True Market Mean BandsIntroducing the "True Market Mean Bands" (TMMB) , a technical analysis tool designed for Bitcoin. TMMB provides a model of market valuation by integrating the concept of Vaulted Realized Price with dynamic volatility bands, offering traders insights into potential market movements.
Core Concept and Utility:
The TMMB centers around the Vaulted Realized Price, an advanced metric that refines the realized price by accounting for Bitcoin that is "vaulted" - or held out of active circulation. This metric offers a deeper understanding of market valuation by considering not just the last transaction prices but also the long-term holding behaviors of investors.
Innovative Bands:
Building on this core concept, the TMMB introduces multiple bands that reflect market volatility and supply dynamics. These bands are derived using a combination of statistical analysis and customizable multipliers, allowing for adaptation to varying market conditions. The bands include:
Standard Deviation Bands: Adjusted for market volatility, providing a dynamic measure of overbought and oversold conditions.
Vaulted Realized Price Multiplier Bands: These bands use multipliers inspired by the price distribution around the mean, aligning with key psychological and mathematical levels in the market.
Technical Insight:
At the heart of TMMB lies a robust calculation framework that leverages:
Security Function: To fetch relevant market data, ensuring real-time accuracy and relevance.
Customizable Multipliers: Allowing users to adjust the sensitivity of the bands according to their trading strategies.
Statistical Analysis: Utilizing standard deviation and mean calculations to dynamically adapt the bands to market conditions.
Originality and Usefulness:
The TMMB stands out by offering a unique perspective on Bitcoin's market valuation, taking into account long-term holding patterns which are often overlooked in traditional indicators. This approach not only enriches market analysis but also provides traders with actionable insights, potentially enhancing trading strategies.
Application and Value:
TMMB is especially useful for traders and analysts looking for a deeper understanding of market dynamics, beyond surface-level price movements. It offers a valuable tool for identifying potential entry and exit points, assessing market sentiment, and making informed trading decisions.
Bitcoin (Kriptopara)
Heikin Ashi RSI + OTT [Erebor]Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a popular momentum oscillator used in technical analysis to measure the speed and change of price movements. Developed by J. Welles Wilder, the RSI is calculated using the average gains and losses over a specified period, typically 14 days. Here's how it works:
Description and Calculation:
1. Average Gain and Average Loss Calculation:
- Calculate the average gain and average loss over the chosen period (e.g., 14 days).
- The average gain is the sum of gains divided by the period, and the average loss is the sum of losses divided by the period.
2. Relative Strength (RS) Calculation:
- The relative strength is the ratio of average gain to average loss.
The RSI oscillates between 0 and 100. Traditionally, an RSI above 70 indicates overbought conditions, suggesting a potential sell signal, while an RSI below 30 suggests oversold conditions, indicating a potential buy signal.
Pros of RSI:
- Identifying Overbought and Oversold Conditions: RSI helps traders identify potential reversal points in the market due to overbought or oversold conditions.
- Confirmation Tool: RSI can be used in conjunction with other technical indicators or chart patterns to confirm signals, enhancing the reliability of trading decisions.
- Versatility: RSI can be applied to various timeframes, from intraday to long-term charts, making it adaptable to different trading styles.
Cons of RSI:
- Whipsaws: In ranging markets, RSI can generate false signals, leading to whipsaws (rapid price movements followed by a reversal).
- Not Always Accurate: RSI may give false signals, especially in strongly trending markets where overbought or oversold conditions persist for extended periods.
- Subjectivity: Interpretation of RSI levels (e.g., 70 for overbought, 30 for oversold) is somewhat subjective and can vary depending on market conditions and individual preferences.
Checking RSIs in Different Periods:
Traders often use multiple timeframes to analyze RSI for a more comprehensive view:
- Fast RSI (e.g., 8-period): Provides more sensitive signals, suitable for short-term trading and quick decision-making.
- Slow RSI (e.g., 32-period): Offers a smoother representation of price movements, useful for identifying longer-term trends and reducing noise.
By comparing RSI readings across different periods, traders can gain insights into the momentum and strength of price movements over various timeframes, helping them make more informed trading decisions. Additionally, divergence between fast and slow RSI readings may signal potential trend reversals or continuation patterns.
Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open 01, high 00 low 00, and close 00 prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by TradingView user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your programming language, indicators and strategies. © TradingView
Kind regards.
© Erebor_GIT
Bitcoin Regression Price BoundariesTLDR
DCA into BTC at or below the blue line. DCA out of BTC when price approaches the red line. There's a setting to toggle the future extrapolation off/on.
INTRODUCTION
Regression analysis is a fundamental and powerful data science tool, when applied CORRECTLY . All Bitcoin regressions I've seen (Rainbow Log, Stock-to-flow, and non-linear models), have glaring flaws ... Namely, that they have huge drift from one cycle to the next.
Presented here, is a canonical application of this statistical tool. "Canonical" meaning that any trained analyst applying the established methodology, would arrive at the same result. We model 3 lines:
Upper price boundary (red) - Predicted the April 2021 top to within 1%
Lower price boundary (green)- Predicted the Dec 2022 bottom within 10%
Non-bubble best fit line (blue) - Last update was performed on Feb 28 2024.
NOTE: The red/green lines were calculated using solely data from BEFORE 2021.
"I'M INTRUIGED, BUT WHAT EXACTLY IS REGRESSION ANALYSIS?"
Quite simply, it attempts to draw a best-fit line over some set of data. As you can imagine, there are endless forms of equations that we might try. So we need objective means of determining which equations are better than others. This is where statistical rigor is crucial.
We check p-values to ensure that a proposed model is better than chance. When comparing two different equations, we check R-squared and Residual Standard Error, to determine which equation is modeling the data better. We check residuals to ensure the equation is sufficiently complex to model all the available signal. We check adjusted R-squared to ensure the equation is not *overly* complex and merely modeling random noise.
While most people probably won't entirely understand the above paragraph, there's enough key terminology in for the intellectually curious to research.
DIVING DEEPER INTO THE 3 REGRESSION LINES ABOVE
WARNING! THIS IS TECHNICAL, AND VERY ABBREVIATED
We prefer a linear regression, as the statistical checks it allows are convenient and powerful. However, the BTCUSD dataset is decidedly non-linear. Thus, we must log transform both the x-axis and y-axis. At the end of this process, we'll use e^ to transform back to natural scale.
Plotting the log transformed data reveals a crucial visual insight. The best fit line for the blowoff tops is different than for the lower price boundary. This is why other models have failed. They attempt to model ALL the data with just one equation. This causes drift in both the upper and lower boundaries. Here we calculate these boundaries as separate equations.
Upper Boundary (in red) = e^(3.24*ln(x)-15.8)
Lower Boundary (green) = e^(0.602*ln^2(x) - 4.78*ln(x) + 7.17)
Non-Bubble best fit (blue) = e^(0.633*ln^2(x) - 5.09*ln(x) +8.12)
* (x) = The number of days since July 18 2010
Anyone familiar with Bitcoin, knows it goes in cycles where price goes stratospheric, typically measured in months; and then a lengthy cool-off period measured in years. The non-bubble best fit line methodically removes the extreme upward deviations until the residuals have the closest statistical semblance to normal data (bell curve shaped data).
Whereas the upper/lower boundary only gets re-calculated in hindsight (well after a blowoff or capitulation occur), the Non-Bubble line changes ever so slightly with each new datapoint. The last update to this line was made on Feb 28, 2024.
ENOUGH NERD TALK! HOW CAN I APPLY THIS?
In the simplest terms, anything below the blue line is a statistical buying opportunity. The closer you approach the green line (the lower boundary) the more statistically strong that opportunity is. As price approaches the red line, is a growing statistical likelyhood/danger of an imminent blowoff top.
So a wise trader would DCA (dollar cost average) into Bitcoin below the blue line; and would DCA out of Bitcoin as it approaches the red line. Historically, you may or may not have a large time-window during points of maximum opportunity. So be vigilant! Anything within 10-20% of the boundary should be regarded as extreme opportunity.
Note: You can toggle the future extrapolation of these lines in the settings (default on).
CLOSING REMARKS
Keep in mind this is a pure statistical analysis. It's likely that this model is probing a complex, real economic process underlying the Bitcoin price. Statistical models like this are most accurate during steady state conditions, where the prevailing fundamentals are stable. (The astute observer will note, that the regression boundaries held despite the economic disruption of 2020).
Thus, it cannot be understated: Should some drastic fundamental change occur in the underlying economic landscape of cryptocurrency, Bitcoin itself, or the broader economy, this model could drastically deviate, and become significantly less accurate.
Furthermore, the upper/lower boundaries cross in the year 2037. THIS MODEL WILL EVENTUALLY BREAK DOWN. But for now, given that Bitcoin price moves on the order of 2000% from bottom to top, it's truly remarkable that, using SOLELY pre-2021 data, this model was able to nail the top/bottom within 10%.
Blockcircle Hard Forks & HalvingsThe Hard Forks & Halvings indicator simply displays the dates of system wide network upgrades being completed for Bitcoin and Ethereum.
Those upgrades are called hard forks and halvings.
In the screenshot you will see that March 13 marked for the system wide Ethereum network upgrade called "ETH Dencun", it is marked in blue.
HOW IT WORKS?
For example:
Bitcoin Halvings: Nov 28, 2012, Jul 9, 2016, May 11, 2020, etc..
Bitcoin Hard Forks: Aug 2015, Feb 2016, Mar 2016, Aug 2017, etc..
Ethereum Hard Forks: Jul 30, 2015, Mar 14, 2016, Mar 13, 2024, etc...
It's conveniently an indicator so it allows you to overlay it on top of any price chart, e.g. BTC/USD, ETH/USD, ARB/USD, MATIC/USD, OP/USD, RONIN/USD, STRK/USD, etc...so you can measure the exact impact each individual significant event had on the underlying asset price.
HOW TO USE IT?
You can apply this to examine price impact on competing Layer 1s and complimentary and key beneficiary Layer 2s like ARB/OP/MATIC/STRK, which are worth monitoring closely in light of the recent Ethereum Hard Fork Dencun Upgrade and Bitcoin Halving on April 18-19.
WHAT MAKES IT' USEFUL AND ORIGINAL?
I could not find an indicator that does anything remotely close to this, so decided to build it as it's so useful to track these key dates. You can plan ahead!
One of the key benefits is a sharp reduction in Layer 2 transaction processing fees, and will lay the ground work required for "Data Blobs", think of it as a form of transaction optimization to improve scalability for the entire Ethereum ecosystem.
This will strongly accelerate staking and retaking efforts. This indicator has already helped so much in being to forecast that we were going to experience a bit of a pull back post Dencun upgrade, because historically, we've generally reverted back to the mean post upgrade.
If you have any questions about it, please post it them! Thank you
Bitcoin Bubble Risk (Adjusted for Diminishing Returns)Description:
This indicator offers a unique lens through which traders can assess risk in the Bitcoin market, specifically tailored to recognize the phenomenon of diminishing returns. By calculating the natural logarithm of the price relative to a 20-month Simple Moving Average (SMA) and applying a dynamic normalization process, this tool highlights periods of varying risk based on historical price movements and adjusted returns. The indicator is designed to provide nuanced insights into potential risk levels, aiding traders in their decision-making processes.
Usage:
To effectively use this indicator, apply it to your chart while ensuring that Bitcoin's price is set to display in monthly candles. This setting is vital for the indicator to accurately reflect the market's risk levels, as it relies on long-term data aggregation to inform its analysis.
This tool is especially beneficial for traders focused on medium to long-term investment horizons in Bitcoin, offering insights into when the market may be entering higher or lower risk phases. By incorporating this indicator into your analysis, you can gain a deeper understanding of potential risk exposures based on the adjusted price trends and market conditions.
Originality and Utility:
This script stands out for its innovative approach to risk analysis in the cryptocurrency space. By adjusting for the diminishing returns seen in mature markets, it provides a refined perspective on risk levels, enhancing traditional methodologies. This script is a significant contribution to the TradingView community, offering a unique tool for traders aiming to navigate the complexities of the Bitcoin market with informed risk management strategies.
Important Note:
This indicator is for informational purposes only and should not be considered investment advice. Users are encouraged to conduct their own research and consult with financial professionals before making investment decisions. The accuracy of the indicator's predictions can only be ensured when applied to monthly candlestick charts of Bitcoin.
Blockunity Miners Synthesis (BMS)Track the status of Bitcoin and Ethereum Miners' Netflows and their asset reserves.
The Idea
The goal is to provide a simple tool for visualizing the changes in miners' flows and reserves.
How to Use
Analysing the behaviour of miners enables you to detect long-term opportunities, in particular with the state of reserves, but also in the shorter term with the visualization of Netflows.
Elements
Miners Reserves
Miners Reserves represent the balances of addresses belonging to mining pools (in BTC or ETH).
This data can also be displayed in USD via the indicator parameters:
Miners Netflow
The Netflow is calculated by subtracting the outflows from the inflows originating from addresses associated with mining pools. When this result is negative, it indicates that more funds are exiting the miners' accounts than the funds they are receiving. Consequently, negative miner netflows suggests selling activity.
This data can also be displayed in USD via the indicator parameters. You can also choose the timeframe. For example, selecting "Yearly" will give a Netflow daily average taking into account the last 365 days:
Settings
In the settings, you can first choose which asset to view, between Bitcoin and Ethereum. Here are the reserves of Ethereum miners:
As with Bitcoin, Netflow can also be displayed in the timeframe of your choice. Here you can see the average daily netflow of Ethereum miners in USD over the last 30 days:
Here are all the parameters:
Asset Selector: Choose between Bitcoin or Ethereum miner data.
Get values in USD: Displays values in USD instead of assets.
Switch between Netflow and Reserve : If checked, displays Miners' Reserves data. If unchecked, displays Miners' Netflow data.
Display timeframe: Allows you to select the timeframe for displaying the Netflow plot.
Period Lookback (in days): Select the period to be taken into account when calculating the variation percentage of Miners' Reserves.
Lastly, you can modify all table and labels parameters.
Bitcoin Pi Cycle Top Indicator - Daily Timeframe Only1 Day Timeframe Only
The Bitcoin Pi Cycle Top Indicator has garnered attention for its historical effectiveness in identifying the timing of Bitcoin's market cycle peaks with remarkable precision, typically within a margin of 3 days.
It utilizes a specific combination of moving averages—the 111-day moving average and a 2x multiple of the 350-day moving average—to signal potential tops in the Bitcoin market.
The 111-day moving average (MA): This shorter-term MA is chosen to reflect more recent price action and trends within the Bitcoin market.
The 350-day moving average (MA) multiplied by 2: This longer-term MA is adjusted to capture broader market trends and cycles over an extended period.
The key premise behind the Bitcoin Pi Cycle Top Indicator is that a potential market top for Bitcoin can be signaled when the 111-day MA crosses above the 350-day MA (which has been doubled). Historically, this crossover event has shown a remarkable correlation with the peaks of Bitcoin's price cycles, making it a tool of interest for traders and investors aiming to anticipate significant market shifts.
#Bitcoin
Crypto Stablecoin Supply - Indicator [presentTrading]█ Introduction and How it is Different
The "Stablecoin Supply - Indicator" differentiates itself by focusing on the aggregate supply of major stablecoins—USDT, USDC, and DAI—rather than traditional price-based metrics. Its premise is that fluctuations in the total supply of these stablecoins can serve as leading indicators for broader market movements, offering traders a unique vantage point to anticipate shifts in market sentiment.
BTCUSD 6h for recent bull market
BTCUSD 8h
█ Strategy, How it Works: Detailed Explanation
🔶 Data Collection
The strategy begins with the collection of the closing supply for USDT, USDC, and DAI stablecoins. This data is fetched using a specified timeframe (**`tfInput`**), allowing for flexibility in analysis periods.
🔶 Supply Calculation
The individual supplies of USDT, USDC, and DAI are then aggregated to determine the total stablecoin supply within the market at any given time. This combined figure serves as the foundation for the subsequent statistical analysis.
🔶 Z-Score Computation
The heart of the indicator's strategy lies in the computation of the Z-Score, which is a statistical measure used to identify how far a data point is from the mean, relative to the standard deviation. The formula for the Z-Score is:
Z = (X - μ) / σ
Where:
- Z is the Z-Score
- X is the current total stablecoin supply (TotalStablecoinClose)
- μ (mu) is the mean of the total stablecoin supply over a specified length (len)
- σ (sigma) is the standard deviation of the total stablecoin supply over the same length
A moving average of the Z-Score (**`zScore_ma`**) is calculated over a short period (defaulted to 3) to smooth out the volatility and provide a clearer signal.
🔶 Signal Interpretation
The Z-Score itself is plotted, with its color indicating its relation to a defined threshold (0.382), serving as a direct visual cue for market sentiment. Zones are also highlighted to show when the Z-Score is within certain extreme ranges, suggesting overbought or oversold conditions.
Bull -> Bear
█ Trade Direction
- **Entry Threshold**: A Z-Score crossing above 0.382 suggests an increase in stablecoin supply relative to its historical average, potentially indicating bullish market sentiment or incoming capital flow into cryptocurrencies.
- **Exit Threshold**: Conversely, a Z-Score dropping below -0.382 may signal a reduction in stablecoin supply, hinting at bearish sentiment or capital withdrawal.
█ Usage
Traders can leverage the "Stablecoin Supply - Indicator" to gain insights into the underlying market dynamics that are not immediately apparent through price analysis alone. It is particularly useful for identifying potential shifts in market sentiment before they are reflected in price movements. By integrating this indicator with other technical analysis tools, traders can develop a more rounded and informed trading strategy.
█ Default Settings
- Timeframe Input (`tfInput`): Allows users to specify the timeframe for data collection, adding flexibility to the analysis.
- Z-Score Length (`len`): Set to 252 by default, representing the period over which the mean and standard deviation of the stablecoin supply are calculated.
- Color Coding: Uses distinct colors (green for bullish, red for bearish) to indicate the Z-Score's position relative to its thresholds, enhancing visual clarity.
- Extreme Range Fill: Highlights areas between defined high and low Z-Score thresholds with distinct colors to indicate potential overbought or oversold conditions.
By integrating considerations of stablecoin supply into the analytical framework, the "Stablecoin Supply - Indicator" offers a novel perspective on cryptocurrency market dynamics, enabling traders to make more nuanced and informed decisions.
STABLECOINS DEPEG FINDERSTABLECOINS DEPEG FINDER
With this script, you will be able to understand how DePeg in stablecoins USDT, USDC, and FDUSD can influence the TOTAL Market Cap.
WHAT IS DEPEG?
DePeg occurs when a stablecoin loses its peg. It can't maintain the $1.00 price for a while (or anymore). Traders can use DePeg for high-quality trading both in Crypto and Stablecoins. Usually, a Negative DePeg (e.g., 0.98%) means you can buy Stablecoins at a 2% discount. This translates to a 2% gain when the Stablecoin returns to its peg. Additionally, a Positive DePeg could be a good moment for selling or withdrawal.
WHY DEPEG MATTERS IN THE CRYPTO SPACE
Depeg in Crypto markets is primarily a matter of "earning from small differences in peg." If well understood, it can help traders and analysts to spot whales' next moves. Usually, when a negative DePeg (below $1) occurs, it means whales are in a hurry to sell their Stablecoin tokens for Crypto Tokens. In this hurry, they sell Stablecoins at a discount. In the short term, a Crypto pump is likely planned, and they buy the next x100 token.
On the other hand, a positive DePeg (above $1) means whales are in a hurry to convert tokens into Stablecoins because they are heavily selling Crypto Tokens. This leads to them paying more for Stablecoins. Positive Depeg is more interesting than Negative DePeg. Usually, it signifies an important sell-off in the crypto environment, creating high tension to safeguard your hard-earned money. Whales hurry to convert altcoins and tokens into stablecoins, causing a Positive Depeg (they are willing to pay more to be safe). Positive DePeg is plotted as Intense Background Color.
Identifying 'areas' where this occurs could help traders and analysts understand this highly manipulative market better and take positions.
THE SCRIPT
This script will help traders and analysts understand when USDT, USDC, and FDUSD depegged and how the crypto market reacted. It comes with the possibility to check and plot backgrounds when there's Positive DePeg or Negative DePeg for USDT, USDC, or FDUSD.
It's pretty useful for data analysis. In the bottom-right part, you can check the actual stablecoin peg for the three Stablecoins:
- Highest Positive DePeg in a given BackTrace
- Average Positive DePeg in a given BackTrace
- Actual Peg for USDT, USDC, FDUSD
- Average Negative DePeg in a given BackTrace
- Lowest Negative DePeg in a given BackTrace
UNDERSTANDING THE BACKGROUND PLOT
NEGATIVE DEPEG
For each Stablecoin, negative DePeg is plotted as Translucent Background Color: USDT lime, USDC aqua, FDUSD grey. You can choose from settings whether it needs to be enabled or disabled for each token.
POSITIVE DEPEG
For each Stablecoin, positive DePeg is plotted as Intense Background Color: USDT lime, USDC aqua, FDUSD grey. You can choose from settings whether it needs to be enabled or disabled for each token.
USE CASE EXAMPLES
With this script you can plan to be alerted WHEN one of those stablecoin are depegging over a threesold. Than you can act accordingly.
BUY OPPORTUNITY
Let' suppose you want to see how USDC can influence Crypto Price when deppeged
I've setup signal to be plotted only for negative Depeg when USDC goes below 0.998. As you can see it was a very good and nice buy area for the entire crypto market
SELL OPPORTUNITY
Spot a selling point could be harder. In the example below let's see how USDC positive DePeg can show signal of Crypto dump earlier in daily TF
Market Activity Risk"Market Activity Risk" (MAR) - Is a dynamic tool designed to structurize the competitive landscape of blockchain transaction blocks, offering traders a strategic edge in anticipating market movements.
By capturing where market participants are actively buying and selling, the MAR indicator provides insights into areas of high competition, allowing traders to make informed decisions and potentially front-run transactions.
At the heart of this tool are blockchain transaction fees , they can represent daily shifts in transaction fee pressures.
By measuring momentum in fees, we can analyze the urgency and competition among traders to have their transactions processed first. This indicator is particularly good at revealing potential support or resistance zones, areas where traders are likely to defend their positions or increase their stakes, thus serving as critical junctures for strategic decision-making.
Key Features:
Adaptable Standard Deviation Settings: Users have the flexibility to adjust the length of the standard deviation and its multipliers, managing the risk bands to their individual risk tolerance.
Color-Coded Risk Levels: The MAR indicator employs an intuitive color scheme, making it easy to interpret the data at a glance.
Multi-Currency Compatibility: While designed with Bitcoin in mind, the MAR indicator is versatile, functioning effectively across various cryptocurrencies including Ethereum, XRP, and several other major altcoins. This broad compatibility ensures that traders across different market segments can leverage the insights provided by this tool.
Customizable Moving Average: The 730-day moving average setting is thoughtfully chosen to reflect the nuances of a typical cryptocurrency cycle, capturing long-term trends and fluctuations. However, recognizing the diverse needs and perspectives of traders, the indicator allows for the moving average period to be modified.
Smart DCA StrategyINSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost .
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on BITSTAMP:BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size , you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
STRATEGY IN ACTION
Here you see the indicator running on the BITSTAMP:BTCUSD pair. You can read the indicator as follows:
Vertical green bands on historical candles represents where buy signals triggered in the past
Table on the top right represents the results of the A/B backtest against a standard DCA strategy
Green Smart Buy column shows that Smart DCA was more profitable than standard DCA on this backtest. That is shown by the percentage GOA (Gain on Account) and the Avg Cost
Smart Buy Zone label marks the threshold which the entire candle must be below to trigger a buy signal (line can be changed to a box under plotting settings)
Green color of Smart Buy Zone label represents that the open candle is still valid for a buy signal. A signal will only be generated if the candle closes while this label is still green
Below is the same BITSTAMP:BTCUSD chart a couple of days later. Notice how the threshold has been broken and the Smart Buy Zone label has turned from green to red. No buy signal can be triggered for this day - even if the candle retraced and closed below the threshold before daily candle close.
Notice how the green vertical bands tend to be present after significant pullbacks in price. This is the reason the strategy works! Below is the same BITSTAMP:BTCUSD chart, but this time zoomed out to present a clearer picture of the times it would invest vs times it would sit out of the market. You will notice it invests heavily in bear markets and significant pullbacks, and does not buy anything during bull markets.
Finally, to visually demonstrate the indicator on an asset other than BTC, here is an example on CRYPTO:ETHUSD . In this case the current daily high has not touched the threshold so it is still possible for this to be a valid buy trigger on daily candle close. The vertical green band will not print until the buy trigger is confirmed.
BACKTEST RESULTS
Now for some backtest results to demonstrate the improved performance over a standard DCA strategy using all non-stablecoin assets in the top 30 cryptos by marketcap.
I've used the TradingView ticker (exchange name denoted as CRYPTO in the symbol search) for every symbol tested with the exception of BTCUSD because there was some dodgy data at the beginning of the TradingView BTCUSD chart which overinflated the effectiveness of the Smart DCA strategy on that ticker. For BTCUSD I've used the BITSTAMP exchange data. The symbol links below will take you to the correct chart and exchange used for the test.
I'm using the GOA (Gain on Account) values to present how each strategy performed.
The value on the left side is the standard DCA result and the right is the Smart DCA result.
✅ means Smart DCA strategy outperformed the standard DCA strategy
❌ means standard DCA strategy outperformed the Smart DCA strategy
To avoid overfitting, and to prove that this strategy does not suffer from overfitting, I've used the exact same input parameters for every symbol tested below. The settings used in these backtests are:
Buying strictness scale: 9
Validation days: 0
You can absolutely tweak the values per symbol to further improve the results of each, however I think using identical settings on every pair tested demonstrates a higher likelihood that the results will be similar in the live markets.
I'm presenting results for two time periods:
First price data available for trading pair -> closing candle on Friday 26th Jan 2024 (ALL TIME)
Opening candle on Sunday 1st Jan 2023 -> closing candle on Friday 26th Jan 2024 (JAN 2023 -> JAN 2024)
ALL TIME:
BITSTAMP:BTCUSD 80,884% / 133,582% ✅
CRYPTO:ETHUSD 17,231% / 36,146% ✅
CRYPTO:BNBUSD 5,314% / 2,702% ❌
CRYPTO:SOLUSD 1,745% / 1,171% ❌
CRYPTO:XRPUSD 2,585% / 4,544% ✅
CRYPTO:ADAUSD 338% / 353% ✅
CRYPTO:AVAXUSD 130% / 160% ✅
CRYPTO:DOGEUSD 13,690% / 16,432% ✅
CRYPTO:TRXUSD 414% / 466% ✅
CRYPTO:DOTUSD -16% / -7% ✅
CRYPTO:LINKUSD 1,161% / 2,164% ✅
CRYPTO:TONUSD 25% / 47% ✅
CRYPTO:MATICUSD 1,769% / 1,587% ❌
CRYPTO:ICPUSD 70% / 50% ❌
CRYPTO:SHIBUSD -20% / -19% ✅
CRYPTO:LTCUSD 486% / 718% ✅
CRYPTO:BCHUSD -4% / 3% ✅
CRYPTO:LEOUSD 102% / 151% ✅
CRYPTO:ATOMUSD 46% / 91% ✅
CRYPTO:UNIUSD -16% / 1% ✅
CRYPTO:ETCUSD 283% / 414% ✅
CRYPTO:OKBUSD 1,286% / 1,935% ✅
CRYPTO:XLMUSD 1,471% / 1,592% ✅
CRYPTO:INJUSD 830% / 1,035% ✅
CRYPTO:OPUSD 138% / 195% ✅
CRYPTO:NEARUSD 23% / 44% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset since the creation of each asset, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 4,998.65%
Profit: $499,865
Closing balance: $509,865
Smart DCA Strategy results:
Average percent return: 7,906.03%
Profit: $790,603
Closing balance: $800,603
JAN 2023 -> JAN 2024:
BITSTAMP:BTCUSD 47% / 66% ✅
CRYPTO:ETHUSD 26% / 33% ✅
CRYPTO:BNBUSD 15% / 17% ✅
CRYPTO:SOLUSD 272% / 394% ✅
CRYPTO:XRPUSD 7% / 12% ✅
CRYPTO:ADAUSD 43% / 59% ✅
CRYPTO:AVAXUSD 116% / 151% ✅
CRYPTO:DOGEUSD 8% / 14% ✅
CRYPTO:TRXUSD 48% / 65% ✅
CRYPTO:DOTUSD 24% / 35% ✅
CRYPTO:LINKUSD 83% / 124% ✅
CRYPTO:TONUSD 7% / 21% ✅
CRYPTO:MATICUSD -3% / 7% ✅
CRYPTO:ICPUSD 161% / 196% ✅
CRYPTO:SHIBUSD 1% / 8% ✅
CRYPTO:LTCUSD -15% / -7% ✅
CRYPTO:BCHUSD 47% / 68% ✅
CRYPTO:LEOUSD 9% / 11% ✅
CRYPTO:ATOMUSD 1% / 15% ✅
CRYPTO:UNIUSD 9% / 23% ✅
CRYPTO:ETCUSD 27% / 40% ✅
CRYPTO:OKBUSD 21% / 30% ✅
CRYPTO:XLMUSD 11% / 19% ✅
CRYPTO:INJUSD 477% / 446% ❌
CRYPTO:OPUSD 77% / 91% ✅
CRYPTO:NEARUSD 78% / 95% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset for the duration of 2023, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 61.42%
Profit: $6,142
Closing balance: $16,142
Smart DCA Strategy results:
Average percent return: 78.19%
Profit: $7,819
Closing balance: $17,819
IBIT Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the iShares Bitcoin Trust (IBIT), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of IBIT compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of IBIT:** We determine the implied price of Bitcoin within IBIT by dividing the IBIT closing price by the known ratio of Bitcoin per share.
- **IBIT Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{IBIT Premium} = \frac{(\text{Implied Bitcoin Price of IBIT } - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where IBIT is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when IBIT is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the IBIT has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the IBIT candlestick chart on TradingView.
GBTC Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the Grayscale Bitcoin Trust (GBTC), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of GBTC compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of GBTC:** We determine the implied price of Bitcoin within GBTC by dividing the GBTC closing price by the known ratio of Bitcoin per share.
- **GBTC Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{GBTC Premium} = \frac{(\text{Implied Bitcoin Price of GBTC} - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where GBTC is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when GBTC is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the GBTC has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the GBTC candlestick chart on TradingView.
MicroStrategy / Bitcoin Market Cap RatioThis indicator offers a unique analytical perspective by comparing the market capitalization of MicroStrategy (MSTR) with that of Bitcoin (BTC) . Designed for investors and analysts interested in the correlation between MicroStrategy's financial performance and the Bitcoin market, the script calculates and visualizes the ratio of MSTR's market capitalization to Bitcoin's market capitalization.
Key Features:
Start Date: The script considers data starting from July 28, 2020, aligning with MicroStrategy's initial announcement to invest in Bitcoin.
Data Sources: It retrieves real-time data for MSTR's total shares outstanding, MSTR's stock price, and BTC's market capitalization.
Market Cap Calculations: The script calculates MicroStrategy's market cap by multiplying its stock price with the total shares outstanding. It then forms a ratio of MSTR's market cap to BTC's market cap.
Bollinger Bands: To add a layer of analysis, the script includes Bollinger Bands around the ratio, with customizable parameters for length and multiplier. These bands can help identify overbought or oversold conditions in the relationship between MSTR's and BTC's market values.
The indicator plots the MSTR/BTC market cap ratio and the Bollinger Bands, providing a clear visual representation of the relationship between these two market values over time.
This indicator is ideal for users who are tracking the impact of Bitcoin's market movements on MicroStrategy's valuation or vice versa. It provides a novel way to visualize and analyze the interconnectedness of a leading cryptocurrency asset and a major corporate investor in the space.
Volume Sum BTC ETFsThis volume indicator tracks the volume of these 10 bitcoin ETFS:
AMEX:GBTC, NASDAQ:IBIT, AMEX:BTCO, AMEX:ARKB, AMEX:HODL, AMEX:EZBC, NASDAQ:BRRR, AMEX:BTCW, AMEX:DEFI, AMEX:BITB
It multiplies the traded shares with the hl2 share price and then devides the volume by the bitcoin hl2 price.
You can change to usd volume in settings.
Enjoy!
Notice that historical volume comes from etfs which traded already before launch like GBTC.
Also notice that that btc trades also when tradfi markets are closed, so then the indicator will show the last available volume. Something to fix later.
MVRV Z-ScoreThe MVRV ratio was created by Murad Mahmudov & David Puell. It simply compares Market Cap to Realised Cap, presenting a ratio (MVRV = Market Cap / Realised Cap). The MVRV Z-Score is a later version, refining the metric by normalising the peaks and troughs of the data.
Qu_Trend+
composition
- Consists of a thick trend line and a thin yellow line.
- The largest (green/red) lines indicate rising and falling markets.
- This line represents the 13-candle moving average of Tilson T3.
- The reason for 13 candles is because it best matches the recent market price based on Bitcoin.
- This value cannot be changed, so if you need it, please modify the public code and use it.
- The yellow line is the MA20 line, the ‘Bollinger Band center line’
(UI will show whether this line has been breakout)
- The same algorithm as 20 of the basic moving average (close standard) is applied.
- The algorithm for breakthrough is calculated based on real-time prices, not based on closing prices.
An additional short-term SMA is created, and whether it crosses the SMA is classified as a breakout/resistance.
How to use it
- If the trend line becomes gentle, it may indicate a change in trend when + MA20 is broken.
- While the slope of the trend line is steep, it indicates that the trend is difficult to change.
(If the trend changes at this time, it is likely to move sideways)
- If the trend changes continuously, it is a sideways market.
At this time, watch out for the movement of the end point where the sideways trend ends.
PlayBit EMAPlayBit EMA Indicator
Introducing the PlayBit EMA, a highly esteemed technical analysis tool within the PlayBit Community and a personal favorite of Bitcoin Playboy. This indicator has cemented its place as a staple among traders for its simplicity and effectiveness.
Key Features:
PB EMA: Utilizes two Exponential Moving Averages (EMAs) to identify support and resistance zones and help identify potential reversal points.
Dynamic Fill Color:
The fill color will change based on if the closing price is above, below, or in between.
This indicator is not only a reflection of market dynamics but also an essential tool for traders looking to make informed decisions based on the relationship between price action and moving averages. Whether you're a seasoned trader or just starting out, the PlayBit EMA is an invaluable addition to your trading arsenal.
Forex Master Pattern Screener 2Overview
The Forex Master Pattern Screener 2 is based on the Master Pattern, which includes contraction, expansion, and trend phases. This indicator is designed to identify and visualize market volatility, market phases, multi-timeframe contractions, liquidity points, and pivot calculations. It provides a clear image of the market's expansion and contraction phases. It's based on an alternative form of technical analysis that reveals the psychological patterns of financial markets through three phases.
Unlike the other master pattern indicators that just use highs and lows and aren't as accurate for finding contractions, this one uses actual measures of volatility to find extremely low levels of volatility and has customizable parameters depending on what you want to do.
What is the Forex Master Pattern?
The Forex Master Pattern is a framework that revolves around understanding market cycles, comprising the three main phases: contraction, expansion, and trend.
Contraction Phase: During this phase, the market has low volatility and is consolidating within a narrow range. Institutional volume tends to be low, and it's suggested to avoid trade entries during this period.
Expansion Phase: Volatility starts to increase, and there start to be bigger moves in price. Institutional traders start accumulating positions in this phase, and they might manipulate prices to draw in retail traders, creating liquidity for their own buying or selling goals.
Trend Phase: This final phase completes the market cycle. Institutional traders begin taking profits, leading to a reversal. This triggers panic among retail traders, resulting in liquidations and stops. This generates liquidity for institutional traders to profit, leaving retail traders with overvalued positions.
Value Line:
The "value line" acts as the fair value zone or the neutral belief zone where buyers and sellers agree on fair value. It can be likened to the center of gravity and is created during contraction zones.
Applications:
Identifying these phases and understanding the value lines can help traders determine the market's general direction and make better trading decisions.
This isn't a strategy but a concept explaining market behavior, allowing traders to develop various strategies based on these principles
The contractions, which are based on volatility calculations, can help you find out when big moves will occur, known as expansions.
How traders can use this indicator
1. Identifying Market Phases:
Contraction Phase: Look for periods where the market has low volatility and is contracting, indicated by a narrow range and highlighted by the contraction box. During this phase, traders prepare for a breakout but usually avoid making new trades until a clearer trend emerges.
Expansion Phase: When the indicator signals an expansion, it suggests that the market is moving out of consolidation and may be beginning a new trend. Traders might look for entry points here, anticipating a continuation of the trend.
Trend Phase: As the market enters this phase, traders look for signs of sustained movement in one direction and consider positions that benefit from this trend.
2. Multi-Timeframe Analysis:
By looking at multiple timeframes, traders can get a broader view of the market. For instance, a contraction phase in a shorter timeframe within an expansion phase in a longer timeframe might suggest a pullback in an overall uptrend. This indicator comes with a MTF contraction screener that is customizable.
2. Fair Value Lines:
The fair value acts like a "center of gravity.". Traders could use this as a reference point for understanding market sentiment and potential reversal points. This indicator shows these values in the middle of the contraction boxes.
3. Volatility Analysis:
This indicator's volatility settings can help traders understand the market's current volatility state. High volatility indicates a more active market with larger, faster moves, while low volatility might suggest caution and tighter stop-losses or take-profits. If volatility is contracting, then an expansion is imminent. This indicator shows the volatility with percentile ranks in 0-100 values and also alerts you when volatility is contracting, aka the contraction phase.
Volatility Calculations:
This indicator uses a geometric standard deviation to measure volatility based on historical price data. This metric quantifies the variability of price changes over a specified lookback period and then computes a percentile rank within a defined sample period. This percentile calculation helps evaluate the current volatility compared to historical levels.
Based on the percentile rank, the indicator sets thresholds to determine whether the current volatility is within a range considered "contraction" or not. For example, if there are really low levels of volatility on the percentile rank, then there is currently a contraction phase. The indicator also compares the volatility value against a moving average, where values above the current moving average value signal the expansion phase.
Multi-Timeframe Analysis (MTF):
This indicator comes with a multi-timeframe table that shows contractions for 5 different timeframes, and the table is customizable.
Bands:
This indicator comes with bands that are constructed based on the statistical calculations of the standard deviation applied to the log-transformed closing prices. It is commonly assumed that the distribution of prices fits some type of right-skewed distribution. To remove most of the skewness, you can use a log transformation , which makes the distribution more symmetrical and easier to analyze, thus the use of these bands . These bands are in the 2 standard deviation range. You can use these bands to trade at extreme levels. The band parameter is based on the contraction volatility lookback, which is in the Volatility Model Settings tab.
Ways the bands could be used with the contractions:
1. Identifying Breakout trades:
Contraction Zones: These zones indicate periods of low volatility where the market is consolidating. There are usually narrow price ranges, which are considered a build-up phase before a significant price move in any direction.
Bands: When the contraction zone occurs, you might notice the bands tightening around the price on smaller lookback periods, reflecting the decreased volatility. A continuous widening of the bands could then signal the beginning of an expansion phase, indicating a potential breakout opportunity.
2. Enhancing Trade Timing:
Before the Breakout: During the contraction phase, the bands might move closer together, reflecting the lower volatility. You can monitor this phase closely and prepare for a potential expansion. The bands can provide additional confirmation; for instance, a price move toward one of the bands might show an extreme occurrence and might show what the direction of the breakout could be.
After the breakout: Once the price breaks out of the contraction zone and goes to the expansion phase, and if it coincides with the bands widening significantly, it could reinforce the strength and potential sustainability of the new trend, providing a clearer entry.
3. Price-touching bands during a contraction:
If the price repeatedly touches one of the bands during a contraction phase, it might suggest a buildup of pressure in that direction. For example, if the price is consistently touching the upper band even though the bands are narrow, it might suggest bullish pressure that could occur once the expansion phase begin.
4. Price at the band extreme levels during Expansion:
If the price is at the extreme levels of the bands once the expansion phase occurs, it might indicate unsustainable levels and a low probability of the price continuing beyond those levels. Potentially signaling that a reversal will occur. Some trades could use these extremes to place entries during the expansion phases.
Liquidity Levels:
This script comes with liquidity points, whose functionality goes towards identifying pivotal levels in price action, focusing on swing highs and swing lows in the market. These points represent areas where significant buying (for swing lows) or selling (for swing highs) activity has occurred, implying potential levels or resistance in the price movement.
These liquidity points, often identified as highs and lows, are points where market participants have shown interest in the past. These levels can act as psychological indications where traders might place orders, leading to increased trading activity when these levels are approached or breached. When used with the Forex Master Pattern phases, liquidity levels can enhance trades placed with this indicator. For instance, if the market is expanding and approaches a significant liquidity level, there might be a higher chance of a breakout or reversal, showing a possible entry or exit point.
Liquidity Levels in the Contraction Phase:
Accumulation and Distribution: During the contraction phase, liquidity levels can indicate where huge positions are likely accumulating or distributing quietly. If price is near a known liquidity level and in a contraction phase, it might suggest that a large market player is building a position in anticipation of the next move.
Breakout Points: Liquidity levels can also give clues about where price could go after the breakout from the contraction phase. A break above a liquidity level might indicate a strong move to come as the market overcomes significant selling pressure.
Liquidity Levels in Expansion Phase:
Direct Confirmation: As the expansion phase begins, breaking through liquidity levels can confirm the new trend's direction. If the price moves past these levels with huge volume, it might indicate that the market has enough momentum to continue the trend.
Target Areas: Liquidity levels can act as target areas during the expansion phase. Traders using this indicator could look to take profits if the price approaches these levels, possibly expecting a reaction from the market.
Bitcoin Price to Volume per $1 FeeTransaction value to transaction fee:
The Bitcoin network's efficiency, usability and volume scalability has been improving over time and this can be measured by dividing the average transaction volume by the transaction fee.
The indicator give us:
Price to volume per $1 fee = BTC price / (avg tx value / avg tx fee)
A low ratio of "Price to volume per $1 fee" indicates that the Bitcoin network is being used for high volumes in comparison to the Bitcoin price, which means that the network is cost-effective compared to the price. On the other hand, a high "Price to volume per $1 fee" suggests that the average transaction size is smaller than the price of Bitcoin, which means that the network is less cost-effective compared to the Bitcoin price.
Note that the dynamics of transaction fees may change over time as new use cases emerge in the Bitcoin chain. These use cases include L2s such as Stacks, where DeFi applications can run, and Bitcoin Ordinals.
It's worth mentioning that Bitcoin is not only a cost-effective way of transferring value, but also highly energy efficient. Despite receiving criticism for its energy consumption, when we compare its energy usage to other industries (such as banking and gold) and correlate it with the transaction volumes, we can easily conclude that Bitcoin's energy efficiency is remarkable when compared to other methods of transferring value.
BTC Price to Hashrate Delta Ratio with MAHistorically, Hashrate and Bitcoin prices have a strong correlation. When hashrate increases more than Bitcoin price, it indicates a rise in Bitcoin price soon.
This indicator uses the formula:
Price/hashrate delta ratio = period price delta / period hashrate delta
Whenever the ratio between the price and hashrate of Bitcoin is positive, it indicates that the price is increasing at a faster rate than the hashrate. This, in turn, means that Bitcoin is becoming more expensive compared to any variations occurring in the hashrate. Using the Price/Hashrate Delta ratio, we can determine whether Bitcoin is overvalued or undervalued in relation to the hashrate. This can be a helpful indicator for assessing the current market conditions.
TTP Big Whale ExplorerThe Big Whale Explorer is an indicator that looks into the ratio of large wallets deposits vs withdrawals.
Whales tend to sale their holding when they transfer their holdings into exchanges and they tend to hold when they withdraw.
In this overlay indicator you'll be able to see in an oscillator format the moves of large wallets.
The moves above 1.5 turn into red symbolising that they are starting to distribute. This can eventually have an impact in the price by causing anything from a mild pullback to a considerable crash depending on how much is being actually sold into the market.
Moves below 0.5 mean that the large whales are heavily accumulating and withdrawing. During these periods price could still pullback or even crash but eventually the accumulation can take prices to new highs.
Instructions:
1) Load INDEX:BTCUSD or BNC:BLX to get the most historic data as possible
2) use the daily timeframe
3) load the indicator into the chart
USDT+USDC+BUSD Market CapThis Pine Script indicator visualizes the combined market capitalization of three prominent stablecoins: USDT, USDC, and BUSD, on a daily basis.
It fetches the daily closing market caps of these stablecoins and sums them. The resulting line graph is displayed in its own separate pane below the main price chart.
The line is color-coded: green on days when the market cap is increasing compared to the previous day, and red when it's decreasing.
