Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
Cerca negli script per "bitcoin"
ADA Stock-to-Flow Model (BSP)ADA Stock-to-Flow Model
This script implements a Stock-to-Flow (S2F) model for ADA (Cardano). The Stock-to-Flow ratio is a popular metric used to assess the scarcity of an asset by comparing its current supply (stock) to the rate at which it is being produced (flow). By visualizing the S2F ratio on ADA, this model helps traders and analysts evaluate potential long-term price trends based on supply scarcity.
Key features:
Calculates ADA's Stock-to-Flow ratio dynamically, adjusting for changes in circulating supply and emission rates.
Provides easy-to-read visualizations with adjustable timeframes, making it accessible for both novice and experienced traders.
The Stock-to-Flow model is widely used in analyzing assets like Bitcoin, and this adaptation for ADA gives unique insights into the relationship between its supply and market value. While the model offers a useful perspective on ADA’s potential trajectory, it should be used in conjunction with other tools for a comprehensive market analysis.
Realized Price Profit/Loss Margin [VWAP Optimized]Shaded Profit/Loss Margin Oscillator
The Shaded Profit/Loss Margin Oscillator is a powerful tool designed to measure Bitcoin’s Net Unrealized Profit/Loss (NUPL). This metric reflects the difference between Bitcoin’s current market price and its realized price, which approximates the price at which coins were last moved. By smoothing the NUPL using a moving average, the indicator provides a clean purple oscillator line that helps users easily gauge market sentiment. When the oscillator is above the zero line, the market is in profit, and when it is below zero, participants are generally in a state of unrealized loss. The shaded area between the oscillator and the zero line enhances visual clarity, making it easier to identify potential shifts in market behavior such as profit-taking or capitulation.
Unique Features and Added Value
What sets this indicator apart from traditional NUPL indicators is the use of a volume-weighted average price (VWAP) as a proxy for the realized price. Unlike the original on-chain NUPL metric, which relies on complex on-chain data, this indicator leverages VWAP to provide an approximation of realized price based solely on price and volume data available directly on TradingView. This method makes it highly accessible to traders who don’t have access to on-chain data platforms.
The use of VWAP not only simplifies the calculation but also provides additional value, as it incorporates volume into the realized price estimation. This volume-sensitive approach may offer a more responsive and dynamic reflection of realized prices compared to on-chain models, which can sometimes lag. In essence, this VWAP-based NUPL oscillator offers a unique edge in tracking profit/loss margins, particularly for traders who want a straightforward and efficient way to gauge sentiment without relying on external on-chain data sources. It brings the essence of NUPL into the world of technical analysis in an accessible and actionable way.
TechniTrend: Dynamic Pair CorrelationTechniTrend: Dynamic Pair Correlation
Description:
The TechniTrend: Dynamic Pair Correlation is a powerful and versatile indicator designed to track the correlation between two assets—whether cryptocurrencies, indices, or other financial instruments—across multiple timeframes. Understanding correlations can provide deep insights into market behavior, helping traders make informed decisions based on how two assets move in relation to each other.
Key Features:
Customizable Pair Selection: Compare any two assets (e.g., Bitcoin and DXY, Ethereum and SP500) to study how their price movements relate over time.
Multi-Timeframe Analysis: Simultaneously track correlations across different timeframes—standard, lower, and higher—providing a comprehensive view of market dynamics.
Dynamic Color Coding for Correlation Strength: Instantly spot correlations with visually intuitive colors—green for strong positive correlation, red for strong negative correlation, and yellow for neutral.
Heatmap Background: An easy-to-read background color heatmap highlights when correlations hit extreme levels, adding another layer of insight to your charts.
Real-Time Alerts: Get notified when correlations exceed your custom thresholds, signaling opportunities for potential breakouts, reversals, or divergences.
Divergence Detection: Automatically highlight moments when asset prices diverge, offering potential entry/exit points for smart trading decisions.
How to Use:
Asset Pair Comparison: Select two symbols to analyze their price correlation, such as BTC/USDT and DXY, or any other pair that fits your strategy.
Set Your Timeframes: Customize your standard, lower, and higher timeframes to monitor correlations at different intervals, allowing you to capture both short-term and long-term relationships.
Track Correlation Strength: Use dynamic color coding to quickly see how closely two assets are moving together. Strong correlations (positive or negative) could signal potential opportunities, while low correlations may indicate the absence of a strong trend.
Utilize Alerts: Receive real-time alerts when correlations cross your predefined thresholds, helping you take action when the market presents strong alignment or divergence.
Divergence Signals: Watch for divergence between the assets on multiple timeframes, which could indicate a potential trend reversal or a shift in market behavior.
Why It’s Essential:
Understanding the relationship between two assets can be a game changer for traders. Whether you're comparing Bitcoin to DXY, tracking the correlation between Ethereum and major indices, or evaluating two cryptocurrencies, this indicator gives you the tools to visualize and respond to market conditions with precision.
Perfect For:
Crypto traders looking to optimize strategies by monitoring the relationship between major cryptocurrencies and other assets.
Arbitrageurs seeking to capitalize on temporary pricing anomalies between correlated pairs.
Trend-followers aiming to catch large movements by detecting alignment or divergence between asset classes.
Portfolio managers monitoring how different asset classes impact each other to hedge or diversify investments.
By leveraging the TechniTrend: Dynamic Pair Correlation indicator, traders can gain deeper insights into market trends, correlations, and divergences, giving them an edge in fast-moving markets.
ETH Signal 15m
This strategy uses the Supertrend indicator combined with RSI to generate buy and sell signals, with stop loss (SL) and take profit (TP) conditions based on ATR (Average True Range). Below is a detailed explanation of each part:
1. General Information BINANCE:ETHUSDT.P
Strategy Name: "ETH Signal 15m"
Designed for use on the 15-minute time frame for the ETH pair.
Default capital allocation is 15% of total equity for each trade.
2. Backtest Period
start_time and end_time: Define the start and end time of the backtest period.
start_time = 2024-08-01: Start date of the backtest.
end_time = 2054-01-01: End date of the backtest.
The strategy will only run when the current time falls within this specified range.
3. Supertrend Indicator
Supertrend is a trend-following indicator that provides buy or sell signals based on the direction of price changes.
factor = 2.76: The multiplier used in the Supertrend calculation (increasing this value makes the Supertrend less sensitive to price movements).
atrPeriod = 12: Number of periods used to calculate ATR.
Output:
direction: Determines the buy/sell direction based on Supertrend.
If direction decreases, it signals a buy (Long).
If direction increases, it signals a sell (Short).
4. RSI Indicator
RSI (Relative Strength Index) is a momentum indicator, often used to identify overbought or oversold conditions.
rsiLength = 12: Number of periods used to calculate RSI.
rsiOverbought = 70: RSI level considered overbought.
rsiOversold = 30: RSI level considered oversold.
5. Entry Conditions
Long Entry:
Supertrend gives a buy signal (ta.change(direction) < 0).
RSI must be below the overbought level (rsi < rsiOverbought).
Short Entry:
Supertrend gives a sell signal (ta.change(direction) > 0).
RSI must be above the oversold level (rsi > rsiOversold).
The strategy will only execute trades if the current time is within the backtest period (in_date_range).
6. Stop Loss (SL) and Take Profit (TP) Conditions
ATR (Average True Range) is used to calculate the distance for Stop Loss and Take Profit based on price volatility.
atr = ta.atr(atrPeriod): ATR is calculated using 12 periods.
Stop Loss and Take Profit are calculated as follows:
Long Trade:
Stop Loss: Set at close - 4 * atr (current price minus 4 times the ATR).
Take Profit: Set at close + 2 * atr (current price plus 2 times the ATR).
Short Trade:
Stop Loss: Set at close + 4 * atr (current price plus 4 times the ATR).
Take Profit: Set at close - 2.237 * atr (current price minus 2.237 times the ATR).
Summary:
This strategy enters a Long trade when the Supertrend indicates an upward trend and RSI is not in the overbought region. Conversely, a Short trade is entered when Supertrend signals a downtrend, and RSI is not oversold.
The trade is exited when the price reaches the Stop Loss or Take Profit levels, which are determined based on price volatility (ATR).
Disclaimer:
The content provided in this strategy is for informational and educational purposes only. It is not intended as financial, investment, or trading advice. Trading in cryptocurrency, stocks, or any financial markets involves significant risk, and you may lose more than your initial investment. Past performance is not indicative of future results, and no guarantee of profit can be made. You should consult with a professional financial advisor before making any investment decisions. The creator of this strategy is not responsible for any financial losses or damages incurred as a result of following this strategy. All trades are executed at your own risk.
Potential Divergence Checker#### Key Features
1. Potential Divergence Signals:
Potential divergences can signal a change in price movement before it occurs. This indicator identifies potential divergences instead of waiting for full confirmation, allowing it to detect signs of divergence earlier than traditional methods. This provides more flexible entry points and can act as a broader filter for potential setups.
2. Exposing Signals for External Use:
One of its advanced features is the ability to expose signals for use in other scripts. This allows users to integrate divergence signals and related entry/exit points into custom strategies or automated systems.
3. Custom Entry/Exit Timing Based on Years and Days:
The indicator provides entry and exit signals based on years and days, which could be useful for time-specific market behavior, long-term trades, and back testing.
#### Basic Usage
This indicator can check for all types of potential divergences: bullish, hidden bullish, bearish, hidden bearish. All you need to do is choose the type you want to check for under “DIVERGENCE TYPE” in the settings. On the chart, potential bullish divergences will show up as triangles below the price candles. one the chart potential bearish divergences will show up as upside down triangles above the price candles
#### Signals for Advanced Usage
You can use this indicator as a source in other indicators or strategies using the following information:
“ PD: Bull divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBull divergence(hidden bull) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: Bear divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBear divergence(hidden bear) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: enter ” signal will return a “1” when both the days and years criteria in the “entry filter settings” are met and “0” when not met.
“ PD: exit ” signal will return a “1” when the days criteria in the “exit filter settings” are met and “0” when not met.
#### Examples of Using Signals
1. If you are testing a long strategy for Bitcoin and do not want it to run during bear market years(e.g., the second year after a US presidential election), you can enable the “year and day filter for entry,” uncheck the following years in the settings: 2010, 2014, 2018, 2022, 2026, and reference the signal below in our strategy
signal: “ PD: enter ”
2. Let’s say you have a good long strategy, but want to make it a bit more profitable, you can tell the strategy not to run on days where there is potential bearish divergence and have it only run on more profitable days using these signals and the appropriate settings in the indicator
signal: “ PD: Bear divergence signal ” will return a ‘0’ with no bearish divergence present
signal: “ PD: enter ” will return a “1” if the entry falls on a specific, more profitable day chosen in the settings
#### Disclaimer
The "Potential Divergence Checker" indicator is a tool designed to identify potential market signals. It may have bugs and not do what it should do. It is not a guarantee of future trading performance, and users should exercise caution when making trading decisions based on its outputs. Always perform your own research and consider consulting with a financial advisor before making any investment decisions. Trading involves significant risk, and past performance is not indicative of future results.
Swing Failure Pattern SFP [TradingFinder] SFP ICT Strategy🔵 Introduction
The Swing Failure Pattern (SFP), also referred to as a "Fake Breakout" or "False Breakout," is a vital concept in technical analysis. This pattern is derived from classic technical analysis, price action strategies, ICT concepts, and Smart Money Concepts.
It’s frequently utilized by traders to identify potential trend reversals in financial markets, especially in volatile markets like cryptocurrencies and forex. SFP helps traders recognize failed attempts to breach key support or resistance levels, providing strategic opportunities for trades.
The Swing Failure Pattern (SFP) is a popular strategy among traders used to identify false breakouts and potential trend reversals in the market. This strategy involves spotting moments where the price attempts to break above or below a previous high or low (breakout) but fails to sustain the move, leading to a sharp reversal.
Traders use this strategy to identify liquidity zones where stop orders (stop hunt) are typically placed and targeted by larger market participants or whales.
When the price penetrates these areas but fails to hold the levels, a liquidity sweep occurs, signaling exhaustion in the trend and a potential reversal. This strategy allows traders to enter the market at the right time and capitalize on opportunities created by false breakouts.
🟣 Types of SFP
When analyzing SFPs, two main variations are essential :
Real SFP : This occurs when the price breaks a critical level but fails to close above it, then quickly reverses. Due to its clarity and strong signal, this SFP type is highly reliable for traders.
Considerable SFP : In this scenario, the price closes slightly above a key level but quickly declines. Although significant, it is not as definitive or trustworthy as a Real SFP.
🟣 Understanding SFP
The Swing Failure Pattern, or False Breakout, is identified when the price momentarily breaks a crucial support or resistance level but cannot maintain the movement, leading to a rapid reversal.
The pattern can be categorized as follows :
Bullish SFP : This type occurs when the price dips below a support level but rebounds above it, signaling that sellers failed to push the price lower, indicating a potential upward trend.
Bearish SFP : This pattern forms when the price surpasses a resistance level but fails to hold, suggesting that buyers couldn’t maintain the higher price, leading to a potential decline.
🔵 How to Use
To effectively identify an SFP or Fake Breakout on a price chart, traders should follow these steps :
Identify Key Levels: Locate significant support or resistance levels on the chart.
Observe the Fake Breakout: The price should break the identified level but fail to close beyond it.
Monitor Price Reversal: After the breakout, the price should quickly reverse direction.
Execute the Trade: Traders typically enter the market after confirming the SFP.
🟣 Examples
Bullish Example : Bitcoin breaks below a $30,000 support level, drops to $29,000, but closes above $30,000 by the end of the day, signaling a Real Bullish SFP.
Bearish Example : Ethereum surpasses a $2,000 resistance level, rises to $2,100, but then falls back below $2,000, forming a Bearish SFP.
🟣 Pros and Cons of SFP
Pros :
Effective in identifying strong reversal points.
Offers a favorable risk-to-reward ratio.
Applicable across different timeframes.
Cons :
Requires experience and deep market understanding.
Risk of encountering false breakouts.
Should be combined with other technical tools for optimal effectiveness.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
SFP Type : Choose between "All", "Real" and "Considerable" modes to identify the swing failure pattern.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert SFP : Enables alerts for Swing Failure Pattern.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Swing Failure Pattern (SFP), or False Breakout, is an essential analytical tool that assists traders in identifying key market reversal points for successful trading.
By understanding the nuances between Real SFP and Considerable SFP, and integrating this pattern with other technical analysis tools, traders can make more informed decisions and better manage their trading risks.
Uptrick: Dual Moving Average Volume Oscillator
Title: Uptrick: Dual Moving Average Volume Oscillator (DPVO)
### Overview
The "Uptrick: Dual Moving Average Volume Oscillator" (DPVO) is an advanced trading tool designed to enhance market analysis by integrating volume data with price action. This indicator is specially developed to provide traders with deeper insights into market dynamics, making it easier to spot potential entry and exit points based on volume and price interactions. The DPVO stands out by offering a sophisticated approach to traditional volume analysis, setting it apart from typical volume indicators available on the TradingView platform.
### Unique Features
Unlike traditional indicators that analyze volume and price movements separately, the DPVO combines these two critical elements to offer a comprehensive view of market behavior. By calculating the Volume Impact, which involves the product of the exponential moving averages (EMAs) of volume and the price range (close - open), this indicator highlights significant trading activities that could indicate strong buying or selling pressure. This method allows traders to see not just the volume spikes, but how those spikes relate to price movements, providing a clearer picture of market sentiment.
### Customization and Inputs
The DPVO is highly customizable, catering to various trading styles and strategies:
- **Oscillator Length (`oscLength`)**: Adjusts the period over which the volume and price difference is analyzed, allowing traders to set it according to their trading timeframe.
- **Fast and Slow Moving Averages (`fastMA` and `slowMA`)**: These parameters control the responsiveness of the DPVO. A shorter `fastMA` coupled with a longer `slowMA` can help in identifying trends quicker or smoothing out market noise for more conservative approaches.
- **Signal Smoothing (`signalSmooth`)**: This input helps in reducing signal noise, making the crossover and crossunder points between the DVO and its smoothed signal line clearer and easier to interpret.
### Functionality Details
The DPVO operates through a sequence of calculated steps that integrate volume data with price movement:
1. **Volume Impact Calculation**: This is the foundational step where the product of the EMA of volume and the EMA of price range (close - open) is calculated. This metric highlights trading sessions where significant volume accompanies substantial price movements, suggesting a strong market response.
2. **Dynamic Volume Oscillator (DVO)**: The heart of the indicator, the DVO, is derived by calculating the difference between the fast EMA and the slow EMA of the Volume Impact. This result is then normalized by dividing by the EMA of the volume over the same period to scale the output, making it consistent across various trading environments.
3. **Signal Generation**: The final output is smoothed using a simple moving average of the DVO to filter out market noise. Buy and sell signals are generated based on the crossover and crossunder of the DVO with its smoothed version, providing clear cues for market entry or exit.
### Originality
The DPVO's originality lies in its innovative integration of volume and price movement, a novel approach not typically observed in other volume indicators. By analyzing the product of volume and price change EMAs, the DPVO captures the essence of market dynamics more holistically than traditional tools, which often only reflect volume levels without contextualizing them with price actions. This dual analysis provides traders with a deeper understanding of market forces, enabling them to make more informed decisions based on a combination of volume surges and significant price movements. The DPVO also introduces a unique normalization and smoothing technique that refines the oscillator's output, offering cleaner and more reliable signals that are adaptable to various market conditions and trading styles.
### Practical Application
The DPVO excels in environments where volume plays a crucial role in validating price movements. Traders can utilize the buy and sell signals generated by the DPVO to enhance their decision-making process. The signals are plotted directly on the trading chart, with buy signals appearing below the price bars and sell signals above, ensuring they are prominent and actionable. This setup is particularly useful for day traders and swing traders who rely on timely and accurate signals to maximize their trading opportunities.
### Best Practices
To maximize the effectiveness of the DPVO, traders should consider the following best practices:
- **Market Selection**: Use the DPVO in markets known for strong volume-price correlation such as major forex pairs, popular stocks, and cryptocurrencies.
- **Signal Confirmation**: While the DPVO provides powerful signals, confirming these signals with additional indicators such as RSI or MACD can increase trade reliability.
- **Risk Management**: Always use stop-loss orders to manage risks associated with trading signals. Adjust the position size based on the volatility of the asset to avoid significant losses.
### Practical Example + How to use it
Practical Example1: Day Trading Cryptocurrencies
For a day trader focusing on the highly volatile cryptocurrency market, the DPVO can be an effective tool on a 15-minute chart. Suppose a trader is monitoring Bitcoin (BTC) during a period of high market activity. The DPVO might show an upward crossover of the DVO above its smoothed signal line while also indicating a significant increase in volume. This could signal that strong buying pressure is entering the market, suggesting a potential short-term rally. The trader could enter a long position based on this signal, setting a stop-loss just below the recent support level to manage risk. If the DPVO later shows a crossover in the opposite direction with decreasing volume, it might signal a good exit point, allowing the trader to lock in profits before a potential pullback.
- **Swing Trading Stocks**: For a swing trader looking at stocks, the DPVO could be applied on a daily chart. If the oscillator shows a consistent downward trend along with increasing volume, this could suggest a potential sell-off, providing a sell signal before a significant downturn.
You can look for:
--> Increase in volume - You can use indicators like 24-hour-Volume to have a better visualization
--> Uptrend/Downtrend in the indicator (HH, HL, LL, LH)
--> Confirmation (Buy signal/Sell signal)
--> Correct Price action (Not too steep moves up or down. Stable moves.) (Optional)
--> Confirmation with other indicators (Optional)
Quick image showing you an example of a buy signal on SOLANA:
### Technical Notes
- **Calculation Efficiency**: The DPVO utilizes exponential moving averages (EMAs) in its calculations, which provides a balance between responsiveness and smoothing. EMAs are favored over simple moving averages in this context because they give more weight to recent data, making the indicator more sensitive to recent market changes.
- **Normalization**: The normalization of the DVO by the EMA of the volume ensures that the oscillator remains consistent across different assets and timeframes. This means the indicator can be used on a wide variety of markets without needing significant adjustments, making it a versatile tool for traders.
- **Signal Line Smoothing**: The final signal line is smoothed using a simple moving average (SMA) to reduce noise. The choice of SMA for smoothing, as opposed to EMA, is intentional to provide a more stable signal that is less prone to frequent whipsaws, which can occur in highly volatile markets.
- **Lag and Sensitivity**: Like all moving average-based indicators, the DPVO may introduce a slight lag in signal generation. However, this is offset by the indicator’s ability to filter out market noise, making it a reliable tool for identifying genuine trends and reversals. Adjusting the `fastMA`, `slowMA`, and `signalSmooth` inputs allows traders to fine-tune the sensitivity of the DPVO to match their specific trading strategy and market conditions.
- **Platform Compatibility**: The DPVO is written in Pine Script™ v5, ensuring compatibility with the latest features and functionalities offered by TradingView. This version takes advantage of optimized functions for performance and accuracy in calculations, making it well-suited for real-time analysis.
Conclusion
The "Uptrick: Dual Moving Average Volume Oscillator" is a revolutionary tool that merges volume analysis with price movement to offer traders a more nuanced understanding of market trends and reversals. Its ability to provide clear, actionable signals based on a unique combination of volume and price changes makes it an invaluable addition to any trader's toolkit. Whether you are managing long-term positions or looking for quick trades, the DPVO provides insights that can help refine any trading strategy, making it a standout choice in the crowded field of technical indicators.
Nothing from this indicator or any other Uptrick Indicators is financial advice. Only you are ultimately responsible for your choices.
Cumulative Net VolumeCumulative Calculation: Summarizes the net volume (buying minus selling volume) cumulatively, providing a running total that reflects the aggregate trading pressure.
Custom Timeframe Flexibility: Users can choose to analyze the volume on a custom timeframe, enhancing adaptability for various trading strategies.
Color-Coded Visualization: Features an intuitive color scheme where green indicates a net buying dominance and red signals net selling dominance, making it easier to interpret shifts in market dynamics.
Versatility: Suitable for all types of assets available on TradingView including cryptocurrencies like Bitcoin, stocks, forex, and more.
Utility: This tool is particularly useful for identifying trends in buying or selling pressure, which could be pivotal during significant market events or when assessing the potential for a trend reversal. By understanding the accumulation and distribution phases through the cumulative net volume, traders can make more informed decisions.
Perfect for both novice traders looking to get a grip on volume analysis and seasoned professionals seeking an edge in their trading tactics.
Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Volume Weighted Average Price Ratio (log) [ilyaQwerty]The VWAP Ratio indicator is a valuable tool for traders aiming to assess market trends and price movements in relation to the Volume Weighted Average Price (VWAP). Volume Weighted Average Price Ratio represents the ratio of the price of the asset compared to total traded volume in US Dollars. In a context of Bitcoin, VWAP ratio helps traders assess the market state, if it is overvalued or undervalued. High values of the indicator can suggest that the market is highly overvalued and low values can indicate a great buying opportunity.
Ratio Calculation: The VWAP Ratio is computed by dividing the current price by the VWAP (Price / VWAP). VWAP represents a ratio between a cumulative sum of a traded value (price multiplied by the volume) and a cumulative traded volume.
BTC-Specific Optimization: Although the indicator can be applied to various assets, the VWAP Ratio indicator is particularly useful for Bitcoin (BTC) due to its significant trading volume and unique market behaviour.
Coinbase Premium ($) Absolute Dollar Amount # Coinbase Dollar Premium Indicator
## Description
The Coinbase Dollar Premium Indicator is a powerful tool for cryptocurrency traders and analysts, providing real-time insight into the price differences between major exchanges. This indicator calculates and visualizes the dollar amount premium or discount of Bitcoin on Coinbase compared to the average price on Binance and Kraken.
## Key Features
1. **Dollar Value**: Unlike percentage-based indicators, this tool shows the actual dollar amount difference, giving traders a clear understanding of the magnitude of price disparities.
2. **Multi-Exchange Comparison**: By averaging the prices from Binance and Kraken, the indicator provides a more robust baseline for comparison, reducing the impact of single-exchange anomalies.
3. **Clear Visual Representation**: The indicator uses a color-coded histogram for easy interpretation:
- Green bars indicate a premium on Coinbase (Coinbase price is higher)
- Red bars indicate a discount on Coinbase (Coinbase price is lower)
- The height of each bar represents the dollar amount of the premium or discount
4. **Zero Line Reference**: A horizontal line at zero helps quickly distinguish between premium and discount states.
## Use Cases
- **Arbitrage Opportunities**: Identify potential arbitrage opportunities between exchanges.
- **Market Sentiment**: Gauge institutional and retail investor sentiment, as Coinbase is often associated with US institutional activity.
- **Price Prediction**: Use divergences between exchanges as a potential indicator of short-term price movements.
- **Risk Management**: Understand the pricing landscape across major exchanges to make more informed trading decisions.
This indicator is valuable for both short-term traders looking for quick opportunities and long-term investors wanting to understand market dynamics. By providing a clear, dollar-based view of inter-exchange price differences, the Coinbase Dollar Premium Indicator offers unique insights into the cryptocurrency market's microstructure.
*Note: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consider your risk tolerance before trading.*
HRC - Hash Rate Capitulation [Da_Prof]The HRC (Hash Rate Capitulation) indicator is a measure of hash rate trend strength. It is the fractional difference between a long and a short simple moving average (SMA) of the bitcoin hash rate. Historically, the 21-day and 105-day SMA work well for this indicator. The hash rate generally increases over time, but when the short SMA crosses below the longer-term SMA, it shows that miners are removing significant hash from the system. This state can be considered a miner "capitulation". Historically, this has marked depressed BTC prices and has led to higher prices within some months. Shout out to foosmoo, the hash rate oscillator indicator prompted this presentation.
BTC outperform atrategy### Code Description
This Pine Script™ code implements a simple trading strategy based on the relative prices of Bitcoin (BTC) on a weekly and a three-month basis. The script plots the weekly and three-month closing prices of Bitcoin on the chart and generates trading signals based on the comparison of these prices. The code can also be applied to Ethereum (ETH) with similar effectiveness.
### Explanation
1. **Inputs and Variables**:
- The user selects the trading symbol (default is "BINANCE:BTCUSDT").
- `weeklyPrice` retrieves the closing price of the selected symbol on a weekly interval.
- `monthlyPrice` retrieves the closing price of the selected symbol on a three-month interval.
2. **Plotting Data**:
- The weekly price is plotted in blue.
- The three-month price is plotted in red.
3. **Trading Conditions**:
- A long position is suggested if the weekly price is greater than the three-month price.
- A short position is suggested if the three-month price is greater than the weekly price.
4. **Strategy Execution**:
- If the long condition is met, the strategy enters a long position.
- If the short condition is met, the strategy enters a short position.
This script works equally well for Ethereum (ETH) by changing the symbol input to "BINANCE:ETHUSDT" or any other desired Ethereum trading pair.
CryptoLibrary "Crypto"
This Library includes functions related to crytocurrencies and their blockchain
btcBlockReward(t)
Delivers the BTC block reward for a specific date/time
Parameters:
t (int) : Time of the current candle
Returns: blockRewardBtc
Crypto SeasonDefinition
This indicator is an informative indicator aiming to predict when the Altcoin season will start and when Bitcoin will enter the month season.
The average of the graph shows the dominance of altcoins other than BTC, ETH and USDT. If this value is over 30, the BTC says that the bull season is over. This value indicates that 20 to 30 BTC is in the bull season or accumulation. If this value is less than 20, it means that the subcoin season has begun.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
Dickey-Fuller Test for Mean Reversion and Stationarity **IF YOU NEED EXTRA SPECIAL HELP UNDERSTANDING THIS INDICATOR, GO TO THE BOTTOM OF THE DESCRIPTION FOR AN EVEN SIMPLER DESCRIPTION**
Dickey Fuller Test:
The Dickey-Fuller test is a statistical test used to determine whether a time series is stationary or has a unit root (a characteristic of a time series that makes it non-stationary), indicating that it is non-stationary. Stationarity means that the statistical properties of a time series, such as mean and variance, are constant over time. The test checks to see if the time series is mean-reverting or not. Many traders falsely assume that raw stock prices are mean-reverting when they are not, as evidenced by many different types of statistical models that show how stock prices are almost always positively autocorrelated or statistical tests like this one, which show that stock prices are not stationary.
Note: This indicator uses past results, and the results will always be changing as new data comes in. Just because it's stationary during a rare occurrence doesn't mean it will always be stationary. Especially in price, where this would be a rare occurrence on this test. (The Test Statistic is below the critical value.)
The indicator also shows the option to either choose Raw Price, Simple Returns, or Log Returns for the test.
Raw Prices:
Stock prices are usually non-stationary because they follow some type of random walk, exhibiting positive autocorrelation and trends in the long term.
The Dickey-Fuller test on raw prices will indicate non-stationary most of the time since prices are expected to have a unit root. (If the test statistic is higher than the critical value, it suggests the presence of a unit root, confirming non-stationarity.)
Simple Returns and Log Returns:
Simple and log returns are more stationary than prices, if not completely stationary, because they measure relative changes rather than absolute levels.
This test on simple and log returns may indicate stationary behavior, especially over longer periods. (The test statistic being below the critical value suggests the absence of a unit root, indicating stationarity.)
Null Hypothesis (H0): The time series has a unit root (it is non-stationary).
Alternative Hypothesis (H1): The time series does not have a unit root (it is stationary)
Interpretation: If the test statistic is less than the critical value, we reject the null hypothesis and conclude that the time series is stationary.
Types of Dickey-Fuller Tests:
1. (What this indicator uses) Standard Dickey-Fuller Test:
Tests the null hypothesis that a unit root is present in a simple autoregressive model.
This test is used for simple cases where we just want to check if the series has a consistent statistical property over time without considering any trends or additional complexities.
It examines the relationship between the current value of the series and its previous value to see if the series tends to drift over time or revert to the mean.
2. Augmented Dickey-Fuller (ADF) Test:
Tests for a unit root while accounting for more complex structures like trends and higher-order correlations in the data.
This test is more robust and is used when the time series has trends or other patterns that need to be considered.
It extends the regular test by including additional terms to account for the complexities, and this test may be more reliable than the regular Dickey-Fuller Test.
For things like stock prices, the ADF would be more appropriate because stock prices are almost always trending and positively autocorrelated, while the Dickey-Fuller Test is more appropriate for more simple time series.
Critical Values
This indicator uses the following critical values that are essential for interpreting the Dickey-Fuller test results. The critical values depend on the chosen significance levels:
1% Significance Level: Critical value of -3.43.
5% Significance Level: Critical value of -2.86.
10% Significance Level: Critical value of -2.57.
These critical values are thresholds that help determine whether to reject the null hypothesis of a unit root (non-stationarity). If the test statistic is less than (or more negative than) the critical value, it indicates that the time series is stationary. Conversely, if the test statistic is greater than the critical value, the series is considered non-stationary.
This indicator uses a dotted blue line by default to show the critical value. If the test-static, which is the gray column, goes below the critical value, then the test-static will become yellow, and the test will indicate that the time series is stationary or mean reverting for the current period of time.
What does this mean?
This is the weekly chart of BTCUSD with the Dickey-Fuller Test, with a length of 100 and a critical value of 1%.
So basically, in the long term, mean-reversion strategies that involve raw prices are not a good idea. You don't really need a statistical test either for this; just from seeing the chart itself, you can see that prices in the long term are trending and no mean reversion is present.
For the people who can't understand that the gray column being above the blue dotted line means price doesn't mean revert, here is a more simple description (you know you are):
Average (I have to include the meaning because they may not know what average is): The middle number is when you add up all the numbers and then divide by how many numbers there are. EX: If you have the numbers 2, 4, and 6, you add them up to get 12, and then divide by 3 (because there are 3 numbers), so the average is 4. It tells you what a typical number is in a group of numbers.
This indicator checks if a time series (like stock prices) tends to return to its average value or time.
Raw prices, which is just the regular price chart, are usually not mean-reverting (It's "always" positively autocorrelating but this group of people doesn't like that word). Price follows trends.
Simple returns and log returns are more likely to have periods of mean reversion.
How to use it:
Gray Column (the gray bars) Above the Blue Dotted Line: The price does not mean revert (non-stationary).
Gray Column Below Blue Line: The time series mean reverts (stationary)
So, if the test statistic (gray column) is below the critical value, which is the blue dotted line, then the series is stationary and mean reverting, but if it is above the blue dotted line, then the time series is not stationary or mean reverting, and strategies involving mean reversion will most likely result in a loss given enough occurrences.
[r380]Bear & Bull Pivot Signal Indicator_(Lite))Bear & Bull Pivot Signal Indicator
Overview:
The Bear & Bull Multi Pivot Signal Indicator is a comprehensive trading tool designed to identify potential market reversal points and trend changes. This indicator combines multiple technical analysis strategies such as RSI, MACD, and pivot points to generate reliable signals. By overlapping these signals, the indicator increases the possibility of accurate trend predictions, providing traders with valuable insights for informed decision-making.
"This indicator is primarily optimized for Bitcoin on a 15-minute timeframe and is recommended for short-term trading. Reliability on other timeframes is not guaranteed."
Key Features:
Bear and Bull Signals: Clearly indicate potential market reversal points using bear and bull emojis.
Support and Resistance Signals: Indicated with sun and snowflake emojis to show critical price levels.
Overheat Cooldown Pivot: Detects market exhaustion points to signal potential reversals.
Settings:
RSI Settings: Adjust the RSI period and thresholds to match your trading strategy. Default values are optimized for short-term trading.
MACD Settings: The MACD settings are pre-configured but can be customized if needed.
Visual Settings: If excessive signals cause visual discomfort, you can selectively enable or disable features in the visual settings.
Signal Descriptions:
🐻 Bear Signal: Indicates a potential high point where the market may reverse downwards. Combines RSI and MACD conditions to provide a reliable overbought signal. When accompanied by high volume, it can indicate a strong resistance level.
🐮 Bull Signal: Indicates a potential low point where the market may reverse upwards. Uses both RSI and MACD conditions to highlight oversold situations. When accompanied by high volume, it can indicate a strong support level.
❄️ Resistance Signal: Shows a resistance level where the price has difficulty moving higher. When the price crosses below this level, it signals a potential downward movement. Combined with high volume, it can signify robust resistance.
☀️ Support Signal: Shows a support level where the price has difficulty moving lower. When the price crosses above this level, it signals a potential upward movement. Combined with high volume, it can signify strong support.
Detailed Explanation:
This indicator is not simply a combination of multiple indicators but is designed to increase the probability of detecting potential trend reversal signals by using multiple signals. If signals only appear when multiple conditions are met, how many trades can we make in a year? Because there is no 100% certainty in any situation, we need to use various signals to construct our strategy and proceed with trading. For example, if only one signal appears, the reliability of the trend reversal signal is somewhat weak, so we can strategize by betting only a portion of the capital. If multiple signals appear simultaneously, we can consider it a highly reliable trend reversal signal and increase the betting amount and stop loss accordingly. The essence of this indicator, in my view, is not to blindly trade based on signals but to use it as an auxiliary tool for strategic decision-making.
RSI (Relative Strength Index), MACD, and Stochastic RSI: By using various indicators to confirm trend reversal signals, bear and bull emojis are included. If the RSI reaches an oversold zone and then drops by a certain amount, while the MACD turns negative and the Stochastic RSI makes a gold or dead cross, the bear and bull signals are activated.
Pivot Points: Calculated based on the high, low, and close prices over a specific lookback period. These points are used to determine support and resistance levels. Pivot points provide a framework for assessing market sentiment and potential reversal zones. The values calculated this way activate the sun and snowflake signals.
The Overheat Cooldown Pivot: captures moments when the market shows signs of exhaustion, particularly when overbought or oversold conditions are accompanied by a drop in volume. This helps traders anticipate market turning points more effectively. These signals appear as red or green triangles indicating potential reversals. Although similar to the bear and bull signals in detecting market cool-off points, these signals rely on volume and may have slightly lower reliability.
Practical Application:
By using this indicator, traders can strategically adjust their bet sizes based on the reliability of the signals. When multiple signals coincide, it indicates a higher probability of a trend reversal, allowing for larger position sizes. Conversely, when signals occur independently, it suggests a lower probability, warranting smaller position sizes. This approach enables traders to manage their risk effectively and capitalize on high-probability trading opportunities without excessively reducing trading frequency.
Trading Method:
The basic setup is for Bitcoin on a 15-minute timeframe, and short-term trading is recommended by the creator. Upon signal activation, if only one signal appears, verify the volume and support/resistance lines, calculate the risk-reward ratio, and enter a position with a low betting ratio. If three signals activate simultaneously, enter a position with a higher betting ratio.
Reliability Order:
🐻🐮 > ❄️☀️ > 🔻🔺 (replacing green triangle emojis)
This indicator provides a powerful method for detecting multiple potential market reversals and trend continuations.
Note: Have realistic expectations and understand the limitations of technical analysis tools. This indicator is a tool to assist in your trading decisions and not a guaranteed prediction of market movements.
Warning! Do not trade solely based on this indicator.
Additionally, if you find the settings lacking, feel free to adjust them yourself! Thank you!
Korean Version
곰돌이와 송아지 멀티 피봇 시그널 인디케이터
개요:
곰돌이와 송아지 멀티 피봇 시그널 인디케이터는 잠재적 시장 반전 지점과 추세 변화를 식별하기 위해 설계된 종합 거래 도구입니다. 이 인디케이터는 RSI, MACD, 피봇 포인트 등의 여러 기술 분석 전략을 결합하여 신뢰할 수 있는 신호를 생성합니다. 이러한 신호들을 중첩함으로써 정확한 추세 예측의 가능성을 높여, 트레이더가 정보를 기반으로 결정을 내리는 데 유용한 통찰력을 제공합니다.
기본적으로 비트코인 15분봉을 기준으로 하며 매매 방법은 단타를 권장합니다. 다른 타임프레임에서의 신뢰는 보장 하지 않습니다.
주요 기능:
곰돌이와 송아지 신호: 시장의 잠재적 반전 지점을 곰돌이와 송아지 이모지로 명확하게 표시합니다.
지지 및 저항 신호: 중요한 가격 수준을 나타내기 위해 태양과 눈송이 이모지로 표시합니다.
오버히트 쿨다운 피봇: 시장 피로 지점을 감지하여 잠재적 반전 신호를 제공합니다.
세팅방법:
RSI 설정: RSI 기간과 임계값을 조정하여 자신의 거래 전략에 맞춥니다. 기본값은 단기 거래에 최적화되어 있습니다.
MACD 설정: MACD 설정은 미리 구성되어 있으며, 필요에 따라 사용자 정의가 가능합니다.
비쥬얼 세팅: 과도한 시그널 때문에 눈이 아프시다면 비쥬얼세팅에서 선택적으로 기능들을 켜거나 끌 수 있으니 참고하세요.
신호 설명:
🐻 곰돌이 신호: 시장이 하락할 가능성이 있는 고점을 나타냅니다. RSI와 MACD 조건을 결합하여 신뢰할 수 있는 과매수 신호를 제공합니다. 높은 거래량과 함께 나타나면 강한 저항 수준을 나타낼 수 있습니다.
🐮 송아지 신호: 시장이 상승할 가능성이 있는 저점을 나타냅니다. RSI와 MACD 조건을 사용하여 과매도 상황을 강조합니다. 높은 거래량과 함께 나타나면 강한 지지 수준을 나타낼 수 있습니다.
❄️ 저항 신호: 가격이 더 이상 상승하기 어려운 저항 수준을 나타냅니다. 가격이 이 수준 아래로 하락하면 잠재적 하락 움직임을 신호합니다. 높은 거래량과 함께 나타나면 강력한 저항을 의미할 수 있습니다.
☀️ 지지 신호: 가격이 더 이상 하락하기 어려운 지지 수준을 나타냅니다. 가격이 이 수준 위로 상승하면 잠재적 상승 움직임을 신호합니다. 높은 거래량과 함께 나타나면 강한 지지를 의미할 수 있습니다.
상세 설명:
이 인디케이터는 여러 인디케이터를 단순히 결합한 것이 아니라, 여러가지 시그널들을 사용해서 잠재적 추세전환 신호 감지 확률을 높이는 것에 목적이 있습니다. 단순히 여러가지 조건들이 중첩되었을때만 신호가 뜬다면 우리는 1년에 몇번이나 매매를 할 수 있을까요. 모든경우에 100% 라는 경우가 없기때문에 우리는 다양한 신호들을 활용하여 전략을 구성하고 매매를 진행 해야합니다. 예를들어 1개의 시그널만 뜬다면 추세전환 신호의 신뢰도가 다소 약하기 때문에 시드의 일부 금액만 배팅 하는 식으로 전략을 구성 할 수도 있고, 만약 여러가지 시그널들이 충접적으로 뜬다면 신뢰도 높은 추세전환의 신호로 인식하여 배팅금액을 높이고 스탑로스를 높게 잡는 방향으로 전략을 구성 할 수 있습니다. 단순히 맹목적으로 시그널이 떳다고 매매하는것이 아닌 보조 신호로써의 기능, 이것이 내가 생각하는 인디케이터의 역할이자 본질 이라고 생각합니다.
RSI (상대 강도 지수)와 MACD, 스토캐스틱 RSI: 여러가지 지표들을 기반으로 추세 반전의 신호를 확인 할 수 있는 곰돌이와 송아지를 넣었습니다. RSI 가 과매도 구간에 도달한 이후일정 수치 이상 하락하는 동시에 MACD가 음수로 변하고 스토캐스틱 RSI가 골드, 데드 크로스가 된다면 곰돌이와 송아지 신호가 활성화 됩니다.
피봇 포인트: 특정 되돌아보기 기간 동안의 최고, 최저, 종가를 기반으로 계산됩니다. 이 포인트는 지지 및 저항 수준을 결정하는 데 사용됩니다. 피봇 포인트는 시장 심리와 잠재적 반전 영역을 평가하는 프레임워크를 제공합니다. 이렇게 계산된 값을 기반으로 눈송이와 해 신호가 활성화 됩니다.
오버히트 쿨다운 피봇: 는 과매수 또는 과매도 상태에서 거래량이 감소할 때 시장 피로 지점을 포착하여 잠재적 반전 지점을 신호합니다. 이러한 피로 지점을 식별함으로써 인디케이터는 트레이더가 시장의 전환점을 보다 효과적으로 예측할 수 있도록 돕습니다. 그렇게 추세 반전의 신호로 녹색 또는 붉은색 삼각형 시그널이 뜹니다. 과열된 시장이 냉각되는 포인트를 찾는점에서는 곰돌이 송아지 신호와 비슷하지만 거래량을 기반으로 하고 있기 때문에 명백히 다른 시그널이며 신뢰도는 약간 낮을 수도 있습니다
실용적 적용:
이 인디케이터를 사용함으로써, 트레이더는 신호의 신뢰도에 따라 베팅 크기를 전략적으로 조정할 수 있습니다. 여러 신호가 동시에 나타날 때, 이는 추세 반전의 가능성이 높음을 나타내며, 더 큰 포지션 크기를 허용합니다. 반대로, 신호가 독립적으로 발생할 때는 낮은 가능성을 나타내므로 작은 포지션 크기가 적합합니다. 이 접근 방식은 트레이더가 효과적으로 리스크를 관리하고 높은 확률의 거래 기회를 활용하면서 거래 빈도를 과도하게 줄이는 것을 방지할 수 있게 합니다.
매매방법:
기본적인 세팅은 비트코인 15분 타임프레임이며 제작자는 단타를 추천합니다. 포지션 진입시 시그널이 1개가 뜬다면 거래량과 지지와 저항라인을 확인하고 손익비를 계산후 낮은 배팅 비율로 포지션에 진입합니다. 만약에 3개의 시그널이 동시에 활성화 된다면 보다 높은 비율로 포지션에 진입합니다.
신뢰도 순서:
]🐻🐮 > ❄️☀️ > 🔻🔺(초록 삼각이모지가 없기때문에 이것으로 대체)
이 지표는 여러 잠재적인 시장 반전 및 추세 지속성을 감지하는 강력한 방법을 제공합니다.
참고: 현실적인 기대를 가지고 기술 분석 도구의 한계를 이해하십시오. 이 지표는 시장 움직임을 보장하는 예측이 아니라 거래 결정을 돕기 위한 도구입니다.
경고! 절대 이 지표만을 가지고 매매하지 마십쇼.
추가적으로 제작자는 지표 세팅에 허접이라 꼬우면 당신이 세팅하십쇼! 감사합니다!
MC vs Total MCMC vs Total MC
this is an edit of StableCoin MC vs Total MC by Crypto5Max supporting muti timeframes and addition dominances
is a powerful and versatile TradingView indicator designed to help traders and analysts visualize the dominance of different types of cryptocurrencies (StableCoin, AltCoin, BTC, ETH) relative to the total market capitalization. This indicator provides a clear and concise way to monitor market trends and make informed decisions based on the dominance of specific cryptocurrency segments.
Key Features:
Customizable Time Frames: Select from a variety of time frames including 5 Min, 15 Min, 30 Min, 1HR, 2HR, 4HR, 8HR, and Daily to tailor the analysis to your needs.
Dominance Type Selection: Choose the type of market capitalization dominance you want to track - StableCoins, AltCoins, Bitcoin, or Ethereum.
Total Market Capitalization Options: Analyze the market with different total market capitalization metrics - total crypto market cap, total market cap excluding BTC, or total market cap excluding BTC and ETH.
Dynamic Label Display: A label that follows the plotted dominance line and dynamically displays the dominance percentage, providing a clear visual representation.
Invisible Background Option: Choose to have an invisible background for a cleaner chart presentation.
How It Works:
Time Frame Selection: Use the time_frame input to choose the desired time frame for your analysis.
Dominance Type Selection: Select the type of dominance to display using the mcap_type input.
Total Market Capitalization Selection: Choose the total market capitalization metric with the total_sym input.
Dominance Calculation: The indicator calculates the dominance of the selected cryptocurrency type as a percentage of the total market capitalization.
Visual Display: The chosen dominance is plotted on the chart, and a label displaying the dominance percentage is dynamically updated to follow the plotted line.
Use Cases:
Market Trend Analysis: Identify trends in the dominance of StableCoins, AltCoins, BTC, or ETH to gauge market sentiment.
Portfolio Allocation: Make informed decisions about portfolio allocation by understanding the market share of different cryptocurrency types.
Technical Analysis: Combine with other technical indicators to enhance your trading strategy and gain deeper market insights.
This indicator is essential for traders, analysts, and investors who want to stay ahead of market movements and make data-driven decisions based on the dominance of various cryptocurrency segments.
Example:
If you select "AltCoin" as the dominance type and "Total 3" as the total market capitalization, the indicator will plot the dominance of AltCoins (excluding BTC and ETH) as a percentage of the total crypto market capitalization (excluding BTC and ETH) on the selected time frame. The dynamic label will display this percentage, updating as the market evolves.
Elevate your market analysis with the MC vs Total MC indicator and gain a comprehensive view of cryptocurrency dominance trends.
Ticker Performance ComparisonTicker Performance Comparison Indicator
With this tool you can compare how three different tickers of your choice have performed over a specific period you choose. It can be used on any timeframe.
As you can see in the image above, I am comparing Nvidia, Bitcoin and Wadzpay over a 365 day period. This shows me at glance which asset has done better and by how much.
It shows how the closing prices have changed from the start of your chosen period to now, by automatically drawing lines on the same scale.
Key Features:
Lookback Period: You decide how many bars (days, weeks, etc.) back to look from today.
Three Tickers: Enter up to three different ticker symbols to see how they stack up against each other
Percentage Change: The tool calculates how much each ticker's closing price has changed, in percentage terms, from the start of your lookback period.
Performance Labels: Labels at the end of the period show the percentage change for each ticker.
Important:
Ignore the lines that are drawn before your lookback period: The lines before your chosen lookback period might be misleading. They appear due to the way historical data is processed and should be ignored. Only consider the data and trends from the start of the lookback period you entered to the present for an accurate comparison.
Use this tool to easily compare how different assets have performed over the timeframe that matters to you.
VolCorrBeta [NariCapitalTrading]Indicator Overview: VolCorrBeta
The VolCorrBeta indicator is designed to analyze and interpret intermarket relationships. This indicator combines volatility, correlation, and beta calculations to provide a comprehensive view of how certain assets (BTC, DXY, CL) influence the ES futures contract (I tailored this indicator to the ES contract, but it will work for any symbol).
Functionality
Input Symbols
BTCUSD : Bitcoin to USD
DXY : US Dollar Index
CL1! : Crude Oil Futures
ES1! : S&P 500 Futures
These symbols can be customized according to user preferences. The main focus of the indicator is to analyze how the price movements of these assets correlate with and lead the price movements of the ES futures contract.
Parameters for Calculation
Correlation Length : Number of periods for calculating the correlation.
Standard Deviation Length : Number of periods for calculating the standard deviation.
Lookback Period for Beta : Number of periods for calculating beta.
Volatility Filter Length : Length of the volatility filter.
Volatility Threshold : Threshold for adjusting the lookback period based on volatility.
Key Calculations
Returns Calculation : Computes the daily returns for each input symbol.
Correlation Calculation : Computes the correlation between each input symbol's returns and the ES futures contract returns over the specified correlation length.
Standard Deviation Calculation : Computes the standard deviation for each input symbol's returns and the ES futures contract returns.
Beta Calculation : Computes the beta for each input symbol relative to the ES futures contract.
Weighted Returns Calculation : Computes the weighted returns based on the calculated betas.
Lead-Lag Indicator : Calculates a lead-lag indicator by averaging the weighted returns.
Volatility Filter : Smooths the lead-lag indicator using a simple moving average.
Price Target Estimation : Estimates the ES price target based on the lead-lag indicator (the yellow line on the chart).
Dynamic Stop Loss (SL) and Take Profit (TP) Levels : Calculates dynamic SL and TP levels using volatility bands.
Signal Generation
The indicator generates buy and sell signals based on the filtered lead-lag indicator and confirms them using higher timeframe analysis. Signals are debounced to reduce frequency, ensuring that only significant signals are considered.
Visualization
Background Coloring : The background color changes based on the buy and sell signals for easy visualization (user can toggle this on/off).
Signal Labels : Labels with arrows are plotted on the chart, showing the signal type (buy/sell), the entry price, TP, and SL levels.
Estimated ES Price Target : The estimated price target for ES futures is plotted on the chart.
Correlation and Beta Dashboard : A table displayed in the top right corner shows the current correlation and beta values for relative to the ES futures contract.
Customization
Traders can customize the following parameters to tailor the indicator to their specific needs:
Input Symbols : Change the symbols for BTC, DXY, CL, and ES.
Correlation Length : Adjust the number of periods used for calculating correlation.
Standard Deviation Length : Adjust the number of periods used for calculating standard deviation.
Lookback Period for Beta : Change the lookback period for calculating beta.
Volatility Filter Length : Modify the length of the volatility filter.
Volatility Threshold : Set a threshold for adjusting the lookback period based on volatility.
Plotting Options : Customize the colors and line widths of the plotted elements.
Funding Rate [CryptoSea]The Funding Rate Indicator by is a comprehensive tool designed to analyze funding rates across multiple cryptocurrency exchanges. This indicator is essential for traders who want to monitor funding rates and their impact on market trends.
Key Features
Exchange Coverage: Includes data from major exchanges such as Binance, Bitmex, Bybit, HTX, Kraken, OKX, Bitstamp, and Coinbase.
Perpetual Futures and Spot Markets: Fetches and analyzes pricing data from both perpetual futures and spot markets to provide a holistic view.
Smoothing and Customization: Allows users to smooth funding rates using a moving average, with customizable MA lengths for tailored analysis.
Dynamic Candle Coloring: Option to color candles based on trading conditions, enhancing visual analysis.
In the example below, the indicator shows how the funding rate shifts with market conditions, providing clear visual cues for bullish and bearish trends.
How it Works
Data Integration: Uses a secure security fetching function to retrieve pricing data while preventing look-ahead bias, ensuring accurate and reliable information.
TWAP Calculation: Computes Time-Weighted Average Prices (TWAP) for both perpetual futures and spot prices, forming the basis for funding rate calculations.
Funding Rate Calculation: Determines the raw funding rate by comparing TWAPs of perpetual futures and spot prices, then applies smoothing to highlight significant trends.
Color Coding: Highlights the funding rate with distinct colors (bullish and bearish), making it easier to interpret market conditions at a glance.
In the example below, the indicator effectively differentiates between bullish and bearish funding rates, aiding traders in making informed decisions based on current market dynamics.
Application
Market Analysis: Enables traders to analyze the impact of funding rates on market trends, facilitating more strategic decision-making.
Trend Identification: Assists in identifying potential market reversals by monitoring shifts in funding rates.
Customizable Settings: Provides extensive input settings for exchange selection, MA length, and candle coloring, allowing for personalized analysis.
The Funding Rate Indicator by is a powerful addition to any trader's toolkit, offering detailed insights into funding rates across multiple exchanges to navigate the cryptocurrency market effectively.
CME Gap Oscillator [CryptoSea]Introducing the CME Gap Oscillator , a pioneering tool designed to illuminate the significance of market gaps through the lens of the Chicago Mercantile Exchange (CME). By leveraging gap sizes in relation to the Average True Range (ATR), this indicator offers a unique perspective on market dynamics, particularly around the critical weekly close periods.
Key Features
Gap Measurement : At its core, the CME Oscillator quantifies the size of weekend gaps in the context of the market's volatility, using the ATR to standardize this measurement.
Dynamic Levels : Incorporating a dynamic extreme level calculation, the tool adapts to current market conditions, providing real-time insights into significant gap sizes and their implications.
Band Analysis : Through the introduction of upper and lower bands, based on standard deviations, traders can visually assess the oscillator's position relative to typical market ranges.
Enhanced Insights : A built-in table tracks the frequency of the oscillator's breaches beyond these bands within the latest CME week, offering a snapshot of recent market extremities.
Settings & Customisation
ATR-Based Measurement : Choose to measure gap sizes directly or in terms of ATR for a volatility-adjusted view.
Band Period Adjustability : Tailor the oscillator's sensitivity by modifying the band calculation period.
Dynamic Level Multipliers : Adjust the multiplier for dynamic levels to suit your analysis needs.
Visual Preferences : Customise the oscillator, bands, and table visuals, including color schemes and line styles.
In the example below, it demonstrates that the CME will want to return to the 0 value, this would be considered a reset or gap fill.
Application & Strategy
Deploy the CME Oscillator to enhance your market analysis
Market Sentiment : Gauge weekend market sentiment shifts through gap analysis, refining your strategy for the week ahead.
Volatility Insights : Use the oscillator's ATR-based measurements to understand the volatility context of gaps, aiding in risk management.
Trend Identification : Identify potential trend continuations or reversals based on the frequency and magnitude of gaps exceeding dynamic levels.
The CME Oscillator stands out as a strategic tool for traders focusing on gap analysis and volatility assessment. By offering a detailed breakdown of market gaps in relation to volatility, it empowers users with actionable insights, enabling more informed trading decisions across a range of markets and timeframes.
