Multi-Timeframe VWAP Master ProThe Multi-Timeframe VWAP Suite is a comprehensive and highly customizable indicator designed for traders who rely on Volume-Weighted Average Price (VWAP) across multiple timeframes and periods. This tool provides a complete suite of VWAP calculations, including daily, weekly, monthly, quarterly, yearly, and custom VWAPs, allowing traders to analyze price action and volume trends with precision. Whether you're a day trader, swing trader, or long-term investor, this indicator offers unparalleled flexibility and depth for your trading strategy.
Multi-Timeframe VWAPs:
Daily, Weekly, Monthly, Quarterly, and Yearly VWAPs: Track VWAP across various timeframes to identify key support and resistance levels.
Customizable Timeframes: Use the SMA timeframe input to adjust the period for moving averages and other calculations.
Previous Period VWAPs:
Previous Daily, Weekly, Monthly, and Quarterly VWAPs: Analyze historical VWAP levels to understand past price behavior and identify potential reversal zones.
Previous Year Quarterly VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
Custom VWAPs:
Custom Start Date and Timeframe: Define your own VWAP periods by specifying a start date and timeframe, allowing for tailored analysis.
Dynamic Custom VWAP Calculation: Automatically calculates VWAP based on your custom inputs, ensuring flexibility for unique trading strategies.
Seasonal and Yearly VWAPs:
April, July, and October VWAPs: Analyze seasonal trends by tracking VWAP levels for specific months.
Yearly VWAP: Get a broader perspective on long-term price trends with the yearly VWAP.
SMA Integration:
SMA Overlay: Combine VWAP analysis with a Simple Moving Average (SMA) for additional confirmation of trends and reversals.
Customizable SMA Length and Timeframe: Adjust the SMA settings to match your trading style and preferences.
User-Friendly Customization:
Toggle Visibility and Labels: Easily enable or disable the display of specific VWAPs and their labels to keep your chart clean and focused.
Color Customization: Each VWAP line and label is color-coded for easy identification and can be customized to suit your preferences.
Dynamic Labeling:
Automatic Labels: Labels are dynamically placed on the last bar, providing clear and concise information about each VWAP level.
Customizable Label Text: Labels include detailed information, such as the timeframe or custom period, for quick reference.
Flexible Timeframe Detection:
Automatic Timeframe Detection: The indicator automatically detects new days, weeks, months, and quarters, ensuring accurate VWAP calculations.
Support for Intraday and Higher Timeframes: Works seamlessly on all chart timeframes, from 1-minute to monthly charts.
Previous Year Quarterly VWAPs:
Q1, Q2, Q3, Q4 VWAPs: Compare current price action to VWAP levels from specific quarters of the previous year.
User-Selectable Year: Choose the year for which you want to calculate previous quarterly VWAPs.
Persistent Monthly VWAPs:
Option to Persist Monthly VWAPs Year-Round: Keep monthly VWAP levels visible even after the month ends for ongoing analysis.
Comprehensive Analysis: Combines multiple VWAP timeframes and periods into a single tool, eliminating the need for multiple indicators.
Customizable and Flexible: Tailor the indicator to your specific trading strategy with customizable timeframes, periods, and settings.
Enhanced Decision-Making: Gain deeper insights into price action and volume trends across different timeframes, helping you make more informed trading decisions.
Clean and Organized Charts: Toggle visibility and labels to keep your chart clutter-free while still accessing all the information you need.
Ideal For:
Day Traders: Use daily and intraday VWAPs to identify intraday support and resistance levels.
Swing Traders: Analyze weekly and monthly VWAPs to spot medium-term trends and reversals.
Long-Term Investors: Leverage quarterly and yearly VWAPs to understand long-term price behavior and key levels.
Seasonal Traders: Track April, July, and October VWAPs to capitalize on seasonal trends.
The Multi-Timeframe VWAP Suite is a powerful and versatile tool for traders of all styles and timeframes. With its comprehensive suite of VWAP calculations, customizable settings, and user-friendly design, it provides everything you need to analyze price action and volume trends with precision and confidence. Whether you're looking to fine-tune your intraday strategy or gain a broader perspective on long-term trends, this indicator has you covered.
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Kalman Filter Trend BreakersThe Kalman filter is a recursive algorithm developed in 1960 by Rudolf E. Kálmán, a Hungarian-American engineer and mathematician, that provides optimal estimates of a system's state by combining noisy measurements with a predictive model. It is widely used in control systems, signal processing, and finance for tracking and forecasting.
In trading, KF might be a good replacement for a moving average, as it reacts to price changes in a different way. Not only it follows price direction, but can also track the velocity of price change. This specific behaviour of KF is used in this indicator to track changes in trends.
Trend is characterized by price moving directionally, however, any trend comes to pause or complete stop and reversal, as the price changes more slowly (a trend fades into a sideways movement for a while) or the price movement changes direction, thus making a reversal.
This indicator detects the points where such changes occur (trend breaker points), and produces signals, which serve as points of current trend pausing or reversing. By applying different settings for KF calculation, you can produce less or more signals that indicate change in trend character, and either detect only significant trends changes, or less and shorter trends changes as well.
The signals do not differentiate the exact type of a trend change (it can be a brief trend pause followed by a continuation, as well as a complete reversal). However, once you are in a trend, the significant velocity change indicates a change in trend structure. In this sense, trend breaker signals should not be followed blindly, and can be used only as trend (and subsequently, position) exit confirmations, but not the entry contrarian confirmations.
For better visual representation, you can use chart signals attached to bars, and additionally paint a vertical gradient at each signal which shows significant trend deceleration.
Kalman filter calculations used in this indicator are partially based on an open-source code from @loxx which was published in 2022 as Kalman filter overlay .
Altcoins Screener [SwissAlgo]Introduction: The Altcoins Screener at a Glance
The Altcoins Screener is a cryptocurrency analysis tool designed to provide an overview of potential trading opportunities across multiple crypto coins/tokens and categories. By combining technical analysis, price action assessment, and social metrics (via LunarCrush data), it presents market information and trading signals for a broad range of altcoins (approx. 300 USDT.P pairs of 9 crypto categories).
The screener is designed to consolidate market information onto a single chart , aiming to streamline the analysis of market conditions. It provides a consolidated market overview, which can simplify the assessment of market conditions, compared to monitoring individual charts with several layered indicators.
Key Features:
🔹 Multi-category analysis covering 300 crypto pairs of 9 categories on a single chart (Layer 1 & Top Coins, Layer2 & Scaling, Defi & Landing, Gaming & Metaverse, AI & Data, Exchanges & Trading, NFT & Social, Memes & Community, Other, User's Custom Portfolio).
🔹 Technical analysis with trade signals (Long/Short) based on an aggregated view of technical and social data points
🔹 Social sentiment integration through LunarCrush metrics (GalaxyScore, AltRank, Social Sentiment)
🔹 Real-time market scanning provides automated alerts when market conditions for specified coins/tokens potentially change.
🔹 Custom watchlist support for personalized monitoring (users can define a custom category containing a set of specific cryptocurrencies, i.e. own portfolio).
The screener presents data in a table format, using color-coded indicators to aid visual analysis. Detailed technical information is also provided. The assessments/trade signals provided by this indicator should be considered as one input among many when forming your trading strategy.
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What It Does
The Altcoins Screener is a cryptocurrency analysis tool that offers:
Data Display and Analysis (Technical/Social):
🔹 Technical Metrics
* Technical Raw Data : Displays raw values for a range of technical indicators, including RSI, Stochastic RSI, DMI/ADX, RVI, ATR, OBV, and Hull Moving Averages (including their recent trends and potential significance).
Detailed view of key technical indicators, for further analysis and evaluation:
* Technical Analysis (Summary) : Provides a summarized interpretation of technical conditions based on aggregated parameters:
* Price Action
* Trend
* Momentum
* Volatility
* Volume
Summarized view of confluences for potential long/short bias:
🔹 Social Metrics (LunarCrush) : Presents data from LunarCrush®, including Galaxy Score®, AltRank®, and Social Sentiment® (including their recent trends and potential significance).
Lunarcrush data for the top 10 coins for each crypto category:
🔹 PVSRA (Price Volume & Market Makers Activity) Candles : Shows special candles highlighting potential market maker activity and volume anomalies, helping identify possible manipulation zones (including imbalance zones, i.e. price areas that market makers may revisit)
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Key Features:
Automated trade signals (Long/Short) are generated based on algorithmic calculations and signal confidence levels across technical and social data points. These signals are intended to be used as one component of a broader trading strategy.
Custom sensitivity settings allow users to adjust the analysis timeframe (options: 1D, 2D, or 1W). Higher timeframes may provide a broader perspective, while the 2D setting is the default configuration.
Multi-category analysis covering a selection of approximately 300 crypto pairs across 9 predefined crypto categories.
Custom symbol selection: Users can define a custom list of up to 10 symbols for focused monitoring.
Automated Alerts to track potential trend changes across crypto categories (Long to Short to Neutral, or vice versa)
Visual Interface:
Organized table display with color-coded indicators to aid interpretation.
Clear and efficient format for scanning market information.
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Target Audience
🔹 The screener is designed for cryptocurrency traders who:
Need to efficiently monitor multiple USDT perpetual futures markets
Use technical analysis in their trading decisions
Want to track sector-wide movements across crypto categories
🔹 Suitable for different trading styles:
Scalpers requiring quick market assessment
Swing traders analyzing multi-day trends
Position traders monitoring longer-term setups
The color-coded interface makes it accessible for intermediate traders while providing detailed metrics for advanced users. A basic understanding of technical analysis and crypto trading is recommended.
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How It Works
The Altcoins Screener evaluates cryptocurrencies through a multi-layered analysis:
🔹 Core Analysis Components
Each parameter combines multiple indicators for comprehensive evaluation:
Price Action
EMA crossovers and momentum
Support/resistance zones
Candlestick patterns
Trend
Hull Moving Average system
DMI/ADX trend strength
Multi-timeframe confirmation
Momentum
RSI/Stochastic RSI readings
MACD convergence/divergence
Oscillator confirmations
Volatility
RVI/ATR measurements
Bollinger Bands behavior
Historical volatility trends
Volume
OBV trend analysis
Volume/price correlations
Volume profile assessment
🔹 Signal Generation Process
1. Real-time data collection across timeframes
2. Weighted indicator calculations
3. Parameter aggregation and analysis
4. Signal strength determination
5. Color-coding and alert generation
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How to Use
🔹 Initial Setup:
Add the indicator to a chart (use the 1D timeframe)
Select your preferred crypto category or create a custom list
Choose between Technical Analysis or Technical Metrics view
Set data sensitivity based on your trading style
🔹 Using the Technical Analysis View:
Monitor color-coded dots for quick market assessment
Green: bullish conditions
Red: bearish conditions
Gray: neutral conditions
Check the "Trade Signal" column for potential Long/Short entries signaled by confluences among technical and/or social data points
🔹 Using the Technical Metrics View:
Review detailed numerical values
Monitor slopes (↑↓ arrows) for the most recent trend direction of each data point
Watch for pivotal points (highlighted cells): these are data points that suggest potential trend reversals
Focus on the confluence of multiple indicators
The technical metrics view corroborates the conclusions shown in the Technical Analysis View, providing more details about some critical data points.
🔹 Alert Configuration:
Enable Technical Alerts for signal notifications (which coin/token seems most suited for Long or Short trades, and which coin/token is in a neutral/uncertain state for trading = "No Trade")
Configure alert conditions based on trading style
Set timeframe-appropriate sensitivity
Monitor alert messages for trade signals
Instructions on how to set alerts are provided in the script (enable "Signals Setup Instructions" in User Interface to get a step-by-step guide about setting up alerts)
Best Practices:
Confirm signals across multiple timeframes
Use appropriate sensitivity for your trading style
Monitor multiple categories for sector rotation
Combine signals with your trading strategy
Verify signals with price action confirmation and deep dive into the charts of your potential targets
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About the Settings
🔹 Crypto Category Selection
Layer 1 & Major: Top market cap coins (BTC, ETH, XRP,...), established protocols
Layer 2 & Scaling: ETH L2s, scaling solutions
DeFi & Lending: Decentralized finance protocols
Gaming & Metaverse: Gaming and virtual world tokens
AI & Data: Artificial intelligence and data projects
Exchange & Trading: Exchange tokens, trading protocols
NFT & Social: NFT platforms, social tokens
Memes & Community: Community-driven tokens
Others & Misc: Other categories
Custom Category: User-defined list (up to 10 symbols)
Data Type Options
Technical Analysis: Color-coded summary view
Technical Metrics: Detailed numerical values of some key technical data points
Sensitivity Settings
Higher: Shorter timeframe, more frequent signals
Default: Balanced timeframe, standard signals
Lower: Longer timeframe, stronger signals
Alert Settings
Technical Alerts: Trade signal notifications
Data Timeframe: Minimum 1D required
Theme: Dark/Light mode options
Note: All analysis is performed on USDT Perpetual Futures pairs from Binance
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FAQ
Q: Does the screener work on other exchanges besides Binance?
A: No, it's designed specifically for Binance USDT Perpetual Futures pairs. Binance offers the highest liquidity and trading volume in the crypto derivatives market, making it ideal for technical analysis. The extensive range of trading pairs and reliable data streams help ensure more accurate signals and analysis. Using a single high-liquidity exchange also helps avoid inconsistencies that could arise from aggregating data across multiple platforms with varying liquidity levels.
Q: What's the minimum timeframe required?
A: The screener requires a minimum 1D (daily) timeframe. This requirement ensures that the technical analysis has sufficient data points for reliable signal generation. Lower timeframes can produce more noise and false signals, while daily timeframes help filter out market noise and identify stronger trends.
Q: Why are some social metrics showing "NaN"?
A: "NaN" (Not a Number) appears when cryptocurrencies don't have associated LunarCrush data. This typically occurs with newer tokens or those with lower market caps. The technical analysis remains fully functional regardless of social metric availability, as these are complementary data points.
Q: How often are signals updated?
A: Signals update with each new candle on the selected timeframe (1D, 2D, or 1W). For example, on the default 2D setting, signals are recalculated every two days as new candles form. This helps reduce noise while maintaining timely analysis of market conditions.
Q: Can I add spot trading pairs?
A: No, the screener is optimized for Binance USDT perpetual futures pairs for data consistency and analysis purposes. While spot and perpetual prices typically align closely due to arbitrage, using a single data source (Binance) and contract type (USDT perpetual) ensures uniform data quality and analysis across all pairs. This standardization helps maintain reliable technical analysis and signal generation.
Q: How many coins can I add to my custom list?
A: Users can add up to 10 custom symbols to their watchlist. This limit is designed to maintain optimal performance while allowing focused monitoring of specific assets. The custom list complements the predefined categories that cover over 300 pairs.
Q: What determines signal confidence levels?
A: Signal confidence is calculated through a weighted algorithm that considers multiple factors: trend strength (Hull MA, DMI/ADX), momentum indicators (RSI, SRSI), volatility measurements (RVI, ATR, BB), volume analysis (OBV, volume trends), and price action patterns. Higher confidence levels indicate stronger alignment across these factors.
Q: Are signals guaranteed to work?
A: No. Signals are analytical tools based on historical and current market data, not guaranteed predictions. They should be used as one component of a comprehensive trading strategy that includes proper risk management, position sizing, and additional confirmation factors. Past performance does not guarantee future results.
Q: Why does the screener need higher timeframes?
A: Higher timeframes (1D minimum) provide several benefits: reduced market noise, more reliable technical signals, better trend identification, and lower likelihood of false signals. They also align better with institutional trading patterns and allow for a more thorough analysis of market conditions across multiple indicators.
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Conclusion
The Altcoins Screener is a comprehensive crypto market analysis tool that:
Scans 300+ cryptocurrencies across 9 sectors on a single chart
Combines technical indicators and social metrics for signal generation
Identifies potential trading opportunities through color-coded visuals
Saves time by eliminating the need to monitor multiple charts
The tool is suited for:
Market overview and sector rotation analysis
Quick assessment of market conditions
Technical and social sentiment tracking
Systematic trading approach with alerts
Use this screener with caution and as a complement to any other tool you use to define your trading strategy.
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Disclaimer
This indicator is for informational and educational purposes only:
Not financial advice: This indicator should not be considered investment advice.
No guarantee of accuracy: The indicator's calculations and signals are based on specific algorithms and data sources, but accuracy cannot be guaranteed. Market conditions can change rapidly.
Past performance is not predictive: Past performance of the indicator's signals or any specific asset is not indicative of future results.
Substantial risk of loss: Trading cryptocurrencies involves a substantial risk of loss. You can lose money trading these assets.
User responsibility: Users are solely responsible for their own trading decisions and should exercise caution.
Independent research required: Always conduct thorough independent research (DYOR) before making any trading decisions.
Technical analysis is one of many tools: Technical analysis, including the output of this indicator, is just one tool among many and should not be relied upon exclusively.
Risk management is essential: Use proper risk management techniques, including position sizing and stop-loss orders.
Comprehensive strategy: Use this tool as part of a comprehensive trading strategy, not as a standalone solution.
No liability for trading results: The Author assumes no responsibility or liability for any trading results or losses incurred as a result of using this indicator.
No TradingView affiliation: SwissAlgo is an independent entity and is not affiliated with or endorsed by TradingView.
LunarCrush data: The indicator utilizes publicly available data from LunarCrush. LunarCrush data and trademarks are the property of LunarCrush.
Consult a financial advisor: Consult with a qualified financial advisor before making any investment decisions.
By using this indicator, you acknowledge and agree to these terms. If you do not agree with these terms, please refrain from using this indicator.
WD Gann: Close Price X Bars Ago with Line or Candle PlotThis indicator is inspired by the principles of WD Gann, a legendary trader known for his groundbreaking methods in time and price analysis. It helps traders track the close price of a security from X bars ago, a technique that is often used to identify key price levels in relation to past price movements. This concept is essential for Gann’s market theories, which emphasize the relationship between time and price.
WD Gann’s analysis often revolved around specific numbers that he considered significant, many of which correspond to squared numbers (e.g., 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936). These numbers are believed to represent natural rhythms and cycles in the market. This indicator can help you explore how past price levels align with these significant numbers, potentially revealing key price zones that could act as support, resistance, or reversal points.
Key Features:
- Historical Close Price Calculation: The indicator calculates and displays the close price of a security from X bars ago (where X is customizable). This method aligns with Gann's focus on price relationships over specific time intervals, providing traders with valuable reference points to assess market conditions.
- Customizable Plot Type: You can choose between two plot types for visualizing the historical close price:
- Line Plot: A simple line that represents the close price from X bars ago, ideal for those who prefer a clean and continuous representation.
- Candle Plot: Displays the close price as a candlestick chart, providing a more detailed view with open, high, low, and close prices from X bars ago.
- Candle Color Coding: For the candle plot type, the script color-codes the candles. Green candles appear when the close price from X bars ago is higher than the open price, indicating bullish sentiment; red candles appear when the close is lower, indicating bearish sentiment. This color coding gives a quick visual cue to market sentiment.
- Customizable Number of Bars: You can adjust the number of bars (X) to look back, providing flexibility for analyzing different timeframes. Whether you're conducting short-term or long-term analysis, this input can be fine-tuned to suit your trading strategy.
- Gann Method Application: WD Gann's methods involved analyzing price action over specific time periods to predict future movements. This indicator offers traders a way to assess how the price of a security has behaved in the past in relation to a chosen time interval, a critical concept in Gann's theories.
How to Use:
1. Input Settings:
- Number of Bars (X): Choose the number of bars to look back (e.g., 100, 200, or any custom period).
- Plot Type: Select whether to display the data as a Line or Candles.
2. Interpretation:
- Using the Line plot, observe how the close price from X bars ago compares to the current market price.
- Using the Candles plot, analyze the full price action of the chosen bar from X bars ago, noting how the close price relates to the open, high, and low of that bar.
3. Gann Analysis: Integrate this indicator into your broader Gann-based analysis. By looking at past price levels and their relationship to significant squared numbers, traders can uncover potential key levels of support and resistance or even potential reversal points. The historical close price can act as a benchmark for predicting future market movements.
Suggestions on WD Gann's Emphasis in Trading:
WD Gann’s trading methods were rooted in several key principles that emphasized the relationship between time and price. These principles are vital to understanding how the "Close Price X Bars Ago" indicator fits into his overall analysis:
1. Time Cycles: Gann believed that markets move in cyclical patterns. By studying price levels from specific time intervals, traders can spot these cycles and predict future market behavior. This indicator allows you to see how the close price from X bars ago relates to current market conditions, helping to spot cyclical highs and lows.
2. Price and Time Squaring: A core concept in Gann’s theory is that certain price levels and time periods align, often marking significant reversal points. The squared numbers (e.g., 1, 4, 9, 16, 25, etc.) serve as potential key levels where price and time might "square" to create support or resistance. This indicator helps traders spot these historical price levels and their potential relevance to future price action.
3. Geometric Angles: Gann used angles (like the 45-degree angle) to predict market movements, with the belief that prices move at specific geometric angles over time. This indicator gives traders a reference for past price levels, which could align with key angles, helping traders predict future price movement based on Gann's geometry.
4. Numerology and Key Intervals: Gann paid particular attention to numbers that held significance, including squared numbers and numbers related to the Fibonacci sequence. This indicator allows traders to analyze price levels based on these key numbers, which can help in identifying potential turning points in the market.
5. Support and Resistance Levels: Gann’s methods often involved identifying levels of support and resistance based on past price action. By tracking the close price from X bars ago, traders can identify past support and resistance levels that may become significant again in future market conditions.
Perfect for:
Traders using WD Gann’s methods, such as Gann angles, time cycles, and price theory.
Analysts who focus on historical price levels to predict future price action.
Those who rely on numerology and geometric principles in their trading strategies.
By integrating this indicator into your trading strategy, you gain a powerful tool for analyzing market cycles and price movements in relation to key time intervals. The ability to track and compare the historical close price to significant numbers—like Gann’s squared numbers—can provide valuable insights into potential support, resistance, and reversal points.
Disclaimer:
This indicator is based on the methods and principles of WD Gann and is for educational purposes only. It is not intended as financial advice. Trading involves significant risk, and you should not trade with money that you cannot afford to lose. Past performance is not indicative of future results. The use of this indicator is at your own discretion and risk. Always do your own research and consider consulting a licensed financial advisor before making any investment decisions.
TOP 20 ALTCOIN INDEXIndicator Description
The "ALT20 INDEX" is a financial analysis tool designed to track the aggregate value of the top 20 cryptocurrencies by market capitalization and closing prices over specific periods. This indicator reflects changes in the combined value of these 20 ALTCOINs, providing an overview of trends in the cryptocurrency market.
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Purpose and Practical Applications
1. Tracking Top Cryptocurrencies:
- The indicator allows monitoring the value of the top 20 ALTCOINs, reflecting the general volatility of the cryptocurrency market.
- Helps investors focus on high-capitalization assets.
2. Performance Comparison:
- Serves as a tool to compare the performance of the ALT20 group against other assets like Bitcoin, Ethereum, or traditional financial indices.
3. Assessing Market Health:
- Enables evaluation of market trends, identifying growth or decline periods.
4. Practical Applications:
- Suitable for fund managers, long-term investors, or trend traders to make decisions based on the overall ALTCOIN market performance.
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How the Indicator Works
1. Selection of Top 20 ALTCOINs:
- Cryptocurrencies are selected based on their market capitalization at each rebalancing period.
2. Weight Allocation and Calculation:
- Weight: Determined by the market capitalization of each ALTCOIN relative to the total market capitalization of the top 20.
- Token Quantity: Calculated based on weight, total allocation points (e.g., 100 points for T1, 722.63 points for T2, etc.), and each ALTCOIN's closing price.
Formula: Token Quantity = Weight × Total Allocation Points/Closing Price
3. Periodic Rebalancing:
- Rebalancing frequency: Once a year.
- At each rebalancing period, the weights and token quantities are adjusted based on new market capitalization and prices.
4. Portfolio Value Calculation:
- The value of each ALTCOIN is calculated as:
Token Value = Closing Price × Token Quantity
- Index Total: ALT20 Index = 20∑'i=1'Token Value'i'
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Rebalancing Periods
T1 (2020-2021): Initial period, token quantities calculated based on weights and a total of 100 points.
T2 (2021-2022): Rebalanced with a total allocation of 722.63 points.
T3 (2022-2023): Total allocation of 252.26 points, reflecting portfolio adjustments based on new prices and market caps.
T4 (2023-2024): Total allocation of 261.43 points.
T5 (2024-Present): Total allocation of 437.42 points, updated to reflect the current market.
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Indicator Features
- Displays Index Value Over Time:
+ index_value_T1 to index_value_T5 represent the portfolio value during specific timeframes.
+ Values are calculated based on the daily closing prices of ALTCOINs.
- Visualization:
+ The index for each period is plotted on the chart, enabling easy observation of market trends over time.
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Practical Applications
- Portfolio Management:
+ The indicator helps track the performance of asset groups within the ALTCOIN portfolio.
- Integration into Trading Systems:
+ Used as a reference for automated or manual trading strategies.
- Market Analysis:
+ Assists analysts in evaluating cryptocurrency market movements based on the top 20 ALTCOINs.
Let me know if further optimization or additional information is needed! Thank!
Mini PortfolioThis code is a simple portfolio tracker calculates the Net Asset Value (NAV) of a portfolio consisting of up to 6 tickers based on Binance prices. Users can input how much of each cryptocurrency they "own," and the script then fetches the opening price of each coin.
After calculating the values of BTC, ETH, and SOL, the code sums these individual values to determine the portfolio's total value, or NAV. This NAV is then plotted on a graph, allowing users to see the overall value of their selected cryptocurrency portfolio over time.
In essence, this code allows users to track the hypothetical value of a small crypto portfolio and see how price fluctuations affect the total portfolio value. It’s a useful tool for visualizing potential portfolio performance without actual investments.
Higher Time Frame Support/Resistance [BigBeluga]The Higher Time Frame Support/Resistance indicator is a tool designed to display pivot points derived from higher timeframes on your current chart. These pivot points are calculated based on the highs and lows of price action in different timeframes, and the indicator draws horizontal lines to represent these levels. These lines act as potential support and resistance zones, giving traders key market levels that may influence future price movement.
Each pivot line is color-coded and labeled with its price value and the timeframe it originates from. This allows traders to clearly differentiate between the significance of the levels based on their timeframe. For example, weekly pivot levels may represent stronger, more long-term support and resistance, while hourly pivots offer more immediate, short-term levels to watch.
🔵 IDEA
The Higher Time Frame Support/Resistance indicator is designed to simplify the process of tracking key support and resistance levels across multiple timeframes. Pivot points, which represent turning points in the market, are essential for identifying areas where price might reverse or break out. By displaying these levels from higher timeframes directly on the current chart, traders can quickly identify and react to critical areas in the market without needing to switch between different timeframe charts.
The indicator labels each pivot point with the specific timeframe it comes from (e.g., 4H, 1D, 1W), making it easy for traders to assess the relative strength of each level. Stronger levels from higher timeframes are likely to act as more significant barriers or support zones, while lower timeframe levels can be used for more precise entries and exits.
🔵 KEY FEATURES
Pivot Levels from Multiple Timeframes:
The indicator calculates pivot highs and lows from various higher timeframes (e.g., 4H, 1D, 1W) and plots these levels on the current chart. These pivot points are represented by horizontal lines that extend across the chart, serving as potential support and resistance zones.
Color-Coded Support and Resistance Lines:
Each pivot level is color-coded based on its timeframe, helping traders quickly differentiate between short-term and long-term support and resistance. This visual aid simplifies the analysis and allows for a clearer understanding of key market levels.
Price Labels and Timeframe Information:
In addition to the pivot lines, the indicator displays labels at each level with the corresponding price and timeframe. For example, a label may show "D Pivot High" followed by the exact price. This helps traders understand the origin and significance of each line, allowing for more informed trading decisions.
Labels up and down mark highs and lows from higher timeframes:
Pivot Shadows for Enhanced Clarity:
The indicator can also draw shadow lines that represent the pivot points but with increased transparency. These shadows allow traders to keep track of previous pivots without cluttering the chart with too many solid lines. The width and transparency of these shadows can be customized in the settings.
🔵 HOW TO USE
🔵 CUSTOMIZATION
Timeframes and Pivot Length: Customize which higher timeframes (e.g., 4H, 1D, 1W) you want to display pivot levels from. Adjust the pivot length to control how sensitive the indicator is in detecting market highs and lows.
Line Style and Colors: Adjust the line style (solid, dashed, dotted) and colors for each timeframe to match your personal preference or chart theme. This customization helps in maintaining a clear and visually appealing chart.
Shadow Line Width and Transparency: Control the width and transparency of the shadow pivot lines to reduce chart clutter while still keeping track of key historical levels.
Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
Adaptive EMA with ATR and Standard Deviation [QuantAlgo]Adaptive EMA with ATR and Standard Deviation by QuantAlgo 📈✨
Introducing the Adaptive EMA with ATR and Standard Deviation , a comprehensive trend-following indicator designed to combine the smoothness of an Exponential Moving Average (EMA) with the volatility adjustments of Average True Range (ATR) and Standard Deviation. This synergy allows traders and investors to better identify market trends while accounting for volatility, delivering clearer signals in both trending and volatile market conditions. This indicator is suitable for traders and investors seeking to balance trend detection and volatility management, offering a robust and adaptable approach across various asset classes and timeframes.
💫 Core Concept and Innovation
The Adaptive EMA with ATR and Standard Deviation brings together the trend-smoothing properties of the EMA and the volatility sensitivity of ATR and Standard Deviation. By using the EMA to track price movements over time, the indicator smooths out minor fluctuations while still providing valuable insights into overall market direction. However, market volatility can sometimes distort simple moving averages, so the ATR and Standard Deviation components dynamically adjust the trend signals, offering more nuanced insights into trend strength and reversals. This combination equips traders with a powerful tool to navigate unpredictable markets while minimizing false signals.
📊 Technical Breakdown and Calculations
The Adaptive EMA with ATR and Standard Deviation relies on three key technical components:
1. Exponential Moving Average (EMA): The EMA forms the base of the trend detection. Unlike a Simple Moving Average (SMA), the EMA gives more weight to recent price changes, allowing it to react more quickly to new data. Users can adjust the length of the EMA to make it more or less responsive to price movements.
2. Standard Deviation Bands: These bands are calculated from the standard deviation of the EMA and represent dynamic volatility thresholds. The upper and lower bands expand or contract based on recent price volatility, providing more accurate signals in both calm and volatile markets.
3. ATR-Based Volatility Filter: The Average True Range (ATR) is used to measure market volatility over a user-defined period. It helps refine the trend signals by filtering out false positives caused by minor price swings. The ATR filter ensures that the indicator only signals significant market movements.
⚙️ Step-by-Step Calculation:
1. EMA Calculation: First, the indicator calculates the EMA over a specified period based on the chosen price source (e.g., close, high, low).
2. Standard Deviation Bands: Then, it computes the standard deviation of the EMA and applies a multiplier to create upper and lower bands around the EMA. These bands adjust dynamically with the level of market volatility.
3. ATR Filtering: In addition to the standard deviation bands, the ATR is applied as a secondary filter to help refine the trend signals. This step helps eliminate signals generated by short-term price spikes or corrections, ensuring that the signals are more reliable.
4. Trend Detection: When the price crosses above the upper band, a bullish trend is identified, while a move below the lower band signals a bearish trend. The system accounts for both the standard deviation and ATR bands to generate these signals.
✅ Customizable Inputs and Features
The Adaptive EMA with ATR and Standard Deviation provides a range of customizable options to fit various trading/investing styles:
📈 Trend Settings:
1. Price Source: Choose the price type (e.g., close, high, low) to base the EMA calculation on, influencing how the trend is tracked.
2. EMA Length: Adjust the length to control how quickly the EMA reacts to price changes. A shorter length provides a more responsive EMA, while a longer period smooths out short-term fluctuations.
🌊 Volatility Controls:
1. Standard Deviation Multiplier: This parameter controls the sensitivity of the trend detection by adjusting the distance between the upper and lower bands from the EMA.
2. TR Length and Multiplier: Fine-tune the ATR settings to control how volatility is filtered, adjusting the indicator’s responsiveness during high or low volatility phases.
🎨 Visualization and Alerts:
1. Bar Coloring: Select different colors for uptrends and downtrends, providing a clear visual cue when trends change.
2. Alerts: Set up alerts to notify you when the price crosses the upper or lower bands, signaling a potential long or short trend shift. Alerts can help you stay informed without constant chart monitoring.
📈 Practical Applications
The Adaptive EMA with ATR and Standard Deviation is ideal for traders and investors looking to balance trend-following strategies with volatility management. Key uses include:
Detecting Trend Reversals: The dynamic bands help identify when the market shifts direction, providing clear signals when a trend reversal is likely.
Filtering Market Noise: By applying both Standard Deviation and ATR filtering, the indicator helps reduce false signals during periods of heightened volatility.
Volatility-Based Risk Management: The adaptability of the bands ensures that traders can manage risk more effectively by responding to shifts in volatility while keeping focus on long-term trends.
⭐️ Comprehensive Summary
The Adaptive EMA with ATR and Standard Deviation is a highly customizable indicator that provides traders with clearer signals for trend detection and volatility management. By dynamically adjusting its calculations based on market conditions, it offers a powerful tool for navigating both trending and volatile markets. Whether you're looking to detect early trend reversals or avoid false signals during periods of high volatility, this indicator gives you the flexibility and accuracy to improve your trading and investing strategies.
Note: The Adaptive EMA with ATR and Standard Deviation is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Price & Volume Breakout Fibonacci Probability [TradeDots]📝 OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
🧮 CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
📊 EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
⚙️ SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
📈 HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
OHLC, Sessions & Key Levels [Orderflowing]Multi-Timeframe (+) OHLC, Sessions & Key Levels | Custom-Timeframe OHLC | Sessions Analysis | Market Key Levels
Built using Pine Script V5.
Introduction
The OHLC, Sessions & Key Levels Indicator is a tool designed for traders who want to integrate Multi-Timeframe (MTF) OHLC Data, Sessions Analysis, and Key Market Levels into their trading system.
This Indicator can help traders by automatically marking the OHLC, Sessions & Key Levels directly on the price chart, saving time furthermore potentially allowing for better judgement in their trading and risk management process.
Innovation and Inspiration
The Indicator draws from multiple concepts;
The OHLC levels across different timeframes, session-based analysis, and plotting potentially important and pivotal market levels.
Concept Inspiration from ICT-Traders / Market Maker Model Traders.
Use of Open-Source Code
Specific parts of this Indicator's code have been inspired by & further developed from publicly available code originally developed for the MetaTrader platform.
All such integrations have been wired to work within the TradingView environment, specifically using Pine Script Version 5.
Elements have been made to benefit the overall functionality, the code logic, to make sure it offers unique value to TradingView's users.
Core Features
OHLC MTF Analysis
Foundation
This component allows traders to track the Open, High, Low, and Close levels across different timeframes, ranging from intraday periods to yearly data.
Customization
Traders can adjust the bar offset, width, and colors of the OHLC bars, as well as display options. Option to highlight the Open/Close with labels and the High/Low with marks.
Application
The OHLC MTF component gives traders a clear view of important price levels, which can serve as support, resistance, or potential entry/exit points.
Main Trading Sessions & Custom Sessions
Starting Point
The Sessions component relies on the user-inputted key market sessions, defaults include New York, London, Asia, and optionally Sydney. Session Defaults to UTC.
Please Note: Adjust Time Zone in TradingView's Desktop App or Web Interface to use the sessions in correct local time.
Customization
Traders can adjust session names, session times, time zone, visibility, session colors, and session-specific high and low markers.
This allows us to visualize price movements during these selected periods.
Application
By highlighting different trading sessions, traders can potentially better time their trades, understanding when significant price movements usually occur. This can potentially be used to try and find patterns in a time-based method.
Key Levels
Customization
Traders can choose which key levels to display and adjust the visual style of these levels, including line width, style, and color.
Application
The Key Levels feature can help traders identify support and resistance levels that can serve as potential entry or exit points. Can be useful in market structure analysis by marking significant price levels based on different timeframes.
Designed for multi-timeframe analysis, allowing traders to track OHLC levels, session ranges, and key market levels.
It’s highly customizable, making it suitable across trading styles and charting setups, whether scalping, day trading, swing trading or longer term investing.
Multi-Timeframe (MTF) OHLC
Can be plotted as a Candlestick or Bar-Chart or Both
These can help traders keep an eye on price levels across multiple timeframes while allowing the actual chart to be on another timeframe than the displayed OHLC.
Example - OHLC on the Weekly Candle/Bar - Chart 4 Hourly Candles
While being on lower timeframes, the trader can keep an eye on how the OHLC candle is developing. ICT-Traders find the Daily (Default Setting) OHLC useful in analysis.
It can be customized to any timeframe the trader wishes to use.
Inspired by ICT-Traders / Market Maker Model Traders and Top-Down Analysis Style.
Combined with Session Analysis to view into the price behavior during specific trading sessions, could potentially be very useful for finding trading setups.
OHLC Levels
Creates lines based on user input - Can potentially be important reference points for trade setups / invalidation / confirmation, levels could be used as the HTF Origin.
Conclusion
The OHLC MTF, Sessions & Key Levels Indicator is a tool that combines multiple market analysis concepts into a single unique script. It offers another view of the market's behavior by combining OHLC data from a different timeframe, main trading sessions, and key levels.
Why Invite-Only?
The OHLC, Sessions & Key Levels Indicator is offered as invite-only because you receive a quality and customizable tool that combines multiple functions into one convenient script.
This Indicator stands out by being a complete and optimized trading tool based on three desirable components.
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Multi-Timeframe OHLC Analysis, Sessions Tracking & Key Levels
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Into One Customizable Indicator.
Disclaimer
While the Indicator offers a view of the OHLC price action on multiple timeframes, key levels & trading sessions, traders should not solely rely on it for trading decisions. As with all trading tools, it should be used as part of a complete trading strategy.
Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ StocksThis script is designed to create a TradingView indicator called **"Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ Stocks."** The purpose of this indicator is to track and visualize the cumulative price delta (the change in price from one period to the next) for the top five NASDAQ stocks: Apple Inc. (AAPL), Microsoft Corporation (MSFT), Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), and Meta Platforms Inc. (FB).
### Key Features of the Script:
1. **Ticker Selection**:
- The script focuses on the top five NASDAQ stocks by automatically setting their tickers.
2. **Price Data Retrieval**:
- It fetches the closing prices for each of these stocks using the `request.security` function for the current timeframe.
3. **Delta Calculation**:
- The script calculates the delta for each stock, which is simply the difference between the current closing price and the previous closing price.
4. **Cumulative Delta Calculation**:
- It calculates the cumulative delta for each stock by adding the current delta to the previous cumulative delta. This helps track the total change in price over time.
5. **Summing and Smoothing**:
- The cumulative deltas for all five stocks are summed together.
- The script then applies an Exponential Moving Average (EMA) with a period of 5 to smooth the summed cumulative delta, making the indicator less sensitive to short-term fluctuations.
6. **Normalization**:
- To ensure the cumulative delta is easy to interpret, the script normalizes it to a range of 0 to 1. This is done by tracking the minimum and maximum values of the smoothed cumulative delta and scaling the data accordingly.
7. **Visualization**:
- The normalized cumulative delta is plotted as a smooth line, allowing users to see the overall trend of the cumulative price changes for the top five NASDAQ stocks.
- A horizontal line is added at 0.5, serving as a midline reference, which can help traders quickly assess whether the normalized cumulative delta is above or below its midpoint.
### Usage:
This indicator is particularly useful for traders and investors who want to monitor the aggregated price movements of the top NASDAQ stocks, providing a high-level view of market sentiment and trends. By smoothing and normalizing the data, it offers a clear and concise visualization that can be used to identify potential market turning points or confirm ongoing trends.
Red Candles with Green Precedent
**Title**: Red Candles with Green Precedent Indicator
**Description**:
This TradingView indicator is designed to help traders identify potential reversal or continuation patterns based on the appearance of consecutive red candles following a green candle. The script marks a region starting from a green candle that precedes at least four consecutive red candles, extending a box forward for a predefined number of bars to analyze the continuation of the trend.
**Key Features**:
- **Consecutive Red Candles Detection**: The indicator counts consecutive red candles that close lower than they open.
- **Initial Green Candle Identification**: Identifies the last green candle before a series of red candles begins. This green candle must close higher than it opens.
- **Visual Box Extension**: Creates a visual box from the open to the high of the green candle and extends it forward to highlight the period of interest.
- **Dynamic Box Termination**: Optionally terminates the box early if a significant green candle appears within the extension period, suggesting a potential reversal.
**Usage**:
1. **Setup**: Apply the indicator to any chart in TradingView. Adjust the number of consecutive red candles to track based on your trading strategy.
2. **Interpretation**: A visual green box will appear when the criteria are met. This box helps focus on the price action following a potentially significant green candle. Traders should watch for price actions within and around the box to make informed decisions.
3. **Alerts**: Consider setting alerts for when a new box is created or when a significant green candle forms that might terminate the box early, indicating potential market movements.
**Suitable for**: This indicator is suitable for traders looking for visual cues about potential bearish exhaustion or the setup for a bullish reversal, particularly in volatile markets.
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Feel free to customize the description and features according to any additional details or personal insights you might want to include based on your trading experience or the specific behaviors of the markets you track.
**Disclaimer**:
This script is provided as a tool for trading analysis and is not intended to be used as the sole basis for any trading decisions. While this indicator aims to identify potential trading opportunities, its effectiveness can depend on market conditions and individual trading strategies. Users should conduct their own research and consult with professional advisors before making any investment decisions. The creator of this script assumes no responsibility for any potential financial losses incurred from using this indicator. Trading in financial markets involves risk, and it is possible to lose more than your initial investment.
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Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
LevelUp^ Trend Follower All-In-OneLevelUp is an all-in-one collection of the most popular trend following tools merged into one indicator. LevelUp automates many aspects of technical analysis to find and highlight chart patterns and signals based on the principles of William O'Neil, Stan Weinstein, Jesse Livermore and other well-known trend followers.
The 10-EMA, 21-EMA and 50-SMA are foundational in LevelUp. LevelUp uses the term moving average alignment to refer to patterns that meet your specific requirements as it relates to moving averages and their relationship to price and one another. For example, you can request the start of MA alignment begin when the low is > 21-EMA, the 21-EMA is > 50-SMA and the 50-SMA is trending up.
LevelUp includes indicators for intraday, daily and weekly timeframes.
Key Features:
Daily Timeframe:
▪ Configure moving average alignment and preferred price action.
▪ Custom RS Line:
▪ Symbol overlays showing new RS highs.
▪ Custom moving average with optional cloud.
▪ View 10-week SMA on daily chart.
▪ Set exit criteria based on moving averages and % below entry.
▪ Stats table to simplify calculating entry/exit points.
▪ Signals table to quickly view if stock is trending up.
▪ Power trend tools and analysis.
Daily & Weekly Timeframe:
▪ Flat base detection with custom configuration.
▪ Consolidation detection with custom configuration.
▪ Highlight lower lows and lower closes (pullbacks).
▪ Highlight 52-week highs.
Weekly Timeframe:
▪ Customizable tight closes.
▪ Customizable up weeks.
Intraday Timeframe:
▪ View daily 10-EMA, 21-EMA and 50-SMA.
▪ 1-day and 2-day AVWAP.
▪ 5-day moving average.
All Timeframes:
▪ Marked highs/lows with lines showing support/resistance.
▪ Custom moving averages.
Daily Chart Examples
The following charts show a range of examples on customization and features in LevelUp when viewing a daily chart.
Weekly Chart Examples
Weekly charts are helpful for identifying longer-term trends and patterns. Trend followers often limit the number of indicators and signals on a weekly timeframe, making for a cleaner chart with less noise.
Intraday Chart Examples
Daily 10-EMA, 21-EMA and 50-SMA on an intraday chart.
AVWAP and marked highs/lows.
RS Line ~ Relative Strength
The RS Line compares a stock's performance to the S&P 500 index. A rising RS Line means the stock is outperforming the overall market. Another important signal is when the RS Line reaches a new high before price. When this occurs, it indicates strong demand for the stock and may precede a significant price increase as buyers accumulate shares. Both signals are customizable within LevelUp providing multiple visual cues when the required conditions are met.
LevelUp also adds a few unique visuals as it relates to the typical RS Line. Included are options to show symbols on the RS line that represent RS Line new high and RS Line new high before price. This provides an at-a-glance view of the trend. Additionally, LevelUp allows for custom moving averages to be applied to the RS Line as well as an optional cloud to help identify support/resistance levels.
Power Trends
When a power trend is active, there is a stronger than usual uptrend underway. The concept of a power trend was created by Investor's Business Daily (IBD) based on extensive backtesting and historical analysis.
A power trend by definition uses a major index, such as the Nasdaq Composite (IXIC), as the data source for determining a power trend's state, either off or on. The LevelUp indicator builds upon this concept by allowing the current active chart symbol to be the data source for the power trend.
What Starts A Power Trend:
▪ Low is above the 21-day EMA for at least 10 days.
▪ 21-day EMA is above the 50-day SMA for at least five days.
▪ 50-day SMA is in an uptrend.
▪ Close up for the day.
What Ends A Power Trend:
▪ 21-day EMA crosses under 50-day SMA and the close is below prior day close.
▪ Close below the 50-day SMA and low is 10% below recent high.
Important Note: The power trend as created by IBD uses the daily 21-EMA and 50-SMA. Hence, the power trend is only shown when on the daily timeframe.
AVWAP - Anchored VWAP
The Anchored Volume Weighted Average Price (AVWAP) , created by Brian Shannon, is used to assess the average price at which an asset has traded since a specific time, event or milestone. This could be the beginning of a trading day, the release of important news, or any other event deemed significant. By anchoring the VWAP to a specific point in time, it helps market participants analyze how prices have evolved relative to that anchor.
If a stock is above a rising AVWAP, buyers are in control, while a declining AVWAP indicates sellers are in control. By analyzing AVWAP, traders can make informed decisions on timing entries, managing losses and profits, or deciding to stay on the sidelines during periods of market indecision.
Tight Weeks And Up Weeks
William O'Neil primarily focused on weekly charts. Two common patterns he looked for were tight weeks and up weeks.
Tight weeks occur when there are small variations in price from one week to the next. This indicates a lack of supply and accumulation by institutions. You can configure the minimum number of weeks and the maximum % change in price from week to week.
Up weeks are defined as multiple weeks where each close is higher than the previous week. This pattern is often a signal of institutional buying. At a minimum, O'Neil looked for three weeks of upward price action. You can configure the minimum number of up weeks required.
Flat Base
A flat based is relatively tight price action within a range. A flat base takes 5+ weeks (25+ days) to form. Although flat bases are often found after a more significant advance in price, this isn't always the case. With that in mind, LevelUp does not currently have requirements for a prior uptrend while scanning for flat bases.
In a flat base, price declines should be no more than 15% from intraday peak to trough. This is an important distinction, as with a consolidation (see below) the maximum depth is based on the high of first bar that started the base.
Default Requirements:
▪ Daily minimum length: 25 days.
▪ Weekly minimum length: 5 weeks.
▪ Depth maximum: 15% (daily or weekly).
Consolidation
A consolidation differs from a flat base in that the former can be much deeper and last longer. In addition, the fluctuations in price of a flat base are often tighter than a consolidation.
Unlike a flat base, the maximum depth is calculated from the high at the start of the consolidation. The minimum length and maximum depth can be customized for all flat base and consolidation patterns.
Default Requirements:
▪ Daily minimum length: 30 days.
▪ Weekly minimum length: 6 weeks.
▪ Depth maximum: 35% (daily or weekly).
Pullback In Price And Potential Bounce
A pullback occurs when the price declines after an initial advance. This is normal price action as prior support levels are tested. Pullbacks also act as a way to shakeout weak holders before the primary trend resumes.
With LevelUp you specify the type of pullback to track: lower lows, lower closes or both. You also set the minimum number of bars required. Different values can be set for daily and weekly charts. Once your requirements are met, LevelUp will highlight the bar after the pullback is complete. This is often a potential entry/add point.
52-Week Highs
A 52-week high refers to the highest closing price within the past 52 weeks. Trend followers often use the 52-week high as a signal to identify assets with upward momentum, considering it as an indication of a potential trend continuation. This approach assumes that assets that have reached a 52-week high are more likely to experience further price appreciation.
52-week highs can be shown on both weekly and daily charts. You can set the location where the 52-week high symbol is shown: above the bar, below the bar, at the top of the chart or at the bottom of the chart.
Marked Highs And Lows
Marked highs/lows, often referred to as pivot highs/lows, can be helpful to find areas of potential support and resistance. As defined by William O'Neil, on a daily chart, a marked high is the highest high going back nine bars and forward nine bars. The number of days forward/backward is referred to as the period. The same concept applies to finding marked lows.
One benefit of LevelUp marked highs/lows is that you can customize the high and low periods on all timeframes.
There is an additional option when viewing marked highs/lows to see where a breakout occurs. The highlight is shown if the current bar high is above the most recent pivot high.
Comparing Stock Performance
With two or more copies of LevelUp installed, you can configure different settings and compare and contrast how indicators and signals perform relative to one another.
This is a great way to come up with your own custom layout for each timeframe, tailored to your preferences and trading style.
Stats And The Signals Table
The stats and signal tables can be very helpful to see price information and patterns at a glance. For example, you can quickly determine potential stoploss placement based on the distance to/from a moving average. The signals tables show the status of several key trend indicators, including 52-week highs, RS Line new high and RS Line new high before price.
Managing Long Term Trends
Depending on your trading style, there are many ways to take advantage of long term trends. For example, the chart that follows show how an uptrend can be a profitable trade whether holding for the duration or taking shorter term trades along the way.
ottlibLibrary "ottlib"
█ OVERVIEW
This library contains functions for the calculation of the OTT (Optimized Trend Tracker) and its variants, originally created by Anıl Özekşi (Anil_Ozeksi). Special thanks to him for the concept and to Kıvanç Özbilgiç (KivancOzbilgic) and dg_factor (dg_factor) for adapting them to Pine Script.
█ WHAT IS "OTT"
The OTT (Optimized Trend Tracker) is a highly customizable and very effective trend-following indicator that relies on moving averages and a trailing stop at its core. Moving averages help reduce noise by smoothing out sudden price movements in the markets, while trailing stops assist in detecting trend reversals with precision. Initially developed as a noise-free trailing stop, the current variants of OTT range from rapid trend reversal detection to long-term trend confirmation, thanks to its extensive customizability.
It's well-known variants are:
OTT (Optimized Trend Tracker).
TOTT (Twin OTT).
OTT Channels.
RISOTTO (RSI OTT).
SOTT (Stochastic OTT).
HOTT & LOTT (Highest & Lowest OTT)
ROTT (Relative OTT)
FT (Original name is Fırsatçı Trend in Turkish which translates to Opportunist Trend)
█ LIBRARY FEATURES
This library has been prepared in accordance with the style, coding, and annotation standards of Pine Script version 5. As a result, explanations and examples will appear when users hover over functions or enter function parameters in the editor.
█ USAGE
Usage of this library is very simple. Just import it to your script with the code below and use its functions.
import ismailcarlik/ottlib/1 as ottlib
█ FUNCTIONS
• f_vidya(source, length, cmoLength)
Short Definition: Chande's Variable Index Dynamic Average (VIDYA).
Details: This function computes Chande's Variable Index Dynamic Average (VIDYA), which serves as the original moving average for OTT. The 'length' parameter determines the number of bars used to calculate the average of the given source. Lower values result in less smoothing of prices, while higher values lead to greater smoothing. While primarily used internally in this library, it has been made available for users who wish to utilize it as a moving average or use in custom OTT implementations.
Parameters:
source (float) : (series float) Series of values to process.
length (simple int) : (simple int) Number of bars to lookback.
cmoLength (simple int) : (simple int) Number of bars to lookback for calculating CMO. Default value is `9`.
Returns: (float) Calculated average of `source` for `length` bars back.
Example:
vidyaValue = ottlib.f_vidya(source = close, length = 20)
plot(vidyaValue, color = color.blue)
• f_mostTrail(source, multiplier)
Short Definition: Calculates trailing stop value.
Details: This function calculates the trailing stop value for a given source and the percentage. The 'multiplier' parameter defines the percentage of the trailing stop. Lower values are beneficial for catching short-term reversals, while higher values aid in identifying long-term trends. Although only used once internally in this library, it has been made available for users who wish to utilize it as a traditional trailing stop or use in custom OTT implementations.
Parameters:
source (float) : (series int/float) Series of values to process.
multiplier (simple float) : (simple float) Percent of trailing stop.
Returns: (float) Calculated value of trailing stop.
Example:
emaValue = ta.ema(source = close, length = 14)
mostValue = ottlib.f_mostTrail(source = emaValue, multiplier = 2.0)
plot(mostValue, color = emaValue >= mostValue ? color.green : color.red)
• f_ottTrail(source, multiplier)
Short Definition: Calculates OTT-specific trailing stop value.
Details: This function calculates the trailing stop value for a given source in the manner used in OTT. Unlike a traditional trailing stop, this function modifies the traditional trailing stop value from two bars prior by adjusting it further with half the specified percentage. The 'multiplier' parameter defines the percentage of the trailing stop. Lower values are beneficial for catching short-term reversals, while higher values aid in identifying long-term trends. Although primarily used internally in this library, it has been made available for users who wish to utilize it as a trailing stop or use in custom OTT implementations.
Parameters:
source (float) : (series int/float) Series of values to process.
multiplier (simple float) : (simple float) Percent of trailing stop.
Returns: (float) Calculated value of OTT-specific trailing stop.
Example:
vidyaValue = ottlib.f_vidya(source = close, length = 20)
ottValue = ottlib.f_ottTrail(source = vidyaValue, multiplier = 1.5)
plot(ottValue, color = vidyaValue >= ottValue ? color.green : color.red)
• ott(source, length, multiplier)
Short Definition: Calculates OTT (Optimized Trend Tracker).
Details: The OTT consists of two lines. The first, known as the "Support Line", is the VIDYA of the given source. The second, called the "OTT Line", is the trailing stop based on the Support Line. The market is considered to be in an uptrend when the Support Line is above the OTT Line, and in a downtrend when it is below.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
length (simple int) : (simple int) Number of bars to lookback. Default value is `2`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `1.4`.
Returns: ( [ float, float ]) Tuple of `supportLine` and `ottLine`.
Example:
= ottlib.ott(source = close, length = 2, multiplier = 1.4)
longCondition = ta.crossover(supportLine, ottLine)
shortCondition = ta.crossunder(supportLine, ottLine)
• tott(source, length, multiplier, bandsMultiplier)
Short Definition: Calculates TOTT (Twin OTT).
Details: TOTT consists of three lines: the "Support Line," which is the VIDYA of the given source; the "Upper Line," a trailing stop of the Support Line adjusted with an added multiplier; and the "Lower Line," another trailing stop of the Support Line, adjusted with a reduced multiplier. The market is considered in an uptrend if the Support Line is above the Upper Line and in a downtrend if it is below the Lower Line.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
length (simple int) : (simple int) Number of bars to lookback. Default value is `40`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `0.6`.
bandsMultiplier (simple float) : Multiplier for bands. Default value is `0.0006`.
Returns: ( [ float, float, float ]) Tuple of `supportLine`, `upperLine` and `lowerLine`.
Example:
= ottlib.tott(source = close, length = 40, multiplier = 0.6, bandsMultiplier = 0.0006)
longCondition = ta.crossover(supportLine, upperLine)
shortCondition = ta.crossunder(supportLine, lowerLine)
• ott_channel(source, length, multiplier, ulMultiplier, llMultiplier)
Short Definition: Calculates OTT Channels.
Details: OTT Channels comprise nine lines. The central line, known as the "Mid Line," is the OTT of the given source's VIDYA. The remaining lines are positioned above and below the Mid Line, shifted by specified multipliers.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`
length (simple int) : (simple int) Number of bars to lookback. Default value is `2`
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `1.4`
ulMultiplier (simple float) : (simple float) Multiplier for upper line. Default value is `0.01`
llMultiplier (simple float) : (simple float) Multiplier for lower line. Default value is `0.01`
Returns: ( [ float, float, float, float, float, float, float, float, float ]) Tuple of `ul4`, `ul3`, `ul2`, `ul1`, `midLine`, `ll1`, `ll2`, `ll3`, `ll4`.
Example:
= ottlib.ott_channel(source = close, length = 2, multiplier = 1.4, ulMultiplier = 0.01, llMultiplier = 0.01)
• risotto(source, length, rsiLength, multiplier)
Short Definition: Calculates RISOTTO (RSI OTT).
Details: RISOTTO comprised of two lines: the "Support Line," which is the VIDYA of the given source's RSI value, calculated based on the length parameter, and the "RISOTTO Line," a trailing stop of the Support Line. The market is considered in an uptrend when the Support Line is above the RISOTTO Line, and in a downtrend if it is below.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
length (simple int) : (simple int) Number of bars to lookback. Default value is `50`.
rsiLength (simple int) : (simple int) Number of bars used for RSI calculation. Default value is `100`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `0.2`.
Returns: ( [ float, float ]) Tuple of `supportLine` and `risottoLine`.
Example:
= ottlib.risotto(source = close, length = 50, rsiLength = 100, multiplier = 0.2)
longCondition = ta.crossover(supportLine, risottoLine)
shortCondition = ta.crossunder(supportLine, risottoLine)
• sott(source, kLength, dLength, multiplier)
Short Definition: Calculates SOTT (Stochastic OTT).
Details: SOTT is comprised of two lines: the "Support Line," which is the VIDYA of the given source's Stochastic value, based on the %K and %D lengths, and the "SOTT Line," serving as the trailing stop of the Support Line. The market is considered in an uptrend when the Support Line is above the SOTT Line, and in a downtrend when it is below.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
kLength (simple int) : (simple int) Stochastic %K length. Default value is `500`.
dLength (simple int) : (simple int) Stochastic %D length. Default value is `200`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `0.5`.
Returns: ( [ float, float ]) Tuple of `supportLine` and `sottLine`.
Example:
= ottlib.sott(source = close, kLength = 500, dLength = 200, multiplier = 0.5)
longCondition = ta.crossover(supportLine, sottLine)
shortCondition = ta.crossunder(supportLine, sottLine)
• hottlott(length, multiplier)
Short Definition: Calculates HOTT & LOTT (Highest & Lowest OTT).
Details: HOTT & LOTT are composed of two lines: the "HOTT Line", which is the OTT of the highest price's VIDYA, and the "LOTT Line", the OTT of the lowest price's VIDYA. A high price surpassing the HOTT Line can be considered a long signal, while a low price dropping below the LOTT Line may indicate a short signal.
Parameters:
length (simple int) : (simple int) Number of bars to lookback. Default value is `20`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `0.6`.
Returns: ( [ float, float ]) Tuple of `hottLine` and `lottLine`.
Example:
= ottlib.hottlott(length = 20, multiplier = 0.6)
longCondition = ta.crossover(high, hottLine)
shortCondition = ta.crossunder(low, lottLine)
• rott(source, length, multiplier)
Short Definition: Calculates ROTT (Relative OTT).
Details: ROTT comprises two lines: the "Support Line", which is the VIDYA of the given source, and the "ROTT Line", the OTT of the Support Line's VIDYA. The market is considered in an uptrend if the Support Line is above the ROTT Line, and in a downtrend if it is below. ROTT is similar to OTT, but the key difference is that the ROTT Line is derived from the VIDYA of two bars of Support Line, not directly from it.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
length (simple int) : (simple int) Number of bars to lookback. Default value is `200`.
multiplier (simple float) : (simple float) Percent of trailing stop. Default value is `0.1`.
Returns: ( [ float, float ]) Tuple of `supportLine` and `rottLine`.
Example:
= ottlib.rott(source = close, length = 200, multiplier = 0.1)
isUpTrend = supportLine > rottLine
isDownTrend = supportLine < rottLine
• ft(source, length, majorMultiplier, minorMultiplier)
Short Definition: Calculates Fırsatçı Trend (Opportunist Trend).
Details: FT is comprised of two lines: the "Support Line", which is the VIDYA of the given source, and the "FT Line", a trailing stop of the Support Line calculated using both minor and major trend values. The market is considered in an uptrend when the Support Line is above the FT Line, and in a downtrend when it is below.
Parameters:
source (float) : (series float) Series of values to process. Default value is `close`.
length (simple int) : (simple int) Number of bars to lookback. Default value is `30`.
majorMultiplier (simple float) : (simple float) Percent of major trend. Default value is `3.6`.
minorMultiplier (simple float) : (simple float) Percent of minor trend. Default value is `1.8`.
Returns: ( [ float, float ]) Tuple of `supportLine` and `ftLine`.
Example:
= ottlib.ft(source = close, length = 30, majorMultiplier = 3.6, minorMultiplier = 1.8)
longCondition = ta.crossover(supportLine, ftLine)
shortCondition = ta.crossunder(supportLine, ftLine)
█ CUSTOM OTT CREATION
Users can create custom OTT implementations using f_ottTrail function in this library. The example code which uses EMA of 7 period as moving average and calculates OTT based of it is below.
Source Code:
//@version=5
indicator("Custom OTT", shorttitle = "COTT", overlay = true)
import ismailcarlik/ottlib/1 as ottlib
src = input.source(close, title = "Source")
length = input.int(7, title = "Length", minval = 1)
multiplier = input.float(2.0, title = "Multiplier", minval = 0.1)
support = ta.ema(source = src, length = length)
ott = ottlib.f_ottTrail(source = support, multiplier = multiplier)
pSupport = plot(support, title = "Moving Average Line (Support)", color = color.blue)
pOtt = plot(ott, title = "Custom OTT Line", color = color.orange)
fillColor = support >= ott ? color.new(color.green, 60) : color.new(color.red, 60)
fill(pSupport, pOtt, color = fillColor, title = "Direction")
Result:
█ DISCLAIMER
Trading is risky and most of the day traders lose money eventually. This library and its functions are only for educational purposes and should not be construed as financial advice. Past performances does not guarantee future results.
