Bollinger Bands Volatility Arrows
Explanation of Changes:
Arrow Style:
Green Up Arrow (▲): Indicates increasing volatility with a positive value.
Red Down Arrow (▼): Indicates decreasing volatility with a negative value.
Labels with Arrows:
label.new is used to create arrows with the label.style_label_up or label.style_label_down styles.
The numerical value of the volatility is displayed beside the arrow using str.tostring.
Label Position:
For increasing volatility, the green arrow is placed near the high of the candle.
For decreasing volatility, the red arrow is placed near the low of the candle.
Text Format:
Includes the arrow symbol and the volatility value (formatted to 4 decimal places).
How It Works:
You’ll see green upward arrows for increasing volatility and red downward arrows for decreasing volatility.
Each arrow includes the exact value of the Bollinger Bands width at that moment.
Индикаторы и стратегии
VWAP Trend with Standard Deviation & MidlinesThis indicator is a sophisticated VWAP (Volume Weighted Average Price) tool with multiple features:
Core Functionality:
1. Calculates a primary VWAP line that changes color based on trend direction (green when rising, red when falling)
2. Creates multiple standard deviation bands around the VWAP at customizable distances
3. Resets calculations at either:
- New York session start time (configurable, default 9:30 AM)
- Daily start time
- Can be hidden on daily/weekly/monthly timeframes if desired
Band Structure:
- Band 1 (innermost): ±1 standard deviation
- Band 2 (middle): ±2 standard deviations
- Band 3 (outermost): ±3 standard deviations
- Midlines at 0.5σ intervals between bands
- All bands can be individually enabled/disabled
Customization Options:
1. Band calculation modes:
- Standard Deviation based
- Percentage based
2. Visual settings:
- Customizable colors for all elements
- Adjustable line widths
- Optional labels with configurable size
- Optional extension lines
- Label position adjustment
3. Source data selection (default: HLC3 - High, Low, Close average)
Common Uses:
- Identifying potential support/resistance levels
- Measuring price volatility
- Spotting mean reversion opportunities
- Trading range analysis
- Trend direction confirmation
The indicator essentially creates a dynamic support/resistance structure that adapts to market volatility and volume, making it useful for both intraday and swing trading strategies.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Implied Leverage Ratio Between Current Symbol and BTCThis script calculates and visualizes the implied leverage ratio between the current symbol and Bitcoin (BTC). The implied leverage ratio is computed by comparing the cumulative price changes of the two symbols over a defined number of candles. The results provide insights into how the current symbol performs relative to BTC in terms of bullish (upward) and bearish (downward) movements.
Features
Cumulative Up and Down Ratios:
The script calculates the cumulative price increase (up) and decrease (down) ratios for both the current symbol and BTC. These ratios are based on the percentage changes relative to each candle's opening price.
Implied Leverage Ratio:
For bullish movements, the cumulative up ratio of the current symbol is divided by BTC's cumulative up ratio.
For bearish movements, the cumulative down ratio of the current symbol is divided by BTC's cumulative down ratio.
These values reflect the implied leverage of the current symbol relative to BTC in both directions.
Customizable Comparison Symbol:
By default, the script compares the current symbol to BINANCE:BTCUSDT. However, you can specify any other symbol to tailor the analysis.
Interactive Visualization:
Green Line: Represents the ratio of cumulative up movements (current symbol vs. BTC).
Red Line: Represents the ratio of cumulative down movements (current symbol vs. BTC).
A horizontal zero line is included for reference, ensuring the chart always starts from zero.
How to Use
Add this script to your chart from the Pine Editor or the public library.
Customize the number of candles (t) to define the period over which cumulative changes are calculated.
If desired, replace the comparison symbol with another asset in the input settings.
Analyze the green and red lines to identify relative strength and implied leverage trends.
Who Can Benefit
Traders and Analysts: Gain insights into the relative performance of altcoins, stocks, or other instruments against BTC.
Leverage Seekers: Identify assets with higher or lower implied leverage compared to Bitcoin.
Market Comparisons: Understand how various assets react to market movements relative to BTC.
This tool is particularly useful for identifying potential outperformers or underperformers relative to Bitcoin and can guide strategic decisions in trading pairs or market analysis.
[blackcat] L1 Banker Move█ OVERVIEW
The Pine Script is an indicator designed to analyze market signals for institutional and short-term investors. It calculates and plots three main signals: Institutional Signal, Institutional Build, and Short-Term Investor Signal. The script uses a combination of price, volume, and moving average data to generate these signals, which can help traders identify potential buying or selling opportunities.
█ LOGICAL FRAMEWORK
The script is structured into several main sections:
1 — Input Parameters
The script does not explicitly define any input parameters, relying on default values for calculations.
2 — Custom Functions
• reference_value(values, length) : Retrieves the first non-NA value from a specified number of past values.
• calculate_institutional_and_short_term_signals(low, close, open, volume) : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
3 — Calculations
• Price and Volume Metrics: The script calculates various smoothed price changes, lowest and highest values over different periods, and volume-weighted prices.
• Moving Averages: It computes simple moving averages (SMA) and exponential moving averages (EMA) for different periods.
• RSI Calculation: The script calculates a custom RSI for different periods.
• Signal Generation: It generates the institutional and short-term investor signals based on the calculated metrics.
4 — Plotting
The script plots the three main signals on the chart using the plot function.
The flow of data and logic is as follows:
• The reference_value function is used to find reference values for calculations.
• The calculate_institutional_and_short_term_signals function performs the core calculations and returns the institutional and short-term investor signals.
• The main script calls this function and plots the results.
█ CUSTOM FUNCTIONS
1 — reference_value(values, length)
• Purpose : Retrieves the first non-NA value from a specified number of past values.
• Parameters :
• values: An array of values.
• length: The number of past values to consider.
• Return Value : The first non-NA value found or na if no valid value is found.
• Functionality : Iterates through the specified number of past values and returns the first non-NA value.
2 — calculate_institutional_and_short_term_signals(low, close, open, volume)
• Purpose : Calculates the institutional and short-term investor signals based on price, volume, and moving average data.
• Parameters :
• low: Low price series.
• close: Close price series.
• open: Open price series.
• volume: Volume series.
• Return Values :
• institutional_signal: The institutional signal.
• institutional_build: The institutional build signal.
• short_term_investor_signal: The short-term investor signal.
• Functionality :
• Computes various price and volume metrics.
• Calculates moving averages and volume-weighted prices.
• Generates the institutional and short-term investor signals based on these metrics.
█ KEY POINTS AND TECHNIQUES
1 — Advanced Pine Script Features
• Custom Functions: The script defines and uses custom functions to encapsulate complex logic.
• Conditional Statements: Extensive use of iff and if statements to control the flow of calculations.
• Looping Constructs: The for loop in reference_value function to iterate through past values.
• Exponential Moving Averages (EMA): Used to smooth out price and signal changes.
• Volume-Weighted Price (VWP): Calculated to factor in volume in price analysis.
• Custom RSI Calculation: A custom RSI formula is used, which differs from the standard RSI calculation.
2 — Optimization Techniques
• Efficient Data Handling: The reference_value function efficiently finds the first non-NA value without unnecessary computations.
• Smoothed Signals: Using EMAs to smooth out noisy signals for better trend identification.
3 — Unique Approaches
• Combination of Metrics: The script combines multiple metrics (price, volume, moving averages, and custom RSI) to generate comprehensive signals.
• Institutional Build Signal: A unique approach to detect institutional activity by comparing current price levels with historical lows and smoothed price changes.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
1 — Potential Modifications
• Input Parameters: Add input parameters to allow users to customize the lengths and thresholds used in the calculations.
• Strategy Version: Convert the indicator into a strategy by adding buy/sell signals based on the generated signals.
• Additional Indicators: Integrate other technical indicators (e.g., MACD, Bollinger Bands) to enhance the signal generation process.
2 — Similar Trading Scenarios
• Institutional Activity Analysis: Use similar techniques to analyze institutional activity in other markets or assets.
• Volume Analysis: Apply the volume-weighted price and volume analysis to identify significant price movements.
• Multi-Timeframe Analysis: Extend the script to analyze signals across multiple timeframes for a more robust trading strategy.
3 — Related Pine Script Concepts
• Pine Script Functions: Understanding how to define and use custom functions effectively.
• Conditional Logic: Mastering the use of iff and if statements for complex logic.
• Looping Constructs: Familiarity with for loops for iterating through data.
• Moving Averages: Knowledge of different types of moving averages and their applications.
• Volume Analysis: Techniques for incorporating volume data into price analysis.
Bitcoin: Mayer MultipleMayer Multiple Indicator
The Mayer Multiple is a powerful tool designed to help traders assess market conditions and identify optimal buying or selling opportunities. It calculates the ratio between the current price and its 200-day simple moving average (SMA), visualizing key thresholds that indicate value zones, caution areas, and overheated markets.
Key Features:
Dynamic Market Zones: Clearly marked levels like "Smash Buy," "Boost DCA," and "Extreme Euphoria" to guide your trading decisions.
Customizable Input: Adjust the SMA length to fit your strategy.
Color-Coded Signals: Intuitive visualization of market sentiment for quick analysis.
Comprehensive Thresholds: Historical insights into price behavior with plotted reference levels based on probabilities.
This indicator is ideal for traders aiming to enhance their long-term strategies and improve decision-making in volatile markets. Use it to gain an edge in identifying potential turning points and managing risk effectively.
Shannon Entropy Volatility AnalyzerThis algorithm aims to measure market uncertainty or volatility using a Shannon entropy-based approach. 🔄📊
Entropy is a measure of disorder or unpredictability, and here we use it to evaluate the structure of price returns within a defined range of periods (window length). 🧩⏳ Thus, the goal is to detect changes to identify conditions of high or low volatility. 🔍⚡
What we seek with Shannon's formula in this algorithm is to measure market uncertainty or volatility through dynamic entropy. This measure helps us understand how unpredictable price behavior is over a given period, which is key to making informed decisions. 📈🧠
Through this formula, we calculate the level of disorder or dispersion in price returns based on their probability of occurrence, enabling us to identify moments of high or low volatility. 💡💥
Shannon Entropy Calculation 📏
• Uses probabilities to measure uncertainty in returns. 🎲
• Entropy is normalized on a scale of 0 to 100, where:
o High Entropy: Unpredictable movements (high uncertainty). ⚠️💥
•
o Low Entropy: Structured movements (low uncertainty). 📉🔒
•
• With probabilities, we measure the level of dispersion or unpredictability of returns using Shannon's entropy formula. 📊🔍
________________________________________
Indicator Usefulness 🛠️
• Identify High Volatility: When the market is unpredictable, the indicator signals "High Uncertainty." ⚡🔮
• Detect Market Stability: When the market is more predictable and structured, the indicator highlights "Low Uncertainty." 🔒🧘♂️
• Neutral Zones: Helps monitor markets without extreme conditions, enabling safer entry or exit opportunities. ⚖️🚶♂️
________________________________________
Uncertainty Zones 🌀
1. High Uncertainty: When entropy exceeds the upper threshold. 🚨🔺
2. Low Uncertainty: When entropy is below the lower threshold. 🔻💡
3. Neutral: When entropy lies between both thresholds. ⚖️🔄
________________________________________
What We Aim to Achieve with the Formula in Practice 🎯
1. Detection of Volatile Moments: Shannon’s formula helps us identify when the market is unpredictable. This is a good moment to take additional precautions, such as reducing position size or avoiding trading during high volatility phases. ⚠️📉
2. Trading Opportunities in Stable Markets: With low entropy, we can identify when the market is more predictable, favoring trend or momentum strategies with a higher chance of success. 🚀📈
3. Optimization of Risk Management: By measuring market volatility in real-time, we can adjust entry and exit strategies, tailoring risk based on the level of uncertainty detected. 🔄⚖️
________________________________________
We hope this makes it easy to interpret and use. If you have any questions or comments, please feel free to reach out to us! 📬😊
Dollar Volume DivergenceOverview
The Dollar Volume Profile and Divergence Indicator is a comprehensive tool designed to analyze both standard volume and dollar volume activity in the market. It visualizes dollar volume (calculated as close * volume) and highlights divergences between dollar volume and standard volume, providing insights into underlying market dynamics that aren't immediately visible with traditional volume analysis.
Key Features
Dollar Volume Profile:
Plots dollar volume as a histogram.
Highlights high-dollar volume bars in green (indicating significant trading activity).
Includes an optional average dollar volume line to show trends over time.
Volume-Divergence Analysis:
Calculates the difference (divergence) between dollar volume and standard volume.
Displays positive divergence (dollar volume > standard volume) in green and negative divergence (dollar volume < standard volume) in red.
Supports both histogram and boolean point visualization for divergence, offering flexibility in how the data is displayed.
Customizable Visualization:
Users can toggle between a Histogram or Boolean Points for divergence visualization.
Option to enable or disable the dollar volume profile and its average line.
Adjustable length parameter to fine-tune sensitivity for averages and divergences.
Use Cases
Volume Confirmation: Analyze whether dollar volume aligns with standard volume to confirm strong price movements.
Divergence Detection: Identify areas where dollar volume and standard volume deviate, which may signal potential reversals or exhaustion in a trend.
Market Strength Analysis: Assess the intensity of trading activity at specific price levels to determine key areas of interest.
How It Works
Dollar Volume Calculation:
Dollar volume is derived by multiplying the close price by the volume for each bar.
A moving average of dollar volume is used to determine relative activity levels.
Divergence Calculation:
The script calculates the difference between dollar volume and standard volume.
Positive values indicate that dollar volume exceeds standard volume, suggesting institutional or larger-scale trades.
Negative values highlight areas of lower dollar volume compared to standard volume.
Visualization:
The Dollar Volume Profile is displayed as a histogram, with high-dollar volume bars highlighted.
Divergences are overlaid as either a histogram or triangle markers, depending on user preference.
Average lines (optional) provide smoother trends for both dollar volume and divergence.
Customization Options
Length: Adjusts the period for moving average calculations.
Plot Style: Choose between Histogram or Boolean Points for divergence visualization.
Toggle Visibility: Enable or disable the Dollar Volume Profile and its average line for a cleaner chart.
Why Use This Indicator?
This indicator bridges the gap between traditional volume analysis and dollar volume analysis, offering deeper insights into market behavior. By combining these metrics, traders can detect nuanced patterns, validate trends, and identify divergences that may signal market turning points or continuation.
Best Practices
Use this indicator in conjunction with price action and other technical indicators for confirmation.
Look for divergences in high-dollar volume areas to detect potential trend reversals.
Analyze the interaction between the dollar volume profile and divergence histogram for a comprehensive view of market activity.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
Tomas' Financial Conditions Z Score"The indicator is a composite z-score comprised of the following four components (equally-weighted):
Credit spreads - ICE BofA High Yield Option Adjusted Spread (BAMLH0A0HYM2) and ICE BofA Corporate Index Option Adjusted Spread (BAMLC0A0CM)
Volatility indexes - VIX (S&P 500 implied volatility) and MOVE (US Treasury bond implied volatility)
I've got it set to a 160-day lookback period, which I think is roughly the best setting after some tinkering.
When the z-score is above zero, it throws a red signal - and when the z-score is below zero, it throws a green signal.
This indicator is a follow-on from the "traffic light financial conditions indicator" that I wrote a thread about a couple of months ago.
I moved on from that previous indicator because it is based on the Federal Reserve's NFCI, which is regularly revised, but I didn't take that into account at the time.
So not a great real-time indicator, if the signal can be subsequently revised in the opposite direction weeks later.
This new indicator is based on real-time market data, so there's no revisions, and it also updates daily, as opposed to weekly for the NFCI"
Custom EMA (v4) [MacroGlide]Custom EMA (v4) is an easy-to-use tool designed for traders who want a clear and reliable way to analyze market trends. By using multiple Exponential Moving Averages (EMAs), this indicator helps you visualize the market's direction and momentum in a straightforward way. Whether you're tracking short-term movements or looking for long-term patterns, Custom EMA makes it simple to spot trends and trading opportunities.
Key Features:
• Multi-EMA System: Plots up to four EMAs on the chart with customizable lengths and colors, providing flexibility to analyze trends over different timeframes.
• Dynamic Trend Cloud: A visually intuitive cloud is generated between the fastest and slowest EMA. The cloud changes color based on market trends:
• Green Cloud: Indicates a bullish trend when shorter EMAs are above longer EMAs.
• Red Cloud: Indicates a bearish trend when shorter EMAs are below longer EMAs.
• Highlighting Zones: Background shading helps distinguish bullish and bearish conditions, further clarifying the prevailing trend in the market.
How to Use:
• Add the Indicator: Load the indicator onto your chart and customize the EMA lengths to suit your trading style.
• Interpret the Cloud: Observe the color of the trend cloud to identify bullish (green) or bearish (red) market conditions.
• Combine with Highlighting Zones: Use the background shading in conjunction with the cloud to confirm trend strength and direction.
• Customize to Fit Your Strategy: Adjust the lengths and colors of the EMAs to align with your preferred analysis timeframe.
Methodology:
This indicator leverages a layered EMA approach, using up to four EMAs to calculate the trend cloud and define market conditions. By comparing the relative positions of the EMAs, it identifies bullish and bearish trends and visually represents them with a color-coded cloud. The inclusion of highlighting zones enhances the trader's ability to quickly grasp market sentiment.
Originality and Usefulness:
Custom EMA (v4) sets itself apart by integrating a trend cloud that adapts dynamically to EMA positions, providing traders with a clean and intuitive way to visualize market trends. The combination of multi-EMA plotting, background shading, and trend cloud offers comprehensive insight into both short-term and long-term market movements.
Charts:
The indicator plots four customizable EMAs alongside a trend cloud that visually captures market direction. Whether you're monitoring short-term price action or identifying long-term trends, the Custom EMA (v4) provides clarity and simplicity for traders at all levels.
Enjoy the game!
IndicatorsLibrary "Indicators"
cmf(lookback, n_to_smooth)
Calculates the Chaikin's Money Flow.
Parameters:
lookback (simple int)
n_to_smooth (simple int)
Returns: float The Money Flow value.
cmma(lookback, atr_length)
Calculates the CMMA (Close Minus Moving Average) indicator.
Parameters:
lookback (simple int)
atr_length (simple int)
Returns: float The CMMA value.
macd(fast_length, slow_length, n_to_smooth)
Calculates the normalized and scaled MACD.
Parameters:
fast_length (simple int)
slow_length (simple int)
n_to_smooth (simple int)
Returns: A tuple containing .
stochK(length, n_to_smooth)
Calculates a simplified Stochastic Oscillator.
Uses: 100 * ta.sma((close - lowest_low) / (highest_high - lowest_low), n_to_smooth)
Parameters:
length (simple int)
n_to_smooth (simple int)
Returns: float The Stochastic %K value.
williamsR(length)
Calculates the Williams %R using the stochK function.
Uses: -1 * (100 - stoch(length, 1))
Parameters:
length (simple int)
Returns: float The Williams %R value.
Standard Deviation of Returns: DivergencePurpose:
The "Standard Deviation of Returns: Divergence" indicator is designed to help traders identify potential trend reversals or continuation signals by analyzing divergences between price action and the statistical volatility of returns. Divergences can signal weakening momentum in the prevailing trend, offering insight into potential buying or selling opportunities.
Key Components
1. Returns Calculation:
* The indicator uses logarithmic returns (log(close / close )) to measure relative price changes in a normalized manner.
* Log returns are more effective than simple price differences when analyzing data across varying price levels, as they account for percentage-based changes.
2. Standard Deviation of Returns:
* The script computes the standard deviation of returns over a user-defined lookback period (ta.stdev(returns, lookback)).
* Standard deviation measures the dispersion of returns around their average, effectively quantifying market volatility.
* A higher standard deviation indicates increased volatility, while lower standard deviation reflects a calmer market.
3. Price Action:
* Detects higher highs (new peaks in price) and lower lows (new troughs in price) over the lookback period.
* Price trends are compared to the behavior of the standard deviation.
4. Divergence Detection:
A divergence occurs when price action (higher highs or lower lows) is not confirmed by a corresponding movement in standard deviation:
Bullish Divergence: Price makes a lower low, but the standard deviation does not, signaling potential upward momentum.
Bearish Divergence: Price makes a higher high, but the standard deviation does not, signaling potential downward momentum.
5. Visual Cues:
The script highlights divergence regions directly on the chart:
Green Background: Indicates a bullish divergence (potential buy signal).
Red Background: Indicates a bearish divergence (potential sell signal).
How It Works
Inputs:
* The user specifies the lookback period (lookback) for calculating the standard deviation and detecting divergences.
Calculation:
* Each bar’s returns are computed and used to calculate the standard deviation over the specified lookback period.
* The indicator evaluates price highs/lows and compares these with the highest and lowest values of the standard deviation within the same lookback period.
Highlight of Divergences:
When divergences are detected:
Bullish Divergence: The background of the chart is shaded green.
Bearish Divergence: The background of the chart is shaded red.
Trading Application
Bullish Divergence:
* Occurs when the market is oversold, or downward momentum is weakening.
* Suggests a potential reversal to an uptrend, signaling a buying opportunity.
Bearish Divergence:
* Occurs when the market is overbought, or upward momentum is weakening.
* Suggests a potential reversal to a downtrend, signaling a selling opportunity.
Contextual Use:
* Use this indicator in conjunction with other technical tools like RSI, MACD, or moving averages to confirm signals.
* Effective in volatile or ranging markets to help anticipate shifts in momentum.
Summary
The "Standard Deviation of Returns: Divergence" indicator is a robust tool for spotting divergences that can signal weakening market trends. It combines statistical volatility with price action analysis to highlight key areas of potential reversals. By integrating this tool into your trading strategy, you can gain additional confirmation for entries or exits while keeping a close watch on momentum shifts.
Disclaimer: This is not a financial advise; please consult your financial advisor for personalized advice.
squeeze candles with volume Function :
This indicator was designed to detect specific candles called “squeeze”. These candles are characterized by a relatively small body (the difference between the opening and closing price) and long shadows (the distance between the high and low prices), accompanied by significant volume. They often indicate a period of increased volatility or a potential trend reversal.
Use :
Visual detection:
Candles identified as "squeeze" are highlighted in red on the chart.
An “S” icon appears above each detected squeeze candle.
Alerts:
The indicator emits an audible and visual alert when a squeeze candle with high volume is detected (if alerts are enabled).
Market analysis:
This indicator is particularly useful for identifying trading opportunities during periods when the market is showing signs of compression or impending volatility.
Customizable settings:
Minimum volume: Defines the threshold at which the volume is considered high.
Maximum body/shadow ratio: Allows you to adjust the sensitivity to detect squeeze candles (the lower the ratio, the smaller the detected candles will have in relation to their shadows).
Benefits :
Provides accurate alerts on key market candles.
Helps anticipate large movements through analysis of volume and candle characteristics.
Adaptable to different strategies thanks to adjustable parameters.
Ideal for:
Traders who want to identify areas of potential volatility or reversal signals in the market, regardless of the asset or time frame used.
US Recessions OverlayThe US Recessions Overlay indicator highlights the periods of US economic recessions directly on your TradingView chart. Using historical data from the Great Depression to the present, it provides a visual representation of recessions as transparent red backgrounds. This can help traders and analysts correlate market movements with historical economic downturns.
Features:
- Displays US recessions since the Great Depression (1929) as shaded areas.
- Automatically adjusts the background shading to match the date ranges of historical recessions.
- A simple and effective way to observe market behavior during recessionary periods.
- Fully customizable to include new recession periods or modify transparency levels.
How to Use:
Apply the indicator to any chart. Recession periods will appear as red-shaded backgrounds, providing a clear visual cue for market behavior during those times.
Use Case:
Ideal for traders, economists, and market historians who wish to study the impact of recessions on financial markets.
Multi Ticker Price TableTable showing the current price of up to 7 tickers
- Tickers are user choice
- Table background is customizable
- User has the choice to turn the Daily % column off
Relative PerformanceSimple relative performance of a token compared to BTC, with display of normalized performance velocity line.
Options Betting Range - Extended# Options Betting Range - Extended
**Options Betting Range - Extended** is a versatile TradingView indicator designed to assist traders in identifying and visualizing optimal options trading ranges for multiple symbols. By leveraging predefined prediction and execution dates along with specific high and low price points, this indicator dynamically draws trendlines to highlight potential options betting zones, enhancing your trading strategy and decision-making process.
## **Key Features**
- **Multi-Symbol Support:** Automatically adapts to popular symbols such as SPY, IWM, QQQ, DIA, TLT, and GOOG, providing tailored options betting ranges for each.
- **Dynamic Trendlines:** Draws both dashed and solid trendlines based on user-defined prediction and execution dates, clearly marking high and low price boundaries.
- **Customizable Parameters:** Easily configure prediction and execution dates, high and low prices, and timezones to suit your specific trading requirements.
- **Single Execution:** Ensures that each trendline is drawn only once per specified prediction date, preventing clutter and maintaining chart clarity.
- **Clear Visual Indicators:** Utilizes color-coded labels to denote high (green) and low (red) price points, making it easy to identify critical trading levels at a glance.
## **How It Works**
1. **Initialization:**
- Upon adding the indicator to your chart, it initializes with predefined symbols and their corresponding high and low price points for two trendlines each.
2. **Configuration:**
- **Trendline 1:**
- **Prediction Date:** Set the year, month, and day when the trendline should be predicted.
- **Execution Date:** Define the year, month, and day when the trendline will be executed.
- **Timezone:** Choose the appropriate timezone to ensure accurate date matching.
- **Trendline 2:**
- Similarly, configure the prediction and execution dates along with the timezone.
3. **Trendline Drawing:**
- On reaching the specified prediction date, the indicator draws dashed trendlines representing the high and low price ranges.
- Solid trendlines are then drawn to solidify the high and low price boundaries.
- Labels are added to clearly mark the high and low price points on the chart.
4. **Visualization:**
- The trendlines and labels provide a visual framework for potential options trading ranges, allowing traders to make informed decisions based on these predefined levels.
## **How to Use**
1. **Add the Indicator:**
- Open your TradingView chart and apply the **Options Betting Range - Extended** indicator.
2. **Select a Symbol:**
- Ensure that the chart is set to one of the supported symbols (e.g., SPY, IWM, QQQ, DIA, TLT, GOOG) to activate the corresponding trendline configurations.
3. **Configure Trendline Parameters:**
- Access the indicator settings to input your desired prediction and execution dates, high and low prices, and select the appropriate timezone for each trendline.
4. **Monitor Trendlines:**
- As the chart progresses to the specified prediction dates, observe the dynamically drawn trendlines and labels indicating the options betting ranges.
5. **Make Informed Trades:**
- Utilize the visual cues provided by the trendlines to identify optimal entry and exit points for your options trading strategies.
## **Benefits**
- **Enhanced Strategy Visualization:** Clearly outlines potential trading ranges, aiding in the formulation and execution of precise options strategies.
- **Time-Saving Automation:** Automatically draws trendlines based on your configurations, reducing the need for manual chart analysis.
- **Improved Decision-Making:** Provides objective price levels for trading, minimizing emotional bias and enhancing analytical precision.
## **Important Considerations**
- **Timezone Accuracy:** Ensure that the timezones selected in the indicator settings align with your chart's timezone to maintain accurate date matching.
- **Chart Timeframe:** The prediction dates should correspond to the timeframe of your chart (e.g., daily, hourly) to ensure that trendlines are triggered correctly.
- **Visible Price Range:** Verify that the high and low prices set for trendlines are within the visible range of your chart to ensure that all trendlines and labels are clearly visible.
## **Conclusion**
**Options Betting Range - Extended** is a powerful tool for traders seeking to automate and visualize their options trading ranges across multiple symbols. By providing clear, customizable trendlines based on specific prediction and execution dates, this indicator enhances your ability to identify and act upon strategic trading opportunities with confidence.
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Crypto Sectors Performance [Daveatt]IMPORTANT
⚠️ This script must be used on the Daily timeframe only.
OVERVIEW
This indicator brings the powerful sector analysis capabilities from velo.xyz/market's
Sector Performance chart to TradingView.
It enables traders to track and compare performance across the crypto market's major sectors, providing essential insights for sector rotation strategies and market analysis.
CALCULATION METHOD
The indicator calculates performance across six key crypto sectors: DeFi, Gaming, Layer 1s, Layer 2s, AI, and Memecoins.
For each sector, it computes a rolling percentage performance by averaging the performance of multiple representative tokens.
All sector performances are rebased to 0% at the start of each period, making relative comparisons clear and intuitive.
VISUALIZATION MODES
The script features two distinct visualization methods:
Plots Mode:
Displays continuous performance lines for each sector over time, ideal for tracking relative strength trends and sector momentum. Each sector has its own color-coded line with performance values clearly marked.
Bars Mode:
Presents current sector performance as vertical bars, offering an immediate visual comparison of sector gains and losses.
The bars are color-coded and labeled with exact percentage values for precise analysis.
For the "Bars Mode", I used the box.new() function
SECTOR COMPOSITION
Each sector comprises carefully selected representative tokens:
- DeFi: AAVE, 1INCH, JUP, MKR, UNI
- Gaming: GALA, AXS, RONIN, SAND
- Layer 1: BTC, ETH, AVAX, APT, SOL, BNB, SUI
- Layer 2: ARB, OP, ZK, POL, STRK, MNT
- AI: FET, NEAR, RENDER, TAO
- Memecoins: PEPE, BONK, SHIB, DOGE, WIFU, POPCAT
PERFORMANCE TRACKING
The indicator implements a rolling window approach for performance calculations.
Starting from 0% at the beginning of each period, it tracks relative performance with positive values indicating outperformance and negative values showing underperformance.
Multiple timeframe options (1W, 1M, 3M, 6M, and 1Y) allow for both short-term and long-term analysis.
APPLICATIONS
This tool proves invaluable for:
- Sector rotation analysis
- Identifying trending sectors
- Comparing relative strength
- Gauging market sentiment
- Understanding market structure through sector performance
Thanks for reading and for the support
Daveatt
Rolling VWAP with Optional Kalman FilterThis script provides an advanced and customizable Rolling VWAP (Volume-Weighted Average Price) indicator, designed for traders who want to refine their trend analysis and improve decision-making. With a unique option to apply a Kalman Filter, you can smooth out VWAP values to reduce noise in volatile markets, making it easier to identify actionable trends.
Key Features:
Dynamic Rolling VWAP:
Choose the rolling window size (number of bars) to match your trading style, whether you’re an intraday scalper or a swing trader.
Kalman Filter Toggle:
Enable the Kalman filter to smooth VWAP values and eliminate market noise.
Adjustable Kalman Gain to control the level of smoothing, making it suitable for both fast and slow markets.
Price Source Flexibility:
Use the Typical Price ((H+L+C)/3) or the Close Price as the basis for VWAP calculation.
Visual Enhancements:
Background shading highlights whether the price is above (bullish) or below (bearish) the VWAP, helping traders make quick visual assessments.
A legend dynamically updates the current VWAP value.
Dual View Option:
Compare the raw Rolling VWAP and the Kalman-filtered VWAP when the filter is enabled, giving you deeper insight into market trends.
Use Cases:
Intraday Traders: Identify key price levels for re-entry or exits using a short rolling window and responsive filtering.
Swing Traders: Analyze broader trends with a longer rolling window and smoother VWAP output.
Volatile Markets: Use the Kalman filter to reduce noise and avoid false signals during high market volatility.
How to Use:
Adjust the Rolling Window to set the number of bars for VWAP calculation.
Toggle Kalman Filter on/off depending on your preference for raw or smoothed VWAP values.
Fine-tune the Kalman Gain for the desired level of smoothing.
Use the shading to quickly assess whether the price is trading above or below the VWAP for potential entry/exit signals.
Alerts and symbolswhat is "Alerts and symbols"?
It is an indicator that allows you to watch more trading pairs and add alarms to them.
what it does?
It allows you to set a total of 20 different intersection alarms, 2 in each pair, for 10 different trading pairs at the same time.
It draws the candlestick chart of a pair you choose among 10 trading pairs and the alarm lines you created for this trading pair on the chart.
It also allows you to see the prices of 10 different trading pairs at the same time, thanks to the table it creates.
how to use it?
First, select the alarm pairs you want to use, for example, BTCUSDT pair is the default value for "pair 1". You can choose 10 different trading pairs as you wish. Just below each trading pair, there are two different sections titled "line 1" and "line 2" so that you can set an alarm. Type here the price levels at which you want to be alerted in case of a price crossover.
You can use the "candle source" section to examine the candlestick charts of trading pairs. The indicator draws the candle chart of the trading pair selected in the "candle source" section.
Check the "show alert lines on chart" box to see the levels you have set an alarm for.
When everything is ready, first click on the three dots next to the indicator's name and then on the clock icon. then create an alarm and that's it.
Square Numbers Horizontal LinesTrading with square numbers is a unique approach to technical analysis, where square numbers (1, 4, 9, 16, 25, etc.) are used to guide the identification of potential levels of support, resistance, and price targets. These numbers are often considered in a more mathematical or geometric context, and they can be applied in trading strategies, chart patterns, and psychological market analysis.
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band
The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean.
Key Concepts and Principles
1. Dollar-Cost Averaging (DCA)
DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time.
In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly.
2. Mean Reversion
Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order.
Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling.
3. Bollinger Bands
Bollinger Bands are a technical analysis tool that consists of three lines:
Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline.
Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions.
Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions.
In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion.
4. Time-Based Entry and Exit
The strategy has specific entry and exit points defined by time parameters:
Open Date: The date when the strategy begins opening positions.
Close Date: The date when all positions are closed.
This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame.
5. Position Sizing
Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price.
6. Closing All Positions
The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe.
7. Background Color Based on Price Relative to Bollinger Bands
The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands:
Red background indicates the price is above the upper band, signaling overbought conditions.
Green background indicates the price is below the lower band, signaling oversold conditions.
This provides an easy-to-interpret visual cue for traders to assess the current market environment.
Postscript: Configuring Initial Capital for Backtesting
To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance:
If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD.
Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD.
This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses.
Conclusion
The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
