Normalized Relative Strength LineNormalized Relative Strength Line Indicator
Overview
The "Normalized Relative Strength Line" indicator measures the relative performance of a stock compared to a benchmark index (e.g., NSE
). This indicator helps traders and investors identify whether a stock is outperforming or underperforming the selected benchmark over a specified lookback period. The values are normalized to a range of -100 to +100 for easy interpretation.
Key Features
Comparison Symbol: Users can select a benchmark index or any other comparison symbol to measure relative performance.
Lookback Period: A user-defined period for normalization, typically set to a number of trading days (e.g., 252 days for one year).
Relative Strength Calculation: The indicator calculates the percentage change in price for both the stock and the comparison symbol from the start of the lookback period.
Normalization: The relative strength values are normalized to a range of -100 to +100 to facilitate comparison and visualization.
Smoothing: An optional 14-period simple moving average (SMA) is applied to the normalized relative strength line for a smoother representation of trends.
Interpretation
Positive Values (+100 to 0): When the normalized relative strength (RS) line is above 0, it indicates that the stock is outperforming the comparison symbol. Higher values signify stronger outperformance.
Negative Values (0 to -100): When the normalized RS line is below 0, it indicates that the stock is underperforming the comparison symbol. Lower values signify stronger underperformance.
Horizontal Line at 0: The horizontal line at 0 serves as a reference point. Crossing this line from below indicates a shift from underperformance to outperformance, and crossing from above indicates a shift from outperformance to underperformance.
Crossovers: The points where the RS line crosses the moving average (red line) can signal potential changes in relative performance trends.
Example Use Case
If the normalized RS line of a stock consistently remains around +100, it suggests that the stock has been strongly outperforming the comparison symbol over the selected lookback period. Conversely, if it remains around -100, it suggests strong underperformance.
Cycles
Bitcoin Power Law Global Liqudity Model by G. SantostasiIn recent studies, we've observed a notable correlation between Bitcoin's price and global liquidity metrics. This relationship reveals significant insights into Bitcoin's price movements and offers a new perspective on using macroeconomic indicators to understand and predict Bitcoin's market trends.
Our analysis shows that Bitcoin's price exhibits periodic bubbles, which seem closely associated with oscillations in global liquidity. Notably, the overall price path of Bitcoin appears to be a complex function of global liquidity. This relationship is not as simple as the Bitcoin Power Law in time that can be described with a simple equation, Price ∼ time⁶.
Instead, we have developed a polynomial model to describe this complex relationship between liquidity and Bitcoin price. With a 4-degree polynomial (with 5 different parameters needed to fit the data), we can get a decent fit to the data.
The fit is obtained using 500 data points by polynomial regression. The vector coefficients of the polynomial are obtained such that the sum of squared error between the observations and theoretical polynomial model is minimized.
This model needs to be taken with a grain of salt given the warning by famous mathematician Von Neumann: "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk." discussing a model created by Italian Physicist Fermi. By this he meant that the Fermi simulations relied on too many input parameters, presupposing an overfitting phenomenon.
We can still gain some insights into the relationship between Global Liquidity and the price evolution of Bitcoin using this complex model.
When the price of Bitcoin is plotted against our global liquidity index, we observe a polynomial relationship. This model allows us to see when Bitcoin's price deviates significantly from the predicted value based on global liquidity:
Above the Model: When Bitcoin's price is above the polynomial fit, it indicates a potential lack of sufficient liquidity to support the current price level, suggesting a likely correction.
Below the Model: Conversely, when the price is below the fit, it implies that liquidity might be higher than what is reflected in the price, indicating potential upward movement.
Our global liquidity index comprises several key macroeconomic metrics from major financial institutions worldwide. Here are some of the major components:
RRP (Reverse Repurchase Agreements): This metric indicates the level of liquidity in the financial system through temporary sales of securities with an agreement to repurchase them.
FED (Federal Reserve System): Represents the balance sheet of the US central bank, reflecting its monetary policy actions.
TGA (Treasury General Account): Reflects the US Treasury’s cash balance, impacting the liquidity in the banking system.
PBC (People's Bank of China): Shows the monetary policy actions and liquidity management by China’s central bank.
ECB (European Central Bank): Represents the balance sheet and liquidity management actions of the Eurozone's central bank.
BOJ (Bank of Japan): Reflects Japan's central bank's monetary policy and liquidity measures.
Other Central Banks: Includes metrics from various other central banks like the Bank of England, Bank of Canada, Reserve Bank of Australia, etc.
M2 Money Supply: This includes money supply metrics from various countries like the USA, Europe, China, Japan, and other significant economies.
These components collectively provide a comprehensive view of global liquidity, which is crucial for understanding its impact on Bitcoin's price.
Using the polynomial model and the author's Bitcoin power law model we can create 2 oscillators, one that shows deviations from the trend (normalized to the price to make the peaks more uniform) and the other showing deviations of the polynomial liquidity model from the power law trend.
The oscillators show the difference between the price and the power law model relative to the price, Orange Line. The Blue Line is instead the difference between the Global Liquidity Model of the price and the power law model relative to the model itself. The two oscillators can be overlayed to show their differences and similarities.
Analysis: In addition to similar observations from the discussion above we can see that most Bitcoin bottoms are not directly associated with bottoms in the liquidity model indicating a different mechanism at play that determines Bitcoin bottoms (probably due to miners' capitulation).
Using the new force_overlay function we plot the polynomial liquidity model directly over the Bitcoin price chart while we display the 2 oscillators in a separate panel.
Heads UpAn indicator that gives you the "heads up" that that bullish/ bearish strength is increasing.
I wanted an indicator that could give me the "heads up" that bullish/ bearish strength is increasing. This would help me get into a breakout early or avoid entering a breakout that had a high probability of failure.
Here are my definitions for this indicator:
My bull bar definition:
- A green candle that closes above 75% of it's candle range.
- The candle's body does not overlap the previous candle's body. Tails/ wicks CAN overlap.
My bear bar definition:
- A red candle that closes below 75% of it's candle range.
- the candle's body does not overlap the previous candle's body. Tails/ ticks CAN overlap.
Bullish strength increasing (arrow up):
- Bull bars are increasing in size (the candle's range) compared to previous 5 bars.
- 2 consecutive bull bars.
Bearish strength increasing (arrow down):
- Bear bars are increasing in size (the candle's range) compared to previous 5 bars.
- 2 consecutive bear bars.
You will not see this indicator trigger very often but when it does - it's because there is a change in bullish bearish strength.
Things to be aware of:
Use the indicator in line with the context of the previous trend. You will get triggers that fail. These are usually because they appear counter trend. When in doubt zoom out.
It will not call every successful breakout. If you understand the definitions you'll understand why it appears.
This is my first indicator and used for my personal use. Feedback and other ideas are welcome.
Biquad Band Pass FilterThis indicator utilizes a biquad band pass filter to isolate and highlight a specific frequency band in price data, helping traders focus on price movements within a targeted frequency range.
The Length parameter determines the center frequency of the filter, affecting which frequency band is isolated. Adjusting this parameter allows you to focus on different parts of the price movement spectrum.
The Bandwidth (BW) controls the width of the frequency band in octaves. It represents the bandwidth between -3 dB frequencies for the band pass filter. A narrower bandwidth results in a more focused filtering effect, isolating a tighter range of frequencies.
Key Features of Biquad Filters
Biquad filters are a type of digital filter that provides a combination of low-pass, high-pass, band-pass, and notch filtering capabilities. In this implementation, the biquad filter is configured as a band pass filter, which allows frequencies within a specified band to pass while attenuating frequencies outside this band. This is particularly useful in trading to isolate specific price movements, making it easier to detect patterns and trends within a targeted frequency range.
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. The customizable length and bandwidth allow for flexible adaptation to different trading strategies and market conditions. Designed for real-time charting, the biquad filter operates efficiently without significant lag, ensuring timely analysis.
By incorporating this biquad band pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into specific frequency bands of price movements, leading to more informed trading decisions.
Volume Weighted Average Price Ratio (log) [ilyaQwerty]The VWAP Ratio indicator is a valuable tool for traders aiming to assess market trends and price movements in relation to the Volume Weighted Average Price (VWAP). Volume Weighted Average Price Ratio represents the ratio of the price of the asset compared to total traded volume in US Dollars. In a context of Bitcoin, VWAP ratio helps traders assess the market state, if it is overvalued or undervalued. High values of the indicator can suggest that the market is highly overvalued and low values can indicate a great buying opportunity.
Ratio Calculation: The VWAP Ratio is computed by dividing the current price by the VWAP (Price / VWAP). VWAP represents a ratio between a cumulative sum of a traded value (price multiplied by the volume) and a cumulative traded volume.
BTC-Specific Optimization: Although the indicator can be applied to various assets, the VWAP Ratio indicator is particularly useful for Bitcoin (BTC) due to its significant trading volume and unique market behaviour.
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.
Bars Counter SeparatorIn the world of market whispers and silent charts, there exists a subtle guardian known as the Bars Counter Separator. With each tick and tock of the trading clock, it watches, counts, and marks the passage of time with delicate precision.
Three sentinels stand watch over the market's flow, each with a different heartbeat, a different rhythm. The first, known as T1, beats with the fervor of 64 bars, marking its presence in bold strokes of crimson red. The second, T2, dances to the tune of 85 bars, its vibrant green lines cutting through the market's chaos. The third, T3, strides with the majestic grace of 112 bars, leaving a trail of serene blue in its wake.
As the market ebbs and flows, these three guardians tirelessly count each bar, each fleeting moment of the trading day. And when the count reaches its destined number, they step forth from the shadows. With a gentle yet decisive hand, they draw a line across the chart—a line that whispers, "Here is a moment of significance."
Above these lines, labels bloom like flowers, each carrying the message of its respective sentinel. "T1 Counter," reads the red blossom, standing tall above the fray. "T2 Counter," declares the green, a beacon of order amidst the chaos. "T3 Counter," sings the blue, a note of calm in the market's symphony.
And so, with every new bar, the guardians reset, their task eternal, their watch unending. They mark the passage of time not with loud proclamations but with the quiet, steadfast duty of recording the market's heartbeat. They remind us that even in the frenetic dance of trades and transactions, there is a rhythm, a pattern, a story unfolding bar by bar.
Input Parameters
T1 (maxBars1): Maximum value for the first counter, default is 64.
T2 (maxBars2): Maximum value for the second counter, default is 85.
T3 (maxBars3): Maximum value for the third counter, default is 112.
Variables and Counters
Counters 1, 2, 3: Initialized to zero, these counters increment with each new bar.
Counters 4, 5, 6: Also initialized to zero, but these are designed to decrement with each new bar (though the condition bar_index < 0 makes them effectively unused since bar_index is never negative).
Increment Logic
Counters 1, 2, and 3 increment by 1 on each new bar if bar_index > 0.
Plotting Function
plot_vertical_line(counter, maxBars, line_color, label_text):
Plots a vertical dotted line and a label at the current bar when the counter reaches its maximum value (maxBars).
Plotting and Alerts
Vertical Lines and Labels: When counters 1, 2, or 3 reach their respective maximum values (maxBars1, maxBars2, maxBars3), a vertical dotted line is drawn with a corresponding label.
Counter 1 uses red lines and labels "T1 Counter".
Counter 2 uses green lines and labels "T2 Counter".
Counter 3 uses blue lines and labels "T3 Counter".
Alerts: An alert is triggered when each counter reaches its maximum value.
Jobinsabu014This Pine Script code is for an advanced trading indicator that displays enhanced moving averages with buy and sell labels, trend probability, and support/resistance levels. Here’s a detailed description of its components and functionality:
### Description:
1. **Indicator Initialization**:
- The indicator is named "Enhanced Moving Averages with Buy/Sell Labels and Trend Probability" and is set to overlay on the chart.
2. **Input Parameters**:
- **Moving Averages**: Four different moving averages (short and long periods for default and enhanced) with customizable periods.
- **Probability Threshold**: Determines the threshold for trend probability.
- **Support/Resistance Lookback**: Number of bars to look back for calculating support and resistance levels.
- **Signals Valid From**: Timestamp from which the signals are considered valid.
3. **Moving Averages Calculation**:
- **Default Moving Averages**: Calculated using simple moving averages (SMA) for the specified periods.
- **Enhanced Moving Averages**: Calculated using SMAs for different specified periods.
4. **Plotting Moving Averages**:
- Plots the default and enhanced moving averages with different colors for distinction.
5. **Crossover Detection**:
- Detects when the short moving average crosses above or below the long moving average for default moving averages.
6. **Buy/Sell Signal Labels**:
- Adds "BUY" and "SELL" labels on the chart when crossovers are detected after the specified valid timestamp.
- Tracks entry prices for buy/sell signals and adds labels when the price moves +100 points.
7. **Trend Detection for Enhanced Indicator**:
- Detects uptrend or downtrend based on the enhanced moving averages.
- Calculates a simple probability of trend based on price movement and EMA.
- Determines buy and sell signals based on trend conditions and volume-based buy/sell pressure.
8. **Plot Buy/Sell Signals for Enhanced Indicator**:
- Plots buy/sell signals based on the enhanced conditions.
9. **Background Color for Trends**:
- Changes the background color to green for uptrend and red for downtrend.
10. **Trend Lines**:
- Draws imaginary trend lines for uptrend and downtrend based on enhanced moving averages.
11. **Support and Resistance Levels**:
- Calculates and plots support and resistance levels using the specified lookback period.
- Stores and plots previous support and resistance levels with dashed lines.
12. **Expected Trend Labels**:
- Adds labels indicating expected uptrend or downtrend based on buy/sell signals.
13. **Alerts**:
- Sets alert conditions for buy and sell signals, triggering alerts when these conditions are met.
14. **Demand and Supply Zones**:
- Draws and extends horizontal lines for demand (support) and supply (resistance) zones.
### Summary:
This script enhances traditional moving average crossovers by adding trend probability calculations, volume-based pressure, and support/resistance levels. It visualizes expected trends and provides comprehensive buy/sell signals with corresponding labels, background color changes, and alerts to help traders make informed decisions.
ICT Killzones and Sessions W/ Silver Bullet + MacrosForex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
Usage:
To maximize your experience, minimize the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience.
Forex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times
This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours.
Features:
Session and Killzone Lines:
Green: London Open (LO)
White: New York (NY)
Orange: Australian (AU)
Purple: Asian (AS)
Includes AM and PM session markers.
Dotted/Striped Lines indicate overlapping kill zones within the session timeline.
Customization Options:
Display sessions and killzones in collapsed or full view.
Hide specific sessions or killzones based on your preferences.
Customize colors, texts, and sizes.
Option to hide drawings older than the current day.
Automatic Updates:
The indicator draws all lines and boxes at the start of a new day.
Automatically adjusts time-based boxes according to the New York timezone.
Killzone Time Windows (for indices):
London KZ: 02:00 - 05:00
New York AM KZ: 07:00 - 10:00
New York PM KZ: 13:30 - 16:00
Silver Bullet Times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro Times:
02:33 - 03:00
04:03 - 04:30
08:50 - 09:10
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Latest Update:
January 15:
Added option to automatically change text coloring based on the chart.
Included additional optional macro times per user request:
12:50 - 13:10
13:50 - 14:15
14:50 - 15:10
15:50 - 16:15
ICT Sessions and Kill Zones
What They Are:
ICT Sessions: These are specific times during the trading day when market activity is expected to be higher, such as the London Open, New York Open, and the Asian session.
Kill Zones: These are specific time windows within these sessions where the probability of significant price movements is higher. For example, the New York AM Kill Zone is typically from 8:30 AM to 11:00 AM EST.
How to Use Them:
Identify the Session: Determine which trading session you are in (London, New York, or Asian).
Focus on Kill Zones: Within that session, focus on the kill zones for potential trade setups. For instance, during the New York session, look for setups between 8:30 AM and 11:00 AM EST.
Silver Bullets
What They Are:
Silver Bullets: These are specific, high-probability trade setups that occur within the kill zones. They are designed to be "one shot, one kill" trades, meaning they aim for precise and effective entries and exits.
How to Use Them:
Time-Based Setup: Look for these setups within the designated kill zones. For example, between 10:00 AM and 11:00 AM for the New York AM session .
Chart Analysis: Start with higher time frames like the 15-minute chart and then refine down to 5-minute and 1-minute charts to identify imbalances or specific patterns .
Macros
What They Are:
Macros: These are broader market conditions and trends that influence your trading decisions. They include understanding the overall market direction, seasonal tendencies, and the Commitment of Traders (COT) reports.
How to Use Them:
Understand Market Conditions: Be aware of the macroeconomic factors and market conditions that could affect price movements.
Seasonal Tendencies: Know the seasonal patterns that might influence the market direction.
COT Reports: Use the Commitment of Traders reports to understand the positioning of large traders and commercial hedgers .
Putting It All Together
Preparation: Understand the macro conditions and review the COT reports.
Session and Kill Zone: Identify the trading session and focus on the kill zones.
Silver Bullet Setup: Look for high-probability setups within the kill zones using refined chart analysis.
Execution: Execute the trade with precision, aiming for a "one shot, one kill" outcome.
By following these steps, you can effectively use ICT sessions, kill zones, silver bullets, and macros to enhance your trading strategy.
Usage:
To maximize your experience, shrink the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts.
Originality and Justification:
This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making.
Credits:
This script incorporates open-source elements with significant improvements to enhance functionality and user experience. All credit goes to itradesize for the SB + Macro boxes
HTF OverlayThe "HTF Overlay" indicator provides a fully customizable higher timeframe (HTF) candle overlay on your current chart, designed to enhance your analysis and trading strategies. This tool is particularly useful for traders utilizing ICT's AMD power of three strategies, focusing on key candle OHLC/OLHC expansions, or those who need a quick reference to a higher timeframe without switching charts.
Originality and Usefulness:
The "HTF Overlay" script stands out due to its seamless integration of HTF candles onto lower timeframe charts. It ensures the current developing candle is left untouched, preserving the clarity of ongoing market activity. This feature is crucial for traders who need to analyze market structure on a smaller timeframe within the context of a larger timeframe candle.
Functionality:
Dynamic HTF Candle Display:
The script overlays HTF candles, updating them in real-time as new HTF candles form. This allows traders to see historical price behavior and trends alongside the current price action.
Visual Customization:
Users can adjust various aspects of the HTF candles, including the number of candles displayed, body colors, wick colors, wick thickness, and transparency levels for both body and wick. This ensures the overlay fits seamlessly with any chart setup.
Real-time Updates:
The indicator updates dynamically, ensuring that the HTF candles remain relevant to the current market conditions without affecting the developing candle.
How It Works:
Data Retrieval: The script uses the request.security function to fetch HTF data, including open, high, low, close, time, and time close values.
Candle Overlay: It calculates the visual parameters for the HTF candles (body and wick positions, colors, and transparency) and overlays them on the chart.
Update Mechanism: The script differentiates between new and ongoing candles, updating the current candle in real-time without disrupting its development.
How to Use:
Setup:
Select the higher timeframe you want to overlay (e.g., 240 minutes for 4-hour candles).
Specify the number of HTF candles to display.
Customize the appearance of the HTF candles, including colors and transparency settings for both the body and wicks.
Interpretation:
Use the HTF overlay to validate trading decisions by analyzing price action from a broader perspective.
Identify key support and resistance levels, trend directions, and potential reversal points by comparing current price action with HTF structures.
Integration:
Combine this indicator with other tools your strategy may use for a more comprehensive analysis.
Use it in conjunction with the first and last candle highlight feature to quickly identify key reference points and enhance your trading strategy.
Conclusion:
The "HTF Overlay" indicator is a versatile and essential tool for traders who need to incorporate higher timeframe analysis into their trading strategies. Its customizable features and real-time updates provide a deeper insight into market dynamics, helping traders make more informed decisions. Whether used for trend confirmation, breakout identification, or support/resistance analysis, this indicator enhances your ability to navigate the markets effectively.
Prometheus OscillatorThis oscillator is a tool meant to determine an up or down trend using a measure of volatility and what skews the market has.
Calculation
The first thing to do is normalize the price to have a 0 handle and be a decimal. The reason to do this is to get the 0 line for every asset.
After the source value has been normalized calculate standard deviation and skew.
Standard Deviation
To calculate standard deviation Prometheus uses Pinescript's built-in function.
standard_dev = ta.stdev(src, len, true)
Standard deviation is a decent and quick estimation of historical volatility over a period of time specified by the user.
Skew
Skew is calculated as follows:
mean = ta.sma(src, len)
m3 = math.sum(math.pow(src - mean, 3), len) / len
m2 = math.pow(math.sum(math.pow(src - mean, 2), len) / len, 1.5)
skew = m3 / m2
Skew is a value used to determine how far on one side of a distribution a value is. When the market is aggressively moving higher the skew will be a bigger positive number. When it is moving lower, a negative number. When the values are small, still either positive or negative, is when the market is moving calmly in either direction.
Adding these two values together provides us with our oscillator.
Trade Examples
A simple way to use this tool is to use 0-line crosses as bullish or bearish alerts
Step 1: Cross above 0 line, long alert. The price proceeds to move up.
Step 2: Cross below 0 line, short alert. The Price moves down.
Step 3: Cross above 0 line, long alert. The price chops then the price proceeds to move up.
0 line crosses can work but may not always be reliable.
Step 1: Cross above 0 line, long alert. The price proceeds to move up.
Step 2: Cross below 0 line, short alert. The Price bounces as the downtrend is signaled, but then continues to sell off.
Step 3: Cross above 0 line, long alert. The price chops at the high and then reverses.
Step 4: Cross below 0 line, short alert. proceeds to move down.
Step 5: Cross above 0 line, long alert. The price proceeds to move up.
Not every alert will be perfect, we encourage traders to use tools as well as their own discretion.
Previous highs and lows may be a good tell if the alert will be true.
Step 1: Cross above 0 line, long alert. The price proceeds to move up.
Step 2: Cross below 0 line, short alert. The Price bounces as the downtrend is signaled, false alert.
Step 3: Cross above 0 line, long alert. The price chops at the high and then moves up.
Step 4: Cross below 0 line, short alert. The price chops a lot with a false break to the upside, the oscillator itself does not move fast or high which could have been a sign it was false.
Step 5: Step 3's downtrend continues.
Step 6: Cross above the 0 line. A new up trend emerges.
The indicator has more than one use. Detecting false moves in a greater trend is advantageous to not get faked out.
Step 1: Price moves up, however, the oscillator does not break 0, and the trend remains bearish before a true break of 0 line and moves up.
Step 2: While the oscillator is below the 0 line the price moves up. The oscillator does not change its sign and the downtrend continues until a true break of 0 line and moves up.
Inputs:
Len: Lookback length for how many bars back to go to calculate the oscillator.
No indicator is 100% accurate, use them along with your own discretion.
Bitcoin Puell Multiple (BPM)The Bitcoin Puell Multiple is a key indicator for evaluating buying and selling opportunities based on the profitability of Bitcoin miners.
The Idea
The Bitcoin Puell Multiple is a ratio that measures the daily profitability of Bitcoin miners in relation to the historical annual average of this profitability. It is calculated by dividing the amount of newly issued Bitcoins (in USD) each day by the 365-day moving average of that same amount. This indicator provides valuable information on Bitcoin's market cycles, helping investors to identify periods when Bitcoin is potentially undervalued or overvalued.
How to Use
To use the Bitcoin Puell Multiple, investors watch for extreme levels of the indicator. A high Puell Multiple suggests that miners are making exceptionally high profits compared to the previous year, which could indicate an overvaluation of Bitcoin and a selling opportunity (red zones). Conversely, a low Puell Multiple indicates that miners' earnings are low relative to history, suggesting an undervaluation of Bitcoin and a potential buying opportunity (green zones). The trigger thresholds for these zones can be configured in the tool's parameters.
What makes this tool different from the other "Puell Multiple" scripts available is that it is up to date in terms of its data sources, with a more precise calculation, and allows you to view the entire history.
Zone trigger limits and their visualization, as well as colors, are all configurable via the tool parameters.
Here, for example, is a configuration with more sensitive trigger levels and a different color:
Bitcoin Production CostFirst inspired by the amazing @capriole_charles, I decided to create my own version of calculating the Bitcoin production cost and to share it with you guys.
One of the main difference is the electricity cost calculation. I used a country-specific input system that calculates the weighted electricity cost leveraged by the distribution of the Bitcoin network hashrate. I like the fact that it requires little updating although it is less realistic for past calculations (further in the past production costs seems too low).
How to use:
- Add the indicator to your chart.
- Adjust the inputs if needed. Update the percentage of Bitcoin network Hashrate or electricity Cost per countries. Update the mining hardware stats to the most recent hardware. For example I used a Bitcoin Miner S21 Pro stats.
- Check the multiple variables in the data window.
- Turn on/off the halving event in the style tab
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.
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.
Risk Radar ProThe "Risk Radar Pro" indicator is a sophisticated tool designed to help investors and traders assess the risk and performance of their investments over a specified period. This presentation will explain each component of the indicator, how to interpret the results, and the advantages compared to traditional metrics.
The "Risk Radar Pro" indicator includes several key metrics:
● Beta
● Maximum Drawdown
● Compound Annual Growth Rate (CAGR)
● Annualized Volatility
● Dynamic Sharpe Ratio
● Dynamic Sortino Ratio
Each of these metrics is dynamically calculated using data from the entire selected period, providing a more adaptive and accurate measure of performance and risk.
1. Start Date
● Description: The date from which the calculations begin.
● Interpretation: This allows the user to set a specific period for analysis, ensuring that all metrics reflect the performance from this point onward.
2. Beta
● Description: Beta measures the volatility or systematic risk of the instrument relative to a reference index (e.g., SPY).
● Interpretation: A beta of 1 indicates that the instrument moves with the market. A beta greater than 1 indicates more volatility than the market, while a beta less than 1 indicates less volatility.
● Advantages: Unlike classic beta, which typically uses fixed historical intervals, this dynamic beta adjusts to market changes over the entire selected period, providing a more responsive measure.
3. Maximum Drawdown
● Description: The maximum observed loss from a peak to a trough before a new peak is achieved.
● Interpretation: This shows the largest single drop in value during the specified period. It is a critical measure of downside risk.
● Advantages: By tracking the maximum drawdown dynamically, the indicator can provide timely alerts when significant losses occur, allowing for better risk management.
4. Annualized Performance
● Description: The mean annual growth rate of the investment over the specified period.
● Interpretation: The Annualized Performance represents the smoothed annual rate at which the investment would have grown if it had grown at a steady rate.
● Advantages: This dynamic calculation reflects the actual long-term growth trend of the investment rather than relying on a fixed time frame.
5. Annualized Volatility
● Description: Measures the degree of variation in the instrument's returns over time, expressed as a percentage.
● Interpretation: Higher volatility indicates greater risk, as the investment's returns fluctuate more.
● Advantages: Annualized volatility calculated over the entire selected period provides a more accurate measure of risk, as it includes all market conditions encountered during that time.
6. Dynamic Sharpe Ratio
● Description: Measures the risk-adjusted return of an investment relative to its volatility.
● Choice of Risk-Free Rate Ticker: Users can select a ticker symbol to represent the risk-free rate in Sharpe ratio calculations. The default option is US03M, representing the 3-month US Treasury bill.
● Interpretation: A higher Sharpe ratio indicates better risk-adjusted returns. This ratio accounts for the risk-free rate to provide a comparison with risk-free investments.
● Advantages: By using returns and volatility over the entire period, the dynamic Sharpe ratio adjusts to changes in market conditions, offering a more accurate measure than traditional static calculations.
7. Dynamic Sortino Ratio
● Description: Similar to the Sharpe ratio, but focuses only on downside risk.
Interpretation: A higher Sortino ratio indicates better risk-adjusted returns, focusing solely on negative returns, which are more relevant to risk-averse investors.
● Choice of Risk-Free Rate Ticker: Similarly, users can choose a ticker symbol for the risk-free rate in Sortino ratio calculations. By default, this is also set to US03M.
● Advantages: This ratio's dynamic calculation considering the downside deviation over the entire period provides a more accurate measure of risk-adjusted returns in volatile markets.
Comparison with Basic Metrics
● Static vs. Dynamic Calculations: Traditional metrics often use fixed historical intervals, which may not reflect current market conditions. The dynamic calculations in "Risk Radar Pro" adjust to market changes, providing more relevant and timely information.
● Comprehensive Risk Assessment: By including metrics like maximum drawdown, Sharpe ratio, and Sortino ratio, the indicator provides a holistic view of both upside potential and downside risk.
● User Customization: Users can customize the start date, reference index, risk-free rate, and table position, tailoring the indicator to their specific needs and preferences.
Conclusion
The "Risk Radar Pro" indicator is a powerful tool for investors and traders looking to assess and manage risk more effectively. By providing dynamic, comprehensive metrics, it offers a significant advantage over traditional static calculations, ensuring that users have the most accurate and relevant information to make informed decisions.
The "Risk Radar Pro" indicator provides analytical tools and metrics for informational purposes only. It is not intended as financial advice. Users should conduct their own research and consider their individual risk tolerance and investment objectives before making any investment decisions based on the indicator's outputs. Trading and investing involve risks, including the risk of loss. Past performance is not indicative of future results.
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.
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.
