BDC - Bitcoin (BTC) Dominance Change [Logue]Bitcoin Dominance Change. Interesting things tend to happen when the Bitcoin dominance increases or decreases rapidly. Perhaps because there is overexuberance in the market in either BTC or the alts. In back testing, I found a rapid 13-day change in dominance indicates interesting switches in the BTC trends. Prior to 2019, the indicator doesn't work as well to signal trend shifts (i.e., local tops and bottoms) likely based on very few coins making up the crypto market.
The BTC dominance change is calculated as a percentage change of the daily dominance. You are able to change the upper bound, lower bound, and the period (daily) of the indicator to your own preferences. The indicator going above the upper bound or below the lower bound will trigger a different background color.
Use this indicator at your own risk. I make no claims as to its accuracy in forecasting future trend changes of Bitcoin.
חפש סקריפטים עבור "bitcoin"
Bitcoin Cycles IndicatorBitcoin Cycles Indicator
The "Bitcoin Cycles Indicator" is designed to provide insights into the current market cycle of Bitcoin. It utilizes a combination of market cap real and total volume transfer to generate a visual representation of the market cycle.
Indicator Phases:
Cycle Lows (Green): Indicates potential low points in the cycle.
Under Valued (Aqua): Represents phases where Bitcoin might be undervalued.
Fair Market Value (Purple): Reflects periods considered to be at fair market value.
Aggressively Valued (Orange): Marks phases where Bitcoin might be aggressively valued.
Over Valued (Red): Suggests potential overvaluation of Bitcoin in the cycle.
Bitcoin Cycles can identify periods of increased risk when transaction behavior on-chain is indicative of major cycle highs. It also identifies areas of value opportunity where on-chain transaction behavior signals major cycle lows.
Historically, Bitcoin has exhibited cyclical behavior roughly every four years, coinciding with significant events known as "halvings."
While the historical correlation between Bitcoin's cycles and halving events is compelling, market dynamics are subject to change. Traders and investors should approach the market with a comprehensive strategy, incorporating multiple indicators and risk management techniques to navigate Bitcoin's evolving landscape.
Bitcoin Market Cap wave model weeklyThis Bitcoin Market Cap wave model indicator is rooted in the foundation of my previously developed tool, the : Bitcoin wave model
To derive the Total Market Cap from the Bitcoin wave price model, I employed a straightforward estimation for the Total Market Supply (TMS). This estimation relies on the formula:
TMS <= (1 - 2^(-h)) for any h.This equation holds true for any value of h, which will be elaborated upon shortly. It is important to note that this inequality becomes the equality at the dates of halvings, diverging only slightly during other periods.
Bitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log(BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in Total Bitcoin Market Cap ranging between 4B and 5B USD.
The projections to the future works well only for weekly timeframe.
Enjoy the mathematical insights!
BITCOIN Miners Revenue VS Price Correlation OscillatorUse 3D(3-day candle) as timeframe for best reading.
------
original template for Correlation indicator was created by obaranova. credit goes to her.
GetTrendStrategy 370 30 minModificación de la estrategia “GetTrendStrategy” optimizada para Bitcoin.
Exponential Bollinger BandsThese Bollinger Bands are exponential because the variance is calculated using the exponential moving average, rather than just adding the normal standard deviation to the ema. This may be more useful because the exponential standard deviation should be more sensitive to near term increases or decreases in volatility.
Please do not forget that Bollinger Bands should always be combined with another method of analysis. Bollinger Bands just provide an easy way to gauge where the price could range in. At 2 standard deviations of a continuously random variable, more than 98% of data points are in this range. I am however going to test this in excel to get the average number of data points that stay in the range for Bitcoin. I will upload my findings when I complete that. Please monitor this description if your interested.
Bitcoin Logarithmic Growth Curve 2025 Z-Score"The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
snapshot
snapshot
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns."
Now with Z-Score calculation for easy and constant valuation classification of Bitcoin according to this metric.
Created for TRW
Market to NAV Premium Arbitrage Alpha IndicatorBitcoin treasury companies such as Microstrategy are known for trading at significant premiums. but how big exactly is the premium? And how can we measure it in real time?
I developed this quantitative tool to identify statistical mispricings between market capitalization and net asset value (NAV), specifically designed for arbitrage strategies and alpha generation in Bitcoin-holding companies, such as MicroStrategy or Sharplink Gaming, or SPACs used primarily to hold cryptocurrencies, Bitcoin ETFs, and other NAV-based instruments. It can probably also be used in certain spin-offs.
KEY FEATURES:
✅ Real-time Premium/Discount Calculation
• Automatically retrieves market cap data from TradingView
• Calculates precise NAV based on underlying asset holdings (for example Bitcoin)
• Formula: (Market Cap - NAV) / NAV × 100
✅ Statistical Analysis
• Historical percentile rankings (customizable lookback period)
• Standard deviation bands (2σ) for extreme value detection (close to these values might be seen as interesting points to short or go long)
• Smoothing period to reduce noise
✅ Multi-Source Market Cap Detection
• You can add the ticker of the NAV asset, but if necessary, you can also put it manually. Priority system: TradingView data → Calculated → Manual override
✅ Advanced NAV Modeling
• Basic NAV: Asset holdings + cash.
• Adjusted NAV: Includes software business value, debt, preferred shares. If the company has a lot of this kind of intrinsic value, put it in the "cash" field
• Support for any underlying asset (BTC, ETH, etc.)
TRADING APPLICATIONS:
🎯 Pairs Trading Signals
• Long/Short opportunities when premium reaches statistical extremes
• Mean reversion strategies based on historical ranges
• Risk-adjusted position sizing using percentile ranks
🎯 Arbitrage Detection
• Identifies when market pricing significantly deviates from fair value
• Quantifies the magnitude of mispricing for profit potential
• Historical context for timing entry/exit points
CONFIGURATION OPTIONS:
• Underlying Asset: Any symbol (default: COINBASE:BTCUSD) NEEDS MANUAL INPUT
• Asset Quantity: Precise holdings amount (for example, how much BTC does the company currently hold). NEEDS MANUAL INPUT
• Cash Holdings: Additional liquid assets. NEEDS MANUAL INPUT
• Market Cap Mode: Auto-detect, calculated, or manual
• Advanced Adjustments: Business value, debt, preferred shares
• Display Settings: Lookback period, smoothing, custom colors
IT CAN BE USED BY:
• Quantitative traders focused on statistical arbitrage
• Institutional investors monitoring NAV-based instruments
• Bitcoin ETF and MSTR traders seeking alpha generation
• Risk managers tracking premium/discount exposures
• Academic researchers studying market efficiency (as you can see, markets are not efficient 😉)
Bitcoin Cycle Log-Curve (JDK-Analysis)Important: The standard parameters provided in the script are specifically tuned for the TradingView Bitcoin Index chart on a monthly timeframe on logarithmic scale, and will yield the most accurate visual alignment when applied to that dataset. (more below)
This very simple script visualizes Bitcoin’s long-term price behavior using a logarithmic regression model designed to reflect the cyclical nature of Bitcoin’s historical market trends. Unlike typical technical indicators that react to recent price movements, this tool is built on the assumption that Bitcoin follows an exponential growth path over time, shaped by its fixed supply structure and four-year halving cycles.
The calculation behind the curved bands:
An upper boundary, a lower boundary, and a central midline, are calculated based on logarithmic functions applied to the bar index (which serves as a proxy for time). The upper and lower bounds are defined using exponential formulas of the type y = exp(constant + coefficient * log(bar_index)), allowing the curves to evolve dynamically over time. These bands serve as a macro-level guide for identifying periods of historical overvaluation (upper red curve) and undervaluation (lower green curve), with a central black curve representing the geometric average of the two.
How to customize the parameters:
The lower1_const and upper1_const values vertically shift the respective lower and upper curves—more negative values push the curve downward, while higher values lift it.
The lower1_coef and upper1_coef control the steepness of the curves over time, with higher values resulting in faster growth relative to time.
The shift_factor allows for uniform vertical adjustment of all curves simultaneously.
Additionally, the channel_width setting determines how far the mirrored bands extend from the original curves, creating a visual “channel” that can highlight more conservative or aggressive valuation zones depending on preference.
How to use this indicator:
This indicator is not intended for short-term trading or intraday signals. Rather, it serves as a contextual framework for long-term investors to identify high-risk zones near the upper curve and potential long-term value opportunities near the lower curve. These areas historically align with cycle tops and bottoms, and the model helps to place current price action within that broader cyclical narrative. While the concept draws inspiration from Bitcoin’s halving-driven market cycles and exponential adoption curve, the implementation is original in its use of time-based logarithmic regression to define dynamic trend boundaries.
It is best used as a strategic tool for cycle analysis, macro positioning, and trend anchoring—rather than as a short-term signal provider.
Bitcoin NUPL IndicatorThe Bitcoin NUPL (Net Unrealized Profit/Loss) Indicator is a powerful metric that shows the difference between Bitcoin's market cap and realized cap as a percentage of market cap. This indicator helps identify different market cycle phases, from capitulation to euphoria.
// How It Works
NUPL measures the aggregate profit or loss held by Bitcoin investors, calculated as:
```
NUPL = ((Market Cap - Realized Cap) / Market Cap) * 100
```
// Market Cycle Phases
The indicator automatically color-codes different market phases:
• **Deep Red (< 0%)**: Capitulation Phase - Most coins held at a loss, historically excellent buying opportunities
• **Orange (0-25%)**: Hope & Fear Phase - Early accumulation, price uncertainty and consolidation
• **Yellow (25-50%)**: Optimism & Anxiety Phase - Emerging bull market, increasing confidence
• **Light Green (50-75%)**: Belief & Denial Phase - Strong bull market, high conviction
• **Bright Green (> 75%)**: Euphoria & Greed Phase - Potential market top, historically good profit-taking zone
// Features
• Real-time NUPL calculation with customizable smoothing
• RSI indicator for additional momentum confirmation
• Color-coded background reflecting current market phase
• Reference lines marking key transition zones
• Detailed metrics table showing NUPL value, market sentiment, market cap, realized cap, and RSI
// Strategy Applications
• **Long-term investors**: Use extreme negative NUPL values (deep red) to identify potential bottoms for accumulation
• **Swing traders**: Look for transitions between phases for potential trend changes
• **Risk management**: Consider taking profits when entering the "Euphoria & Greed" phase (bright green)
• **Mean reversion**: Watch for overbought/oversold conditions when NUPL reaches historical extremes
// Settings
• **RSI Length**: Adjusts the period for RSI calculation
• **NUPL Smoothing Length**: Applies moving average smoothing to reduce noise
// Notes
• Premium TradingView subscription required for Glassnode and Coin Metrics data
• Best viewed on daily timeframes for macro analysis
• Historical NUPL extremes have often marked cycle bottoms and tops
• Use in conjunction with other indicators for confirmation
Bitcoin MVRV Z-Score Indicator### **What This Script Does (In Plain English)**
Imagine Bitcoin has a "fair price" based on what people *actually paid* for it (called the **Realized Value**). This script tells you if Bitcoin is currently **overpriced** or **underpriced** compared to that fair price, using math.
---
### **How It Works (Like a Car Dashboard)**
1. **The Speedometer (Z-Score Line)**
- The blue line (**Z-Score**) acts like a speedometer for Bitcoin’s price:
- **Above Red Line** → Bitcoin is "speeding" (overpriced).
- **Below Green Line** → Bitcoin is "parked" (underpriced).
2. **The Warning Lights (Colors)**
- **Red Background**: "Slow down!" – Bitcoin might be too expensive.
- **Green Background**: "Time to fuel up!" – Bitcoin might be a bargain.
3. **The Alarms (Alerts)**
- Your phone buzzes when:
- Green light turns on → "Buy opportunity!"
- Red light turns on → "Be careful – might be time to sell!"
---
### **Real-Life Example**
- **2021 Bitcoin Crash**:
- The red light turned on when Bitcoin hit $60,000+ (Z-Score >7).
- A few months later, Bitcoin crashed to $30,000.
- **2023 Rally**:
- The green light turned on when Bitcoin was around $20,000 (Z-Score <0.1).
- Bitcoin later rallied to $35,000.
---
### **How to Use It (3 Simple Steps)**
1. **Look at the Blue Line**:
- If it’s **rising toward the red zone**, Bitcoin is getting expensive.
- If it’s **falling toward the green zone**, Bitcoin is getting cheap.
2. **Check the Colors**:
- Trade carefully when the background is **red**.
- Look for buying chances when it’s **green**.
3. **Set Alerts**:
- Get notified when Bitcoin enters "cheap" or "expensive" zones.
---
### **Important Notes**
- **Not Magic**: This tool helps spot trends but isn’t perfect. Always combine it with other indicators.
- **Best for Bitcoin**: Works great for Bitcoin, not as well for altcoins.
- **Long-Term Focus**: Signals work best over months/years, not hours.
---
Think of it as a **thermometer for Bitcoin’s price fever** – it tells you when the market is "hot" or "cold." 🔥❄️
Bitcoin Reversal PredictorOverview
This indicator displays two lines that, when they cross, signal a potential reversal in Bitcoin's price trend. Historically, the high or low of a bull market cycle often occurs near the moment these lines intersect. The lines consist of an Exponential Moving Average (EMA) and a logarithmic regression line fitted to all of Bitcoin's historical data.
Inspiration
The inspiration for this indicator came from the PI Cycle Top indicator, which has accurately predicted past bull market peaks. However, I believe the PI Cycle Top indicator may not be as effective in the future. In that indicator, two lines cross to mark the top, but the extent of the cross has been diminishing over time. This was especially noticeable in the 2021 cycle, where the lines barely crossed. Because of this, I created a new indicator that I think will continue to provide reliable reversal signals in the future.
How It Works
The logarithmic regression line is fitted to the Bitcoin (BTCUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). This results in a steadily decreasing line. The EMA oscillates above and below this regression line. Each time the two lines cross, a vertical colored bar appears, indicating that Bitcoin's price momentum is likely to reverse.
Use Cases
- Price Bottoming:
Bitcoin often bottoms out when the EMA crosses below the logarithmic regression line.
- Price Topping:
In contrast, Bitcoin often peaks when the EMA crosses above the logarithmic regression line.
- Profitable Strategy:
Trading at the crossovers of these lines can be a profitable strategy, as these moments often signal significant price reversals.
Bitcoin Pi Cycle TrackerThe Bitcoin Pi Cycle Tracker is based on the widely recognized Pi Cycle Top Indicator, a concept used to identify potential market cycle tops in Bitcoin's price. This implementation combines the 111-day Simple Moving Average (SMA) and the 350-day SMA (multiplied by 2) to detect key crossover points. When the 111-day SMA crosses above the 350-day SMA x2, it signals a potential market peak.
Key Features:
Plots the 111-day SMA (blue) and the 350-day SMA x2 (red) for clear visualization.
Displays visual markers and vertical lines at crossover points to highlight key moments.
Sends alerts for crossovers, helping traders stay ahead of market movements.
This tool is an implementation of the Pi Cycle concept originally popularized by Bitcoin market analysts. Use it to analyze historical price cycles and prepare for significant market events. Please note that while the Pi Cycle Indicator has been historically effective, it should be used alongside other tools for a comprehensive trading strategy.
Bitcoin Premium [SAKANE]Overview
"Bitcoin Premium " is an indicator designed to analyze the price differences (premiums) of Bitcoin between major exchanges. By using this tool, you can visualize these differences and trends across exchanges, helping you make more informed trading decisions.
Features
1. Premium Calculation and Display
- Calculates and visualizes the price differences between major exchanges like Coinbase, Bitfinex, Upbit, and Binance.
- Premiums are displayed in a histogram format for intuitive analysis.
2. Forex Rate Adjustment
- Prices quoted in KRW (e.g., from Upbit) are converted to USD using real-time KRW/USD forex rates.
3. Moving Average Option
- Displays moving averages (SMA or EMA) of premiums for a clearer view of long-term trends.
4. Customizable Settings
- Toggle the premium display for each exchange on or off.
- Includes label displays to support visual analysis.
What Can It Do for You?
1. Identify Arbitrage Opportunities
By observing price differences (premiums) between exchanges, you can identify arbitrage opportunities.
Example: If Bitcoin is cheaper on Binance and more expensive on Coinbase, you could buy on Binance and sell on Coinbase to capture the price difference.
2. Understand Regional Supply and Demand Trends
Each exchange's premium reflects the supply and demand dynamics of its respective region.
Example: A high premium on Upbit may indicate excess demand or regulatory impacts in the South Korean market.
3. Analyze Liquidity
Price differences often highlight liquidity disparities between exchanges. Markets with lower trading volumes tend to have larger premiums due to price distortions.
4. Evaluate Macroeconomic Impacts
Premium movements may reflect changes in macroeconomic factors, such as exchange rates, regulations, or financial conditions specific to each region.
5. Analyze Trends and Market Sentiment
By tracking premium trends, you can gauge market sentiment and understand regional or exchange-specific behaviors to inform your investment decisions.
6. Support Strategic Trading
This tool is useful for short-term arbitrage strategies as well as long-term evaluations of market health.
Exchange Characteristics and Premium Implications
The meaning of premiums varies by exchange.
- Coinbase (US Market)
Primarily used by investors buying directly with fiat currency (USD). A higher premium often signals bullish sentiment among institutional and retail investors.
- Bitfinex (Global Market)
A trader-focused exchange with active large-scale and leveraged trading. Premiums may reflect liquidity and risk appetite.
- Upbit (South Korean Market)
Priced in KRW, making it subject to forex rates and local market dynamics. High premiums may indicate strong demand or regulatory influences in South Korea.
- Binance (Global Market)
The largest exchange by trading volume. Premiums here are often a reflection of the overall market balance.
Notes
- This indicator is for reference only and does not guarantee trading decisions.
- Please consider the characteristics and conditions of each exchange when using this tool.
Bitcoin COT [SAKANE]#Overview
Bitcoin COT is an indicator that visualizes Bitcoin futures market positions based on the Commitment of Traders (COT) report provided by the CFTC (Commodity Futures Trading Commission).
This indicator stands out from similar tools with the following features:
- Flexible Data Switching: Supports multiple COT report types, including "Financial," "Legacy," "OpenInterest," and "Force All."
- Position Direction Selection: Easily switch between long, short, and net positions. Net positions are automatically calculated.
- Open Interest Integration: View the overall trading volume in the market at a glance.
- Comparison and Customization: Toggle individual trader types (Dealer, Asset Manager, Commercials, etc.) on and off, with visually distinct color-coded graphs.
- Force All Mode: Simultaneously display data from different report types, enabling comprehensive market analysis.
These features make it a powerful tool for both beginners and advanced traders to deeply analyze the Bitcoin futures market.
#Use Cases
1. Analyzing Trader Sentiment
- Compare net positions of various trader types (Dealer, Asset Manager, Commercials, etc.) to understand market sentiment.
2. Identifying Trend Reversals
- Detect early signs of trend reversals from sudden increases or decreases in long and short positions.
3. Utilizing Open Interest
- Monitor the overall trading volume represented by open interest to evaluate entry points or changes in volatility.
4. Tracking Position Structures
- Compare positions of leveraged funds and asset managers to analyze risk-on or risk-off environments.
#Key Features
1. Report Type Selection
- Financial (Financial Traders)
- Legacy (Legacy Report)
- Open Interest
- Force All (Display all data)
2. Position Direction Selection
- Long
- Short
- Net
3. Visualization of Major Trader Types
- Financial Traders: Dealer, Asset Manager, Leveraged Funds, Other Reportable
- Legacy: Commercials, Non-Commercials, Small Speculators
4. Open Interest Visualization
- Monitor the total open positions in the market.
5. Flexible Customization
- Toggle individual trader types on and off.
- Intuitive settings with tooltips for better usability.
#How to Use
1. Add the indicator to your chart and click the settings icon in the top-right corner.
2. Select the desired report type in the "Report Type" field.
3. Choose the position direction (Long/Short/Net) in the "Direction" field.
4. Toggle the visibility of trader types as needed.
#Notes
- Data is provided by the CFTC and is updated weekly. It is not real-time.
- Changes to the settings may take a few seconds to reflect.
Bitcoin Cycle [BigBeluga]Bitcoin Cycle Indicator is designed exclusively for analyzing Bitcoin’s long-term market cycles, working only on the 1D BTC chart . This indicator provides an in-depth view of potential cycle tops and bottoms, assisting traders in identifying key phases in Bitcoin’s market evolution.
🔵 Key Features:
Heatmap Cycle Phases: The indicator colors each cycle from blue to red , reflecting Bitcoin’s market cycle progression. Cooler colors (blue/green) signal potential accumulation or early growth phases, while warmer colors (yellow/red) indicate maturation and potential top regions.
All-Time High (ATH) and Future ATH Projection: Tracks the current ATH in real-time, while applying a linear regression model to project a possible new ATH in the future. This projection aims to provide insights into the next major cycle peak for long-term strategy.
Dashboard Overview: Displays the current ATH, potential new ATH, and the percentage distance between them. This helps users assess how far the current price is from the projected target.
Top & Bottom Cycle Signals: Red down arrows mark significant price peaks, potentially indicating cycle tops. Up arrows, numbered sequentially (inside each cycle), denote possible bottom signals for strategic DCA (Dollar Cost Averaging) entries.
1D BTC Chart Only: Built solely for the 1D BTC timeframe. Switching to any other timeframe or asset will trigger a warning message: " BTC 1D Only ." This ensures accuracy in analyzing Bitcoin’s unique cyclical behavior.
🔵 When to Use:
Ideal for long-term Bitcoin investors and cycle analysts, the Bitcoin Cycle Indicator empowers users to:
Identify key accumulation and distribution phases.
Track Bitcoin’s cyclical highs and lows with visual heatmap cues.
Estimate future potential highs based on historical patterns.
Strategize long-term positions by monitoring cycle tops and possible accumulation zones.
By visualizing Bitcoin’s cycles with color-coded clarity and top/bottom markers, this indicator is an essential tool for any BTC analyst aiming to navigate market cycles effectively.
Bitcoin Thermocap [InvestorUnknown]The Bitcoin Thermocap indicator is designed to analyze Bitcoin's market data using a variant of the "Thermocap Multiple" concept from BitBo. This indicator offers several modes for interpreting Bitcoin's historical block and price data, aiding investors and analysts in understanding long-term market dynamics and generating potential investing signals.
Key Features:
1. Thermocap Calculation
The core of the indicator is based on the Thermocap Multiple, which evaluates Bitcoin's value relative to its cumulative historical blocks mined.
Thermocap Formula:
Source: Bitbo
btc_price = request.security("INDEX:BTCUSD", "1D", close)
BTC_BLOCKSMINED = request.security("BTC_BLOCKSMINED", "D", close)
// Variable to store the cumulative historical blocks
var float historical_blocks = na
// Initialize historical blocks on the first bar
if (na(historical_blocks))
historical_blocks := 0.0
// Update the cumulative blocks for each day
historical_blocks += BTC_BLOCKSMINED * btc_price
// Calculate the Thermocap
float thermocap = ((btc_price / historical_blocks) * 1000000) // the multiplication is just for better visualization
2. Multiple Display Modes:
The indicator can display data in four different modes, offering flexibility in interpretation:
RAW: Displays the raw Thermocap value.
LOG: Applies the logarithm of the Thermocap to visualize long-term trends more effectively, especially for large-value fluctuations.
MA Oscillator: Shows the ratio between the Thermocap and its moving average (MA). Users can choose between Simple Moving Average (SMA) or Exponential Moving Average (EMA) for smoothing.
Normalized MA Oscillator: Provides a normalized version of the MA Oscillator using a dynamic min-max rescaling technique.
3. Normalization and Rescaling
The indicator normalizes the Thermocap Oscillator values between user-defined limits, allowing for easier interpretation. The normalization process decays over time, with values shrinking towards zero, providing more relevance to recent data.
Negative values can be allowed or restricted based on user preferences.
f_rescale(float value, float min, float max, float limit, bool negatives) =>
((limit * (negatives ? 2 : 1)) * (value - min) / (max - min)) - (negatives ? limit : 0)
f_max_min_normalized_oscillator(float x) =>
float oscillator = x
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
if time >= normalization_start_date
max := max * decay
min := min * decay
normalized_oscillator = f_rescale(x, min, max, lim, neg)
Usage
The Bitcoin Thermocap indicator is ideal for long-term market analysis, particularly for investors seeking to assess Bitcoin's relative value based on mining activity and price dynamics. The different display modes and customization options make it versatile for a variety of market conditions, helping users to:
Identify periods of overvaluation or undervaluation.
Generate potential buy/sell signals based on the MA Oscillator and its normalized version.
By leveraging this Thermocap-based analysis, users can gain a deeper understanding of Bitcoin's historical and current market position, helping to inform investment strategies.
Bitcoin Power Law Oscillator [InvestorUnknown]The Bitcoin Power Law Oscillator is a specialized tool designed for long-term mean-reversion analysis of Bitcoin's price relative to a theoretical midline derived from the Bitcoin Power Law model (made by capriole_charles). This oscillator helps investors identify whether Bitcoin is currently overbought, oversold, or near its fair value according to this mathematical model.
Key Features:
Power Law Model Integration: The oscillator is based on the midline of the Bitcoin Power Law, which is calculated using regression coefficients (A and B) applied to the logarithm of the number of days since Bitcoin’s inception. This midline represents a theoretical fair value for Bitcoin over time.
Midline Distance Calculation: The distance between Bitcoin’s current price and the Power Law midline is computed as a percentage, indicating how far above or below the price is from this theoretical value.
float a = input.float (-16.98212206, 'Regression Coef. A', group = "Power Law Settings")
float b = input.float (5.83430649, 'Regression Coef. B', group = "Power Law Settings")
normalization_start_date = timestamp(2011,1,1)
calculation_start_date = time == timestamp(2010, 7, 19, 0, 0) // First BLX Bitcoin Date
int days_since = request.security('BNC:BLX', 'D', ta.barssince(calculation_start_date))
bar() =>
= request.security('BNC:BLX', 'D', bar())
int offset = 564 // days between 2009/1/1 and "calculation_start_date"
int days = days_since + offset
float e = a + b * math.log10(days)
float y = math.pow(10, e)
float midline_distance = math.round((y / btc_close - 1.0) * 100)
Oscillator Normalization: The raw distance is converted into a normalized oscillator, which fluctuates between -1 and 1. This normalization adjusts the oscillator to account for historical extremes, making it easier to compare current conditions with past market behavior.
float oscillator = -midline_distance
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
rescale(float value, float min, float max) =>
(2 * (value - min) / (max - min)) - 1
normalized_oscillator = rescale(oscillator, min, max)
Overbought/Oversold Identification: The oscillator provides a clear visual representation, where values near 1 suggest Bitcoin is overbought, and values near -1 indicate it is oversold. This can help identify potential reversal points or areas of significant market imbalance.
Optional Moving Average: Users can overlay a moving average (either SMA or EMA) on the oscillator to smooth out short-term fluctuations and focus on longer-term trends. This is particularly useful for confirming trend reversals or persistent overbought/oversold conditions.
This indicator is particularly useful for long-term Bitcoin investors who wish to gauge the market's mean-reversion tendencies based on a well-established theoretical model. By focusing on the Power Law’s midline, users can gain insights into whether Bitcoin’s current price deviates significantly from what historical trends would suggest as a fair value.
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
(mab) Dynamic Bitcoin NVT SignalBitcoin`s NVT is calculated by dividing the Network Value (market cap) by the USD volume transmitted through the blockchain daily. Note this equivalent of the bitcoin token supply divided by the daily BTC value transmitted through the blockchain, NVT is technically inverse monetary velocity.
Credits go to Willy Woo for creating the Network Value Transaction Ratio (NVT). Credits go also to Dimitry Kalichkin improving NVT and creating the NVT Signal (NVTS).
According to its creator, the NVT Ratio is somewhat similar to the PE Ratio used in equity markets. When Bitcoin`s NVT is high, it indicates that its network valuation is outstripping the value being transmitted on its payment network, this can happen when the network is in high growth and investors are valuing it as a high return investment, or alternatively when the price is in an unsustainable bubble.
I created this indicator because the NVT indicator I was using suddenly stopped working. I tried a number of other NVT indicators, but all of them seem to have the same problem and stopped updating after a certain date. The cause is that the data feed from 'Quandl' that is used by most NVT indicators is no longer updated through the previous API.
Instead TradingView created a special API to access 'Quandl" data. This indicator not only uses the new API for 'Quandl', it can also access data from other providers like 'Glassnode', 'CoinMetrics' and 'IntoTheBlock'. However, the 'Quandl' data feed seems to produce the best results with this indicator.
The indicator provides dynamically adjusting overbought and oversold thresholds based on a two year moving average and standard devition with adjustable multipliers. It also implements alerts for NVT going into overbought, oversold or crossing the moving average.
Version 1.0
--
Version history
0.1 Beta
- Initial version
1.0
- First release
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Bitcoin ETF Tracker (BET)Get all the information you need about all the different Bitcoin ETFs.
With the Bitcoin ETF Tracker, you can observe all possible Bitcoin ETF data:
The ETF name.
The ticker.
The price.
The volume.
The share of total ETF volume.
The ETF fees.
The exchange and custodian.
At the bottom of the table, you'll find the day's total volume.
In addition, you can see the volume for the different Exchanges, as well as for the different Custodians.
If you don't want to display these lines to save space, you can uncheck "Show Additional Data" in the indicator settings.
The Idea
The goal is to provide the community with a tool for tracking all Bitcoin ETF data in a synthesized way, directly in your TradingView chart.
How to Use
Simply read the information in the table. You can hover above the Fees and Exchanges cells for more details.
The table takes space on the chart, you can remove the extra lines by unchecking "Show Additional Data" in the indicator settings or reduce text size by changing the "Table Text Size" parameter.
Upcoming Features
As soon as we have a little more history, we'll add variation rates as well as plots to observe the breakdown between the various Exchanges and Custodians.
Bitcoin Halving Cycle ProfitThe Bitcoin Halving Cycle Profit indicator, developed by Kevin Svenson , unveils a consistent and predetermined profit-taking cycle triggered by each Bitcoin halving event. This indicator streamlines the analysis of halving occurrences, providing explicit signals for both profit-taking and Dollar-Cost Averaging strategies.
Following each Bitcoin halving event, a fixed number of weeks consistently mark the period of maximum profitability for profit-taking:
🔄 Halving Cycle Profit Timeline Explained:
• 40 Weeks (Post-Halving) = Start of the optimal profit-taking zone.
• 80 Weeks (Post-Halving) = "Last Call" for profit-taking before the onset of a bear market.
• 125 Weeks (Post-Halving) = The optimal timeframe to begin Dollar-Cost Averaging.
(Bitcoin Weekly Chart using Halving Cycle Profit)
One standout feature of this indicator is its inherent clarity and comprehensive labeling. This quality makes it exceptionally easy to discern the locations of key factors and turning points, enhancing your understanding of the market dynamics it highlights.
(Bitcoin Daily Chart using Halving Cycle Profit)
🚀 This indicator doesn't limit its effectiveness to just Bitcoin; it seamlessly integrates with top blue-chip altcoins like Ethereum and most household names in the crypto industry.
( Ethereum Weekly Chart using Halving Cycle Profit)
🛠️ Customizable display options are availible. Users have the flexibility to toggle/adjust labels, lines, and color fills according to their preferences.
📑 In summary, the Bitcoin Halving Cycle Profit indicator is a versatile and user-friendly tool, offering clarity and customization for traders navigating both Bitcoin and top altcoins.
⚠️ It's important to note that while the Bitcoin Halving Cycle Profit indicator provides historical insights, past performance does not guarantee future results. Timing profitability in the cryptocurrency market involves inherent risks, and this indicator should not be construed as financial advice. Users are encouraged to exercise caution, conduct thorough research, and make informed decisions based on their individual risk tolerance and financial goals.
