn't use rsi, close, ... values.
• Consider what you're measuring
For example rsi of the current bar will always lead to a close higher than the previous close, since this is inherent to the rsi calculations.
• Be careful; often, there are na -values at the beginning of the series, which are not included in the calculations!
• Always keep in mind considering what the close price did without any condition
• The numbers must be large enough. Each entry must be five or more. In other words, it is vital to make the 'population' large enough.
• The code can be developed further, for example, by splitting UP, DOWN in close UP 1-2%, close UP 2-3%, close UP 3-4%, ...
• rsi can be supplemented with stochRSI, MFI, sma, ema, ...
🔶 SETTINGS
🔹 Population
• Choose the population size; in other words, how many bars you want to go back to. If fewer bars are available than set, this will be automatically adjusted.
🔹 Inputs
At least two conditions need to be chosen.
• Users can add up to 11 conditions, where each condition can contain two different conditions.
🔹 RSI
• Length
🔹 Levels
• Set the used levels as desired.
🔹 Levels
• P-value: P-value retrieved using a standard table method or a function.
• Used function, derived from Chi-Square Distribution Function; JavaScript
LogGamma(Z) =>
S = 1
+ 76.18009173 / Z
- 86.50532033 / (Z+1)
+ 24.01409822 / (Z+2)
- 1.231739516 / (Z+3)
+ 0.00120858003 / (Z+4)
- 0.00000536382 / (Z+5)
(Z-.5) * math.log(Z+4.5) - (Z+4.5) + math.log(S * 2.50662827465)
Gcf(float X, A) => // Good for X > A +1
A0=0., B0=1., A1=1., B1=X, AOLD=0., N=0
while (math.abs((A1-AOLD)/A1) > .00001)
AOLD := A1
N += 1
A0 := A1+(N-A)*A0
B0 := B1+(N-A)*B0
A1 := X*A0+N*A1
B1 := X*B0+N*B1
A0 := A0/B1
B0 := B0/B1
A1 := A1/B1
B1 := 1
Prob = math.exp(A * math.log(X) - X - LogGamma(A)) * A1
1 - Prob
Gser(X, A) => // Good for X < A +1
T9 = 1. / A
G = T9
I = 1
while (T9 > G* 0.00001)
T9 := T9 * X / (A + I)
G := G + T9
I += 1
G *= math.exp(A * math.log(X) - X - LogGamma(A))
Gammacdf(x, a) =>
GI = 0.
if (x<=0)
GI := 0
else if (x
Chisqcdf = Gammacdf(Z/2, DF/2)
Chisqcdf := math.round(Chisqcdf * 100000) / 100000
pValue = 1 - Chisqcdf
🔶 REFERENCES
mathsisfun.com, Chi-Square Test
Chi-Square Distribution Function
Supply Demand Profiles [LuxAlgo]The Supply Demand Profiles is a charting tool that measures the traded volume at all price levels on the market over a specified time period and highlights the relationship between the price of a given asset and the willingness of traders to either buy or sell it, in other words, highlights key concepts as significant supply & demand zones, the distribution of the traded volume, and market sentiment at specific price levels within a specified time period, allowing traders to reveal dominant and/or significant price levels and to analyze the trading activity of a particular user-selected range.
In other words, this tool highlights key concepts as significant supply & demand zones, the distribution of the traded volume, and market sentiment at specific price levels within a specified time period, allowing traders to reveal dominant and/or significant price levels and to analyze the trading activity of a particular user-selected range.
Besides having the tool as a combo tool, the uniqueness of this version of the tool compared to its early versions is its ability to benefit from different volume data sources and its ability to use a variety of different polarity methods, where polarity is a measure used to divide the total volume into either up volume (trades that moved the price up) or down volume (trades that moved the price down).
🔶 USAGE
Supply & demand zones are presented as horizontal zones across the selected range, hence adding the ability to visualize the price interaction with them
By default, the right side of the profile is the volume profile which highlights the distribution of the traded activity at different price levels, emphasizing the value area, the range of price levels in which the specified percentage of all volume was traded during the time period, and levels of significance, such as developing point of control line, value area high/low lines, and profile high/low labels
The left side of the profile is the sentiment profile which highlights the market sentiment at specific price levels
🔶 DETAILS
🔹 Volume data sources
The users have the option to select volume data sources as either 'volume' (regular volume) or 'volume delta', where volume represents all the recorded trades that occur at a given bar and volume delta is the difference between the buying and the selling volume, that is, the net demand at a given bar
🔹 Polarity methods
The users are able to choose the methods of how the tool to take into consideration the polarity of the bar (the direction of a bar, green (bullish) or red (bearish) bar) among a variety of different options, such as 'bar polarity', 'bar buying/selling pressure', 'intrabar (chart bars at a lower timeframe than the chart's) polarity', 'intrabar buying/selling pressure', and 'heikin ashi bar polarity'.
Finally, the interactive mode of the tool is activated, as such users can easily modify the intervals of their interest just by selecting the indicator and moving the points on the chart
🔶 SETTINGS
The script takes into account user-defined parameters and plots the profiles and zones
🔹 Calculation Settings
Volume Data Source and Polarity: This option is to set the desired volume data source and polarity method
Lower Timeframe Precision: This option is applicable in case any of the 'Intrabar (LTF)' options are selected, please check the tooltip for further details
Value Area Volume %: Specifies the percentage for the value area calculation
🔹 Presentation Settings
Supply & Demand Zones: Toggles the visibility of the supply & demand zones
Volume Profile: Toggles the visibility of the volume profile
Sentiment Profile: Toggles the visibility of the sentiment profile
🔹 Presentation, Others
Value Area High (VAH): Toggles the visibility of the VAH line and color customization option
Point of Control (POC): Toggles the visibility of the developing POC line and color customization option
Value Area Low (VAL): Toggles the visibility of the VAL line and color customization option
🔹 Supply & Demand, Others
Supply & Demand Threshold %: This option is used to set the threshold value to determine supply & demand zones
Supply/Demand Zones: Color customization option
🔹 Volume Profile, Others
Profile, Up/Down Volume: Color customization option
Value Area, Up/Down Volume: Color customization option
🔹 Sentiment Profile, Others
Sentiment, Bullish/Bearish: Color customization option
Value Area, Bullish/Bearish: Color customization option
🔹 Others
Number of Rows: Specify how many rows the profile will have
Placment: Specify where to display the profile
Profile Width %: Alters the width of the rows in the profile, relative to the profile range
Profile Price Levels: Toggles the visibility of the profile price levels
Profile Background, Color: Fills the background of the profile range
Value Area Background, Color: Fills the background of the value area range
Start Calculation/End Calculation: The tool is interactive, where the user may modify the range by selecting the indicator and moving the points on the chart or can set the start/end time using these options
🔶 RELATED SCRIPTS
Volume-Profile
Volume-Profile-Maps
Volume-Delta
Line Colorizer - DurbtradeThe Line Colorizer is a simple indicator that can plot up/down-colorized lines for up to 10 unique individual sources!
Plot up/down colors are based on whether the current value is above or below the previous value.
Also included is a separate color for when the current value is equal to the previous value.
All colors can be modified, along with the plot styles.
--------------------------------------------
--------------------------------------------
Here is the Inputs tab of the Settings menu :
As you can see, you can plot a colorized line of up to 10 individual sources!
Checking the checkbox turns on that particular colorized plot,
and clicking on the drop down menu allows you select the source for that plot.
The plot styles, up/equal/down colors, and opacities
are customizable under the Style tab within the Settings menu :
Overall, it is pretty easy to use.
--------------------------------------------
Let's look at some examples of the Line Colorizer being used...
Colorize a basic Bollinger Bands indicator :
Want to colorize 3 EMA's? Go for it :
Spice up the standard MACD salad :
Customize the colors of your RSI's :
Try using the Line Colorizer on all of your favorite indicators.
--------------------------------------------
Script Stats :
Pinescript Version : 5
Code Length : 44 Lines
Max Unique Input Sources : 10
Max Visible Plots : 10
Total Colors/Opacities : 30
--------------------------------------------
Tips :
Typically you will want this indicator to be on a layer above (in front of) the source plot layer.
Stay mindful of line thicknesses,
and whether the original source plot is still visible or not.
The final output of the colorized plots are drawn in numerical order,
so, Colorized Source #1 is drawn first, and will appear below Colorized Source #2 on the chart...
and so on, with Colorized Source #10 being drawn last, at the very top.
Final Thoughts :
I like having this indicator.
The idea and script is simple, and the indicator is practical.
It's one method of easily separating some of the aspects of color from your favorite indicators and scripts,
and then customizing those aspects to your liking.
Especially practical for those who do not want to learn about writing their own scripts.
I think that this indicator can be a useful tool in the shed,
used for customizing the visuals of multiple unique sources
that are all on the same price/value scale.
It can help increase chart clarity and/or detail...
whether using it on top of a main chart that is simple,
or on top of a standalone indicator that is crowded with oscillating information.
I hope that you enjoy it and find it useful!
- Please feel free to comment your thoughts, critiques, or suggestions. They are all very helpful!
- Also, please feel free to comment any positive feedback, or awesome screencaps/ideas of the indicator in action!
- Check out my other Pinescript indicators if you like this one... they work well together.
- May your trades be successful!
--------------------------------------------
// Durbtrade
Universal MA Trend(Republishing in Open source)
Hello traders,
Many existing moving average indicators have not been satisfactory in terms of the number, types, and length adjustments of moving averages.
Feeling the inconvenience, I created a moving average indicator and collected numerous famous moving averages.
Fortunately, there was a PineCoder "andre_007" who had already compiled various Moving Averages,
so I was able to find a new Moving Average and combine it with the indicator. Here is the link below
Among these, for the JMA, which has not been publicly disclosed, I utilized the source code from TradingView Wizard everget:
For VIDYA, I also used everget's source code:
And also MAMA / FAMA Coded from Pinescript Wizard everget :
Ehlers MESA Adaptive Moving Averages (MAMA & FAMA)
For Frama, I used the code from nemozny's source code :
Thanks to all these Pinecoders.
---
By using these excellent moving averages together, I found that the simultaneous Up/Down changes of various moving averages with different characteristics tend to be maintained for quite a long time.
Therefore, this indicator not only collects various moving averages but also displays areas with simultaneous trends as background.
An example can be found here:
Furthermore, to prevent the up/down changes of the moving averages due to factors like whipsaws, a smoothing filter has been introduced.
And Also, Alert is able when trend changes.
---
(오픈소스화 후 재발행)
안녕하세요 트레이더여러분.
기존의 이동평균선 지표들은, 이동평균선의 갯수, 종류, 길이조절 등에서 만족스럽지 못한 점들이 많았습니다.
불편함을 느끼고 직접 이동평균선 지표를 만들면서, 유명한 수 많은 이동평균선들을 모았습니다.
그리고 이미 이러한 수많은 이동평균선을 손수 모아서 정리해주신 고마우신 파인코더(andere_007 님)가 있어서, 그 분의 코드를 많이 이용했습니다. 링크는 아래와 같습니다.
이 중 소스가 공개되지 않은 이동평균선 중 JMA는 트레이딩뷰 위자드이신 everget의 소스코드를 이용했습니다.
VIDYA 역시 everget의 소스코드를 이용했습니다.
MAMA와 FAMA의 코드 역시 everget님의 코드를 가져왔습니다.
Ehlers MESA Adaptive Moving Averages (MAMA & FAMA)
Frama는 nemozny님의 코드를 이용했습니다.
의 코드를 이용했습니다.
이 자리를 빌어 위의 파인코더님들께 감사의 말씀을 전합니다.
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이러한 좋은 이동평균선을 모아서 사용해보니, 다양한 특성을 갖고 있는 이동평균선의 동시적인 Up/Down 변화는 꽤 오랫동안 유지된다는 점을 발견했습니다.
그래서 이 지표는, 위의 여러가지 이동평균선을 모아놓은 것 뿐만 아니라,
그것에서 동시적인 트랜드가 나오는 곳을 배경화면으로 표시해두었습니다.
예시는 다음과 같습니다.
나아가 휩쏘 등으로 이동평균선의 up/down이 바뀌는 것을 막고자, Smoothing 필터도 도입했습니다.
또한 트랜드가 바뀔 때 얼러트가 울리도록, 얼러트 기능을 설정해놓을 수 있게 해놓았으며, 현재 이동평균선과 상태를 보기 쉽도록 테이블을 만들어놓았습니다.
Ectopic Bar by Moti RakamEctopic Bar is an indicator that highlights a pin-bar candle that has divergence in it's shape and volume delta. To find volume delta, code of standard Up/Down volume indicator has been used.
PIN BAR : pin bar are marked by using Close Range option parameter. Default value is set to 0.35 which implies any candle that closes in the 35% of its high/low will be considered a pin bar (of course the code also ensures that rest of the bar body is only a wick).
HOW IT WORKS:
Up/Down volume variables "Up Volume" and "Down Volume" are checked against the shape of the pin bar to find an ectopic situation. For example, if a bullish pin bar candle (a bullish hammer) has more sell volume than buy volume, that's an ectopic situation. The bullish hammer shows a buying push from the bottom of the wick, instead the up/down volume indicator shows there were more sell orders than buy orders. Hence the ectopic situation. Similarly, an inverted hammer (a bearish hammer) in general should have more sell volume, but instead if it has more buying volume, the indicator highlights it as an ectopic bar.
Ectopic Bars are painted in yellow colour.
