D2MAThe script is called "D2MA" (Distance to Moving Average). It calculates the distance between the closing price and a user-selected type of moving average (MA). It also plots this distance on a chart, allowing users to see how far the price is from the chosen moving average. Users can choose to display this distance as either an absolute value or as a percentage.
Input Parameters
Length (len): The number of bars (or periods) used to calculate the moving average.
Source (src): The price data used for calculations, typically the closing price.
Percentage Distance (pc): A boolean option to display the distance as a percentage instead of an absolute value.
MA Type (maType): The type of moving average to use.
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
Triple Exponential Moving Average (T3)
Power Weighted Moving Average (PWMA)
The script includes functions to calculate different types of moving averages:
The difference between the source price (e.g., closing price) and the calculated moving average. if Distance as Percentage , the distance expressed as a percentage of the moving average value.
Plotting the Data
Signal Line: The signal line changes colour (green or red) based on whether the distance is increasing or decreasing.
Visual Representation
How to Use
Identify Trends: By seeing how far the price is from a selected moving average, traders can gauge the strength of a trend.
Spot Reversals: Significant deviations from the moving average can signal potential reversals.
Kitaran
Empirical Kaspa Power Law Full Model v3.1🔶 First we need to understand what Power Laws are.
Power laws are mathematical relationships where one quantity varies as a power of another. They are prevalent in both natural and social systems, describing phenomena such as earthquake magnitudes, word frequencies, and wealth distributions. In a power-law relationship, a change in one quantity results in a proportional change in another, typically following a consistent and predictable mathematical pattern.
🔶 Why Do Power Laws work for Bitcoin and Kaspa?
Power laws work for Bitcoin and Kaspa due to the underlying principles of network dynamics and growth patterns that these cryptocurrencies exhibit. Here's how:
1. Network Growth and User Adoption:
Both Bitcoin and Kaspa grow as more users join their networks. The value of these networks often increases in a manner consistent with Metcalfe’s Law, which states that the value of a network is proportional to the square of its number of users. This relationship is a form of a power law, where network effects lead to exponential growth as more users participate.
2. Mining and Hash Rate:
The mining difficulty and hash rate in cryptocurrencies like Bitcoin and Kaspa adjust based on network activity. As more miners join, the difficulty increases to maintain a stable rate of block production. This self-adjusting mechanism creates feedback loops that can be described by power laws, ensuring the stability and security of the network over time.
3. Price Behavior:
Astrophysicist Giovanni Santostasi discovered that Bitcoin’s price follows a power-law distribution over time. This means that despite short-term volatility, Bitcoin’s long-term price behavior is predictable and adheres to specific mathematical patterns. Santostasi's model provides a framework for understanding Bitcoin’s price movements and forecasting future trends. He also discovered that Kaspa might be following a power-law aswell but it might be to early to tell because Kaspa hasn't been around for too long(2years).
4. Resource Allocation and System Stability:
As the price of Bitcoin or Kaspa increases, more resources are allocated to mining, leading to more sophisticated mining operations. This iterative process of investment and technological advancement follows a power-law pattern, driving the growth and stability of the network.
In summary, the application of power laws to Bitcoin and Kaspa offers a structured framework for understanding their price movements, network growth, and overall stability. These principles provide valuable predictive tools for long-term forecasting, helping to explain the dynamic behavior of these cryptocurrencies.
🔶 What does it look like on a chart?
Here is the Kaspa power law plotted on the KaspaUSD chart. Notice that the y-axis is in logarithmic scale. Unfortunately, TradingView does not allow the x-axis to be in logarithmic scale, which would otherwise make the power law appear as a straight line.
🔶 All the features of the Empirical Kaspa Power Law Full Model
This indicator includes a variety of scripts and tools, meticulously designed and developed to navigate the Kaspa market effectively.
🔹 Power Law & Deviation bands
The decision to use the lower two bands, marking an area between -40% to -50% below the power law, is based on historical analysis. Historically, this range has proven to be a great buying opportunity. In the case of Bitcoin, the bottom typically lies around -60% from the power law. However, for Kaspa, the bottom appears to be less distant from the power law. This discrepancy can be attributed to the differing supply dynamics of the two. Bitcoin undergoes a halving event approximately every four years, significantly reducing the rate at which new coins are introduced into circulation. This cyclical halving can lead to larger price fluctuations and a greater deviation from the power law. In contrast, Kaspa employs a more gradual reduction in its emission rate, with a 5% decrease each month. This consistent and incremental reduction helps Kaspa's price follow the power law more closely, resulting in less pronounced deviations. Consequently, the bottom for Kaspa tends to be closer to the power law, typically around -40% to -50%, rather than the -60% observed with Bitcoin.
The top two deviation bands are fitted to a few bubble data points, which are honestly not very reliable compared to the bottom bands that are based on a larger number of data points. When examining Bitcoin, we see that the bottoms are quite predictable due to the availability of thousands of data points, making it easier to identify patterns and trends.
However, predicting the tops is significantly more challenging because we lack a substantial amount of data for the peaks. This limited data makes it difficult to draw reliable conclusions about the upper deviation bands. As a result, while the bottom bands offer a robust framework for analysis, the top bands should be approached with caution due to their lesser reliability.
🔹 Alternating Sine wave
In observing the price behavior of Kaspa, an intriguing pattern emerges: it tends to follow a roughly four-month cycle. This cycle appears to alternate between smaller and larger waves. To capture this pattern, the sine wave in our indicator is designed to follow the power law, with both the top and bottom of the wave adjusting according to it.
Here's a simple explanation of how this works:
1. Four-Month Cycle: Empirically, Kaspa’s price seems to oscillate over approximately 120 days. This cycle includes periods of growth and decline, repeating every four months. Within these cycles, we observe alternating phases one smaller and one larger in amplitude.
2. Power Law Influence: The sine wave component of our indicator is not arbitrary; it follows a power law that predicts the general price trend of Kaspa. The power law essentially provides a baseline that reflects the longer-term price trajectory.
3. Diminishing Returns and Smoothing: To model diminishing returns, we adjust the amplitude of the sine wave over time, making it smaller as the cycle progresses. This helps to capture the natural tendency for price movements to become less volatile over longer periods. Additionally, the bottom of the sine wave adheres to the power law, ensuring it remains consistent with the overall trend.
🔹 Sine wave Cycle Start & End
Color transitions play a crucial role in visualizing different phases of the four-month cycle.
Based on empirical data, Kaspa experiences approximately 60 days of downward price action following each cycle peak, a period we refer to as the bear phase. This phase is followed by the bull phase, which also lasts around 60 days. To indicate the cycle peak, we have added a colored warning on the sine wave.
Cycle Start (Purple): The sine wave starts with a purple color, marking the beginning of a new cycle. This bull phase often represents a potential bottom or accumulation zone where prices are lower and stable, offering a strategic point for entering the market.
Cycle Top (Red): As the cycle progresses, the sine wave transitions through colors until it reaches red. This red phase indicates the top of the cycle, where the price is likely peaking. It's a critical area for investors to consider dollar-cost averaging (DCA) out of Kaspa, as it signifies a period of potential overvaluation and heightened risk.
These color transitions provide a visual guide to the market's cyclical nature, helping investors identify optimal entry and exit points. By following the sine wave's color changes, you can better time your investments, entering at the start of the cycle and considering exits as the cycle tops out.
🔹 Colored Deviation from the Power Law Bubbles
In trading, having a clear visual signal can significantly enhance decision-making, especially when dealing with complex models like power laws. This inspired the creation of the "deviation bubbles" in my indicator, which provides an intuitive, color-coded visual queue to help me, and other traders, better grasp market deviations and make timely trading decisions.
Here's a breakdown of how the deviation bubbles work:
1. Power Law Reference: The core of the indicator calculates a theoretical price level (the power law price) for Kaspa.
2. Deviation Calculation: For each day, the indicator computes the percentage deviation of the actual closing price from this power law price. This tells how much the market price diverges from the theoretically expected level.
3. Color-Coding Based on Deviation:
The deviation is categorized into various ranges (e.g., ≥ 100%, 90-100%, 80-90%, etc.).
Each range is assigned a distinct color, from red for extreme positive deviations to blue for extreme negative deviations.
This gradient helps in quickly identifying significant market deviations.
By integrating these bubbles into the chart, the indicator offers a simple yet powerful visual tool, aiding in recognizing critical market conditions without the need to delve into complex calculations manually. This approach not only enhances the ease of trading but also helps in overcoming the hesitation often faced when pulling the trigger on trades.
🔹 Projected Power Law Bands
Extends the current power law bands into the future using the same formula that defines the current power law.
Visual Representation: Dotted lines on the chart indicate the projected power law price and deviation bands.
Limitations: TradingView restricts how far these projections can extend, typically up to a reasonable future period.
These projected bands help anticipate future price movements, aiding in more informed trading decisions.
🔹 Projected Sine Wave
This projection continues to calculate the phase and amplitude, adjusting for diminishing returns and cycle transitions. It also estimates the future power law price, ensuring the projection reflects potential market dynamics.
Visual Representation: The projected sine wave is shown with dotted blue lines, providing a clear visual of the expected trend, aiding traders in their decision-making process.
Limitations: Again, TradingView restricts how far these projections can extend, typically up to a reasonable future period.
🔶 Why are all these different scripts made into one indicator?
As a trader and crypto analyst, I needed specific tools and customizations that no other indicator offered. Being a visual person, I rely heavily on visual triggers such as colors and patterns to make trading decisions. Initially, I developed this indicator for my personal use to enhance my market analysis with these visual cues. However, after sharing my insights, other traders expressed interest in using it. In response, I expanded the functionality and added various options to cater to a broader range of users.
This comprehensive indicator integrates multiple features into one tool, providing a powerful and flexible solution for analyzing market trends and making informed trading decisions. The use of colors and visual elements helps in quickly identifying key signals and market phases. The customizable options allow you to fine-tune the indicator to suit your specific needs, making it a versatile tool for both novice and experienced traders.
🔶 Usage & Settings:
This indicator is best used on the Daily chart for KASUSD - crypto because it uses a power law formula based on days.
🔹 Using the Indicator for 4-Month Cycles:
For traders interested in playing the 4-month cycles, this indicator provides a straightforward strategy. When the bubbles turn purple or the sine wave shows the purple start color, it signals a good time to dollar-cost average (DCA) into the market. Conversely, when the bubbles turn red or the cycle top is near, indicated by a red color, it’s time to DCA out of the Kaspa market. This visual approach helps traders make timely decisions based on color-coded signals, simplifying the trading process.
Historically, it was nearly impossible to accurately time all the 4-month cycle tops because they alternate each time. Without the combination of multiple scripts in this indicator, identifying these cyclical patterns and their respective peaks was extremely challenging. This integrated tool now provides a clear and reliable method for detecting these critical points, enhancing trading effectiveness.
🔹 Combining the visual queues for market extremes
The chart above illustrates the alignment of visual cues indicating market extremes. Notably, these visual cues—marked by red and purple boxes—historically pinpoint areas of extreme value or opportunities. When red aligns with red and purple aligns with purple, these zones have consistently indicated significant market extremes.
Understanding and recognizing these patterns provides a strategic advantage. By identifying these visual triggers, traders can plan and execute informed trades with greater confidence whenever similar scenarios unfold in the future.
Kaspa is perhaps one of the most cyclical and predictable cryptocurrencies in the market. Given its consistent behavior, traders might wonder why they would trade anything else. As long as there are no signs indicating a change in Kaspa's cyclical nature, there is no reason to make significant alterations to our predictions. This makes Kaspa an attractive option for traders seeking reliable and repeatable trading opportunities.
🔹 Settings & customization:
As a visually-oriented trader, it is essential to customize the appearance of indicators to effectively navigate the Kaspa market. The Indicator offers extensive customization options, allowing users to modify the colors of various elements to suit their preferences. For example, users can adjust the colors of the deviation bubbles, deviation bands, sine wave, and power law to enhance visual clarity and focus on specific data points. This level of personalization not only enhances the overall user experience but also ensures that the visual representation aligns with unique trading strategies, making it easier to interpret complex market data.
Additionally, users can change the power law inputs and other parameters as shown in the image. For instance, the Power Law Intercept and Power Law Slope can be manually adjusted, allowing traders to update these values. This flexibility is crucial as the future power law for Kaspa may evolve/change.
🔶 Limitations
Like any technical analysis tool, the Empirical Kaspa Power Law Full Model indicator has limitations. It's based on historical data, which may not always accurately predict future market movements.
🔶 Credits
I want to thank Dr. Giovanni Santostasi · Professor of physics and Mathematics.
He was one of the first who applied the concept of the power law to Bitcoin's price movements, which has been instrumental in providing insights into the long-term growth and potential future value of Bitcoin. Giovanni also offers coding classes on his Discord, which I attended. He personally taught me how to code specific things in Pine Editor and Python, sparking my interest in developing my own indicator.
Additionally, I would like to extend my gratitude to the following individuals for their invaluable contributions in terms of ideas, theories, formulas, testing, and guidance:
Forgowork, PlanC, Miko Genno, Chancellor, SavingFace, Kaspapero, JJ Venema.
Bitcoin Destiny Line Model v1.1The Bitcoin Destiny Line Model
Table of Contents
1. Overview
2. Analytical and Technical Techniques Employed
3. Objectives of the Bitcoin Destiny Line Model
4. Key Technical Components and Functionalities
4.1. Bitcoin Destiny Line and Heatmap
4.2. Halving Cycles Markers
4.3. Dynamic Repricing Rails with Diminishing Volatility Adjustment
4.4. Seasonal Dynamics
4.5. Support and Resistance Zones
4.6. Market Action Indicators
4.7. Cycle Projections
4.8. Heatmap Only
5. Settings
6. Different Strategies to Utilize the Model
6.1. Value-Based Entry Strategy
6.2. Long-Term Position Strategy
6.3. Scaling Out Strategy
6.4. Portfolio Rebalancing Strategy
6.5. Bear Market Strategy
6.6. Short-Term Trading Strategy
7. Recommendations and Disclosures
1. Overview
The Bitcoin Destiny Line Model is a technical analysis toolset designed exclusively for Bitcoin. It integrates a comprehensive suite of analytical methodologies to provide deep insights into Bitcoin's market dynamics focusing on long-term investment strategies.
By analyzing historical data through various technical frameworks, the model helps investors gain insight into the current market structure, cycle dynamics, direction, and trend of Bitcoin, assisting investors and traders with data-driven decision-making.
2. Analytical and Technical Techniques Employed
The model integrates a range of analytical techniques:
Cycle Analysis - Centers on the Bitcoin halving event to anticipate phases within the Bitcoin cycle.
Logarithmic Regression Analysis - Calculates the logarithmic growth of Bitcoin over time.
Standard Deviation - Measures how significantly the price action differs from the long-term logarithmic trend.
Fibonacci Analysis - Identifies support and resistance levels.
Multi-Timeframe Momentum - Analyzes overbought or oversold conditions across multiple periods.
Trendlines - Draws trendlines from expected cycle lows to expected cycle highs extending logarithmic and deviation lines into the future as projection lines.
3. Objectives of the Bitcoin Destiny Line Model
The model is crafted to deliver an empirical framework for Bitcoin investing:
Bitcoin Market Structure - Offers insights into Bitcoin’s market structure.
Identify Value Opportunities and Risk Areas - Pinpoints potential value-entry opportunities and recognizes when the market is over-extended.
Leverage Market Cycles - Utilizes knowledge of Bitcoin’s seasonal dynamics and halving cycles to inform investment strategies.
Mitigate Downside Risk - Provides indicators for potential market corrections, aiding in risk management and avoidance of buying at peak prices.
4. Key Technical Components and Functionalities
4.1. Bitcoin Destiny Line and Heatmap
The cycle low to cycle high line with a risk-based color-coded heatmap serves as a central reference for Bitcoin’s price trajectory.
It emphasizes the long-term trend indicating areas of value in cool colors and areas of risk in warm colors.
4.2. Halving Cycles Markers
Bitcoin halving events are marked on the chart with vertical lines forming anchor points for cycle analysis.
4.3. Dynamic Repricing Rails with Diminishing Volatility Adjustment
Repricing rails based on the long-term logarithmic trend highlight the rails on which Bitcoin's price will reprice up or down.
Adjusts to the diminishing volatility of the asset over time as it matures.
4.4. Seasonal Dynamics
Integrates Bitcoin's inherent seasonal trends to provide additional context for market conditions aligning with broader market analysis.
Understanding Bitcoin’s seasons:
Spring Awakening - The initial recovery phase where the market begins to rebound from a bear market showing early signs of improvement. This is an ideal time for cautious optimism. Investors should consider gradually increasing their positions in Bitcoin, focusing on accumulation as confidence in market recovery grows.
Blossom Boom - A market bottom has been confirmed by now and market interest continues to pick up ahead of the Bitcoin halving. This typically presents a great opportunity for investors to position themselves advantageously ahead of expected price movements. It’s a good time to review and adjust portfolios to align with anticipated trends.
Midsummer Momentum - This phase follows the Bitcoin halving, characterized by a sideways to upward price trend often supported by heightened interest and media coverage. It represents potentially the last opportunity in the cycle for investors to purchase Bitcoin at lower price levels unlikely to be seen again. Investors should closely monitor the market for value buying opportunities to bolster their long-term investment strategies.
Rocket Rise - A phase where Bitcoin prices are likely to surge dramatically driven by a mix of Fear of Missing Out (FOMO) among new investors and widespread media hype. The strategy here is twofold: long-term holders should hold steady to reap maximum gains whereas more speculative investors might look to capitalize on the volatility by taking profits at optimal moments before a potential correction.
Winter Whispers - Following a bull run, the market begins to cool, marked by some investors taking profits and consequently increasing price fluctuations and volatility. During this time, investors should remain vigilant, tightening stop-loss orders to safeguard gains. This phase may be suitable for those looking to liquidate a portion of their long-term investments. However, for an investor to be selling the majority of their Bitcoin holdings is generally not advisable as it could preclude benefiting from potential future appreciations.
Deep Freeze - The market enters a bearish phase with significant price declines and market corrections. It's a period of consolidation and resetting of price levels. The end of this stage could typically be seen as a buying opportunity for the long-term investor. Accumulating Bitcoin during this phase can be advantageous as prices are lower and provide a foundation for significant growth in the next cycle.
4.5. Support and Resistance Zones
Calculates key levels that inform stop-loss placements and trading size decisions enhancing trading strategy around the Bitcoin Destiny Line.
4.6. Market Action Indicators
Suggests potential trading actions for different market phases aiding traders in identifying investment/trading opportunities.
Risk Indicator - Signals when prices are extremely over-extended helping to avoid entries during potential peak valuations.
4.7. Cycle Projections
Extends repricing levels into the future providing a visual forecast of expected price movements and enhancing strategic planning capabilities.
Cycle-High Price Projection Range - Provides a probabilistic range for upcoming cycle peaks based on historical trends and current market analysis.
4.8. Heatmap Only
It is also possible to plot the heatmap only as a background or as a bar in a second indicator.
4.9. Complete Visual View
A complete view of all key elements switched on the model.
5. Settings
Users can select to only show specific elements or all elements of the model.
They can set the sensitivity of some of the model elements and adjust certain view settings.
6. Different Strategies to Utilize the Model
The following strategies are enabled by the Bitcoin Destiny Line model:
6.1. Value-Based Entry Strategy
Investors can optimize their investment strategy by deploying investable cash either as a lump sum or on a dollar-cost averaging basis upon the display of a value indicator (Up-Triangles) which signals the highest probability for value entries.
6.2. Long-Term Position Strategy
As an alternative, investors may prefer to continue deploying investable funds while cooler colors (green or blue) are displayed on the value map, indicating favorable conditions for long-term positions.
6.3. Scaling Out Strategy
Investors may choose to scale out some of their investment upon the display of a risk indicator (circles) reducing exposure to potential downturns.
6.4. Portfolio Rebalancing Strategy
A sound strategy can also be to follow a portfolio rebalancing approach by deploying available investable cash upon the display of a value indicator. Rebalance the portfolio to maintain 25% in cash upon the display of a risk indicator. Adjust this ratio as subsequent risk indicators are triggered, deploying available cash upon future value signals.
6.5. Bear Market Strategy
In a bear market, traders may seek short positions upon the display of the Continued Downward Momentum indicator (Down Triangles) capitalizing on declining market trends.
6.6. Short-Term Trading Strategy
Traders can use hourly or 4-hourly data along with the daily Price Rails and Heatmap Bar for short-term positions. They may incorporate other preferred indicators such as RSI for entry/exit decisions.
7. Recommendations and Disclosures
Investors are recommended to take a prudent approach. It is not recommended for investors to scale out completely or significantly reduce the largest portion of their long-term Bitcoin positions in hopes of buying back at lower prices unless they have a compelling reason to do so. The future market conditions may not replicate past opportunities making this strategy uncertain. However, scaling out a smaller portion such as 25% can offer a high potential for an asymmetric risk-reward ratio. This approach is likely to provide a higher risk-adjusted return compared to traditional dollar-cost averaging or random lump sum adjustments.
The Bitcoin Destiny Line Model leverages 13.5 years of available price data across four complete Bitcoin market cycles.
While each additional cycle enriches the model's robustness and enhances the reliability of its forecasts, it is crucial for users to understand that historical trends are indicative of probable future directions and potential price ranges. Users should be cognizant that past performance is not a definitive predictor of future results and should not be the sole basis for investment decisions.
Moving Average CyclesMoving Average Cycles Indicator
Description:
The Moving Average Cycles indicator is a versatile tool designed to help traders identify and analyze bullish and bearish cycles based on price movements relative to a moving average. This indicator offers valuable insights into market trends and potential reversal points.
Key Features:
Customizable Moving Average: Users can adjust the MA period and resolution (Daily, Weekly, Monthly) to suit their trading style.
Cycle Identification: The indicator tracks bull and bear cycles, providing visual cues through color-coded histograms.
Comprehensive Metrics: A detailed table displays crucial cycle statistics, including:
Current cycle information (candles and % distance from MA)
Maximum and average cycle lengths (in candles)
Maximum and average percentage distances from the MA
How to Use:
Apply the indicator to your chart and adjust the MA period and resolution as needed.
Green histograms represent bullish cycles, while red histograms indicate bearish cycles.
Use the metrics table to gain insights into historical cycle behavior and current market positioning.
This indicator is designed to complement your existing trading strategy by providing a clear visual representation of market cycles and detailed statistical information. It can be particularly useful for identifying potential trend reversals and gauging the strength of current trends compared to the past.
Note: Past performance does not guarantee future results. This indicator is meant for informational purposes only and should not be considered as financial advice. Always combine multiple analysis tools and conduct your own research before making trading decisions.
This script is published as open-source under the Mozilla Public License 2.0. Feel free to use and modify it, but please provide appropriate credit if you build upon this work.
I hope you find this Moving Average Cycles indicator helpful in your trading journey. If you have any questions or suggestions for improvement, please feel free to leave a comment below.
Asset Drawdown & Drawdown HeatMap [InvestorUnknown]Overview
The "Asset Drawdown & Drawdown HeatMap" indicator is designed for educational purposes to help users visualize and analyze the drawdowns of various assets. It highlights both recent and historical drawdowns, offering valuable insights into the performance and risk of different investments. Additionally, it can serve as a complementary analysis tool for trading and investing decisions.
Features
Drawdown Calculation:
Computes the drawdown from the highest value (ATH) to the current value, showing the percentage decline.
Displays both the current drawdown and the maximum historical drawdown for the selected assets.
HeatMap Visualization:
Uses a gradient color scheme to represent the magnitude of drawdowns over a specified lookback period.
Helps identify periods of significant decline and recovery visually.
Multiple Assets:
Supports up to 10 different assets (adding more would make it harder to see the drawdowns of different assets), allowing users to compare drawdowns across various symbols.
Each asset can be individually plotted and color-coded for clarity.
Customizable Settings:
User inputs for high and low value calculations, color preferences, and lookback periods.
Option to color bars based on the drawdown heatmap.
Detailed Functionality
Drawdown Calculation:
The DD() function calculates the current drawdown and the maximum historical drawdown based on the high and low values.
The drawdown is calculated as 100 - (lowvalue / ATH * 100), where ATH is the highest value observed so far.
// - - - - - Custom Function - - - - - //{
DD() =>
ATH = highvalue
ATH := na(ATH ) ? highvalue : math.max(highvalue, ATH )
Drawdown = 100 - lowvalue / ATH * 100
MaxDrawdown = Drawdown
MaxDrawdown := na(MaxDrawdown ) ? Drawdown : math.max(Drawdown, MaxDrawdown )
//}
Security Request:
Uses the request.security() function to fetch drawdown data for each specified asset on a daily timeframe.
Computes both current drawdown (TnDD) and maximum drawdown (TnMDD) for each asset.
// - - - - - Create Variables - - - - - //{
= request.security("", "1D", DD()) // Chart
= request.security(t1, "1D", DD())
= request.security(t2, "1D", DD())
= request.security(t3, "1D", DD())
= request.security(t4, "1D", DD())
= request.security(t5, "1D", DD())
= request.security(t6, "1D", DD())
= request.security(t7, "1D", DD())
= request.security(t8, "1D", DD())
= request.security(t9, "1D", DD())
= request.security(t10, "1D", DD())
//}
Plotting:
Plots the drawdown values for each asset on the chart, with the option to enable or disable plotting for individual assets.
Colors the plotted lines and labels based on user-specified preferences.
HeatMap:
Creates a heatmap color gradient based on the drawdown values over the lookback period.
Colors the bars on the chart according to the heatmap to visualize drawdown severity over time.
// - - - - - HeatMap - - - - - //{
heatcol = color.from_gradient(T0DD, ta.lowest(T0DD,lookback), ta.highest(T0DD,lookback), topcol, botcol)
barcolor(colbars ? heatcol : na)
//}
Labels:
Displays labels for each asset's drawdown value at the end of the chart for quick reference.
This indicator is an excellent tool for educational purposes, helping users understand drawdown dynamics and their implications on asset performance. It also provides a visual aid for monitoring and comparing drawdowns across multiple assets, which can be beneficial for making informed trading and investment decisions.
US Presidential Elections (Names & Dates)US Presidential Elections (Names & Dates)
Description :
This indicator marks key dates in US presidential history, highlighting both election days and inauguration dates. It's designed to provide historical context to your charts, allowing you to see how major political events align with market movements.
Key Features:
• Displays US presidential elections from 1936 to 2052
• Shows inauguration dates for each president
• Customizable colors and styles for both election and inauguration markers
• Toggle visibility of election and inauguration labels separately
• Adapts to different timeframes (daily, weekly, monthly)
• Includes president names for historical context
The indicator uses yellow labels for election days and blue labels for inauguration dates. Election labels show the year and "Election", while inauguration labels display the name of the incoming president.
Customization options include:
• Colors for election and inauguration labels and text
• Line widths for both types of events
• Label placement styles
This tool is perfect for traders and analysts who want to correlate political events with market trends over long periods. It provides a unique perspective on how presidential cycles might influence financial markets.
Note: Future elections (2024 onwards) are marked with a placeholder (✅) as the presidents are not yet known.
Use this indicator to:
• Identify potential market patterns around election cycles
• Analyze historical market reactions to specific presidencies
• Add political context to your long-term chart analysis
Enhance your chart analysis with this comprehensive view of US presidential history!
Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
MA Optimizer Simplified [CHE]Introduction:
The MA Optimizer Simplified is a powerful tool for traders and analysts who want to compare and optimize various moving averages (MA). This tool is specifically designed to identify the best or worst performers among a variety of moving averages based on their cumulative performance.
Features and Benefits:
1. Versatility:
- Supports multiple types of moving averages, including:
- Simple Moving Average (SMA): A basic MA calculated by averaging the closing prices over a specified period.
- Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
- Weighted Moving Average (WMA): Assigns more weight to recent data, but in a linear fashion.
- Volume-Weighted Moving Average (VWMA): Averages prices based on volume, giving more importance to periods with higher trading volume.
- Hull Moving Average (HMA): Designed to reduce lag while improving smoothness.
- Smoothed Moving Average (SMMA or RMA): Averages prices over a longer period, providing a smoother line.
- Bollinger Bands: Uses SMA as a basis and adds upper and lower bands based on standard deviations.
- T3: A smoother and less lagging MA that reduces market noise.
- Allows users to easily switch between MA types and test different periods.
2. Performance Evaluation:
- Calculates the cumulative performance of up to ten different MAs.
- Automatically identifies the best or worst performer based on user selection (Best or Worst).
3. Crossover Detection:
- Detects crossovers of prices and MAs to measure performance.
- Provides clear visual signals when the price crosses a moving average.
4. Visual Representation:
- Plots the best MA indicator on the chart, dynamically changing its color based on price movement relative to the MA.
- Table functionality to display the performance of each MA, including the length and achieved performance in percentage.
5. Customizable Settings:
- Customizable settings for table size and position as well as colors for better visualization and user-friendliness.
- Flexibility in selecting the number of candles that must be above or below the MA before a signal is triggered.
Special Features:
1. T3 Indicator:
- The T3 indicator provides a smoother representation and reduces market noise, leading to more precise signals.
2. Crossover and Crossunder Logic:
- The script includes advanced logic for detecting crossover and crossunder events to identify accurate entry points.
3. Dynamic Color Change:
- The best MA indicator changes color based on the number of candles above or below the MA, helping to quickly recognize market sentiment.
4. Comprehensive Performance Analysis:
- The calculation of cumulative performance for each MA allows for detailed analysis and helps identify the most effective trading strategies.
Conclusion:
The MA Optimizer Simplified is an essential tool for any trader looking to analyze and optimize the performance of various moving averages. With its versatile features and user-friendly settings, it offers a comprehensive and efficient solution for technical analysis.
Best regards, Chervolino
Fourier Extrapolation of PriceOverview
The "Fourier Extrapolation of Price" indicator utilizes Fourier Transform methods to analyze and predict future price movements based on historical data. By decomposing price series into their frequency components, this indicator provides a forecast of future price trends, making it a powerful tool for traders seeking advanced analytical techniques.
Key Features
Fourier Transform Analysis: Applies Discrete Fourier Transform (DFT) to the price series to identify frequency components.
Price Prediction: Forecasts future prices based on the dominant frequencies detected in the historical data.
Customizable Parameters: Allows users to set the length of historical data for analysis and the forecast period.
Visual Representation: Plots historical and forecasted prices for easy comparison.
How It Works
The indicator first normalizes the price series by subtracting the mean. It then applies the Discrete Fourier Transform (DFT) to the normalized data, extracting the real and imaginary parts. The magnitude and phase of these components are used to forecast future prices through an inverse DFT. Finally, the forecasted prices are denormalized and plotted alongside the historical prices on the chart.
Usage Instructions
Configure Parameters: Set the length of the historical data (DFT Length) and the forecast period (Forecast Length) to suit your analysis.
Apply to Chart: Add the indicator to your chart to start the analysis. Note that the computation may take a minute to complete due to the complexity of the Fourier Transform.
Analyze Results: Review the plotted forecasted prices (in red) alongside the historical prices (in blue) to identify potential future trends.
Trading Decisions: Use the forecasted price trends to inform your trading decisions, such as identifying potential entry and exit points based on predicted market movements.
Note : Due to the computational complexity of the Fourier Transform, the prediction may take a minute to load. Please be patient as the indicator processes the data to provide accurate forecasts.
This indicator is useful for traders who:
Advanced Analysis: Seek advanced mathematical techniques for market analysis.
Trend Prediction: Want to forecast future price movements based on historical data.
Customizable Analysis: Prefer customizable parameters for tailored analysis.
Visual Insights: Appreciate visual representation of historical and forecasted prices for better decision-making.
[MAD] Custom Session VWAP BandsOverview
This indicator helps visualize the Volume Weighted Average Price (VWAP) and its associated standard deviation bands over specified time periods, providing traders with a clear understanding of price trends, volatility, and potential support/resistance levels.
Inputs
Deviation
StDev mult 1: Multiplier for the first standard deviation band (Default: 1.0)
StDev mult 2: Multiplier for the second standard deviation band (Default: 2.0)
StDev mult 3: Multiplier for the third standard deviation band (Default: 3.0)
StDev mult 4: Multiplier for the fourth standard deviation band (Default: 4.0)
Line width: Width of the lines for the bands (Default: 2)
Custom Vwap session reset settings
Many different options are considered when a session is going to be reset.
Plot and Fill Options
Enable Fills: Enable/disable filling between bands.
Plot +4: Enable/disable plotting the +4 standard deviation band.
Plot +3: Enable/disable plotting the +3 standard deviation band.
Plot +2: Enable/disable plotting the +2 standard deviation band.
Plot +1: Enable/disable plotting the +1 standard deviation band.
Plot VWAP: Enable/disable plotting the VWAP line.
Plot -1: Enable/disable plotting the -1 standard deviation band.
Plot -2: Enable/disable plotting the -2 standard deviation band.
Plot -3: Enable/disable plotting the -3 standard deviation band.
Plot -4: Enable/disable plotting the -4 standard deviation band.
How to Use the Indicator
Adding the Indicator
Add the indicator to your chart through your trading platform's indicator menu.
Configuring the VWAP Reset
Specify reset intervals based on time, days of the week, or specific dates.
Adjust the time zone if necessary.
Customizing Standard Deviation Bands
Set the multipliers for the standard deviation bands.
Choose line width for better visualization.
Enabling Plots and Fills
Select which bands to display.
Enable or disable fills between the bands.
Practical Application of VWAP Bands
Understanding VWAP
VWAP is a trading benchmark that calculates the average price a security has traded at throughout the day based on volume and price. It is primarily used for intraday trading but can also offer insights during end-of-day reviews.
Using VWAP for Trading
Intraday Trading
Entry and Exit Points: VWAP can help identify optimal buy and sell points. Buy when the price is above VWAP and sell when it's below.
Support and Resistance: VWAP often acts as a dynamic support/resistance level. Prices tend to revert to VWAP, making it a crucial level for intraday traders.
Trend Confirmation
Uptrends and Downtrends: In an uptrend, the price will generally stay above VWAP. Conversely, in a downtrend, it will stay below. Use this to confirm market direction.
Combining with Other Indicators
Moving Averages and Bollinger Bands: Combining VWAP with these indicators can provide a more robust trading signal, confirming trends and potential reversals.
Setting Stop-Loss and Profit Targets
Conservative Stop Orders: Place stop orders at recent lows for pullback trades.
Profit Targets: Use daily highs or Fibonacci extension levels to set profit targets.
Strategies for Using VWAP
Pullback Strategy
Buy during pullbacks to VWAP in an uptrend, and sell during rallies to VWAP in a downtrend.
Breakout Strategy
Look for breakouts above/below VWAP after the market open to capitalize on new trends.
Momentum Trading
Use VWAP to confirm the strength of a trend. Buy when the price is consistently above VWAP and sell when it's consistently below.
Institutional Strategies
Institutional traders use VWAP to execute large orders without causing significant market impact, ensuring trades are made around the average price.
By incorporating these strategies, traders can better understand market dynamics, make informed trading decisions, and manage their risk effectively.
Some setup possibilities
MTF Regime Filter II [CHE]Regime Filter II - Comprehensive Guide
Introduction
The "Regime Filter II " indicator is a tool designed to help traders identify market trends by smoothing price data and applying a color scheme to visualize bullish and bearish conditions. This guide provides a detailed explanation of the script's functionality, benefits, and how to use it effectively in TradingView.
Key Benefits
1. Trend Identification: Smooths price data to highlight underlying trends, making it easier for traders to spot potential buying or selling opportunities.
2. Visual Clarity: Uses distinct color schemes to differentiate between bullish and bearish market conditions, enhancing visual analysis.
3. Customization: Offers various settings to adjust smoothing and averaging lengths, choose between different color schemes, and set visibility for different timeframes.
4. Neutral Candle Option: Provides an option to display neutral candles for clearer visual representation when market conditions are neither strongly bullish nor bearish.
5. Timeframe Adaptability: Includes functions to determine appropriate step sizes based on different timeframes, ensuring the indicator remains accurate across various trading periods.
Script Breakdown
1. Indicator Declaration
The script starts by declaring itself as a TradingView indicator using the latest version of Pine Script. This sets up the framework for the indicator's functionality.
2. User Inputs for Smoothing and Averaging Lengths
The script allows users to input specific lengths for smoothing and averaging intervals. These inputs are crucial for determining how the price data is processed to identify trends. By adjusting these lengths, users can fine-tune the sensitivity of the indicator to market movements.
3. Color Scheme Selection
Users can choose between two color schemes: "Traditional" and "WT1 0 Rule". The selected color scheme will determine how the indicator colors the candles to represent bullish and bearish conditions. This customization enhances the visual appeal and usability of the indicator according to personal preferences.
4. Settings for Timeframe Visibility
The script includes settings that allow users to specify which timeframes the indicator should be visible on. This feature helps traders focus on the most relevant timeframes for their trading strategies. Additionally, users can set the number of recent candles to display, providing a clear view of the most recent market trends.
5. Color Definitions
The indicator defines specific colors for bearish and bullish candles. Bearish candles are colored red, while bullish candles are green. These color definitions are applied based on the selected color scheme and the calculated trend, providing a quick visual reference for market conditions.
6. Time Constants
To manage different timeframes effectively, the script uses constants that represent various time intervals in milliseconds, such as minutes, hours, and days. These constants are used to convert timeframes into a format that the script can work with to determine the appropriate step size for calculations.
7. Step Size Determination
The script includes a function that determines the step size based on the selected timeframe. This function ensures that the indicator adapts to different timeframes, maintaining its accuracy and relevance across various trading periods. The step size is calculated based on time intervals, and appropriate labels (like "60", "240", "1D") are assigned.
- For timeframes less than or equal to 1 minute, the step size is set to "60".
- For timeframes less than or equal to 5 minutes, the step size is set to "240".
- For timeframes less than or equal to 1 hour, the step size is set to "1D" (daily).
- For timeframes less than or equal to 4 hours, the step size is set to "3D" (three days).
- For timeframes less than or equal to 12 hours, the step size is set to "7D" (weekly).
- For timeframes less than or equal to 1 day, the step size is set to "1M" (monthly).
- For timeframes less than or equal to 1 week, the step size is set to "3M" (three months).
- For all other timeframes, the step size is set to "12M" (yearly).
8. Trend Calculation
The core of the indicator is its ability to calculate market trends. Here's a detailed breakdown of how the `calculateTrend` function works:
- Initialization: Variables for the middle price and scale, and summations of high/low prices and ranges, are initialized.
- Summation Loop: A loop runs over the smoothing length to calculate the sum of high and low prices and their range.
- Middle and Scale Calculation: The middle price is determined as the average of high/low sums, and the scale is calculated as a fraction of the average range.
- Normalization: The high, low, and close prices are normalized based on the middle price and scale.
- HT Calculation: The normalized prices are smoothed using a simple moving average (SMA).
- Frequency and Exponential Calculations: The frequency and related constants (a, c1, c2, c3) are calculated for further smoothing.
- Smoothed Moving Average (SMA): A smoothed moving average is computed using the HT values and exponential constants.
- WT1 and WT2 Calculation: The final smoothed values (WT1) and their average (WT2) are derived.
9. Color Application Based on Trend
Once the trend is calculated, the script applies the appropriate color to the candles based on the selected color scheme. This function ensures that the visual representation of the trend is consistent with the user’s preferences.
10. Label Plotting for Timeframes
If the option to display timeframe labels is enabled, the script plots labels on the chart to indicate the current timeframe. This feature helps users quickly identify which timeframe they are analyzing.
11. Shape Plotting Based on Trend and Color Scheme
The indicator plots shapes (squares) on the chart based on the calculated trend and selected color scheme. These shapes provide an additional visual cue for market conditions, enhancing the overall clarity of the indicator.
12. Neutral Candle Color Option
The script includes an option to set the color of neutral candles when market conditions are neither strongly bullish nor bearish. This option helps traders better visualize periods of market indecision.
Summary
The "Regime Filter II " is a powerful and customizable tool for traders, offering clear visual cues for market trends and adaptability to various timeframes. By smoothing price data and applying intuitive color schemes, it helps traders make more informed decisions. With features like adjustable smoothing lengths, multiple color schemes, and optional neutral candle displays, this indicator enhances market analysis and trading strategy development. By following this comprehensive guide, traders can effectively utilize the "Regime Filter II " indicator to enhance their market analysis and make more informed trading decisions.
Best regards
Weighted Global Liquidity Index (WGLI) ROCThe Weighted Global Liquidity Index (WGLI) ROC indicator calculates the rate of change (ROC) of the WGLI, providing valuable insights into the dynamics of global liquidity. The WGLI consolidates major central bank balance sheets and key financial indicators, such as Foreign Exchange Reserves, Interbank Rates, and Interest Rates, converted to USD and expressed in trillions. Specific US accounts like the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP) are subtracted from the Federal Reserve's balance sheet for a more detailed view of US liquidity.
Using both the WGLI and the WGLI ROC together allows users to track changes in global liquidity and understand policy trajectories and economic conditions. This dual approach offers insights into asset pricing and helps investors make informed decisions about capital allocation.
Feel free to explore and customize the WGLI ROC script to suit your analysis needs!
Weighted Global Liquidity Index (WGLI)The Weighted Global Liquidity Index (WGLI) provides a comprehensive view of major central bank balance sheets from around the world, using data converted to USD for consistency and expressed in trillions. This indicator includes specific US accounts like the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), which are subtracted from the Federal Reserve's balance sheet to offer a more detailed perspective on US liquidity.
The WGLI incorporates not only the balance sheets but also additional key financial indicators such as Foreign Exchange Reserves, Interbank Rates, and Interest Rates, weighted by their global liquidity importance. The regions and central banks included are:
Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP)
European Central Bank (ECB)
People's Bank of China (PBC)
Bank of Japan (BOJ)
Bank of England (BOE)
Bank of Canada (BOC)
Reserve Bank of Australia (RBA)
Reserve Bank of India (RBI)
Swiss National Bank (SNB)
Central Bank of the Russian Federation (CBR)
Central Bank of Brazil (BCB)
Bank of Korea (BOK)
Reserve Bank of New Zealand (RBNZ)
Sweden's Central Bank (Riksbank)
Central Bank of Malaysia (BNM)
This tool is designed for anyone interested in gaining a snapshot of global liquidity to interpret macroeconomic trends. By examining these balance sheets and additional indicators, users can understand policy trajectories and evaluate the global economic climate. It also offers insights into asset pricing and helps investors make informed capital allocation decisions.
Feel free to explore and customize the WGLI script on Trading View to suit your analysis needs!
US M2### Relevance and Functionality of the "US M2" Indicator
#### Relevance
The "US M2" indicator is relevant for several reasons:
1. **Macro-Economic Insight**: The M2 money supply is a critical indicator of the amount of liquidity in the economy. Changes in M2 can significantly impact financial markets, including equities, commodities, and cryptocurrencies.
2. **Trend Identification**: By analyzing the M2 money supply with moving averages, the indicator helps identify long-term and short-term trends, providing insights into economic conditions and potential market movements.
3. **Trading Signals**: The indicator generates bullish and bearish signals based on moving average crossovers and the difference between current M2 values and their moving averages. These signals can be useful for making informed trading decisions.
#### How It Works
1. **Data Input**:
- **US M2 Money Supply**: The indicator fetches the US M2 money supply data using the "USM2" symbol with a monthly resolution.
2. **Moving Averages**:
- **50-Period SMA**: Calculates the Simple Moving Average (SMA) over 50 periods (months) to capture short-term trends.
- **200-Period SMA**: Calculates the SMA over 200 periods to identify long-term trends.
3. **Difference Calculation**:
- **USM2 Difference**: Computes the difference between the current M2 value and its 50-period SMA to highlight deviations from the short-term trend.
4. **Amplification**:
- **Amplified Difference**: Multiplies the difference by 100 to make the deviations more visible on the chart.
5. **Bullish and Bearish Conditions**:
- **Bullish Condition**: When the current M2 value is above the 50-period SMA, indicating a positive short-term trend.
- **Bearish Condition**: When the current M2 value is below the 50-period SMA, indicating a negative short-term trend.
6. **Short-Term SMA of Amplified Difference**:
- **14-Period SMA**: Applies a 14-period SMA to the amplified difference to smooth out short-term fluctuations and provide a clearer trend signal.
7. **Plots and Visualizations**:
- **USM2 Plot**: Plots the US M2 data for reference.
- **200-Period SMA Plot**: Plots the long-term SMA to show the broader trend.
- **Amplified Difference Histogram**: Plots the amplified difference as a histogram with green bars for bullish conditions and red bars for bearish conditions.
- **SMA of Amplified Difference**: Plots the 14-period SMA of the amplified difference to track the trend of deviations.
8. **Moving Average Cross Signals**:
- **Bullish Cross**: Plots an upward triangle when the 50-period SMA crosses above the 200-period SMA, signaling a potential long-term uptrend.
- **Bearish Cross**: Plots a downward triangle when the 50-period SMA crosses below the 200-period SMA, signaling a potential long-term downtrend.
### Summary
The "US M2" indicator provides a comprehensive view of the US M2 money supply, highlighting significant trends and deviations. By combining short-term and long-term moving averages with amplified difference analysis, it offers valuable insights and trading signals based on macroeconomic liquidity conditions.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
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.
Percentile Nearest Rank Without Arrays [CHE] Presentation of the "Percentile Nearest Rank Without Arrays " Indicator
The "Percentile Nearest Rank Without Arrays " is a robust trading indicator designed to calculate the percentile value of a specific price within a defined time frame. This indicator provides traders with a visual representation that helps identify market trends and potential turning points.
Key Features and Functions:
- Percentile Calculation: The indicator calculates the percentile of the closing price within a specified period (default length is 15 periods). This allows traders to view the current price in the context of its historical distribution.
- Customizable Parameters: Traders can adjust the length of the observed period and the desired percentile value, making the analysis more tailored to their trading strategies.
- Color-Coded Visualization: The indicator uses color coding to signal whether the current closing price is above (green) or below (red) the calculated percentile value, providing visual clarity and quick decision-making.
- Efficiency Without Arrays: By avoiding the use of arrays, the indicator is more efficient in terms of computation and memory usage. This results in faster performance, especially when dealing with large datasets or real-time data.
Importance for Traders:
1. Trend Identification: By analyzing whether the current price is above or below a specific percentile value, traders can identify trends early and act accordingly.
2. Risk Management: The indicator helps traders better understand volatility and price distribution, leading to more effective risk management.
3. Trading Strategies: It can be used as part of trading strategies to identify entry and exit points based on statistical distributions.
4. Simplicity and Efficiency: As the indicator operates without the use of arrays, it is more efficient and simpler to implement, reducing computation time and improving the performance of the trading platform.
Scientific Explanation of Percentile Nearest Rank:
The Percentile Nearest Rank method is a statistical technique used to determine the relative standing of a value within a data set. For a given dataset of length \( n \) and a desired percentile \( p \), the method follows these steps:
1. Index Calculation: The index corresponding to the desired percentile is calculated using the formula:
index = ( p / 100 n ) -1
where "ceiling" denotes rounding up to the nearest integer.
2. Value Sorting: The values in the dataset are conceptually sorted from smallest to largest.
3. Count Comparison: For each value in the dataset, count how many values are smaller. When the count matches the calculated index, the value at this position is the percentile value.
4. Result Assignment: The value identified as the percentile value is then used for further analysis or plotting.
This method is advantageous for trading because it provides a non-parametric way to understand price distributions, making it less sensitive to outliers and more robust in volatile markets.
Scientific Context and Utility:
- Statistical Robustness: Unlike mean and median, the percentile provides a robust measure of the data distribution, less influenced by extreme values. This robustness is crucial for traders dealing with volatile markets.
- Non-Parametric Analysis: Percentiles do not assume any underlying distribution (e.g., normal distribution) of the data, making the analysis more flexible and broadly applicable.
- Quantitative Decision Making: By using percentiles, traders can make data-driven decisions based on the relative standing of current prices within historical data, enhancing the objectivity of their strategies.
- Efficiency Without Arrays: Avoiding the use of arrays reduces memory consumption and computational overhead, making the indicator more suitable for real-time applications and large datasets. This improves overall performance and responsiveness on trading platforms, which is crucial for making timely trading decisions.
In summary, the "Percentile Nearest Rank Without Arrays " indicator is a powerful tool for traders seeking to integrate statistical price distribution insights into their trading strategies. It provides a robust, non-parametric, and visually intuitive method to analyze market trends and volatility, while offering enhanced computational efficiency by avoiding the use of arrays.
MTF WaveTrend [CryptoSea]The MTF WaveTrend Indicator is a sophisticated tool designed to enhance market analysis through multi-timeframe WaveTrend calculations. This tool is built for traders who seek to identify market momentum and potential reversals with higher accuracy.
In the example below, we can see all the choosen timeframes agree on bearish momentum.
Key Features
Multi-Timeframe WaveTrend Analysis: Tracks WaveTrend values across multiple timeframes to provide a comprehensive view of market momentum.
Customizable Colour Rules: Offers three different colour rules (Traditional, WT1 0 Rule, WT1 & WT2 0 Rule) to suit various trading strategies.
Timeframe Visibility Control: Allows users to enable or disable specific timeframes, providing flexibility in analysis.
Clear Visual Indicators: Uses color-coded squares and labels to clearly display WaveTrend status across different timeframes.
Candle Colouring Option: Includes a setting for neutral candle coloring to enhance chart readability.
This example shows what can happen when all timeframes start alligning with eachother.
How it Works
WaveTrend Calculation: Computes the WaveTrend oscillator by applying a series of exponential moving averages and scaling calculations.
Multi-Timeframe Data Aggregation: Utilizes the `request.security` function to gather and display WaveTrend values from various timeframes without repainting issues.
Conditional Plotting: Displays visual cues only when higher timeframes align with the selected timeframe, ensuring relevant and reliable signals.
Dynamic Colour Rules: Adjusts the indicator colors based on the chosen rule, whether it's a traditional crossover, WT1 crossing zero, or both WT1 & WT2 crossing zero.
Traditional: Colors are determined by the relationship between WT1 and WT2. If WT1 is greater than WT2, it is bullish (bullColour), otherwise bearish (bearColour).
WT1 0 Rule: Colors are based on whether WT1 is above or below zero. WT1 above zero is bullish (bullColour), below zero is bearish (bearColour).
WT1 & WT2 0 Rule: A more complex rule where both WT1 and WT2 need to be above zero for a bullish signal (bullColour) or both below zero for a bearish signal (bearColour). If WT1 and WT2 are not in agreement, a neutral color (neutralColour) is displayed.
This indicator will make sure that the lowest timeframe you can see data from will be the timeframe you are on. This is to avoid false signals as you cannot display 3 x 5 minute candles whilst looking at the 15 minute candle.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of WaveTrend movements across different timeframes.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with multi-timeframe WaveTrend analysis.
Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of WaveTrend data.
The MTF WaveTrend Indicator by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
Wosabi 2 Time Cycle Gann and candles v3Important Note: This indicator relies on your expertise in time cycles and does not provide any buy or sell signals. It helps you by automating the drawing of minor and major time cycles and digital gates, relying on your personal expertise. It simply draws a vertical line every 12 candles from your selected starting candle and repeats this until the cycle is complete after 12 minor cycles. Additionally, it calculates digital gates, and you need to configure the settings to choose the type of calculation for the digital gate, whether it's based on the commonly known digital gates (12-15-18) or gate targets, for example (369-693-936-258-582-825-147...), and then multiply them based on the price difference you input to draw horizontal lines for the expected gates. If a gate is broken, the price will continue to the next gate.
This indicator is an auxiliary tool for drawing the five, seven, ten, and even fifty or more cycles that Gann discussed. With its default settings, it draws vertical lines every 12 candles for 12 minor cycles (modifiable), forming a major cycle of 144 candles, which is the ten-cycle. (You should have experience in time cycle patterns as explained by Gann to know if the trend will continue up or down over time). The indicator only draws the columns that define the minor cycles, and their total forms the major cycle.
- The indicator also draws digital gates as horizontal lines, which you need to set manually and adjust the price difference from one currency to another in the settings.
- When adding the indicator for the first time, you must specify the starting candle of the trend, whether at a bottom or a top, and determine the highest or lowest price expected to reach five digital gates. If you expect an upward cycle, set the price at the resistance area where you expect the price to bounce. If you want to draw a downward cycle, set the price at the support area where you expect the bounce. You can later adjust the gates from the settings if you want to calculate them according to the digital gate. For example, if you start drawing the downward cycle for Bitcoin, as in the above picture when the highest price was 73881, we add the first two digits 7+3=10, 1+0=1, and the number 1 corresponds to gate 12, so you select it from the settings and then adjust the price difference to 1000 or its multiples since Bitcoin's price is in thousands. If it is another currency with a price not exceeding $100, adjust the price difference to 10 or its multiples. Thus, adjust the price difference from one currency to another. For currencies with values in fractions, the price difference will be 0.0001 or the closest figure to the currency's price, as an example.
- You can display a horizontal line at the close of each minor cycle, i.e., every 12 candles.
- You can display a strategic line at candle 42 from the start of the cycle. The strategic line is used to guide you; if the trend is up and doesn't close below this line after 7 minor cycles, the trend will likely continue up, or above it if the trend is down. In a downtrend, there are slightly different rules that can't be fully explained here.
- You can also display lines on the vibration candles, which are multiples of the number 3 from the start of the cycle, i.e., 3, 9, 12, 15, etc.
- When the trend is upward, the ending price should be higher than the starting price to draw the trend towards the gates correctly. When the trend is downward, the ending price should be lower than the starting price.
- You can now calculate digital gates in more than one way, and you can adjust the digital gates (if you have a specific method for calculating them), double them, or divide them.
** One of the most important additions is the ability to convert minor time cycles into candles to visualize the upcoming direction of the minor cycle.
ملاحظة هامة : هذا المؤشر يعتمد على خبرتك في الدورات الزمنية ولن يعطيك اي اشارات شراء او بيع فهو مؤشر يوفر عليك الرسم للدورات الزمنية الصغرى والكبرى والبوابات الرقمية ويعتمد على خبرتك الشخصية وعمله ببساطه يقوم برسم خط عمودي كل 12 شمعة من بعد اختيارك لاي شمعة ويكرر رسم الاعمده حتى اكتمال الدورة بعد 12 دورة زمنية صغرى كما انه يقوم بحساب البوابات الرقمية ويجب عليك ضبط الاعدادات من المؤشر باختيار نوع الحساب للبوابة الرقمية هل هو حساب البوابات الرقمية المتعارف عليها ( 12-15-18) او حسب اهداف البوابات كمثال (369-693-936-258-582-825-147.....) ثن يتم مضاعفتها حسب ادخالك لفارق الاسعار ليتم رسم خطوط افقيه للبوابات المتوقع اذا كسرها يستمر السعر بالوصول للبوابة التي تليها .
هذا المؤشر اداة مساعدة لرسم دورة الخمس او السبع اوالعشر وحتى الخمسين واكثر التي تحدث عنها gan ، فهو باعداداته الافتراضية يرسم خطوط اعمده راسية كل 12 شمعة ولعدد 12 دورة صغرى (يمكن تعديلها) لتتكون دورة كبرى من 144 شمعة وهي دورة العشرة ، (يجب ان يكون ليك خبرة في انماط الدورات الزمنية كما شرحها gan لتعرف هل سيستمر الصعود او الهبوط زمنياً ) فالمؤشر فقط يرسم الاعمدة التي تحدد الدورات الصغرى ومجموعها يكون الدورة الكبرى .
- يقوم المؤشر ايضا برسم البوابات الرقمية في خطوط افقية وعليك تحديدها بشكل يدوي وتعديل فارق السعر من عملة لاخرى من الاعدادات .
- عند اضافة المؤشر لاول مرة يجب تحديد شمعة بداية الاتجاه سواء عند قاع او قمة وكذلك تحديد السعر الاعلى او الادنى المتوقع ان تصل له خمس بوابات رقمية فاذا كنت تتوقع ان الدورة صاعدة فحينها تحدد السعر عند منطقة المقاومة التي تتوقع ان يرتد منها السعر وان كنت تريد رسم دورة هابطة فحينها تحدد السعر عند منطقة الدعم المتوقع الارتداد منه ويمكنك تعديل البوابات لاحقا من الاعدادات اذا اردت حسابها حسب البوابة الرقمية على سبيل المثال اذا رسمت بداية الدورة الهابطة للبيتكوين كما في الصورة اعلاه حينما كان سعر اعلى قمة 73881 نقوم بجمع اول رقمين و هم 7+3=10 , 1+0=1 والرقم 1 يتبع البوابه 12 فتقوم باختيارها من الاعدادات ثم تقوم بتعديل فارق السعر الى 1000 او مضاعفاته كون سعر البيتكوين بالالاف وان كانت عمله اخرى نفترض ان سعرها ل يتجاوز 100 دولار نعدل فارق السعر الى 10 او مضاعفاته وهكذا نقوم بتعديل فارق السعر من عملة الى اخرى ففي العملات الصفرية سيكون فارق السعر 0.0001 او حسب الرقم القريب لسعر العملة هذا فقط كمثال .
- يمكنك اظهار خط افقي عند اغلاق كل دورة صغرى اي كل 12 سمعة .
- يمكنك اظهار خط الاستراتيجي عند شمعة 42 من بداية الدورة وخط الاستراتيجي يسترشد من خلاله اذا لم يتم الاغلاق اسفله اذا كان الاتجاه صاعد بعد 7 دورات صغرى ان الاتجاه سيستمر او اعلاه اذا كان الاتجاه هابط وفي الاتجاه الهابط هنالك قواعد مختلفة قليلاً لا يتسع المجال لشرحها.
- يمكنك كذلك اظهار خطوط على شمعات الاهتزاز التي تكون من بداية الدورة مضاعفات الرقم 3 اي 3,9,12,15 وهكذ .
- عندما يكون الاتجاه صاعد يجب ان يكون سعر النهاية اعلى من سعر البداية ليتم رسم الاتتجاه للبوابات بشكل صحيح وعندما يكون الاتجاه هابط يجب ان يكون سعر النهاية ادنى من سعر البداية .
- يمكنك الان حساب البوابات الرقمية باكثر من طريقة ويمكنك تعديل البوابات الرقمية (اذا كان لديك طريقة معينة لحسابها) او مضاعفتها او تقسيمها .
** من اهم الاضافات هو امكانية تحويل الدورات الزمنية الصغرة الى شموع حتى تتخيل الاتجاه القادم لحركة الدورة الصغرى .
RSI Sector analysis
Screening tool that produces a table with the various sectors and their RSI values. The values are shown in 3 rows, each with a user-defined length, and can be averaged out and displayed as a single value. The chart is color coded as well. Each ETF representing a sector can be looked at individually, with the top holdings in each preprogrammed, but users can define their own if they wish. The left most ticker is the "benchmark"; SPY is the benchmark for the various sectors, and the ETF is the benchmark for the tickers within.
Symbols are color coded: light blue text indicates that a symbol has greater RSI values in all three timeframes than the benchmark (the leftmost symbol). Orange text indicates that a symbol has a lower RSI value for all three timeframes. In the first row, light blue text indicates the largest RSI increase from the third row to the first row. Orange text indicates the largest RSI decrease from the third row to the first row.
A blue highlight indicates that the value is the highest among the tickers, excluding the benchmark, and an orange highlight indicates that the value is the lowest among the tickers, also excluding the benchmark. A blue highlight on the ticker indicates that it has the highest average value of the 3 rows, and a orange highlight on the ticker indicates that it has the lowest average value of the 3 rows.
HTF Dynamic EMA Smoothing Indicator [CHE] with Kernel SelectionThe Dynamic EMA Smoothing Indicator with Kernel Selection is a powerful Pine Script indicator for TradingView designed to smooth moving averages and identify market trends more clearly. Here is a detailed description of its functionalities and settings:
Main Functions:
1. Time Period Display:
- Option to show or hide an info box displaying the current time period.
- Customizable info box: Users can adjust the size, position, and colors of the info box to suit their preferences.
2. Timeframe Type Selection:
- Auto Timeframe: Automatically calculates the best timeframe based on the current resolution.
- Multiplier: Allows using an alternate timeframe as a multiple of the current resolution.
- Manual Resolution: Users can manually set a specific timeframe.
3. Colors:
- Custom colors for various graphical elements, including EMA lines and signals.
4. Basic Settings:
- EMA and Signal Periods: Defines the periods for the exponential moving averages (EMA) and signal lines.
- Smoothing Length and Kernel Type: Allows selecting the smoothing length and the type of kernel used for weighting the EMAs.
- ATR Multiplier: Defines the multiplier for the ATR (Average True Range) to identify relevant price ranges.
5. EMA Calculations:
- The indicator calculates a weighted EMA using several methods like Linear, Exponential, Epanechnikov, Triangular, and Cosine kernels.
- Smoothing is achieved by adding and removing values in a float array that stores the EMA values.
6. Plotting EMA and Signal Lines:
- The indicator plots the smoothed EMA and signal lines on the chart. The line colors change according to the trend direction (green for uptrend, red for downtrend).
7. Trading Signals:
- Long Signals: An upward arrow is displayed when the smoothed EMA indicates an uptrend.
- Short Signals: A downward arrow is displayed when the smoothed EMA indicates a downtrend.
- Alert Conditions: Alerts are triggered when long or short signals are detected.
8. ATR Bands:
- The indicator shows upper and lower ATR bands to identify potential support and resistance zones.
9. Time Period Display on Chart:
- A table is used to display the selected time period on the chart when the corresponding option is enabled.
This indicator offers extensive customization and allows traders to conduct complex market analyses using smoothed EMAs and custom timeframes. The integration of various kernels for smoothing makes it a versatile tool adaptable to different trading strategies.
First Candle Marker[fitfatq]Description
This script is designed to mark the first candle of each trading day on the chart. It provides both a label and a vertical line as options to visually highlight the first candle.
Key Features
Label Settings:
Show Label: Option to display a label above the first candle of the day.
Label Text: Customizable text for the label.
Label Color: Customizable color for the label.
Label Text Color: Customizable text color for the label.
Label Transparency: Customizable transparency for the label.
Vertical Line Settings:
Show Vertical Line: Option to display a vertical line at the first candle of the day.
Vertical Line Color: Customizable color for the vertical line.
Vertical Transparency: Customizable transparency for the vertical line.
Vertical Width: Customizable width for the vertical line.
How It Works
The script identifies the first candle of each trading day by comparing the day of the week of the current bar with the previous bar.
If the current bar is the first candle of the day, it draws a label above the candle and/or a vertical line through the candle based on user settings.
Usage
This script is useful for traders who want to quickly identify the first candle of each trading day. It helps in recognizing patterns and significant price movements that occur at the start of the trading day.
Prometheus Polarized Fractal Efficiency (PFE)This indicator uses market data to calculate Polarized Fractal Efficiency (PFE) on an asset, so traders can have a better idea of which direction it may go.
Users can control the lookback length for the fractal calculation, the lookback length for the Exponential Moving Average (EMA), and whether or not to display lines at the -50 and 50 level, or -25 and 25 level.
Polarized Fractal Efficiency:
The Polarized Fractal Efficiency (PFE) indicator is a value between -100 and 100 with 0 as a midpoint.
A PFE above 0 indicates the asset may trend higher, a PFE below 0 indicates the asset may trend lower.
There are many ways to trade with PFE, the intuitive trend riding as described above, or reversals.
Even when the PFE is above 0, if it gets high enough, it may also be an indication of a reversal. A PFE of 90 - 100, or -100 - -90, may indicate price is ready to revert the other direction. Furthermore, traders already in a position may look to breaks of other levels to be their take profit or stop out spot.
Calculation:
Pi = 100 x (Price - Price )2 + N2 / Summation, j= 0, to N-2 (Price - Price )2 + 1
If Close < Close Pi = -Pi
PFEi = EMA(Pi, M)
Where:
N = period of indicator
M = smoothing period
Citation: www.investopedia.com
Scenarios:
Inputs are (9, 5) and every display option is on.
Trend example
Step 1: A short trade appears as PFE crosses below -25. We reach a safe take profit as PFE crosses below -50. Traders can use these levels to exit as well as enter.
Step 2: On the cross above 25 there is a safe long. As the PFE value breaks 0 a safe, early take profit could be appropriate for this trade. No guarantee we would see 50.
Step 3: Long scenario at break of 25, straight to 50. Simple, straightforward setup.
Step 4: This long results in a stop loss. Once again entry as PFE crosses 25, but as we cross the 0 line it is for a loss.
Step 5: The last trade in this example is reminiscent of step 3. This is a short trade entry at break of 25 and exit at break of 50.
Traders have liberty to use the PFE value to determine spots to enter and exit trades, long or short. 25 and 50 were chosen arbitrarily, values like 10 and 60 may work as well, we encourage traders to use their own discretion along with tools.
Reversal example
Step 1: PFE is around -100, crossing below it at one point! Strong zone for a potential reversal.
Step 2: PFE crosses above 25 adding conviction.
Step 3: Option to exit at 70.
Step 4: Option to exit at 90.
There is no “one size fits all method”, this approach may be more intuitive for some users and is just as feasible as the first.
Longer trend example
Step 1: Using -50 and 50 this time instead of -25 and 25 to be safer on our entries we see a short here. Was a good entry and as the value gets closer to -70 we can safely close.
Step 2: On this candle we see a long for the break of 50. On the next candle we break the 0 line, but because of our safe entry at 50, we could hold this and only stop out at a break of -25. We get close but stay in it and close at 70.
Step 3: Break of 50 for a long once again. This time the break of 0 line occurs as we are in profit, not letting a green trade go red is a golden rule of trading, so an early exit here.
Step 4: Same at step 2, break of 50 to long and stay in it, not stopping out at break of 0 line. The PFE value eventually reaches 70 and there is a good exit.
Quicker Reversal example
Step 1: Notice a close with PFE below -90, enter long for the reversal. Then close for profit when the PFE crosses above 70.
Step 2: When the PFE breaks above 90 we have a short entry. Like the long closing it when it crosses below -70.
Step 3: This step is the same setup as step 2. As PFE breaks above 90 we have a short entry. Closing it when it crosses below -70.
Recap:
Described above are 4 different examples with many different trades. Both trend and reversal trades. The PFE value is an indicator that can be used by traders in many different ways and Prometheus encourages traders to use their own discretion along with tools and not follow indicators blindly.
Options:
Users can control the input for the lookback of the indicator. The default is 9.
The smoothing factor for the EMA is also changeable, default is 5.
Users have options to display lines at -50, -25, 25, and 50.
