Advanced Physics Financial Indicator Each component represents a scientific theory and is applied to the price data in a way that reflects key principles from that theory.
Detailed Explanation
1. Fractal Geometry - High/Low Signal
Concept: Fractal geometry studies self-similar patterns that repeat at different scales. In markets, fractals can be used to detect recurring patterns or turning points.
Implementation: The script detects pivot highs and lows using ta.pivothigh and ta.pivotlow, representing local turning points in price. The fractalSignal is set to 1 for a pivot high, -1 for a pivot low, and 0 if there is no signal. This logic reflects the cyclical, self-similar nature of price movements.
Practical Use: This signal is useful for identifying local tops and bottoms, allowing traders to spot potential reversals or consolidation points where fractal patterns emerge.
2. Quantum Mechanics - Probabilistic Monte Carlo Simulation
Concept: Quantum mechanics introduces uncertainty and probability into systems, much like how future price movements are inherently uncertain. Monte Carlo simulations are used to model a range of possible outcomes based on random inputs.
Implementation: In this script, we simulate 100 random outcomes by generating a random number between -1 and 1 for each iteration. These random values are stored in an array, and the average of these values is calculated to represent the Quantum Signal.
Practical Use: This probabilistic signal provides a sense of randomness and uncertainty in the market, reflecting the possibility of price movement in either direction. It simulates the market’s chaotic nature by considering multiple possible outcomes and their average.
3. Thermodynamics - Efficiency Ratio Signal
Concept: Thermodynamics deals with energy efficiency and entropy in systems. The efficiency ratio in financial terms can be used to measure how efficiently the price is moving relative to volatility.
Implementation: The Efficiency Ratio is calculated as the absolute price change over n periods divided by the sum of absolute changes for each period within n. This ratio shows how much of the price movement is directional versus random, mimicking the concept of efficiency in thermodynamic systems.
Practical Use: A high efficiency ratio suggests that the market is trending smoothly (high efficiency), while a low ratio indicates choppy, non-directional movement (low efficiency, or high entropy).
4. Chaos Theory - ATR Signal
Concept: Chaos theory studies how complex systems are highly sensitive to initial conditions, leading to unpredictable behavior. In markets, chaotic price movements can often be captured through volatility indicators.
Implementation: The script uses a very long ATR period (1000) to reflect slow-moving chaos over time. The Chaos Signal is computed by measuring the deviation of the current price from its long-term average (SMA), normalized by ATR. This captures price deviations over time, hinting at chaotic market behavior.
Practical Use: The signal measures how far the price deviates from its long-term average, which can signal the degree of chaos or extreme behavior in the market. High deviations indicate chaotic or volatile conditions, while low deviations suggest stability.
5. Network Theory - Correlation with BTC
Concept: Network theory studies how different components within a system are interconnected. In markets, assets are often correlated, meaning that price movements in one asset can influence or be influenced by another.
Implementation: This indicator calculates the correlation between the asset’s price and the price of Bitcoin (BTC) over 30 periods. The Network Signal shows how connected the asset is to BTC, reflecting broader market dynamics.
Practical Use: In a highly correlated market, BTC can act as a leading indicator for other assets. A strong correlation with BTC might suggest that the asset is likely to move in line with Bitcoin, while a weak or negative correlation might indicate that the asset is moving independently.
6. String Theory - RSI & MACD Interaction
Concept: String theory attempts to unify the fundamental forces of nature into a single framework. In trading, we can view the RSI and MACD as interacting forces that provide insights into momentum and trend.
Implementation: The script calculates the RSI and MACD and combines them into a single signal. The formula for String Signal is (RSI - 50) / 100 + (MACD Line - Signal Line) / 100, normalizing both indicators to a scale where their contributions are additive. The RSI represents momentum, and MACD shows trend direction and strength.
Practical Use: This signal helps in detecting moments where momentum (RSI) and trend strength (MACD) align, giving a clearer picture of the asset's direction and overbought/oversold conditions. It unifies these two indicators to create a more holistic view of market behavior.
7. Fluid Dynamics - On-Balance Volume (OBV) Signal
Concept: Fluid dynamics studies how fluids move and flow. In markets, volume can be seen as a "flow" that drives price movement, much like how fluid dynamics describe the flow of liquids.
Implementation: The script uses the OBV (On-Balance Volume) indicator to track the cumulative flow of volume based on price changes. The signal is further normalized by its moving average to smooth out fluctuations and make it more reflective of price pressure over time.
Practical Use: The Fluid Signal shows how the flow of volume is driving price action. If the OBV rises significantly, it suggests that there is strong buying pressure, while a falling OBV indicates selling pressure. It’s analogous to how pressure builds in a fluid system.
8. Final Signal - Combining All Physics-Based Indicators
Implementation: Each of the seven physics-inspired signals is combined into a single Final Signal by averaging their values. This approach blends different market insights from various scientific domains, creating a comprehensive view of the market’s condition.
Practical Use: The final signal gives you a holistic, multi-dimensional view of the market by merging different perspectives (fractal behavior, quantum probability, efficiency, chaos, correlation, momentum/trend, and volume flow). This approach helps traders understand the market's dynamics from multiple angles, offering deeper insights than any single indicator.
9. Color Coding Based on Signal Extremes
Concept: The color of the final signal plot dynamically reflects whether the market is in an extreme state.
Implementation: The signal color is determined using percentiles. If the Final Signal is in the top 55th percentile of its range, the signal is green (bullish). If it is between the 45th and 55th percentiles, it is orange (neutral). If it falls below the 45th percentile, it is red (bearish).
Practical Use: This visual representation helps traders quickly identify the strength of the signal. Bullish conditions (green), neutral conditions (orange), and bearish conditions (red) are clearly distinguished, simplifying decision-making.
Komut dosyalarını "bitcoin" için ara
Rounded Grid Levels🟩 Rounded Grid Levels is a visual tool that helps traders quickly identify key psychological price levels on any chart. By dynamically adapting to the user's visible screen area, it provides consistent, easy-to-read round number grids that align with price action. The indicator offers a traditional visualization of horizontal round level grids, along with enhanced options such as tilted grids that align with market sentiment, and fan-shaped grids for alternative price interaction views. It serves purely as a visual aid, providing an adaptable way to observe rounded price levels without making predictions or generating trading signals.
⚡ OVERVIEW ⚡
The Rounded Grid Levels indicator is a visual tool designed to help traders identify and track price levels that may hold psychological significance, such as round numbers or significant milestones. These levels often serve as potential areas for price reactions, including support, resistance, or points of market interest. The indicator's gridlines are determined by user-defined settings and adjust dynamically based on the visible chart area, meaning they are influenced by the user's current zoom level and perspective. This behavior is similar to TradingView's built-in grid lines found in the chart settings canvas, which also adjust in real-time based on the visible screen, ensuring the most relevant price levels are displayed. By default, the indicator provides consistent gridlines to represent traditional round number levels, offering a straightforward view of key psychological areas. Additionally, users have access to experimental and novel configurations, such as fan-shaped layouts, which expand from a central point and adapt directionally based on user settings. This configuration can provide an alternate perspective for traders, especially useful in analyzing broader market moves and visualizing expansion relative to the current price.
Users can display the gridlines in a variety of configurations, including horizontal, neutral, auto, or fan-shaped layouts, depending on their preferred method of analysis. This flexibility allows traders to focus on different types of price action without overcrowding the visual representation of price movements.
This indicator is intended purely as a visual aid for understanding how price interacts with rounded levels over time. It does not generate predictive trading signals or recommendations but rather provides traders with a customizable framework to enhance their market analysis.
⭕ ROUND NUMBERS IN MARKET PSYCHOLOGY ⭕
Round numbers hold a significant place in financial markets, largely due to the psychological tendencies of traders and investors. These levels often represent areas of interest where human behavior, market biases, and trading strategies converge. Whether it's prices ending in 000, 500, or other recognizable values, these levels naturally attract more attention and influence decision-making.
Round numbers can act as key support or resistance levels and often become focal points in market activity. They are frequently highlighted by financial media, embedded in products like options, and serve as foundations for various trading theories. Their impact extends across different market participants and strategies, making them important focal points in both short-term and long-term market analysis.
Round numbers play an important role in guiding trader behavior and market activity. To better understand why these levels are so impactful, there are several key factors that highlight their significance in trading and price dynamics:
Psychological Impact : Humans naturally gravitate toward round numbers, such as prices ending in 000, 500, or 00. These levels tend to draw attention as traders perceive them as psychologically significant. This behavior is rooted in the cognitive bias known as "left-digit bias," where people assign greater importance to rounded, more recognizable numbers. In trading, this means that prices at these levels are more memorable and thus more likely to attract attention, creating an area where traders focus their buying or selling decisions.
Order Clustering : Traders often place buy and sell orders around these rounded levels, either manually or automatically through stop and limit orders. This clustering leads to the formation of visible support or resistance zones, as the concentrated orders tend to influence price behavior around these key levels. Market participants tend to converge their orders around these price points because of their perceived psychological importance, creating a liquidity pocket. As a result, these areas often act as barriers that the price either struggles to cross or uses as springboards for further movement.
External Influences : Financial media frequently highlights round-number milestones, amplifying market sentiment and drawing traders' attention to these levels. Additionally, algorithmic trading systems often react to round-number thresholds, which can further reinforce price movements, creating self-reinforcing reactions at these levels. As media and analysts emphasize these milestones, more traders pay attention to them, leading to increased volume and often heightened volatility at those points. This self-reinforcing cycle makes round numbers an area where price movement can either accelerate due to a breakout or stall because of clustering interest.
Option Strike Prices : Options contracts typically have strike prices set at round numbers, and as expiration approaches, these levels can influence the price of the underlying asset due to concentrated trading activity. The behavior around these levels, often called "pinning," happens because traders adjust their positions to avoid unfavorable scenarios at these key strikes. This activity tends to concentrate price movement toward these levels as traders hedge their positions, leading to increased liquidity and the potential for abrupt price reactions near option expiration dates.
Whole Number Theory : This theory suggests that whole numbers act as natural psychological barriers, where traders tend to make decisions, place orders, or expect price reactions, making these levels crucial for analysis. Whole numbers are simple to remember and are often used as informal targets for profit-taking or stop placement. This behavior leads to a natural ebb and flow around these levels, where the market finds equilibrium temporarily before deciding on a future direction. Whole numbers tend to work like magnets, drawing price to them and often creating reactions that are visible across different timeframes.
Quarters Theory : Commonly used in Forex markets, this theory focuses on quarter-point increments (e.g., 1.0000, 1.2500, 1.5000) as key levels where price often pauses or reverses. These quarter levels are treated as important psychological barriers, with price frequently interacting at these intervals. Traders use these points to gauge market strength or weakness because quarter levels divide larger round-number ranges into more manageable and meaningful segments. For example, in highly traded forex pairs like EUR/USD, traders might treat 1.2500 as a significant barrier because it represents a halfway point between 1.0000 and 1.5000, offering a balanced reference point for decision-making.
Big Round Numbers : Major round numbers, such as 100, 500, or 1000, often attract significant attention and serve as psychological thresholds. Traders anticipate strong reactions when prices approach or cross these levels. This is often because large round numbers symbolize major milestones, and price behavior around them tends to signal important market sentiment shifts. When price crosses a major level, such as a stock moving above $100 or Bitcoin crossing $50,000, it often creates a surge in trading activity as it is viewed as a validation or invalidation of market trends, drawing in momentum traders and triggering both retail and institutional responses.
By visualizing these round levels on the chart, the Rounded Grid Levels indicator helps traders identify areas where price may pause, reverse, or gain momentum. While round numbers provide useful insights, they should be used in conjunction with other technical analysis tools for a comprehensive trading strategy.
🛠️ CONFIGURATION AND SETTINGS 🛠️
The Rounded Grid Levels indicator offers a variety of configurable settings to tailor the visualization according to individual trader preferences. Below are the key settings available for customization:
Custom Settings
Rounding Step : The Rounding Step parameter sets the minimum interval between gridlines. This value determines how closely spaced the rounded levels are on the chart. For example, if the Rounding Step is set to 100, gridlines will be displayed at every 100 points (e.g., $100, $200, $300) relative to the current price level. The Rounding Step is scaled to the chart's visible area, meaning users should adjust it appropriately for different assets to ensure effective visualization. Lower values provide a more granular view, while larger values give a broader, higher-level perspective.
Major Grids : Defines the interval at which major gridlines will appear compared to minor ones. For example, if the Rounding Step is 100 and Major Grids is set to 10, major gridlines will be displayed every $1,000, while minor gridlines will be at every $100. This distinction allows traders to better visualize key psychological levels by emphasizing significant price intervals.
Direction : Users can select the gridline direction, choosing between options such as 'Up', 'Down', 'Auto', or 'Neutral'. This setting controls how the gridlines extend relative to the current price level, which can help in analyzing directional trends.
Neutral Direction : This option provides balanced gridlines both above and below the current price, allowing traders to visualize support and resistance levels symmetrically. This is useful for analyzing sideways or ranging markets without directional bias.
Up Direction : The gridlines are tilted upwards, starting from visible lows and extending toward the rounded level at the current price. By choosing Up , traders emphasize an upward sentiment, visualizing price action that aligns with rising trends. This option helps illustrate potential areas where pullbacks may occur, as well as how price might expand upwards in the current market context.
Down Direction : The gridlines are tilted downwards, starting from visible highs and extending toward the rounded level at the current price. Selecting Down allows traders to emphasize a downward sentiment, visualizing how price may expand downwards, which is particularly useful when analyzing downtrends or potential correction levels. The gridlines provide an illustrative view of how price interacts with lower levels during market declines.
Auto Direction : The gridlines automatically adjust their direction based on recent market trends. This adaptive option allows traders to visualize gridlines that dynamically change according to price action, making it suitable for evolving market conditions where the direction is uncertain. It’s useful for traders looking for an indicator that moves in sync with market shifts and doesn’t require manual adjustment.
Grid Type : Allows users to choose between 'Linear' or 'Fan' grid types. The Linear type creates evenly spaced gridlines that can be either horizontal or tilted, depending on the chosen direction setting, providing a straightforward view of price levels. The Fan type radiates lines from a central point, offering a more dynamic perspective for analyzing price expansions relative to the current price. These grid types introduce experimental visualizations influenced by chart properties, including visible highs, lows, and the current price. Regardless of the configuration, the gridlines will always end at the current bar, which represents a rounded price level, ensuring consistency in how key price areas are displayed.
Extend : This setting allows gridlines to be projected into the future, helping traders see potential levels beyond the current bar. When enabled, the behavior of the extended lines varies based on the selected grid type and direction. For Neutral and Horizontal Linear settings, the extended gridlines maintain their round-number alignment indefinitely. However, for Up , Down , or Auto directions, the angle of the extended gridlines can change dynamically based on the chart’s visible high and low or the latest price action. As a result, extended lines may not continue to align with round-number levels beyond the current bar, reflecting instead the current trend and sentiment of the market. Regardless of direction, extended gridlines remain consistently spaced and either parallel or evenly distributed, ensuring a structured visual representation.
Color Settings : Users can customize the colors for resistance, support, and minor gridlines at the current price. This helps in visually distinguishing between different grid types and their significance on the chart.
Color Options
These configuration options make the Rounded Grid Levels indicator a versatile tool for traders looking to customize their charts based on their personal trading strategies and analytical preferences.
🖼️ CHART EXAMPLES 🖼️
The following chart examples illustrate different configurations available in the Rounded Grid Levels indicator. These examples show how variations in grid type, direction, and rounding step settings impact the visualization of price levels. Traders may find that smaller rounding steps are more effective on lower time frames, where precision is key, whereas larger rounding steps help to reduce clutter and highlight key levels on higher time frames. Each image includes a caption to explain the specific configuration used, helping users better understand how to apply these settings in different market conditions.
Smaller Rounding Step (100) : With a smaller rounding step, the gridlines are spaced closely together. This setting is particularly useful for lower time frames where price action is more granular and finer details are needed. It allows traders to track price interactions at narrower levels, but on higher time frames, it may lead to clutter and exceed Pine Script's 500-line limit.
Larger Rounding Step (1000) : With a larger rounding step, the gridlines are spaced farther apart. This visualization is better suited for higher time frames or broader market overviews, allowing users to focus on major psychological levels without overloading the chart. On lower time frames, this may result in fewer actionable levels, but it helps in maintaining clarity and staying within Pine Script's line limit.
Linear Grid Type, Neutral Direction (Traditional Rounded Price Levels) : The Linear gridlines are displayed in a neutral fashion, representing traditional round-number levels with consistent spacing above and below the current price. This layout helps visualize key psychological price levels over time in a straightforward manner.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, remaining parallel and ending at the rounded level at the current price. This setup emphasizes downward market sentiment, allowing traders to visualize price expansion towards lower levels, which is useful when analyzing downtrends or potential correction levels.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, extending from the current price to lower levels. Useful for observing downtrending price movements and visualizing pullback areas during uptrends.
Linear Grid Type, Auto Direction : The Linear gridlines adjust dynamically, tilting either upwards or downwards to align with recent price trends, remaining parallel and ending at the rounded level at the current price. This configuration reflects the current market sentiment and offers traders a flexible way to observe price dynamics as they develop in real time.
Fan Grid Type, Neutral Direction : The fan-shaped gridlines radiate symmetrically from a central point, ending at the rounded level at the current price. This configuration provides an unbiased view of price action, giving traders a balanced visualization of rounded levels without directional influence.
Fan Grid Type, Up Direction : The fan-shaped gridlines originate from lower visible price points and radiate upwards, ending at the rounded level at the current price. This layout helps visualize potential price expansion to higher levels, offering insights into upward momentum while maintaining a dynamic and evolving perspective on market conditions.
Fan Grid Type, Down Direction : The fan-shaped gridlines originate from higher visible price points and radiate downwards, ending at the rounded level at the current price. This setup is particularly useful for observing potential price expansion towards lower levels, illustrating areas where the price might extend during a downtrend.
Fan Grid Type, Auto Direction : The fan-shaped gridlines dynamically adjust, originating from visible chart points based on the current market trend, and radiate outward, ending at the rounded level at the current price. This adaptive visualization offers a continuously evolving representation that aligns with changing market sentiment, helping traders assess price expansion dynamically.
📊 SUMMARY 📊
The Rounded Grid Levels indicator helps traders highlight important round-number price levels on their charts, providing a dynamic way to visualize these psychological areas. With customizable gridline options—including traditional, tilted, and fan-shaped styles—users can adapt the indicator to suit their analysis needs. The gridlines adjust with chart zoom or scale, offering a flexible tool for observing price action, without providing specific trading signals or predictions.
⚙️ COMPATIBILITY AND LIMITATIONS ⚙️
Asset Compatibility :
The Rounded Grid Levels indicator is compatible with all asset classes, including cryptocurrencies, forex, stocks, and commodities. Users should adjust both the Rounding Step and the Major Grid settings to ensure the correct scale is used for the specific asset. This adjustment ensures that the most relevant round price levels are displayed effectively regardless of the instrument being analyzed. For instance, when analyzing BTCUSD, a higher Rounding Step may be needed compared to forex pairs like EURUSD, and the Major Grid value should also be adjusted to appropriately emphasize significant levels.
Line Limitations in Pine Script :
The Rounded Grid Levels indicator is subject to Pine Script's 500-line limit. This means that it cannot draw more than 500 gridlines on the chart at any given time. The number of gridlines depends directly on the chosen Rounding Step . If the steps are too small, the gridlines will be spaced too closely, causing the indicator to quickly reach the line limit. For example, if Ethereum is trading around $2,500, a Rounding Step of 100 might be appropriate, but a step of 1.00 would create too many gridlines, exceeding Pine Script's limit. Users should consider appropriate settings to avoid running into this constraint.
Runtime Error Considerations
When using the Rounded Grid Levels indicator, users might encounter a runtime error in specific scenarios. This typically happens if the Rounding Step is set too small, causing the indicator to exceed Pine Script's line limit or take too long to process. This can often occur when switching between charts that have significantly different price ranges. Since the Rounding Step requires flexibility to work with a wide variety of assets—ranging from decimals to thousands—it is not practically limited within the script itself. If a runtime error occurs, the recommended solution is to increase the Rounding Step to a larger value that better matches the current asset's price range.
Runtime Error: If the Rounding Step is too small for the current asset or chart, the indicator may generate a runtime error. Users should increase the Rounding Step to ensure proper visualization.
⚠️ DISCLAIMER ⚠️
The Rounded Grid Levels indicator is not designed as a predictive tool. While it extends gridlines into the future, this extension is purely for visual continuity and does not imply any forecast of future price movements. The primary function of this indicator is to help users visualize significant round number price levels.
The gridlines adjust dynamically based on the visible chart range, ensuring that the most relevant round price levels are displayed. This behavior allows the indicator to adapt to your current view of the market, but it should not be used to predict price movements. The indicator is intended as a visual aid and should be used alongside other tools in a comprehensive market analysis approach.
While gridlines may align with significant price levels in hindsight, they should not be interpreted as indicators of future price movements. Traders are encouraged to adjust settings based on their strategy and market conditions.
🧠 BEYOND THE CODE 🧠
The Rounded Grid Levels indicator, like other xxattaxx indicators , is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new grid calculation indicators, drawings, and strategies. We hope this indicator serves as a framework and a starting point for future innovations in grid trading.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We actively encourage your feedback and contributions, which will directly help us refine and improve the Rounded Grid Levels indicator. We look forward to seeing the creative ways in which you use and enhance this tool.
Multi Fibonacci Supertrend with Signals【FIbonacciFlux】Multi Fibonacci Supertrend with Signals (MFSS)
Overview
The Multi Fibonacci Supertrend with Signals (MFSS) is an advanced technical analysis tool that combines multiple Supertrend indicators using Fibonacci ratios to identify trend directions and potential trading opportunities.
Key Features
1. Fibonacci-Based Supertrend Levels
* Factor 1 (Weak) : 0.618 - The golden ratio
* Factor 2 (Medium) : 1.618 - The Fibonacci ratio
* Factor 3 (Strong) : 2.618 - The extension ratio
2. Visual Components
* Multi-layered Trend Lines
* Different line weights for easy identification
* Progressive transparency from Factor 1 to Factor 3
* Color-coded trend directions (Green for bullish, Red for bearish)
* Dynamic Fill Areas
* Gradient fills between price and trend lines
* Visual representation of trend strength
* Automatic color adjustment based on trend direction
* Signal Indicators
* Clear BUY/SELL labels on chart
* Position-adaptive signal placement
* High-visibility color scheme
3. Signal Generation Logic
The system generates signals based on two key conditions:
* Primary Condition :
* BUY : Price crossunder Supertrend2 (Factor 1.618)
* SELL : Price crossover Supertrend2 (Factor 1.618)
* Confirmation Filter :
* Signals only trigger when Supertrend3 confirms the trend direction
* Reduces false signals in volatile markets
Technical Details
Input Parameters
* ATR Period : 10 (default)
* Customizable for different market conditions
* Affects sensitivity of all Supertrend levels
* Factor Settings :
* All factors are customizable
* Default values based on Fibonacci sequence
* Minimum value: 0.01
* Step size: 0.01
Alert System
* Built-in alert conditions
* Customizable alert messages
* Real-time notification support
Use Cases
* Trend Trading
* Identify strong trend directions
* Filter out weak signals
* Confirm trend continuations
* Risk Management
* Multiple trend levels for stop-loss placement
* Clear entry and exit signals
* Trend strength visualization
* Market Analysis
* Multi-timeframe analysis capability
* Trend strength assessment
* Market structure identification
Benefits
* Reliability
* Based on proven Supertrend algorithm
* Enhanced with Fibonacci mathematics
* Multiple confirmation levels
* Clarity
* Clear visual signals
* Easy-to-interpret interface
* Reduced noise in signal generation
* Flexibility
* Customizable parameters
* Adaptable to different markets
* Suitable for various trading styles
Performance Considerations
* Optimized code structure
* Efficient calculation methods
* Minimal resource usage
Installation and Usage
Setup
* Add indicator to chart
* Adjust parameters if needed
* Enable alerts as required
Best Practices
* Use with other confirmation tools
* Adjust factors based on market volatility
* Consider timeframe appropriateness
Backtesting Results and Strategy Performance
This indicator is specifically designed for pullback trading with optimized risk-reward ratios in trend-following strategies. Below are the detailed backtesting results from our proprietary strategy implementation:
BTCUSDT Performance (Binance)
* Test Period: Approximately 7 years
* Risk-Reward Ratio: 2:1
* Take Profit: 8%
* Stop Loss: 4%
Key Metrics (BTCUSDT):
* Net Profit: +2,579%
* Total Trades: 551
* Win Rate: 44.8%
* Profit Factor: 1.278
* Maximum Drawdown: 42.86%
ETHUSD Performance (Binance)
* Risk-Reward Ratio: 4.33:1
* Take Profit: 13%
* Stop Loss: 3%
Key Metrics (ETHUSD):
* Net Profit: +8,563%
* Total Trades: 581
* Win Rate: 32%
* Profit Factor: 1.32
* Maximum Drawdown: 55%
Strategy Highlights:
* Optimized for pullback trading in strong trends
* Focus on high risk-reward ratios
* Proven effectiveness in major cryptocurrency pairs
* Consistent performance across different market conditions
* Robust profit factor despite moderate win rates
Note: These results are from our proprietary strategy implementation and should be used as reference only. Individual results may vary based on market conditions and implementation.
Important Considerations:
* The strategy demonstrates strong profitability despite lower win rates, emphasizing the importance of proper risk-reward ratios
* Higher drawdowns are compensated by significant overall returns
* The system shows adaptability across different cryptocurrencies with consistent profit factors
* Results suggest optimal performance in volatile crypto markets
Real Trading Examples
BTCUSDT 4-Hour Chart Analysis
Example of pullback strategy implementation on Bitcoin, showing clear trend definition and entry points
ETHUSDT 4-Hour Chart Analysis
Ethereum chart demonstrating effective signal generation during strong trends
BTCUSDT Detailed Signal Example (15-Minute Scalping)
Close-up view of signal generation and trend confirmation process on 15-minute timeframe, demonstrating the indicator's effectiveness for scalping operations
Chart Analysis Notes:
* Green and red zones clearly indicate trend direction
* Multiple timeframe confirmation visible through different Supertrend levels
* Clear entry signals during pullbacks in established trends
* Precise stop-loss placement opportunities below support levels
Implementation Guidelines:
* Wait for main trend confirmation from Factor 3 (2.618)
* Enter trades on pullbacks to Factor 2 (1.618)
* Use Factor 1 (0.618) for fine-tuning entry points
* Place stops below the relevant Supertrend level
Footnotes:
* Charts provided are from Binance exchange, using both 4-hour and 15-minute timeframes
* Trading view screenshots captured during actual market conditions
* Indicators shown: Multi Fibonacci Supertrend with all three factors
* Time period: Recent market activity showing various market conditions
Important Notice:
These charts are for educational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management.
Disclaimer
This indicator is for informational purposes only. Past performance is not indicative of future results. Always conduct proper risk management and due diligence.
License
Open source under MIT License
Author's Note
Contributions and suggestions for improvement are welcome. Please feel free to fork and enhance.
BTC ETF Flow Trading SignalsTracks large money flows (500M+) across major Bitcoin ETFs (IBIT, BTCO, FBTC, ARKB, BITB)
Generates long/short signals based on institutional money movement
Shows flow trends and strength of movements
This script provides a foundation for comparing ETF inflows and Bitcoin price. The effectiveness of the analysis depends on the quality of the data and your interpretation of the results. Key levels of 500M and 350M Inflow/Outflow Enjoy
Collaboration with Vivid Vibrations
Enjoy & improve!
Saturn Retrograde PeriodsSaturn Retrograde Periods Visualizer for TradingView
This Pine Script visualizes all Saturn retrograde periods since 2009, including the current retrograde ending on November 15, 2024. The script overlays yellow boxes on your TradingView chart to highlight the exact periods of Saturn retrograde. It's a great tool for astrologically-inclined traders or those interested in market timing based on astrological events.
Key Features:
Full Historical Coverage: Displays Saturn retrograde periods from 2009 (the inception of Bitcoin) to the current retrograde ending in November 2024.
Customizable Appearance: You can easily adjust the color and opacity of the boxes directly from the script's settings window, making it flexible for various chart styles.
Visual Clarity: The boxes span the full vertical range of your chart, ensuring the retrograde periods are clearly visible over any asset, timeframe, or price action.
How to Use:
Add the script to your TradingView chart.
Adjust the color and opacity in the settings to suit your preferences.
View all relevant Saturn retrograde periods and analyze how these astrological events may align with price movements in your selected asset.
This script is perfect for traders and analysts who want to combine astrology with financial market analysis!
scripted by chat.gpt - version 1.0
Ping Pong Bot StrategyOverview:
The Ping Pong Bot Strategy is designed for traders who focus on scalping and short-term opportunities using support and resistance levels. This strategy identifies potential buy entries when the price reaches a key support area and shows bullish momentum (a green bar). It aims to capitalize on small price movements with predefined risk management and take profit levels, making it suitable for active traders looking to maximize quick trades in trending or ranging markets.
How It Works:
Support & Resistance Calculation:
The strategy dynamically identifies support and resistance levels using the lowest and highest price points over a user-defined period. These levels help pinpoint potential price reversal areas, guiding traders on where to enter or exit trades.
Buy Entry Criteria:
A buy signal is triggered when the closing price is at or below the support level, and the bar is green (i.e., the closing price is higher than the opening price). This ensures that entries are made when prices show signs of upward momentum after hitting support.
Risk Management:
For each trade, a stop loss is calculated based on a user-defined risk percentage, helping to protect against significant drawdowns. Additionally, a take profit level is set at a ratio relative to the risk, ensuring a disciplined approach to exit points.
0.5% Take Profit Target:
The strategy also includes a 0.5% quick take profit target, indicated by an orange arrow when reached. This feature helps traders lock in small gains rapidly, making it ideal for volatile market conditions.
Customizable Inputs:
Length: Adjusts the period for calculating support and resistance levels.
Risk-Reward Ratio: Allows traders to set the desired risk-to-reward ratio for each trade.
Risk Percentage: Defines the risk tolerance for stop loss calculations.
Take Profit Target: Enables the customization of the quick take profit target.
Ideal For:
Traders who prefer an active trading style and want to leverage support and resistance levels for precise entries and exits. This strategy is particularly useful in markets that experience frequent price bounces between support and resistance, allowing traders to "ping pong" between these levels for profitable trades.
Note:
This strategy is developed mainly for the 5-minute chart and has not been tested on longer time frames. Users should perform their own testing and adjustments if using it on different time frames.
Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
ADA Stock-to-Flow Model (BSP)ADA Stock-to-Flow Model
This script implements a Stock-to-Flow (S2F) model for ADA (Cardano). The Stock-to-Flow ratio is a popular metric used to assess the scarcity of an asset by comparing its current supply (stock) to the rate at which it is being produced (flow). By visualizing the S2F ratio on ADA, this model helps traders and analysts evaluate potential long-term price trends based on supply scarcity.
Key features:
Calculates ADA's Stock-to-Flow ratio dynamically, adjusting for changes in circulating supply and emission rates.
Provides easy-to-read visualizations with adjustable timeframes, making it accessible for both novice and experienced traders.
The Stock-to-Flow model is widely used in analyzing assets like Bitcoin, and this adaptation for ADA gives unique insights into the relationship between its supply and market value. While the model offers a useful perspective on ADA’s potential trajectory, it should be used in conjunction with other tools for a comprehensive market analysis.
Realized Price Profit/Loss Margin [VWAP Optimized]Shaded Profit/Loss Margin Oscillator
The Shaded Profit/Loss Margin Oscillator is a powerful tool designed to measure Bitcoin’s Net Unrealized Profit/Loss (NUPL). This metric reflects the difference between Bitcoin’s current market price and its realized price, which approximates the price at which coins were last moved. By smoothing the NUPL using a moving average, the indicator provides a clean purple oscillator line that helps users easily gauge market sentiment. When the oscillator is above the zero line, the market is in profit, and when it is below zero, participants are generally in a state of unrealized loss. The shaded area between the oscillator and the zero line enhances visual clarity, making it easier to identify potential shifts in market behavior such as profit-taking or capitulation.
Unique Features and Added Value
What sets this indicator apart from traditional NUPL indicators is the use of a volume-weighted average price (VWAP) as a proxy for the realized price. Unlike the original on-chain NUPL metric, which relies on complex on-chain data, this indicator leverages VWAP to provide an approximation of realized price based solely on price and volume data available directly on TradingView. This method makes it highly accessible to traders who don’t have access to on-chain data platforms.
The use of VWAP not only simplifies the calculation but also provides additional value, as it incorporates volume into the realized price estimation. This volume-sensitive approach may offer a more responsive and dynamic reflection of realized prices compared to on-chain models, which can sometimes lag. In essence, this VWAP-based NUPL oscillator offers a unique edge in tracking profit/loss margins, particularly for traders who want a straightforward and efficient way to gauge sentiment without relying on external on-chain data sources. It brings the essence of NUPL into the world of technical analysis in an accessible and actionable way.
TechniTrend: Dynamic Pair CorrelationTechniTrend: Dynamic Pair Correlation
Description:
The TechniTrend: Dynamic Pair Correlation is a powerful and versatile indicator designed to track the correlation between two assets—whether cryptocurrencies, indices, or other financial instruments—across multiple timeframes. Understanding correlations can provide deep insights into market behavior, helping traders make informed decisions based on how two assets move in relation to each other.
Key Features:
Customizable Pair Selection: Compare any two assets (e.g., Bitcoin and DXY, Ethereum and SP500) to study how their price movements relate over time.
Multi-Timeframe Analysis: Simultaneously track correlations across different timeframes—standard, lower, and higher—providing a comprehensive view of market dynamics.
Dynamic Color Coding for Correlation Strength: Instantly spot correlations with visually intuitive colors—green for strong positive correlation, red for strong negative correlation, and yellow for neutral.
Heatmap Background: An easy-to-read background color heatmap highlights when correlations hit extreme levels, adding another layer of insight to your charts.
Real-Time Alerts: Get notified when correlations exceed your custom thresholds, signaling opportunities for potential breakouts, reversals, or divergences.
Divergence Detection: Automatically highlight moments when asset prices diverge, offering potential entry/exit points for smart trading decisions.
How to Use:
Asset Pair Comparison: Select two symbols to analyze their price correlation, such as BTC/USDT and DXY, or any other pair that fits your strategy.
Set Your Timeframes: Customize your standard, lower, and higher timeframes to monitor correlations at different intervals, allowing you to capture both short-term and long-term relationships.
Track Correlation Strength: Use dynamic color coding to quickly see how closely two assets are moving together. Strong correlations (positive or negative) could signal potential opportunities, while low correlations may indicate the absence of a strong trend.
Utilize Alerts: Receive real-time alerts when correlations cross your predefined thresholds, helping you take action when the market presents strong alignment or divergence.
Divergence Signals: Watch for divergence between the assets on multiple timeframes, which could indicate a potential trend reversal or a shift in market behavior.
Why It’s Essential:
Understanding the relationship between two assets can be a game changer for traders. Whether you're comparing Bitcoin to DXY, tracking the correlation between Ethereum and major indices, or evaluating two cryptocurrencies, this indicator gives you the tools to visualize and respond to market conditions with precision.
Perfect For:
Crypto traders looking to optimize strategies by monitoring the relationship between major cryptocurrencies and other assets.
Arbitrageurs seeking to capitalize on temporary pricing anomalies between correlated pairs.
Trend-followers aiming to catch large movements by detecting alignment or divergence between asset classes.
Portfolio managers monitoring how different asset classes impact each other to hedge or diversify investments.
By leveraging the TechniTrend: Dynamic Pair Correlation indicator, traders can gain deeper insights into market trends, correlations, and divergences, giving them an edge in fast-moving markets.
ETH Signal 15m
This strategy uses the Supertrend indicator combined with RSI to generate buy and sell signals, with stop loss (SL) and take profit (TP) conditions based on ATR (Average True Range). Below is a detailed explanation of each part:
1. General Information BINANCE:ETHUSDT.P
Strategy Name: "ETH Signal 15m"
Designed for use on the 15-minute time frame for the ETH pair.
Default capital allocation is 15% of total equity for each trade.
2. Backtest Period
start_time and end_time: Define the start and end time of the backtest period.
start_time = 2024-08-01: Start date of the backtest.
end_time = 2054-01-01: End date of the backtest.
The strategy will only run when the current time falls within this specified range.
3. Supertrend Indicator
Supertrend is a trend-following indicator that provides buy or sell signals based on the direction of price changes.
factor = 2.76: The multiplier used in the Supertrend calculation (increasing this value makes the Supertrend less sensitive to price movements).
atrPeriod = 12: Number of periods used to calculate ATR.
Output:
direction: Determines the buy/sell direction based on Supertrend.
If direction decreases, it signals a buy (Long).
If direction increases, it signals a sell (Short).
4. RSI Indicator
RSI (Relative Strength Index) is a momentum indicator, often used to identify overbought or oversold conditions.
rsiLength = 12: Number of periods used to calculate RSI.
rsiOverbought = 70: RSI level considered overbought.
rsiOversold = 30: RSI level considered oversold.
5. Entry Conditions
Long Entry:
Supertrend gives a buy signal (ta.change(direction) < 0).
RSI must be below the overbought level (rsi < rsiOverbought).
Short Entry:
Supertrend gives a sell signal (ta.change(direction) > 0).
RSI must be above the oversold level (rsi > rsiOversold).
The strategy will only execute trades if the current time is within the backtest period (in_date_range).
6. Stop Loss (SL) and Take Profit (TP) Conditions
ATR (Average True Range) is used to calculate the distance for Stop Loss and Take Profit based on price volatility.
atr = ta.atr(atrPeriod): ATR is calculated using 12 periods.
Stop Loss and Take Profit are calculated as follows:
Long Trade:
Stop Loss: Set at close - 4 * atr (current price minus 4 times the ATR).
Take Profit: Set at close + 2 * atr (current price plus 2 times the ATR).
Short Trade:
Stop Loss: Set at close + 4 * atr (current price plus 4 times the ATR).
Take Profit: Set at close - 2.237 * atr (current price minus 2.237 times the ATR).
Summary:
This strategy enters a Long trade when the Supertrend indicates an upward trend and RSI is not in the overbought region. Conversely, a Short trade is entered when Supertrend signals a downtrend, and RSI is not oversold.
The trade is exited when the price reaches the Stop Loss or Take Profit levels, which are determined based on price volatility (ATR).
Disclaimer:
The content provided in this strategy is for informational and educational purposes only. It is not intended as financial, investment, or trading advice. Trading in cryptocurrency, stocks, or any financial markets involves significant risk, and you may lose more than your initial investment. Past performance is not indicative of future results, and no guarantee of profit can be made. You should consult with a professional financial advisor before making any investment decisions. The creator of this strategy is not responsible for any financial losses or damages incurred as a result of following this strategy. All trades are executed at your own risk.
Potential Divergence Checker#### Key Features
1. Potential Divergence Signals:
Potential divergences can signal a change in price movement before it occurs. This indicator identifies potential divergences instead of waiting for full confirmation, allowing it to detect signs of divergence earlier than traditional methods. This provides more flexible entry points and can act as a broader filter for potential setups.
2. Exposing Signals for External Use:
One of its advanced features is the ability to expose signals for use in other scripts. This allows users to integrate divergence signals and related entry/exit points into custom strategies or automated systems.
3. Custom Entry/Exit Timing Based on Years and Days:
The indicator provides entry and exit signals based on years and days, which could be useful for time-specific market behavior, long-term trades, and back testing.
#### Basic Usage
This indicator can check for all types of potential divergences: bullish, hidden bullish, bearish, hidden bearish. All you need to do is choose the type you want to check for under “DIVERGENCE TYPE” in the settings. On the chart, potential bullish divergences will show up as triangles below the price candles. one the chart potential bearish divergences will show up as upside down triangles above the price candles
#### Signals for Advanced Usage
You can use this indicator as a source in other indicators or strategies using the following information:
“ PD: Bull divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBull divergence(hidden bull) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: Bear divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBear divergence(hidden bear) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: enter ” signal will return a “1” when both the days and years criteria in the “entry filter settings” are met and “0” when not met.
“ PD: exit ” signal will return a “1” when the days criteria in the “exit filter settings” are met and “0” when not met.
#### Examples of Using Signals
1. If you are testing a long strategy for Bitcoin and do not want it to run during bear market years(e.g., the second year after a US presidential election), you can enable the “year and day filter for entry,” uncheck the following years in the settings: 2010, 2014, 2018, 2022, 2026, and reference the signal below in our strategy
signal: “ PD: enter ”
2. Let’s say you have a good long strategy, but want to make it a bit more profitable, you can tell the strategy not to run on days where there is potential bearish divergence and have it only run on more profitable days using these signals and the appropriate settings in the indicator
signal: “ PD: Bear divergence signal ” will return a ‘0’ with no bearish divergence present
signal: “ PD: enter ” will return a “1” if the entry falls on a specific, more profitable day chosen in the settings
#### Disclaimer
The "Potential Divergence Checker" indicator is a tool designed to identify potential market signals. It may have bugs and not do what it should do. It is not a guarantee of future trading performance, and users should exercise caution when making trading decisions based on its outputs. Always perform your own research and consider consulting with a financial advisor before making any investment decisions. Trading involves significant risk, and past performance is not indicative of future results.
Swing Failure Pattern SFP [TradingFinder] SFP ICT Strategy🔵 Introduction
The Swing Failure Pattern (SFP), also referred to as a "Fake Breakout" or "False Breakout," is a vital concept in technical analysis. This pattern is derived from classic technical analysis, price action strategies, ICT concepts, and Smart Money Concepts.
It’s frequently utilized by traders to identify potential trend reversals in financial markets, especially in volatile markets like cryptocurrencies and forex. SFP helps traders recognize failed attempts to breach key support or resistance levels, providing strategic opportunities for trades.
The Swing Failure Pattern (SFP) is a popular strategy among traders used to identify false breakouts and potential trend reversals in the market. This strategy involves spotting moments where the price attempts to break above or below a previous high or low (breakout) but fails to sustain the move, leading to a sharp reversal.
Traders use this strategy to identify liquidity zones where stop orders (stop hunt) are typically placed and targeted by larger market participants or whales.
When the price penetrates these areas but fails to hold the levels, a liquidity sweep occurs, signaling exhaustion in the trend and a potential reversal. This strategy allows traders to enter the market at the right time and capitalize on opportunities created by false breakouts.
🟣 Types of SFP
When analyzing SFPs, two main variations are essential :
Real SFP : This occurs when the price breaks a critical level but fails to close above it, then quickly reverses. Due to its clarity and strong signal, this SFP type is highly reliable for traders.
Considerable SFP : In this scenario, the price closes slightly above a key level but quickly declines. Although significant, it is not as definitive or trustworthy as a Real SFP.
🟣 Understanding SFP
The Swing Failure Pattern, or False Breakout, is identified when the price momentarily breaks a crucial support or resistance level but cannot maintain the movement, leading to a rapid reversal.
The pattern can be categorized as follows :
Bullish SFP : This type occurs when the price dips below a support level but rebounds above it, signaling that sellers failed to push the price lower, indicating a potential upward trend.
Bearish SFP : This pattern forms when the price surpasses a resistance level but fails to hold, suggesting that buyers couldn’t maintain the higher price, leading to a potential decline.
🔵 How to Use
To effectively identify an SFP or Fake Breakout on a price chart, traders should follow these steps :
Identify Key Levels: Locate significant support or resistance levels on the chart.
Observe the Fake Breakout: The price should break the identified level but fail to close beyond it.
Monitor Price Reversal: After the breakout, the price should quickly reverse direction.
Execute the Trade: Traders typically enter the market after confirming the SFP.
🟣 Examples
Bullish Example : Bitcoin breaks below a $30,000 support level, drops to $29,000, but closes above $30,000 by the end of the day, signaling a Real Bullish SFP.
Bearish Example : Ethereum surpasses a $2,000 resistance level, rises to $2,100, but then falls back below $2,000, forming a Bearish SFP.
🟣 Pros and Cons of SFP
Pros :
Effective in identifying strong reversal points.
Offers a favorable risk-to-reward ratio.
Applicable across different timeframes.
Cons :
Requires experience and deep market understanding.
Risk of encountering false breakouts.
Should be combined with other technical tools for optimal effectiveness.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
SFP Type : Choose between "All", "Real" and "Considerable" modes to identify the swing failure pattern.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert SFP : Enables alerts for Swing Failure Pattern.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Swing Failure Pattern (SFP), or False Breakout, is an essential analytical tool that assists traders in identifying key market reversal points for successful trading.
By understanding the nuances between Real SFP and Considerable SFP, and integrating this pattern with other technical analysis tools, traders can make more informed decisions and better manage their trading risks.
Uptrick: Dual Moving Average Volume Oscillator
Title: Uptrick: Dual Moving Average Volume Oscillator (DPVO)
### Overview
The "Uptrick: Dual Moving Average Volume Oscillator" (DPVO) is an advanced trading tool designed to enhance market analysis by integrating volume data with price action. This indicator is specially developed to provide traders with deeper insights into market dynamics, making it easier to spot potential entry and exit points based on volume and price interactions. The DPVO stands out by offering a sophisticated approach to traditional volume analysis, setting it apart from typical volume indicators available on the TradingView platform.
### Unique Features
Unlike traditional indicators that analyze volume and price movements separately, the DPVO combines these two critical elements to offer a comprehensive view of market behavior. By calculating the Volume Impact, which involves the product of the exponential moving averages (EMAs) of volume and the price range (close - open), this indicator highlights significant trading activities that could indicate strong buying or selling pressure. This method allows traders to see not just the volume spikes, but how those spikes relate to price movements, providing a clearer picture of market sentiment.
### Customization and Inputs
The DPVO is highly customizable, catering to various trading styles and strategies:
- **Oscillator Length (`oscLength`)**: Adjusts the period over which the volume and price difference is analyzed, allowing traders to set it according to their trading timeframe.
- **Fast and Slow Moving Averages (`fastMA` and `slowMA`)**: These parameters control the responsiveness of the DPVO. A shorter `fastMA` coupled with a longer `slowMA` can help in identifying trends quicker or smoothing out market noise for more conservative approaches.
- **Signal Smoothing (`signalSmooth`)**: This input helps in reducing signal noise, making the crossover and crossunder points between the DVO and its smoothed signal line clearer and easier to interpret.
### Functionality Details
The DPVO operates through a sequence of calculated steps that integrate volume data with price movement:
1. **Volume Impact Calculation**: This is the foundational step where the product of the EMA of volume and the EMA of price range (close - open) is calculated. This metric highlights trading sessions where significant volume accompanies substantial price movements, suggesting a strong market response.
2. **Dynamic Volume Oscillator (DVO)**: The heart of the indicator, the DVO, is derived by calculating the difference between the fast EMA and the slow EMA of the Volume Impact. This result is then normalized by dividing by the EMA of the volume over the same period to scale the output, making it consistent across various trading environments.
3. **Signal Generation**: The final output is smoothed using a simple moving average of the DVO to filter out market noise. Buy and sell signals are generated based on the crossover and crossunder of the DVO with its smoothed version, providing clear cues for market entry or exit.
### Originality
The DPVO's originality lies in its innovative integration of volume and price movement, a novel approach not typically observed in other volume indicators. By analyzing the product of volume and price change EMAs, the DPVO captures the essence of market dynamics more holistically than traditional tools, which often only reflect volume levels without contextualizing them with price actions. This dual analysis provides traders with a deeper understanding of market forces, enabling them to make more informed decisions based on a combination of volume surges and significant price movements. The DPVO also introduces a unique normalization and smoothing technique that refines the oscillator's output, offering cleaner and more reliable signals that are adaptable to various market conditions and trading styles.
### Practical Application
The DPVO excels in environments where volume plays a crucial role in validating price movements. Traders can utilize the buy and sell signals generated by the DPVO to enhance their decision-making process. The signals are plotted directly on the trading chart, with buy signals appearing below the price bars and sell signals above, ensuring they are prominent and actionable. This setup is particularly useful for day traders and swing traders who rely on timely and accurate signals to maximize their trading opportunities.
### Best Practices
To maximize the effectiveness of the DPVO, traders should consider the following best practices:
- **Market Selection**: Use the DPVO in markets known for strong volume-price correlation such as major forex pairs, popular stocks, and cryptocurrencies.
- **Signal Confirmation**: While the DPVO provides powerful signals, confirming these signals with additional indicators such as RSI or MACD can increase trade reliability.
- **Risk Management**: Always use stop-loss orders to manage risks associated with trading signals. Adjust the position size based on the volatility of the asset to avoid significant losses.
### Practical Example + How to use it
Practical Example1: Day Trading Cryptocurrencies
For a day trader focusing on the highly volatile cryptocurrency market, the DPVO can be an effective tool on a 15-minute chart. Suppose a trader is monitoring Bitcoin (BTC) during a period of high market activity. The DPVO might show an upward crossover of the DVO above its smoothed signal line while also indicating a significant increase in volume. This could signal that strong buying pressure is entering the market, suggesting a potential short-term rally. The trader could enter a long position based on this signal, setting a stop-loss just below the recent support level to manage risk. If the DPVO later shows a crossover in the opposite direction with decreasing volume, it might signal a good exit point, allowing the trader to lock in profits before a potential pullback.
- **Swing Trading Stocks**: For a swing trader looking at stocks, the DPVO could be applied on a daily chart. If the oscillator shows a consistent downward trend along with increasing volume, this could suggest a potential sell-off, providing a sell signal before a significant downturn.
You can look for:
--> Increase in volume - You can use indicators like 24-hour-Volume to have a better visualization
--> Uptrend/Downtrend in the indicator (HH, HL, LL, LH)
--> Confirmation (Buy signal/Sell signal)
--> Correct Price action (Not too steep moves up or down. Stable moves.) (Optional)
--> Confirmation with other indicators (Optional)
Quick image showing you an example of a buy signal on SOLANA:
### Technical Notes
- **Calculation Efficiency**: The DPVO utilizes exponential moving averages (EMAs) in its calculations, which provides a balance between responsiveness and smoothing. EMAs are favored over simple moving averages in this context because they give more weight to recent data, making the indicator more sensitive to recent market changes.
- **Normalization**: The normalization of the DVO by the EMA of the volume ensures that the oscillator remains consistent across different assets and timeframes. This means the indicator can be used on a wide variety of markets without needing significant adjustments, making it a versatile tool for traders.
- **Signal Line Smoothing**: The final signal line is smoothed using a simple moving average (SMA) to reduce noise. The choice of SMA for smoothing, as opposed to EMA, is intentional to provide a more stable signal that is less prone to frequent whipsaws, which can occur in highly volatile markets.
- **Lag and Sensitivity**: Like all moving average-based indicators, the DPVO may introduce a slight lag in signal generation. However, this is offset by the indicator’s ability to filter out market noise, making it a reliable tool for identifying genuine trends and reversals. Adjusting the `fastMA`, `slowMA`, and `signalSmooth` inputs allows traders to fine-tune the sensitivity of the DPVO to match their specific trading strategy and market conditions.
- **Platform Compatibility**: The DPVO is written in Pine Script™ v5, ensuring compatibility with the latest features and functionalities offered by TradingView. This version takes advantage of optimized functions for performance and accuracy in calculations, making it well-suited for real-time analysis.
Conclusion
The "Uptrick: Dual Moving Average Volume Oscillator" is a revolutionary tool that merges volume analysis with price movement to offer traders a more nuanced understanding of market trends and reversals. Its ability to provide clear, actionable signals based on a unique combination of volume and price changes makes it an invaluable addition to any trader's toolkit. Whether you are managing long-term positions or looking for quick trades, the DPVO provides insights that can help refine any trading strategy, making it a standout choice in the crowded field of technical indicators.
Nothing from this indicator or any other Uptrick Indicators is financial advice. Only you are ultimately responsible for your choices.
Cumulative Net VolumeCumulative Calculation: Summarizes the net volume (buying minus selling volume) cumulatively, providing a running total that reflects the aggregate trading pressure.
Custom Timeframe Flexibility: Users can choose to analyze the volume on a custom timeframe, enhancing adaptability for various trading strategies.
Color-Coded Visualization: Features an intuitive color scheme where green indicates a net buying dominance and red signals net selling dominance, making it easier to interpret shifts in market dynamics.
Versatility: Suitable for all types of assets available on TradingView including cryptocurrencies like Bitcoin, stocks, forex, and more.
Utility: This tool is particularly useful for identifying trends in buying or selling pressure, which could be pivotal during significant market events or when assessing the potential for a trend reversal. By understanding the accumulation and distribution phases through the cumulative net volume, traders can make more informed decisions.
Perfect for both novice traders looking to get a grip on volume analysis and seasoned professionals seeking an edge in their trading tactics.
Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Volume Weighted Average Price Ratio (log) [ilyaQwerty]The VWAP Ratio indicator is a valuable tool for traders aiming to assess market trends and price movements in relation to the Volume Weighted Average Price (VWAP). Volume Weighted Average Price Ratio represents the ratio of the price of the asset compared to total traded volume in US Dollars. In a context of Bitcoin, VWAP ratio helps traders assess the market state, if it is overvalued or undervalued. High values of the indicator can suggest that the market is highly overvalued and low values can indicate a great buying opportunity.
Ratio Calculation: The VWAP Ratio is computed by dividing the current price by the VWAP (Price / VWAP). VWAP represents a ratio between a cumulative sum of a traded value (price multiplied by the volume) and a cumulative traded volume.
BTC-Specific Optimization: Although the indicator can be applied to various assets, the VWAP Ratio indicator is particularly useful for Bitcoin (BTC) due to its significant trading volume and unique market behaviour.
Coinbase Premium ($) Absolute Dollar Amount # Coinbase Dollar Premium Indicator
## Description
The Coinbase Dollar Premium Indicator is a powerful tool for cryptocurrency traders and analysts, providing real-time insight into the price differences between major exchanges. This indicator calculates and visualizes the dollar amount premium or discount of Bitcoin on Coinbase compared to the average price on Binance and Kraken.
## Key Features
1. **Dollar Value**: Unlike percentage-based indicators, this tool shows the actual dollar amount difference, giving traders a clear understanding of the magnitude of price disparities.
2. **Multi-Exchange Comparison**: By averaging the prices from Binance and Kraken, the indicator provides a more robust baseline for comparison, reducing the impact of single-exchange anomalies.
3. **Clear Visual Representation**: The indicator uses a color-coded histogram for easy interpretation:
- Green bars indicate a premium on Coinbase (Coinbase price is higher)
- Red bars indicate a discount on Coinbase (Coinbase price is lower)
- The height of each bar represents the dollar amount of the premium or discount
4. **Zero Line Reference**: A horizontal line at zero helps quickly distinguish between premium and discount states.
## Use Cases
- **Arbitrage Opportunities**: Identify potential arbitrage opportunities between exchanges.
- **Market Sentiment**: Gauge institutional and retail investor sentiment, as Coinbase is often associated with US institutional activity.
- **Price Prediction**: Use divergences between exchanges as a potential indicator of short-term price movements.
- **Risk Management**: Understand the pricing landscape across major exchanges to make more informed trading decisions.
This indicator is valuable for both short-term traders looking for quick opportunities and long-term investors wanting to understand market dynamics. By providing a clear, dollar-based view of inter-exchange price differences, the Coinbase Dollar Premium Indicator offers unique insights into the cryptocurrency market's microstructure.
*Note: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consider your risk tolerance before trading.*
HRC - Hash Rate Capitulation [Da_Prof]The HRC (Hash Rate Capitulation) indicator is a measure of hash rate trend strength. It is the fractional difference between a long and a short simple moving average (SMA) of the bitcoin hash rate. Historically, the 21-day and 105-day SMA work well for this indicator. The hash rate generally increases over time, but when the short SMA crosses below the longer-term SMA, it shows that miners are removing significant hash from the system. This state can be considered a miner "capitulation". Historically, this has marked depressed BTC prices and has led to higher prices within some months. Shout out to foosmoo, the hash rate oscillator indicator prompted this presentation.
BTC outperform atrategy### Code Description
This Pine Script™ code implements a simple trading strategy based on the relative prices of Bitcoin (BTC) on a weekly and a three-month basis. The script plots the weekly and three-month closing prices of Bitcoin on the chart and generates trading signals based on the comparison of these prices. The code can also be applied to Ethereum (ETH) with similar effectiveness.
### Explanation
1. **Inputs and Variables**:
- The user selects the trading symbol (default is "BINANCE:BTCUSDT").
- `weeklyPrice` retrieves the closing price of the selected symbol on a weekly interval.
- `monthlyPrice` retrieves the closing price of the selected symbol on a three-month interval.
2. **Plotting Data**:
- The weekly price is plotted in blue.
- The three-month price is plotted in red.
3. **Trading Conditions**:
- A long position is suggested if the weekly price is greater than the three-month price.
- A short position is suggested if the three-month price is greater than the weekly price.
4. **Strategy Execution**:
- If the long condition is met, the strategy enters a long position.
- If the short condition is met, the strategy enters a short position.
This script works equally well for Ethereum (ETH) by changing the symbol input to "BINANCE:ETHUSDT" or any other desired Ethereum trading pair.
CryptoLibrary "Crypto"
This Library includes functions related to crytocurrencies and their blockchain
btcBlockReward(t)
Delivers the BTC block reward for a specific date/time
Parameters:
t (int) : Time of the current candle
Returns: blockRewardBtc
Crypto SeasonDefinition
This indicator is an informative indicator aiming to predict when the Altcoin season will start and when Bitcoin will enter the month season.
The average of the graph shows the dominance of altcoins other than BTC, ETH and USDT. If this value is over 30, the BTC says that the bull season is over. This value indicates that 20 to 30 BTC is in the bull season or accumulation. If this value is less than 20, it means that the subcoin season has begun.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
Dickey-Fuller Test for Mean Reversion and Stationarity **IF YOU NEED EXTRA SPECIAL HELP UNDERSTANDING THIS INDICATOR, GO TO THE BOTTOM OF THE DESCRIPTION FOR AN EVEN SIMPLER DESCRIPTION**
Dickey Fuller Test:
The Dickey-Fuller test is a statistical test used to determine whether a time series is stationary or has a unit root (a characteristic of a time series that makes it non-stationary), indicating that it is non-stationary. Stationarity means that the statistical properties of a time series, such as mean and variance, are constant over time. The test checks to see if the time series is mean-reverting or not. Many traders falsely assume that raw stock prices are mean-reverting when they are not, as evidenced by many different types of statistical models that show how stock prices are almost always positively autocorrelated or statistical tests like this one, which show that stock prices are not stationary.
Note: This indicator uses past results, and the results will always be changing as new data comes in. Just because it's stationary during a rare occurrence doesn't mean it will always be stationary. Especially in price, where this would be a rare occurrence on this test. (The Test Statistic is below the critical value.)
The indicator also shows the option to either choose Raw Price, Simple Returns, or Log Returns for the test.
Raw Prices:
Stock prices are usually non-stationary because they follow some type of random walk, exhibiting positive autocorrelation and trends in the long term.
The Dickey-Fuller test on raw prices will indicate non-stationary most of the time since prices are expected to have a unit root. (If the test statistic is higher than the critical value, it suggests the presence of a unit root, confirming non-stationarity.)
Simple Returns and Log Returns:
Simple and log returns are more stationary than prices, if not completely stationary, because they measure relative changes rather than absolute levels.
This test on simple and log returns may indicate stationary behavior, especially over longer periods. (The test statistic being below the critical value suggests the absence of a unit root, indicating stationarity.)
Null Hypothesis (H0): The time series has a unit root (it is non-stationary).
Alternative Hypothesis (H1): The time series does not have a unit root (it is stationary)
Interpretation: If the test statistic is less than the critical value, we reject the null hypothesis and conclude that the time series is stationary.
Types of Dickey-Fuller Tests:
1. (What this indicator uses) Standard Dickey-Fuller Test:
Tests the null hypothesis that a unit root is present in a simple autoregressive model.
This test is used for simple cases where we just want to check if the series has a consistent statistical property over time without considering any trends or additional complexities.
It examines the relationship between the current value of the series and its previous value to see if the series tends to drift over time or revert to the mean.
2. Augmented Dickey-Fuller (ADF) Test:
Tests for a unit root while accounting for more complex structures like trends and higher-order correlations in the data.
This test is more robust and is used when the time series has trends or other patterns that need to be considered.
It extends the regular test by including additional terms to account for the complexities, and this test may be more reliable than the regular Dickey-Fuller Test.
For things like stock prices, the ADF would be more appropriate because stock prices are almost always trending and positively autocorrelated, while the Dickey-Fuller Test is more appropriate for more simple time series.
Critical Values
This indicator uses the following critical values that are essential for interpreting the Dickey-Fuller test results. The critical values depend on the chosen significance levels:
1% Significance Level: Critical value of -3.43.
5% Significance Level: Critical value of -2.86.
10% Significance Level: Critical value of -2.57.
These critical values are thresholds that help determine whether to reject the null hypothesis of a unit root (non-stationarity). If the test statistic is less than (or more negative than) the critical value, it indicates that the time series is stationary. Conversely, if the test statistic is greater than the critical value, the series is considered non-stationary.
This indicator uses a dotted blue line by default to show the critical value. If the test-static, which is the gray column, goes below the critical value, then the test-static will become yellow, and the test will indicate that the time series is stationary or mean reverting for the current period of time.
What does this mean?
This is the weekly chart of BTCUSD with the Dickey-Fuller Test, with a length of 100 and a critical value of 1%.
So basically, in the long term, mean-reversion strategies that involve raw prices are not a good idea. You don't really need a statistical test either for this; just from seeing the chart itself, you can see that prices in the long term are trending and no mean reversion is present.
For the people who can't understand that the gray column being above the blue dotted line means price doesn't mean revert, here is a more simple description (you know you are):
Average (I have to include the meaning because they may not know what average is): The middle number is when you add up all the numbers and then divide by how many numbers there are. EX: If you have the numbers 2, 4, and 6, you add them up to get 12, and then divide by 3 (because there are 3 numbers), so the average is 4. It tells you what a typical number is in a group of numbers.
This indicator checks if a time series (like stock prices) tends to return to its average value or time.
Raw prices, which is just the regular price chart, are usually not mean-reverting (It's "always" positively autocorrelating but this group of people doesn't like that word). Price follows trends.
Simple returns and log returns are more likely to have periods of mean reversion.
How to use it:
Gray Column (the gray bars) Above the Blue Dotted Line: The price does not mean revert (non-stationary).
Gray Column Below Blue Line: The time series mean reverts (stationary)
So, if the test statistic (gray column) is below the critical value, which is the blue dotted line, then the series is stationary and mean reverting, but if it is above the blue dotted line, then the time series is not stationary or mean reverting, and strategies involving mean reversion will most likely result in a loss given enough occurrences.
