Vegas SuperTrend Enhanced - Strategy [presentTrading]█ Introduction and How it is Different
The "Vegas SuperTrend Enhanced - Strategy " trading strategy represents a novel integration of two powerful technical analysis tools: the Vegas Channel and the SuperTrend indicator. This fusion creates a dynamic, adaptable strategy designed for the volatile and fast-paced cryptocurrency markets, particularly focusing on Bitcoin trading.
Unlike traditional trading strategies that rely on a static set of rules, this approach modifies the SuperTrend's sensitivity to market volatility, offering traders the ability to customize their strategy based on current market conditions. This adaptability makes it uniquely suited to navigating the often unpredictable swings in cryptocurrency valuations, providing traders with signals that are both timely and reflective of underlying market dynamics.
BTC 6h LS
█ Strategy, How it Works: Detailed Explanation
This is an innovative approach that combines the volatility-based Vegas Channel with the trend-following SuperTrend indicator to create dynamic trading signals. This section delves deeper into the mechanics and mathematical foundations of the strategy.
Detail picture to show :
🔶 Vegas Channel Calculation
The Vegas Channel serves as the foundation of this strategy, employing a simple moving average (SMA) coupled with standard deviation to define the upper and lower bounds of the trading channel. This channel adapts to price movements, offering a visual representation of potential support and resistance levels based on historical price volatility.
🔶 SuperTrend Indicator Adjustment
Central to the strategy is the SuperTrend indicator, which is adjusted according to the width of the Vegas Channel. This adjustment is achieved by modifying the SuperTrend's multiplier based on the channel's volatility, allowing the indicator to become more sensitive during periods of high volatility and less so during quieter market phases.
🔶 Trend Determination and Signal Generation
The market trend is determined by comparing the current price with the SuperTrend values. A shift from below to above the SuperTrend line signals a potential bullish trend, prompting a "buy" signal, whereas a move from above to below indicates a bearish trend, generating a "sell" signal. This methodology ensures that trades are entered in alignment with the prevailing market direction, enhancing the potential for profitability.
BTC 6h Local
█ Trade Direction
A distinctive feature of this strategy is its configurable trade direction input, allowing traders to specify whether they wish to engage in long positions, short positions, or both. This flexibility enables users to tailor the strategy according to their risk tolerance, trading style, and market outlook, providing a personalized trading experience.
█ Usage
To utilize the "Vegas SuperTrend - Enhanced" strategy effectively, traders should first adjust the input settings to align with their trading preferences and the specific characteristics of the asset being traded. Monitoring the strategy's signals within the context of overall market conditions and combining its insights with other forms of analysis can further enhance its effectiveness.
█ Default Settings
- Trade Direction: Both (allows trading in both directions)
- ATR Period for SuperTrend: 10 (determines the length of the ATR for volatility measurement)
- Vegas Window Length: 100 (sets the length of the SMA for the Vegas Channel)
- SuperTrend Multiplier Base: 5 (base multiplier for SuperTrend calculation)
- Volatility Adjustment Factor: 5.0 (adjusts SuperTrend sensitivity based on Vegas Channel width)
These default settings provide a balanced approach suitable for various market conditions but can be adjusted to meet individual trading needs and objectives.
Cerca negli script per "crypto"
Trend Regression Kernel [IkkeOmar]Kernel by @jdehorty huge shoutout to him! This is only an idea for how I use it when trading
All credit for the kernel goes to him, I did not make the kernel! I don't know how to make it more clear.
I use this to assist with top-down analysis.
timeframe I want to trade : timeframe to analyse with white noise and kernel:
1m : 1H
5m : 2H
15m : 4H
1H : 1D
In the chart you see that I have the 1H open, I use the white noise at a "lower setting length" (55 in this case), I change the source of to be the kernel on the higher timeframe. When a new trend is detected by the White noise I wait for price to retest the kernel before building a position. Another case described below:
Here i use the adaptive MCVF (I have made this free for everyone on TradingView) to buy when price is below the kernel while the trend for the white noise is bullish .
Notice that the Kernel is set on the 4H timeframe! The source of the white noise is the kernel!
Here is an example in a bearish trend:
Notice, I am on the 5m chart, kernel uses the 2H chart and the source of the white noise is the kernel.
I use the adaptive MCVF to help me get entries AFTER the first touch of the kernel.
Mandatory code explanation, with respect to the house rules:
Input settings:
Input Settings:
The script provides various input parameters to customize the indicator:
src: The source of price data, defaulted to closing prices.
h, r, x_0: Parameters for Kernel 1.
h2, r2, x_2: Parameters for Kernel 2.
Kernel Regression Functions:
Two functions kernel_regression1 and kernel_regression2 are defined to perform kernel regression calculations.
These functions estimate the trend using the Nadaraya-Watson kernel non-parametric regression method.
They take the source data (_src), the size of the data series (_size), and the lookback window (_h) as inputs.
They iterate over the data series and calculate the weighted sum of the values based on the specified kernel parameters.
The result is divided by the cumulative weight to obtain the estimated value.
Estimations:
The kernel_regression1 and kernel_regression2 functions are called with the respective parameters to estimate trends (yhat1 and yhat2).
Buy and Sell Signals:
Buy and sell signals are generated based on crossover and crossunder conditions between the two trend estimates (yhat1 and yhat2).
buySignal is true when yhat1 crosses above yhat2.
SellSignal is true when yhat1 crosses below yhat2.
Plotting:
The average of the two trend estimates (yhat1 and yhat2) is calculated and plotted.
The color of the plot is determined based on whether yhat1 is greater than yhat2, less than yhat2, or equal to yhat2.
Buy and sell signals are plotted using triangle shapes below and above bars, respectively.
Alerts:
Alert conditions are set based on buy and sell signals. Alerts are triggered when a crossover (long signal) or crossunder (short signal) occurs.
The alerts include information about the signal type, symbol, and price.
It's important to mention that the buy and sell signals from the indicator is very discretionary, I rarely use them, and if I do it's if they are in confluence with a correction i am biased towards or if it has confluence with some of my other systems.
The adaptive MCVF and White noise is free for everyone on TradingView, linked below:)
Huge shoutout to @jdehorty, original kernel below:
PVSRA Candles Auto OverrideWhat does this “PVSRA Candles Auto Override” Indicator
do?
This indicator automates PVSRA analysis for crypto traders. It finds the corresponding Binance Perpetual Futures chart for the current instrument, then replaces the current chart's volume profile with the perpetual futures data (if available) to ensure the PVSRA calculation uses the most relevant volume. This not only reduces human error during market scans but also automatically selects the appropriate Binance Perpetual Futures contract, saving time and improving the accuracy of PVSRA calculations.
How can a trader use this indicator?
This helps the trader to identify if there is volume data available in an equivalent Binance Perpetual Futures chart and automatically displays it, making it easier to switch coins whilst viewing the market. Why do we want to use Binance Perpetual Futures Volume? In most markets Binance volume surpasses those of other crypto exchanges so this will give us a better view on the volume spikes in the market.
What is PVSRA and how can I trade using this indicator?
PVSRA candles are a type of candlestick chart formatting. PVSRA stands for Price, Volume, Support and Resistance Analysis.
Here's a breakdown of what PVSRA candles aim to achieve:
Combine multiple factors: They take into account price movement, trading volume, and support and resistance levels to identify potential trading opportunities.
Highlight potential imbalances: By color-coding candles based on PVSRA analysis, they aim to show areas of high volume activity, potentially representing imbalances created by market makers (large institutions that influence price).
Identify areas of revisit: The theory is that these high-volume zones may be revisited by the market in the future, as there's "unrecovered liquidity" in those areas.
Usage of the Indicator:
By default the indicator will automatically use the Equivalent Binance Perpetual Chart for the Data
You can override the symbol manually if you what to view another instrument’s data.
Open Interest Auto OverrideWhat does this “Open Interest Auto Override” Indicator
do?
Open Interest data is not supplied by every exchange to TradingView, however it is available on Binance Perpetual Futures. This script helps the crypto trader to identify the equivalent Binance Perpetual Futures Chart that has Open Interest Data available and automatically displays this on the traders chart.
How can a trader use this indicator?
This helps the trader to identify if there is Open Interest Data available in Binance and automatically displays it, making it easier to switch Coins whilst viewing the market.
What is Open Interest and how can I trade using this indicator?
Open Interest (OI) is the number of open futures contracts held by traders in active positions. The higher the value the Higher the number of open positions which indicates an increase in interest by traders in the asset.
If OI is increasing an equal number of longs and short positions are being opened.
If OI Decreases both longs and shorts are exiting the market.
If OI remains unchanged, no new contracts are entering or exiting, or an equal number of positions are being opened as there are being closed.
Open Interest can help traders by giving us a hint that a breakout may occur. If Open Interest is increasing whilst price is consolidating it may indicate that a breakout is imminent. If Open Interest is decreasing whilst price is consolidating it is likely that a false move in the form of a stop hunt may be issued prior to the actual breakout.
Usage of the Indicator:
By default the indicator will automatically use the Equivalent Binance Perpetual Chart for the Data
You can override the symbol manually if you what to view another exchanges data.
Neutral State Stochastic Oscillator {DCAquant}Neutral State Stochastic Oscillator {DCAquant}
The Neutral State Stochastic Oscillator {DCAquant} is an enhanced version of the classic Stochastic Oscillator. This iteration aims to refine the detection of neutral market states — periods where the market is neither overbought nor oversold — potentially signaling a period of consolidation or equilibrium before the next significant price move.
Key Features:
Advanced Oscillator Analysis: It extends the traditional use of the Stochastic Oscillator by identifying a neutral zone, which may signal a pause in market momentum.
Customizable Sensitivity: Users can adjust parameters such as K and D periods, Smooth K, and neutral zone thresholds to tailor the indicator to their trading style.
Neutral Zone Detection: This tool is especially adept at pinpointing where the %K and %D lines converge within a specific threshold, marking a neutral state.
How it Works:
%K and %D Calculation: The indicator calculates the Stochastic %K and %D lines over user-defined periods, smoothing %K for clearer signals.
Neutral Zone Threshold: A threshold defines how close %K and %D lines should be to each other to qualify as a neutral state, offering a refined perspective on market momentum.
Visual Contrast: The indicator employs a distinct color scheme to distinguish between neutral (gray), bullish (%K>%D in aqua), and bearish (%K<%D in fuchsia) market conditions, directly on the price chart.
Visual Indicators and Interpretation:
Neutral Market Condition: A gray background indicates a neutral state where %K and %D are close, suggesting a balanced market awaiting new forces to define the trend.
Market Extremes: Aqua and fuchsia backgrounds highlight when the market is exiting the neutral zone, potentially signaling the start of an uptrend or downtrend.
Strategic Application:
Consolidation and Breakout Identification: This tool helps in identifying consolidation zones which could lead to potential breakouts or breakdowns, aiding in strategic entry and exit decisions.
Multifaceted Market Analysis: By revealing neutral market states, it serves as a vital component in a comprehensive trading strategy, augmenting the insights provided by other technical indicators.
Customization and Usage:
Flexible for Various Markets: The Neutral State Stochastic Oscillator {DCAquant} is adaptable for a variety of markets, whether you're trading cryptocurrencies, stocks, forex, or commodities.
Confirmatory Tool: It acts as an excellent confirmatory tool when used with price action analysis, other oscillators, or trend indicators, ensuring a well-rounded analytical approach.
Disclaimer and User Guidance:
The Neutral State Stochastic Oscillator {DCAquant} is a sophisticated trading tool designed for informative purposes. Traders are advised to use it in conjunction with a robust risk management strategy and not as a standalone decision-making tool. As with all trading indicators, success cannot be guaranteed, and it is recommended that traders perform their due diligence before executing trades based on signals from this or any other analytical tool.
ATH Distance HeatmapThe "ATH Distance Heatmap" is a powerful visualization tool designed for traders and investors who seek to quickly assess the relative performance of assets against their All-Time Highs (ATH). By mapping the percentage distance of current prices from their historical peaks, this script provides a unique perspective on market sentiment, potential recovery opportunities, and overvaluation risks.
Key Features:
Visual Clarity: Utilize a color-coded heatmap to instantly recognize which assets are near or far from their ATHs. Colors transition smoothly from cool to warm tones, indicating smaller to larger distances respectively.
Real-Time Updates: The script updates dynamically with live market data, ensuring you have the most current information at your fingertips.
Versatile Application: Whether you're tracking stocks, cryptocurrencies, commodities, or indices, the "ATH Distance Heatmap" adapts to a wide array of assets, making it a versatile tool for your trading arsenal.
Insightful Analysis: Beyond mere visualization, this tool can help identify potential buying opportunities in assets that are significantly below their ATHs, or highlight caution for those nearing their peaks.
How to Use:
Configure Your Assets: Start by selecting the assets you wish to track. The script can be customized to monitor a broad market range or a specific segment.
Interpret the Colors: Use the color gradient to gauge the distance of each asset from its ATH. Cooler colors indicate assets closer to their ATH, while warmer colors highlight those further away.
Ideal for:
Traders looking for a quick visual guide to market trends and asset performance.
Investors aiming to capitalize on recovery opportunities or to evaluate entry and exit points.
Market analysts interested in a concise overview of asset health relative to historical performance.
Bitcoin Regression Price BoundariesTLDR
DCA into BTC at or below the blue line. DCA out of BTC when price approaches the red line. There's a setting to toggle the future extrapolation off/on.
INTRODUCTION
Regression analysis is a fundamental and powerful data science tool, when applied CORRECTLY . All Bitcoin regressions I've seen (Rainbow Log, Stock-to-flow, and non-linear models), have glaring flaws ... Namely, that they have huge drift from one cycle to the next.
Presented here, is a canonical application of this statistical tool. "Canonical" meaning that any trained analyst applying the established methodology, would arrive at the same result. We model 3 lines:
Upper price boundary (red) - Predicted the April 2021 top to within 1%
Lower price boundary (green)- Predicted the Dec 2022 bottom within 10%
Non-bubble best fit line (blue) - Last update was performed on Feb 28 2024.
NOTE: The red/green lines were calculated using solely data from BEFORE 2021.
"I'M INTRUIGED, BUT WHAT EXACTLY IS REGRESSION ANALYSIS?"
Quite simply, it attempts to draw a best-fit line over some set of data. As you can imagine, there are endless forms of equations that we might try. So we need objective means of determining which equations are better than others. This is where statistical rigor is crucial.
We check p-values to ensure that a proposed model is better than chance. When comparing two different equations, we check R-squared and Residual Standard Error, to determine which equation is modeling the data better. We check residuals to ensure the equation is sufficiently complex to model all the available signal. We check adjusted R-squared to ensure the equation is not *overly* complex and merely modeling random noise.
While most people probably won't entirely understand the above paragraph, there's enough key terminology in for the intellectually curious to research.
DIVING DEEPER INTO THE 3 REGRESSION LINES ABOVE
WARNING! THIS IS TECHNICAL, AND VERY ABBREVIATED
We prefer a linear regression, as the statistical checks it allows are convenient and powerful. However, the BTCUSD dataset is decidedly non-linear. Thus, we must log transform both the x-axis and y-axis. At the end of this process, we'll use e^ to transform back to natural scale.
Plotting the log transformed data reveals a crucial visual insight. The best fit line for the blowoff tops is different than for the lower price boundary. This is why other models have failed. They attempt to model ALL the data with just one equation. This causes drift in both the upper and lower boundaries. Here we calculate these boundaries as separate equations.
Upper Boundary (in red) = e^(3.24*ln(x)-15.8)
Lower Boundary (green) = e^(0.602*ln^2(x) - 4.78*ln(x) + 7.17)
Non-Bubble best fit (blue) = e^(0.633*ln^2(x) - 5.09*ln(x) +8.12)
* (x) = The number of days since July 18 2010
Anyone familiar with Bitcoin, knows it goes in cycles where price goes stratospheric, typically measured in months; and then a lengthy cool-off period measured in years. The non-bubble best fit line methodically removes the extreme upward deviations until the residuals have the closest statistical semblance to normal data (bell curve shaped data).
Whereas the upper/lower boundary only gets re-calculated in hindsight (well after a blowoff or capitulation occur), the Non-Bubble line changes ever so slightly with each new datapoint. The last update to this line was made on Feb 28, 2024.
ENOUGH NERD TALK! HOW CAN I APPLY THIS?
In the simplest terms, anything below the blue line is a statistical buying opportunity. The closer you approach the green line (the lower boundary) the more statistically strong that opportunity is. As price approaches the red line, is a growing statistical likelyhood/danger of an imminent blowoff top.
So a wise trader would DCA (dollar cost average) into Bitcoin below the blue line; and would DCA out of Bitcoin as it approaches the red line. Historically, you may or may not have a large time-window during points of maximum opportunity. So be vigilant! Anything within 10-20% of the boundary should be regarded as extreme opportunity.
Note: You can toggle the future extrapolation of these lines in the settings (default on).
CLOSING REMARKS
Keep in mind this is a pure statistical analysis. It's likely that this model is probing a complex, real economic process underlying the Bitcoin price. Statistical models like this are most accurate during steady state conditions, where the prevailing fundamentals are stable. (The astute observer will note, that the regression boundaries held despite the economic disruption of 2020).
Thus, it cannot be understated: Should some drastic fundamental change occur in the underlying economic landscape of cryptocurrency, Bitcoin itself, or the broader economy, this model could drastically deviate, and become significantly less accurate.
Furthermore, the upper/lower boundaries cross in the year 2037. THIS MODEL WILL EVENTUALLY BREAK DOWN. But for now, given that Bitcoin price moves on the order of 2000% from bottom to top, it's truly remarkable that, using SOLELY pre-2021 data, this model was able to nail the top/bottom within 10%.
Pi Cycle Indicator Low and High
The Pi Cycle Indicator is a technical analysis tool used in finance, particularly within cryptocurrency markets, to identify potential market tops or bottoms. It is based on two moving averages: the 111-day moving average and the 350-day moving average of Bitcoin's price. The indicator suggests that when these two moving averages converge or cross each other, it may signal significant market turning points. The name "Pi Cycle" comes from the mathematical relationship between these two moving averages, roughly equivalent to the mathematical constant Pi (3.14). Traders and analysts use this indicator to gauge potential trend reversals and make informed decisions regarding their trading strategies. However, like any technical analysis tool, it should be used in conjunction with other indicators and fundamental analysis for a comprehensive understanding of market conditions.
ATH finder showing passed daysATH Finder Showing Passed Days Indicator
Introducing the "ATH Finder Showing Passed Days" – a cutting-edge TradingView indicator meticulously designed for traders and investors focused on capturing and analyzing the all-time highs (ATHs) of financial markets. Whether you're navigating the volatile waves of cryptocurrencies, the dynamic shifts of the stock market, forex, or any other trading instrument, this indicator is your essential tool for highlighting and understanding ATHs with precision.
Core Features:
Dynamic ATH Tracking: Seamlessly identifies and marks the most recent ATHs in any given market, ensuring that you are always up-to-date with significant price levels that matter the most.
Days Since ATH Visualization: Innovatively displays the number of days that have passed since the last ATH was reached. This powerful feature provides crucial insights into market sentiment, offering a clear view of how long the current price has been consolidating or retreating from its peak.
Visual Enhancements: Features a striking yellow arrow precisely at the ATH point, drawing immediate attention to pivotal market moments without cluttering your chart.
Strategic Placement of Information: Incorporates a non-intrusive label placed in the top right corner of your chart, summarizing the ATH value alongside the days elapsed since its occurrence. This approach ensures your chart remains clean and organized, allowing for other analyses to be conducted without distraction.
Customizable to Fit Your Needs: While it's ready to use out of the box, the indicator provides flexibility for customization, making it adaptable to various timeframes and individual trading strategies.
Benefits for Traders and Investors:
Provides a historical context to current price levels, helping to gauge the strength and potential of market trends.
Aids in identifying potential resistance levels, offering strategic insights for entry and exit points.
Enhances market analysis with a clear, visual representation of significant price milestones and their temporal context.
Easy Setup:
To integrate the "ATH Finder Showing Passed Days" indicator into your trading strategy, simply add it from the TradingView Indicators menu to your chart. Customize according to your preferences and let the indicator illuminate your path to more informed decision-making.
Why Choose the ATH Finder Showing Passed Days?
In the quest for market excellence, understanding the nuances of price movements and their historical significance is paramount. The "ATH Finder Showing Passed Days" indicator not only highlights where and when the market reached its zenith but also contextualizes these moments within the broader tapestry of trading days. Equip yourself with the insight to discern the momentum and potential retracements, elevating your trading to new heights.
BTC Spread Indicator"Hot potato, Bitcoin style!
In the dynamic world of cryptocurrency, keeping an eye on price movements across different exchanges can be as exhilarating as a game of hot potato. By calculating the average Bitcoin price across major exchanges, we can then dive deeper to identify the spreads between this global average and the prices on individual exchanges. This analysis reveals who's currently 'holding the potato'—or dealing with higher prices—and predicts who might be next. It's a fun, yet insightful way to visualize market volatility and trading opportunities. Let's see where the potato lands next!"
Change in DominanceTitle: Change in Dominance Indicator
Description:
This is a tool designed to gauge the prevailing trend in the cryptocurrency market. By analyzing the Rate of Change (ROC) in percentage terms over the previous 9 bars for BTC Dominance (BTC.D), Ethereum Dominance (ETH.D), Other Altcoins Dominance (OTHER.D), and USDT Dominance (USDT.D).
How It Works:
The indicator calculates the ROC for BTC.D, ETH.D (aggregated as part of the Altcoin market), OTHER.D (also included in the Altcoin calculation), and USDT.D.
Three lines represent the trends for Bitcoin (BTC), Altcoins (ETH and OTHER combined), and USDT respectively:
Green Line: Represents the trend for BTC. A higher green line indicates a dominance of BTC in the market trend, suggesting money flow into Bitcoin.
Silver Line: Indicates the Altcoin trend (combining ETH and OTHER). When the silver line is the highest among the three, it signals that Altcoins are leading the market, which can be considered bullish as it suggests money is flowing into Altcoins.
Red Line: Represents the USDT trend. A dominant red line over others implies a bearish market sentiment, indicating money flow out of cryptocurrencies and into USDT.
Usage Tips:
Altcoin Bullishness: When the silver line is above both the red and green lines, it suggests a bullish trend for Altcoins, indicating that money is flowing into the Altcoin sector of the market.
Market Bearishness: If the red line surpasses the silver and green lines, it could be a signal that investors are moving their funds into USDT, often a sign of bearish market sentiment.
BTC Bullishness: A higher green line compared to the silver and red lines implies that Bitcoin is the dominant force in the market, suggesting a bullish sentiment for BTC.
MACD by Take and TradeImproved version of MACD with asymmetrical BUY and SELL approaches.
This indicator is based on popular MACD one, but with some "tricks" designed to make it more applicable to the rapidly changing crypto market.
Key benefits:
Dynamic auto-adjusted threshold to filter out weak signals
Highlighted BUY/SELL signals with divergence (if a signal is accompanied by divergence, for example, price makes a new high while macd has a second high below the first, this signal is considered stronger and will be highlighted in a darker color)
Boost BUY signals on very slow market in accumulation phase
Not symmetric! It uses 2 different signal lines, which allows to obtain SELL signals earlier comparing to classic MACD approach
Classic concept of MACD
Classic MACD, in its simplest case, consists of two lines - macd line and signal line. Macd line is a difference between so-called "fast" and "slow" EMA lines (there are just a Exponential Moving Average lines with different windows: "12" for fast and "26" for slow). Signal line is just a smoothed "macd" line.
When macd line crosses signal line from bottom to up and intersection point < 0, this is "BUY" signal. And vise versa, when macd line crosses signal line from top to bottom, and intersection point > 0, this is "SELL" signal.
Parameters used in default configuration of classic MACD indicator:
Fast line: EMA-12
Slow line: EMA-26
Signal line: EMA-9
Problem of classic concept
Classic MACD indicator usually gives not bad "BUY" signals, especially if using them not for operational trading but for "investment" strategy. But "SELL" signalls usually generated too late. Simply because the market tends to fall much faster than it rises.
Possible solution (the main feature of our version of MACD)
To make indicator react faster on SELL condition, while still keeping it reliable for BUY signals, we decided to use two signal lines . Faster than default signal line (with window=6) for BUY signals and much faster than default (with window=2) for SELL signals.
This approach allowed us to receive sell signals earlier and exit deals on more favorable prices. Trade off of this change - is the number of SELL signals - there were more of them. However, this does not matter, since we receive the very first sell signal with a "very fast signal line" much earlier than with classic indicator settings.
Parameters we use in our improved MACD indicator:
Fast line: EMA-12
Slow line: EMA-24
Faster signal line: EMA-6
Much faster signal line: EMA-2
Removing noise (false triggerings)
Other drawback of classic MACD - it generates a lot of "weak" (false) signals. This signals are generated when macd crosses signal line much close to zero-line. And usually there are a lot of such intersections.
To remove this kind of noise, we added a trigger threshold, which by default is equal to 2.5% of the average asset price over a long period of time. Due to the link to the average price, this threshold automatically takes a specific value for each trading pair. Threshold 2.5% works perfect for all trading pairs for 1D timeframe. For other timeframes user can (and maybe will want) change it.
Boost weak BUY signals in a prolonged bear market
Signals on bearish stage are usually very weak, because there is no volatility, and no price impulse. And such signals will be filtered out as "noise" - see above. But this time is perfect time to buy! Therefore, we further boost the buy signals in a prolonged bear market so that they can pass through the filter and appear on the chart. Bearish period is the best time to invest!
Developed by Take and Trade. Enjoy using it!
Bitcoin Halving Dates + CountdownBitcoin Halving Dates + Countdown Indicator
This unique TradingView Indicator is designed to provide traders and cryptocurrency enthusiasts with critical information about the Bitcoin halving events directly on their charts. Bitcoin halving is a significant event that reduces the reward for mining Bitcoin transactions by half, an occurrence that happens approximately every four years and is known to impact Bitcoin's price significantly.
Features:
▪ Halving Date Lines: The indicator plots vertical lines on the chart at the dates of past and the upcoming Bitcoin halving events.
Customizable Appearance: Users can personalize the look of the indicator with options to change the color of the halving lines, label background, and text for better visibility against their chart theme.
▪ Halving Event Labels: Each halving event is marked with a label indicating its sequence (e.g., 1st Halving) and the exact date it occurred or is expected to occur.
Countdown to Next Halving: For the upcoming halving event, the indicator displays a countdown in days, hours, minutes, and seconds, helping users anticipate the event with precise timing.
▪ User-friendly Options: Toggle the visibility of labels for a cleaner chart appearance and customize color schemes to match personal preferences or chart themes.
Usage:
This indicator is invaluable for those looking to understand Bitcoin's historical halving events and their timing in relation to price movements. It's also perfect for preparing for the next halving event, as the countdown feature provides a clear and timely reminder.
Customization Options:
▪ Show Labels: Toggle on/off the visibility of halving event labels.
Line Color: Choose the color of the vertical lines marking each halving event.
Label Background Color & Text Color: Customize the background and text color of the labels for better readability.
▪ Countdown Label Colors: Separate customization options for the countdown label's background and text colors, allowing for clear visibility and distinction from other chart elements.
Enhance your chart with this indicator and trade with more context and anticipation towards the future of Bitcoin.
Volatility Visualizer by Oddbeaker LLCUse this to determine if a crypto pair has volatility suitable for your Oddbeaker Synthetic Miner. Draws entry/exit lines over the candles.
"Show me every place on the chart where I could have made X percent gains in Y days or less."
Inputs :
Percent Gain : Minimum percent gains to show on the chart.
Scan Bars : Maximum number of bars allowed to reach the profit target.
Notes :
Lines drawn on the chart indicate the entry and exit times and prices to reach the exact profit target.
The indicator only uses the low price of each candle to determine entry. It does not show every possible entry point.
When counting lines, count any group of lines that cross each other as one. Also, count any group of lines that do not cross but overlap in price over the same time period as one.
Tips :
For best results, set Percent Gain to double the amount of the sum of Min Profit and Min Stash on your Synth Miner. Example: If you have minProfit=5 and minStash=5, 5+5=10, so percentGain should be 20 on the chart.
Use a daily chart and set Scan Bars to 7 or less on highly volatile pairs.
Look for charts with the highest number of lines that don't overlap.
Use this indicator combined with the Synthetic Mining Channel for best results.
Global Liquidity Index (Candles)The Global Liquidity Index (Candles) provides a comprehensive overview of major central bank balance sheets worldwide, presenting values converted to USD for consistency and comparability, following relevant forex rates. This indicator, based on the code developed by user ingeforberg , incorporates essential US accounts including the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), subtracted from the Federal Reserve's balance sheet to offer a nuanced perspective on US liquidity. Users can tailor their analysis by selectively enabling or disabling specific central banks and special accounts according to their preferences. The index exclusively includes central banks abstaining from currency pegging and with reliable data accessible since late 2007, ensuring a robust aggregated liquidity model.
The calculation of the Global Liquidity Index involves subtracting the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP) from the Federal Reserve System (FED) and adding the balance sheets of major central banks worldwide: the European Central Bank (ECB), the People's Bank of China (PBC), the Bank of Japan (BOJ), the Bank of England (BOE), the Bank of Canada (BOC), the Reserve Bank of Australia (RBA), the Reserve Bank of India (RBI), the Swiss National Bank (SNB), the Central Bank of the Russian Federation (CBR), the Central Bank of Brazil (BCB), the Bank of Korea (BOK), the Reserve Bank of New Zealand (RBNZ), Sweden's Central Bank (Riksbank), and the Central Bank of Malaysia (BNM).
This tool proves invaluable for individuals seeking a consolidated perspective on global liquidity to interpret macroeconomic trends. Analyzing these balance sheets enables users to discern policy trajectories and assess the global economic landscape, providing insights into asset pricing and assisting investors in making well-informed capital allocation decisions. Historically, assets perceived as riskier, such as small caps and cryptocurrencies, have tended to perform favorably during periods of escalating liquidity. Thus, investors may exercise caution regarding additional risk exposure unless a sustained upward trend in global liquidity is evident.
Main differences between the original and updated indicators:
The "Global Liquidity Index (Candles)" script, compared to the original "Global Liquidity Index" script, offers a more detailed and visually rich representation of liquidity data.
"Global Liquidity Index (Candles)" employs candlestick visualization to represent liquidity data. Each candlestick encapsulates open, high, low, and close prices over a given period. This format provides granular insights into liquidity fluctuations, facilitating a more nuanced analysis.
By using candlesticks, the script offers traders detailed information about liquidity dynamics. They can analyze the patterns formed by candlesticks to discern trends, reversals, and market sentiment shifts, aiding in making informed trading decisions.
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
Open Liquidity Heatmap [BigBeluga]Open Liquidity Heatmap is an indicator designed to display accumulated resting liquidity on the chart.
Unlike any other liquidity heatmap, this aims to accumulate liquidity at specific levels that build up over time, showing larger areas of liquidity.
🔶 FEATURES
The indicator includes the following settings:
Lookback : Used to determine the range calculation of the heatmap.
Leverage : Leverage of the liquidation (Counted as % in price, Example: 4.5 will return a distance from price of 4.5%, indicating any possible resting liquidity in this range).
Levels : Amount of levels to display (Each level is counted as liquidity resting on the chart; fewer levels will return a bigger area of liquidity sitting on the chart).
Mode : Apply a color gradient from the minimum liquidation to the maximum liquidity level. Set the maximum color gradient value (Counted as volume).
Offset : Automatically determine the offset range of the Volume Profiles. Manual offset of the Volume Profiles.
🔶 CALCULATION
for i = 0 to step - 1
float plotter = na
switch i
0 =>
plotter := hs
=>
plotter := hs - diff * ( i )
cls.hm.gnL(plotter)
cls.vp.put(plotter, 0)
We calculate levels like a normal volume profile with steps, from the highest point within the lookback to the lowest one. Each level will contain the corresponding amount of volume that the candle has closed in that range.
As we can see in the image above, we add liquidity each time the distance in % from price is between two levels.
Unlike many liquidity indicators that provide a single candle liquidity heatmap, this aims to add up liquidity (volume) in already present levels.
This can be extremely useful to see which levels are likely to be more liquid and tend to get a bigger reaction to the price.
Imagine it like a range of levels that each time price revisits that area, a new position area is added; we add volume in that area each time price visits that zone. Liquidity builds up in those zones, causing a bigger reaction to the price once the price visits it.
This indicator is not the same as a single candle heatmap like many others. What is a single candle heatmap?
A single candle heatmap is when a level is created on every new candle, coloring the level based on the total volume of it.
This indicator, on the contrary, aims to provide a more specific use by adding up liquidity each time price visits it.
🔶 BASIC DEMOSTRATION
This is a basic demonstration of how we can spot high liquidity points overall using confluence:
We see the POC of the liquidation in a low volume area of the normal volume profile adding up as confluence.
Resistance from the POC Volume Profile suggesting price will go lower.
Major long open liquidity down.
As we can see, price takes out all the long liquidity and right after pumping, indicating that all the major liquidity got taken out.
Some key note to take is that a POC in the liquidation heatmap in a low volume area of the normal Volume Profile add confluence of a possible big reaction in that zone.
In the forex market, we suggest to use a low distance from price (Leverage) while in a crypto market you can use the one that fit the best the current timeframe.
🔶 CONCLUSION
This indicator aims to show open resting liquidity that had built up over time, showing the most amount of liquidation in specific areas in an aggregated way unlike many liquidation heatmap indicators that show single-level liquidation.
🔶 RELATED SCRIPT
RVOL++Overview
RVOL++ is a valuable tool for intraday traders to gauge market participation and anticipate the pace of the market. By understanding the RVOL levels, traders can adjust their strategies and expectations to align with the current market conditions. RVOL is a simple mathematical formula that compares the current volume to a prior lookback period, such as the previous 5 days or previous 10 days. This indicator helps traders understand the level of interest or participation in the market, which in turn can indicate the speed or pace of the market.
How to calculate RVOL at Time
Check if the current time is within the specified time period (e.g., 9:30 AM to 5:00 PM EST).
If it is, calculate the current cumulative volume for that period.
Find the average cumulative volume for the same period over the past X days (where X is the lookback period).
Calculate the RVOL at Time as:
RVOL at Time =(Current Cumulative Volume/Average Cumulative Volume)×100
For more info about calculating RVOL at time please refer to the Tradingview article.
www.tradingview.com
Key Features of RVOL++
Two Session and Daily Modes: In Two Session mode, it calculates RVOL for two distinct trading sessions, while in Daily mode, it calculates RVOL for the entire trading day. Two Session mode helps for instruments like futures, forex, crypto that trade 23+ hours. If you are using an instrument such as a stock like AAPL, if you don't have pre-market/extended hours enabled you will want to use "Daily Mode".
Session Time Settings: The indicator allows users to define the trading session times in Eastern Standard Time (EST) for more accurate RVOL calculations.
Customizable Lookback Period: Users can set the number of days for the lookback period, allowing for flexibility in calculating the average volume at time (RVOL).
Color-Coded RVOL Histogram: The indicator displays a color-coded histogram to visualize RVOL levels. Different colors represent different RVOL ranges, making it easy to identify low, neutral, and high RVOL periods.
RVOL Ranges**: The indicator defines RVOL ranges as follows:
40 - 80: Low RVOL (Red/Yellow)
80 - 120: Neutral RVOL (Blue/Cyan)
120+: High RVOL (Green-Lime)
Low RVOL Environment
Expect slow market movement with limited opportunities.
Focus on A+ setups and be selective.
Use tighter stops, size down, and adjust trading goals.
Neutral RVOL Environment
Expect a more normalized trading pace with frequent rotations.
Lean on structure and incorporate other trading tools.
Use normal sizing and stop management.
High RVOL Environment
Expect the best opportunities for range expansion and rotations.
Be more relaxed about overtrading but stay focused on structure.
Start with smaller initial size and build up to a full position.
Bandwidth Volatility - Silverman Rule of thumb EstimatorOverview
This indicator calculates volatility using the Rule of Thumb bandwidth estimator and incorporating the standard deviations of returns to get historical volatility. There are two options: one for the original rule of thumb bandwidth estimator, and another for the modified rule of thumb estimator. This indicator comes with the bandwidth , which is shown with the color gradient columns, which are colored by a percentile of the bandwidth, and the moving average of the bandwidth, which is the dark shaded area.
The rule of thumb bandwidth estimator is a simple and quick method for estimating the bandwidth parameter in kernel density estimation (KSE) or kernel regression. It provides a rough approximation of the bandwidth without requiring extensive computation resources or fine-tuning. One common rule of thumb estimator is Silverman rule, which is given by
h = 1.06*σ*n^(-1/5)
where
h is the bandwidth
σ is the standard deviation of the data
n is the number of data points
This rule of thumb is based on assuming a Gaussian kernel and aims to strike a balance between over-smoothing and under-smoothing the data. It is simple to implement and usually provides reasonable bandwidth estimates for a wide range of datasets. However , it is important to note that this rule of thumb may not always have optimal results, especially for non-Gaussian or multimodal distributions. In such cases, a modified bandwidth selection, such as cross-validation or even applying a log transformation (if the data is right-skewed), may be preferable.
How it works:
This indicator computes the bandwidth volatility using returns, which are used in the standard deviation calculation. It then estimates the bandwidth based on either the Silverman rule of thumb or a modified version considering the interquartile range. The percentile ranks of the bandwidth estimate are then used to visualize the volatility levels, identify high and low volatility periods, and show them with colors.
Modified Rule of thumb Bandwidth:
The modified rule of thumb bandwidth formula combines elements of standard deviations and interquartile ranges, scaled by a multiplier of 0.9 and inversely with a number of periods. This modification aims to provide a more robust and adaptable bandwidth estimation method, particularly suitable for financial time series data with potentially skewed or heavy-tailed data.
Formula for Modified Rule of Thumb Bandwidth:
h = 0.9 * min(σ, (IQR/1.34))*n^(-1/5)
This modification introduces the use of the IQR divided by 1.34 as an alternative to the standard deviation. It aims to improve the estimation, mainly when the underlying distribution deviates from a perfect Gaussian distribution.
Analysis
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Modelling Requirements
Rule of thumb Bandwidth: Provides a broader perspective on volatility trends, smoothing out short-term fluctuations and focusing more on the overall shape of the density function.
Historical Volatility: Offers a more granular view of volatility, capturing day-to-day or intra-period fluctuations in asset prices and returns.
Pros of Bandwidth as a volatility measure
Robust to Data Distribution: Bandwidth volatility, especially when estimated using robust methods like Silverman's rule of thumb or its modifications, can be less sensitive to outliers and non-normal distributions compared to some other measures of volatility
Flexibility: It can be applied to a wide range of data types and can adapt to different underlying data distributions, making it versatile for various analytical tasks.
How can traders use this indicator?
In finance, volatility is thought to be a mean-reverting process. So when volatility is at an extreme low, it is expected that a volatility expansion happens, which comes with bigger movements in price, and when volatility is at an extreme high, it is expected for volatility to eventually decrease, leading to smaller price moves, and many traders view this as an area to take profit in.
In the context of this indicator, low volatility is thought of as having the green color, which indicates a low percentile value, and also being below the moving average. High volatility is thought of as having the yellow color and possibly being above the moving average, showing that you can eventually expect volatility to decrease.
Dynamic Momentum GaugeOverview
The Dynamic Momentum Gauge is an indicator designed to provide information and insights into the trend and momentum of a financial asset. While this indicator is not directional , it helps you know when there will be a trend, big move, or when momentum will have a run, and when you should take profits.
How It Works
This indicator calculates momentum and then removes the negative values to focus instead on when the big trend could likely happen and when it could end, or when you should enter a trade based on momentum or exit. Traders can basically use this indicator to time their market entries or exits, and align their strategies with momentum dynamics.
How To Use
As previously mentioned, this is not a directional indicator but more like a timing indicator. This indicator helps you find when the trend moves, and big moves in the markets will occur and its possibly best to exit the trades. For example, if you decide to enter a long trade if the Dynamic Momentum Gauge value is at an extreme low and another momentum indicator that you use has conditions that you would consider to long with, then this indicator is basically telling you that there isn't more space for the momentum to squeeze any longer, can only really expand from that point or stay where it currently is, but this is also a mean reverting process so it does tend to go back up from the low point.
Settings:
Length: This is the length of the momentum, by default its at 100.
Normalization Length: Length of the Normalization which ensures the the values fall within a consistent range.
Stablecoin Dominance [LuxAlgo]The Stablecoin Dominance tool displays the evolution of the relative supply dominance of major stablecoins such as USDT, USDC, BUSD, DAI, and TUSD.
Users can disable supported stablecoins to only show the supply dominance relative to the ones enabled.
🔶 USAGE
The stablecoin space is subject to constant change due to new arriving stablecoins, regulation, collapse of coins...etc.
Studying the evolution in supply dominance can help see the effect that certain events can have on the stablecoin sphere.
This dominance graph is displayed over the user price chart to easily observe the correlation between stablecoin dominances and market prices. Users can still move the tool to a new pane below if having it on the price chart is not desired.
🔶 DETAILS
Supported stablecoins include:
Tether (USDT)
USD Coin (USDC)
Binance USD (BUSD)
Dai (DAI)
TrueUSD (TUSD)
Supply dominance of a stablecoin is calculated by dividing the total supply of that stablecoin by the total supply of all enabled stablecoins. That is for N stablecoins:
sd(stablecoin A) = supply(stablecoin 1) / [supply(stablecoin 1) + supply(stablecoin 2) + supply(stablecoin 3) + ... + supply(stablecoin N)
🔹 Display
Users can control the fill style of the displayed areas, with "Gradient" enabled by default. Using "Solid" will use a solid color for each area:
This can improve the performance of the script.
Selecting "None" will not display areas.
🔶 SETTINGS
Fill Style: Fill style of the areas between each returned supply dominance. "Gradient" will color the areas using a gradient, while "Solid" will use a solid color.
Stablecoins List: List of stablecoins used for the supply dominance calculation, disabling one stablecoin will exclude it from all calculations.
RSI Volatility Bands [QuantraSystems]RSI Volatility Bands
Introduction
The RSI Volatility Bands indicator introduces a unique approach to market analysis by combining the traditional Relative Strength Index (RSI) with dynamic, volatility adjusted deviation bands. It is designed to provide a highly customizable method of trend analysis, enabling investors to analyze potential entry and exit points in a new and profound way.
The deviation bands are calculated and drawn in a manner which allows investors to view them as areas of dynamic support and resistance.
Legend
Upper and Lower Bands - A dynamic plot of the volatility-adjusted range around the current price.
Signals - Generated when the RSI volatility bands indicate a trend shift.
Case Study
The chart highlights the occurrence of false signals, emphasizing the need for caution when the bands are contracted and market volatility is low.
Juxtaposing this, during volatile market phases as shown, the indicator can effectively adapt to strong trends. This keeps an investor in a position even through a minor drawdown in order to exploit the entire price movement.
Recommended Settings
The RSI Volatility Bands are highly customisable and can be adapted to many assets with diverse behaviors.
The calibrations used in the above screenshots are as follows:
Source = close
RSI Length = 8
RSI Smoothing MA = DEMA
Bandwidth Type = DEMA
Bandwidth Length = 24
Bandwidth Smooth = 25
Methodology
The indicator first calculates the RSI of the price data, and applies a custom moving average.
The deviation bands are then calculated based upon the absolute difference between the RSI and its moving average - providing a unique volatility insight.
The deviation bands are then adjusted with another smoothing function, providing clear visuals of the RSI’s trend within a volatility-adjusted context.
rsiVal = ta.rsi(close, rsiLength)
rsiEma = ma(rsiMA, rsiVal, bandLength)
bandwidth = ma(bandMA, math.abs(rsiVal - rsiEma), bandLength)
upperBand = ma(bandMA, rsiEma + bandwidth, smooth)
lowerBand = ma(bandMA, rsiEma - bandwidth, smooth)
long = upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50)
short= not (upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50))
By dynamically adjusting to market conditions, the RSI trend bands offer a unique perspective on market trends, and reversal zones.
Ichimoku Clouds Strategy Long and ShortOverview:
The Ichimoku Clouds Strategy leverages the Ichimoku Kinko Hyo technique to offer traders a range of innovative features, enhancing market analysis and trading efficiency. This strategy is distinct in its combination of standard methodology and advanced customization, making it suitable for both novice and experienced traders.
Unique Features:
Enhanced Interpretation: The strategy introduces weak, neutral, and strong bullish/bearish signals, enabling detailed interpretation of the Ichimoku cloud and direct chart plotting.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Dual Trading Modes: Long and Short modes are available, allowing alignment with market trends.
Flexible Risk Management: Offers three styles in each mode, combining fixed risk management with dynamic indicator states for versatile trade management.
Indicator Line Plotting: Enables plotting of Ichimoku indicator lines on the chart for visual decision-making support.
Methodology:
The strategy utilizes the standard Ichimoku Kinko Hyo model, interpreting indicator values with settings adjustable through a user-friendly menu. This approach is enhanced by TradingView's built-in strategy tester for customization and market selection.
Risk Management:
Our approach to risk management is dynamic and indicator-centric. With data from the last year, we focus on dynamic indicator states interpretations to mitigate manual setting causing human factor biases. Users still have the option to set a fixed stop loss and/or take profit per position using the corresponding parameters in settings, aligning with their risk tolerance.
Backtest Results:
Operating window: Date range of backtests is 2023.01.01 - 2024.01.04. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Maximum Single Position Loss: -6.29%
Maximum Single Profit: 22.32%
Net Profit: +10 901.95 USDT (+109.02%)
Total Trades: 119 (51.26% profitability)
Profit Factor: 1.775
Maximum Accumulated Loss: 4 185.37 USDT (-22.87%)
Average Profit per Trade: 91.67 USDT (+0.7%)
Average Trade Duration: 56 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Backtest is calculated using deep backtest option in TradingView built-in strategy tester
How to Use:
Add the script to favorites for easy access.
Apply to the desired chart and timeframe (optimal performance observed on the 1H chart, ForEx or cryptocurrency top-10 coins with quote asset USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
