EM Yield Curve IndexThis script calculates the Emerging Markets (EM) Yield Curve Index by aggregating the 2-year and 10-year bond yields of major emerging economies. The bond yields are weighted based on each country's bond market size, with data sourced from TradingView. The yield curve is derived by subtracting the 2-year yield from the 10-year yield, providing insights into economic conditions, risk sentiment, and potential recessions in emerging markets. The resulting EM Yield Curve Index is plotted for visualization.
Note: In some cases, TradingView's TVC data did not provide a 2-year bond yield. When this occurred, the best available alternative yield (such as 3-month, 1-year or 4-year yields) was used to approximate the short-term interest rate for that country.
Поиск скриптов по запросу "腾讯10大股东"
Momentum Volume Divergence (MVD) EnhancedMomentum Volume Divergence (MVD) Enhanced is a powerful indicator that detects price-momentum divergences and momentum suppression for reversal trading. Optimized for XRP on 1D charts, it features dynamic lookbacks, ATR-adjusted thresholds, and SMA confirmation. Signals include strong divergences (triangles) and suppression warnings (crosses). Includes a detailed user guide—try it out and share your feedback!
Setup: Add to XRP 1D chart with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA crossovers. See full guide for details!
Disclaimer: This indicator is for educational purposes only, not financial advice. Trading involves risk—use at your discretion.
Momentum Volume Divergence (MVD) Enhanced Indicator User Guide
Version: Pine Script v6
Designed for: TradingView
Recommended Use: XRP on 1-day (1D) chart
Date: March 18, 2025
Author: Herschel with assistance from Grok 3 (xAI)
Overview
The Momentum Volume Divergence (MVD) Enhanced indicator is a powerful tool for identifying price-momentum divergences and momentum suppression patterns on XRP’s 1-day (1D) chart. Plotted below the price chart, it provides clear visual signals to help traders spot potential reversals and trend shifts.
Purpose
Detect divergences between price and momentum for buy/sell opportunities.
Highlight momentum suppression as warnings of fading trends.
Offer actionable trading signals with intuitive markers.
Indicator Components
Main Plot
Volume-Weighted Momentum (vw_mom): Blue line showing momentum adjusted by volume.
Above 0 = bullish momentum.
Below 0 = bearish momentum.
Zero Line: Gray dashed line at 0, separating bullish/bearish zones.
Key Signals
Strong Bearish Divergence:
Marker: Red triangle at the top.
Meaning: Price makes a higher high, but momentum weakens, confirmed by a drop below the 5-day SMA.
Action: Potential sell/short signal.
Strong Bullish Divergence:
Marker: Green triangle at the bottom.
Meaning: Price makes a lower low, but momentum strengthens, confirmed by a rise above the 5-day SMA.
Action: Potential buy/long signal.
Bearish Suppression:
Marker: Orange cross at the top + red background.
Meaning: Strong bullish momentum with low volume in a volume downtrend, suggesting fading strength.
Action: Warning to avoid longs or exit early.
Bullish Suppression:
Marker: Yellow cross at the bottom + green background.
Meaning: Strong bearish momentum with low volume in a volume uptrend, suggesting fading weakness.
Action: Warning to avoid shorts or exit early.
Debug Plots (Optional)
Volume Ratio: Gray line (volume vs. its MA) vs. yellow line (threshold).
Momentum Threshold: Purple lines (positive/negative momentum cutoffs).
Smoothed Momentum: Orange line (raw momentum).
Confirmation SMA: Purple line (price trend confirmation).
Labels
Text labels (e.g., "Bear Div," "Bull Supp") mark detected patterns.
How to Use the Indicator
Step-by-Step Trading Process
1. Monitor the Chart
Load your XRP 1D chart with the indicator applied.
Observe the blue vw_mom line and signal markers.
2. Spot a Signal
Primary Signals: Look for red triangles (strong_bear) or green triangles (strong_bull).
Warnings: Note orange crosses (suppression_bear) or yellow crosses (suppression_bull).
3. Confirm the Signal
For Strong Bullish Divergence (Buy):
Green triangle appears.
Price closes above the 5-day SMA (purple line) and a recent swing high.
Optional: Volume ratio (gray line) exceeds the threshold (yellow line).
For Strong Bearish Divergence (Sell):
Red triangle appears.
Price closes below the 5-day SMA and a recent swing low.
Optional: Volume ratio (gray line) falls below the threshold (yellow line).
4. Enter the Trade
Long:
Buy at the close of the signal bar.
Stop loss: Below the recent swing low or 2 × ATR(14) below entry.
Short:
Sell/short at the close of the signal bar.
Stop loss: Above the recent swing high or 2 × ATR(14) above entry.
5. Manage the Trade
Take Profit:
Aim for a 2:1 or 3:1 risk-reward ratio (e.g., risk $0.05, target $0.10-$0.15).
Or exit when an opposite suppression signal appears (e.g., orange cross for longs).
Trailing Stop:
Move stop to breakeven after a 1:1 RR move.
Trail using the 5-day SMA or 2 × ATR(14).
Early Exit:
Exit if a suppression signal appears against your position (e.g., suppression_bull while short).
6. Filter Out Noise
Avoid trades if a suppression signal precedes a divergence within 2-3 days.
Optional: Add a 50-day SMA on the price chart:
Longs only if price > 50-SMA.
Shorts only if price < 50-SMA.
Example Trades (XRP 1D)
Bullish Trade
Signal: Green triangle (strong_bull) at $0.55.
Confirmation: Price closes above 5-SMA and $0.57 high.
Entry: Buy at $0.58.
Stop Loss: $0.53 (recent low).
Take Profit: $0.63 (2:1 RR) or exit on suppression_bear.
Outcome: Price hits $0.64, exit at $0.63 for profit.
Bearish Trade
Signal: Red triangle (strong_bear) at $0.70.
Confirmation: Price closes below 5-SMA and $0.68 low.
Entry: Short at $0.67.
Stop Loss: $0.71 (recent high).
Take Profit: $0.62 (2:1 RR) or exit on suppression_bull.
Outcome: Price drops to $0.61, exit at $0.62 for profit.
Tips for Success
Combine with Price Levels:
Use support/resistance zones (e.g., weekly pivots) to confirm entries.
Monitor Volume:
Rising volume (gray line above yellow) strengthens signals.
Adjust Sensitivity:
Too many signals? Increase div_strength_threshold to 0.7.
Too few signals? Decrease to 0.3.
Backtest:
Review 20-30 past signals on XRP 1D to assess performance.
Avoid Choppy Markets:
Skip signals during low volatility (tight price ranges).
Troubleshooting
No Signals:
Lower div_strength_threshold to 0.3 or mom_threshold_base to 0.2.
Check if XRP’s volatility is unusually low.
False Signals:
Increase sma_confirm_length to 7 or add a 50-SMA filter.
Indicator Not Loading:
Ensure the script compiles without errors.
Customization (Optional)
Change Colors: Edit color.* values (e.g., color.red to color.purple).
Add Alerts: Use TradingView’s alert menu for "Strong Bearish Divergence Confirmed," etc.
Test Other Assets: Experiment with BTC or ETH, adjusting inputs as needed.
Disclaimer
This indicator is for educational purposes only and not financial advice. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion.
Setup: Use on XRP 1D with defaults (mom_length_base=8, vol_length_base=10). Signals: Red triangle (sell), Green triangle (buy), Orange cross (bear warning), Yellow cross (bull warning). Confirm with 5-day SMA cross. Stop: 2x ATR(14). Profit: 2:1 RR or suppression exit. Full guide available separately!
Volume Predictor [PhenLabs]📊 Volume Predictor
Version: PineScript™ v6
📌 Description
The Volume Predictor is an advanced technical indicator that leverages machine learning and statistical modeling techniques to forecast future trading volume. This innovative tool analyzes historical volume patterns to predict volume levels for upcoming bars, providing traders with valuable insights into potential market activity. By combining multiple prediction algorithms with pattern recognition techniques, the indicator delivers forward-looking volume projections that can enhance trading strategies and market analysis.
🚀 Points of Innovation:
Machine learning pattern recognition using Lorentzian distance metrics
Multi-algorithm prediction framework with algorithm selection
Ensemble learning approach combining multiple prediction methods
Real-time accuracy metrics with visual performance dashboard
Dynamic volume normalization for consistent scale representation
Forward-looking visualization with configurable prediction horizon
🔧 Core Components
Pattern Recognition Engine : Identifies similar historical volume patterns using Lorentzian distance metrics
Multi-Algorithm Framework : Offers five distinct prediction methods with configurable parameters
Volume Normalization : Converts raw volume to percentage scale for consistent analysis
Accuracy Tracking : Continuously evaluates prediction performance against actual outcomes
Advanced Visualization : Displays actual vs. predicted volume with configurable future bar projections
Interactive Dashboard : Shows real-time performance metrics and prediction accuracy
🔥 Key Features
The indicator provides comprehensive volume analysis through:
Multiple Prediction Methods : Choose from Lorentzian, KNN Pattern, Ensemble, EMA, or Linear Regression algorithms
Pattern Matching : Identifies similar historical volume patterns to project future volume
Adaptive Predictions : Generates volume forecasts for multiple bars into the future
Performance Tracking : Calculates and displays real-time prediction accuracy metrics
Normalized Scale : Presents volume as a percentage of historical maximums for consistent analysis
Customizable Visualization : Configure how predictions and actual volumes are displayed
Interactive Dashboard : View algorithm performance metrics in a customizable information panel
🎨 Visualization
Actual Volume Columns : Color-coded green/red bars showing current normalized volume
Prediction Columns : Semi-transparent blue columns representing predicted volume levels
Future Bar Projections : Forward-looking volume predictions with configurable transparency
Prediction Dots : Optional white dots highlighting future prediction points
Reference Lines : Visual guides showing the normalized volume scale
Performance Dashboard : Customizable panel displaying prediction method and accuracy metrics
📖 Usage Guidelines
History Lookback Period
Default: 20
Range: 5-100
This setting determines how many historical bars are analyzed for pattern matching. A longer period provides more historical data for pattern recognition but may reduce responsiveness to recent changes. A shorter period emphasizes recent market behavior but might miss longer-term patterns.
🧠 Prediction Method
Algorithm
Default: Lorentzian
Options: Lorentzian, KNN Pattern, Ensemble, EMA, Linear Regression
Selects the algorithm used for volume prediction:
Lorentzian: Uses Lorentzian distance metrics for pattern recognition, offering excellent noise resistance
KNN Pattern: Traditional K-Nearest Neighbors approach for historical pattern matching
Ensemble: Combines multiple methods with weighted averaging for robust predictions
EMA: Simple exponential moving average projection for trend-following predictions
Linear Regression: Projects future values based on linear trend analysis
Pattern Length
Default: 5
Range: 3-10
Defines the number of bars in each pattern for machine learning methods. Shorter patterns increase sensitivity to recent changes, while longer patterns may identify more complex structures but require more historical data.
Neighbors Count
Default: 3
Range: 1-5
Sets the K value (number of nearest neighbors) used in KNN and Lorentzian methods. Higher values produce smoother predictions by averaging more historical patterns, while lower values may capture more specific patterns but could be more susceptible to noise.
Prediction Horizon
Default: 5
Range: 1-10
Determines how many future bars to predict. Longer horizons provide more forward-looking information but typically decrease accuracy as the prediction window extends.
📊 Display Settings
Display Mode
Default: Overlay
Options: Overlay, Prediction Only
Controls how volume information is displayed:
Overlay: Shows both actual volume and predictions on the same chart
Prediction Only: Displays only the predictions without actual volume
Show Prediction Dots
Default: false
When enabled, adds white dots to future predictions for improved visibility and clarity.
Future Bar Transparency (%)
Default: 70
Range: 0-90
Controls the transparency of future prediction bars. Higher values make future bars more transparent, while lower values make them more visible.
📱 Dashboard Settings
Show Dashboard
Default: true
Toggles display of the prediction accuracy dashboard. When enabled, shows real-time accuracy metrics.
Dashboard Location
Default: Bottom Right
Options: Top Left, Top Right, Bottom Left, Bottom Right
Determines where the dashboard appears on the chart.
Dashboard Text Size
Default: Normal
Options: Small, Normal, Large
Controls the size of text in the dashboard for various display sizes.
Dashboard Style
Default: Solid
Options: Solid, Transparent
Sets the visual style of the dashboard background.
Understanding Accuracy Metrics
The dashboard provides key performance metrics to evaluate prediction quality:
Average Error
Shows the average difference between predicted and actual values
Positive values indicate the prediction tends to be higher than actual volume
Negative values indicate the prediction tends to be lower than actual volume
Values closer to zero indicate better prediction accuracy
Accuracy Percentage
A measure of how close predictions are to actual outcomes
Higher percentages (>70%) indicate excellent prediction quality
Moderate percentages (50-70%) indicate acceptable predictions
Lower percentages (<50%) suggest weaker prediction reliability
The accuracy metrics are color-coded for quick assessment:
Green: Strong prediction performance
Orange: Moderate prediction performance
Red: Weaker prediction performance
✅ Best Use Cases
Anticipate upcoming volume spikes or drops
Identify potential volume divergences from price action
Plan entries and exits around expected volume changes
Filter trading signals based on predicted volume support
Optimize position sizing by forecasting market participation
Prepare for potential volatility changes signaled by volume predictions
Enhance technical pattern analysis with volume projection context
⚠️ Limitations
Volume predictions become less accurate over longer time horizons
Performance varies based on market conditions and asset characteristics
Works best on liquid assets with consistent volume patterns
Requires sufficient historical data for pattern recognition
Sudden market events can disrupt prediction accuracy
Volume spikes may be muted in predictions due to normalization
💡 What Makes This Unique
Machine Learning Approach : Applies Lorentzian distance metrics for robust pattern matching
Algorithm Selection : Offers multiple prediction methods to suit different market conditions
Real-time Accuracy Tracking : Provides continuous feedback on prediction performance
Forward Projection : Visualizes multiple future bars with configurable display options
Normalized Scale : Presents volume as a percentage of maximum volume for consistent analysis
Interactive Dashboard : Displays key metrics with customizable appearance and placement
🔬 How It Works
The Volume Predictor processes market data through five main steps:
1. Volume Normalization:
Converts raw volume to percentage of maximum volume in lookback period
Creates consistent scale representation across different timeframes and assets
Stores historical normalized volumes for pattern analysis
2. Pattern Detection:
Identifies similar volume patterns in historical data
Uses Lorentzian distance metrics for robust similarity measurement
Determines strength of pattern match for prediction weighting
3. Algorithm Processing:
Applies selected prediction algorithm to historical patterns
For KNN/Lorentzian: Finds K nearest neighbors and calculates weighted prediction
For Ensemble: Combines multiple methods with optimized weighting
For EMA/Linear Regression: Projects trends based on statistical models
4. Accuracy Calculation:
Compares previous predictions to actual outcomes
Calculates average error and prediction accuracy
Updates performance metrics in real-time
5. Visualization:
Displays normalized actual volume with color-coding
Shows current and future volume predictions
Presents performance metrics through interactive dashboard
💡 Note:
The Volume Predictor performs optimally on liquid assets with established volume patterns. It’s most effective when used in conjunction with price action analysis and other technical indicators. The multi-algorithm approach allows adaptation to different market conditions by switching prediction methods. Pay special attention to the accuracy metrics when evaluating prediction reliability, as sudden market changes can temporarily reduce prediction quality. The normalized percentage scale makes the indicator consistent across different assets and timeframes, providing a standardized approach to volume analysis.
Gold Price LevelsThis indicator identifies and displays key price levels for gold trading. It highlights important psychological and technical price points that often act as support and resistance levels.
Features
Automatically identifies and displays key price levels ending in 92, 84, 78, 55, 42, 27, and 00
Special emphasis on critical levels ending in 68, 32, and 10 with increased line width
Color-coded visualization: green for levels above current price, red for levels below
Customizable line style, width, and label visibility
Automatically adjusts to different price ranges (works with any gold price)
How to Use
This indicator helps gold traders identify potential support and resistance zones. Watch for price reactions at these levels for potential trade entries, exits, or stop placement. The thicker lines (68, 32, 10) often represent more significant price levels where stronger reactions may occur.
Perfect for both day traders and swing traders looking to optimize their gold trading strategy with key price levels.
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
Pivot P/N VolumesTitle: Pivot P/N Volumes
Short Title: PPNV
Description:
The "Pivot P/N Volumes" indicator is a minimalistic volume analysis tool designed to cut through market noise and highlight key volume events in a separate pane. It strips away conventional volume clutter, focusing on four distinct volume types with clear visual cues, making it ideal for traders seeking actionable insights without distractions.
Key Features:
Blue Bars: Pocket Pivot Volumes (PPV) - Up-day volumes exceeding the highest down-day volume of the last 10 down-days, signaling potential bullish strength.
Orange Bars: Pivot Negative Volumes - Down-day volumes greater than the highest up-day volume of the last 10 up-days, indicating significant bearish pressure.
Red Bars: Down-day volumes above the 50-period EMA of volume, highlighting above-average selling activity.
Green Bars: Up-day volumes above the 50-period EMA of volume, showing above-average buying interest.
Noise: All other volumes are muted as dark grey (down-days) or light grey (up-days) for easy filtering.
Volume Buy/Sell ChartVolume Buy/Sell Chart
This script visualizes the distribution of buying and selling volume within each candlestick, helping traders identify dominant market pressure at a glance. It separates volume into Buy Volume (Green) and Sell Volume (Red) using a unique calculation based on price movement within a candle.
Features:
✅ Customizable Bar Display: Choose to display 5, 10, or 100 bars using a simple dropdown selection.
✅ Buy & Sell Volume Calculation: The script determines buying and selling volume dynamically based on price action within the candle.
✅ Custom Volume Threshold for Alerts: Set a percentage threshold (0–100) to trigger alerts when buy or sell volume exceeds a predefined level.
✅ Color-Coded Histogram:
Green Bars: Represent the estimated buy volume.
Red Bars: Represent the estimated sell volume.
✅ Alerts Integration: Automatically detect strong buy or sell signals when the respective volume percentage exceeds your set threshold.
How It Works:
The script calculates total price movement within a candle.
It then estimates buying and selling volume ratios based on whether the price closes higher or lower than it opened.
Finally, it normalizes the buy/sell volume against the total volume and plots it as a column chart.
Usage Guide:
Add the script to your chart.
Select how many bars to display (5, 10, or 100).
Adjust the Custom Volume Percentage Threshold (default: 75%).
Watch for significant buy/sell volume imbalances that might indicate market turning points!
This tool is great for traders looking to analyze volume flow and market sentiment with a simple yet effective visualization. 🚀
Volume Block Order AnalyzerCore Concept
The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements.
How It Works: The Mathematical Model
1. Volume Anomaly Detection
The strategy first identifies "block trades" using a statistical approach:
```
avgVolume = ta.sma(volume, lookbackPeriod)
isHighVolume = volume > avgVolume * volumeThreshold
```
This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade.
2. Directional Impact Calculation
For each block trade identified, its price action determines direction:
- Bullish candle (close > open): Positive impact
- Bearish candle (close < open): Negative impact
The magnitude of impact is proportional to the volume size:
```
volumeWeight = volume / avgVolume // How many times larger than average
blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10)
```
This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values.
3. Cumulative Impact with Time Decay
The key innovation is the cumulative impact calculation with decay:
```
cumulativeImpact := cumulativeImpact * impactDecay + blockImpact
```
This mathematical model has important properties:
- Recent block trades have stronger influence than older ones
- Impact gradually "fades" at rate determined by decay factor (default 0.95)
- Sustained directional pressure accumulates over time
- Opposing pressure gradually counteracts previous momentum
Trading Logic
Signal Generation
The strategy generates trading signals based on momentum shifts in institutional order flow:
1. Long Entry Signal: When cumulative impact crosses from negative to positive
```
if ta.crossover(cumulativeImpact, 0)
strategy.entry("Long", strategy.long)
```
*Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement*
2. Short Entry Signal: When cumulative impact crosses from positive to negative
```
if ta.crossunder(cumulativeImpact, 0)
strategy.entry("Short", strategy.short)
```
*Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement*
3. Exit Logic: Positions are closed when the cumulative impact moves against the position
```
if cumulativeImpact < 0
strategy.close("Long")
```
*Logic: The original signal is no longer valid as institutional flow has reversed*
Visual Interpretation System
The strategy employs multiple visualization techniques:
1. Color Gradient Bar System:
- Deep green: Strong buying pressure (impact > 0.5)
- Light green: Moderate buying pressure (0.1 < impact ≤ 0.5)
- Yellow-green: Mild buying pressure (0 < impact ≤ 0.1)
- Yellow: Neutral (impact = 0)
- Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0)
- Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1)
- Red: Strong selling pressure (impact ≤ -0.5)
2. Dynamic Impact Line:
- Plots the cumulative impact as a line
- Line color shifts with impact value
- Line movement shows momentum and trend strength
3. Block Trade Labels:
- Marks significant block trades directly on the chart
- Shows direction and volume amount
- Helps identify key moments of institutional activity
4. Information Dashboard:
- Current impact value and signal direction
- Average volume benchmark
- Count of significant block trades
- Min/Max impact range
Benefits and Use Cases
This strategy provides several advantages:
1. Institutional Flow Detection: Identifies where large players are positioning themselves
2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements
3. Market Context Enhancement: Provides deeper insight than simple price action alone
4. Objective Decision Framework: Quantifies what might otherwise be subjective observations
5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds
Customization Options
The strategy allows users to fine-tune its behavior:
- Volume Threshold: How unusual a volume spike must be to qualify
- Lookback Period: How far back to measure average volume
- Impact Decay Factor: How quickly older trades lose influence
- Visual Settings: Labels and line width customization
This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
JP225 Influence AnalyzerThis tool provides a way to assess how USDJPY and DJIA influence JP225, using standardization and linear regression for quantitative evaluation. It also detects deviations from the linear model and displays the results in a colored table.
Table Structure
Row 1: Current value of USDJPY and its change from the previous bar
Row 2: Current value of DJIA and its change from the previous bar
Row 3: Theoretical value of Nikkei 225 calculated using the least squares method from USDJPY
and DJIA, and its change from the previous bar
Row 4: Current value of the chart symbol (Nikkei 225) and its change from the previous bar
Background Color Meanings
A. Current Value Column (Column 2)
If USDJPY or DJIA significantly contributes to the change in the theoretical value of Nikkei 225, the cell turns blue (increase) or red (decrease). The threshold is 1.5.
If the current value of Nikkei 225 increases, it turns blue; if it decreases, it turns red.
B. Change Value Column (Column 3)
If there is a discrepancy between the change in the theoretical value and the actual change of Nikkei 225, the cell turns yellow (moderate discrepancy: threshold 20) or red (significant discrepancy: threshold 50).
Judgment Based on Current Value Column (Column 2)
If the color of USDJPY or DJIA matches the color of Nikkei 225, that symbol is the main cause.
If there is no match, the main cause is "other factors."
Judgment Based on Change Column (Column 3)
Yellow: Suggests that other factors may be influencing the price.
Red: Strongly indicates that other factors are the main cause.
Parameter Descriptions Parameter Descriptions
symbol_x: Symbol for USDJPY (default: "SAXO:USDJPY")
symbol_y: Symbol for DJIA (default: "OSE:DJIA1!")
threshold_value1: Threshold for determining the influence of USDJPY and DJIA (blue/red color) (default: 1.5)
threshold_value2: Threshold for detecting specific price movements in Nikkei 225 (yellow color) (default: 20)
threshold_value3: Threshold for detecting significant price movements in Nikkei 225 (red color) (default: 50)
data_count: Number of past data points used for calculations (default: 10)
インジケーターの概要
このインジケーターは、日経225先物やCFDの値動きの主な原因が
以下のどれに起因するのかをリアルタイムで表示します
1. ドル円 (USDJPY)
2. ダウ (DJIA)
3. その他の要因（突発的なニュース、225の節目価格への攻防など）
テーブルの構成
1行目 ドル円の現在値と前足からの増減
2行目 ダウの現在値と前足からの増減
3行目 ドル円とダウから最小二乗法で算出した225の理論値とその増減
4行目 チャート銘柄（225）の現在値と前足からの増減
背景色の意味
1. 現在値列 (2列目):ドル円またはダウが225の理論値増減に大きく寄与した場合、
それぞれ青（増加）または赤（減少）に変化。閾値は1.5
225の現在値が増加すれば青、減少すれば赤。
2. 増減値列 (3列目):225の理論値増減と実際の増減が乖離した場合、
黄（中程度：閾値は20）または赤（大幅：閾値は50）に変化。
現在値列(2列目)での判断:
1. 銘柄（ドル円またはダウ）の色が225の色と一致する場合、その銘柄が主な原因。
2. 一致しない場合、主な原因は「その他」。
増減列(3列目)での判断:
黄色 その他の要因が影響している可能性。
赤色 その他の要因が主な原因と強く示唆。
パラメータの説明
symbol_x ドル円のシンボル（デフォルト: "SAXO:USDJPY"）
symbol_y ダウのシンボル（デフォルト: "OSE:DJIA1!"）
threshold_value1 ドル円とダウの影響を判定する(青/赤色)閾値（デフォルト: 1.5）
threshold_value2 225固有の値動きを判定する(黄色)閾値（デフォルト: 20）
threshold_value3 225固有の大きな値動きを判定する(赤色)閾値（デフォルト: 50）
data_count 計算に使用する過去データの本数（デフォルト: 10）
FTB Smart Trader System — Market Maker Levels, EMAs & VectorsThe FTB Trade Engine is an indicator suite I built for myself as a crypto trader. It's designed specifically for trading Institution levels, EMAs, PVSRA Volume Candles, and Session Timings. It helps me spot high probability trade setups without overcomplicating things.
🔑 Features of this Indicator
📌 🔥 Key Session Levels (extend lines in settings as needed)
✅ Weekly High & Low (HOW/LOW) — Automatically plots the previous week's high and low
✅ Daily High & Low (HOD/LOD) — Marks the prior day's range
✅ Asia Session High & Low — Plots the Asian session’s high and low, helping you detect potential breakouts or fakeouts, as Asia often sets the initial high and low of the day.
✅ 50% Asia Level — Automatically calculates and displays the midpoint between Asia’s high and low, an important level for intraday trading.
📌 🔥 Advanced EMA Suite
✅ Includes 10, 20, 50, 200, and 800 EMAs — providing key zones of support, resistance, and trend direction.
👀 Good to know: the break of the 50EMA WITH a vector candle is significant for reversals.
📌 🔥 PVSRA Candles
(👀 IMPORTANT: To properly view PVSRA candles, make sure to UNCHECK all default candle settings — Color Bars, Body, Borders, and Wick — in your chart's candle settings.)
✅ Price, Volume, Support & Resistance Analysis (PVSRA) Candles — These special candles combine price action with volume analysis, color-coded to highlight areas potentially influenced by market makers, institutions, and large players. Perfect for identifying key volume zones and quickly analyzing any coin or pair without switching tools.
Candle Colors Explained:
Bullish Candles:
🟢 Green — 200% increase in volume on bullish moves (strong buyer presence).
🔵 Blue — 150% increase in bullish volume, but may also indicate fatigue or possible reversal.
⚪ White — Normal bullish volume (standard green candles).
Bearish Candles:
🔴 Red — 200% increase in bearish volume compared to the last 10 candles (strong selling).
🟣 Magenta — 150% increase in bearish volume, signaling possible continuation or exhaustion.
⚫ Gray — Normal bearish volume (standard red candles).
Candle Size Alertت وضیحات برای انتشار ابزار در TradingView
🔹 نام ابزار: Candle Size Alert
🔹 توضیحات:
این اندیکاتور برای شناسایی کندلهای بزرگ طراحی شده است. این ابزار میانگین اندازهی ۱۰ کندل گذشته را محاسبه کرده و اگر کندل فعلی ۳ برابر میانگین کندلهای قبلی باشد، یک لیبل هشدار در بالای کندل نمایش میدهد. همچنین میتوان هشدارهای معاملاتی را از طریق alertcondition() فعال کرد.
🔹 ویژگیها:
✅ امکان تغییر تعداد کندلهای محاسبه شده (پیشفرض: ۱۰)
✅ امکان تنظیم ضریب حساسیت (پیشفرض: ۳ برابر)
✅ نمایش لیبل هشدار در بالای کندلهای بزرگ
✅ پشتیبانی از هشدارهای خودکار (AlertCondition)
⚠️ نکته: این اندیکاتور فقط برای تحلیل استفاده میشود و سیگنال خرید یا فروش ارائه نمیدهد.
🔹 Indicator Name: Candle Size Alert
🔹 Description:
This indicator detects large candles by calculating the average size of the last 10 candles. If the current candle is 3 times larger than the average of the previous candles, a warning label appears above the candle. Additionally, automated alerts can be triggered using alertcondition().
🔹 Features:
✅ Adjustable candle count for calculations (default: 10)
✅ Customizable sensitivity multiplier (default: 3x)
✅ Visual alert label above large candles
✅ Supports automated alerts (AlertCondition)
⚠️ Note: This indicator is for analysis purposes only and does not provide buy/sell signals.
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.
Multi-Timeframe Trend Table - DOTANMulti Timeframe Trend Signal table - Wizord_KS
"Multi-Timeframe Trend Table"
This Pine Script indicator displays a table on the TradingView chart that shows the trend direction (Bullish/Bearish) across multiple timeframes. The trend is determined using a Simple Moving Average (SMA).
🔹 Key Features of the Script
Calculates trend direction based on SMA for:
The current timeframe.
10 different user-defined timeframes.
Determines a "Main Signal" based on trend strength:
Counts the number of bullish and bearish trends across all timeframes.
Uses this count to generate an overall market sentiment (Bullish, Bearish, or Neutral).
The strength of the main signal determines its background transparency.
Displays a table in the top-right corner of the chart showing:
The main trend signal (aggregated from multiple timeframes).
The trend for the current timeframe.
The trend for each of the 10 selected timeframes.
Dual SuperTrend w VIX Filter - Strategy [presentTrading]Hey everyone! Haven't been here for a long time. Been so busy again in the past 2 months. I recently started working on analyzing the combination of trend strategy and VIX, but didn't get outstanding results after a few tries. Sharing this tool with all of you in case you have better insights.
█ Introduction and How it is Different
The Dual SuperTrend with VIX Filter Strategy combines traditional trend following with market volatility analysis. Unlike conventional SuperTrend strategies that focus solely on price action, this experimental system incorporates VIX (Volatility Index) as an adaptive filter to create a more context-aware trading approach. By analyzing where current volatility stands relative to historical norms, the strategy adjusts to different market environments rather than applying uniform logic across all conditions.
BTCUSD 6hr Long Short Performance
█ Strategy, How it Works: Detailed Explanation
🔶 Dual SuperTrend Core
The strategy uses two SuperTrend indicators with different sensitivity settings:
- SuperTrend 1: Length = 13, Multiplier = 3.5
- SuperTrend 2: Length = 8, Multiplier = 5.0
The SuperTrend calculation follows this process:
1. ATR = Average of max(High-Low, |High-PreviousClose|, |Low-PreviousClose|) over 'length' periods
2. UpperBand = (High+Low)/2 - (Multiplier * ATR)
3. LowerBand = (High+Low)/2 + (Multiplier * ATR)
Trend direction is determined by:
- If Close > previous LowerBand, Trend = Bullish (1)
- If Close < previous UpperBand, Trend = Bearish (-1)
- Otherwise, Trend = previous Trend
🔶 VIX Analysis Framework
The core innovation lies in the VIX analysis system:
1. Statistical Analysis:
- VIX Mean = SMA(VIX, 252)
- VIX Standard Deviation = StdDev(VIX, 252)
- VIX Z-Score = (Current VIX - VIX Mean) / VIX StdDev
2. **Volatility Bands:
- Upper Band 1 = VIX Mean + (2 * VIX StdDev)
- Upper Band 2 = VIX Mean + (3 * VIX StdDev)
- Lower Band 1 = VIX Mean - (2 * VIX StdDev)
- Lower Band 2 = VIX Mean - (3 * VIX StdDev)
3. Volatility Regimes:
- "Very Low Volatility": VIX < Lower Band 1
- "Low Volatility": Lower Band 1 ≤ VIX < Mean
- "Normal Volatility": Mean ≤ VIX < Upper Band 1
- "High Volatility": Upper Band 1 ≤ VIX < Upper Band 2
- "Extreme Volatility": VIX ≥ Upper Band 2
4. VIX Trend Detection:
- VIX EMA = EMA(VIX, 10)
- VIX Rising = VIX > VIX EMA
- VIX Falling = VIX < VIX EMA
Local performance:
🔶 Entry Logic Integration
The strategy combines trend signals with volatility filtering:
Long Entry Condition:
- Both SuperTrend 1 AND SuperTrend 2 must be bullish (trend = 1)
- AND selected VIX filter condition must be satisfied
Short Entry Condition:
- Both SuperTrend 1 AND SuperTrend 2 must be bearish (trend = -1)
- AND selected VIX filter condition must be satisfied
Available VIX filter rules include:
- "Below Mean + SD": VIX < Lower Band 1
- "Below Mean": VIX < VIX Mean
- "Above Mean": VIX > VIX Mean
- "Above Mean + SD": VIX > Upper Band 1
- "Falling VIX": VIX < VIX EMA
- "Rising VIX": VIX > VIX EMA
- "Any": No VIX filtering
█ Trade Direction
The strategy allows testing in three modes:
1. **Long Only:** Test volatility effects on uptrends only
2. **Short Only:** Examine volatility's impact on downtrends only
3. **Both (Default):** Compare how volatility affects both trend directions
This enables comparative analysis of how volatility regimes impact bullish versus bearish markets differently.
█ Usage
Use this strategy as an experimental framework:
1. Form a hypothesis about how volatility affects trend reliability
2. Configure VIX filters to test your specific hypothesis
3. Analyze performance across different volatility regimes
4. Compare results between uptrends and downtrends
5. Refine your volatility filtering approach based on results
6. Share your findings with the trading community
This framework allows you to investigate questions like:
- Are uptrends more reliable during rising or falling volatility?
- Do downtrends perform better when volatility is above or below its historical average?
- Should different volatility filters be applied to long vs. short positions?
█ Default Settings
The default settings serve as a starting point for exploration:
SuperTrend Parameters:
- SuperTrend 1 (Length=13, Multiplier=3.5): More responsive to trend changes
- SuperTrend 2 (Length=8, Multiplier=5.0): More selective filter requiring stronger trends
VIX Analysis Settings:
- Lookback Period = 252: Establishes a full market cycle for volatility context
- Standard Deviation Bands = 2 and 3 SD: Creates statistically significant regime boundaries
- VIX Trend Period = 10: Balances responsiveness with noise reduction
Default VIX Filter Selection:
- Long Entry: "Above Mean" - Tests if uptrends perform better during above-average volatility
- Short Entry: "Rising VIX" - Tests if downtrends accelerate when volatility is increasing
Feel Free to share your insight below!!!
Whale Buy Activity Detector (Real-Time)Whale Buy Activity Detector (Real-Time)
This indicator helps to identify abnormal spikes in the volume of purchases, which may indicate the activity of large players ("whales"). It analyzes the volume of purchases and compares it with the average volume over a certain period of time. If the volume of purchases exceeds a set threshold, the indicator marks this as potential whale activity.
Basic parameters:
Volume Threshold (x Average): The coefficient by which the current purchase volume must exceed the average volume in order to be considered abnormal. The default value is 2.0, which means that the purchase volume should be 2 times the average volume for the selected time period. This parameter can be adjusted in the range from 1.0 and higher in increments of 0.1.
Example: If you set the value to 1.5, the indicator will mark situations when the volume of purchases exceeds the average volume by 1.5 times.
Lookback Period: The time period used to calculate the average purchase volume. The default value is 20, which means that the average purchase volume will be calculated for the last 20 candles. This parameter can be set in the range from 1 and above.Example: If you set the value to 10, the average purchase volume will be calculated for the last 10 candles.
How to use:
Buy Volume: Shows the volume of purchases on each candle. This is the volume that was sold at a price higher than the opening price of the candle.
Average Buy Volume: The average volume of purchases over a given time period (Lookback Period). This parameter helps to determine the "normal" level of purchase volume.
Whale Buy: Notes abnormal spikes in the volume of purchases, which may indicate the activity of "whales". The indicator draws a mark on the top of the candle when the purchase volume exceeds the threshold set by the Volume Threshold parameter.
Notifications:
The indicator can send notifications when an abnormal volume of purchases is detected. You can set up notifications via the TradingView menu to receive real-time alerts.
Usage example:
If you are trading in a highly volatile market, you can increase the Volume Threshold to filter out small volume spikes.
If you trade in a low-volatility market, you can reduce the Volume Threshold to capture even small anomalies.
Quarterly Theory ICT 02 [TradingFinder] True Open Session 90 Min🔵 Introduction
The Quarterly Theory ICT indicator is an advanced analytical system built on ICT (Inner Circle Trader) concepts and fractal time. It divides time into four quarters (Q1, Q2, Q3, Q4), and is designed based on the consistent repetition of these phases across all trading timeframes (annual, monthly, weekly, daily, and even shorter trading sessions).
Each cycle consists of four distinct phases: the first phase (Q1) is the Accumulation phase, characterized by price consolidation; the second phase (Q2), known as Manipulation or Judas Swing, is marked by initial false movements indicating a potential shift; the third phase (Q3) is Distribution, where price volatility peaks; and the fourth phase (Q4) is Continuation/Reversal, determining whether the previous trend continues or reverses.
🔵 How to Use
The central concept of this strategy is the "True Open," which refers to the actual starting point of each time cycle. The True Open is typically defined at the beginning of the second phase (Q2) of each cycle. Prices trading above or below the True Open serve as a benchmark for predicting the market's potential direction and guiding trading decisions.
The practical application of the Quarterly Theory strategy relies on accurately identifying True Open points across various timeframes.
True Open points are defined as follows :
Yearly Cycle :
Q1: January, February, March
Q2: April, May, June (True Open: April Monthly Open)
Q3: July, August, September
Q4: October, November, December
Monthly Cycle :
Q1: First Monday of the month
Q2: Second Monday of the month (True Open: Daily Candle Open price on the second Monday)
Q3: Third Monday of the month
Q4: Fourth Monday of the month
Weekly Cycle :
Q1: Monday
Q2: Tuesday (True Open: Daily Candle Open Price on Tuesday)
Q3: Wednesday
Q4: Thursday
Daily Cycle :
Q1: 18:00 - 00:00 (Asian session)
Q2: 00:00 - 06:00 (True Open: Start of London Session)
Q3: 06:00 - 12:00 (NY AM)
Q4: 12:00 - 18:00 (NY PM)
90 Min Asian Session :
Q1: 18:00 - 19:30
Q2: 19:30 - 21:00 (True Open at 19:30)
Q3: 21:00 - 22:30
Q4: 22:30 - 00:00
90 Min London Session :
Q1: 00:00 - 01:30
Q2: 01:30 - 03:00 (True Open at 01:30)
Q3: 03:00 - 04:30
Q4: 04:30 - 06:00
90 Min New York AM Session :
Q1: 06:00 - 07:30
Q2: 07:30 - 09:00 (True Open at 07:30)
Q3: 09:00 - 10:30
Q4: 10:30 - 12:00
90 Min New York PM Session :
Q1: 12:00 - 13:30
Q2: 13:30 - 15:00 (True Open at 13:30)
Q3: 15:00 - 16:30
Q4: 16:30 - 18:00
Micro Cycle (22.5-Minute Quarters) : Each 90-minute quarter is further divided into four 22.5-minute sub-segments (Micro Sessions).
True Opens in these sessions are defined as follows :
Asian Micro Session :
True Session Open : 19:30 - 19:52:30
London Micro Session :
T rue Session Open : 01:30 - 01:52:30
New York AM Micro Session :
True Session Open : 07:30 - 07:52:30
New York PM Micro Session :
True Session Open : 13:30 - 13:52:30
By accurately identifying these True Open points across various timeframes, traders can effectively forecast the market direction, analyze price movements in detail, and optimize their trading positions. Prices trading above or below these key levels serve as critical benchmarks for determining market direction and making informed trading decisions.
🔵 Setting
Show True Range : Enable or disable the display of the True Range on the chart, including the option to customize the color.
Extend True Range Line : Choose how to extend the True Range line on the chart, with the following options:
None: No line extension
Right: Extend the line to the right
Left: Extend the line to the left
Both: Extend the line in both directions (left and right)
Show Table : Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed.
Show More Info : Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle.
🔵 Conclusion
The Quarterly Theory ICT, by dividing time into four distinct quarters (Q1, Q2, Q3, and Q4) and emphasizing the concept of the True Open, provides a structured and repeatable framework for analyzing price action across multiple time frames.
The consistent repetition of phases—Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal—allows traders to effectively identify recurring price patterns and critical market turning points. Utilizing the True Open as a benchmark, traders can more accurately determine potential directional bias, optimize trade entries and exits, and manage risk effectively.
By incorporating principles of ICT (Inner Circle Trader) and fractal time, this strategy enhances market forecasting accuracy across annual, monthly, weekly, daily, and shorter trading sessions. This systematic approach helps traders gain deeper insight into market structure and confidently execute informed trading decisions.
