PowerStrike Pro V3Purpose of the Script
"PowerStrike Pro V3" is a custom indicator designed to generate high-accuracy buy/sell signals by combining multiple technical analysis tools. This script is optimized for trend-following, scalping, and support/resistance strategies. It integrates popular indicators such as RSI, Supertrend, Bollinger Bands, and dynamic support/resistance levels to provide traders with reliable signals.
Components of the Script and How It Works
The script combines the following key components, each contributing to the total signal strength based on user-defined weights. Below is a detailed explanation of how each component works and how it contributes to the overall score:
1. RSI (Relative Strength Index)
How It Works:
RSI identifies overbought (above 70) and oversold (below 30) conditions in the market.
The script uses RSI values to measure the strength of the trend and generate buy/sell signals.
When RSI is in the oversold zone, it strengthens buy signals. When in the overbought zone, it strengthens sell signals.
Contribution to Total Score:
RSI's contribution is calculated based on its strength in the oversold or overbought zones.
The final contribution is weighted by the user-defined "RSI Weight" and added to the total score.
2. Support and Resistance Levels
How It Works:
The script dynamically calculates recent peaks (resistance) and valleys (support) using a user-defined lookback period.
These levels are plotted on the chart as dynamic support and resistance lines.
The proximity of the price to these levels strengthens the signals.
Contribution to Total Score:
If the price is near a support level, it increases the strength of buy signals.
If the price is near a resistance level, it increases the strength of sell signals.
The contribution is weighted by the "Support/Resistance Weight" and added to the total score.
3. Supertrend Indicator
How It Works:
Supertrend uses ATR (Average True Range) and a multiplier to determine the trend direction.
The script uses Supertrend's direction changes as a filter for buy/sell signals.
When Supertrend is in an uptrend, it strengthens buy signals. When in a downtrend, it strengthens sell signals.
Contribution to Total Score:
Supertrend's contribution is weighted by the "Supertrend Weight" and added to the total score.
4. Bollinger Bands
How It Works:
Bollinger Bands measure price volatility and identify potential support/resistance levels.
The script generates buy signals when the price crosses above the lower band and sell signals when it crosses below the upper band.
Contribution to Total Score:
A crossover above the lower band increases the strength of buy signals.
A crossover below the upper band increases the strength of sell signals.
The contribution is weighted by the "Bollinger Bands Weight" and added to the total score.
5. Order Book Data
How It Works:
The script analyzes bid/ask volumes from the order book to assess market depth.
High bid volume near support levels strengthens buy signals.
High ask volume near resistance levels strengthens sell signals.
Contribution to Total Score:
Order book data is weighted by the "Order Book Weight" and added to the total score.
Signal Types and Their Meaning
The script generates two types of signals:
Weak Signals:
Weak signals indicate the early stages of a trend or minor corrections.
These are represented by small green (buy) or red (sell) triangles on the chart.
Weak signals are suitable for low-risk trades or scalping strategies.
Strong Signals:
Strong signals indicate the continuation of a trend or significant reversal points.
These are represented by larger green (buy) or red (sell) arrows on the chart.
Strong signals are suitable for higher-risk, higher-reward trades.
Total Score Calculation
The script calculates the total buy and sell scores by combining the weighted contributions of all components. The formula for the total score is as follows:
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Total Buy Score = (RSI Buy Strength * RSI Weight) + (Support Strength * Support/Resistance Weight) + (Supertrend Buy Strength * Supertrend Weight) + (Bollinger Buy Strength * Bollinger Weight) + (Order Book Buy Strength * Order Book Weight)
Total Sell Score = (RSI Sell Strength * RSI Weight) + (Resistance Strength * Support/Resistance Weight) + (Supertrend Sell Strength * Supertrend Weight) + (Bollinger Sell Strength * Bollinger Weight) + (Order Book Sell Strength * Order Book Weight)
The total score is then compared to user-defined thresholds to generate weak or strong signals. For example:
A total buy score above 80% generates a weak buy signal.
A total buy score above 85% generates a strong buy signal.
Recommended Strategies
Trend Following: Use strong signals to trade in the direction of the main trend.
Scalping: Use weak signals to capture short-term price movements.
Support/Resistance Trading: Use the dynamically plotted support and resistance levels to identify reversal points.
How to Use the Script
Weight Settings:
Adjust the weights for each component (RSI, Supertrend, Bollinger Bands, etc.) in the script settings to customize the signal strength calculation.
Signal Thresholds:
Set the thresholds for weak and strong signals (e.g., 80% for weak signals, 85% for strong signals).
Chart Visualization:
The script automatically plots buy/sell signals on the chart. Use these signals in conjunction with your trading strategy.
Unique Features of the Script
Dynamic Weighting: Each component's contribution to the total score can be customized using user-defined weights.
Integrated Support/Resistance: The script dynamically calculates and plots support/resistance levels, enhancing signal accuracy.
Order Book Analysis: The inclusion of order book data provides additional confirmation for signals.
Final Notes
While "PowerStrike Pro V3" combines multiple indicators to generate reliable signals, no indicator guarantees 100% accuracy. Always use proper risk management and combine this script with other analysis tools for the best results
Forecasting
Fibonacci Trading Strategy (Auto Levels)How It Works
Swing Highs and Lows Detection:
The script identifies the highest high and lowest low over a specified lookback period (default: 50 candles). These points are used as the basis for Fibonacci calculations.
Fibonacci Levels:
Fibonacci retracement levels: 0%, 38.2%, 50%, 61.8%, 78.6%, and 100%.
Fibonacci extension levels: 127.2%, 161.8%, 200%, 261.8%, and 361.8%.
Each level is plotted on the chart with a specific color and labeled with the corresponding price.
Entry Zones:
Pullback Area: Between the 50% and 61.8% retracement levels. This area is highlighted in green, indicating a potential entry for conservative traders.
Full Margin Area: Between the 61.8% and 78.6% retracement levels. This area is highlighted in red, suggesting a higher-risk entry for aggressive traders.
Stop Loss (SL):
The Stop Loss is placed at the 78.6% Fibonacci retracement level. A dotted red line is drawn at this level to provide a visual reference for risk management.
Entry labels include the Stop Loss price for clarity.
Take Profit (TP) Levels:
Multiple take-profit targets are identified using Fibonacci extension levels (127.2%, 161.8%, 200%, 261.8%, and 361.8%).
Each level is labeled with the price and target percentage.
Visual Aids:
The script dynamically labels each Fibonacci level with its corresponding price.
Entry points (Pullback and Full Margin) are marked with clear labels, including the recommended Stop Loss.
Background highlights help distinguish the Pullback and Full Margin areas.
Strategy Highlights
Risk Management:
Incorporates a well-defined Stop Loss at the 78.6% level to limit downside risk.
Multiple take-profit levels help traders scale out of positions gradually.
Automation:
Automatically recalculates levels when new swing highs or lows are detected, ensuring accuracy in dynamic markets.
Customizability:
Users can adjust the lookback period to suit different timeframes or trading styles.
Clarity:
Clean visuals and detailed labels ensure the strategy is easy to interpret and apply.
When to Use
The strategy is suitable for trend-following traders looking to enter during pullbacks in an established trend.
It works best in trending markets where Fibonacci levels often act as strong support or resistance.
Example Scenario
Bullish Setup:
Price retraces to the 50%-61.8% area (Pullback Area) after a swing high.
A buy order is placed in this zone, with the Stop Loss at the 78.6% level.
Profit targets are set at the 127.2%, 161.8%, and higher Fibonacci extensions.
Bearish Setup:
In a downtrend, price retraces upward to the 50%-61.8% zone.
A sell order is placed, with the Stop Loss at the 78.6% level and take-profit levels below.
PreMarket_Estimator Portfolio [n_dot]AMEX:SOXL ; NASDAQ:TQQQ ; AMEX:FNGU ; AMEX:SOXS ; NASDAQ:SQQQ ; AMEX:FNGD
Strategy Core Idea:
I focus on stocks that are expected to show significant price movements (gaps) during the premarket, usually due to news or earnings reports. I record the highest price formed during the premarket, and if the price exceeds this level after the market opens, I go LONG. Based on my experience, it’s advisable to exit after a few percentage points of increase, as the premarket boom often corrects itself.
Usage:
The indicator is best used in pairs: Pre_Market_Estimator Single and Pre_Market_Estimator Portfolio.
In this portfolio version, you can set up 6 different instruments, which are displayed stacked vertically on the screen, while the single version monitors only one instrument. The portfolio does not plot charts at the actual price levels but offsets them vertically, displaying the current prices in a label at the end of each chart.
Settings:
Time point 1: Start of the observation period.
Time point 2: End of the observation period / Start of the trading period.
GAP: is used to adjust the distance between the charts displayed in the portfolio view. This allows you to customize the spacing for better readability and visualization of the monitored instruments.
Usage:
Set the timeframe period to "1m".
Set Time point 1 to the start of the premarket session on the current day (e.g., NYSE: 9:00).
Set Time point 2 to the market open (e.g., NYSE: 9:30).
The indicator monitors the highest price during the premarket period, marking it with a blue line.
During the subsequent trading period, if the price exceeds the premarket high, it generates a buy signal marked with a blue plus sign.
Limitations:
The premarket prediction typically provides actionable signals during the first 30 minutes to 1 hour of the trading session. After this, the trend is usually driven by daily market events or news.
To reduce data usage, the portfolio version of the indicator (which monitors 6 instruments simultaneously) only loads the last 24 hours of data (60 * 24 minutes). After this, the chart stops providing signals, and the time points need to be reset.
Additional Use Cases:
This type of breakout monitoring is not only suitable for observing premarket events but can also provide relevant information before major announcements.
For example, in the case of central bank rate hikes:
Set Point 1 to 1 hour before the announcement.
Set Point 2 to the time of the announcement.
I hope this contributes to your success!
Stock Scanner - 38 AssetsPullback Scanner and Trading Strategy:
The Scanner's Purpose:
This tool helps identify stocks and futures from a set-list that are in a strong uptrend (above 200 SMA) but experiencing a temporary pullback (RSI below 38), creating potential buying opportunities.
Load 38 Favourite Stocks. They need to be bullish ie: Trading usually above 200 SMA. A drop down switch lets you choose which group. You can find suitable stocks using the filter at FINVIZ:
use on 4hr Timeframes and Above
You must use this on at least the 4hr timeframe, otherwise the 200SMA is not truly placed correctly and a valid trade depends upon the price action being ABOVE the 200SMA.
finviz.com
Key Components:
200 Simple Moving Average (SMA)
Acts as a trend filter
Price above 200 SMA indicates a long-term uptrend
Helps avoid trading against the main trend
Relative Strength Index (RSI)
Set to 38 as the oversold threshold
Identifies temporary weakness in strong trends
Acts as the pullback confirmation. You could add an RSI indicator to the chart for monitoring.
Visual Signals:
Green row: Indicates both conditions are met (price > 200 SMA and RSI < 38)
Yellow triangle: Appears at price bottom when RSI drops below 38
Yellow 200 SMA line: Shows the trend direction and potential support
Trade Setup:
First Requirement: Price must be trading above the 200 SMA
Second Requirement: Wait for RSI to drop below 38
Entry Trigger: When both conditions align (row turns green)
Risk Management: Set stop loss below recent swing low
Exit: When RSI moves above 53 or price crosses below 200 SMA
The scanner monitors multiple instruments simultaneously, allowing traders to identify setups across different markets without manually checking each chart. When a row turns green, that instrument deserves closer attention for potential trade setup.
Example Trade:
Looking at the chart of Apple (AAPL), the yellow triangles show where RSI dropped below 38 while price remained above the rising 200 SMA, providing multiple long entry opportunities in an established uptrend. Actually Apple may be better with RSI below 26.
If you use ctrader, I have made a cbot version of this to automatically take trades on the ctrader platform: eg: XAUUSD i.postimg.cc
Detecting Sideways Market or Strong Trends| Copy Trade Tungdubai**Tool Description**:
The **"Detecting Sideways Market or Strong Trends | Copy Trade Tungdubai"** tool is designed to help traders identify two key market conditions:
1. **Sideways Market**:
- This condition is detected when the ADX is below 20, the price stays within the Bollinger Bands, and the RSI is between 45 and 55.
- When the market is sideways, the chart background will turn yellow as a visual alert.
2. **Strong Trend Market**:
- This condition is identified when the ADX is above 25, and either the price breaks out of the Bollinger Bands or the RSI surpasses the overbought (70) or oversold (30) levels.
- When the market is in a strong trend, the chart background will turn blue as a visual alert.
**Key Components of the Tool**:
- **ADX**: Measures the strength of the market trend, with key thresholds at 20 and 25.
- **Bollinger Bands**: Helps determine volatility and checks if the price is within or outside the bands.
- **RSI**: Measures momentum, helping identify overbought and oversold levels.
**Visual Features on the Chart**:
- ADX, RSI, and Bollinger Bands are clearly plotted with their respective key thresholds for easier recognition of market conditions.
- The chart background changes color to reflect the current market condition (yellow for sideways, blue for strong trends).
**Alerts**:
- Alerts are triggered when the market enters either a sideways or strong trend phase, providing notifications to help users act promptly.
This tool serves as a practical aid in recognizing market conditions, allowing traders to make informed decisions aligned with their strategies.
**Mô tả công cụ**:
Công cụ **"Detecting Sideways Market or Strong Trends | Copy Trade Tungdubai"** được thiết kế để giúp các nhà giao dịch xác định hai trạng thái chính của thị trường:
1. **Thị trường đi ngang (Sideways)**:
- Điều kiện được xác định dựa trên chỉ số ADX thấp hơn ngưỡng 20, giá nằm trong dải Bollinger Bands, và chỉ số RSI dao động trong khoảng từ 45 đến 55.
- Khi thị trường đi ngang, nền của biểu đồ sẽ chuyển sang màu vàng để cảnh báo trực quan.
2. **Thị trường bùng nổ sóng mạnh (Strong Trend)**:
- Điều kiện được xác định khi ADX vượt qua ngưỡng 25 và giá phá vỡ dải Bollinger Bands (hoặc) chỉ số RSI vượt ngưỡng quá mua 70 hoặc quá bán 30.
- Khi thị trường bùng nổ sóng mạnh, nền biểu đồ sẽ chuyển sang màu xanh để cảnh báo trực quan.
**Các thành phần chính của công cụ**:
- **ADX**: Được sử dụng để đo sức mạnh xu hướng thị trường, với các ngưỡng quan trọng là 20 và 25.
- **Bollinger Bands**: Được sử dụng để xác định mức độ biến động và kiểm tra giá nằm trong hay ngoài dải.
- **RSI**: Dùng để đo mức độ quá mua/quá bán, xác định động lượng giá.
**Hiển thị trên biểu đồ**:
- Các đường ADX, RSI, và Bollinger Bands được vẽ rõ ràng, cùng với các ngưỡng quan trọng (hỗ trợ nhận biết trạng thái thị trường).
- Nền biểu đồ thay đổi màu sắc tương ứng với điều kiện thị trường.
**Cảnh báo**:
- Cảnh báo sẽ được kích hoạt khi thị trường rơi vào trạng thái đi ngang hoặc bùng nổ sóng mạnh, với các thông báo giúp người dùng hành động kịp thời.
Công cụ này là một trợ thủ hữu ích trong việc nhận biết trạng thái thị trường, từ đó giúp các nhà giao dịch đưa ra quyết định phù hợp với chiến lược của mình.
Dynamic Market ScannerDynamic Market Scanner is a powerful tool for analyzing financial markets, combining a variety of indicators to provide clear and understandable signals.
Key Features:
- Signal Generation:
The main signals "Buy", "Sell", and "Hold" are formed based on the analysis of indicators:
- MACD
- RSI
- SMA
- EMA
- WMA
- Hull MA
Additional Analytical Tools:
- ATR is used to assess volatility and helps to understand the risk of the current market situation.
- SMA Ichimoku does not generate signals but is used to assess their accuracy.
- If the price is above the SMA, "Buy" signals are more likely, as this confirms the strength of the upward movement.
- If the price is below the SMA, "Buy" signals require additional confirmations.
Dashboard:
Displays the current price position relative to the indicators, helping the trader understand how strong or weak the current signals are.
Advantages of Using:
1. Signal Filtering:
The price position relative to the SMA Ichimoku helps to assess the likelihood of successful trades.
2. Volatility Analysis:
ATR provides additional information about risks and market fluctuations.
3. Comprehensive Approach:
Signal generation is based on a combination of key indicators, offering a multifaceted view of the market.
Explanation of Percent Calculation in the Table:
- The table shows the values of indicators such as MACD, ATR, EMA, SMA, WMA, and Hull MA in percentages. Percentages are calculated based on the current value of the indicator relative to its maximum and minimum.
- Percentages are displayed for each indicator, allowing traders to assess market conditions based on their current values.
Dynamic Market Scanner will become a reliable assistant in your technical analysis toolkit, providing a comprehensive overview of market conditions and helping to make informed trading decisions.
MW:TA Days of the WeekENG: Vertical separators to easily detect days of the week and see which past liquidity was taken down. Screenshot example contains days of the week indicator and manually drawn lines of grabbed liquidity. Useful for trades based on liquidity grab and reaction.
Tested on Forex, Crypto, Indexes, Stocks, Commodities markets.
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РУС: Вертикальные разделители для визуального определения дней недели и просмотра снятой ликвидности на графике. На скриншоте отмечен индикатор разделительных периодов (дней) и вручную нарисованные линии, которые отмечают снятую ликвидность и реакцию цены на снятие. Полезно для тех трейдеров, которые торгуют по реакции на снятую ликвидность.
Протестировано на рынках Форекс, Крипто, ИНдексов, Акций и Сырья.
FuTech : MACD Crossovers Advanced Alert Lines=============================================================
Indicator : FuTech: MACD Crossovers Advanced Alert Lines
Overview:
The "FuTech: MACD Crossovers Advanced Alert Lines" indicator is designed to assist traders in identifying key technical patterns using the :-
1. MACD (Moving Average Convergence Divergence) and
2. Golden/Death Crossovers
By visualizing these indicators directly on the chart with advanced lines, it helps traders make more informed decisions on when to enter or exit trades.
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Key Features of "FuTech: MACD Crossovers Advanced Alert Lines":
1. MACD Crossovers:
a) The MACD is one of the most widely used indicators for identifying momentum shifts and potential buy/sell signals. This indicator plots vertical lines on the chart whenever the MACD line crosses the signal line.
b) Upward Crossover (Bullish Signal) : When the MACD line crosses above the signal line, a green vertical line will appear, indicating a potential buying opportunity.
c) Downward Crossover (Bearish Signal) : When the MACD line crosses below the signal line, a red vertical line will appear, signaling a potential selling opportunity.
2. Golden Cross & Death Cross:
a) The Golden Cross occurs when the price moves above a long-term moving average (like the 50-day moving average), signaling a potential upward trend.
b) The Death Cross occurs when the price moves below a long-term moving average, signaling a potential downward trend.
c) These crossovers are displayed with customizable lines on the chart to easily spot when the market is shifting direction.
d) Golden Cross (Bullish Signal) : A blue vertical line appears when the price crosses above the selected long-term moving average.
e) Death Cross (Bearish Signal) : A purple vertical line appears when the price crosses below the selected long-term moving average.
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Customization Options:
This indicator offers several customization options to suit your trading preferences:
1) MACD Settings:
a) Choose between different moving average types (EMA, SMA, or VWMA) for calculating the MACD.
b) Adjust the lengths of the fast, slow, and signal MACD periods.
c) Control the width and color of the vertical lines drawn on the chart for both up and down crossovers.
2) Golden Cross / Death Cross Settings:
a) Select the moving average type for the Golden Cross / Death Cross (EMA, SMA, or VWMA).
b) Define the lookback period for calculating the Golden Cross / Death Cross.
c) Customize the appearance of the Golden and Death Cross lines, including their width and color.
You can use both as well as either of the MACD lines or Golden Crossover / Death Crossover Lines respectively as per your trading strategies
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How "FuTech: MACD Crossovers Advanced Alert Lines" indicator Works:
a) The indicator monitors the price and calculates the MACD and Golden/Death Crosses.
b) When the MACD line crosses above or below the signal line, or when the price crosses above or below the long-term moving average, it plots a vertical line on the chart.
c) These lines help traders quickly spot potential turning points in the market, providing clear signals to act upon.
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Use Case:
a) Swing Traders: The indicator is useful for spotting momentum shifts and trend reversals, helping you time entries and exits for short- to medium-term trades.
b) Long-Term Traders: The Golden and Death Cross signals help identify major trend changes, giving insights into potential market shifts.
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Why Use This "FuTech: MACD Crossovers Advanced Alert Lines" Indicator ?
a) Clear Visuals : The vertical lines provide clear and easy-to-spot signals for MACD crossovers and Golden/Death Crosses.
b) Customizable : Adjust settings for your personal trading strategy, whether you're focusing on short-term momentum or long-term trend shifts.
c) Supports Decision Making : With its advanced line plotting and customizable features, this indicator helps you make quicker and more informed trading decisions.
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How to Use:
a) MACD Crossovers: Look for green lines to signal potential buying opportunities (when the MACD line crosses above the signal line) and red lines for selling opportunities (when the MACD line crosses below the signal line).
b) Golden Cross / Death Cross: Use the blue lines to confirm when a positive trend may begin (Golden Cross) and purple lines to warn when a negative trend may start (Death Cross).
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Conclusion:
"FuTech: MACD Crossovers Advanced Alert Lines" indicator combines two powerful technical analysis tools, the MACD and Golden/Death Crosses, to provide clear, actionable signals on your chart.
By customizing the appearance of these signals and combining them with your trading strategy, you can enhance your decision-making process and improve your trading outcomes.
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Thank you !
Jai Swaminarayan Dasna Das !
He Hari ! Bas Ek Tu Raji Tha !
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Rolling Window Geometric Brownian Motion Projections📊 Rolling GBM Projections + EV & Adjustable Confidence Bands
Overview
The Rolling GBM Projections + EV & Adjustable Confidence Bands indicator provides traders with a robust, dynamic tool to model and project future price movements using Geometric Brownian Motion (GBM). By combining GBM-based simulations, expected value (EV) calculations, and customizable confidence bands, this indicator offers valuable insights for decision-making and risk management.
Key Features
Rolling GBM Projections: Simulate potential future price paths based on drift (μμ) and volatility (σσ).
Expected Value (EV) Line: Represents the average projection of simulated price paths.
Confidence Bands: Define ranges where the price is expected to remain, adjustable from 51% to 99%.
Simulation Lines: Visualize individual GBM paths for detailed analysis.
EV of EV Line: A smoothed trend of the EV, offering additional clarity on price dynamics.
Customizable Lookback Periods: Adjust the rolling lookback periods for drift and volatility calculations.
Mathematical Foundation
1. Geometric Brownian Motion (GBM)
GBM is a mathematical model used to simulate the random movement of asset prices, described by the following stochastic differential equation:
dSt=μStdt+σStdWt
dSt=μStdt+σStdWt
Where:
StSt: Price at time tt
μμ: Drift term (expected return)
σσ: Volatility (standard deviation of returns)
dWtdWt: Wiener process (standard Brownian motion)
2. Drift (μμ) and Volatility (σσ)
Drift (μμ): Represents the average logarithmic return of the asset. Calculated using a simple moving average (SMA) over a rolling lookback period.
μ=SMA(ln(St/St−1),Lookback Drift)
μ=SMA(ln(St/St−1),Lookback Drift)
Volatility (σσ): Measures the standard deviation of logarithmic returns over a rolling lookback period.
σ=STD(ln(St/St−1),Lookback Volatility)
σ=STD(ln(St/St−1),Lookback Volatility)
3. Price Simulation Using GBM
The GBM formula for simulating future prices is:
St+Δt=St×e(μ−12σ2)Δt+σϵΔt
St+Δt=St×e(μ−21σ2)Δt+σϵΔt
Where:
ϵϵ: Random variable from a standard normal distribution (N(0,1)N(0,1)).
4. Confidence Bands
Confidence bands are determined using the Z-score corresponding to a user-defined confidence percentage (CC):
Upper Band=EV+Z⋅σ
Upper Band=EV+Z⋅σ
Lower Band=EV−Z⋅σ
Lower Band=EV−Z⋅σ
The Z-score is computed using an inverse normal distribution function, approximating the relationship between confidence and standard deviations.
Methodology
Rolling Drift and Volatility:
Drift and volatility are calculated using logarithmic returns over user-defined rolling lookback periods (default: μ=20μ=20, σ=16σ=16).
Drift defines the overall directional tendency, while volatility determines the randomness and variability of price movements.
Simulations:
Multiple GBM paths (default: 30) are generated for a specified number of projection candles (default: 12).
Each path is influenced by the current drift and volatility, incorporating random shocks to simulate real-world price dynamics.
Expected Value (EV):
The EV is calculated as the average of all simulated paths for each projection step, offering a statistical mean of potential price outcomes.
Confidence Bands:
The upper and lower bounds of the confidence bands are derived using the Z-score corresponding to the selected confidence percentage (e.g., 68%, 95%).
EV of EV:
A running average of the EV values, providing a smoothed perspective of price trends over the projection horizon.
Indicator Functionality
User Inputs:
Drift Lookback (Bars): Define the number of bars for rolling drift calculation (default: 20).
Volatility Lookback (Bars): Define the number of bars for rolling volatility calculation (default: 16).
Projection Candles (Bars): Set the number of bars to project future prices (default: 12).
Number of Simulations: Specify the number of GBM paths to simulate (default: 30).
Confidence Percentage: Input the desired confidence level for bands (default: 68%, adjustable from 51% to 99%).
Visualization Components:
Simulation Lines (Blue): Display individual GBM paths to visualize potential price scenarios.
Expected Value (EV) Line (Orange): Highlight the mean projection of all simulated paths.
Confidence Bands (Green & Red): Show the upper and lower confidence limits.
EV of EV Line (Orange Dashed): Provide a smoothed trendline of the EV values.
Current Price (White): Overlay the real-time price for context.
Display Toggles:
Enable or disable components (e.g., simulation lines, EV line, confidence bands) based on preference.
Practical Applications
Risk Management:
Utilize confidence bands to set stop-loss levels and manage trade risk effectively.
Use narrower confidence intervals (e.g., 50%) for aggressive strategies or wider intervals (e.g., 95%) for conservative approaches.
Trend Analysis:
Observe the EV and EV of EV lines to identify overarching trends and potential reversals.
Scenario Planning:
Analyze simulation lines to explore potential outcomes under varying market conditions.
Statistical Insights:
Leverage confidence bands to understand the statistical likelihood of price movements.
How to Use
Add the Indicator:
Copy the script into the TradingView Pine Editor, save it, and apply it to your chart.
Customize Settings:
Adjust the lookback periods for drift and volatility.
Define the number of projection candles and simulations.
Set the confidence percentage to tailor the bands to your strategy.
Interpret the Visualization:
Use the EV and confidence bands to guide trade entry, exit, and position sizing decisions.
Combine with other indicators for a holistic trading strategy.
Disclaimer
This indicator is a mathematical and statistical tool. It does not guarantee future performance.
Use it in conjunction with other forms of analysis and always trade responsibly.
Happy Trading! 🚀
MA Resist TrendThis Pine Script™ code designed to provide insights into price trends and potential buy/sell signals based on a moving average of resistance levels. It features dynamic calculations of a resistance line and a base moving average, enabling traders to visualize trend direction and reversal points effectively.
Key Features:
1. Moving Average Selection:
The indicator supports a wide variety of moving averages, including:
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
HMA (Hull Moving Average)
McGinley Dynamic
RMA (Relative Moving Average)
MD (Mode Average)
WMA (Weighted Moving Average)
VWMA (Volume-Weighted Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
This provides flexibility in tailoring the indicator to suit different market conditions and trading styles.
2. Dynamic Resistance Calculation:
MAR: A smoothed moving average of the mid-range between highest price period and lowest price period. This represents the main trend resistance line.
3. Base Line and Resistance Line:
The base line is calculated as the EMA of the closing price.
The resistance line is derived by subtracting the distance between MAR and the base line from the base line. This distance is used to identify potential reversal points.
4. Color Coding:
The MAR line changes color based on its relationship with the current closing price:
Green (lime): Indicates bullish conditions (price above mar).
Red: Indicates bearish conditions (price below mar).
5. Buy and Sell Signals:
A buy signal is triggered when the MAR line crosses below the resistance line.
A sell signal is triggered when the MAR line crosses above the resistance line.
Signals are displayed using labeled shapes on the chart:
"BUY" shape appears below the bar for buy signals.
"SELL" shape appears above the bar for sell signals.
6. Customizable Parameters:
len: Length of the moving average (default: 14).
ma: Type of moving average to use.
lb: Lookback period for high and low prices (default: 3).
smt: Smoothing factor for the mar line (default: 3).
Visualization:
The indicator plots the following on the price chart:
MAR Line: Represents the dynamic resistance line, colored based on market conditions.
Resistance Line: A yellow line indicating the calculated resistance levels.
Buy/Sell Labels: Visual markers indicating potential trade opportunities.
Use Cases:
Trend Identification:
The MAR line provides insights into the current trend direction.
Color changes highlight transitions between bullish and bearish conditions.
Reversal Detection:
Buy and sell signals help identify potential trend reversals.
Dynamic Resistance Levels:
The resistance line offers additional context for understanding price action and possible resistance points.
Notes:
This indicator is particularly useful for trend-following traders who incorporate moving averages into their strategies.
It supports a wide range of moving averages, making it versatile across different asset classes and timeframes.
Traders can experiment with different len, lb, and smt values to fine-tune the indicator's responsiveness.
This script is provided for prediction purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Market Cap LevelsThis indicator zeroes in on those key “round number” market caps and marks them right on your price chart, converting cumbersome billions into crisp, easy-to-track figures (e.g., “10 B”). Instead of getting lost in massive numbers, you’ll instantly see whether a stock is flirting with a big valuation threshold.
Why It Matters & How Big Players Might Use It:
Round-Number Magnet: Institutions often treat nice, round market caps as psychological checkpoints. When a company edges near or beyond SEED_TVCODER77_ETHBTCDATA:5B , SEED_TVCODER77_ETHBTCDATA:10B , or even $500B, it can spark new waves of interest—or caution.
Behavioral Insights: These lines can act like magnets or barriers, hinting at spots where price action could shift if the broader market starts perceiving the company as hitting “the next major level.”
Clean Visuals, Quick Decisions: By placing these key valuations directly on your chart, you can instantly gauge whether a stock is hovering just below or sailing above a major capital milestone—no calculator needed.
US and Asia Trading Hoursadds vertical lines to your chart that show US trading hours 9-4 and NY trading hours based off of EST
Holy-Cow IndicatorHoly-Cow Indicator
Advanced Multi-Pattern Candlestick Analyzer (HC, NV, RN)
Description
Overview
This indicator is designed to detect key candlestick patterns based on foundational principles of price action analysis, now presented with a modernized approach for easier recognition and enhanced utility. Drawing inspiration from the work of candlestick charting pioneer Steve Nison (Japanese Candlestick Charting Techniques) and advanced price action strategies popularized by Linda Raschke (Street Smarts), this tool identifies and highlights unique combinations such as the Holy-Cow (HC), Nova (NV), and Red-Nova (RN) patterns.
These patterns simplify the complexities of price action into actionable setups, making them suitable for all types of traders.
Features
Inside Bars (IB):
Marks consolidation zones where the current candle’s range is inside the previous candle’s range. Useful for spotting breakout opportunities.
Outside Bars (OB):
Identifies candles where the current range exceeds the previous candle’s range.
Indicates potential reversals or trap setups.
Holy-Cow Pattern (HC):
Inspired by: Trap + Consolidation Setup
An Outside Bar followed by an Inside Bar.
Highlights volatility followed by tight consolidation, often preceding a breakout.
Nova Pattern (NV):
Inspired by: Breakout Trap + Expansion
An Inside Bar followed by an Outside Bar.
Signals breakout traps and subsequent volatility, useful for reversals or momentum moves.
Red-Nova Pattern (RN):
Inspired by: Volatility Trap + Major Breakout Zone
A combination of Holy-Cow (HC) and Nova (NV) patterns.
Represents a highly compressed market state, often leading to significant, high-intensity moves.
Bollinger Bands Integration:
Provides context on volatility and potential overbought/oversold levels.
Customizable Visibility:
Toggle specific patterns (IB, OB, HC, NV, RN) to suit your trading strategy.
How to Use
Pattern Detection:
Enable the patterns you want to focus on through the settings panel (e.g., HC for breakout setups, RN for high-intensity moves).
Observe highlighted zones and labels for actionable trade setups.
Trading Strategies:
Breakout Trades:
Look for HC, NV, or RN patterns near support/resistance and trade in the breakout direction.
Reversal Trades:
Use NV or RN patterns forming near key levels to catch reversals.
Stop-Loss:
Place below/above the low/high of the identified pattern.
Take Profit:
Use support/resistance levels, Fibonacci extensions, or a predefined risk-reward ratio (e.g., 2:1).
Recommended Timeframes:
1–15 minutes: Scalping or intraday trading.
1-hour: Intraday and swing trading.
Daily/Weekly: Ideal for significant trend analysis and major market moves.
Acknowledgments
This indicator is based on well-established trading principles and enhanced with unique combinations for modern trading. The foundational ideas behind these patterns are drawn from:
Steve Nison: Who introduced candlestick charting to Western traders in his seminal work, Japanese Candlestick Charting Techniques, and popularized concepts such as Inside and Outside Bars.
Linda Raschke: Who furthered the application of price action patterns in her book Street Smarts, showcasing multi-bar setups and momentum strategies.
While the patterns Holy-Cow (HC), Nova (NV), and Red-Nova (RN) are unique to this indicator, they build upon these foundational principles to offer traders actionable insights.
Disclaimer
This indicator is an independent creation inspired by publicly available price action principles. It is not affiliated with any proprietary tool or service. Back testing and proper risk management are strongly advised before live trading.
Eroina Trend Reversal Indicator with ConfirmationsEroina Trend Reversal Indicator with Confirmations
Overview (English):
The Trend Reversal Indicator with Confirmations is designed to identify potential trend reversals by analyzing dynamic resistance and support levels. This script uses a robust confirmation system to reduce false signals, making it ideal for traders who seek disciplined, data-driven decisions.
Key Features:
• Dynamic Levels: Calculates resistance and support levels based on user-defined lengths.
• Breakout Confirmation: Confirms trend reversals by validating price action over a specified number of candles.
• Visual Cues: Displays “LONG” and “SHORT” signals directly on the chart, alongside resistance/support levels.
• Customizable Parameters: Adaptable to different timeframes and market conditions.
How It Works:
1. Resistance & Support Levels:
• Resistance: Calculated as the highest high over the last N bars.
• Support: Calculated as the lowest low over the last N bars.
2. Breakout Detection:
• A resistance breakout occurs when the price closes above the resistance level.
• A support breakout occurs when the price closes below the support level.
3. Confirmation Logic:
• Signals are validated only if the price remains above/below the levels for a user-defined number of candles.
4. Entry Signals:
• “LONG” signals indicate a confirmed breakout above resistance.
• “SHORT” signals indicate a confirmed breakdown below support.
Settings:
• Resistance Length: Defines the number of candles used to calculate resistance levels.
• Support Length: Defines the number of candles used to calculate support levels.
• Confirmation Candles: Specifies how many candles are required to confirm breakouts.
Usage:
This indicator is ideal for identifying trend reversals and optimizing entry points. Combine it with volume analysis or other technical indicators to enhance accuracy. For example:
• Use in conjunction with RSI to avoid overbought/oversold conditions.
• Combine with moving averages to confirm the trend direction.
Overview (Additional Language):
(Your additional language description can go here after English, e.g., Russian, Spanish, etc.)
Line Break Chart StrategyHello All!
We should not pass this year without a gift!
My last publication in 2024 is Complete Line Break Chart Strategy with many features!
What is Line Break Chart?
" Line Break is a Japanese chart style that disregards time intervals and only focuses on price movements, similar to the Kagi and Renko chart styles. Line Break charts form a series of up and down bars (referred to as lines). Up lines represent rising prices, and down lines represent falling prices. New confirmed lines only form on the chart when closing prices break the range covered by previous lines. Users can control the number of past lines used in the calculation via the "Number of Lines" input in the chart settings. The typical "Number of Lines" setting is 3, meaning the chart forms a new up line when the closing price is above the high prices of the last three lines, and it forms a new down line when the closing price is below the past three lines' low prices. If the current price is higher, it is an up line and if it is lower, it is a down line. If the current closing price is the same or the move in the opposite direction is not large enough to warrant a reversal, l then no new line is draw n" by Tradingview. You can find it here
Now let's start examining the features of the indicator:
By using Line break reversals it shows trend on the main chart. You can create alert .
Moreover, you can decide which trade should be taken by using Risk Management in the indicator. You can set the " Maximum Risk " and then if the risk is more than you set then the trade is not taken. When trend changed it checks the distance between reversal level and open price and compare it with the Maximum Risk
Breakout:
It can find breakouts and shows on the chart. You can create alert for breakouts
It can show breakouts on the main chart:
Flip-Flops:
Upon looking at set of price break charts, the trader will notice that there are instances when uptrend blocks is followed by one reversal block, and then by a reversal to a series of uptrend blocks. The opposite is also possible: a series of downtrend blocks is followed by one reversal box and then by an immediate reversal to downtrend. This price action is called a " Flip-Flop ". This structure usually produces trend continuation signal. when we see this then we better use Buy/Sell stop order. lets see this on the chart:
Temporal Sequence Table:
Sequence frequency shows the frequency distribution of the number of sequential highs and the number of sequential lows that have been generated. This is quite important to the trader who is seeking to join a trend or put on a trade when the price break reverses into a new trend direction. For example, if the pattern over the past year has been that there never were more than nine consecutive high closes, it would make sense not to enter a position late into the sequence of new high closes.
also you can see market structure. I have tried to formalize it and show it under the table. so you can understand if it's choppy market.
"Number of Lines" has very important role. While using low time frames such seconds/minutes time frame you may want to choose higher number of lines such 5,6. ( this may minimize the risk of a whipsaw )
Gaps feature:
You can set Gaps on/off. if Gaps on then you can see how long it takes for each box
Reversal and Continuation Probability:
The script calculated Reversal level and Continuation probability of the trend by using Sequence frequency.
It also shows unconfirmed box and current closing price level:
Last but not least it has Overlay option for all items, and can show all items in the main chart!
P.S. I added alerts :)
Wish you all a happy new year!
Enjoy!
Longest Candles HighlighterDescription:
The Longest Candles Highlighter is a simple yet effective tool that identifies and highlights candles with significant price ranges. By visually marking candles that meet specific size criteria, this indicator helps traders quickly spot high-volatility moments or significant market moves on the chart.
Features:
1. Customizable Candle Range:
- Define the minimum and maximum candle size in pips using input fields.
- Tailor the indicator to highlight candles that are most relevant to your trading strategy.
2. Flexible for Different Markets:
- Automatically adjusts pip calculation based on the instrument type (Forex or non-Forex).
- Accounts for differences in pip values, such as the 0.01 pip for JPY pairs in Forex.
3. Visual Highlighting:
- Highlights qualifying candles with a customizable background color for easy identification.
- The default color is red, but you can choose any color to match your chart theme.
4. Precision and Efficiency:
- Quickly scans and identifies candles that meet your criteria, saving you time in analyzing charts.
- Works seamlessly across all timeframes and asset classes.
How It Works:
- The indicator calculates the range of each candle in pips by subtracting the low from the high and dividing by the appropriate pip value.
- It checks whether the candle's size falls within the user-defined minimum and maximum pip range.
- If the conditions are met, the background of the candle is highlighted with the specified color, drawing your attention to significant price movements.
Use Case:
- This indicator is ideal for identifying key market moments, such as breakouts, volatility spikes, or significant price movements.
- Traders can use it to quickly locate large candles on any chart, aiding in technical analysis and strategy development.
This tool simplifies the process of spotting important candles, empowering traders to make faster and more informed trading decisions.
JCM_MadridThis indicator provides dynamic bar coloring and buy/sell signals based on EMA relationships and price momentum. It allows traders to visually identify trend changes and potential trade opportunities directly on the chart.
Indicator Basics:
Name: The script is titled "JCM_Madrid".
Overlay: It overlays its calculations and outputs directly on the price chart.
User Inputs:
-Range: Defines the length of the EMA (Exponential Moving Average).
-Ref-1 and Ref-2: Set reference lengths for secondary EMAs used in the calculations.
-Source: The price data source for EMA calculations (e.g., close, open, high, low).
-Enable Buy/Sell: Boolean toggles to activate or deactivate buy and sell signals.
Calculations:
EMA Value: Computes the main EMA based on the source and Range.
CloseMA: The difference between the close price and the EMA.
SqzMA: The difference between a secondary EMA (Ref-1) and the main EMA.
RefMA: The difference between another secondary EMA (Ref-2) and the main EMA.
Bar Coloring:
Bars are colored based on the relationship between SqzMA and CloseMA:
Purple: When SqzMA > CloseMA.
Blue: When SqzMA < CloseMA.
Buy/Sell Signals:
A Buy Signal is generated when:
CloseMA crosses from below to above 0.
The close price is higher than the previous close.
Buy signals are enabled.
A Sell Signal is generated when:
CloseMA crosses from above to below 0.
The close price is lower than the previous close.
Sell signals are enabled.
Signals are displayed as labels on the chart:
"Buy": Green label below the candle.
"Sell": Yellow label below the candle
Divergence-Weighted clouds V 1.0Comprehensive Introduction to Divergence-Weighted Clouds V 1.0 (DW)
In financial markets, the analysis of volume and price plays a fundamental role in identifying trends, reversals, and making trading decisions. Volume indicates the level of market interest and liquidity focused on an asset, while price reflects changes in supply and demand. Alongside these two elements, market volatility, support and resistance levels, and cash flow are also critical factors that help analysts form a comprehensive view of the market. The Divergence-Weighted Clouds V 1.0 (DW) indicator is designed to simultaneously analyze these fundamental elements and other important market dynamics. To achieve this, it utilizes data generated from 13 distinct indicators, each measuring specific aspects of the market:
Trend and Momentum: Analyzing the direction and strength of price movements.
Volume and Cash Flow: Understanding the inflow and outflow of capital in the market.
Oscillators: Identifying overbought and oversold conditions.
Support and Resistance Levels: Highlighting key price levels.
The Core Challenge: Standardizing Diverse Data
The primary challenge lies in the fact that the outputs of these indicators differ significantly in scale and meaning. For example:
Volume often generates very large values (e.g., millions of shares).
Oscillators provide data within fixed ranges (e.g., 0 to 100).
Price-based metrics may vary in entirely different scales (e.g., tens or hundreds of units).
These differences make direct comparison of the data impractical. The DW indicator resolves this challenge through an advanced mathematical methodology:
Normalization and Hierarchical Evaluation:
To standardize the data, a process called hierarchical EMA evaluation is employed. Initially, the raw outputs of each indicator are computed over different timeframes using Exponential Moving Averages (EMA) based on prime-number intervals.
Hierarchical Scoring:
A pyramid-like structure is used to evaluate the performance of each indicator. This method examines the relationships and distances between EMAs for each indicator and assigns a numerical score.
Final Integration and Aggregation:
The scores of all 13 indicators are then mathematically aggregated into a single number. This final value represents the overall market performance at that moment, enabling a unified interpretation of volume, price, and volatility.
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Indicators Used in DW
To achieve this comprehensive analysis, DW leverages 13 carefully selected indicators, each offering unique insights into market dynamics:
Trend and Momentum
- ALMA (Arnaud Legoux Moving Average): Reduces lag for faster trend identification.
- Aroon Up: Analyzes the stability of uptrends.
- ADX (Average Directional Index): Measures the strength of a trend.
Volume and Cash Flow
- CMF (Chaikin Money Flow): Identifies cash flow based on price and volume.
- EFI (Elder’s Force Index): Evaluates the strength of price changes alongside volume.
- Volume Delta: Tracks the balance between buying and selling pressure.
- Raw Volume: Analyzes unprocessed volume data.
Oscillators
- Fisher Transform: Normalizes data to detect price reversals.
- MFI (Money Flow Index): Identifies overbought and oversold levels.
Support, Resistance, and Price Dynamics
- Ichimoku Lines (Tenkan-sen & Kijun-sen): Analyzes support and resistance levels.
- McGinley Dynamic: Minimizes errors caused by rapid price movements.
- Price Hierarchy: Evaluates the relative position of prices across timeframes.
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Example: Hierarchical Scoring for Price Analysis
To illustrate how the DW indicator processes data, let’s take the price as an example and analyze it using the first four prime numbers (2, 3, 5, and 7) as intervals for Exponential Moving Averages (EMAs). This example will demonstrate how the indicator evaluates price relationships and assigns a hierarchical score.
Step-by-Step Calculation:
1. Raw Data:
Let’s assume the closing prices for a specific asset over recent days are as follows:
Day 1: 100
Day 2: 102
Day 3: 101
Day 4: 104
Day 5: 103
Day 6: 105
Day 7: 106
2. Calculate EMAs for Prime Number Intervals:
Using the prime-number intervals (2, 3, 5, 7), we calculate the EMAs for these timeframes:
EMA(2): Averages the last 2 closing prices equal to 105.33
EMA(3): Averages the last 3 closing prices equal to 104.25
EMA(5): Averages the last 5 closing prices equal to 103.17
EMA(7): Averages the last 7 closing prices equal to 102.67
3. Compare EMAs Hierarchically:
To assign a score, the relationships between the EMAs are analyzed hierarchically. We evaluate whether each smaller EMA is greater or less than the larger ones:
Compare EMA(2) to EMA(3), EMA(5), and EMA(7):
EMA(2) > EMA(3):105.33>104.25 => +1
EMA(2) > EMA(5): 105.33>103.17 => +1
EMA(2) > EMA(7): 105.33 > 102.67 => +1
Compare EMA(3) to EMA(5) and EMA(7):
EMA(3) > EMA(5) : 104.25>103.17 => +1
EMA(3) > EMA(7):104.25 >102.67 => +1
Compare EMA(5) to EMA(7):
EMA(5) > EMA(7):103.17>102.67 => +1
Assign a Score:
Each positive comparison adds +1 to the score. In this example:
Total Score for Price = 1+1+1+1+1+1+1=6
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Logic Behind Scoring:
The score reflects the "steepness" or "hierarchy" of price movement across different timeframes:
A higher score indicates that shorter EMAs are consistently above longer ones, signaling a strong upward trend.
A lower score or negative values would indicate the opposite (e.g., short-term prices lagging behind long-term averages, signaling weakness or potential reversal).
This method ensures that even complex data points (like price, volume, or oscillators) can be distilled into a single, comparable numerical value. When repeated across all 13 indicators, it enables the DW indicator to create a unified, normalized score that represents the overall market condition.
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Settings and Customization in Divergence-Weighted Clouds V 1.0 (DW)
The Divergence-Weighted Clouds V 1.0 (DW) indicator provides extensive customization options to empower traders to fine-tune the analysis according to their specific needs and trading strategies. Each of the 13 indicators is fully customizable through the settings menu, allowing adjustments to parameters such as lookback periods, sensitivity, and calculation methods. This flexibility ensures that DW can adapt seamlessly to a wide range of market conditions and asset classes.
Key Features of the Settings Menu
1. Global Settings:
Lookback Periods: Define the timeframe for data aggregation and analysis across all indicators.
Normalization Settings: Adjust parameters to refine the process of scaling diverse outputs to a comparable range.
Divergence Sensitivity: Control the weight given to indicators deviating from the average, enabling a focus on outliers or broader trends.
2. Indicator-Specific Settings:
Each of the 13 indicators has its own dedicated section in the settings menu for precise customization. Examples include:
ALMA (Arnaud Legoux Moving Average):
Window Size: Set the number of bars used for calculating the average.
Offset: Control the sensitivity of trend detection.
Sigma: Adjust the smoothing factor for the calculation.
Aroon Up:
Length: Modify the lookback period for identifying highs and evaluating uptrends.
ADX (Average Directional Index):
DI Length: Specify the period for calculating directional indicators (DI).
ADX Smoothing: Adjust the smoothing period for trend strength analysis.
3. Oscillator Settings:
Fisher Transform:
Length: Customize the period for normalization and detecting reversals.
Money Flow Index (MFI):
Length: Set the timeframe for analyzing overbought and oversold conditions.
4. Volume and Cash Flow Settings:
Chaikin Money Flow (CMF):
Length: Define the period for analyzing cash flow based on price and volume.
Volume Delta:
Timeframe: Select a custom timeframe for analyzing buying and selling pressure.
5. Support and Resistance Settings:
In the Support and Resistance category of the DW indicator, we address the logic behind four components:
McGinley Dynamic
Price Hierarchy
Base Line
Conversion Line
The settings structure for this section primarily focuses on McGinley Dynamic, while the other three elements—Price Hierarchy, Base Line, and Conversion Line—operate based on predefined values derived from the mathematical structure and logic of the DW indicator. Let’s explore this in detail:
McGinley Dynamic
Length: The only customizable setting in this category. Users can adjust the length parameter to tailor the responsiveness of the McGinley Dynamic to different market conditions. McGinley Dynamic adapts dynamically to the speed of price changes, reducing lag and minimizing false signals. Its flexibility allows it to serve as both a trendline and a support/resistance guide.
Price Hierarchy
The Price Hierarchy component in DW leverages a pyramid structure and triangular scoring based on prime-number intervals (e.g., 2, 3, 5, 7). This methodology ensures a mathematically robust framework for evaluating the relative position of prices across multiple timeframes.
Why No Settings for Price Hierarchy?
The unique properties of prime numbers make them ideal for constructing this hierarchical scoring system. Changing these intervals would compromise the integrity of the calculations, as they are specifically designed to ensure precision and consistency. Therefore, no customization is allowed for this component in the settings menu.
Conversion Line and Base Line
The Conversion Line (Tenkan-sen) and Base Line (Kijun-sen) are integral components derived from DW’s scoring methodology and represent short-term and medium-term equilibrium levels, respectively. These lines are calculated using the Ichimoku framework, which provides a reliable and well-recognized mathematical basis:
Conversion Line: The average of the highest high and lowest low over a fixed period of 9 bars.
Base Line: The average of the highest high and lowest low over a fixed period of 26 bars./list]
Both lines are utilized in DW as part of the 13 generated indicator variables to assess market equilibrium.
Why Default Values for Conversion and Base Lines?
These values are fixed to the default Ichimoku parameters to:
- Ensure consistency with the broader Ichimoku logic for users familiar with its methodology.
- Prevent confusion in the settings menu, as customization of these parameters is unnecessary for DW’s scoring system.
Important Note: While these lines are derived using Ichimoku logic, they are not standalone Ichimoku components but are embedded into DW’s mathematical structure. In the next section, we will elaborate on how the Ichimoku framework is employed for the graphical visualization of DW’s calculations.
Displaying the Results of 13 Indicator Integration in DW Indicator
The Divergence-Weighted Clouds V 1.0 (DW) employs a rigorous methodology to integrate 13 distinct indicators into a single, normalized output. Here's how the process works, followed by an explanation of the visualization strategy leveraging Ichimoku logic.
Simultaneous Evaluation of 13 Indicators
1. Mathematical Integration Logic:
Normalization: The outputs of all 13 indicators (e.g., ALMA, ADX, CMF) are normalized into comparable ranges, ensuring compatibility despite their diverse scales.
Hierarchical Scoring with Prime Intervals: For each indicator, Exponential Moving Averages (EMAs) are calculated using prime-number intervals (e.g., 2, 3, 5, 7). These EMAs are evaluated through a triangular scoring system, creating individual scores for each indicator.
Divergence Weighting: Indicators showing significant divergence from group averages are given higher weights, amplifying their influence on the final score.
2. Unified Score Calculation:
The normalized and weighted outputs of all 13 indicators are aggregated into a single score.
This score represents the overall behavior of the market, based on the simultaneous evaluation of trend, volume, oscillators, and price metrics.
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Challenge of Visualizing Results
The next challenge lies in effectively visualizing the score to make it actionable for traders. The DW indicator resolves this challenge by leveraging the Ichimoku framework.
Why Ichimoku for Visualization?
The Ichimoku system is known for its clear and predictive visualization capabilities, making it ideal for representing DW’s complex calculations:
1. Cloud-Based Display: Ichimoku Clouds (Kumo) are intuitive for identifying equilibrium zones and future price movements.
2. Projection Ability: The forward-projected Leading Spans (Senkou A and B) provide predictive insights based on past and current data.
3. Trader Familiarity: Ichimoku is widely recognized, reducing the learning curve for users.
Implementation of Ichimoku Logic
1. Mapping Score to Price:
The score is normalized and mapped to price using a scale factor, ensuring alignment with price data while preserving DW’s analytical integrity.
2. Ichimoku Cloud Lines:
Conversion Line (Tenkan-sen): Short-term equilibrium based on the score, calculated using a 9-period high-low average.
Base Line (Kijun-sen): Medium-term equilibrium calculated using a 26-period high-low average.
Leading Spans (Senkou A & B):
- Senkou A: Average of the Conversion and Base Lines.
- Senkou B: High-low average over a 52-period window.
Lagging Span (Chikou): Unlike traditional Ichimoku, DW’s Lagging Span reflects the Nebula Score shifted backward, providing a historical perspective on combined indicator behavior
3. Cloud Dynamics:
The Kumo Cloud is filled based on the relative position of Senkou A and Senkou B, using color shading to distinguish bullish and bearish conditions.
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Customization in Computational Settings
The core computational components of DW allow some customization for sensitivity adjustments:
Divergence Sensitivity: Controls the weight assigned to indicators with higher divergence.
Volatility Normalization: Adjusts the lookback period for volatility adjustments, refining the Nebula Score scaling.
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Advantages of Using Ichimoku Logic
1. Predictive Visualization:
The forward-projected cloud provides actionable insights for identifying trends and reversals earlier than traditional Ichimoku.
2. Aligned Lagging Span:
DW’s Lagging Span represents the normalized evaluation of all 13 indicators, offering a unique perspective beyond just closing price.
3. Intuitive Interpretation:
Traders familiar with Ichimoku can easily interpret DW’s outputs, making it accessible and effective.
Conclusion
By combining rigorous mathematical evaluation with Ichimoku’s visualization strengths, DW provides traders with a clear, actionable representation of market conditions. This ensures that the complex integration of 13 indicators is not only analytically robust but also visually intuitive.
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Comparison Between Divergence-Weighted Clouds V 1.0 (DW) and Traditional Ichimoku: NVIDIA 4H Chart
The chart showcases a side-by-side comparison of the Divergence-Weighted Clouds V 1.0 (DW) indicator (on the left) and the Traditional Ichimoku indicator (on the right). This comparison highlights the differences in how the two indicators interpret market trends and project equilibrium zones using their respective methodologies.
Key Observations and Insights
1. Base and Conversion Line Movements:
On Thursday, November 21, 2024, 17:30, in the DW indicator (left chart), the Base Line crosses above the Conversion Line, signaling a shift in medium-term equilibrium relative to short-term equilibrium.
On the Traditional Ichimoku (right chart), this crossover is not reflected until Monday, November 25, 2024, 17:30, occurring 4 days later.
Significance:
The DW indicator identifies the crossover and equilibrium shift significantly earlier due to its ability to process and normalize data from 13 distinct indicators.
This predictive capability provides traders with earlier insights, enabling them to anticipate changes and adjust their strategies proactively.
2. Cloud Dynamics and Leading Spans:
In both charts, the cloud (Kumo) represents the equilibrium and potential support/resistance zones.
The DW indicator’s Leading Span A and Leading Span B react faster to market changes, creating a more responsive and forward-looking cloud compared to the traditional Ichimoku.
Example:
On the DW chart (left), the cloud begins shifting to reflect the crossover earlier, signaling potential future support/resistance levels.
In the Ichimoku chart (right), the cloud reacts more slowly, lagging behind the DW indicator.
3. Lagging Span (Chikou Line):
In the DW indicator, the Lagging Span is based on the normalized output of the 13 indicators, reflecting their aggregated behavior rather than just the closing price shifted backward as in the traditional Ichimoku.
This provides a unique perspective on past market strength, aligning the Lagging Span more closely with the overall market condition derived from DW’s computations.
4. Price Alignment:
In the DW indicator, all normalized scores and values are mapped to align with price action, ensuring that the visualization remains intuitive while incorporating complex calculations.
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Advantages of DW Over Traditional Ichimoku
1.Earlier Signal Detection:
As demonstrated by the Base and Conversion Line crossover, DW detects changes in market equilibrium 4 days earlier, giving traders a significant advantage in anticipating price movements.
2. Enhanced Predictive Power:
The Leading Spans in DW’s cloud react faster, providing clearer forward-looking support and resistance zones compared to the traditional Ichimoku.
3. Comprehensive Data Integration:
While the Ichimoku relies solely on price-based calculations, DW integrates outputs from 13 distinct indicators, offering a more robust and comprehensive analysis of market conditions.
4. Alignment with Market Behavior:
The DW Lagging Span reflects the aggregated score of multiple indicators, aligning more closely with overall market sentiment and providing a deeper context than the price-based Lagging Span in Ichimoku.
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Final Note
The chart comparison illustrates how the Divergence-Weighted Clouds V 1.0 (DW) indicator outperforms traditional Ichimoku in terms of signal responsiveness and predictive accuracy. By combining the mathematical rigor of DW’s calculations with the visual clarity of Ichimoku, traders gain a powerful tool for analyzing market trends and making informed decisions.
Look at the DW chart (left) to see how early signals and cloud adjustments provide actionable insights compared to the slower reactions of the Traditional Ichimoku chart (right).
Compare TOTAL, TOTAL2, TOTAL3, and OTHERSCompare TOTAL, TOTAL2, TOTAL3, and OTHERS
This indicator compares the performance of major cryptocurrency market cap indices: TOTAL, TOTAL2, TOTAL3, and OTHERS. It normalizes each index's performance relative to its starting value and visualizes their relative changes over time.
Features
- Normalized Performance: Tracks the percentage change of each index from its initial value.
- Customizable Timeframe: Allows users to select a base timeframe for the data (e.g., daily, weekly).
- Dynamic Labels: Displays the latest performance of each index as a label on the chart, aligned to the right of the corresponding line for easy comparison.
- Color-Coded Lines: Each index is assigned a distinct color for clear differentiation:
-- TOTAL (Blue): Represents the total cryptocurrency market cap.
-- TOTAL2 (Green): Excludes Bitcoin.
-- TOTAL3 (Orange): Excludes Bitcoin and Ethereum.
-- OTHERS (Red): Represents all cryptocurrencies excluding the top 10 by market cap.
- Baseline Reference: Includes a horizontal line at 0% for reference.
Use Cases:
- Market Trends: Identify which segments of the cryptocurrency market are outperforming or underperforming over time.
- Portfolio Insights: Assess the impact of Bitcoin and Ethereum dominance on the broader market.
- Market Analysis: Compare smaller-cap coins (OTHERS) with broader indices (TOTAL, TOTAL2, and TOTAL3).
This script is ideal for traders and analysts who want a quick, visual way to track how different segments of the cryptocurrency market perform relative to each other over time.
Note: The performance is normalized to highlight percentage changes, not absolute values.
Pi Cycle MACD Inverse OscillatorPi Cycle MACD Inverse Oscillator with Gradient and Days Since Last Top
This indicator is ideal for Bitcoin traders seeking a robust tool to visualize long-term and short-term trends with enhanced clarity and actionable insights.
This script combines the concept of the Pi Cycle indicator with a unique MACD-based inverse oscillator to analyze Bitcoin market trends. It introduces several features to help traders understand market conditions better:
Inverse Oscillator:
- Oscillator ranges between 1 and -1.
- A value of 1 indicates the two moving averages (350 MA and 111 MA) are equal.
- A value of -1 indicates the maximum observed distance between the moving averages during the selected lookback period.
- The oscillator dynamically adjusts to price changes using a configurable scaling factor.
Gradient Visualization:
The oscillator line transitions smoothly from green (closer to -1) to yellow (at 0) and red (closer to 1).
The color gradient provides a quick visual cue for market momentum.
Days Since Last Pi Cycle Top:
Calculates and displays the number of days since the last "Pi Cycle Top" (defined as a crossover between the two moving averages).
The label updates dynamically and appears only on the most recent bar.
Conditional Fill:
Highlights the area between 0 and 1 with a green gradient when the price is above the long moving average.
Enhances visual understanding of the oscillator's position relative to key thresholds.
Inputs:
- Long Moving Average (350 default): Determines the primary trend.
- Short Moving Average (111 default): Measures shorter-term momentum.
- Oscillator Lookback Period (100 default): Defines the range for normalizing the oscillator.
- Price Scaling Factor (0.01 default): Adjusts the normalization to account for large price fluctuations.
How to Use:
- Use the oscillator to identify potential reversal points and trend momentum.
- Look for transitions in the gradient color and the position relative to 0.
- Monitor the "Days Since Last Top" label for insights into the market's cycle timing.
- Utilize the conditional fill to quickly assess when the market is in a favorable position above the long moving average.
ForecastPro by BinhMyco1. Overview:
This Pine Script implements a custom forecasting tool on TradingView, labeled "BinhMyco." It provides a method to predict future price movements based on historical data and a comparison with similar historical patterns. The script supports two types of forecasts: **Prediction** and **Replication**, where the forecasted price can be either based on price peaks/troughs or an average direction. The script also calculates a confidence probability, showing how closely the forecasted data aligns with historical trends.
2. Inputs:
- Source (`src`): The input data source for forecasting, which defaults to `open`.
- Length (`len`): The length of the training data used for analysis (fixed at 200).
- Reference Length (`leng`): A fixed reference length for comparing similar historical patterns (set to 70).
- Forecast Length (`length`): The length of the forecast period (fixed at 60).
- Multiplier (`mult`): A constant multiplier for the forecast confidence cone (set to 4.0).
- Forecast Type (`typ`): Type of forecast, either **Prediction** or **Replication**.
- Direction Type (`dirtyp`): Defines how the forecast is calculated — either based on price **peaks/troughs** or an **average direction**.
- Forecast Divergence Cone (`divcone`): A boolean option to enable the display of a confidence cone around the forecast.
3. Color Constants:
- Green (`#00ffbb`): Color used for upward price movements.
- Red (`#ff0000`): Color used for downward price movements.
- Reference Data Color (`refcol`): Blue color for the reference data.
- Similar Data Color (`simcol`): Orange color for the most similar data.
- Forecast Data Color (`forcol`): Yellow color for forecasted data.
4. Error Checking:
- The script checks if the reference length is greater than half the training data length, and if the forecast length exceeds the reference length, raising errors if either condition is true.
5. Arrays for Calculation:
- Correlation Array (`c`): Holds the correlation values between the data source (`src`) and historical data points.
- Index Array (`index`): Stores the indices of the historical data for comparison.
6. Forecasting Logic:
- Correlation Calculation: The script calculates the correlation between the historical data (`src`) and the reference data over the given reference length. It then identifies the point in history most similar to the current data.
- Forecast Price Calculation: Based on the type of forecast (Prediction or Replication), the script calculates future prices either by predicting based on similar bars or by replicating past data. The forecasted prices are stored in the `forecastPrices` array.
- Forecast Line Drawing: The script draws lines to represent the forecasted price movements. These lines are color-coded based on whether the forecasted price is higher or lower than the current price.
7. Divergence Cone (Optional):
- If the **divcone** option is enabled, the script calculates and draws a confidence cone around the forecasted prices. The upper and lower bounds of the cone are calculated using a standard deviation factor, providing a visual representation of forecast uncertainty.
8. Probability Table:
- A table is displayed on the chart, showing the probability of the forecast being accurate. This probability is calculated using the correlation between the current data and the most similar historical pattern. If the probability is positive, the table background turns green; if negative, it turns red. The probability is presented as a percentage.
9. Key Functions:
- `highest_range` and `lowest_range`: Functions to find the highest and lowest price within a range of bars.
- `ftype`: Determines the forecast type (Prediction or Replication) and adjusts the forecasting logic accordingly.
- `ftypediff`: Computes the difference between the forecasted and actual prices based on the selected forecast type.
- `ftypelim`, `ftypeleft`, `ftyperight`: Additional functions to adjust the calculation of the forecast based on the forecast type.
10. Conclusion:
The "ForecastPro" script is a unique tool for forecasting future price movements on TradingView. It compares historical price data with similar historical trends to generate predictions. The script also offers a customizable confidence cone and displays the probability of the forecast's accuracy. This tool provides traders with valuable insights into future price action, potentially enhancing decision-making in trading strategies.
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This script provides advanced functionality for traders who wish to explore price forecasting, and can be customized to fit various trading styles.
Market Movement After OpenDescription:
This script provides a detailed visualization of market movements during key trading hours: the German market opening (08:00–09:00 UTC+1) and the US market opening (15:30–16:30 UTC+1). It is designed to help traders analyze price behavior in these critical trading periods by capturing and presenting movement patterns and trends directly on the chart and in an interactive table.
Key Features:
Market Movement Analysis:
Tracks the price movement during the German market's first hour (08:00–09:00 UTC+1) and the US market's opening session (15:30–16:30 UTC+1).
Analyzes whether the price moved up or down during these intervals.
Visual Representation:
Dynamically colored price lines indicate upward (green) or downward (red) movement during the respective periods.
Labels ("DE" for Germany and "US" for the United States) mark key moments in the chart.
Historical Data Table:
Displays the past 10 trading days' movement trends in an interactive table, including:
Date: Trading date.
German Market Movement: Up (▲), Down (▼), or Neutral (-) for 08:00–09:00 UTC+1.
US Market Movement: Up (▲), Down (▼), or Neutral (-) for 15:30–16:30 UTC+1.
The table uses color coding for easy interpretation: green for upward movements, red for downward, and gray for neutral.
Real-Time Updates:
Automatically updates during live trading sessions to reflect the most recent movements.
Highlights incomplete periods (e.g., ongoing sessions) to indicate their status.
Customizable:
Suitable for intraday analysis or broader studies of market trends.
Designed to overlay directly on any price chart.
Use Case:
This script is particularly useful for traders who focus on market openings, which are often characterized by high volatility and significant price movements. By providing a clear visual representation of historical and live data, it aids in understanding and capitalizing on market trends during these critical periods.
Notes:
The script works best when the chart is set to the appropriate timezone (UTC+1 for the German market or your local equivalent).
For precise trading decisions, consider combining this script with other technical indicators or trading strategies.
Feel free to share feedback or suggest additional features to enhance the script!
