2 CGC EMAChecks for 2 green closes above EMA.
Sends only one buy signal when this happens initially.
Won't send another buy signal until price closes below the EMA at least once (resets).
EMA is plotted with your offset visually.
Educational
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Monthly Session Divider (Alt Background) | Chart_BullyEasily visualize monthly transitions with alternating background shading. Designed for traders who like to spot macro trends, monthly opens, and institutional order flow.
✅ Alternates background color each month
✅ Auto-detects new months using live date logic
✅ Great for RTH or ETH intraday and swing strategies
✅ Clean gray overlay with low opacity
✅ Works on intraday, daily, and weekly charts
✅ Built for clarity, not clutter
Use this tool to:
Identify monthly pivots or volume rotations
Anchor monthly VWAPs or FVGs with visual context
Frame long-term setups with clean visual breaks
Weekly Session Divider (Alt Background) | Chart_BullyThis tool adds subtle alternating background shading for each new week, helping you visually distinguish trading sessions at a glance.
✅ Alternates background by weekly session
✅ Works great on intraday and daily timeframes
✅ Ideal for traders who rely on weekly pivots, volume profiles, or macro structure
✅ Compatible with both RTH and ETH charts
✅ Clean design for easy chart integration
Use it to improve your session awareness, spot emerging weekly trends, and avoid mental fatigue when reading extended charts.
Alternate Day Divider Background | Chart_BullyThis free utility shades every other trading day on your chart, helping you visually separate sessions and spot daily rhythm or pattern shifts more easily.
✅ Automatically alternates background shading by day
✅ Works on both Regular Trading Hours (RTH) and Extended Trading Hours (ETH)
✅ Especially useful on intraday and daily timeframes
✅ Helps identify breakout setups, trend shifts, or volume cycles by session
Great for scalpers, day traders, and anyone who wants a subtle visual edge without chart clutter.
📡 ETF RADAR HUD (SPY · QQQ · SPX) Auto-detects if you’re on SPY, SPX or QQQ
Shows a sleek status dashboard with:
Trend condition (EMA crossover)
Volatility meter (based on ATR vs price)
RSI mood
Volume activity
Instrument tag ("SPY 🔍", "QQQ 🚀", "SPX" or "Other 🪐")
🧠 Strategy:
We build a situational awareness HUD so SPY/QQQ/SPX day traders know:
Are we trending or ranging?
Is volatility expanding?
Are we in overbought/oversold territory?
Is there a volume surge?
Bot LabelsLive 1-minute BTCGBP chart with automated VWAP, current volume, and 20-bar average volume labels. Designed for bot integration to detect high-volume breakouts or momentum shifts. Updated every minute with real-time data for precision entry signals. Ideal for algorithmic trading or volume-based strategy monitoring.
Critical Pivot PointsCritical pivot points, marked on chart.
Top pivot points marked with green box
Bottom pivot points marked with red box
Simple & easy!
Pattern DetectorPattern detector - detects double tops, double bottoms, wedges & other common patterns. Draws the lines & prints on chart what it's identifying.
[Top] Simple Position + SL CalculatorThis indicator is a user-friendly tool designed to help traders easily calculate optimal position sizing, determine suitable stop-loss levels, and quantify maximum potential losses in dollar terms based on their personalized trading parameters.
Key Features:
Position Size Calculation: Automatically computes the number of shares to purchase based on the trader’s total account size and specified percentage of the account allocated per trade.
Stop-Loss Level: Suggests an appropriate stop-loss price point calculated based on the trader’s defined risk percentage per trade.
Max Loss Visualization: Clearly displays the maximum potential loss (in dollars) should the stop-loss be triggered.
Customizable Interface: Provides the flexibility to place the calculation table in different chart positions (Top Left, Top Right, Bottom Left, Bottom Right) according to user preference.
How to Use:
Enter your total Account Size.
Set the desired Position Size as a percentage of your account. (Typically, 1%–5% per trade is recommended for cash accounts.)
Define the Risk per Trade percentage (commonly between 0.05%–0.5%).
Choose your preferred Table Position to comfortably integrate with your trading chart.
Note:
If you identify a technical support level below the suggested stop-loss point, consider reducing your position size to manage the increased risk effectively.
Keep in mind that the calculations provided by this indicator are based solely on standard industry best practices and the specific inputs entered by you. They do not account for market volatility, news events, or any other factors outside the provided parameters. Always complement this indicator with sound technical and fundamental analysis.
My Trading mantra/playbook🧠 My Trading Mantra — Motivational Trading Reminder Overlay
This indicator displays a customizable trading mantra as an overlay on your TradingView charts to keep your mindset sharp and disciplined during trading sessions.
You can customize the mantra text, font size, text color, background color, transparency, and screen position (top, middle, bottom, left, right, center).
It’s designed to serve as a constant motivational reminder emphasizing core trading principles like planning, risk management, patience, and learning from losses to grow profits.
Features:
Customizable multi-line mantra text input
Adjustable font size (small to huge)
Color customization for text and background
Adjustable background transparency
Multiple screen position options for display
Lightweight and simple overlay, no performance impact
Purpose:
To help traders stay mentally focused and disciplined by having their personalized mantra visible at all times while analyzing charts.
Additionally, it can be used as a trading plan or playbook, allowing traders to display their key rules, strategies, or reminders directly on their charts for quick reference during live trading.
code is open with love.
you are a good trader don't let the markets tell you diffrent.
Position Size & Stop-Loss CalculatorPine Script Code for Position Size & Stop-Loss Calculator Indicator
This Pine Script indicator for TradingView will allow you to input your trading parameters and see the calculated Stop-Loss Price plotted on the chart, along with the recommended number of shares and maximum dollar risk displayed as a text label.
LB | SB | OH | OL (Auto Futures OI)This indicator is for trading purposes, particularly in futures markets given the inclusion of open interest (OI) data.
Indicator Name and Overlay: The indicator is named "LB | SB | OH | OL" and is set to overlay on the price chart (overlay=true).
Override Symbol Input: Users can input a symbol to override the default symbol for analysis.
Open Interest Data Retrieval: It retrieves open interest data for the specified symbol and time frame. If no data is found, it generates a runtime error.
Dashboard Configuration: Users can choose to display a dashboard either at the top right, bottom right, or bottom left of the chart.
Calculations:
It calculates the percentage change in open interest (oi_change).
It calculates the percentage change in price compared to the previous day's close (price_change).
Build Up Conditions:
Long Build Up: When there's a significant increase in open interest (OIChange threshold) and price rises (PriceChange threshold).
Short Build Up: When there's a significant increase in open interest (OIChange threshold) and price falls (PriceChange threshold).
Display Table:
It creates a table on the chart showing the build-up conditions, open interest change percentage, and price change percentage.
Labeling:
It allows for the labeling of buy and sell conditions based on price movements.
Overall, this indicator provides a visual representation of open interest and price movements, helping traders identify potential trading opportunities based on build-up conditions and price behavior.
The "LB | SB | OH | OL" indicator is a tool designed to assist traders in analyzing price movements and open interest (OI) changes in FNO markets. This indicator combines various elements to provide insights into long build-up (LB), short build-up (SB), open-high (OH), and open-low (OL) scenarios.
Key features of the indicator include:
Override Symbol Input: Traders can override the default symbol and input their preferred symbol for analysis.
Open Interest Data: The indicator retrieves open interest data for the selected symbol and time frame, facilitating analysis based on changes in open interest.
Dashboard: The indicator features a customizable dashboard that displays key information such as build-up conditions, OI change, and price change.
Build-Up Conditions: The indicator identifies long build-up and short build-up scenarios based on user-defined thresholds for OI change and price change percentages.
Customization Options: Traders have the flexibility to customize various aspects of the indicator, including colors for long build-up, short build-up, positive OI change, negative OI change, positive price change, and negative price change.
Label Plots: Buy and sell labels are plotted on the chart to highlight potential trading opportunities. Traders can customize the colors and text colors of these labels based on their preferences.
Overall, the "LB | SB | OH | OL" indicator offers traders a comprehensive tool for analyzing price movements and open interest changes, helping them make informed trading decisions in the FNO markets.
ATR | LOTSIZE | Risk (Futures)This Pine Script is a futures-specific trading utility designed to help F\&O (Futures and Options) traders quickly assess the volatility and position sizing for any selected stock on the chart — even if it's not a futures chart.
What the Script Does:
* Automatically detects the futures symbol for the underlying equity using a dynamic mapping system.
* Calculates the ATR (Average True Range) of the futures contract using either SMA or EMA.
* Fetches the Lot Size (Point Value) of the futures instrument.
* Computes risk per lot by multiplying ATR with lot size (Risk = ATR × Lot Size).
* Displays all 3 values — ATR, Lot Size, and Risk in INR — in a compact table on the chart.
Why This Is Useful for F\&O Traders:
* ✅ Quick Risk Assessment: Helps traders understand how much is at risk per lot without switching to the actual futures chart.
* ✅ Position Sizing: Provides data to calculate how many lots to trade based on a defined risk per trade.
* ✅ Volatility Awareness:ATR gives insights into how much the stock typically moves, guiding stop-loss and target placements.
* ✅ Efficient Workflow:No need to load separate futures charts or lookup lot sizes manually — saves time and reduces error.
This tool is ideal for discretionary and systematic traders who want risk and volatility context for every trade, especially in the NSE Futures & Options segment.
Open Range Breakout (ORB) with Alerts
📘 Open Range Breakout (ORB) Indicator – by thechartsalgo™
🧠 What It Does:
This indicator helps traders identify breakout opportunities from t he initial price range of the trading day — typically the first 15 or 30 minutes after the market opens.
It tracks the high and low of a user-defined time window (e.g. 9:30–9:45) and plots these levels on the chart. Once the session range is set, it detects breakouts when price moves above the range high (bullish breakout) or below the range low (bearish breakout).
⚙️ Key Features:
✅ Custom Time Window
Define your own start and end time for the range (e.g., 09:30–09:45).
✅ Breakout Signals
Arrows show up when price breaks above or below the range after it has formed.
✅ Color Customization
Choose your own colors for range lines and background zone.
✅ Background Highlight
Optional shaded fill between high/low makes the range visually clear.
✅ Only Show Today's Range
Option to hide previous day levels to keep your chart clean.
✅ Alerts
Built-in alerts notify you when a breakout occurs — long or short.
📈 How to Use It:
Set the start and end time to match your market’s open range (commonly first 15, 30, or 60 minutes).
Wait for the range to lock in (highlighted area on chart).
Trade the breakout direction once price moves above or below the range.
Optionally, use it in combination with volume or price action confirmation.
🔔 Alerts (Optional Setup):
ORB Breakout Up → triggers when price closes above the high
ORB Breakout Down → triggers when price closes below the low
📌 Who Is It For?
Day traders looking to catch early momentum
Scalpers using session-based price action
Strategy developers who use the opening range as a key concept.
⚠️ Disclaimer:
This indicator is for educational and informational purposes only. It is not financial advice, and no guarantees are made regarding its accuracy or effectiveness.
All trading involves risk. You are solely responsible for your own trading decisions. Always do your own research and consult with a licensed financial advisor before making any investment decisions.
By using this script, you agree that thechartsalgo™, its developers, and affiliates are not liable for any losses or damages resulting from the use of this tool.
TZSesThe script visually highlights major forex trading sessions (London, New York, Tokyo) and a "true day" separator on the chart background to help traders identify the most active market hours and daily boundaries.
Volume pressure by GSK-VIZAG-AP-INDIA🔍 Volume Pressure by GSK-VIZAG-AP-INDIA
🧠 Overview
“Volume Pressure” is a multi-timeframe, real-time table-based volume analysis tool designed to give traders a clear and immediate view of buying and selling pressure across custom-selected timeframes. By breaking down buy volume, sell volume, total volume, and their percentages, this indicator helps traders identify demand/supply imbalances and volume momentum in the market.
🎯 Purpose / Trading Use Case
This indicator is ideal for intraday and short-term traders who want to:
Spot aggressive buying or selling activity
Track volume dynamics across multiple timeframes *1 min time frame will give best results*
Use volume pressure as a confirming tool alongside price action or trend-based systems
It helps determine when large buying/selling activity is occurring and whether such behavior is consistent across timeframes—a strong signal of institutional interest or volume-driven trend shifts.
🧩 Key Features & Logic
Real-Time Table Display: A clean, dynamic table showing:
Buy Volume
Sell Volume
Total Volume
Buy % of total volume
Sell % of total volume
Multi-Time frame Analysis: Supports 8 user-selectable custom time frames from 1 to 240 minutes, giving flexibility to analyze volume pressure at various granularities.
Color-Coded Volume Bias:
Green for dominant Buy pressure
Red for dominant Sell pressure
Yellow for Neutral
Intensity-based blinking for extreme values (over 70%)
Dynamic Data Calculation:
Uses volume * (close > open) logic to estimate buy vs sell volumes bar-by-bar, then aggregates by timeframe.
⚙️ User Inputs & Settings
Timeframe Selectors (TF1 to TF8): Choose any 8 timeframes you want to monitor volume pressure across.
Text & Color Settings:
Customize text colors for Buy, Sell, Total volumes
Choose Buy/Sell bias colors
Enable/disable blinking for visual emphasis on extremes
Table Appearance:
Set header color, metric background, and text size
Table positioning: top-right, bottom-right, etc.
Blinking Highlight Toggle: Enable this to visually highlight when Buy/Sell % exceeds 70%—a sign of strong pressure.
📊 Visual Elements Explained
The table has 6 rows and 10 columns:
Row 0: Headers for Today and TF1 to TF8
Rows 1–3: Absolute values (Buy Vol, Sell Vol, Total Vol)
Rows 4–5: Relative percentages (Buy %, Sell %), with dynamic background color
First column shows the metric names (e.g., “Buy Vol”)
Cells blink using alternate background colors if volume pressure crosses thresholds
💡 How to Use It Effectively
Use Buy/Sell % rows to confirm potential breakout trades or identify volume exhaustion zones
Look for multi-timeframe confluence: If 5 or more TFs show >70% Buy pressure, buyers are in control
Combine with price action (e.g., breakouts, reversals) to increase conviction
Suitable for equities, indices, futures, crypto, especially on lower timeframes (1m to 15m)
🏆 What Makes It Unique
Table-based MTF Volume Pressure Display: Most indicators only show volume as bars or histograms; this script summarizes and color-codes volume bias across timeframes in a tabular format.
Customization-friendly: Full control over colors, themes, and timeframes
Blinking Alerts: Rare visual feature to capture user attention during extreme pressure
Designed with performance and readability in mind—even for fast-paced scalping environments.
🚨 Alerts / Extras
While this script doesn’t include TradingView alert functions directly, the visual blinking serves as a strong real-time alert mechanism.
Future versions may include built-in alert conditions for buy/sell bias thresholds.
🔬 Technical Concepts Used
Volume Dissection using close > open logic (to estimate buyer vs seller pressure)
Simple aggregation of volume over custom timeframes
Table plotting using Pine Script table.new, table.cell
Dynamic color logic for bias identification
Custom blinking logic using na(bar_index % 2 == 0 ? colorA : colorB)
⚠️ Disclaimer
This indicator is a tool for analysis, not financial advice. Always backtest and validate strategies before using any indicator for live trading. Past performance is not indicative of future results. Use at your own risk and apply proper risk management.
✍️ Author & Signature
Indicator Name: Volume Pressure
Author: GSK-VIZAG-AP-INDIA
TradingView Username: prowelltraders
80-20_DCA-Alert
The idea for this indicator comes from the book “$1,000 To $1,000,000 Proven Strategies for Triple Leveraged ETF Success” by B.D. Collins. In the book, he describes a charming 80/20 DCA strategy with a stronger price weighting when prices fall in order to trade leveraged ETFs. This indicator is applied to the chart of the unleveraged (!) underlying or index of the ETF. You can then use the alarm function to receive a (daily) update on how much of the cash should currently be invested into the corresponding leveraged ETF. Depending on whether the price is above or below the freely definable levels, a different weighting is recommended. The default settings are based on B.D. Collins' original strategy and are as follows:
At the beginning of each quarter, if the price of the unleveraged underlying (index) of the ETF
- is between 0 and 15% below the ATH, 20% of the saved cash balance is invested
- between 16 and 25% below the ATH, 40% of the saved cash balance is invested
- between 26 and 35% below the ATH, 60% of the saved cash balance is invested
- greater than 35% below the ATH, 80% of the saved cash balance is invested
More details in his book.
This is not financial advice. Trading with leveraged ETFs is very risky and can lead to extreme losses
Good Luck and may the force be with us
Bullish Bearish Signal with EMA Color + LabelsThis script generates clear BUY and SELL signals based on a combination of trend direction, momentum, and confirmation from multiple indicators. It is intended to help traders identify strong bullish or bearish conditions using commonly trusted tools: EMA 200, MACD, and RSI.
🔍 How it works:
The strategy combines three key elements:
EMA 200 Trend Filter
Identifies the long-term trend:
Price above EMA200 → Bullish trend bias
Price below EMA200 → Bearish trend bias
The EMA line is color-coded:
🔵 Blue for bullish
🔴 Red for bearish
⚪ Gray for neutral/unclear
MACD Crossover
Detects shifts in market momentum:
Bullish: MACD line crosses above signal line
Bearish: MACD line crosses below signal line
RSI Confirmation
Adds an extra layer of confirmation:
Bullish: RSI is above its signal line
Bearish: RSI is below its signal line
✅ Signal Logic:
BUY Signal appears when:
Price > EMA200
MACD crosses up
RSI > its signal line
SELL Signal appears when:
Price < EMA200
MACD crosses down
RSI < its signal line
Labels will appear on the chart to highlight these events.
🔔 Alerts:
The script includes alerts for both Buy and Sell conditions, so you can be notified in real-time when they occur.
📈 How to Use:
Best used in trending markets.
Recommended for higher timeframes (1H and above).
May be combined with other tools such as support/resistance or candlestick analysis.
⚠️ Disclaimer: This script is intended for educational purposes only and does not constitute financial advice or a trading recommendation.
Abusuhil Bullish Candles (Label + Table)Abusuhil Bullish Candles is a pattern recognition indicator designed to identify key bullish reversal candlestick formations including Hammer, Bullish Engulfing, Morning Star, Piercing Line, Three White Soldiers, and Three Inside Up.
The script includes optional filters such as Stochastic and Volume Confirmation, providing more precise signal detection.
Each pattern and filter is fully customizable via settings. Alerts are also included to support active trading workflows.
This script was written originally and does not copy open-source indicators. It's ideal for traders seeking visual clarity on bullish opportunities with professional-grade logic.
مؤشر الشموع الصعودية هو مؤشر احترافي يكتشف أبرز نماذج الانعكاس الصعودي في الشموع اليابانية مثل: Hammer، Bullish Engulfing، Morning Star، Piercing Line، Three White Soldiers، و Three Inside Up.
يوفر المؤشر فلاتر إضافية مثل فلتر Stochastic وفلتر الفوليوم لتعزيز دقة الإشارات. جميع الإعدادات قابلة للتعديل بما يتناسب مع احتياج كل متداول.
يحتوي المؤشر أيضًا على تنبيهات تلقائية لدعم استراتيجيات التداول اللحظي. تمت برمجة المؤشر من الصفر ويعتمد على منطق خاص غير منسوخ من سكربتات مفتوحة المصدر.
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🇸🇦 التحديثات – النسخة الجديدة (Abusuhil Bullish Candles)
✅ تم تغيير الملصقات بشكل أوضح: باستخدام دوائر ملونة أسفل الشموع بدلًا من المربعات لتفادي التراكب.
🟦 إضافة جدول تفاعلي على الشارت يعرض أسماء النماذج وألوانها المخصصة.
🎨 إمكانية تغيير ألوان كل نموذج من الإعدادات حسب رغبة المستخدم.
🧩 تفعيل/تعطيل كل نموذج على حدة من خلال إعدادات منفصلة.
🔔 إضافة تنبيه احترافي واحد يتم تفعيله عند تحقق أي نموذج نشط من النماذج المحددة.
📋 توافق كامل مع سياسة TradingView:
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لا تكرار للوظائف أو العناوين.
وصف واضح مع تحكم كامل للمستخدم.
🇬🇧 Updates – Latest Version (Abusuhil Bullish Candles)
✅ Clearer Signal Labels: Now uses colored circles under candles instead of labels to avoid overlapping.
🟦 Interactive Table showing pattern names and user-defined colors.
🎨 Customizable colors for each candlestick pattern from the settings menu.
🧩 Toggle each pattern independently using dedicated checkboxes.
🔔 Single professional alert condition that triggers only when any enabled pattern is detected.
📋 Fully compliant with TradingView's publishing policy:
No reused or built-in indicator code.
No duplicated logic or misleading titles.
Clean and modular design with full user customization.