BTC-USDT Liquidity Trend [Ajit Pandit]his script helps traders visualize trend direction and identify liquidity zones where price might react due to past pivot levels. The color-coded candles and extended pivot lines make it easier to spot support/resistance levels and potential breakout points.
Key Features:
1. Trend Detection Using EMA
Uses two EMA calculations to determine the trend:
emaValue: Standard EMA based on length1
correction: Adjusted price movement relative to EMA
Trend: Another EMA of the corrected value
Determines bullish (signalUp) and bearish (signalDn) signals when Trend crosses emaValue.
2. Candlestick Coloring Based on Trend
Candlesticks are colored:
Uptrend → Blue (up color)
Downtrend → Pink (dn color)
Neutral → No color
3. Liquidity Zones (Pivot Highs & Lows)
Identifies pivot highs and lows using a customizable pivot length.
Draws liquidity lines:
High pivot lines (Blue, adjustable width)
Low pivot lines (Pink, adjustable width)
Extends lines indefinitely until price breaks above/below the level.
Removes broken pivot levels dynamically.
Cerca negli script per "usdt"
BTC Spot vs Perpetual CVD DivergenceThis indicator:
Data Sources:
Uses Binance BTC/USDT for spot market
Uses Binance BTC/USD perpetual (USD-M) for futures market
Both symbols should be available on TradingView
CVD Approximation:
Since true CVD requires order book data (not fully available in Pine Script), we approximate it by:
Multiplying volume by price direction (+1 for up bars, -1 for down bars)
Summing over the specified lookback period
Normalization:
Normalizes both CVD values to a -1 to 1 range for fair comparison
This accounts for different volume scales between spot and perpetual markets
Divergence Calculation:
Subtracts normalized perpetual CVD from spot CVD
Positive values indicate spot market is more bullish than perpetual
Negative values indicate perpetual market is more bullish than spot
Visualization:
Red line: Main divergence indicator
Green line: Normalized spot CVD
Blue line: Normalized perpetual CVD
Green background: Strong positive divergence (>0.5)
Red background: Strong negative divergence (<-0.5)
Gray dashed line at zero
Limitations:
This is an approximation since true CVD requires buy/sell volume separation, which isn't directly available
Results may vary depending on timeframe and lookback period
Assumes volume data reliability from both markets
Boilerplate Configurable Strategy [Yosiet]This is a Boilerplate Code!
Hello! First of all, let me introduce myself a little bit. I don't come from the world of finance, but from the world of information and communication technologies (ICT) where we specialize in data processing with the aim of automating it and eliminating all human factors and actors in the processes. You could say that I am an algotrader.
That said, in my journey through trading in recent years I have understood that this world is often shown to be incomplete. All those who want to learn about trading only end up learning a small part of what it really entails, they only seek to learn how to read candlesticks. Therefore, I want to share with the entire community a fraction of what I have really understood it to be.
As a computer scientist, the most important thing is the data, it is the raw material of our work and without data you simply cannot do anything. Entropy is simple: Data in -> Data is transformed -> Data out.
The quality of the outgoing data will directly depend on the incoming data, there is no greater mystery or magic in the process. In trading it is no different, because at the end of the day it is nothing more than data. As we often say, if garbage comes in, garbage comes out.
Most people focus on the results only, on the outgoing data, because in the end we all want the same thing, to make easy money. Very few pay attention to the input data, much less to the process.
Now, I am not here to delude you, because there is no bigger lie than easy money, but I am here to give you a boilerplate code that will help you create strategies where you only have to concentrate on the quality of the incoming data.
To the Point
The code is a strategy boilerplate that applies the technique that you decide to customize for the criteria for opening a position. It already has the other factors involved in trading programmed and automated.
1. The Entry
This section of the boilerplate is the one that each individual must customize according to their needs and knowledge. The code is offered with two simple, well-known strategies to exemplify how the code can be reused for your own benefits.
For the purposes of this post on tradingview, I am going to use the simplest of the known strategies in trading for entries: SMA Crossing
// SMA Cross Settings
maFast = ta.sma(close, length)
maSlow = ta.sma(open, length)
The Strategy Properties for all cases published here:
For Stock TSLA H1 From 01/01/2025 To 02/15/2025
For Crypto XMR-USDT 30m From 01/01/2025 To 02/15/2025
For Forex EUR-USD 5m From 01/01/2025 To 02/15/2025
But the goal of this post is not to sell you a dream, else to show you that the same Entry decision works very well for some and does not for others and with this boilerplate code you only have to think of entries, not exits.
2. Schedules, Days, Sessions
As you know, there are an infinite number of markets that are susceptible to the sessions of each country and the news that they announce during those sessions, so the code already offers parameters so that you can condition the days and hours of operation, filter the best time parameters for a specific market and time frame.
3. Data Filtering
The data offered in trading are numerical series presented in vectors on a time axis where an endless number of mathematical equations can be applied to process them, with matrix calculation and non-linear regressions being the best, in my humble opinion.
4. Read Fundamental Macroeconomic Events, News
The boilerplate has integration with the tradingview SDK to detect when news will occur and offers parameters so that you can enable an exclusion time margin to not operate anything during that time window.
5. Direction and Sense
In my experience I have found the peculiarity that the same algorithm works very well for a market in a time frame, but for the same market in another time frame it is only a waste of time and money. So now you can easily decide if you only want to open LONG, SHORT or both side positions and know how effective your strategy really is.
6. Reading the money, THE PURPOSE OF EVERYTHING
The most important section in trading and the reason why many clients usually hire me as a financial programmer, is reading and controlling the money, because in the end everyone wants to win and no one wants to lose. Now they can easily parameterize how the money should flow and this is the genius of this boilerplate, because it is what will really decide if an algorithm (Indicator: A bunch of math equations) for entries will really leave you good money over time.
7. Managing the Risk, The Ego Destroyer
Many trades, little money. Most traders focus on making money and none of them know about statistics and the few who do know something about it, only focus on the winrate. Well, with this code you can unlock what really matters, the true success criteria to be able to live off of trading: Profit Factor, Sortino Ratio, Sharpe Ratio and most importantly, will you really make money?
8. Managing Emotions
Finally, the main reason why many lose money is because they are very bad at managing their emotions, because with this they will no longer need to do so because the boilerplate has already programmed criteria to chase the price in a position, cut losses and maximize profits.
In short, this is a boilerplate code that already has the data processing and data output ready, you only have to worry about the data input.
“And so the trader learned: the greatest edge was not in predicting the storm, but in building a boat that could not sink.”
DISCLAIMER
This post is intended for programmers and quantitative traders who already have a certain level of knowledge and experience. It is not intended to be financial advice or to sell you any money-making script, if you use it, you do so at your own risk.
Aggregation BTC CVDThe script calculates the Cumulative Volume Delta (CVD) for multiple cryptocurrency exchanges, then averages these values and plots them.
Indicator Setup:
The script sets up an indicator called "BTC Cumulative Volume Delta (CVD) for multiple cryptocurrency exchanges", displayed as a separate panel (not overlaid on the price chart) with volume format.
Getting 1-minute data from multiple exchanges:
It retrieves 1-minute data (buy and sell volumes) for Bitcoin (BTC) against USD or USDT from several exchanges: Binance, OKEx, Coinbase (both BTCUSDT and BTCUSD), Bitfinex, Bybit, Huobi, and Kraken.
Calculating total buying and selling volume for each exchange:
For each exchange, it calculates the total buying volume (buy_vol_...), selling volume (sell_vol_...), and the difference between them (delta_vol_...).
It then computes the cumulative delta volume (cum_delta_vol_...), which is a running total of delta_vol_....
Calculating the average CVD:
It calculates the average cumulative delta volume (average_cum_delta_vol) by summing the cumulative delta volumes from all exchanges and dividing by the number of exchanges.
Plotting the average CVD:
Finally, it plots the average CVD with white color, and a line width of 2.
This script essentially provides an averaged Cumulative Volume Delta across multiple exchanges, giving a comprehensive view of buying and selling pressure in the Bitcoin market across these platforms.
Price in BTC (x1000)I'm not a coder. I just knocked this together with AI
Shows how the current asset performed relative to BTC (COINBASE:BTCUSD) on the current timeframe
Works with assets priced in USD, USDT and USDC but you can easily add more
Had to multiply the price by 1000 to mitigate leading zeros and improve compatibility with low-denomination assets (e.g. PEPE)
MAs and crossovers included
Feel free to use it however you want
RSI Bands with Volume and EMAThis script is a comprehensive technical analysis tool designed to help traders identify key market signals using RSI bands, volume, and multiple Exponential Moving Averages (EMAs). It overlays the following on the chart:
RSI Bands: The script calculates and plots two bands based on the Relative Strength Index (RSI), indicating overbought and oversold levels. These bands act as dynamic support and resistance zones:
Resistance Band (Upper Band): Plotted when the RSI exceeds the overbought level, typically indicating a potential sell signal.
Support Band (Lower Band): Plotted when the RSI falls below the oversold level, typically indicating a potential buy signal.
Midline: The average of the upper and lower bands, acting as a neutral reference.
Buy/Sell Labels: Labels are dynamically added to the chart when price reaches the overbought or oversold levels.
A "Buy" label appears when the price reaches the oversold (lower) band.
A "Sell" label appears when the price reaches the overbought (upper) band.
Volume Indicator: The script visualizes trading volume as histograms, with red or green bars representing decreasing or increasing volume, respectively. The volume height is visually reduced for better clarity and comparison.
Exponential Moving Averages (EMAs): The script calculates and plots four key EMAs (12, 26, 50, and 200) to highlight short-term, medium-term, and long-term trends:
EMA 12: Blue
EMA 26: Orange
EMA 50: Purple
EMA 200: Green
The combined use of RSI, volume, and EMAs offers traders a multi-faceted view of the market, assisting in making informed decisions about potential price reversals, trends, and volume analysis. The script is particularly useful for identifying entry and exit points on charts like BTC/USDT, although it can be applied to any asset.
P/L CalculatorDescription of the P/L Calculator Indicator
The P/L Calculator is a dynamic TradingView indicator designed to provide traders with real-time insights into profit and loss metrics for their trades. It visualizes key levels such as entry price, profit target, and stop-loss, while also calculating percentage differences and net profit or loss, factoring in fees.
Features:
Customizable Input Parameters:
Entry Price: Define the starting price of the trade.
Profit and Stop-Loss Levels (%): Set percentage thresholds for targets and risk levels.
USDT Amount: Specify the trade size for precise calculations.
Trade Type: Choose between "Long" or "Short" positions.
Visual Representation:
Entry Price, Profit Target, and Stop-Loss levels are plotted as horizontal lines on the chart.
Line styles, colors, and thicknesses are fully customizable for better visibility.
Real-Time Metrics:
Percentage difference between the live price and the entry price is calculated dynamically.
Profit/Loss (P/L) and fees are computed in real time to display net profit or loss.
Alerts:
Alerts are triggered when:
The live price hits the profit target.
The live price crosses the stop-loss level.
The price reaches the specified entry level.
A user-defined percentage difference is reached.
Labels and Annotations:
Displays percentage difference, P/L, and fee information in a clear label near the live price.
Custom Fee Integration:
Allows input of trading fees (%), enabling accurate net profit or loss calculations.
Price Scale Visualization:
Displays the percentage difference on the price scale for enhanced context.
Use Case:
The P/L Calculator is ideal for traders who want to monitor their trades' performance and make informed decisions without manually calculating metrics. Its visual cues and alerts ensure you stay updated on critical levels and price movements.
This indicator supports a wide range of trading styles, including swing trading, scalping, and position trading, making it a versatile tool for anyone in the market.
Crypto/Stable Mcap Ratio NormalizedCreate a normalized ratio of total crypto market cap to stablecoin supply (USDT + USDC + DAI). Idea is to create a reference point for the total market cap's position, relative to total "dollars" in the crypto ecosystem. It's an imperfect metric, but potentially helpful. V0.1.
This script provides four different normalization methods:
Z-Score Normalization:
Shows how many standard deviations the ratio is from its mean
Good for identifying extreme values
Mean-reverting properties
Min-Max Normalization:
Scales values between 0 and 1
Good for relative position within recent range
More sensitive to recent changes
Percent of All-Time Range:
Shows where current ratio is relative to all-time highs/lows
Good for historical context
Less sensitive to recent changes
Bollinger Band Position:
Similar to z-score but with adjustable sensitivity
Good for trading signals
Can be tuned via standard deviation multiplier
Features:
Adjustable lookback period
Reference bands for overbought/oversold levels
Built-in alerts for extreme values
Color-coded plots for easy visualization
BTC/USDT Volume-Based StrategyOverview
There is a distinct difference between the buying pressure exerted by individual investors and the buying pressure of institutional or "whale" traders. Monitoring volume data over a shorter period of time is crucial to distinguish these subtle differences. When whale investors or other significant market players signal price increases, volume often surges noticeably. Indeed, volume often acts as an important leading indicator in market dynamics.
Key Features
This metric, calibrated with a 5-minute Bitcoin spot chart, identifies a significant inflow of trading volume. For every K-plus surge in trading volume, those candles are shown in a green circle.
When a green circle appears, consider active long positions in subsequent declines and continue to accumulate long positions despite temporary price declines. Pay attention to the continuity of the increase in volume before locking in earnings even after the initial bullish wave.
Conversely, it may be wise to reevaluate the long position if the volume is not increasing in parallel and the price is rising. Under these conditions, starting a partial short position may be advantageous until a larger surge in volume reappears.
Coinbase Premium Index (Any Symbol)The Coinbase Premium Index provides a valuable insight into market dynamics by calculating the price premium between Coinbase (USD pairs) and Binance (USDT pairs). A positive premium typically indicates heavy buying pressure on Coinbase, often coinciding with upward price trends on lower timeframes. Conversely, a negative premium suggests selling pressure or weaker demand on Coinbase compared to Binance.
** Key Features: **
**Dynamic Symbol Detection**: Automatically detects the current chart symbol and adapts the premium calculation accordingly.
**Customizable Moving Averages**:
Select between SMA (Simple Moving Average) or EMA (Exponential Moving Average).
Adjust the moving average period to suit your trading strategy (default: SMA with 50 periods).
**Error Handling for Missing Data**:
Displays "Symbol not on Coinbase" when the cryptocurrency is unavailable on Coinbase.
Plots zero-value columns in light grey for unsupported symbols.
**Visual Representation**:
Premium values are displayed as columns: green for positive premiums, red for negative premiums.
A moving average line in light grey helps highlight trends.
Zero Line: A horizontal dashed line is included as a reference point.
** Why Use This Script?**
The Coinbase Premium Index helps traders identify moments of increased buying pressure among U.S. investors, often indicative of bullish momentum on lower timeframes. Use this tool to monitor premium dynamics and gain a clearer understanding of market sentiment across major exchanges.
** How to Use: **
Add this script to your TradingView chart.
Adjust the moving average type and period through the input menu.
Use the premium columns and moving averages to identify potential price trends and validate exchange-specific trading opportunities.
True Total Altcoin Market CapThis indicator calculates the real total altcoin market capitalization by removing Bitcoin, Ethereum, and major stablecoins (USDT, USDC, BUSD, DAI) from the total cryptocurrency market cap. It replaces the standard price bars with custom-colored candlesticks showing the true altcoin market movements.
Features:
Excludes BTC, ETH, and major stablecoins for accurate altcoin market analysis
Custom color scheme: Green (#26a79b) for bullish and Red (#ef5351) for bearish candles
Based on CRYPTOCAP:TOTAL data
Helps traders focus on pure altcoin market trends
Non-repainting, using standard OHLC data
This tool provides a clearer view of altcoin market strength by filtering out the influence of major cryptocurrencies and stablecoins.
Stablecoin Dominance Oscillator
The SDO is a normalized oscillator that tracks the relationship between stablecoin market capitalization (USDT + USDC + DAI) and total crypto market capitalization. It helps identify periods where stablecoins represent an unusually high or low portion of the total crypto market value.
Key components:
Main Signal (Blue Line):
Shows the normalized deviation of stablecoin dominance from its trend. Higher values indicate higher stablecoin dominance relative to history (which often corresponds with market bottoms/fear), while lower values indicate lower stablecoin dominance (often seen during strong bull markets/greed).
Dynamic Bands (Gray):
These adapt to market volatility, expanding during volatile periods and contracting during stable periods
Generally suggest temporary boundaries for the oscillator
Volatility Reference (Purple Line):
Shows the ratio between short-term and long-term volatility
Higher values indicate more volatile market conditions
Helps contextualize the reliability of the current signal
The indicator uses a 500-period lookback for baseline calculations and a 15-period Hull Moving Average for smoothing, making it responsive while filtering out noise. The final signal is normalized and volatility-adjusted to maintain consistent readings across different market regimes.
XRP Comparative Price Action Indicator - Final VersionXRP Comparative Price Action Indicator - Final Version
The XRP Comparative Price Action Indicator provides a comprehensive visual analysis of XRP’s price movements relative to key cryptocurrencies and market indices. This indicator normalises price data across various assets, allowing traders and investors to assess XRP’s performance against its peers and major market influences at a glance.
Key Features:
• Normalised Price Data: Prices are scaled between 0.00 and 1.00,
enabling straightforward comparisons between different assets.
• Key Comparisons: Includes normalised prices for:
• XRP/USD (Bitstamp)
• XRP Dominance (CryptoCap)
• XRP/BTC (Bitstamp)
• BTC/USD (Bitstamp)
• BTC Dominance (CryptoCap)
• USDT Dominance (CryptoCap)
• S&P 500 (SPY)
• DXY (Dollar Index)
• ETH/USD (Bitstamp)
• ETH Dominance (CryptoCap)
• XRP/ETH (Binance)
• Visual Clarity: Each asset is plotted with distinct colors for easy identification,
with thicker lines enhancing visibility on the chart.
• Reference Lines: Optional horizontal lines indicate the minimum (0) and maximum (1) normalised values, providing clear reference points for analysis.
This indicator is ideal for traders looking to understand XRP’s relative performance, gauge market sentiment, and make informed trading decisions based on comparative price action.
Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
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.
Crypto Liquidation Heatmap [LuxAlgo]The Crypto Liquidation Heatmap tool offers real-time insights into the liquidations of the top cryptocurrencies by market capitalization, presenting the current state of the market in a visually accessible format. Assets are sorted in descending order, with those experiencing the highest liquidation values placed at the top of the heatmap.
Additional details, such as the breakdown of long and short liquidation values and the current price of each asset, can be accessed by hovering over individual boxes.
🔶 USAGE
The crypto liquidation heatmap tool provides real-time insights into liquidations across all timeframes for the top 29 cryptocurrencies by market capitalization. The assets are visually represented in descending order, prioritizing assets with the highest liquidation values at the top of the heatmap.
Different colors are used to indicate whether long or short liquidations are dominant for each asset. Green boxes indicate that long liquidations surpass short liquidations, while red boxes indicate the opposite, with short liquidations exceeding long liquidations.
Hovering over each box provides additional details, such as the current price of the asset, the breakdown of long and short liquidation values, and the duration for the calculated liquidation values.
🔶 DETAILS
🔹Crypto Liquidation
Crypto liquidation refers to the process of forcibly closing a trader's positions in the cryptocurrency market. It occurs when a trader's margin account can no longer support their open positions due to significant losses or a lack of sufficient margin to meet the maintenance requirements. Liquidations can be categorized as either a long liquidation or a short liquidation.
A long liquidation occurs when long positions are being liquidated, typically due to a sudden drop in the price of the asset being traded. Traders who were bullish on the asset and had opened long positions will face losses as the market moves against them.
On the other hand, a short liquidation occurs when short positions are being liquidated, often triggered by a sudden spike in the price of the asset. Traders who were bearish on the asset and had opened short positions will face losses as the market moves against them.
🔹Liquidation Data
It's worth noting that liquidation data is not readily available on TradingView. However, we recognize the close correlation between liquidation data, trading volumes, and asset price movements. Therefore, this script analyzes accessible data sources, extracts necessary information, and offers an educated estimation of liquidation data. It's important to emphasize that the presented data doesn't reflect precise quantitative values of liquidations. Traders and analysts should instead focus on observing changes over time and identifying correlations between liquidation data and price movements.
🔶 SETTINGS
🔹Cryptocurrency Asset List
It is highly recommended to select instruments from the same exchange with the same currency to maintain proportional integrity among the chosen assets, as different exchanges may have varying trading volumes.
Supported currencies include USD, USDT, USDC, USDP, and USDD. Remember to use the same currency when selecting assets.
List of Crypto Assets: The default options feature the top 29 cryptocurrencies by market capitalization, currently listed on the Binance Exchange. Please note that only crypto assets are supported; any other asset type will not be processed or displayed. To maximize the utility of this tool, it is crucial to heed the warning message displayed above.
🔹Liquidation Heatmap Settings
Position: Specifies the placement of the liquidation heatmap on the chart.
Size: Determines the size of the liquidation heatmap displayed on the chart.
🔶 RELATED SCRIPTS
Liquidations-Meter
Liquidation-Estimates
Liquidation-Levels
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Emibap's HEX Uniswap v3 Liquidity PoolThis script will display a histogram of the Uniswap V3 HEX liquidity pool, versus as many tokens as possible.
Current supported pairs:
HEX/USDC
HEX/WETH
HEX/WETH.USD (Ethereum expressed in USD)
HEX/USDT (Just showing the USDC liquidity)
Similar to what you can see in the liquidity section of the Uniswap pool page but conveniently rendered alongside your chart.
It's meant to be used on a HEX / WETH chart only. The price should be expressed in WETH for it to work.
One of the main motivations for using this in your chart is to get an idea of the current sentiment: If most of the volume is above the price it might be an indication of an upcoming move up, for instance.
I'll try to update the liquidity regularly.
Using the 4h, daily, or weekly time frames is highly recommended.
The options are straightforward:
Histogram bars color. Default is blue
Histogram background color. Default is black at 20% opacity
Upper price limit of the diagram: Visible upper bound price limit for the histogram, based on the current price. I.E: 200%: If the price is 1, the histogram will show 3 as the upper bound
Lower price limit of the diagram. Visible lower bound price limit for the histogram, based on the current price. I.E: 99%: If the price is 1, the histogram will show 0. 01 as the upper bound
Width of the widest bar: Width (in bars) for the widest bar of the histogram. The more the higher resolution you'll get
Locked volume marker line thickness
Locked volume marker color
RSI over screener (any tickers)█ OVERVIEW
This screener allow you to watch up to 240 any tickers you need to check RSI overbought and oversold using multiple periods, including the percentage of RSIs of different periods being overbought/oversold, as well as the average between these multiple RSIs.
█ THANKS
LuxAlgo for his RSI over multi length
I made function for this RSI and screener based on it.
allanster for his amazing idea how to split multiple symbols at once using a CSV list of ticker IDs
█ HOW TO USE
- hide chart:
- add 6 copies of screener
- change list number at settings from 1 to 6
- add you tickers
Screener shows signals when RSI was overbought or oversold and become to 0, this signal you may use to enter position(check other market condition before enter).
At settings you cam change Prefics, Appendix and put you tickers.
limitations are:
- max 40 tickers for one list
- max 4096 characters for one list
- tickers list should be separated by comma and may contains one space after the comma
By default it shows almost all BINANCE USD-M USDT tickers
Also you can adjust table for your screen by changing width of columns at settings.
If you have any questions or suggestions write comment or message.
Cryptocurrency Altcoin Screener
This indicator works as a screener for bullish/bearish moves. There are two versions showing two different sets of Altcoins, just choose version 1 or 2. Load up any chart and it will show all selected pairs and their current state regardless of asset or timeframe. Assets can be shown/unshown and longs/shorts can be shown/unshown.
It shows (asset) +1 if it considers it bullish
(asset) -1 if it considers it bearish
(asset) 0 if considers the asset to be neutral/choppy
You can see how effective the indicator is by loading up the asset you're looking at, this will show the true history of the markers for that asset.
This script utilises MACD and RSI on the daily timeframe on both USDT and BTC pairs in order to identify a trend.
The main purpose of the script is to easily identify strong trends that allow you to do TA with rather than manually looking at every asset
3 Important Value CompositesCalculated on February 17, 2024. USDT 378 items, BTC 282 items, BINANCE
This is a watchlist, along with the most accurate computed values that I could achieve. It may be beneficial for those who want to change values from the "120x ticker screener (composite tickers)" indicator, which is one of the excellent indicators to bypass the limitation of the request. security() function that limits to only 40 requests. I've thought about this before but couldn't succeed, but someone finally did it. :)
--> 120x ticker screener (composite tickers)
Thank you once again for this idea.
You must look for this and change it.
t1 = 'symbol', n1 = Multiply , r1 = Pricescale(decimal)
Example of grouping: Group 1
BINANCE:ETHUSDT , BINANCE:FDUSDUSDT , BINANCE:BTCUSDT
2, 4, 2
13, 10
█ Note
• Tickers: For your watchlist, arrange them from left to right, pairing them in groups of 3.
• Pricescale: This represents the decimal length, arrange them from left to right, pairing them in groups of 3.
• Multiply: This involves multiplying the first 2 items in each pair of watchlists. Arrange them from left to right, pairing them in groups of 2.
* If you group items incorrectly, it may lead to inaccurate results.
* Please be advised that if one of the values in the "Pricescale"(decimal) trio changes, there may be a need to adjust those values accordingly to ensure correct digit separation. Otherwise, within the group, the numbers might appear peculiar.
Crypto USD LiquidityThe "Crypto USD Liquidity " indicator is designed to offer a comprehensive analysis of liquidity dynamics within the cryptocurrency market, specifically focusing on various stablecoins. This versatile tool allows users to tailor their analysis by adjusting key parameters such as the Rate of Change (ROC) length and the smoothing rate.
The indicator incorporates a user-friendly interface with options to selectively display the supply data for major stablecoins, including USDT, BUSD, USDC, DAI, and TUSD . Users can toggle these options to observe and compare the liquidity trends of different stablecoin assets.
The total liquidity is computed as the summation of the selected stablecoin supplies, providing a holistic view of the overall crypto market liquidity. The Rate of Change (ROC) and its smoothing are then applied to the aggregated liquidity data. This process helps users identify trends and potential turning points in the liquidity landscape.
The visual representation on the chart includes a color-coded display: positive changing ROC values are shaded in green, indicating potential increases in liquidity, while negative values are shaded in red, suggesting potential decreases. This color scheme enhances the user's ability to quickly interpret the changing dynamics of stablecoin liquidity.
Moreover, the script includes a Zero Line for reference and overlays the raw ROC values for additional insight. The resulting chart not only serves as a powerful analytical tool for traders and investors but also contributes to a deeper understanding of the nuanced movements within the broader cryptocurrency market.
In summary, the "Crypto USD Liquidity" Pine Script indicator empowers users with a customizable and visually informative tool for analyzing and interpreting the complex dynamics of stablecoin liquidity, facilitating more informed decision-making in the realm of cryptocurrency trading and investment.
Machine Learning: STDEV Oscillator [YinYangAlgorithms]This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from its standard movement. This Indicator may help display both when the price is Overbought or Underbought, and likewise, where the price may face Support and Resistance. The reason for this is that rather than simply plotting a Machine Learning Standard Deviation (STDEV), we instead create a High and a Low variant of STDEV, and then use its Highest and Lowest values calculated within another Deviation to create Deviation Zones. These zones may help to display these Support and Resistance locations; and likewise may help to show if the price is Overbought or Oversold based on its placement within these zones. This Oscillator may also help display Momentum when the High and/or Low STDEV crosses the midline (0). Lastly, this Oscillator may also be useful for seeing the spacing between the High and Low of the STDEV; large spacing may represent volatility within the STDEV which may be helpful for seeing when there is Momentum in the form of volatility.
Tutorial:
Above is an example of how this Indicator looks on BTC/USDT 1 Day. As you may see, when the price has parabolic movement, so does the STDEV. This is due to this price movement deviating from the mean of the data. Therefore when these parabolic movements occur, we create the Deviation Zones accordingly, in hopes that it may help to project future Support and Resistance locations as well as helping to display when the price is Overbought and Oversold.
If we zoom in a little bit, you may notice that the Support Zone (Blue) is smaller than the Resistance Zone (Orange). This is simply because during the last Bull Market there was more parabolic price deviation than there was during the Bear Market. You may see this if you refer to their values; the Resistance Zone goes to ~18k whereas the Support Zone is ~10.5k. This is completely normal and the way it is supposed to work. Due to the nature of how STDEV works, this Oscillator doesn’t use a 1:1 ratio and instead can develop and expand as exponential price action occurs.
The Neutral (0) line may also act as a Support and Resistance location. In the example above we can see how when the STDEV is below it, it acts as Resistance; and when it’s above it, it acts as Support.
This Neutral line may also provide us with insight as towards the momentum within the market and when it has shifted. When the STDEV is below the Neutral line, the market may be considered Bearish. When the STDEV is above the Neutral line, the market may be considered Bullish.
The Red Line represents the STDEV’s High and the Green Line represents the STDEV’s Low. When the STDEV’s High and Low get tight and close together, this may represent there is currently Low Volatility in the market. Low Volatility may cause consolidation to occur, however it also leaves room for expansion.
However, when the STDEV’s High and Low are quite spaced apart, this may represent High levels of Volatility in the market. This may mean the market is more prone to parabolic movements and expansion.
We will conclude our Tutorial here. Hopefully this has given you some insight into how applying Machine Learning to a High and Low STDEV then creating Deviation Zones based on it may help project when the Momentum of the Market is Bullish or Bearish; likewise when the price is Overbought or Oversold; and lastly where the price may face Support and Resistance in the form of STDEV.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
