Intraday Volume Indicator for INDICES by TBTPH Pine Script code for an intraday volume indicator with session and lunch break highlights looks great! Here’s a summary of what each part of the script does:
Indicator Settings:
The indicator is set to show on a separate pane (overlay=false).
The SMA Length is adjustable with an input box (default of 20).
Volume and SMA Calculation:
You calculate the Simple Moving Average (SMA) of the volume over the selected length.
The volume color is determined based on whether the close price is higher or lower than the previous close and if the volume is above or below the SMA.
Volume Plot:
Volume is plotted as a histogram with different colors to indicate if the volume is higher or lower than the SMA.
You plot the SMA of the volume with an orange line for easier comparison.
Background Color:
You set a light gray background color to give a subtle contrast.
NYSE and LSE trading sessions are highlighted with green and blue, respectively.
Lunch break periods are highlighted with a white background for both exchanges.
Here are a couple of improvements or suggestions you might consider:
Session Time Overlap Handling:
If the script is applied to a chart where both NYSE and LSE data is visible, they may overlap depending on the time zone of your chart. Ensure the session times align with the active market's timezone, especially if you are using a chart with a different timezone setting.
Color Customization:
The color scheme for bullish/bearish volume could be enhanced further. For example, you could introduce more transparency for low-volume periods to make the histogram appear more subtle during less active trading times.
Handling Different Time Zones:
If your chart is not in the "America/New_York" or "GMT" time zone, be mindful of the session times. The timestamp function depends on the chart’s time zone, so ensuring you're adjusting for different markets is key.
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zone trading stratThis only works for DOGEUSD , I made it for the 8cap chart so only use it for that.
If you want this for other symbols/charts you need to comment below or msg me.
# Price Zone Trading System: Technical Explanation
## Core Concept
The Price Zone Tracker is built on the concept that price tends to respect certain key levels or "zones" on the chart. These zones act as support and resistance areas where price may bounce or break through. The system combines zone analysis with multiple technical indicators to generate high-probability trading signals.
## Zone Analysis
The system tracks 9 predefined price zones. Each zone has both a high and low boundary, except for Zone 5 which is represented by a single line. When price enters a zone, the system monitors whether it stays within the zone, breaks above it (bullish), or breaks below it (bearish).
This zone behavior establishes the foundational bias of the system:
- When price closes above its previous zone: Zone State = Bullish
- When price closes below its previous zone: Zone State = Bearish
- When price remains within a zone: Zone State = Neutral
## Trend Analysis Components
The system performs multi-timeframe analysis using several technical components:
1. **Higher Timeframe Analysis** (±3 points in scoring)
- Uses 15-minute charts for sub-5-minute timeframes
- Uses 30-minute charts for 5-minute timeframes
- Uses 60-minute charts for timeframes above 5 minutes
- Evaluates candlestick patterns and EMA crossovers on the higher timeframe
2. **EMA Direction** (±1 point in scoring)
- Compares 12-period and 26-period EMAs
- Bullish when fast EMA > slow EMA
- Bearish when fast EMA < slow EMA
3. **MACD Analysis** (±1 point in scoring)
- Uses standard 12/26/9 MACD settings
- Bullish when MACD line crosses above signal line with positive histogram
- Bearish when MACD line crosses below signal line with negative histogram
4. **Price Action** (±2 points in scoring)
- Evaluates whether price is making higher highs/higher lows (uptrend)
- Or lower highs/lower lows (downtrend)
- Also considers ATR-based volatility and strength of movements
## Trend Score Calculation
All these components are weighted and combined into a trend score:
- Higher timeframe components have stronger weights (±2-3 points)
- Current timeframe components have moderate weights (±1 point)
- Price action components have varied weights (±0.5-2 points)
The final trend state is determined by thresholds:
- Score > +3: Trend Analysis State = Bullish
- Score < -3: Trend Analysis State = Bearish
- Score between -3 and +3: Trend Analysis State = Neutral
## Signal Generation Logic
The system combines the Zone State with the Trend Analysis State:
1. If Zone State and Trend Analysis State are both bullish:
- Combined State = Bullish
- Line Color = Green
2. If Zone State and Trend Analysis State are both bearish:
- Combined State = Bearish
- Line Color = Red
3. If Zone State and Trend Analysis State contradict each other:
- Combined State = Neutral
- Line Color = Black
This implements a safety mechanism requiring both zone analysis and technical indicators to agree before generating a directional signal.
## Trading Signals
Trading signals are generated based on changes in the Combined State:
- When Combined State changes from neutral/bearish to bullish:
- Trading Signal = LONG (green triangle appears on chart)
- When Combined State changes from neutral/bullish to bearish:
- Trading Signal = SHORT (red triangle appears on chart)
- When Combined State changes from bullish/bearish to neutral:
- Trading Signal = EXIT (yellow X appears on chart)
- When Combined State remains unchanged:
- Trading Signal = NONE (no new marker appears)
## Reversal Warning
The system also monitors for potential reversal conditions:
- When Combined State is bullish but both RSI and MFI are overbought (>70)
- When Combined State is bearish but both RSI and MFI are oversold (<30)
In these cases, a yellow diamond appears on the chart as a warning that a reversal might be imminent.
## Visual Elements
The indicator provides multiple visual elements:
1. Zone boundaries as translucent orange areas
2. A single colored line below price (green/red/black) showing the current signal
3. Trading signals as shapes on the chart
4. An information panel showing all relevant indicator values and signals
## Usage Limitations
The indicator is designed to work optimally on timeframes below 30 minutes. On higher timeframes, a warning appears and analysis is disabled.
Composite Reversal IndicatorOverview
The "Composite Reversal Indicator" aggregates five technical signals to produce a composite score that ranges from -5 (strongly bearish) to +5 (strongly bullish). These signals come from:
Relative Strength Index (RSI)
Moving Average Convergence Divergence (MACD)
Accumulation/Distribution (A/D)
Volume relative to its moving average
Price proximity to support and resistance levels
Each signal contributes a value of +1 (bullish), -1 (bearish), or 0 (neutral) to the total score. The raw score is plotted as a histogram, and a smoothed version is plotted as a colored line to highlight trends.
Step-by-Step Explanation
1. Customizable Inputs
The indicator starts with user-defined inputs that allow traders to tweak its settings. These inputs include:
RSI: Length (e.g., 14), oversold level (e.g., 30), and overbought level (e.g., 70).
MACD: Fast length (e.g., 12), slow length (e.g., 26), and signal length (e.g., 9).
Volume: Moving average length (e.g., 20) and multipliers for high (e.g., 1.5) and low (e.g., 0.5) volume thresholds.
Price Levels: Period for support and resistance (e.g., 50) and proximity percentage (e.g., 2%).
Score Smoothing: Length for smoothing the score (e.g., 5).
These inputs make the indicator adaptable to different trading styles, assets, or timeframes.
2. Indicator Calculations
The script calculates five key indicators using the input parameters:
RSI: Measures momentum and identifies overbought or oversold conditions.
Formula: rsi = ta.rsi(close, rsi_length)
Example: With a length of 14, it analyzes the past 14 bars of closing prices.
MACD: Tracks trend and momentum using two exponential moving averages (EMAs).
Formula: = ta.macd(close, macd_fast, macd_slow, macd_signal)
Components: MACD line (fast EMA - slow EMA), signal line (EMA of MACD line).
Accumulation/Distribution (A/D): A volume-based indicator showing buying or selling pressure.
Formula: ad = ta.accdist
Reflects cumulative flow based on price and volume.
Volume Moving Average: A simple moving average (SMA) of trading volume.
Formula: vol_ma = ta.sma(volume, vol_ma_length)
Example: A 20-bar SMA smooths volume data.
Support and Resistance Levels: Key price levels based on historical lows and highs.
Formulas:
support = ta.lowest(low, price_level_period)
resistance = ta.highest(high, price_level_period)
Example: Over 50 bars, it finds the lowest low and highest high.
These calculations provide the raw data for generating signals.
3. Signal Generation
Each indicator produces a signal based on specific conditions:
RSI Signal:
+1: RSI < oversold level (e.g., < 30) → potential bullish reversal.
-1: RSI > overbought level (e.g., > 70) → potential bearish reversal.
0: Otherwise.
Logic: Extreme RSI values suggest price may reverse.
MACD Signal:
+1: MACD line > signal line → bullish momentum.
-1: MACD line < signal line → bearish momentum.
0: Equal.
Logic: Crossovers indicate trend shifts.
A/D Signal:
+1: Current A/D > previous A/D → accumulation (bullish).
-1: Current A/D < previous A/D → distribution (bearish).
0: Unchanged.
Logic: Rising A/D shows buying pressure.
Volume Signal:
+1: Volume > high threshold (e.g., 1.5 × volume MA) → strong activity (bullish).
-1: Volume < low threshold (e.g., 0.5 × volume MA) → weak activity (bearish).
0: Otherwise.
Logic: Volume spikes often confirm reversals.
Price Signal:
+1: Close near support (within proximity %, e.g., 2%) → potential bounce.
-1: Close near resistance (within proximity %) → potential rejection.
0: Otherwise.
Logic: Price near key levels signals reversal zones.
4. Composite Score
The raw composite score is the sum of the five signals:
Formula: score = rsi_signal + macd_signal + ad_signal + vol_signal + price_signal
Range: -5 (all signals bearish) to +5 (all signals bullish).
Purpose: Combines multiple perspectives into one number.
5. Smoothed Score
A smoothed version of the score reduces noise:
Formula: score_ma = ta.sma(score, score_ma_length)
Example: With a length of 5, it averages the score over 5 bars.
Purpose: Highlights the trend rather than short-term fluctuations.
6. Visualization
The indicator plots two elements:
Raw Score: A gray histogram showing the composite score per bar.
Style: plot.style_histogram
Color: Gray.
Smoothed Score: A line that changes color:
Green: Score > 0 (bullish).
Red: Score < 0 (bearish).
Gray: Score = 0 (neutral).
Style: plot.style_line, thicker line (e.g., linewidth=2).
These visuals make it easy to spot potential reversals.
How It Works Together
The indicator combines signals from:
RSI: Momentum extremes.
MACD: Trend shifts.
A/D: Buying/selling pressure.
Volume: Confirmation of moves.
Price Levels: Key reversal zones.
By summing these into a composite score, it filters out noise and provides a unified signal. A high positive score (e.g., +3 to +5) suggests a bullish reversal, while a low negative score (e.g., -3 to -5) suggests a bearish reversal. The smoothed score helps traders focus on the trend.
Practical Use
Bullish Reversal: Smoothed score is green and rising → look for buying opportunities.
Bearish Reversal: Smoothed score is red and falling → consider selling or shorting.
Neutral: Score near 0 → wait for clearer signals.
Traders can adjust inputs to suit their strategy, making it versatile for stocks, forex, or crypto.
StatPivot- Dynamic Range Analyzer - indicator [PresentTrading]Hello everyone! In the following few open scripts, I would like to share various statistical tools that benefit trading. For this time, it is a powerful indicator called StatPivot- Dynamic Range Analyzer that brings a whole new dimension to your technical analysis toolkit.
This tool goes beyond traditional pivot point analysis by providing comprehensive statistical insights about price movements, helping you identify high-probability trading opportunities based on historical data patterns rather than subjective interpretations. Whether you're a day trader, swing trader, or position trader, StatPivot's real-time percentile rankings give you a statistical edge in understanding exactly where current price action stands within historical contexts.
Welcome to share your opinions! Looking forward to sharing the next tool soon!
█ Introduction and How it is Different
StatPivot is an advanced technical analysis tool that revolutionizes retracement analysis. Unlike traditional pivot indicators that only show static support/resistance levels, StatPivot delivers dynamic statistical insights based on historical pivot patterns.
Its key innovation is real-time percentile calculation - while conventional tools require new pivot formations before updating (often too late for trading decisions), StatPivot continuously analyzes where current price stands within historical retracement distributions.
Furthermore, StatPivot provides comprehensive statistical metrics including mean, median, standard deviation, and percentile distributions of price movements, giving traders a probabilistic edge by revealing which price levels represent statistically significant zones for potential reversals or continuations. By transforming raw price data into statistical insights, StatPivot helps traders move beyond subjective price analysis to evidence-based decision making.
█ Strategy, How it Works: Detailed Explanation
🔶 Pivot Point Detection and Analysis
The core of StatPivot's functionality begins with identifying significant pivot points in the price structure. Using the parameters left and right, the indicator locates pivot highs and lows by examining a specified number of bars to the left and right of each potential pivot point:
Copyp_low = ta.pivotlow(low, left, right)
p_high = ta.pivothigh(high, left, right)
For a point to qualify as a pivot low, it must have left higher lows to its left and right higher lows to its right. Similarly, a pivot high must have left lower highs to its left and right lower highs to its right. This approach ensures that only significant turning points are recognized.
🔶 Percentage Change Calculation
Once pivot points are identified, StatPivot calculates the percentage changes between consecutive pivot points:
For drops (when a pivot low is lower than the previous pivot low):
CopydropPercent = (previous_pivot_low - current_pivot_low) / previous_pivot_low * 100
For rises (when a pivot high is higher than the previous pivot high):
CopyrisePercent = (current_pivot_high - previous_pivot_high) / previous_pivot_high * 100
These calculations quantify the magnitude of each market swing, allowing for statistical analysis of historical price movements.
🔶 Statistical Distribution Analysis
StatPivot computes comprehensive statistics on the historical distribution of drops and rises:
Average (Mean): The arithmetic mean of all recorded percentage changes
CopyavgDrop = array.avg(dropValues)
Median: The middle value when all percentage changes are arranged in order
CopymedianDrop = array.median(dropValues)
Standard Deviation: Measures the dispersion of percentage changes from the average
CopystdDevDrop = array.stdev(dropValues)
Percentiles (25th, 75th): Values below which 25% and 75% of observations fall
Copyq1 = array.get(sorted, math.floor(cnt * 0.25))
q3 = array.get(sorted, math.floor(cnt * 0.75))
VaR95: The maximum expected percentage drop with 95% confidence
Copyvar95D = array.get(sortedD, math.floor(nD * 0.95))
Coefficient of Variation (CV): Measures relative variability
CopycvD = stdDevDrop / avgDrop
These statistics provide a comprehensive view of market behavior, enabling traders to understand the typical ranges and extreme moves.
🔶 Real-time Percentile Ranking
StatPivot's most innovative feature is its real-time percentile calculation. For each current price, it calculates:
The percentage drop from the latest pivot high:
CopycurrentDropPct = (latestPivotHigh - close) / latestPivotHigh * 100
The percentage rise from the latest pivot low:
CopycurrentRisePct = (close - latestPivotLow) / latestPivotLow * 100
The percentile ranks of these values within the historical distribution:
CopyrealtimeDropRank = (count of historical drops <= currentDropPct) / total drops * 100
This calculation reveals exactly where the current price movement stands in relation to all historical movements, providing crucial context for decision-making.
🔶 Cluster Analysis
To identify the most common retracement zones, StatPivot performs a cluster analysis by dividing the range of historical drops into five equal intervals:
CopyrangeSize = maxVal - minVal
For each interval boundary:
Copyboundaries = minVal + rangeSize * i / 5
By counting the number of observations in each interval, the indicator identifies the most frequently occurring retracement zones, which often serve as significant support or resistance areas.
🔶 Expected Price Targets
Using the statistical data, StatPivot calculates expected price targets:
CopytargetBuyPrice = close * (1 - avgDrop / 100)
targetSellPrice = close * (1 + avgRise / 100)
These targets represent statistically probable price levels for potential entries and exits based on the average historical behavior of the market.
█ Trade Direction
StatPivot functions as an analytical tool rather than a direct trading signal generator, providing statistical insights that can be applied to various trading strategies. However, the data it generates can be interpreted for different trade directions:
For Long Trades:
Entry considerations: Look for price drops that reach the 70-80th percentile range in the historical distribution, suggesting a statistically significant retracement
Target setting: Use the Expected Sell price or consider the average rise percentage as a reasonable target
Risk management: Set stop losses below recent pivot lows or at a distance related to the statistical volatility (standard deviation)
For Short Trades:
Entry considerations: Look for price rises that reach the 70-80th percentile range, indicating an unusual extension
Target setting: Use the Expected Buy price or average drop percentage as a target
Risk management: Set stop losses above recent pivot highs or based on statistical measures of volatility
For Range Trading:
Use the most common drop and rise clusters to identify probable reversal zones
Trade bounces between these statistically significant levels
For Trend Following:
Confirm trend strength by analyzing consecutive higher pivot lows (uptrend) or lower pivot highs (downtrend)
Use lower percentile retracements (20-30th percentile) as entry opportunities in established trends
█ Usage
StatPivot offers multiple ways to integrate its statistical insights into your trading workflow:
Statistical Table Analysis: Review the comprehensive statistics displayed in the data table to understand the market's behavior. Pay particular attention to:
Average drop and rise percentages to set reasonable expectations
Standard deviation to gauge volatility
VaR95 for risk assessment
Real-time Percentile Monitoring: Watch the real-time percentile display to see where the current price movement stands within the historical distribution. This can help identify:
Extreme movements (90th+ percentile) that might indicate reversal opportunities
Typical retracements (40-60th percentile) that might continue further
Shallow pullbacks (10-30th percentile) that might represent continuation opportunities in trends
Support and Resistance Identification: Utilize the plotted pivot points as key support and resistance levels, especially when they align with statistically significant percentile ranges.
Target Price Setting: Use the expected buy and sell prices calculated from historical averages as initial targets for your trades.
Risk Management: Apply the statistical measurements like standard deviation and VaR95 to set appropriate stop loss levels that account for the market's historical volatility.
Pattern Recognition: Over time, learn to recognize when certain percentile levels consistently lead to reversals or continuations in your specific market, and develop personalized strategies based on these observations.
█ Default Settings
The default settings of StatPivot have been carefully calibrated to provide reliable statistical analysis across a variety of markets and timeframes, but understanding their effects allows for optimal customization:
Left Bars (30) and Right Bars (30): These parameters determine how pivot points are identified. With both set to 30 by default:
A pivot low must be the lowest point among 30 bars to its left and 30 bars to its right
A pivot high must be the highest point among 30 bars to its left and 30 bars to its right
Effect on performance: Larger values create fewer but more significant pivot points, reducing noise but potentially missing important market structures. Smaller values generate more pivot points, capturing more nuanced movements but potentially including noise.
Table Position (Top Right): Determines where the statistical data table appears on the chart.
Effect on performance: No impact on analytical performance, purely a visual preference.
Show Distribution Histogram (False): Controls whether the distribution histogram of drop percentages is displayed.
Effect on performance: Enabling this provides visual insight into the distribution of retracements but can clutter the chart.
Show Real-time Percentile (True): Toggles the display of real-time percentile rankings.
Effect on performance: A critical setting that enables the dynamic analysis of current price movements. Disabling this removes one of the key advantages of the indicator.
Real-time Percentile Display Mode (Label): Chooses between label display or indicator line for percentile rankings.
Effect on performance: Labels provide precise information at the current price point, while indicator lines show the evolution of percentile rankings over time.
Advanced Considerations for Settings Optimization:
Timeframe Adjustment: Higher timeframes generally benefit from larger Left/Right values to identify truly significant pivots, while lower timeframes may require smaller values to capture shorter-term swings.
Volatility-Based Tuning: In highly volatile markets, consider increasing the Left/Right values to filter out noise. In less volatile conditions, lower values can help identify more potential entry and exit points.
Market-Specific Optimization: Different markets (forex, stocks, commodities) display different retracement patterns. Monitor the statistics table to see if your market typically shows larger or smaller retracements than the current settings are optimized for.
Trading Style Alignment: Adjust the settings to match your trading timeframe. Day traders might prefer settings that identify shorter-term pivots (smaller Left/Right values), while swing traders benefit from more significant pivots (larger Left/Right values).
By understanding how these settings affect the analysis and customizing them to your specific market and trading style, you can maximize the effectiveness of StatPivot as a powerful statistical tool for identifying high-probability trading opportunities.
Volume with Sessions, SMA, and ATR Pine Script creates a custom volume indicator with several features, including:
SMA of Volume: It calculates the simple moving average (SMA) of the volume, which helps identify trends and determine if the current volume is above or below the average.
ATR (Average True Range): It calculates the ATR, which measures market volatility over a defined period.
Bullish/Bearish Volume Coloring: The script colors the volume bars depending on whether the price is moving up (bullish) or down (bearish), and whether the volume is above or below the SMA of volume.
Session Highlighting: It defines two major trading sessions:
NYSE (New York Stock Exchange) session from 9:30 AM to 4:00 PM Eastern Time.
LSE (London Stock Exchange) session from 8:00 AM to 4:30 PM GMT. These sessions are highlighted with background colors for easy identification.
Plotting: The volume is plotted as a histogram with varying colors depending on price movement and volume relative to its SMA. The ATR is also plotted as a purple line, and the SMA of volume is displayed as an orange line.
Background Colors: Background colors are applied during the NYSE and LSE sessions to visually differentiate between these trading periods.
Here's a breakdown of each section:
Key Inputs:
smaLength and atrLength: User-defined values for the lengths of the SMA and ATR calculations.
Main Calculations:
smaVolume: The SMA of the volume over the user-defined length (smaLength).
atrValue: The Average True Range over the user-defined length (atrLength).
Color Logic for Volume Bars:
If the current close is higher than the previous close, the volume is considered bullish, and the bar is colored green. If the volume is above the SMA, it’s a darker green; otherwise, it’s a lighter shade.
If the current close is lower than the previous close, the volume is considered bearish, and the bar is colored red. If the volume is above the SMA, it’s a darker red; otherwise, it’s a lighter red.
Plotting:
The script plots the volume as a histogram with dynamic coloring.
The SMA of the volume is plotted as a line.
ATR is plotted as a purple line for reference.
Background Color Highlighting:
The background is colored green during the NYSE session and blue during the LSE session.
Indiq 2.0The functionality of the indicator includes the following features:
Moving Averages (MA):
The ability to adjust periods for short (short_ma_length) and long (long_ma_length) moving averages.
Display of moving averages on the chart:
Short MA (blue line).
Long MA (red line).
Generation of buy and sell signals:
Buy (BUY): When the short MA crosses the long MA from below.
Sell (SELL): When the short MA crosses the long MA from above.
Visualization of signals on the chart:
Buy is displayed as a green BUY marker below the candle.
Sell is displayed as a red SELL marker above the candle.
Liquidity Heatmap:
Liquidity levels:
Levels are calculated based on the closing price and a step (liquidity_step).
Levels are grouped by the nearest price values.
Volumes at levels:
Volume (volume) is accumulated for each liquidity level.
Levels with a volume less than min_volume_filter are not displayed.
Time filtering:
Levels that have not been updated within the last time_filter bars are not displayed.
Volatility filtering:
Levels are filtered by volatility (ATR) to exclude those outside the volatility range.
Color gradient:
The color of levels depends on volume (gradient from gradient_start_color to gradient_end_color).
Visualization:
Liquidity levels are displayed as horizontal lines.
Volumes at levels are shown as text labels.
RSI Filtering:
The ability to enable/disable RSI filtering (rsi_filter).
Liquidity levels are filtered based on overbought (rsi_overbought) and oversold (rsi_oversold) conditions.
Levels that do not meet RSI conditions are not displayed.
MACD Filtering:
The ability to enable/disable MACD filtering (macd_filter).
Liquidity levels are filtered based on the MACD histogram condition (e.g., only if the histogram is above zero).
Levels that do not meet MACD conditions are not displayed.
Display of Market Maker Buys:
Condition for market maker buys:
Volume exceeds the average volume over the last 20 bars by 2 times.
Closing price is above the opening price.
Market maker buys are displayed on the chart as orange MM Buy markers below the candle.
Indicator Settings:
Moving average parameters:
short_ma_length: Period for the short MA.
long_ma_length: Period for the long MA.
Liquidity heatmap parameters:
liquidity_step: Step between liquidity levels.
max_levels: Maximum number of levels to display.
time_filter: Time filter (last N bars).
min_volume_filter: Minimum volume for displaying a level.
volatility_filter: Volatility filter (ATR multiplier).
RSI parameters:
rsi_filter: Enable/disable RSI filtering.
rsi_overbought: Overbought RSI level.
rsi_oversold: Oversold RSI level.
MACD parameters:
macd_filter: Enable/disable MACD filtering.
Color settings:
gradient_start_color: Starting color of the gradient.
gradient_end_color: Ending color of the gradient.
Visualization:
Moving averages:
Short MA: Blue line.
Long MA: Red line.
Signals:
Buy: Green BUY marker.
Sell: Red SELL marker.
Liquidity heatmap:
Liquidity levels: Horizontal lines with a color gradient.
Volumes: Text labels at levels.
Market maker buys:
Orange MM Buy markers.
Alerts:
The ability to set alerts for signals:
Buy (BUY).
Sell (SELL).
Additional Features:
Flexible filter settings:
Filtering by time, volume, volatility, RSI, and MACD.
Extensibility:
The ability to add new filters (e.g., Stochastic, Volume Profile, etc.).
Visual customization:
Adjustment of colors, sizes, and display styles.
Summary:
The indicator provides a comprehensive tool for analyzing liquidity, generating trading signals, and tracking market maker activity. It combines:
A liquidity heatmap.
Signals based on moving averages.
Filtering by RSI and MACD.
Display of market maker buys.
Flexible settings and visualization.
This indicator is suitable for traders who want to analyze liquidity levels, identify entry and exit points, and monitor the actions of large market players.
SMA Trend Filter Oscillator (Adaptive)The "SMA Trend Filter Oscillator (Adaptive)" indicator is a technical analysis tool that helps traders determine the direction and strength of a trend based on an adaptive Simple Moving Average (SMA). The oscillator calculates the difference between the closing price and the SMA value, allowing for the visualization of price deviation from the average and the assessment of current market dynamics.
Key Features of the Indicator:
Adaptation to Time Frame: The indicator automatically adjusts the SMA length based on the current time frame, making it versatile for use across different time intervals. For example:
Monthly Time Frame: SMA with a length of 50.
Weekly Time Frame: SMA with a length of 40.
Daily Time Frame: SMA with a length of 20.
Hourly Time Frame: SMA with a length of 10.
Intraday Time Frames: SMA with a length of 5 (for time frames up to 15 minutes) or 7 (for others).
SMA-Based Oscillator: The oscillator is calculated as the difference between the closing price and the SMA value. This allows:
Bullish Trend Identification: When the oscillator is above zero (price is above SMA).
Bearish Trend Identification: When the oscillator is below zero (price is below SMA).
Visualization: The oscillator is displayed as a histogram, where:
Green Color indicates a bullish trend.
Red Color indicates a bearish trend.
The Zero Line (Gray) serves as a reference for trend reversal.
How to Use the Indicator:
Trend Identification: If the oscillator is above zero and colored green, it signals a bullish trend. If it is below zero and colored red, it indicates a bearish trend.
Trend Strength: The larger the oscillator value (in either direction), the stronger the trend. Small oscillator values (close to zero) may indicate sideways movement or weak trend.
Entry and Exit Points:
Buy: When the oscillator crosses the zero line from below to above (transition from red to green).
Sell: When the oscillator crosses the zero line from above to below (transition from green to red).
Signal Filtering: Use the indicator in combination with other technical analysis tools (e.g., RSI, MACD, or support/resistance levels) to confirm signals.
Advantages of the Indicator:
Adaptability: Automatic adjustment of SMA length to the current time frame makes it versatile.
Simplicity: Intuitive histogram visualization allows for quick assessment of market conditions.
Flexibility: Can be used on any market (stocks, forex, cryptocurrencies) and time frame.
Limitations:
Lag: Like any SMA-based indicator, it can lag due to the use of average values.
False Signals: In sideways markets (flat), the indicator may generate false signals.
Risk Management:
Always set stop-losses and take-profits to minimize losses.
Test the indicator on historical data before using it on a live account.
The "SMA Trend Filter Oscillator (Adaptive)" is a powerful tool for traders seeking to quickly evaluate trends and their strength. Its adaptability and simplicity make it suitable for both novice and experienced traders.
Индикатор "SMA Trend Filter Oscillator (Adaptive)" — это инструмент технического анализа, который помогает трейдерам определять направление тренда и его силу на основе адаптивной скользящей средней (SMA). Осциллятор рассчитывает разницу между ценой закрытия и значением SMA, что позволяет визуализировать отклонение цены от среднего значения и оценивать текущую рыночную динамику.
Основные особенности индикатора:
Адаптация к таймфрейму
Индикатор автоматически подстраивает длину SMA в зависимости от текущего таймфрейма, что делает его универсальным для использования на различных временных интервалах. Например:
Месячный таймфрейм (Monthly): SMA с длиной 50.
Недельный таймфрейм (Weekly): SMA с длиной 40.
Дневной таймфрейм (Daily): SMA с длиной 20.
Часовой таймфрейм (Hourly): SMA с длиной 10.
Внутридневные таймфреймы (Intraday): SMA с длиной 5 (для таймфреймов до 15 минут) или 7 (для остальных).
Осциллятор на основе SMA
Осциллятор рассчитывается как разница между ценой закрытия и значением SMA. Это позволяет:
Определять бычий тренд, когда осциллятор выше нуля (цена выше SMA).
Определять медвежий тренд, когда осциллятор ниже нуля (цена ниже SMA).
Визуализация
Осциллятор отображается в виде гистограммы, где:
Зелёный цвет указывает на бычий тренд.
Красный цвет указывает на медвежий тренд.
Линия нуля (серая) служит ориентиром для определения смены тренда.
Как использовать индикатор:
Определение тренда
Если осциллятор находится выше нуля и окрашен в зелёный цвет, это сигнализирует о бычьем тренде.
Если осциллятор находится ниже нуля и окрашен в красный цвет, это указывает на медвежий тренд.
Сила тренда
Чем больше значение осциллятора (в положительную или отрицательную сторону), тем сильнее тренд.
Небольшие значения осциллятора (близкие к нулю) могут указывать на боковое движение или слабость тренда.
Точки входа и выхода
Покупка (Buy): Когда осциллятор пересекает нулевую линию снизу вверх (переход из красной зоны в зелёную).
Продажа (Sell): Когда осциллятор пересекает нулевую линию сверху вниз (переход из зелёной зоны в красную).
Фильтрация сигналов
Используйте индикатор в сочетании с другими инструментами технического анализа (например, RSI, MACD или уровнями поддержки/сопротивления) для подтверждения сигналов.
Преимущества индикатора:
Адаптивность: Автоматическая настройка длины SMA под текущий таймфрейм делает индикатор универсальным.
Простота: Интуитивно понятная визуализация в виде гистограммы позволяет быстро оценить рыночную ситуацию.
Гибкость: Может использоваться на любых рынках (акции, форекс, криптовалюты) и таймфреймах.
Ограничения:
Запаздывание: Как и любой индикатор на основе SMA, он может запаздывать из-за использования средних значений.
Ложные сигналы: В условиях бокового движения (флэта) индикатор может генерировать ложные сигналы.
Управление рисками: Всегда устанавливайте стоп-лоссы и тейк-профиты, чтобы минимизировать потери.
Тестирование: Перед использованием на реальном счёте протестируйте индикатор на исторических данных.
Индикатор "SMA Trend Filter Oscillator (Adaptive)" — это мощный инструмент для трейдеров, которые хотят быстро оценить тренд и его силу. Его адаптивность и простота делают его подходящим как для начинающих, так и для опытных трейдеров
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.
Pearson OscillatorThe Pearson Oscillator is a custom TradingView indicator that leverages statistical correlation analysis to gauge the trend strength of a given price series. By calculating the Pearson correlation coefficient between time (as an index) and price over a user-defined period, the indicator provides traders with an insight into how strongly the market is trending or oscillating.
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Key Features
- User-Defined Parameters:
– Set the calculation length, price source, and smoothing period.
– Adjust upper and lower threshold levels to suit your trading strategy.
– Customize color settings for increasing, decreasing, and neutral conditions.
- Dynamic Trend Analysis:
– Computes the Pearson correlation coefficient to measure the relationship between time and price.
– Applies a simple moving average to smooth out fluctuations in the coefficient, offering a more stable reading.
- Visual Representation:
– Plots the smoothed Pearson coefficient as a continuous line.
– Displays a histogram showing the variation (first derivative) of the coefficient to highlight changes in trend strength.
– Draws horizontal reference lines at the specified upper and lower thresholds as well as at the zero level for quick visual assessment.
- Alerts and Dynamic Labeling:
– Automatically triggers alerts when the smoothed Pearson coefficient crosses the predefined threshold levels, so you never miss a potential market turning point.
– Generates a dynamic label on the last bar that displays important statistical information, including:
- The current Pearson coefficient (rounded to three decimals).
- A classification of correlation strength (e.g., STRONG, MEDIUM, WEAK, NEUTRAL) based on the absolute value of the coefficient.
- The trend direction (Upward, Downward, or Stable).
- The delta of the coefficient, offering insight into how quickly the trend is evolving.
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How It Works
1. Calculation of the Pearson Coefficient:
- A custom function iterates over a specified number of price bars, summing time indices, price values, and their squared and cross-products.
- Using the Pearson correlation formula, it computes a coefficient that ranges between -1 and 1—values close to ±1 indicate a strong trend or linear relationship, while values near 0 suggest a weak or non-existent trend.
2. Smoothing Process:
- The raw Pearson coefficient is then smoothed using a simple moving average (SMA) to reduce noise and provide a clearer view of the underlying trend.
3. Delta (Variation) Computation:
- The script calculates the change (delta) between the current smoothed coefficient and its value on the previous bar.
- This derivative is plotted as a histogram, signaling the speed at which the correlation (and thus the trend) is changing.
4. Visual and Alert Mechanisms:
- The smoothed coefficient and its delta are plotted with colors that dynamically update to reflect increasing or decreasing trends.
- Horizontal lines set at user-defined thresholds help to quickly identify overbought or oversold (or extreme correlation) scenarios.
- Alerts are defined to notify you when the smoothed coefficient crosses these key levels, ensuring timely trade decisions.
5. Dynamic Label:
- At the last bar, a dynamic label is created displaying the current Pearson value, its strength, the direction of the trend, and the delta.
- This quick snapshot helps traders assess the market condition at a glance without diving into detailed analysis.
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Why Use the Pearson Oscillator?
This indicator is particularly useful for traders who need a quantitative measure of trend strength that goes beyond traditional moving averages. By integrating statistical correlation directly into market analysis, the Pearson Oscillator helps you:
- Identify periods of strong trending behavior or potential reversals.
- Enhance your risk management through early alerts.
- Visualize the rate of change in market sentiment, enabling more informed entry and exit decisions.
Whether you are a technical analyst or a systematic trader, this indicator provides a robust tool to complement your existing trading toolkit.
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The Pearson Oscillator merges statistical insights with technical charting, creating an intuitive yet powerful tool for market analysis. With its adjustable parameters, visual cues, dynamic labeling, and automated alerts, it assists traders in monitoring and responding to evolving market conditions efficiently. This makes it a valuable addition to any TradingView chart, particularly for those looking to quantify the strength and evolution of market trends.
Feel free to adapt the parameters and visual settings to best align the indicator with your trading strategy. Happy trading!
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
EMA Alignment & Spread Monitor (Sang Youn)Overview
The EMA Alignment & Spread Monitor is a dynamic trading script designed to monitor EMA (Exponential Moving Average) alignments, track spread deviations, and provide real-time alerts when significant conditions are met. This script allows traders to customize their EMA periods, analyze market trends based on EMA positioning, and receive visual and audio alerts when key spread conditions occur.
🔹 Key Features
✅ Customizable EMA Periods – Users can input their own EMA lengths to adapt the script to various market conditions. (Default: 5, 10, 20, 60, 120)
✅ EMA Alignment Detection – Identifies bullish alignment (all EMAs in ascending order) and bearish alignment (all EMAs in descending order).
✅ Spread Calculation & Monitoring – Computes the spread difference between each EMA and tracks the average spread over a user-defined period.
✅ Deviation Alerts – Notifies traders when:
Bullish Trend: The spread exceeds its average, indicating a potential strong uptrend.
Bearish Trend: The spread falls below its average, signaling a possible downtrend.
✅ Chart Annotations – Displays 📈 (green triangle) when bullish spread exceeds average and 📉 (red triangle) when bearish spread drops below average for easy visualization.
✅ Real-time Alerts – Sends alerts when spread conditions are met, helping traders react to market shifts efficiently.
✅ Spread Histogram – Visual representation of bullish and bearish spread levels for trend analysis.
🔹 How It Works
1️⃣ Set your EMA periods in the script settings (default: 5, 10, 20, 60, 120).
2️⃣ Define the spread average calculation length (default: 50 candles).
3️⃣ The script tracks EMA alignment to determine bullish or bearish trends.
4️⃣ If the spread deviates significantly from its average, the script:
Places a 📈 green triangle above candles in a bullish trend when spread > average.
Places a 📉 red triangle below candles in a bearish trend when spread < average.
Triggers an alert for timely decision-making.
5️⃣ Use the histogram & real-time alerts to stay ahead of market movements.
Bitcoin Total VolumeThis Pine Script indicator, titled "Bitcoin Top 16 Volume," is designed to provide traders with an aggregate view of Bitcoin (BTC) spot trading volume across leading cryptocurrency exchanges. Unlike traditional volume indicators that focus on a single exchange, this tool compiles data from a selection of the top exchanges as ranked by CoinMarketCap, offering a broader perspective on overall market activity.
The indicator works by fetching real-time volume data for specific BTC trading pairs on various exchanges. It currently incorporates data from prominent platforms such as Binance (BTCUSDT), Coinbase (BTCUSD), OKX (BTCUSDT), Bybit (BTCUSDT), Kraken (BTCUSD), Bitfinex (BTCUSD), Bitstamp (BTCUSD), Gemini (BTCUSD), Upbit (BTCKRW), Bithumb (BTCKRW), KuCoin (BTCUSDT), Gate.io (BTCUSDT), MEXC (BTCUSDT), Crypto.com (BTCUSD), Poloniex (BTCUSDT), and BitMart (BTCUSDT). It's important to note that while the indicator aims to represent the "Top 16" exchanges, the actual number included may vary due to data availability within TradingView and the dynamic nature of exchange rankings.
The script then calculates the total volume by summing up the volume data retrieved from each of these exchanges. This aggregated volume is visually represented as a histogram directly on your TradingView chart, displayed in white by default. By observing the height of the histogram bars, traders can quickly assess the total trading volume for Bitcoin spot markets over different time periods, corresponding to the chart's timeframe.
This indicator is valuable for traders seeking to understand the overall market depth and liquidity of Bitcoin. Increased total volume can often signal heightened market interest and potential trend strength or reversals. Conversely, low volume might suggest consolidation or reduced market participation. Traders can use this indicator to confirm trends, identify potential breakouts, and gauge the general level of activity in the Bitcoin spot market across major exchanges. Keep in mind that the list of exchanges included may need periodic updates to accurately reflect the top exchanges as rankings on CoinMarketCap evolve.
Shavarie's MCV IndicatorShavarie's MCV Indicator (MACD + CCI + Volume Delta) is a custom-built trend-following and volume-based indicator that helps traders confirm market direction with high accuracy. It combines the MACD (Moving Average Convergence Divergence), CCI (Commodity Channel Index), and Volume Delta, ensuring that all three indicators align before making a trading decision. The goal is to filter out false signals and provide high-probability trade setups.
History & Development
Shavarie's MCV Indicator was developed by Shavarie Gordon, an experienced swing trader, to improve trend confirmation on Gold (XAUUSD) and other markets. After testing various indicators, Shavarie discovered that MACD, CCI, and Volume Delta together provide the best combination of trend strength, momentum, and real-time volume flow. This indicator was designed to eliminate lagging signals, improve win rates, and enhance market timing for both swing and scalping strategies.
How It Works & Calculations
MACD (Moving Average Convergence Divergence)
Measures momentum and trend strength using the difference between a 12-period EMA and a 26-period EMA.
The MACD line and Signal line crossover confirms buy/sell signals.
A rising MACD histogram confirms bullish strength, while a falling histogram confirms bearish strength.
CCI (Commodity Channel Index)
Measures how far the price is from its statistical average.
Above +100 → Overbought (strong trend continuation or reversal).
Below -100 → Oversold (strong trend continuation or reversal).
When CCI aligns with MACD, it confirms momentum strength.
Volume Delta
Measures the difference between buying and selling volume in real time.
A positive delta means more aggressive buying (bullish).
A negative delta means more aggressive selling (bearish).
Helps confirm MACD and CCI trends by showing real volume strength.
Key Takeaways & Features
✅ No false signals: All three indicators must align before entering a trade.
✅ Trend confirmation: Ensures momentum and volume agree before trading.
✅ Works on multiple timeframes: Designed for swing trading on the daily and scalping on 45 min + 5 min.
✅ Great for Gold & Metals: Optimized for XAUUSD, XAUJPY, XAU/AUD, and possibly Palladium (XPDUSD).
✅ Custom-built by a professional trader: Developed by Shavarie Gordon after extensive testing.
Summary
Shavarie’s MCV Indicator is a powerful and reliable trading tool that combines momentum, trend, and volume analysis. By ensuring that MACD, CCI, and Volume Delta align, it eliminates false signals and increases trade accuracy. Whether used for swing trading or scalping, this indicator helps traders enter high-probability trades with confidence.
EMA Scoring Strategy## **📊 EMA Scoring Strategy for Trend Analysis**
This strategy is designed to **identify bullish trends** based on multiple **Exponential Moving Averages (EMAs)**. It assigns a **score** based on how the price and EMAs interact, and highlights strong bullish conditions when the score reaches **4 or above**.
---
## **🔹 Strategy Logic**
### 1️⃣ **Calculating EMAs**
- **EMA 21** → Short-term trend
- **EMA 50** → Mid-term trend
- **EMA 100** → Long-term trend
---
### 2️⃣ **Scoring System**
For each trading day, the strategy assigns **+1 or -1 points** based on the following conditions:
| Condition | Score |
|-----------|-------|
| If **Price > EMA 21** | +1 |
| If **Price > EMA 50** | +1 |
| If **Price > EMA 100** | +1 |
| If **EMA 21 > EMA 50** | +1 |
| If **EMA 50 > EMA 100** | +1 |
| If **EMA 21 > EMA 100** | +1 |
| If **Price < EMA 21** | -1 |
| If **Price < EMA 50** | -1 |
| If **Price < EMA 100** | -1 |
| If **EMA 21 < EMA 50** | -1 |
| If **EMA 50 < EMA 100** | -1 |
| If **EMA 21 < EMA 100** | -1 |
---
### 3️⃣ **Bullish Confirmation** (Score ≥ 4)
- The **score is calculated every day**.
- When the **score reaches 4 or above**, it confirms a strong **bullish trend**.
- A **green background** is applied to highlight such days.
- A **histogram** is plotted **only when the score is 4 or higher** to keep the chart clean.
- A **buy signal** is generated when the score **crosses above 4**.
---
## **🔹 Visualization & Alerts**
### ✅ **What You See on the Chart**
1. **EMA Lines (21, 50, 100)** 📈
2. **Green Background for Strong Bullish Days (Score ≥ 4)** ✅
3. **Histogram Showing Score (Only for 4 and above)** 📊
4. **Buy Signal When Score Crosses Above 4** 💰
### 🔔 **Alerts**
- **An alert is triggered** when the score crosses **above 4**, notifying the user about a bullish trend.
---
## **📌 How to Use This Strategy**
1. **Identify Strong Bullish Trends:** When the score is **4 or above**, it suggests that price momentum is strong.
2. **Enter Trades on Buy Signals:** When the score **crosses above 4**, it could be a good time to buy.
3. **Stay in the Trade While Score is 4+:** The green background confirms a **strong uptrend**.
4. **Exit When Score Drops Below 4:** This suggests weakening momentum.
---
## **🔹 Advantages of This Strategy**
✅ **Simple & Objective** - Uses clear rules for trend confirmation
✅ **Filters Out Noise** - Only highlights strong bullish conditions
✅ **Works on Any Market** - Can be applied to stocks, indices, crypto, etc.
✅ **Customizable** - You can tweak EMAs or score conditions as needed
---
## **🚀 Next Steps**
Would you like me to add **stop-loss conditions**, **sell signals**, or any **extra confirmations like RSI or volume**? 😃
GM+For a Short Trade:
When a bullish candle (close > open) is larger than the previous candle and the MACD histogram for the past three bars is consecutively lower (suggesting weakening upward momentum), the script enters a short position.
For a Long Trade:
When a bearish candle (close < open) is larger (in body size) than the previous candle and the MACD histogram for the past three bars is consecutively higher (suggesting the downward move is losing strength), the script enters a long position.
Position Management:
There are no stop loss or take profit levels. The position is closed only when an opposite signal appears.
Enhanced Momentum Divergence Radar+ [Alpha Extract]Enhanced Momentum Divergence Radar+
The AE's Enhanced Momentum Divergence Radar+ is designed to detect momentum shifts and divergence patterns, helping traders identify potential trend reversals and continuation points. By normalizing momentum readings and applying divergence detection, it enhances market timing for entries and exits.
🔶 CALCULATION
The indicator calculates normalized momentum using a combination of Detrended Price Oscillator (DPO) and volatility-adjusted smoothing techniques. It highlights overbought and oversold conditions while identifying bullish and bearish divergences.
Core Calculation:
ATR-based volatility adjustment ensures dynamic sensitivity.
DPO is derived from the price minus a simple moving average (SMA) to isolate cyclical movements.
Momentum score is normalized using historical max values for consistent scaling.
Thresholds are dynamically adjusted based on average absolute momentum.
dpo = close - ma
sd = (dpo / volatility) * 100
normalizedSD = sd / maxAbsSD
The momentum score is plotted as a histogram, where:
Green bars indicate strong upward momentum.
Red bars indicate strong downward momentum.
Neutral values fade into gray.
🔶 DETAILS
📊 Visual Features:
Histogram bars dynamically color-coded based on momentum strength.
Threshold bands provide reference points for overbought and oversold levels.
Divergence markers (Bullish/Bearish & Hidden Bullish/Bearish) highlight key reversal signals.
🛠 How Divergences Work:
Bullish Divergence (𝓞𝓢): Price makes a lower low while momentum makes a higher low.
Bearish Divergence (𝓞𝓑): Price makes a higher high while momentum makes a lower high.
Hidden Divergences confirm trend continuations rather than reversals.
📌 Example of Divergence Logic:
bullishDiv = (low == priceLow) and (sd > momentumLow)
bearishDiv = (high == priceHigh) and (sd < momentumHigh)
🔶 EXAMPLES
📍 The chart below illustrates price reacting to momentum divergences, identifying potential tops and bottoms before major price moves.
📌 Example snapshots:
A bullish divergence leading to a reversal in price.
A bearish divergence marking the beginning of a downtrend.
🔶 SETTINGS
🔹 Customization Options:
Lookback Period: Adjusts sensitivity to market cycles.
Smoothing Period: Controls signal clarity.
Color Options: Enables bar coloring based on momentum strength.
Divergence Sensitivity: Choose to display hidden divergences.
Market Sentiment - Historic Movement & Pending Orders The "Market Sentiment Osc" is a custom trading indicator designed to assess market sentiment based on bid-ask and tick-based data. This oscillator aggregates data from two key sources:
It measures the balance between market upticks, market downticks, cumulative bids and cumulative asks. By doing this we are attempting to guage sentiment by combining the actions that have happened in the past as well as the pending actions the market is willing to make.
The indicator combines these two components to form a composite oscillator that highlights shifts in market sentiment. When the composite value is positive, it suggests a bullish trend, while a negative value indicates bearish sentiment.
The Hoodie Market Trend is plotted as a histogram, with color coding:
Green: Bullish momentum (positive values).
Red: Bearish momentum (negative values).
Additionally, the user can toggle the histogram visibility with the provided input option.
This oscillator can be applied across various timeframes and stock symbols without allowing for symbol customization, making it a simple yet effective tool for market trend analysis. The zero line (purple) serves as a reference point to gauge whether the market is in a bullish or bearish phase.
Opening Score with DivergenceOverview
The Opening Score Indicator is a versatile tool designed to help traders assess market sentiment, trend direction, and potential reversals. By combining Opening Range Breakout (ORB), VWAP, Trend, Volatility, and Divergence Detection, this indicator provides a composite score that adapts to different market conditions.
This version includes divergence detection between the Opening Score and price, which highlights potential trend reversals or continuations before they happen. When a regular divergence occurs, the histogram bar turns orange, signaling an increased probability of a trend change.
Best for Both Intraday & Longer-Term Charts
📊 Optimized for intraday trading → Works well on 1m to 30m timeframes for short-term strategies.
📈 Also effective on longer-term charts → Can be used on 1-hour, 4-hour, daily, or weekly charts to identify macro trends and momentum shifts.
🕰️ Adapts to different market conditions → Whether you’re a day trader, swing trader, or position trader, the Opening Score helps you track trend health and reversals.
How It Works
📊 Composite Opening Score Calculation
• ORB Signal → Detects bullish/bearish breakouts based on the opening range.
• VWAP Signal → Measures price positioning relative to VWAP for trend confirmation.
• Trend Signal → Uses a moving average to determine market direction.
• Volatility Signal → Tracks ATR changes to assess market strength.
• Divergence Detection → Identifies regular and hidden divergences for potential reversals or trend continuation.
🔹 Reversal Alerts with Color-Coded Histogram
• Green Bars → Normal bullish Opening Score.
• Red Bars → Normal bearish Opening Score.
• Orange Bars → Warning! Regular Divergence detected → Possible trend reversal.
🔹 Hidden & Regular Divergence Detection
• Regular Divergence (Reversal Signals)
• 📉 Bearish Regular Divergence → Price makes a Higher High, but Opening Score makes a Lower High → 🔻 Possible Downtrend Reversal.
• 📈 Bullish Regular Divergence → Price makes a Lower Low, but Opening Score makes a Higher Low → 🔼 Possible Uptrend Reversal.
• Hidden Divergence (Trend Continuation Signals)
• 📉 Bearish Hidden Divergence → Price makes a Lower High, but Opening Score makes a Higher High → 🔻 Trend Likely to Continue Down.
• 📈 Bullish Hidden Divergence → Price makes a Higher Low, but Opening Score makes a Lower Low → 🔼 Trend Likely to Continue Up.
How to Use It
✅ Watch for Reversal Alerts (Orange Bars) → These highlight potential market turning points.
✅ Use the Zero Line as a Trend Filter → A score above 0 suggests bullish conditions, while below 0 signals bearish conditions.
✅ Combine with Market Structure & Volume Profile → Works well when paired with support/resistance levels, liquidity zones, and order flow data.
✅ Adjust settings based on timeframe → Increase moving average length & lookback periods for longer-term analysis.
Why Use This Indicator?
🚀 Works for both short-term and long-term traders → Adapts to intraday and higher timeframes.
📊 Multi-Factor Analysis → Combines multiple key market indicators for better accuracy.
🎯 Customizable Weighting → Adjust the influence of each signal to suit your trading style.
✅ No Clutter – Only the Opening Score is plotted → Keeps your chart clean & efficient.
🔔 Recommended for Intraday Trading (1m – 30m) AND Longer-Term Analysis (1H – Weekly) → Use this indicator to enhance your trend detection & reversal strategy! 🚀
Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Aggregated Volume (Multi-Exchange)Indicator: Aggregated Volume (Multi-Exchange)
Overview:
The Aggregated Volume (Multi-Exchange) indicator is designed to aggregate trading volume data from multiple exchanges for a specific cryptocurrency pair. The goal is to provide a consolidated view of the total trading volume across different platforms, helping traders and analysts gauge the overall market activity for a given asset.
Features:
Multi-Exchange Support: The indicator allows you to aggregate trading volume data from various exchanges. Users can enable or disable volume data from specific exchanges (e.g., Binance, Bybit, Kucoin, etc.).
Spot and Futures Volumes: The indicator can sum the volume for spot trading and futures trading separately if desired. However, in the current version, it only sums the volume for specific pairs across multiple exchanges, without distinguishing between spot and futures volumes (though this feature can be added if necessary).
Customizable Exchange Selection: Users can select which exchanges' volume data to include in the aggregation.
Real-Time Updates: The volume data is updated in real-time as new bars are formed on the chart, providing an up-to-date picture of the trading volume.
Purpose:
The primary purpose of this indicator is to consolidate trading volume information from multiple exchanges for the same trading pair (e.g., BTC/USD). Traders can use this aggregated volume to gain a better understanding of market activity across various platforms, as well as assess the level of liquidity and interest in a particular asset.
By viewing the total aggregated volume, traders can:
Track market trends: Higher aggregated volume can signal increased market interest, making it easier to spot trends or potential breakouts.
Analyze liquidity: This indicator can help traders assess liquidity in the market, especially when using multiple exchanges.
Identify potential market manipulation: If there is a sudden spike in volume on multiple exchanges, it could signal market manipulation or an event-driven surge.
How it Works:
Volume Aggregation: The indicator collects and sums the volume data for a given symbol (e.g., BTC/USD) from different exchanges like Binance, Bybit, Kucoin, and others.
Multiple Exchanges: The volume data is aggregated from each selected exchange and plotted as a single volume value on the chart.
Real-Time Volume Plotting: The total aggregated volume is then plotted as a histogram on the chart, with the color of the bars changing depending on whether the price is rising or falling (typically green for rising prices and red for falling prices).
Inputs/Settings:
Exchange Selection: A list of checkboxes where users can choose which exchanges' volume data to include (e.g., Binance, Bybit, Kucoin, etc.).
Color Settings: Users can set the color for the histogram bars based on price direction (e.g., green for rising and red for falling).
Volume Calculation: The indicator calculates the volume for a specific cryptocurrency pair across selected exchanges in real-time.
Volatility & Big Market MovesThis indicator shows the volatility per candle, and highlights candles where volatility exceeds a defined threshold.
Data shown:
Furthest %-distance from the previous candle's closing price to the top (positive histogram).
Furthest %-distance from the previous candle's closing price to the bottom (negative histogram).
Xmaster Formula Indicator [TradingFinder] No Repaint Strategies🔵 Introduction
The Xmaster Formula Indicator is a powerful tool for forex trading, combining multiple technical indicators to provide insights into market trends, support and resistance levels, and price reversals. Developed in the early 2010s, it is widely valued for generating reliable buy and sell signals.
Key components include Exponential Moving Averages (EMA) for identifying trends and price momentum, and MACD (Moving Average Convergence Divergence) for analyzing trend strength and direction.
The Stochastic Oscillator and RSI (Relative Strength Index) enhance accuracy by signaling potential price reversals. Additionally, the Parabolic SAR assists in identifying trend reversals and managing risk.
By integrating these tools, the Xmaster Formula Indicator provides a comprehensive view of market conditions, empowering traders to make informed decisions.
🔵 How to Use
The Xmaster Formula Indicator offers two distinct methods for generating signals: Standard Mode and Advance Mode. Each method caters to different trading styles and strategies.
Standard Mode :
In Standard Mode, the indicator uses normalized moving average data to generate buy and sell signals. The difference between the short-term (10-period) and long-term (38-period) EMAs is calculated and normalized to a 0-100 scale.
Buy Signal : When the normalized value crosses above 55, accompanied by the trend line turning green, a buy signal is generated.
Sell Signal : When the normalized value crosses below 45, and the trend line turns red, a sell signal is issued.
This mode is simple, making it ideal for traders looking for straightforward signals without the need for additional confirmations.
Advance Mode :
Advance Mode combines multiple technical indicators to provide more detailed and robust signals.
This method analyzes trends by incorporating :
🟣 MACD
Buy Signal : When the MACD histogram bars are positive.
Sell Signal : When the MACD histogram bars are negative.
🟣 RSI
Buy Signal : When RSI is below 30, indicating oversold conditions.
Sell Signal : When RSI is above 70, suggesting overbought conditions.
🟣 Stochastic Oscillator
Buy Signal : When Stochastic is below 20.
Sell Signal : When Stochastic is above 80.
🟣 Parabolic SAR
Buy Signal : When SAR is below the price.
Sell Signal : When SAR is above the price.
A signal is generated in Advance Mode only when all these indicators align :
Buy Signal : All conditions point to a bullish trend.
Sell Signal : All conditions indicate a bearish trend.
This mode is more comprehensive and suitable for traders who prefer deeper analysis and stronger confirmations before executing trades.
🔵 Settings
Method :
Choose between "Standard" and "Advance" modes to determine how signals are generated. In Standard Mode, signals are based on normalized moving average data, while in Advance Mode, signals rely on the combination of MACD, RSI, Stochastic Oscillator, and Parabolic SAR.
Moving Average Settings :
Short Length : The period for the short-term EMA (default is 10).
Mid Length : The period for the medium-term EMA (default is 20).
Long Length : The period for the long-term EMA (default is 38).
MACD Settings :
Fast Length : The period for the fast EMA in the MACD calculation (default is 12).
Slow Length : The period for the slow EMA in the MACD calculation (default is 26).
Signal Line : The signal line period for MACD (default is 9).
Stochastic Settings :
Length : The period for the Stochastic Oscillator (default is 14).
RSI Settings :
Length : The period for the Relative Strength Index (default is 14).
🔵 Conclusion
The Xmaster Formula Indicator is a versatile and reliable tool for forex traders, offering both simplicity and advanced analysis through its Standard and Advance modes. In Standard Mode, traders benefit from straightforward signals based on normalized moving average data, making it ideal for quick decision-making.
Advance Mode, on the other hand, provides a more detailed analysis by combining multiple indicators like MACD, RSI, Stochastic Oscillator, and Parabolic SAR, delivering stronger confirmations for critical market decisions.
While the Xmaster Formula Indicator offers valuable insights and reliable signals, it is important to use it alongside proper risk management and other analytical methods. By leveraging its capabilities effectively, traders can enhance their trading strategies and achieve better outcomes in the dynamic forex market.
Adaptive Momentum Cycle Oscillator (AMCO)1. Concept and Foundation
The Adaptive Momentum Cycle Oscillator (AMCO) is an advanced indicator designed to dynamically adjust to varying market conditions while identifying price cycles and trends. It combines momentum and volatility into a single, oscillating signal that helps traders detect turning points in price movements. By incorporating adaptive periods and trend filtering, AMCO ensures relevance across different asset classes and timeframes. This innovation bridges the gap between traditional oscillators and trending indicators, providing a comprehensive tool for both cycle identification and trend confirmation.
2. Dynamic Adaptation to Market Conditions
A standout feature of AMCO is its ability to adapt its sensitivity based on market volatility. Using the ATR (Average True Range) as a measure of current volatility, AMCO adjusts its calculation periods dynamically. During periods of high volatility, it extends its lookback periods to smooth out noise and avoid false signals. Conversely, in low-volatility environments, it shortens its periods to remain responsive to smaller price fluctuations. This adaptability ensures that AMCO remains effective and reliable in both trending and ranging markets.
3. Trend Awareness and Directional Weighting
AMCO integrates a trend filter based on a long-term moving average, such as SMA(200), to align its signals with the broader market direction. This filter ensures that buy signals are prioritized during uptrends and sell signals during downtrends, reducing counter-trend trades. Additionally, a directional weighting mechanism amplifies momentum signals that align with the prevailing trend. This dual-layer approach significantly enhances the accuracy of signals, making AMCO especially useful in markets with clear directional bias.
4. Normalized Visualization for Clarity
The AMCO includes a normalized histogram that provides a clear visual representation of momentum strength relative to recent volatility. By dividing the raw AMCO value by the ATR, the histogram ensures consistency across assets with varying price ranges and volatility levels. Positive bars indicate bullish momentum, while negative bars signify bearish momentum. This intuitive visualization makes it easier for traders to interpret market dynamics and act on actionable signals, regardless of asset type or timeframe.
5. Practical and Actionable Signals
AMCO generates practical signals based on zero-line crossovers, allowing traders to easily identify shifts between bullish and bearish cycles. Positive values above the zero line suggest upward momentum, signaling potential buying opportunities, while negative values below the zero line indicate downward momentum, signaling potential sell opportunities. By combining adaptive behavior, trend filtering, and momentum-strength normalization, AMCO offers traders a robust framework for navigating complex markets with confidence. Its versatility makes it suitable for scalping, swing trading, and even longer-term investing.
