Buy Sell Trend MonitorDescription
The purpose of this indicator is to create symbols that try to show the most accurate positions possible for trading. The formation of BUY/SELL symbols is based on the intersection of SYMBOL(Himself), BTC.D, BTC and DXY indices. The resulting signals take values between 0 and 16. These values represent the strength of the signal, and the higher its numerical value, the stronger the signal. Here, 2 different calculation methods are followed for BTC and Altcoins. In BTC, calculations are made according to the direction of BTC Market value and DXY averages, while in Altcoins, calculations are made according to the direction of BTC, BTC.D and DXY averages. If DXY for BTC is trending downwards and the BTC market value is trending upwards, the BUY symbol is formed depending on the level at which the trend occurs. For altcoins, if DXY is trending down, BTC is trending up and BTC.D is trending down, the BUY symbol is formed depending on the level at which the trend occurs. For the SELL signal, the opposite is true.
Symbols are drawn according to standard ticker and OHLC4 values.
The averages of the 1-length RSI value of these symbols are taken as the 6-length SMA.
Symbols
The symbols are explained one by one below.
Orange Line: Bitcoin Marketcap line.
White Line: DXY line.
Red Line: Bitcoin Dominance line.
Aqua Line: Current Symbol line.
Best Use
This indicator should be used for SPOT trades. Regardless, since it is not possible to know exactly the direction of the market, it should be considered to buy gradually at buy signals and sell gradually at sell signals.
It should be followed for at least a 4-hour period. We do not recommend its use as the margin of error will increase in shorter time periods.
Since the signals are not guaranteed to work 100%, we do not recommend you to trade with all your money.
No Repainting
Repainting is definitely not done. After the symbols appear, the closing should be expected. Once the closing occurs, the symbol will now be permanent.
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
Bantlar ve Kanallar
60-Day Cycle Long-Only IndicatorThe following indicator generates ‘Buy’ signals based on rotating 60-day cycles. The general theory is that when buying strong, growth-oriented assets, 60-day micro-cycles culminate into larger macro-cycles.
Summary:
Explaining the Upper and Lower Bounds in the 60-Day Cycle Strategy:
1. Cycle High (Upper Bound):
The cycle high is the highest closing price of the asset over the past 60 days. This value acts as the upper boundary of the 60-day cycle, indicating the peak price level during this period. When the current closing price is above this boundary, it suggests a potential distribution phase, where the asset might be overbought, and larger players may be selling off their positions. In the strategy, the cycle high is plotted as a red line on the chart, helping traders visually identify the upper limit of the 60-day trading range.
2. Cycle Low (Lower Bound):
The cycle low is the lowest closing price of the asset over the past 60 days. This value acts as the lower boundary of the 60-day cycle, indicating the trough price level during this period. When the current closing price is below this boundary, it suggests a potential accumulation phase, where the asset might be oversold, and larger players may be accumulating positions at lower prices. In the strategy, the cycle low is plotted as an orange line on the chart, helping traders visually identify the lower limit of the 60-day trading range.
How These Bounds Are Calculated:
• Cycle High: Calculated using the highest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.highest(close, cycle_length), where cycle_length is set to 60 days.
• Cycle Low: Calculated using the lowest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.lowest(close, cycle_length), where cycle_length is set to 60 days.
Interpretation and Application:
• Buy Signal: A buy signal is generated when the closing price crosses above the cycle low. This indicates a potential end to the bearish phase and the start of a bullish trend.
• Distribution Phase: When the closing price crosses above the cycle high, it suggests the market is in a distribution phase, potentially signaling a bearish trend or a sell-off period.
Example:
On a trading chart, the cycle high and cycle low are plotted as horizontal lines, with their colors distinguishing them (red for cycle high and orange for cycle low). These lines create a visual range within which the asset's price has moved over the last 60 days, helping traders quickly assess whether the current price is near the upper or lower bound.
By identifying and plotting these upper and lower bounds, traders can better understand the current market phase and make more informed trading decisions based on the 60-day cycle strategy. This indicator can be used across various assets.
Moving Average Exponential-DonCHI-SUPERTRENDThe "Moving Average Exponential-DonCHI-SUPERTREND" is a trading strategy or indicator that combines three distinct technical analysis tools:
Moving Average Exponential (EMA): This is a type of moving average that gives more weight to recent prices, making it more responsive to price changes compared to a simple moving average.
Donchian Channels (DonCHI): These are bands that are plotted above and below the recent price highs and lows. They help identify the current price volatility and potential breakout points.
SUPERTREND: This is a trend-following indicator that uses the average true range (ATR) to determine the direction of the trend. It provides signals similar to moving averages but with less lag.
United HUN CityPurpose and Usage
The purpose of this strategy is to create a composite indicator that combines the signals from the MFI, Fisher Transform, and Bollinger Bands %b indicators. By normalizing and averaging these indicators, the script aims to provide a smoother and more comprehensive signal that can be used to make trading decisions.
MFI (Money Flow Index): Measures buying and selling pressure based on price and volume.
Fisher Transform: Highlights potential reversal points by transforming price data to a Gaussian normal distribution.
Bollinger Bands %b: Indicates where the price is relative to the Bollinger Bands, helping to identify overbought or oversold conditions.
The combined indicator can be used to identify potential buy or sell signals based on the smoothed composite value. For instance, a high combined indicator value might indicate overbought conditions, while a low value might indicate oversold conditions.
PEV Price BandThe PEV Price Band shows prices calculated using the high and low P/FQ EV of the previous period. (price to enterprise value per share for the last quarter) multiplied by FQ's current EVPS (similar to comparing marketcap to enterprise value but edit equations that are close to the theory of P/E)
If the current price is lower than the minimum P/EVPS, it is considered cheap. In other words, a current price is above the maximum is considered expensive.
PEV Price Band consists of 2 parts.
- First of all, the current P/EVPS value is "green" (if the markecap is less than the enterprise value) or "red" (if the marketcap is more than the enterprise value) or "gold" (if the market value is less than the enterprise value and less than equity)
- Second, the blue line is the closing price.
Bitcoin Logarithmic Regression
This indicator displays logarithmic regression channels for Bitcoin. A logarithmic regression is a function that increases or decreases rapidly at first, but then steadily slows as time moves. The original version of this indicator/model was created as an open source script by a user called Owain but is not available on TradingView anymore. So I decided to update the code to the latest version of pinescript and fine tune some of the parameters.
How to read and use the logarithmic regression:
There are 3 different regression lines or channels visible:
Green Channel: These lines represent different levels of support derived from the logarithmic regression model.
Purpose: The green channel is used to identify potential support levels where the price might find a bottom or bounce back upwards.
Interpretation:
If the price is approaching or touching the lower green lines, it might indicate a buying opportunity or an area where the price is considered undervalued.
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Red Channel: These lines represent different levels of resistance derived from the logarithmic regression model.
Purpose: The red channel is used to identify potential resistance levels where the price might encounter selling pressure or face difficulty moving higher.
Interpretation:
If the price is approaching or touching the upper red lines, it might indicate a selling opportunity or an area where the price is considered overvalued.
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Purple Line This line represents to so-called "fair price" of Bitcoin according to the regression model.
Purpose: The purple line can be used to identify if the current price of Bitcoin is under- or overvalued.
Interpretation: A simple interpretation here would be that over time the price will have the tendency to always return to its "fair price", so starting to DCA more when price is under the line and less when it is over the line could be a suitable investment strategy.
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Practical Application:
You can use this regression channel to build your own, long term, trading strategies. Notice how Bitcoin seems to always act in kind of the same 4 year cycle:
- Price likes to trade around the purple line at the time of the halvings
- After the halvings we see an extended sideways range for up to 300 days
- After the sideways range Bitcoin goes into a bull market frenzy (the area between the green and red channel)
- The price tops out at the upper red channel and then enters a prolonged bear market.
Buying around the purple line or lower line of the green channel and selling once the price reaches the red channel can be a suitable and very profitable strategy.
($ROSE Trader) Mean Multiple OscillatorThe ROSE Trader Mean Multiple Oscillator is an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Who is this indicator for?
While this indicator will function on any chart, it is setup for trading Oasis BINANCE:ROSEUSDT token specifically — the presets used are tailored to the ROSE chart.
While it is an open source public script, it has been released primarily for the ROSE community
What does this indicator offer?
This indicator follows the same concepts as the Mayer Multiple, popular with BTC. What makes it unique is that it the presets are setup specifically for the BINANCE:ROSEUSDT , based upon my trading experience.
About the Mayer Multiple:
The Mayer Multiple is a derivative of the 200-day MA, calculated by dividing the BTC market price by the 200-day MA. The 200-day MA is a widely recognised indicator for BTC in establishing macro bull or bear bias. The Mayer Multiple therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For BTC overbought, and oversold conditions, have historically coincided with Mayer Multiple values of 2.4, and 0.8 respectively.
Adapting this concept to the ROSE token:
The adaption of the Mayer Multiple offered here adjusts the 200-day MA to suit the higher delta or volatility of the BINANCE:ROSEUSDT token specifically. For ROSE I use the 99-day MA to establish macro bull or bear bias. The derived 'Mean Multiple', based on the 99-day MA therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For ROSE overbought, and oversold conditions, tend to coincide with values of 1.618, and 0.618 respectively. Further offsets have been preprogrammed to add nuance to the way this indicator may be used in different market conditions
The ROSE Trader Mean Multiple Oscillator:
The Oscillator version of this script is useful to determine possible levels that price is likely to reach overbought and over sold conditions by plotting the offsets and values directly on the price chart
Calculations:
99-Day Simple Moving Average (99D SMA) * by offset
This script is partnered with the "ROSE Trade Mean Multiple”: an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Note: this script is setup to work with any instrument, but the presets are built to provide actionable data on the Oasis BINANCE:ROSEUSDT token specifically. It is not a predicative model, it rather shows how price has behaved historically / statistically at these levels given past data.
($ROSE Trader) Mean MultipleThe ROSE Trader Mean Multiple is an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Who is this indicator for?
While this indicator will function on any chart, it is setup for trading Oasis BINANCE:ROSEUSDT token specifically — the presets used are tailored to the ROSE chart.
While it is an open source public script, it has been released primarily for the ROSE community
What does this indicator offer?
This indicator follows the same concepts as the Mayer Multiple, popular with BTC. What makes it unique is that it the presets are setup specifically for the BINANCE:ROSEUSDT , based upon my trading experience.
About the Mayer Multiple:
The Mayer Multiple is a derivative of the 200-day MA, calculated by dividing the BTC market price by the 200-day MA. The 200-day MA is a widely recognised indicator for BTC in establishing macro bull or bear bias. The Mayer Multiple therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For BTC overbought, and oversold conditions, have historically coincided with Mayer Multiple values of 2.4, and 0.8 respectively.
Adapting this concept to the ROSE token:
The adaption of the Mayer Multiple offered here adjusts the 200-day MA to suit the higher delta or volatility of the BINANCE:ROSEUSDT token specifically. For ROSE I use the 99-day MA to establish macro bull or bear bias. The derived 'Mean Multiple', based on the 99-day MA therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For ROSE overbought, and oversold conditions, tend to coincide with values of 1.618, and 0.618 respectively. Further offsets have been preprogrammed to add nuance to the way this indicator may be used in different market conditions
Calculations:
Mean Multiple is calculated by dividing the market price by the 99-Day Simple Moving Average (99D SMA). The indicator allows you to adjust the period if desired.
The indicator horizontals are set at regular offsets from Mean multiple (MM), these are calculated by multiplying the SMA from which the MM is derived by a set number to arrive at each offset, based upon historic price data.
The indicator horizontals may work as oversold and over bought levels, as they show the distance the price has moved from the mean, and how the Mean Multiple (as a derivation of price) has behaved at these levels historically
This script is partnered with the "ROSE Trade Mean Multiple Oscillator" which shows this data plotted on the price chart (This Oscillator is pictured in the chart but must be added separately, it can be found in my other public scripts)
Note: this script is setup to work with any instrument, but the presets are built to provide actionable data on the Oasis BINANCE:ROSEUSDT token specifically. It is not a predicative model, it rather shows how price has behaved historically / statistically at these levels given past data.
Adaptive Bollinger-RSI Trend Signal [CHE]Adaptive Bollinger-RSI Trend Signal
Indicator Overview:
The "Adaptive Bollinger-RSI Trend Signal " (ABRT Signal ) is a sophisticated trading tool designed to provide clear and actionable buy and sell signals by combining the power of Bollinger Bands and the Relative Strength Index (RSI). This indicator aims to help traders identify potential trend reversals and confirm entry and exit points with greater accuracy.
Key Features:
1. Bollinger Bands Integration:
- Utilizes Bollinger Bands to detect price volatility and identify overbought or oversold conditions.
- Configurable parameters: Length, Source, and Multiplier for precise adjustments based on trading preferences.
- Color customization: Change the colors of the basis line, upper band, lower band, and the fill color between bands.
2. RSI Integration:
- Incorporates the Relative Strength Index (RSI) to validate potential buy and sell signals.
- Configurable parameters: Length, Source, Upper Threshold, and Lower Threshold for customized signal generation.
3. Signal Generation:
- Buy Signal: Generated when the price crosses below the lower Bollinger Band and the RSI crosses above the lower threshold, indicating a potential upward trend.
- Sell Signal: Generated when the price crosses above the upper Bollinger Band and the RSI crosses below the upper threshold, indicating a potential downward trend.
- Color customization: Change the colors of the buy and sell signal labels.
4. State Tracking:
- Tracks and records crossover and crossunder states of the price and RSI to ensure signals are only generated under the right conditions.
- Monitors the basis trend (SMA of the Bollinger Bands) to provide context for signal validation.
5. Counters and Labels:
- Labels each buy and sell signal with a counter to indicate the number of consecutive signals.
- Counters reset upon the generation of an opposite signal, ensuring clarity and preventing signal clutter.
6. DCA (Dollar-Cost Averaging) Calculation:
- Stores the close price at each signal and calculates the average entry price (DCA) for both buy and sell signals.
- Displays the number of positions and DCA values in a label on the chart.
7. Customizable Inputs:
- Easily adjustable parameters for Bollinger Bands, RSI, and colors to suit various trading strategies and timeframes.
- Boolean input to show or hide the table label displaying position counts and DCA values.
- Intuitive and user-friendly configuration options for traders of all experience levels.
How to Use:
1. Setup:
- Add the "Adaptive Bollinger-RSI Trend Signal " to your TradingView chart.
- Customize the input parameters to match your trading style and preferred timeframe.
- Adjust the colors of the indicator elements to your preference for better visibility and clarity.
2. Interpreting Signals:
- Buy Signal: Look for a "Buy" label on the chart, indicating a potential entry point when the price is oversold and RSI signals upward momentum.
- Sell Signal: Look for a "Sell" label on the chart, indicating a potential exit point when the price is overbought and RSI signals downward momentum.
3. Trade Execution:
- Use the buy and sell signals to guide your trade entries and exits, aligning them with your overall trading strategy.
- Monitor the counter labels to understand the strength and frequency of signals, helping you make informed decisions.
4. Adjust and Optimize:
- Regularly review and adjust the indicator parameters based on market conditions and backtesting results.
- Combine this indicator with other technical analysis tools to enhance your trading accuracy and performance.
5. Monitor DCA Values:
- Enable the table label to display the number of positions and average entry prices (DCA) for both buy and sell signals.
- Use this information to assess the cost basis of your trades and make strategic adjustments as needed.
Conclusion:
The Adaptive Bollinger-RSI Trend Signal is a powerful and versatile trading tool designed to help traders identify and capitalize on trend reversals with confidence. By combining the strengths of Bollinger Bands and RSI, this indicator provides clear and reliable signals, making it an essential addition to any trader's toolkit. Customize the settings, interpret the signals, and execute your trades with precision using this comprehensive indicator.
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.
Uptrick : HMA Adaptive Trend and Volatility BandsThis proprietary trading indicator, named "Uptrick: HMA Adaptive Trend and Volatility Bands," offers a sophisticated blend of trend detection and volatility measurement for financial markets. Designed to overlay directly on the price chart, it leverages a variety of technical analysis tools to provide clear visual signals and comprehensive market insights.
Key Features:
Hull Moving Average (HMA) with Volatility Bands:
HMA Calculation: Utilizes the Hull Moving Average (HMA) for smooth trend identification, applied to the average price of high and low (hl2).
Adaptive Volatility Bands: Incorporates bands around the HMA based on a responsive standard deviation adjusted by an Exponential Moving Average (EMA). These bands dynamically expand and contract with market volatility.
Parameters:
Length: Configurable period for the HMA and standard deviation (default 14).
Multiplier: Determines the width of the bands (default 2.0).
MACD (Moving Average Convergence Divergence):
MACD Calculation: Includes fast and slow EMA periods with a signal line to detect trend direction and strength.
Histogram: Difference between MACD line and signal line to visualize momentum.
Parameters:
Fast Length: Short-term EMA period (default 6).
Slow Length: Long-term EMA period (default 13).
Signal Length: Signal line EMA period (default 5).
Relative Strength Index (RSI):
RSI Calculation: Measures the speed and change of price movements to identify overbought or oversold conditions.
Parameter:
RSI Length: Period for RSI calculation (default 10).
Average True Range (ATR):
ATR Calculation: Evaluates market volatility by considering the true range over a specified period.
Parameter:
ATR Length: Period for ATR calculation (default 7).
Volume and Liquidity Analysis:
Volume: Directly incorporated into the indicator to gauge market activity.
Liquidity: Assessed using the HMA of volume to determine the ease of trade execution.
Parameter:
Liquidity Length: Period for HMA of volume calculation (default 14).
Trend Identification:
Uptrend Conditions: A combination of positive MACD histogram, RSI above 50, ATR above its HMA, and volume exceeding liquidity.
Downtrend Conditions: Negative MACD histogram, RSI below 50, ATR above its HMA, and volume exceeding liquidity.
Visual Cues: Color-coded background (green for uptrend, red for downtrend) with corresponding labels on the price chart to indicate trend shifts.
Additional Moving Averages and Bollinger Bands:
SMA (Simple Moving Average): Includes 50 and 200-period SMAs for long-term trend analysis.
EMA (Exponential Moving Average): Includes a 20-period EMA for short-term trend analysis.
Bollinger Bands: Standard deviation bands around a 20-period SMA to measure market volatility and identify potential breakout points.
Information Table:
Real-Time Data Display: An optional table that provides current values for key metrics such as price, volume, liquidity, ATR, RSI, MACD histogram, SMAs, EMA, Buy+Sell Pressure, ATH, Global liquidity, Distance from ATH and Bollinger Bands, offering traders a comprehensive snapshot of market conditions.
Visualization:
Upper and Lower Bands: Clearly plotted with distinct colors (blue for upper, red for lower) to highlight volatility boundaries.
Trend Labels: Automatic annotations on the chart to signal uptrend and downtrend conditions.
Background Highlighting: Subtle shading to visually emphasize prevailing trend conditions.
This indicator is designed for traders seeking an advanced tool to detect trends, measure volatility, and make informed trading decisions based on comprehensive technical analysis. By integrating multiple technical indicators and providing clear visual signals, it aims to enhance trading accuracy and market insight.
Super IndicatorOverview of the Combined Indicator
This combined indicator leverages three major technical analysis tools:
Bollinger Bands
Linear Regression Channels
Scalping Strategy Indicators (RSI, MACD, SMA)
Each of these tools provides unique insights into market conditions, and their integration offers a comprehensive view of price movements, trends, and potential trading signals.
1. Bollinger Bands
Purpose:
Bollinger Bands are used to measure market volatility and identify overbought or oversold conditions.
Components:
Basis (Middle Band): Typically a 20-period Simple Moving Average (SMA).
Upper Band: Basis + (2 * Standard Deviation).
Lower Band: Basis - (2 * Standard Deviation).
Why They Complement:
Bollinger Bands expand and contract based on market volatility. When the bands are narrow, it indicates low volatility and potential for a significant move. Wide bands indicate high volatility. This helps traders gauge the strength of market moves and potential reversals.
2. Linear Regression Channels
Purpose:
Linear Regression Channels identify the overall trend direction and measure deviation from the mean price over a specific period.
Components:
Middle Line (Linear Regression Line): The line of best fit through the price data over a specified period.
Upper and Lower Lines: Channels created by adding/subtracting a multiple of the standard deviation or another deviation measure from the regression line.
Why They Complement:
Linear Regression Channels provide a clear visual representation of the trend direction and the range within which prices typically fluctuate. This can help traders identify trend continuations and reversals, making it easier to spot entry and exit points.
3. Scalping Strategy Indicators
Purpose:
The RSI, MACD, and SMA are used to generate short-term buy and sell signals, which are essential for scalping strategies aimed at capturing quick profits from small price movements.
Components:
RSI (Relative Strength Index): Measures the speed and change of price movements, typically over 14 periods. It helps identify overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Consists of the MACD line, Signal line, and histogram. It helps identify changes in the strength, direction, momentum, and duration of a trend.
SMA (Simple Moving Average): The average price over a specified period, used to smooth out price data and identify trends.
Why They Complement:
These indicators provide short-term signals that can confirm or refute the signals given by Bollinger Bands and Linear Regression Channels. For example, a buy signal might be more reliable if the price is near the lower Bollinger Band and the MACD crosses above its signal line.
How They Work Together
Scenario 1: Confirming Trend Continuations
Bollinger Bands: Price staying near the upper band suggests a strong uptrend.
Linear Regression Channels: Price staying above the middle line confirms the uptrend.
5-Minute Scalping Strategy: RSI not in overbought territory, and MACD showing bullish momentum confirms continuation.
Scenario 2: Identifying Reversals
Bollinger Bands: Price touching or moving outside the lower band suggests oversold conditions.
Linear Regression Channels: Price at the lower channel line indicates potential support.
5-Minute Scalping Strategy: RSI in oversold territory, and MACD showing a bullish crossover indicates a reversal.
Scenario 3: Volatility Breakouts
Bollinger Bands: Bands contracting indicates low volatility and potential breakout.
Linear Regression Channels: Price moving away from the middle line signals potential breakout direction.
Scalping Strategy: MACD and RSI confirming the breakout direction for entry.
Input Parameters:
Define settings for Bollinger Bands, Linear Regression Channels, and the scalping strategy.
Allow users to customize lengths, multipliers, and colors.
Bollinger Bands Calculation:
Calculate the basis (SMA) and standard deviation.
Derive the upper and lower bands from the basis and standard deviation.
Linear Regression Channel Calculation:
Compute the slope, average, and intercept of the linear regression line.
Calculate deviations to plot upper and lower channel lines.
5-Minute Scalping Strategy:
Calculate RSI, MACD, and SMA for short-term trend analysis.
Define buy and sell conditions based on these indicators.
Plotting and Alerts:
Plot Bollinger Bands and Linear Regression Channels on the chart.
Plot buy and sell signals with shapes.
Set alerts for key conditions like exiting the regression channel bounds and trend switches.
Conclusion
By combining Bollinger Bands, Linear Regression Channels, and a 5-minute scalping strategy, this indicator offers a robust tool for traders. Bollinger Bands provide volatility insights, Linear Regression Channels highlight trend direction and potential reversals, and the scalping strategy offers precise entry and exit points. Together, these tools can enhance a trader's ability to make informed decisions in various market conditions.
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.
Preday Price ChannelPreday Price Channel Indicator
This indicator is designed to help traders easily observe and capitalize on key price levels and their implications on market trends. It displays the previous day's high and low prices, as well as lines representing Fibonacci ratios between these prices. When a high or low is double-broken (retested and broken again), the indicator confirms a trend change and fills the channel with orange or navy color to visually indicate this shift.
Before a large directionality appears in the market, a breakout of the previous day's high or low must occur in that direction. As long as the previous day's low is maintained, an uptrend persists, and as long as the previous day's high is maintained, a downtrend persists.
In the crypto market, the significance of the previous day's high or low is often underemphasized and less known. This simple indicator was created to help traders observe the powerful influence of the previous day's high and low, and to potentially use it to their advantage in trading.
Wishing you successful trading with this tool.
Options
Day Open: Check this box to display the current day's opening price on the chart. The opening price of the day often remains intact and is one of the simplest and most powerful indicators of whether the day's trend is upward or downward.
Preday Open: Check this box to display the previous day's opening price on the chart. The previous day's opening price often exhibits a strong tendency for retests.
Preday High and Low: Check this box to display the previous day's high and low prices on the chart. These levels are critical for determining potential breakout points.
FIB On: Check this box to display the Fibonacci ratios between the previous day's high and low prices. This feature helps identify potential support and resistance levels within this range.
Day Mid On: Check this box to display the midpoint of the preday's price range on the chart. This serves as a reference point for trend changes.
Day Trend Color On: Check this box to enable color-coding for uptrends and downtrends based on the previous day's high and low prices.
When the previous day's high is breached, the trend value is set to 2, and an orange shaded area is filled in.
When the previous day's low is breached, the trend value is set to -2, and a navy shaded area is filled in.
When a high or low is double-broken (retested and broken again), the indicator confirms the trend change, filling the channel with orange for an uptrend and navy for a downtrend to make it easy for users to recognize the trend change.
These trend values and colors remain as long as the midpoint of the previous day's price range is not violated, indicating the trend is still valid.
If, during a downtrend (trend value of -2), the low price crosses above the previous day's midpoint, the trend value changes to 1, indicating a potential issue in the downtrend, and a light orange color is displayed.
Conversely, if, during an uptrend (trend value of 2), the high price crosses below the previous day's midpoint, the trend value changes to -1, signaling a potential issue in the uptrend, and a light navy color is displayed.
This comprehensive set of features allows traders to make informed decisions by clearly observing key price levels and their implications on market trends.
IsAlgo - Manual Channel► Overview:
Manual Channel is a strategy that allows traders to manually insert channel lines and set the lines’ width. Trades are opened when the price hits one of the lines and bounces back, with the expectation that it will move towards the opposite line. This strategy offers flexibility in configuring channel lines and trading behavior.
► Description:
The Manual Channel strategy is based on the use of manually defined channel lines to guide trading decisions. Traders start by marking four key points on the chart to create the channel. The first two points share the same time but different prices, and the last two points also share the same time but different prices. This method allows traders to place the channel lines precisely based on their analysis and insights. Additionally, the strategy allows for adjusting the width of the channel lines, which acts as a buffer zone around the main lines.
Once the channel is established, the strategy continuously monitors the price movements in relation to these lines. When the price touches one of the channel lines, the strategy opens a trade with the expectation that the price will bounce back and move towards the opposite line. For example, if the price hits the lower channel line, a long trade (buy) might be opened with the anticipation that the price will rise to the upper channel line. Conversely, if the price hits the upper channel line, a short trade (sell) might be opened expecting the price to fall to the lower channel line.
The strategy offers several options for managing trades. Traders can choose to close a trade when the price reaches the opposite channel line, capturing the expected movement within the channel. Additionally, if the price breaks outside the channel, traders have the option to close trades immediately or stop further trade executions to avoid potential losses.
↑ Channel Example:
↓ Channel Example:
► Features and Settings:
⚙︎ Channel: Define the time and prices of the four main points of the channel lines, and set the lines’ width.
⚙︎ Entry Candle: Specify the minimum and maximum body size and the body-to-candle size ratio for entry candles.
⚙︎ Trading Session: Define specific trading hours during which the strategy operates, restricting trades to preferred market periods.
⚙︎ Trading Days: Specify active trading days to avoid certain days of the week.
⚙︎ Backtesting: Perform backtesting for a selected period to evaluate strategy performance. This feature can be deactivated if not needed.
⚙︎ Trades: Configure trade direction (long, short, or both), position sizing (fixed or percentage-based), maximum number of open trades, and daily trade limits.
⚙︎ Trades Exit: Set profit/loss limits, specify trade duration, or exit based on channel breaks.
⚙︎ Stop Loss: Choose from various stop-loss methods, including fixed pips, ATR-based, or highest/lowest price points within a specified number of candles. Trades can also be closed after a certain number of adverse candle movements.
⚙︎ Break Even: Adjust stop loss to break even once predefined profit levels are reached, protecting gains.
⚙︎ Trailing Stop: Implement a trailing stop to adjust the stop loss as the trade becomes profitable, securing gains and potentially capturing further upside.
⚙︎ Take Profit: Set up to three take-profit levels using methods such as fixed pips, ATR, or risk-to-reward ratios. Alternatively, specify a set number of candles moving in the trade’s direction.
⚙︎ Alerts: Comprehensive alert system to notify users of significant actions, including trade openings and closings. Supports dynamic placeholders for take-profit levels and stop-loss prices.
⚙︎ Dashboard: Visual display on the chart providing detailed information about ongoing and past trades, aiding users in monitoring strategy performance and making informed decisions.
► Backtesting Details:
Timeframe: 15-minute EURUSD chart
Initial Balance: $10,000
Order Size: 10 units
Commission: 0.05%
Slippage: 5 ticks
This strategy opens trades around a manually drawn channel, which results in a smaller number of closed trades.
VWAP Bands [UAlgo]The "VWAP Bands " indicator is designed to provide traders with valuable insights into market trends and potential support/resistance levels using Volume Weighted Average Price (VWAP) bands. This indicator integrates the core concepts of VWAP with additional trend analysis features, making it a versatile tool for both range trading and trend-following strategies.
The VWAP bands are plotted based on the standard deviation multipliers, creating upper and lower bands around the VWAP. These bands serve as dynamic support and resistance levels. When the price approaches these bands, traders can anticipate potential reversals or continuations of the current trend. Additionally, the indicator provides visual cues for trend strength and potential trend changes, helping traders make informed decisions in various market conditions.
🔶 Settings
Source (Data Source): The data source for VWAP calculations. The default setting is the typical price (HLC3), which is the average of the high, low, and close prices.
Length: The number of bars used in the VWAP calculation. This determines the lookback period for the indicator.
Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the primary upper and lower VWAP bands. This setting controls the distance of the bands from the VWAP.
Secondary Standard Deviation Multiplier: The multiplier applied to the standard deviation to create the secondary upper and lower VWAP bands, providing additional levels of support and resistance.
Display Trend: A toggle to enable or disable the display of the trend analysis feature. When enabled, the indicator highlights trend strength and potential trend changes.
Display Trend Crossovers: A toggle to enable or disable the display of trend crossover signals. When enabled, the indicator plots shapes to indicate where trend switches are likely occurring.
🔶 Calculations
The calculations behind the "VWAP Bands " indicator begin with determining the Volume Weighted Average Price (VWAP), which provides a comprehensive view of the average price of an asset, weighted by trading volume. This gives a more accurate representation of the asset's true average price over a specified period.
The first step in this process involves summing the trading volume over a chosen period, typically represented by the length parameter. Simultaneously, the product of the price (usually an average of the high, low, and close prices) and the trading volume is calculated and summed. By dividing this cumulative price-volume product by the total volume, we obtain the VWAP value. This VWAP serves as the central anchor around which the price action oscillates.
To enhance the utility of VWAP, we introduce standard deviation calculations. Standard deviation measures the extent of price dispersion from the VWAP, providing insight into price volatility. By calculating the variance (which involves the squared deviations of price) and then taking its square root, we derive the standard deviation. This helps in understanding how far prices typically stray from the VWAP.
With the VWAP and standard deviation in hand, we then establish upper and lower bands by adding and subtracting multiples of the standard deviation from the VWAP. These bands act as dynamic support and resistance levels, adapting to changes in market volatility. The primary bands, set by the first standard deviation multiplier, are augmented by secondary bands defined by a larger multiplier, offering additional layers of potential support and resistance.
It also integrates trend analysis, highlighting areas where the price action suggests a strong or weak trend. This is achieved by overlaying colored zones above and below the bands, indicating the strength and direction of the trend. When the price crosses these bands, it signals potential trend changes, aiding traders in making timely decisions.
🔶 Disclaimer
The "VWAP Bands " indicator is provided for educational and informational purposes only. It is not intended as financial advice and should not be construed as such.
Trading involves significant risk and may not be suitable for all investors. Before using this indicator or making any investment decisions, it is important to conduct thorough research and consider your financial situation.
Midpoint Line with Dynamic Bands, RSI Filter, and AlertsTitle: Midpoint Line with Dynamic Bands, RSI Filter, and Alerts
Description:
This Pine Script indicator provides a comprehensive analysis tool combining dynamic midpoint bands, RSI filtering, and alert conditions for overbought and oversold market states.
Features:
Dynamic Midpoint Bands:
Calculates the midpoint based on the highest high and lowest low over a user-defined lookback period.
Supports both percentage and fixed point offsets for the upper and lower bands.
Threshold Levels:
Defines overbought and oversold thresholds using a user-specified percentage.
RSI Filter:
Uses a 100-period RSI to filter market trends.
Plots candles in green if RSI > 50 and in red if RSI < 50.
Visual Overlays:
Fills the overbought area in red and the oversold area in green.
Plots green arrows below the bars when RSI > 50 and the price is in the oversold area.
Plots red arrows above the bars when RSI < 50 and the price is in the overbought area.
Alerts:
Generates alerts for potential long and short trading opportunities based on the defined conditions.
How to Use:
Customize the lookback period, percentage offset, fixed point offset, and threshold percentage as needed.
Use the RSI filter to identify the prevailing market trend.
Watch for visual signals (arrows) indicating potential buy or sell opportunities.
Set up alerts to receive notifications when long or short conditions are met.
This script provides traders with a robust tool for identifying key market conditions and making informed trading decisions. Customize the parameters to fit your trading strategy and use the visual cues and alerts to enhance your market analysis.
ADX + CCI + MA - Uncle SamStrategy Name: ADX + CCI + MA - Uncle Sam
Overview
This strategy aims to capitalize on trending markets by combining the Average Directional Index (ADX), Commodity Channel Index (CCI), and a customizable Moving Average (MA). It's designed for traders seeking a balanced approach to both long (buy) and short (sell) opportunities. Special thanks to the creators of the ADX and CCI indicators for their invaluable contributions to technical analysis.
Strategy Concept
The core idea is to identify strong trends with the ADX, confirm potential entry points with the CCI, and use the MA to filter trades in the direction of the broader trend. This approach seeks to avoid entering positions during periods of consolidation or when the trend is weak.
Indicator Logic
ADX (Average Directional Index): The ADX measures the strength of a trend, regardless of its direction. A value above the customizable adx_threshold (default 20) signals a strong trend, making it a prime environment for this strategy.
CCI (Commodity Channel Index): The CCI is a momentum oscillator that helps identify overbought (above 100) and oversold (below -100) conditions. We use CCI crossovers to time entries in the direction of the prevailing trend.
MA (Moving Average): The MA acts as a trend filter, ensuring we only enter trades aligned with the overall market direction. You have flexibility in choosing the MA type (SMA, EMA, etc.) and its length to suit your trading style and timeframe.
Entry Conditions
Long (Buy):
ADX is above the adx_threshold.
CCI crosses above 100.
Price is above the chosen Moving Average (if MA trend filtering is enabled).
Short (Sell):
ADX is above the adx_threshold.
CCI crosses below -100.
Price is below the chosen Moving Average (if MA trend filtering is enabled).
Exit Conditions
Stop Loss (SL): Each position has a customizable stop-loss percentage to manage risk. The default setting is 1%.
Take Profit (TP): Each position has a customizable take-profit percentage to secure gains. The default setting is 5%.
MA-Based Risk Management (Optional): This feature allows for early exits if the price closes against the MA trend for a specified number of candles. The default setting is 2 candles.
Default Settings
CCI Period: 15
ADX Length: 10
ADX Threshold: 20
MA Type: HMA
MA Length: 200
MA Source: Close
Commission Fee: $0.0
A commission fee is not added, add your trading/platform commission for realistic trading costs.
Backtest Results
The strategy has been backtested on with the default settings and a starting capital of $1000, with 0.0% commission fee. It shows promising results.
Disclaimer: Backtesting is hypothetical and does not guarantee future performance.
Important Considerations:
Customization: The strategy offers extensive customization to tailor it to your preferences. Experiment with different parameters and settings to find what works best for your trading style.
Risk Management: Always use proper risk management techniques, including position sizing and stop losses, to protect your capital.
Keltner Channel+EMA with Buy/Sell SignalsIndicator Name: Double Keltner Channel with EMA (Buy/Sell Signals)
Description:
This indicator is designed to help traders identify potential trend reversals and generate buy/sell signals in volatile markets. It combines two Keltner Channels with different sensitivities (multipliers of 2.6 and 3.8) to visualize dynamic support and resistance levels. The addition of a 20-period EMA helps confirm trend direction and filter out potential false signals.
How the Indicator Works:
• Keltner Channels: These bands dynamically adjust to changing market volatility, offering a visual representation of potential price ranges. The 2.6 multiplier Keltner Channel (KC) is more sensitive to price changes, potentially highlighting short-term reversals, while the 3.8 multiplier KC focuses on broader trend shifts.
• 20-period EMA: This widely used trend indicator helps smooth out price fluctuations and identify the underlying direction of the market.
• Buy Signals: Generated when a candle's low touches or crosses below either Keltner Channel's lower band, and within the next 6 candles, that same candle closes above the 20 EMA. This combination suggests a potential rejection of lower prices (support) and a possible resumption of the uptrend.
• Sell Signals: Mirror the buy signal logic but are triggered when the candle's high touches or crosses above either Keltner Channel's upper band and then closes below the 20 EMA within the next 6 candles. This indicates a potential rejection of higher prices (resistance) and a possible shift to a downtrend.
How to Use the Indicator:
1. Identify the Trend: Use the 20 EMA to determine the overall trend direction. Look for buy signals primarily in uptrends and sell signals in downtrends.
2. Confirm with RSI : While not included in this indicator, consider using a separate Relative Strength Index (RSI) with a length of 10, SMA type, MA length of 14, and standard deviation of 2. Look for oversold conditions (RSI below 20) to confirm buy signals and overbought conditions (RSI above 80) to confirm sell signals.
3.Apply Risk Management: Always use appropriate risk management techniques, such as stop-loss orders, to protect your capital.
Key Points:
• This indicator is most effective in trending markets.
• It is not a standalone trading system and should be used in conjunction with other analysis tools and confirmation.
• The Keltner Channel multiplier values can be adjusted to suit your trading style and risk tolerance.
Important Disclaimer:
This indicator is a modification of the original Keltner Channel code and is intended for educational and informational purposes only.
It does not constitute financial advice. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.
DTB
Dynamic Trendline Bands with Buy/Sell Pressure Detection
This indicator provides a comprehensive analysis of price movements by incorporating smoothed high and low bands, a midline, and the detection of buying and selling pressure. It is designed to help traders identify key support and resistance levels as well as potential buy and sell signals.
**Features:**
- **Smooth High and Low Bands:** Based on the highest high and lowest low over a specified period, smoothed using a simple moving average (SMA) to reduce noise and enhance clarity.
- **Midline:** The average of the smoothed high and low bands, providing a central reference point for price movements.
- **Buying and Selling Pressure Detection:** Highlights candles with significant buying or selling pressure, indicated by light green for buying pressure and light red for selling pressure. This is determined based on volume thresholds and price movement.
- **Trendlines:** Dynamic trendlines are drawn based on recent highs and lows, helping to visualize the current trend direction.
**How to Use:**
1. **High-Low Bands:** Use these bands to identify key support and resistance levels.
2. **Midline:** Monitor the midline for potential mean reversion trades.
3. **Buying/Selling Pressure Candles:** Look for candles highlighted in light green or red to identify potential buy or sell signals.
4. **Trendlines:** Follow the dynamic trendlines to understand the direction of the current trend.
**Inputs:**
- **Length:** Number of bars to consider for calculating the highest high and lowest low (default: 200).
- **Smooth Length:** Period for the simple moving average to smooth the high and low bands (default: 10).
- **Volume Threshold Multiplier:** Multiplier for the average volume to detect significant buying or selling pressure (default: 1.5).
This indicator is suitable for all timeframes and can be used in conjunction with other technical analysis tools to enhance your trading strategy.
Golden Area### Golden Area Indicator Description
The "Golden Area" indicator is a technical analysis tool designed to assist traders by identifying potential buy and sell signals based on moving averages and support/resistance levels within a specific time frame. This indicator can be applied directly to price charts.
#### How It Works
1. **Inputs:**
- **MA50 Length:** The period length for the 50-period Simple Moving Average (SMA).
- **MA200 Length:** The period length for the 200-period Simple Moving Average (SMA).
2. **Calculations:**
- **MA50 (50-period SMA):** Calculated by averaging the closing prices over the past 50 periods.
- **MA200 (200-period SMA):** Calculated by averaging the closing prices over the past 200 periods.
- **Support Level:** The lowest price over the last 50 periods.
- **Resistance Level:** The highest price over the last 50 periods.
3. **Time Filter:**
- **Start Time:** The indicator becomes active at 12:30 IST (07:00 UTC).
- **End Time:** The indicator deactivates at 10:30 IST the next day (05:00 UTC).
- A background color change (yellow) highlights the active time range on the chart.
4. **Signals:**
- **Buy Signal:** Triggered when the current time matches the start time and the closing price is below the support level.
- **Sell Signal:** Triggered when the current time matches the start time and the closing price is above the resistance level.
5. **Plots:**
- **MA50:** Plotted as a blue line on the chart.
- **MA200:** Plotted as a red line on the chart.
- **Buy Signals:** Indicated by a green 'B' below the bars.
- **Sell Signals:** Indicated by a red 'S' above the bars.
This indicator provides visual cues for potential trading opportunities within the specified time frame, aiding traders in making informed decisions.
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.
