Daily ATR Bonanza: Expected Moves - Tr33man Daily ATR Bonanza: Expected Moves
Overview 🤷♂️
The Daily ATR Bonanza script is a powerful trading tool designed to help traders visualize and understand potential price movements using the Average True Range (ATR). It provides daily and weekly ATR levels, historical statistics, and conditional probability analysis to give traders actionable insights. The script also plots the daily Keltner channel. This script is ideal for traders who want to gauge volatility, identify key levels, and make data-driven decisions.
b]Key Features:
📈 1. Daily and Weekly ATR Levels
🔵ATR Levels: The script calculates and displays ATR-based levels for the day and week. These levels are derived from the previous day's or week's close price and are adjusted using customizable multipliers (0.5x, 1x, and 1.5x by default).
🔵You can choose the number of ATR levels (1, 2, or 3) and adjust the multipliers to suit your trading strategy.
🌐 2. ATR Bands (Keltner Channels)
🔵The script includes an option to display ATR Bands, which are volatility-based envelopes around a moving average. These bands help identify overbought and oversold conditions.
🔵You can adjust the ATR multiplier and the length of the moving average used for the bands.
🧮 3. Historical Statistics and Conditional Probability
🔵 Historical Analysis: The script analyzes historical price movements to calculate the likelihood of closing at certain ATR levels.
🔵 Conditional Probability: This feature shows the probability of the price reaching specific ATR levels given the current market conditions. The conditional matches historical data by an open in the same opening ATR bucket, as well as the current price bucket having been visited in the historical case. Conditional probabilities are just statistics, and do not predict anything.
Data Table: 📚
🔵 Historical Close Probability: The percentage of days the price closed within each ATR level.
🔵 Conditional Close Probability: The likelihood of the price closing within each ATR level today.
❓ What is Conditional Probability? ❓
Conditional probability is a statistical measure that calculates the likelihood of an event occurring given that another event has already occurred. In this script, it is used to determine the probability of the price reaching specific ATR levels based on the current opening range as well as current ATR distance from the previous close.
For example:
If the market opens near the lower end of the first ATR level, the script calculates the likelihood of the price reaching the upper end of the first, second, or third ATR level.
This analysis is based on historical data, making it a powerful tool for understanding potential price movements.
🌟 Understanding the Levels
🔵Daily Levels: These are based on the previous day's close price and ATR. They are updated at the start of each new day.
🔵Weekly Levels: These are based on the previous week's close price and ATR. They are updated at the start of each new week.
🔵ATR Bands: These are dynamic levels that adjust with market volatility.
🔬 Analyze the Statistics (Daily only for now, no weekly yet)
🔵Use the interactive table to understand historical probabilities and conditional probabilities.
🔵Focus on the current opening range and the likelihood of reaching specific levels.
🧠 Make Trading Decisions
🔵Use the ATR levels and bands to identify key support and resistance levels.
🔵Use the conditional probability table to gauge the likelihood of reaching specific targets.
🔵Adjust your strategy based on the historical performance of the market.
Example Use Cases
1. Day Trading
Use the daily ATR levels to set intraday targets and stop-loss levels.
Monitor the conditional probability table to adjust your expectations based on the opening range.
2. Swing Trading
Use the weekly ATR levels to identify longer-term support and resistance levels.
3. Scalping
Use the ATR bands to identify overbought and oversold conditions.
Use the conditional probability table to quickly assess the likelihood of price movements.
ابحث في النصوص البرمجية عن "bands"
Median Volume Weighted DeviationMVWD (Median Volume Weighted Deviation)
The Median Volume-Weighted Deviation is a technical trend following indicator that overlays dynamic bands on the price chart, centered around a Volume Weighted Average Price (VWAP). By incorporating volume-weighted standard deviation and its median, it identifies potential overbought and oversold conditions, generating buy and sell signals based on price interactions with the bands. The fill color between the bands visually reflects the current signal, enhancing market sentiment analysis.
How it Works
VWAP Calculation: Computes the Volume-Weighted Average Price over a specific lookback period (n), emphasizing price levels with higher volume.
Volume Weighted Standard Deviation: Measures price dispersion around the VWAP, weighted by volume, over the same period.
Median Standard Deviation: Applies a median filter over (m) periods to smooth the stand deviation, reducing noise in volatility estimates.
Bands: Constructs upper and lower bands by adding and subtracting a multiplier (k) times the median standard deviation from the VWAP
Signals:
Buy Signal: Triggers when the closing price crosses above the upper band.
Sell Signal: Triggers when the closing price crosses below the lower band.
Inputs
Lookback (n): Number of periods for the VWAP and standard deviation calculations. Default is set to 14.
Median Standard Deviation (m): Periods for the median standard deviation. Default is set to 2.
Standard Deviation Multiplier (k): Multiplier to adjust band width. Default is set to 1.7 with a step of 0.1.
Customization
Increase the Lookback (n) for a smoother VWAP and broader perspective, or decrease the value for higher sensitivity.
Adjust Median Standard Deviation (m) to control the smoothness of the standard deviation filter.
Modify the multiplier (k) to widen or narrow the bands based on the market volatility preferences.
Dynamic VWAP Levels (V1.0)The script calculates bands around the VWAP (Volume Weighted Average Price) using the Average True Range (ATR) to adjust the levels according to market reality. Buy and sell signals are generated when the price crosses these bands.
Customizable Parameters SmoothingLength (SmoothLength): The period used to smooth the levels. A higher value results in smoother bands that are less susceptible to rapid fluctuations.
Use EMA for smoothing?: Selects between using the Exponential Moving Average (EMA) or the Simple Moving Average (SMA) for smoothing.
ATR Length: The period used to calculate the ATR, which determines the frequency.
ATR Multiplier: A multiplier that adjusts the amplitude of the bands around the VWAP.
How the Script Works Calculating VWAP and Bands: The VWAP is calculated to obtain the volume weighted average price.
Bands are created around the VWAP by adding or subtracting a fraction of the ATR to account for the current market variation.
Smoothing Application: Price levels are smoothed to reduce market noise, allowing for better visualization of trends.
Signal Generation: Buy Signal: Generated when price crosses upwards the smoothed lower band (default dp7_smooth).
Sell Signal: Generated when price crosses downwards the smoothed upper band (default dp1_smooth).
PlanDeFi: Adaptive Trend Ribbons [ATR+RSI]#### **Overview**
The **Crypto Half-Trend Pro ** is a trend-following indicator designed to identify bullish and bearish market conditions using a combination of **moving averages, volatility adjustments, and dynamic ATR bands**. This enhanced version improves on the traditional Half-Trend system by incorporating **EMA smoothing, volatility-based adjustments, and additional fakeout/reversal detection mechanisms**.
#### **Key Features**
✅ **Trend Detection:**
- Uses a combination of fast and slow moving averages (EMA/SMA) to determine trend direction.
- Implements **Hull Moving Average (HMA)** smoothing for better trend visualization.
✅ **Dynamic ATR Bands:**
- Adjusts bands based on market volatility using **RSI-based ATR multipliers**.
- Helps identify potential **breakouts and trend reversals**.
✅ **Fakeout & Reversal Detection:**
- Detects potential **fake breakouts** by analyzing price action against extended ATR bands.
- Identifies **early reversal signals** using price crossovers and volume confirmation.
✅ **Customizable Alerts & Visuals:**
- Built-in **buy & sell signals** for trend confirmation.
- Color-coded bullish/bearish trend lines and **fakeout warnings**.
- **TradingView alerts** for trend shifts and reversals.
#### **How It Works**
🔹 The indicator calculates a **smoothed trend line** using a Hull Moving Average on dynamic price levels.
🔹 ATR bands expand/contract dynamically based on **market volatility** to improve signal accuracy.
🔹 Trend direction is confirmed when price crosses the trend line **with volume confirmation**.
🔹 **Fakeouts** are detected when price temporarily exceeds extended bands but fails to hold momentum.
🔹 **Reversal signals** are generated when price breaks back into the ATR zone with volume spikes.
#### **How to Use It**
- 📈 **Buy Signal:** When price breaks above the trend line, confirmed by volume and crossover signals.
- 📉 **Sell Signal:** When price breaks below the trend line with confirmed bearish conditions.
- 🚨 **Reversal Warning:** If price sharply re-enters the ATR zone with volume confirmation, expect a potential trend shift.
- 🛑 **Fakeout Alert:** If price temporarily breaks resistance but closes back inside, it may be a false move.
#### **Ideal For**
✔️ Crypto & Forex traders looking for **dynamic trend signals**
✔️ Swing traders wanting to **avoid fakeouts & catch reversals**
✔️ Traders seeking a **customizable, volatility-adjusted trend system**
🚀 **Try PlanDeFi: Adaptive Trend Ribbons today and improve your trend analysis!**
Half-Trend Channel [BigBeluga]Half Trend Channel is a powerful trend-following indicator designed to identify trend direction, fakeouts, and potential reversal points. The combination of upper/lower bands, midline coloring, and specific signals makes it ideal for spotting trend continuation and market reversals.
The base of the channel is calculated using smoothed half-trend logic.
// Initialize half trend on the first bar
if barstate.isfirst
hl_t := close
// Update half trend value based on conditions
switch
closeMA < hl_t and highestHigh < hl_t => hl_t := highestHigh
closeMA > hl_t and lowestLow > hl_t => hl_t := lowestLow
=> hl_t := hl_t
// Smooth
float s_hlt = ta.hma(hl_t, len)
🔵 Key Features:
Upper and Lower Bands:
The bands adapt dynamically to market volatility.
Price movements toward the bands help identify areas of overextension and potential reversal points.
Midline Trend Signal:
The midline changes color to reflect the current trend:
Green Midline: Indicates an uptrend.
Purple Midline: Signals a downtrend.
Fakeout Signals ("X"):
"X" markers appear when price briefly breaches the outer bands but fails to sustain the move.
Fakeouts help traders identify areas where price momentum weakens.
Reversal Signals (Triangles):
Triangles (▲ and ▼) mark potential tops and bottoms:
▲ Up Triangles: Suggest a potential bottom and a reversal to the upside.
▼ Down Triangles: Indicate a potential top and a reversal to the downside.
Dynamic Trend Labels:
At the last bar, the indicator displays labels like "Trend Up" or "Trend Dn" , reflecting the current trend direction.
🔵 Usage:
Use the colored midline to determine the overall trend direction.
Monitor "X" fakeout signals to spot failed breakouts or momentum exhaustion near the bands.
Watch for reversal triangles (▲ and ▼) to identify potential trend reversals at tops or bottoms.
Combine the bands and midline signals to confirm trade entries and exits:
Enter long trades when price bounces off the lower band with a green midline.
Consider short trades when price reverses from the upper band with a purple midline.
Use the trend label (e.g., "Trend Up" or "Trend Dn") for quick confirmation of the current market state.
The Half Trend Channel is an essential tool for traders who want to follow trends, avoid fakeouts, and identify reliable tops and bottoms to optimize their trading decisions.
Volatility Signaling 50SMAOverview of the Script:
The script implements a volatility signaling indicator using a 50-period Simple Moving Average (SMA). It incorporates Bollinger Bands and the Average True Range (ATR) to dynamically adjust the SMA's color based on volatility conditions. Here's a detailed breakdown:
Components of the Script:
1. Inputs:
The script allows the user to customize key parameters for flexibility:
Bollinger Bands Length (length): Determines the period for calculating the Bollinger Bands.
Source (src): The price data to use, defaulting to the closing price.
Standard Deviation Multiplier (mult): Scales the Bollinger Bands' width.
ATR Length (atrLength): Sets the period for calculating the ATR.
The 50-period SMA length (smaLength) is fixed at 50.
2. Bollinger Bands Calculation:
Basis: Calculated as the SMA of the selected price source over the specified length.
Upper and Lower Bands: Determined by adding/subtracting a scaled standard deviation (dev) from the basis.
3. ATR Calculation:
Computes the Average True Range over the user-defined atrLength.
4. Volatility-Based Conditions:
The script establishes thresholds for Bollinger Band width relative to ATR:
Yellow Condition: When the band width (upper - lower) is less than 1.25 times the ATR.
Orange Condition: When the band width is less than 1.5 times the ATR.
Red Condition: When the band width is less than 1.75 times the ATR.
5. Dynamic SMA Coloring:
The 50-period SMA is colored based on the above conditions:
Yellow: Indicates relatively low volatility.
Orange: Indicates moderate volatility.
Red: Indicates higher volatility.
White: Default color when no conditions are met.
6. Plotting the 50-Period SMA:
The script plots the SMA (sma50) with a dynamically assigned color, enabling visual analysis of market conditions.
Use Case:
This script is ideal for traders seeking to assess market volatility and identify changes using Bollinger Bands and ATR. The colored SMA provides an intuitive way to gauge market dynamics directly on the chart.
Example Visualization:
Yellow SMA: The market is in a low-volatility phase.
Orange SMA: Volatility is picking up but remains moderate.
Red SMA: Higher volatility, potentially signaling significant market activity.
White SMA: Neutral/default state.
EMA 9/13/18/25 + Bollinger BandThe indicator combines two components: Exponential Moving Averages (EMAs) and Bollinger Bands.
Exponential Moving Averages (EMAs): The indicator calculates four EMAs with different periods: 9, 13, 18, and 25. An Exponential Moving Average is a type of moving average that places a greater weight and significance on the most recent data points. As the name suggests, it's an average of the asset's price over a certain period, with recent prices given more weight in the calculation, making it more responsive to recent price changes.
Bollinger Bands: Bollinger Bands consist of a simple moving average (the basis) and two standard deviations plotted away from it. The standard deviations are multiplied by a factor (usually 2) to determine the distance from the basis. These bands dynamically adjust themselves based on recent price movements. The upper band represents the highest price level reached in the given period, while the lower band represents the lowest price level.
Combining these components provides traders with insights into both trend direction and volatility. The EMAs help identify trends by smoothing out price data, while the Bollinger Bands offer insights into volatility and potential price reversal points. Traders often use the crossovers of EMAs and interactions with Bollinger Bands to make trading decisions. For example, when the price touches the upper Bollinger Band, it may indicate overbought conditions, while touching the lower band may suggest oversold conditions. Additionally, crossovers of EMAs (such as the shorter-term EMA crossing above or below the longer-term EMA) may signal changes in trend direction.
Investor Tool - Z ScoreThe Investor Tool is intended as a tool for long term investors, indicating periods where prices are likely approaching cyclical tops or bottoms. The tool uses two simple moving averages of price as the basis for under/overvalued conditions: the 2-year MA (green) and a 5x multiple of the 2-year MA (red).
Price trading below the 2-year MA has historically generated outsized returns, and signalled bear cycle lows.
Price trading above the 2-year MA x5 has been historically signalled bull cycle tops and a zone where investors de-risk.
Just like the Glassnode one, but here on TV and with StDev bands
Now with Z-SCORE calculation:
The Z-Score is calculated to be -3 Z at the bottom bands and 3 Z at the top bands
mean = (upper_sma + bottom_sma) / 2
bands_range = upper_sma - bottom_sma
stdDev = bands_range != 0 ? bands_range / 6 : 0
zScore = stdDev != 0 ? (close - mean) / stdDev : 0
Created for TRW
Mogwai Method with RSI and EMA - BTCUSD 15mThis is a custom TradingView indicator designed for trading Bitcoin (BTCUSD) on a 15-minute timeframe. It’s based on the Mogwai Method—a mean-reversion strategy—enhanced with the Relative Strength Index (RSI) for momentum confirmation. The indicator generates buy and sell signals, visualized as green and red triangle arrows on the chart, to help identify potential entry and exit points in the volatile cryptocurrency market.
Components
Bollinger Bands (BB):
Purpose: Identifies overextended price movements, signaling potential reversions to the mean.
Parameters:
Length: 20 periods (standard for mean-reversion).
Multiplier: 2.2 (slightly wider than the default 2.0 to suit BTCUSD’s volatility).
Role:
Buy signal when price drops below the lower band (oversold).
Sell signal when price rises above the upper band (overbought).
Relative Strength Index (RSI):
Purpose: Confirms momentum to filter out false signals from Bollinger Bands.
Parameters:
Length: 14 periods (classic setting, effective for crypto).
Overbought Level: 70 (price may be overextended upward).
Oversold Level: 30 (price may be overextended downward).
Role:
Buy signal requires RSI < 30 (oversold).
Sell signal requires RSI > 70 (overbought).
Exponential Moving Averages (EMAs) (Plotted but not currently in signal logic):
Purpose: Provides trend context (included in the script for visualization, optional for signal filtering).
Parameters:
Fast EMA: 9 periods (short-term trend).
Slow EMA: 50 periods (longer-term trend).
Role: Can be re-added to filter signals (e.g., buy only when Fast EMA > Slow EMA).
Signals (Triangles):
Buy Signal: Green upward triangle below the bar when price is below the lower Bollinger Band and RSI is below 30.
Sell Signal: Red downward triangle above the bar when price is above the upper Bollinger Band and RSI is above 70.
How It Works
The indicator combines Bollinger Bands and RSI to spot mean-reversion opportunities:
Buy Condition: Price breaks below the lower Bollinger Band (indicating oversold conditions), and RSI confirms this with a reading below 30.
Sell Condition: Price breaks above the upper Bollinger Band (indicating overbought conditions), and RSI confirms this with a reading above 70.
The strategy assumes that extreme price movements in BTCUSD will often revert to the mean, especially in choppy or ranging markets.
Visual Elements
Green Upward Triangles: Appear below the candlestick to indicate a buy signal.
Red Downward Triangles: Appear above the candlestick to indicate a sell signal.
Bollinger Bands: Gray lines (upper, middle, lower) plotted for reference.
EMAs: Blue (Fast) and Orange (Slow) lines for trend visualization.
How to Use the Indicator
Setup
Open TradingView:
Log into TradingView and select a BTCUSD chart from a supported exchange (e.g., Binance, Coinbase, Bitfinex).
Set Timeframe:
Switch the chart to a 15-minute timeframe (15m).
Add the Indicator:
Open the Pine Editor (bottom panel in TradingView).
Copy and paste the script provided.
Click “Add to Chart” to apply it.
Verify Display:
You should see Bollinger Bands (gray), Fast EMA (blue), Slow EMA (orange), and buy/sell triangles when conditions are met.
Trading Guidelines
Buy Signal (Green Triangle Below Bar):
What It Means: Price is oversold, potentially ready to bounce back toward the Bollinger Band middle line.
Action:
Enter a long position (buy BTCUSD).
Set a take-profit near the middle Bollinger Band (bb_middle) or a resistance level.
Place a stop-loss 1-2% below the entry (or based on ATR, e.g., ta.atr(14) * 2).
Best Context: Works well in ranging markets; avoid during strong downtrends.
Sell Signal (Red Triangle Above Bar):
What It Means: Price is overbought, potentially ready to drop back toward the middle line.
Action:
Enter a short position (sell BTCUSD) or exit a long position.
Set a take-profit near the middle Bollinger Band or a support level.
Place a stop-loss 1-2% above the entry.
Best Context: Effective in ranging markets; avoid during strong uptrends.
Trend Filter (Optional):
To reduce false signals in trending markets, you can modify the script:
Add and ema_fast > ema_slow to the buy condition (only buy in uptrends).
Add and ema_fast < ema_slow to the sell condition (only sell in downtrends).
Check the Fast EMA (blue) vs. Slow EMA (orange) alignment visually.
Tips for BTCUSD on 15-Minute Charts
Volatility: BTCUSD can be erratic. If signals are too frequent, increase bb_mult (e.g., to 2.5) or adjust RSI levels (e.g., 75/25).
Confirmation: Use volume spikes or candlestick patterns (e.g., doji, engulfing) to confirm signals.
Time of Day: Mean-reversion works best during low-volume periods (e.g., Asian session in crypto).
Backtesting: Use TradingView’s Strategy Tester (convert to a strategy by adding entry/exit logic) to evaluate performance with historical BTCUSD data up to March 13, 2025.
Risk Management
Position Size: Risk no more than 1-2% of your account per trade.
Stop Losses: Always use stops to protect against BTCUSD’s sudden moves.
Avoid Overtrading: Wait for clear signals; don’t force trades in choppy or unclear conditions.
Example Scenario
Chart: BTCUSD, 15-minute timeframe.
Buy Signal: Price drops to $58,000, below the lower Bollinger Band, RSI at 28. A green triangle appears.
Action: Buy at $58,000, target $59,000 (middle BB), stop at $57,500.
Sell Signal: Price rises to $60,500, above the upper Bollinger Band, RSI at 72. A red triangle appears.
Action: Sell at $60,500, target $59,500 (middle BB), stop at $61,000.
This indicator is tailored for mean-reversion trading on BTCUSD. Let me know if you’d like to tweak it further (e.g., add filters, alerts, or alternative indicators)!
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
Super IndicatorOverview of the Combined Indicator
This combined indicator leverages three major technical analysis tools:
Bollinger Bands
Linear Regression Channels
Scalping Strategy Indicators (RSI, MACD, SMA)
Each of these tools provides unique insights into market conditions, and their integration offers a comprehensive view of price movements, trends, and potential trading signals.
1. Bollinger Bands
Purpose:
Bollinger Bands are used to measure market volatility and identify overbought or oversold conditions.
Components:
Basis (Middle Band): Typically a 20-period Simple Moving Average (SMA).
Upper Band: Basis + (2 * Standard Deviation).
Lower Band: Basis - (2 * Standard Deviation).
Why They Complement:
Bollinger Bands expand and contract based on market volatility. When the bands are narrow, it indicates low volatility and potential for a significant move. Wide bands indicate high volatility. This helps traders gauge the strength of market moves and potential reversals.
2. Linear Regression Channels
Purpose:
Linear Regression Channels identify the overall trend direction and measure deviation from the mean price over a specific period.
Components:
Middle Line (Linear Regression Line): The line of best fit through the price data over a specified period.
Upper and Lower Lines: Channels created by adding/subtracting a multiple of the standard deviation or another deviation measure from the regression line.
Why They Complement:
Linear Regression Channels provide a clear visual representation of the trend direction and the range within which prices typically fluctuate. This can help traders identify trend continuations and reversals, making it easier to spot entry and exit points.
3. Scalping Strategy Indicators
Purpose:
The RSI, MACD, and SMA are used to generate short-term buy and sell signals, which are essential for scalping strategies aimed at capturing quick profits from small price movements.
Components:
RSI (Relative Strength Index): Measures the speed and change of price movements, typically over 14 periods. It helps identify overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Consists of the MACD line, Signal line, and histogram. It helps identify changes in the strength, direction, momentum, and duration of a trend.
SMA (Simple Moving Average): The average price over a specified period, used to smooth out price data and identify trends.
Why They Complement:
These indicators provide short-term signals that can confirm or refute the signals given by Bollinger Bands and Linear Regression Channels. For example, a buy signal might be more reliable if the price is near the lower Bollinger Band and the MACD crosses above its signal line.
How They Work Together
Scenario 1: Confirming Trend Continuations
Bollinger Bands: Price staying near the upper band suggests a strong uptrend.
Linear Regression Channels: Price staying above the middle line confirms the uptrend.
5-Minute Scalping Strategy: RSI not in overbought territory, and MACD showing bullish momentum confirms continuation.
Scenario 2: Identifying Reversals
Bollinger Bands: Price touching or moving outside the lower band suggests oversold conditions.
Linear Regression Channels: Price at the lower channel line indicates potential support.
5-Minute Scalping Strategy: RSI in oversold territory, and MACD showing a bullish crossover indicates a reversal.
Scenario 3: Volatility Breakouts
Bollinger Bands: Bands contracting indicates low volatility and potential breakout.
Linear Regression Channels: Price moving away from the middle line signals potential breakout direction.
Scalping Strategy: MACD and RSI confirming the breakout direction for entry.
Input Parameters:
Define settings for Bollinger Bands, Linear Regression Channels, and the scalping strategy.
Allow users to customize lengths, multipliers, and colors.
Bollinger Bands Calculation:
Calculate the basis (SMA) and standard deviation.
Derive the upper and lower bands from the basis and standard deviation.
Linear Regression Channel Calculation:
Compute the slope, average, and intercept of the linear regression line.
Calculate deviations to plot upper and lower channel lines.
5-Minute Scalping Strategy:
Calculate RSI, MACD, and SMA for short-term trend analysis.
Define buy and sell conditions based on these indicators.
Plotting and Alerts:
Plot Bollinger Bands and Linear Regression Channels on the chart.
Plot buy and sell signals with shapes.
Set alerts for key conditions like exiting the regression channel bounds and trend switches.
Conclusion
By combining Bollinger Bands, Linear Regression Channels, and a 5-minute scalping strategy, this indicator offers a robust tool for traders. Bollinger Bands provide volatility insights, Linear Regression Channels highlight trend direction and potential reversals, and the scalping strategy offers precise entry and exit points. Together, these tools can enhance a trader's ability to make informed decisions in various market conditions.
No Wick Bull/Bear Candlesticks with Arrow premiumNo Wick Bull/Bear Candlesticks with Arrow premium
This script is for a custom trading indicator called "No Wick Bull/Bear Candlesticks with Arrow premium" developed by ClearTradingMind. It is designed for use with trading platforms that support scripting, such as TradingView. This indicator combines several technical analysis tools to help traders identify potential buy and sell signals in a financial market.
Key Components of the Indicator:
Moving Average (MA): The script allows users to select from various types of moving averages (SMA, EMA, HMA, etc.), which smooth out price data to identify trends. Users can set the length and type of the moving average.
Upper and Lower Bands: These bands are set at a specified deviation percentage above and below the chosen moving average. They help in identifying overbought and oversold conditions.
No Wick Bull/Bear Candlestick Identification:
Bullish Condition: A bullish candlestick is identified when the closing price is higher than the opening price, the low equals the open, and the close is above the moving average.
Bearish Condition: A bearish candlestick is identified when the closing price is lower than the opening price, the high equals the open, and the close is below the moving average.
No Wick: These conditions also imply that the candlesticks have no wicks, suggesting strong buying or selling pressure.
Arrows for Trading Signals:
No lower wick bull bar
No upper wick bear bar
When a bullish condition is met, a green upward-pointing triangle is plotted below the candlestick, indicating a potential buy signal.
When a bearish condition is met, a red downward-pointing triangle is plotted above the candlestick, indicating a potential sell signal.
EMA 20: An additional Exponential Moving Average with a length of 20 periods is plotted for further trend analysis.
Background Color Changes: The script changes the background color to blue if the EMA 20 is above the upper band, and to red if it is below the lower band, providing visual cues about the market trend.
How It Works:
Traders can input their preferences for the moving average type and length, source of the MA (like closing prices), and the deviation percentage for the bands.
The script then calculates the moving average, upper and lower bands, and checks for bullish or bearish candlestick conditions without wicks.
When such conditions are met, it plots arrows to suggest buy or sell signals.
The EMA 20 and background color changes offer additional trend information.
Usage:
This indicator is particularly useful in markets with clear trends. The no wick bull/bear candlesticks indicate strong buying or selling pressure, and the arrows provide clear visual signals for traders to consider entering or exiting positions. As with all trading indicators, it's recommended to use this tool in conjunction with other forms of analysis to confirm trading signals.
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
Dynamic Volatility EnvelopeDynamic Volatility Envelope: Indicator Overview
The Dynamic Volatility Envelope is an advanced, multi-faceted technical indicator designed to provide a comprehensive view of market trends, volatility, and potential future price movements. It centers around a customizable linear regression line, enveloped by dynamically adjusting volatility bands. The indicator offers rich visual feedback through gradient coloring, candle heatmaps, a background volatility pulse, and an on-chart trend strength meter.
Core Calculation Mechanism
Linear Regression Core :
-A central linear regression line is calculated based on a user-defined source (e.g., close, hl2) and lookback period.
-The regression line can be optionally smoothed using an Exponential Moving Average (EMA) to reduce noise.
-The slope of this regression line is continuously calculated to determine the current trend direction and strength.
Volatility Channel :
-Dynamic bands are plotted above and below a central basis line. This basis is typically the calculated regression line but shifts to an EMA in Keltner mode.
-The width of these bands is determined by market volatility, using one of three user-selectable modes:
ATR Mode : Bandwidth is a multiple of the Average True Range (ATR).
Standard Deviation Mode : Bandwidth is a multiple of the Standard Deviation of the source data.
Keltner Mode (EMA-based ATR) : ATR-based bands are plotted around a central Keltner EMA line, offering a smoother channel.
The channel helps identify dynamic support and resistance levels and assess market volatility.
Future Projection :
The indicator can project the current regression line and its associated volatility bands into the future for a user-defined number of bars. This provides a visual guide for potential future price pathways based on current trend and volatility characteristics.
Candle Heatmap Coloring :
-Candle bodies and/or wicks/borders can be colored based on the price's position within the upper and lower volatility bands.
-Colors transition in a gradient from bearish (when price is near the lower band) through neutral (mid-channel) to bullish (when price is near the upper band), providing an intuitive visual cue of price action relative to the dynamic envelope.
Background Volatility Pulse :
The chart background color can be set to dynamically shift based on a ratio of short-term to long-term ATR. This creates a "pulse" effect, where the background subtly changes color to indicate rising or falling market volatility.
Trend Strength Meter :
An on-chart text label displays the current trend status (e.g., "Strong Bullish", "Neutral", "Bearish") based on the calculated slope of the regression line relative to user-defined thresholds for normal and strong trends.
Key Features & Components
-Dynamic Linear Regression Line: Core trend indicator with optional smoothing and slope-based gradient coloring.
-Multi-Mode Volatility Channel: Choose between ATR, Standard Deviation, or Keltner (EMA-based ATR) calculations for band width.
-Customizable Vertical Gradient Channel Fills: Visually distinct fills for upper and lower channel segments with user-defined top/bottom colors and gradient spread.
-Future Projection: Extrapolates regression line and volatility bands to forecast potential price paths.
-Price-Action Based Candle Heatmap: Intuitive candle coloring based on position within the volatility channel, with adjustable gradient midpoint.
-Volatility-Reactive Background Gradient: Subtle background color shifts to reflect changes in market volatility.
-On-Chart Trend Strength Meter: Clear textual display of current trend direction and strength.
-Extensive Visual Customization: Fine-tune colors, line styles, widths, and gradient aggressiveness for most visual elements.
-Comprehensive Tooltips: Detailed explanations for every input setting, ensuring ease of use and understanding.
Visual Elements Explained
Regression Line : The primary trend line. Its color dynamically changes (e.g., green for uptrend, red-pink for downtrend, neutral for flat) based on its slope, with smooth gradient transitions.
Volatility Channel :
Upper & Lower Bands : These lines form the outer boundaries of the envelope, acting as dynamic support and resistance levels.
Channel Fill : The area between the band center and the outer bands is filled with a vertical gradient. For example, the upper band fill might transition from a darker green near the center to a lighter green at the upper band.
Band Borders : The lines outlining the upper and lower bands, with customizable color and width.
Future Projection Lines & Fill :
Projected Regression Line : An extension of the current regression line into the future, typically styled differently (e.g., dashed).
Projected Channel Bands : Extensions of the upper and lower volatility bands.
Projected Area Fill : A semi-transparent fill between the projected upper and lower bands.
Candle Heatmap Coloring : When enabled, candles are colored based on their closing price's relative position within the channel. Bullish colors appear when price is in the upper part of the channel, bearish in the lower, and neutral in the middle. Users can choose to color the entire candle body or just the wicks and borders.
Background Volatility Pulse : The chart's background color subtly shifts (e.g., between a calm green and an agitated red-pink) to reflect the current volatility regime.
Trend Strength Meter : A text label (e.g., "TREND: STRONG BULLISH") positioned on the chart, providing an at-a-glance summary of the trend.
Configuration Options
Users can tailor the indicator extensively via the settings panel, with options logically grouped:
Core Analysis Engine : Adjust regression source data, lookback period, and EMA smoothing for the regression line.
Regression Line Visuals : Control visibility, line width, trend-based colors (uptrend, downtrend, flat), slope thresholds for trend definition, strong slope multiplier (for Trend Meter), and color gradient sharpness.
Volatility Channel Configuration : Select band calculation mode (ATR, StdDev, Keltner), set relevant periods and multipliers. Customize colors for vertical gradient fills (upper/lower, top/bottom), border line colors, widths, and the gradient spread factor for fills.
Future Projection Configuration : Toggle visibility, set projection length (number of bars), line style, and colors for projected regression and band areas.
Appearance & Candle Theme : Set default bull/bear candle colors, enable/disable candle heatmap, choose if body color matches heatmap, and configure heatmap gradient target colors (bull, neutral, bear) and the gradient's midpoint.
Background Volatility Pulse : Enable/disable the background effect and configure short/long ATR periods for the volatility calculation.
Trend Strength Meter : Enable/disable the meter, and choose its on-chart position and text size.
Interpretation Notes
-The Regression Line is the primary indicator of trend direction. Its slope and color provide immediate insight.
-The Volatility Bands serve as dynamic support and resistance zones. Price approaching or touching these bands may indicate potential turning points or breakouts. The width of the channel itself reflects market volatility – widening suggests increasing volatility, while narrowing suggests consolidation.
Future Projections are not predictions but rather an extension of current conditions. They can help visualize potential areas where price might interact with projected support/resistance if the current trend and volatility persist.
Candle Heatmap Coloring offers a quick visual assessment of where price is trading within the dynamic envelope, highlighting strength or weakness relative to the channel.
The Background Volatility Pulse gives a contextual feel for overall market agitation or calmness.
This indicator is designed to be a comprehensive analytical tool. Its signals and visualizations are best used in conjunction with other technical analysis techniques, price action study, and robust risk management practices. It is not intended as a standalone trading system.
Risk Disclaimer
Trading and investing in financial markets involve substantial risk of loss and is not suitable for every investor. The Dynamic Volatility Envelope indicator is provided for analytical and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance is not indicative of future results. Always use sound risk management practices and never trade with capital you cannot afford to lose. The developers assume no liability for any financial losses incurred based on the use of this indicator.
Mean-Reversion Indicator_V2_SamleeOverview
This is the second version of my mean reversion indicator. It combines a moving average with adaptive standard deviation bands to detect when the price deviates significantly from its mean. The script provides automatic entry/exit signals, real-time PnL tracking, and shaded trade zones to make mean reversion trading more intuitive.
Core Logic
Mean benchmark: Simple Moving Average (MA).
Volatility bands: Standard deviation of the spread (close − MA) defines upper and lower bands.
Trading rules:
Price breaks below the lower band → Enter Long
Price breaks above the upper band → Enter Short
Price reverts to MA → Exit position
What’s different vs. classic Bollinger/Keltner
Bandwidth is based on the standard deviation of the price–MA spread, not raw closing prices.
Entry signals use previous-bar confirmation to reduce intrabar noise.
Exit rule is a mean-touch condition, rather than fixed profit/loss targets.
Enhanced visualization:
A shaded box dynamically shows the distance between entry and current/exit price, making it easy to see profit/loss zones over the holding period.
Instant PnL labels display current position side (Long/Short/Flat) and live profit/loss in both pips and %.
Entry and exit points are clearly marked on the chart with labels and exact prices.
These visualization tools go beyond what most indicators provide, giving traders a clearer, more practical view of trade evolution.
Key Features
Automatic detection of position status (Long / Short / Flat).
Chart labels for entries (“Entry”) and exits (“Exit”).
Real-time floating PnL calculation in both pips and %.
Info panel (top-right) showing entry price, current price, position side, and PnL.
Dynamic shading between entry and current/exit price to visualize profit/loss zones.
Usage Notes & Risk
Mean reversion may underperform in strong trending markets; parameters (len_ma, len_std, mult) should be validated per instrument and timeframe.
Works best on relatively stable, mean-reverting pairs (e.g., AUDNZD).
Risk management is essential: use independent stop-loss rules (e.g., limit risk to 1–2% of equity per trade).
This script is provided for educational purposes only and is not financial advice.
Multi Scanner Plot & Table V1Here's how to interpret each column in the table:
Price vs MAs:
What it shows: Where the current price is relative to the short-term (e.g., 20-period) and long-term (e.g., 50-period) Simple Moving Averages (SMAs) calculated on your current chart's timeframe.
Interpretation:
Above Both (Green background): Price is above both the short and long MAs. Generally considered a bullish sign for the current trend.
Below Both (Red background): Price is below both MAs. Generally considered a bearish sign.
Mixed (Gray background): Price is between the two MAs (e.g., above the short but below the long, or vice-versa). Indicates indecision or a potential trend change.
RSI Value:
What it shows: The actual numerical value of the Relative Strength Index (RSI) calculated on your current chart's timeframe.
Interpretation: Just the raw RSI number (e.g., 65.32). The background is always gray. You compare this value to standard overbought/oversold levels (like 70/30) or the levels defined in the script's inputs.
RSI Status:
What it shows: Interprets the RSI Value based on the Overbought/Oversold levels set in the script's inputs (default 70/30). Calculated on your current chart's timeframe.
Interpretation:
Overbought (Red background): RSI is above the overbought level (e.g., > 70). Suggests the asset might be due for a pullback or reversal downwards. Red indicates a potentially bearish condition.
Oversold (Green background): RSI is below the oversold level (e.g., < 30). Suggests the asset might be due for a bounce or reversal upwards. Green indicates a potentially bullish condition.
Neutral (Gray background): RSI is between the oversold and overbought levels.
Last Sig Price:
What it shows: The price level where the last "SIG NOW" Buy or Sell signal occurred on your current chart's timeframe.
Interpretation: Helps you see the entry price of the most recent short-term signal generated by this script. The background color matches the signal type: Green for the last Buy signal, Red for the last Sell signal. N/A if no signal has occurred yet.
SIG NOW:
What it shows: This is the main short-term signal generated by the script based on conditions on your current chart's timeframe. It combines the "Price vs MAs" status and specific RSI conditions (price must be above/below both MAs and RSI must be within a certain range defined in the inputs).
Interpretation:
BUY (Green background): The specific buy conditions are met right now. (Price above both MAs AND RSI is strong but not necessarily overbought).
SELL (Red background): The specific sell conditions are met right now. (Price below both MAs AND RSI is weak but not necessarily oversold).
NEUTRAL (Gray background): Neither the Buy nor the Sell conditions are currently met.
ALERT:
What it shows: Flags unusual volume activity on the current bar compared to the recent average volume (calculated on your current chart's timeframe).
Interpretation:
SPIKE (Yellow background, black text): Current volume is significantly higher than the recent average (defined by the Volume Spike Multiplier). Can indicate strong interest or a potential climax.
DUMP (Purple background): Current volume is significantly lower than the recent average (defined by the Volume Dump Multiplier). Can indicate fading interest.
NONE (Gray background): Volume is within the normal range for the lookback period.
SD$:
What it shows: The price level where the last Volume Spike or Dump occurred on your current chart's timeframe.
Interpretation: Shows the price associated with the most recent significant volume event. The background color indicates the type of the last event: Green if the last event was a Spike, Red if the last event was a Dump. N/A if no Spike/Dump has occurred yet.
BB Value (%B):
What it shows: This relates to Bollinger Bands, but specifically calculated on a Higher Timeframe (HTF) that you can set in the inputs (e.g., Daily BBs while viewing an Hourly chart). It shows the Bollinger Band Percent B (%B) value for that HTF. %B measures where the HTF closing price is relative to the HTF upper and lower bands.
Interpretation:
Value > 1: HTF price closed above the HTF upper Bollinger Band.
Value < 0: HTF price closed below the HTF lower Bollinger Band.
Value between 0 and 1: HTF price closed within the HTF Bollinger Bands (e.g., 0.5 is exactly on the middle band).
The background is always gray.
LTS (Long Term Signal):
What it shows: A signal derived only from the Higher Timeframe (HTF) Bollinger Bands.
Interpretation:
BUY (Green background): The HTF price closed above the HTF upper Bollinger Band (see BB Value > 1). Considered a strong bullish signal from the higher timeframe perspective.
SELL (Red background): The HTF price closed below the HTF lower Bollinger Band (see BB Value < 0). Considered a strong bearish signal from the higher timeframe perspective.
NEUTRAL (Gray background): The HTF price closed within the HTF Bollinger Bands.
How to Understand Bollinger Bands and Signals in this Context:
Bollinger Bands are primarily used for the Long Term Signal (LTS) column. This script calculates BBs on a higher timeframe (you choose which one, or it defaults to the chart's timeframe if left blank).
The "LTS" signal triggers:
A BUY when the price on that higher timeframe closes above its upper Bollinger Band. This often indicates strong momentum or a potential breakout.
A SELL when the price on that higher timeframe closes below its lower Bollinger Band. This often indicates strong negative momentum or a potential breakdown.
The "BB Value" column gives you the raw %B number from that same higher timeframe, showing you exactly where the price is relative to the bands (is it just barely above/below, or way outside?).
The script does not directly use Bollinger Bands from the current chart timeframe for the "SIG NOW" or other table signals. The main short-term signals ("SIG NOW") rely on Moving Averages and RSI on the current timeframe. The LTS provides a longer-term perspective using HTF Bollinger Bands.
In summary: Look at the table to quickly gauge:
Short-term trend (Price vs MAs).
Short-term momentum (RSI Status, SIG NOW).
Recent short-term entry points (Last Sig Price).
Current volume anomalies (ALERT).
Long-term strength/weakness based on HTF Bollinger Bands (LTS, BB Value).
Combine these pieces of information to get a more rounded view of the current market conditions according to this specific script's logic.
Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
Extreme Entry with Mean Reversion and Trend FilterThis non-repainting indicator is an improved version of my previous work, a more versatile tool designed to provide traders with dynamic and adaptive entry signals while incorporating a mean reversion and trend filtering mechanism. By combining RSI overbought/oversold, regular divergence and confirmatory momentum oscillator such as CCI or MOM, this indicator generates more precise and timely signals for entering trades.
The indicator offers a comprehensive set of entry conditions for both Buy and Sell entries:
• For Buy entries, it checks for oversold conditions based on RSI levels, and detects bullish divergence patterns while oversold and it identifies upward crossovers in the selected entry signal source (CCI or Momentum).
• Similarly, for Sell entries, it identifies downward crossovers of the CCI or Mom, after the recent overbought conditions, and bearish divergence patterns inside the overbought RSI.
To refine the entry signals even further, the indicator utilizes a mean reversion filter. Traders can choose to display signals that occur inside or outside the upper and lower mean reversion bands:
• Range Entries are indicating potential buying opportunities near the lower band and selling opportunities near the upper band. This is based on the concept of mean reversion, which suggests that prices tend to return to the average when they reach the upper or lower bands. By focusing on these signals, traders can take advantage of price movements that have a higher probability of reversing towards the mean.
• Extreme Entries, on the other hand, represent signals that occur outside of the bands, signaling potential pullbacks during strong trends. By entering positions only at extreme highs or lows, traders can avoid getting caught in the middle of the trend. This approach helps traders capitalize more favorable trading opportunities which have a high reward-risk ratio.
Trend Filter acts as a directional bias for the entry signals. When enabled, long and short entry conditions are filtered based on the relationship between the closing price and the EMA.
Traders have the flexibility to customize, tweak the indicator filter and values in the settings according to their preferences strategies and traded assets, tailoring the signals to their specific needs. The script sets alert conditions to trigger alerts for buy, sell, or both entry signals. This indicator can be used in conjunction with price action or other technical analysis tools for confirmation and better trading decisions.
I created this indicator for my own use, and I share this for informational purposes only. It does not constitute financial advice so use at your own risk and consider your financial situation before making any trading decisions. The indicator's accuracy is not guaranteed, and past performance is not indicative of future results.
I appreciate your feedback on this indicator. As I am new to script development, I am open to comments and suggestions to improve it. If you encounter any issues while using this indicator, please let me know in the comments section. If you find it helpful, I kindly ask for your support in boosting it. Thank you for your cooperation.
Multifactor Buy/Sell Strategy V2 | RSI, MACD, ATR, EMA, Boll.BITGET:1INCHUSDT
This Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
### Input Parameters
The script includes multiple customizable parameters:
- RSI, EMA, MACD parameters — for setting periods and signals of MACD and RSI.
- ATR and Bollinger Bands — used for volatility analysis and level determination.
- Minimum Volatility Threshold — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility dataThis Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
Input Parameters
The script includes multiple customizable parameters:
- **RSI, EMA, MACD parameters** — for setting periods and signals of MACD and RSI.
- **ATR and Bollinger Bands** — used for volatility analysis and level determination.
- **Minimum Volatility Threshold** — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility
- Volatility Status — indicates high or low volatility.
- Bollinger Band Width — current width as a percentage.
- ATR Ratio — ratio of current ATR to long-term average ATR.
This script is suitable for trading in high-volatility conditions, combining multiple filters and factors to generate precise buy and sell signals.
WAP Maverick - (Dual EMA Smoothed VWAP) - [mutantdog]Short Version:
This here is my take on the popular VWAP indicator with several novel features including:
Dual EMA smoothing.
Arithmetic and Harmonic Mean plots.
Custom Anchor feat. Intraday Session Sizes.
2 Pairs of Bands.
Side Input for Connection to other Indicator.
This can be used 'out of the box' as a replacement VWAP, benefitting from smoother transitions and easy-to-use custom alerts.
By design however, this is intended to be a highly customisable alternative with many adjustable parameters and a pseudo-modular input system to connect with another indicator. Well suited for the tweakers around here and those who like to get a little more creative.
I made this primarily for crypto although it should work for other markets. Default settings are best suited to 15m timeframe - the anchor of 1 week is ideal for crypto which often follows a cyclical nature from Monday through Sunday. In 15m, the default ema length of 21 means that the wap comes to match a standard vwap towards the end of Monday. If using higher chart timeframes, i recommend decreasing the ema length to closely match this principle (suggested: for 1h chart, try length = 8; for 4h chart, length = 2 or 3 should suffice).
Note: the use of harmonic mean calculations will cause problems on any data source incorporating both positive and negative values, it may also return unusable results on extremely low-value charts (eg: low-sat coins in /btc pairs).
Long version:
The development of this project was one driven more by experimentation than a specific end-goal, however i have tried to fine-tune everything into a coherent usable end-product. With that in mind then, this walkthrough will follow something of a development chronology as i dissect the various functions.
DUAL-EMA SMOOTHING
At its core this is based upon / adapted from the standard vwap indicator provided by TradingView although I have modified and changed most of it. The first mod is the dual ema smoothing. Rather than simply applying an ema to the output of the standard vwap function, instead i have incorporated the ema in a manner analogous to the way smas are used within a standard vwma. Sticking for now with the arithmetic mean, the basic vwap calculation is simply sum(source * volume) / sum(volume) across the anchored period. In this case i have simply applied an ema to each of the numerator and denominator values resulting in ema(sum(source * volume)) / ema(sum(volume)) with the ema length independent of the anchor. This results in smoother (albeit slower) transitions than the aforementioned post-vwap method. Furthermore in the case when anchor period is equal to current timeframe, the result is a basic volume-weighted ema.
The example below shows a standard vwap (1week anchor) in blue, a 21-ema applied to the vwap in purple and a dual-21-ema smoothed wap in gold. Notably both ema types come to effectively resemble the standard vwap after around 24 hours into the new anchor session but how they behave in the meantime is very different. The dual-ema transitions quite gradually while the post-vwap ema immediately sets about trying to catch up. Incidentally. a similar and slower variation of the dual-ema can be achieved with dual-rma although i have not included it in this indicator, attempted analogues using sma or wma were far less useful however.
STANDARD DEVIATION AND BANDS
With this updated calculation, a corresponding update to the standard deviation is also required. The vwap has its own anchored volume-weighted st.dev but this cannot be used in combination with the ema smoothing so instead it has been recalculated appropriately. There are two pairs of bands with separate multipliers (stepped to 0.1x) and in both cases high and low bands can be activated or deactivated individually. An example usage for this would be to create different upper and lower bands for profit and stoploss targets. Alerts can be set easily for different crossing conditions, more on this later.
Alongside the bands, i have also added the option to shift ('Deviate') the entire indicator up or down according to a multiple of the corrected st.dev value. This has many potential uses, for example if we want to bias our analysis in one direction it may be useful to move the wap in the opposite. Or if the asset is trading within a narrow range and we are waiting on a breakout, we could shift to the desired level and set alerts accordingly. The 'Deviate' parameter applies to the entire indicator including the bands which will remain centred on the main WAP.
CUSTOM (W)ANCHOR
Ever thought about using a vwap with anchor periods smaller than a day? Here you can do just that. I've removed the Earnings/Dividends/Splits options from the basic vwap and added an 'Intraday' option instead. When selected, a custom anchor length can be created as a multiple of minutes (default steps of 60 mins but can input any value from 0 - 1440). While this may not seem at first like a useful feature for anyone except hi-speed scalpers, this actually offers more interesting potential than it appears.
When set to 0 minutes the current timeframe is always used, turning this into the basic volume-weighted ema mentioned earlier. When using other low time frames the anchor can act as a pre-ema filter creating a stepped effect akin to an adaptive MA. Used in combination with the bands, the result is a kind of volume-weighted adaptive exponential bollinger band; if such a thing does not already exist then this is where you create it. Alternatively, by combining two instances you may find potential interesting crosses between an intraday wap and a standard timeframe wap. Below is an example set to intraday with 480 mins, 2x st.dev bands and ema length 21. Included for comparison in purple is a standard 21 ema.
I'm sure there are many potential uses to be found here, so be creative and please share anything you come up with in the comments.
ARITHMETIC AND HARMONIC MEAN CALCULATIONS
The standard vwap uses the arithmetic mean in its calculation. Indeed, most mean calculations tend to be arithmetic: sma being the most widely used example. When volume weighting is involved though this can lead to a slight bias in favour of upward moves over downward. While the effect of this is minor, over longer anchor periods it can become increasingly significant. The harmonic mean, on the other hand, has the opposite effect which results in a value that is always lower than the arithmetic mean. By viewing both arithmetic and harmonic waps together, the extent to which they diverge from each other can be used as a visual reference of how much price has changed during the anchored period.
Furthermore, the harmonic mean may actually be the more appropriate one to use during downtrends or bearish periods, in principle at least. Consider that a short trade is functionally the same as a long trade on the inverse of the pair (eg: selling BTC/USD is the same as buying USD/BTC). With the harmonic mean being an inverse of the arithmetic then, it makes sense to use it instead. To illustrate this below is a snapshot of LUNA/USDT on the left with its inverse 1/(LUNA/USDT) = USDT/LUNA on the right. On both charts is a wap with identical settings, note the resistance on the left and its corresponding support on the right. It should be easy from this to see that the lower harmonic wap on the left corresponds to the upper arithmetic wap on the right. Thus, it would appear that the harmonic mean should be used in a downtrend. In principle, at least...
In reality though, it is not quite so black and white. Rarely are these values exact in their predictions and the sort of range one should allow for inaccuracies will likely be greater than the difference between these two means. Furthermore, the ema smoothing has already introduced some lag and thus additional inaccuracies. Nevertheless, the symmetry warrants its inclusion.
SIDE INPUT & ALERTS
Finally we move on to the pseudo-modular component here. While TradingView allows some interoperability between indicators, it is limited to just one connection. Any attempt to use multiple source inputs will remove this functionality completely. The workaround here is to instead use custom 'string' input menus for additional sources, preserving this function in the sole 'source' input. In this case, since the wap itself is dependant only price and volume, i have repurposed the full 'source' into the second 'side' input. This allows for a separate indicator to interact with this one that can be used for triggering alerts. You could even use another instance of this one (there is a hidden wap:mid plot intended for this use which is the midpoint between both means). Note that deleting a connected indicator may result in the deletion of those connected to it.
Preset alertconditions are available for crossings of the side input above and below the main wap, alongside several customisable alerts with corresponding visual markers based upon selectable conditions. Alerts for band crossings apply only to those that are active and only crossings of the type specified within the 'crosses' subsection of the indicator settings. The included options make it easy to create buy alerts specific to certain bands with sell alerts specific to other bands. The chart below shows two instances with differing anchor periods, both are connected with buy and sell alerts enabled for visible bands.
Okay... So that just about covers it here, i think. As mentioned earlier this is the product of various experiments while i have been learning my way around PineScript. Some of those experiments have been branched off from this in order to not over-clutter it with functions. The pseudo-modular design and the 'side' input are the result of an attempt to create a connective framework across various projects. Even on its own though, this should offer plenty of tweaking potential for anyone who likes to venture away from the usual standards, all the while still retaining its core purpose as a traders tool.
Thanks for checking this out. I look forward to any feedback below.
Rolling VWAP LevelsRolling VWAP Levels Indicator
Overview
Dynamic horizontal lines showing rolling Volume Weighted Average Price (VWAP) levels for multiple timeframes (7D, 30D, 90D, 365D) that update in real-time as new bars form.
Who This Is For
Day traders using VWAP as support/resistance
Swing traders analyzing multi-timeframe price structure
Scalpers looking for mean reversion entries
Options traders needing volatility bands for strike selection
Institutional traders tracking volume-weighted fair value
Risk managers requiring dynamic stop levels
How To Trade With It
Mean Reversion Strategies:
Buy when price is below VWAP and showing bullish divergence
Sell when price is above VWAP and showing bearish signals
Use multiple timeframes - enter on shorter, confirm on longer
Target opposite VWAP level for profit taking
Breakout Trading:
Watch for price breaking above/below key VWAP levels with volume
Use 7D VWAP for intraday breakouts
Use 30D/90D VWAP for swing trade breakouts
Confirm breakout with move beyond first standard deviation band
Support/Resistance Trading:
VWAP levels act as dynamic support in uptrends
VWAP levels act as dynamic resistance in downtrends
Multiple timeframe VWAP confluence creates stronger levels
Use standard deviation bands as additional S/R zones
Risk Management:
Place stops beyond next VWAP level
Use standard deviation bands for position sizing
Exit partial positions at VWAP levels
Monitor distance table for overextended moves
Key Features
Real-time Updates: Lines move and extend as new bars form
Individual Styling: Custom colors, widths, styles for each timeframe
Standard Deviation Bands: Optional volatility bands with custom multipliers
Smart Labels: Positioned above, below, or diagonally relative to lines
Distance Table: Shows percentage distance from each VWAP level
Alert System: Get notified when price crosses VWAP levels
Memory Efficient: Automatically cleans up old drawing objects
Settings Explained
Display Group: Show/hide labels, font size, line transparency, positioning
Individual VWAP Groups: Color, line width (1-5), line style for each timeframe
Standard Deviation Bands: Enable bands with custom multipliers (0.5, 1.0, 1.5, 2.0, etc.)
Labels Group: Position (8 options including diagonal), custom text, price display
Additional Info: Distance table, alert conditions
Technical Implementation
Uses rolling arrays to maintain sliding windows of price*volume data. The core calculation function processes both VWAP and standard deviation efficiently. Lines are created dynamically and updated every bar. Memory management prevents object accumulation through automatic cleanup.
Best Practices
Start with 7D and 30D VWAP for most strategies
Add 90D/365D for longer-term context
Use standard deviation bands when volatility matters
Position labels to avoid chart clutter
Enable distance table during high volatility periods
Set alerts for key VWAP level breaks
Market Applications
Forex: Major pairs during London/NY sessions
Stocks: Large cap names with good volume
Crypto: Bitcoin, Ethereum, major altcoins
Futures: ES, NQ, CL, GC with continuous volume
Options: Use SD bands for strike selection and volatility assessment
Green*DiamondGreen*Diamond (GD1)
Unleash Dynamic Trading Signals with Volatility and Momentum
Overview
GreenDiamond is a versatile overlay indicator designed for traders seeking actionable buy and sell signals across various markets and timeframes. Combining Volatility Bands (VB) bands, Consolidation Detection, MACD, RSI, and a unique Ribbon Wave, it highlights high-probability setups while filtering out noise. With customizable signals like Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, plus vibrant candle and volume visuals, GreenDiamond adapts to your trading style—whether you’re scalping, day trading, or swing trading.
Key Features
Volatility Bands (VB): Plots dynamic upper and lower bands to identify breakouts or reversals, with toggleable buy/sell signals outside consolidation zones.
Consolidation Detection: Marks low-range periods to avoid choppy markets, ensuring signals fire during trending conditions.
MACD Signals: Offers flexible buy/sell conditions (e.g., cross above signal, above zero, histogram up) with RSI divergence integration for precision.
RSI Filter: Enhances signals with customizable levels (midline, oversold/overbought) and bullish divergence detection.
Ribbon Wave: Visualizes trend strength using three EMAs, colored by MACD and RSI for intuitive momentum cues.
Custom Signals: Includes Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, with limits on consecutive signals to prevent overtrading.
Candle & Volume Styling: Blends MACD/RSI colors on candles and scales volume bars to highlight momentum spikes.
Alerts: Set up alerts for VB signals, MACD crosses, Green*Diamond signals, and custom conditions to stay on top of opportunities.
How It Works
Green*Diamond integrates multiple indicators to generate signals:
Volatility Bands: Calculates bands using a pivot SMA and standard deviation. Buy signals trigger on crossovers above the lower band, sell signals on crossunders below the upper band (if enabled).
Consolidation Filter: Suppresses signals when candle ranges are below a threshold, keeping you out of flat markets.
MACD & RSI: Combines MACD conditions (e.g., cross above signal) with RSI filters (e.g., above midline) and optional volume spikes for robust signals.
Custom Logic: Green-Yellow Buy uses MACD bullishness, Pullback Sell targets retracements, and Inverse Pullback Buy catches reversals after downmoves—all filtered to avoid consolidation.
Visuals: Ribbon Wave shows trend direction, candles blend momentum colors, and volume bars scale dynamically to confirm signals.
Settings
Volatility Bands Settings:
VB Lookback Period (20): Adjust to 10–15 for faster markets (e.g., 1-minute scalping) or 25–30 for daily charts.
Upper/Lower Band Multiplier (1.0): Increase to 1.5–2.0 for wider bands in volatile stocks like AEHL; decrease to 0.5 for calmer markets.
Show Volatility Bands: Toggle off to reduce chart clutter.
Use VB Signals: Enable for breakout-focused trades; disable to focus on Green*Diamond signals.
Consolidation Settings:
Consolidation Lookback (14): Set to 5–10 for small caps (e.g., AEHL) to catch quick consolidations; 20 for higher timeframes.
Range Threshold (0.5): Lower to 0.3 for stricter filtering in choppy markets; raise to 0.7 for looser signals.
MACD Settings:
Fast/Slow Length (12/26): Shorten to 8/21 for scalping; extend to 15/34 for swing trading.
Signal Smoothing (9): Reduce to 5 for faster signals; increase to 12 for smoother trends.
Buy/Sell Signal Options: Choose “Cross Above Signal” for classic MACD; “Histogram Up” for momentum plays.
Use RSI Div + MACD Cross: Enable for high-probability reversal signals.
RSI Settings:
RSI Period (14): Drop to 10 for 1-minute charts; raise to 20 for daily.
Filter Level (50): Set to 55 for stricter buys; 45 for sells.
Overbought/Oversold (70/30): Tighten to 65/35 for small caps; widen to 75/25 for indices.
RSI Buy/Sell Options: Select “Bullish Divergence” for reversals; “Cross Above Oversold” for momentum.
Color Settings:
Adjust bullish/bearish colors for visibility (e.g., brighter green/red for dark themes).
Border Thickness (1): Increase to 2–3 for clearer candle outlines.
Volume Settings:
Volume Average Length (20): Shorten to 10 for scalping; extend to 30 for swing trades.
Volume Multiplier (2.0): Raise to 3.0 for AEHL’s volume surges; lower to 1.5 for steady stocks.
Bar Height (10%): Increase to 15% for prominent bars; decrease to 5% to reduce clutter.
Ribbon Settings:
EMA Periods (10/20/30): Tighten to 5/10/15 for scalping; widen to 20/40/60 for trends.
Color by MACD/RSI: Disable for simpler visuals; enable for dynamic momentum cues.
Gradient Fill: Toggle on for trend clarity; off for minimalism.
Custom Signals:
Enable Green-Yellow Buy: Use for momentum confirmation; limit to 1–2 signals to avoid spam.
Pullback/Inverse Pullback % (50): Set to 30–40% for small caps; 60–70% for indices.
Max Buy Signals (1): Increase to 2–3 for active markets; keep at 1 for discipline.
Tips and Tricks
Scalping Small Caps (e.g., AEHL):
Use 1-minute charts with VB Lookback = 10, Consolidation Lookback = 5, and Volume Multiplier = 3.0 to catch $0.10–$0.20 moves.
Enable Green-Yellow Buy and Inverse Pullback Buy for quick entries; disable VB Signals to focus on Green*Diamond logic.
Pair with SMC+ green boxes (if you use them) for reversal confirmation.
Day Trading:
Try 5-minute charts with MACD Fast/Slow = 8/21 and RSI Period = 10.
Enable RSI Divergence + MACD Cross for high-probability setups; set Max Buy Signals = 2.
Watch for volume bars turning yellow to confirm entries.
Swing Trading:
Use daily charts with VB Lookback = 30, Ribbon EMAs = 20/40/60.
Enable Pullback Sell (60%) to exit after rallies; disable RSI Color for cleaner candles.
Check Ribbon Wave gradient for trend strength—bright green signals strong bulls.
Avoiding Noise:
Increase Consolidation Threshold to 0.7 on volatile days to skip false breakouts.
Disable Ribbon Wave or Volume Bars if the chart feels crowded.
Limit Max Buy Signals to 1 for disciplined trading.
Alert Setup:
In TradingView’s Alerts panel, select:
“GD Buy Signal” for standard entries.
“RSI Div + MACD Cross Buy” for reversals.
“VB Buy Signal” for breakout plays.
Set to “Once Per Bar Close” for confirmed signals; “Once Per Bar” for scalping.
Backtesting:
Replay on small caps ( Float < 5M, Price $0.50–$5) to test signals.
Focus on “GD Buy Signal” with yellow volume bars and green Ribbon Wave.
Avoid signals during gray consolidation squares unless paired with RSI Divergence.
Usage Notes
Markets: Works on stocks, forex, crypto, and indices. Best for volatile assets (e.g., small-cap stocks, BTCUSD).
Timeframes: Scalping (1–5 minutes), day trading (15–60 minutes), or swing trading (daily). Adjust settings per timeframe.
Risk Management: Combine with stop-losses (e.g., 1% risk, $0.05 below AEHL entry) and take-profits (3–5%).
Customization: Tweak inputs to match your strategy—experiment in replay to find your sweet spot.
Disclaimer
Green*Diamond is a technical tool to assist with trade identification, not a guarantee of profits. Trading involves risks, and past performance doesn’t predict future results. Always conduct your own analysis, manage risk, and test settings before live trading.
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Love Green*Diamond? Found a killer setup?
Advanced Trend and Volatility Indicator with Alerts by ZaimonThis script presents a comprehensive analytical tool that integrates multiple technical indicators to provide a holistic view of market trends and volatility. By uniquely combining Moving Averages (MA), Relative Strength Index (RSI), Stochastic Oscillator, Bollinger Bands, and Average True Range (ATR), it offers nuanced insights into price movements and helps identify potential trading opportunities.
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### **Key Features and Integration:**
1. **Moving Averages (MA20 & MA50):**
- **Trend Identification:**
- **Methodology:** Calculates two Simple Moving Averages—MA20 (short-term) and MA50 (long-term).
- **Bullish Trend:** When MA20 crosses above MA50, indicating upward momentum.
- **Bearish Trend:** When MA20 crosses below MA50, signaling downward momentum.
- **Golden Cross & Death Cross Alerts:**
- **Golden Cross:** MA20 crossing above MA50 generates a bullish alert and visual symbol.
- **Death Cross:** MA20 crossing below MA50 triggers a bearish alert and visual symbol.
- **Integration:**
- Serves as the foundational trend indicator, influencing interpretations of other indicators within the script.
2. **Relative Strength Index (RSI):**
- **Momentum Measurement:**
- **Methodology:** Calculates RSI to assess the speed and change of price movements over a 14-period length.
- **Overbought/Oversold Conditions:** Customizable thresholds set at 70 (overbought) and 30 (oversold).
- **Alerts:**
- Generates alerts when RSI crosses above or below the specified thresholds.
- **Integration:**
- Confirms trend strength identified by MAs.
- Overbought/Oversold signals can precede potential trend reversals, especially when aligned with MA crossovers.
3. **Stochastic Oscillator:**
- **Momentum and Reversal Signals:**
- **Methodology:** Uses %K and %D lines to evaluate price momentum relative to high-low range over recent periods.
- **Bullish Signal:** %K crossing above %D in oversold territory (below 20).
- **Bearish Signal:** %K crossing below %D in overbought territory (above 80).
- **Alerts:**
- Provides alerts on bullish and bearish crossovers in extreme regions.
- **Integration:**
- Enhances RSI signals by providing additional momentum confirmation.
- When both RSI and Stochastic indicate overbought/oversold conditions, it strengthens the likelihood of a reversal.
4. **Bollinger Bands:**
- **Volatility Visualization:**
- **Methodology:** Plots upper and lower bands based on standard deviations from a moving average (BB Basis).
- **Dynamic Support/Resistance:** Prices touching or exceeding the bands may indicate potential reversals.
- **Integration:**
- Works with RSI and Stochastic to identify overextended price movements.
- Helps in assessing volatility alongside trend and momentum indicators.
5. **Average True Range (ATR):**
- **Volatility Assessment:**
- **Methodology:** Calculates ATR over a 14-period length to measure market volatility.
- **ATR Bands:** Plots upper and lower bands relative to the current price using an ATR multiplier.
- **Integration:**
- Assists in setting stop-loss and take-profit levels based on current volatility.
- Complements Bollinger Bands for a comprehensive volatility analysis.
6. **Information Table:**
- **Real-Time Data Display:**
- Shows current values of MA20, MA50, RSI, Stochastic %K and %D, BB Basis, ATR, and Trend Status.
- **Trend Status Indicator:**
- Displays "Bullish," "Bearish," or "Sideways" based on MA conditions.
- **Integration:**
- Provides a consolidated view for quick decision-making without analyzing individual indicators separately.
7. **Periodic Labels:**
- **Enhanced Visibility:**
- Adds labels every 50 bars showing RSI and Stochastic values.
- **Integration:**
- Helps track momentum changes over time and spot longer-term patterns.
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### **How the Components Work Together:**
- **Synergistic Analysis:**
- **Trend Confirmation:** MA crossovers establish the primary trend, while RSI and Stochastic confirm momentum within that trend.
- **Volatility Context:** Bollinger Bands and ATR provide context on market volatility, refining entry and exit points suggested by trend and momentum indicators.
- **Signal Strength:** Concurrent signals from multiple indicators increase confidence in trading decisions.
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### **Usage Guidelines:**
1. **Trend Analysis:**
- **Identify Trend Direction:**
- Observe MA20 and MA50 crossovers.
- Refer to the Trend Status in the information table.
- **Confirm with Momentum Indicators:**
- Ensure RSI and Stochastic support the identified trend.
2. **Entry and Exit Points:**
- **Overbought/Oversold Conditions:**
- Look for RSI and Stochastic reaching extreme levels.
- Consider entering positions when oversold in a bullish trend or overbought in a bearish trend.
- **Bollinger Band Interactions:**
- Use price interactions with Bollinger Bands to identify potential reversal zones.
3. **Risk Management:**
- **ATR-Based Levels:**
- Set stop-loss and take-profit levels using ATR bands to account for current volatility.
- **Adjusting to Volatility:**
- Modify position sizes and targets based on Bollinger Band width and ATR values.
4. **Alerts Setup:**
- **Customize Alert Thresholds:**
- Configure alerts for MA crossovers, RSI levels, and Stochastic crossovers according to your trading strategy.
- **Stay Informed:**
- Use alerts to monitor key events without constant chart observation.
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### **Customization:**
- **Flexible Parameters:**
- All indicator lengths, thresholds, and settings are adjustable to suit different trading styles and timeframes.
- **Adjustable Visuals:**
- Modify plot colors, line styles, and label positions to enhance chart readability.
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### **Originality and Value Addition:**
This script differentiates itself by:
- **Integrated Approach:**
- Seamlessly combining multiple indicators to provide a more comprehensive analysis than using each indicator separately.
- **Enhanced Visualization:**
- Utilizing plots, fills, labels, and an information table to present data intuitively.
- **User-Friendly Features:**
- Pre-configured alerts and real-time data displays reduce the need for manual monitoring.
By explaining how each component interacts and contributes to the overall analysis, the script adds substantial value to traders seeking a multi-faceted tool for market analysis.
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### **Additional Notes:**
- **Learning Resource:**
- The script is well-commented, serving as an educational tool for those learning Pine Script and technical analysis integration.
- **Further Enhancements:**
- Opportunities exist to incorporate additional indicators like MACD or ADX, and to develop advanced alert logic, such as RSI or Stochastic divergences.
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### **Disclaimer:**
- **Educational Purpose Only:**
- This script is provided for informational purposes and should not be construed as financial advice.
- **Risk Acknowledgment:**
- Trading involves significant risk; past performance is not indicative of future results.
- **Due Diligence:**
- Users should conduct their own analysis and consider consulting a financial professional before making trading decisions.
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By providing detailed explanations of the methodologies and the synergistic use of multiple indicators, this script aligns with TradingView's guidelines for originality and usefulness. It offers traders a unique tool that enhances market analysis through the thoughtful integration of technical indicators.
