Rma Stdev BandsStandard Deviation support resistances with percent boxes.
The Relative Moving Average isn’t a well-known moving average. But TradingView uses this average with two popular indicators: the Relative Strength Index (RSI) and Average True Range (ATR)
The weighting factors that the Relative Moving Average uses decrease exponentially. That way recent bars have the highest weight, while earlier bars get smaller weights the older they are.
Search in scripts for "bands"
Bollinger Bands with momentum SMA'sA useful tool to look for add on opportunities. The settiing are such that 4Hr shows a Bollinger band for the daily TF. That's the settings to get a higher time frame picture but with a lower time frame focus
CPR PIVOT, 2ST, 5MA, VWAPSUPERTREND
2 supertrend with diffrent patameters.
MOVING AVERAGE RIBBON
5 differenT EMA
VWAP
Simple vwap with bands nothing special
every parameters and looks can be change
AND CPR
BANDSTrend indicator. It is based on a simple moving average, the maximum and minimum of this moving average for the period. When the moving average coincides with its maximum for the period , the trend is rising, when the moving average coincides with its minimum for the period, the trend is falling. The optimal periods should be selected for each timeframe and trading instrument.
Big Candle Touches Bollinger BandWhat It Does:
This indicator helps you spot important trading signals by combining Bollinger Bands with big candles.
Key Features:
Bollinger Bands: These bands show the average price (middle band) and the range of price movement (upper and lower bands) over a set period. The bands widen when prices are more volatile and narrow when they are less volatile.
Big Candle Detection: A "big candle" is a candle that has a larger body compared to the average price movement over a period. This is determined using the Average True Range (ATR), which measures market volatility.
How It Works:
Detects Big Candles: It checks if a candle’s body (the difference between its open and close prices) is bigger than usual, based on a multiplier of the ATR.
Touching Bollinger Bands: It looks for candles that touch or cross the upper or lower Bollinger Bands.
Highlights Important Signals:
Sell Signal: When a big candle touches the upper Bollinger Band, it marks it as a "Sell" signal with a red label.
Buy Signal: When a big candle touches the lower Bollinger Band, it marks it as a "Buy" signal with a green label.
Alerts:
You'll get alerts when a big candle touches the upper or lower Bollinger Bands, so you don’t miss these potential trading opportunities.
Visuals:
Bollinger Bands: Shown as three lines on the chart — the upper band (red), the lower band (green), and the middle band (blue).
Labels: Red labels for sell signals and green labels for buy signals when a big candle touches the bands.
This indicator helps you identify potential trading opportunities by focusing on significant price movements and how they interact with the Bollinger Bands.
MA Rainbow-AYNETSummary of the "MA Rainbow"
The 200 MA Rainbow script creates a visually appealing representation of multiple moving averages (MAs) with varying lengths and colors to provide insights into price trends and market momentum.
Key Features:
Base Moving Average:
A starting point (ma_length, default 200) is used as the foundation for all other bands.
Rainbow Bands:
The script generates multiple moving averages (bands) with increasing lengths, spaced by a user-defined band_spacing multiplier.
The number of bands is controlled by rainbow_bands, allowing up to 7 bands.
Moving Average Types:
Users can select the MA type: Simple (SMA), Exponential (EMA), or Weighted (WMA).
Dynamic Colors:
Each band is assigned a unique color from a predefined rainbow palette, making the chart visually distinct.
Inputs for Customization:
ma_length: Adjust the base period of the moving average.
rainbow_bands: Set the number of bands to display.
band_spacing: Control the spread between bands.
How It Works:
Precomputing Bands:
Each band’s length is calculated based on the base length (ma_length) and a multiplier (band_spacing).
For example, if ma_length = 200 and band_spacing = 0.2, the lengths of the first 3 bands will be:
Band 1: 200
Band 2: 240
Band 3: 280
Global Plotting:
Each band’s moving average is precomputed using the selected type (SMA, EMA, or WMA).
Bands are plotted globally to avoid scope issues, ensuring compatibility with Pine Script rules.
Color Cycling:
Colors are assigned dynamically from a rainbow palette (red, orange, yellow, green, blue, purple, teal).
Use Case:
The 200 MA Rainbow helps traders:
Visualize market trends with multiple layers of moving averages.
Identify areas of support and resistance.
Gauge momentum through the spread and alignment of bands.
Customization:
Users can:
Change the base moving average length (ma_length).
Adjust the number of bands (rainbow_bands).
Control the spread between bands with band_spacing.
Select the moving average type (SMA, EMA, WMA).
Application:
Copy the script into the Pine Editor in TradingView.
Apply it to your chart to observe the Rainbow MA visualization.
Adjust inputs to match your trading style or strategy.
This script is a versatile tool for both beginner and advanced traders, providing a colorful way to track price trends and market conditions. 🌈
2Mars - MA / BB / SuperTrend
The 2Mars strategy is a trading approach that aims to improve trading efficiency by incorporating several simple order opening tactics. These tactics include moving average crossovers, Bollinger Bands, and SuperTrend.
Entering a Position with the 2Mars Strategy:
Moving Average Crossover: This method considers the crossing of moving averages as a signal to enter a position.
Price Crossing Bollinger Bands: If the price crosses either the upper or lower Bollinger Band, it is seen as a signal to enter a position.
Price Crossing Moving Average: If the price crosses the moving average, it is also considered a signal to enter a position.
SuperTrend and Bars confirm:
The SuperTrend indicator is used to provide additional confirmation for entering positions and setting stop loss levels. "Bars confirm" is used only for entry to positions.
Moving Average Crossover Strategy:
A moving average crossover refers to the point on a chart where there is a crossover of the signal or fast moving average, above or below the basis or slow moving average. This strategy also uses moving averages for additional orders #3.
Basis Moving Average Length: Ratio * Multiplier
Signal Moving Average Length: Multiplier
Bollinger Bands:
Bollinger Bands consist of three bands: an upper band, a lower band, and a basis moving average. However, the 2Mars strategy incorporates multiple upper and lower levels for position entry and take profit.
Basis +/- StdDev * 0.618
Basis +/- StdDev * 1.618
Basis +/- StdDev * 2.618
Additional Orders:
Additional Order #1 and #2: closing price crosses above or below the Bollinger Bands.
Additional Order #3: closing price crosses above or below the basis or signal moving average.
Take Profit:
The strategy includes three levels for taking profits, which are based on the Bollinger Bands. Additionally, a percentage of the position can be chosen to close long or short positions.
Limit Orders:
The strategy allows for entering a position using a limit order. The calculation for the limit order involves the Average True Range (ATR) for a specific period.
For long positions: Low price - ATR * Multiplier
For short positions: High price + ATR * Multiplier
Stop Loss:
To manage risk, the strategy recommends using stop loss options. The stop loss is updated with each entry order and take-profit level 3. When using the SuperTrend Confirmation, the stop loss requires confirmation of a trend change. It allows for flexible adjustment of the stop loss when the trend changes.
There are three options for setting the stop loss:
1. ATR (Average True Range):
For long positions: Low price - ATR * Long multiplier
For short positions: High price + ATR * Short multiplier
2. SuperTrend + ATR:
For long positions: SuperTrend - ATR * Long multiplier
For short positions: SuperTrend + ATR * Short multiplier
3. StdDev:
For long positions: StdDev - ATR * Long multiplier
For short positions: StdDev + ATR * Short multiplier
Flexible Stop Loss:
There is also a flexible stop loss option for the ATR and StdDev methods. It is triggered when the SuperTrend or moving average trend changes unfavorably.
For long positions: Stop-loss price + (ATR * Long multiplier) * Multiplier
For short positions: Stop-loss price - (ATR * Short multiplier) * Multiplier
How configure:
Disable SuperTrend, take profit, stop loss, additional orders and begin setting up a strategy.
Pick soucre data
Number of bars for confirm
Pick up the ratio of the base moving average and the signal moving average.
Set up a SuperTrend
Time for set up of the Bollinger Bands and the take profit
And finaly set up of stop loss and limit orders
All done!
For OKX exchange:
WaveTrend Dynamic (Lazy Bear Style)█ OVERVIEW
The WaveTrend Dynamic indicator (in the style of Lazy Bear) is an advanced tool based on the Exponential Smoothing Average (ESA), which adapts to the volatility and price of a financial instrument. It is more flexible than the classic WaveTrend but shares a similar concept of bands around a main oscillator line.
The indicator uses dynamic bands calculated as distances from the ESA, with their width adjustable via the "level" parameter. This allows it to be tailored to various markets, timeframes, and volatility conditions, making it easier to identify trends, reversal points, and buy/sell signals.
█ CONCEPTS
The WaveTrend Dynamic combines oscillator functions with trend analysis. Below, we explain the key components in a simple way, understandable even for beginner users.
Core Calculations
The indicator relies on the adaptive ESA and a few straightforward steps:
1 — ESA (Adaptive Average): Calculated as a smoothed average of the price (from high, low, and close, or HLC3) using the ESA Length parameter (default: 10). This number determines how many past candles are considered in the calculation. The ESA quickly responds to price changes, helping to track trends.
2 — Deviation (D): Measures how much the price deviates from the ESA, factoring in market volatility. This allows the indicator to adapt to different instruments.
3 — Price Distance Indicator (CI): Shows how far the price is from the ESA relative to market volatility. This forms the basis for the main indicator line, reacting to price movements.
4 — WT1 (WaveTrend 1): The main line, smoothing the Price Distance Indicator (CI) with the Average Length parameter (default: 21). It reflects the direction of price movement and momentum.
5 — WT2 (WaveTrend 2): A signal line that further smooths WT1 (with a period of 4). It helps confirm signals through crossovers with WT1.
6 — Bands (UpperBand and LowerBand): These form a dynamic channel around the ESA. Their width depends on the level parameter (default: 100). Wider bands result in fewer but more reliable signals. In the original WaveTrend, the oscillator bands use lower values, such as 50 or 60. To achieve classic oscillator signals (more frequent WT1/WT2 crossovers outside the bands), set the level to 50–60.
Trend Identification
The indicator identifies two types of trends:
• Major Trend: Determined by the position of WT1 relative to the ESA. When WT1 is above the ESA, it indicates a bullish trend. When below, it signals a bearish trend. Line and fill colors reflect this trend.
• Mini-Trend: Based on WT1 and WT2 crossovers. When the lines cross, they change to the same color, signaling short-term changes or reversal points. This is ideal for quick trading decisions.
Visuals and Effects
• WT1 and WT2 Lines: Scaled to price and displayed on the price chart for easier analysis.
• Fills: Between the bands (UpperBand/LowerBand) and between WT1/WT2, with a "wave" effect that adjusts transparency based on the trend (green for bullish, red for bearish).
• Signals: Three types—return-to-band, WT1/WT2 crossovers outside the bands, and crossovers inside the bands. Signals are displayed as triangles with different colors for buy and sell.
█ FEATURES
Detailed features of the indicator, aligned with the order of settings in the script:
• Basic Parameters: ESA Length — controls ESA smoothing; Average Length — affects WT1 responsiveness; level (WT Level) — adjusts band width for signal filtering.
• Display Elements: Options to show/hide ESA, bands, WT1/WT2; customizable colors for lines, fills, and the wave effect.
• Signals: Three signal groups (return-to-band, crossovers outside bands, crossovers inside bands) with display and color customization options.
█ HOW TO USE
1 — Add the indicator to your TradingView chart and adjust parameters: — Increase ESA Length and Average Length for low-volatility markets (e.g., stocks), or decrease for cryptocurrencies or forex. — Set level to 50–60 for classic WaveTrend signals with WT1/WT2 crossovers outside bands. The default value of 100 creates wider bands and fewer signals.
2 — Analyze trends: — Major trend (WT1 vs. ESA) shows the overall market direction. — Mini-trends (WT1/WT2 crossovers) help time short-term entries.
3 — Use signals: — Return-to-band: Buy at the lower band, sell at the upper band (mean-reversion). — Crossovers outside bands: Indicate strong momentum (with a lower level, e.g., 50). — Crossovers inside bands: Signal weaker trend changes.
4 — Combine with other tools: Use with volume, RSI, or support/resistance for better decisions. Test on historical data to optimize settings.
Candle Channel█ OVERVIEW
The "Candle Channel" indicator is a versatile technical analysis tool that plots a price channel based on the Simple Moving Average (SMA) of candlestick midpoints. The channel bands, calculated based on candlestick volatility, form dynamic support and resistance levels that adapt to price movements. The script generates signals for reversals from the bands and SMA breakouts, making it useful for both short-term and long-term traders. By adjusting the SMA length, the channel can vary in nature—from a wide channel encapsulating price movement to narrower support/resistance or trend-following bands. The channel width can be further customized using a scaling parameter, allowing adaptation to different trading styles and markets.
█ MECHANISM
Band Calculation
The indicator is based on the following calculations:
Candlestick Midpoint: Calculated as the arithmetic average of the candle’s high and low prices: (high + low) / 2.
Simple Moving Average (SMA): The average of candlestick midpoints over a specified length (default: 20 candles), forming the channel’s centerline.
Average Candle Height: Calculated as the average difference between the high and low prices (high - low) over the same SMA length, serving as a measure of market volatility.
Band Scaling: The user specifies a percentage of the average candle height (default: 200%), which is multiplied by the average height to create an offset. The upper band is SMA + offset, and the lower band is SMA - offset.Example: For an average candle height of 10 points and 200% scaling, the offset is 20 points, meaning the bands are ±20 points from the SMA.
Channel Characteristics: The SMA length determines the channel’s dynamics. Shorter SMA values (10–30) create a wide channel that contains price movement, ideal for scalping or short-term trading. Longer SMA values (above 30, e.g., 50–100) transform the channel into narrower support/resistance or trend-following bands, suitable for longer-term analysis. Band scaling further adjusts the channel width to match market volatility.
Signals
Reversal from Bands: Signals are generated when the price closes outside the band (above the upper or below the lower) and then returns to the channel, indicating a potential trend reversal.
SMA Breakout: Signals are generated when the price crosses the SMA upward (bullish signal) or downward (bearish signal), suggesting potential trend changes.
Visualization
Centerline: The SMA of candlestick midpoints, displayed as a thin line.
Channel Bands: Upper and lower channel boundaries, with customizable colors.
Fill: Options include a gradient (smooth color transition between bands) or solid color. The fill can also be disabled for greater clarity.
█ FEATURES AND SETTINGS
SMA Length: Determines the moving average period (default: 20). Values of 10–30 are suitable for a wide channel containing price movement, ideal for short-term timeframes. Longer values (e.g., 50–100) create narrower support/resistance or trend-following bands, better suited for higher timeframes.
Band Scaling: Percentage of the average candle height (default: 200%). Adjusts the channel width to match market volatility—smaller values (e.g., 50–100%) for narrower bands, larger values (e.g., 200–300%) for wider channels.
Fill Type: Gradient, solid, or no fill, allowing customization to user preferences.
Colors: Options to change the colors of bands, fill, and signals for better readability.
Signals: Options to enable/disable reversal signals from bands and SMA breakout signals.
█ HOW TO USE
Add the script to your chart in TradingView by clicking "Add to Chart" in the Pine Editor.
Adjust input parameters in the script settings:
SMA Length: Set to 10–30 for a wide channel containing price movement, suitable for scalping or short-term trading. Set above 30 (e.g., 50–100) for narrower support/resistance or trend-following bands.
Band Scaling: Adjust the channel width to market volatility. Smaller values (50–100%) for tighter support/resistance bands, larger values (200–300%) for wider channels containing price movement.
Fill Type and Colors: Choose a gradient for aesthetics or a solid fill for clarity.
Analyze signals:
Reversal Signals: Triangles above (bearish) or below (bullish) candles indicate potential reversal points.
SMA Breakout Signals: Circles above (bearish) or below (bullish) candles indicate trend changes.
Test the indicator on different instruments and timeframes to find optimal settings for your trading style.
█ LIMITATIONS
The indicator may generate false signals in highly volatile or consolidating markets.
On low-liquidity charts (e.g., exotic currency pairs), the bands may be less reliable.
Effectiveness depends on properly matching parameters to the market and timeframe.
Ultimate Volatility CloudUltimate Volatility Cloud
The Ultimate Volatility Cloud is a powerful and highly customizable indicator designed to help traders visualize market volatility, easily identify trend, and overextended moves in price with adaptive bands. It combines the strengths of the Arnaud Legoux Moving Average, Kaufman's Adaptive Moving Average, ATR Channels, and Standard Deviation bands, offering multiple pre-configured profiles and extensive customization options.
Key Features:
Dynamic Volatility Bands: The indicator plots multiple layers of volatility bands around a central basis line, providing a comprehensive view of price deviation.
Hybrid Band Calculation: Bands are a sophisticated blend of Keltner Channels, KAMA ATR Channels and Standard Deviation, allowing for a nuanced representation of volatility.
Adaptive Smoothing: Bands are smoothed using either Exponential Moving Average (EMA) or Kaufman's Adaptive Moving Average (KAMA) based on the selected profile, ensuring responsiveness tailored to market conditions.
Layered Fills: The cloud uses distinct color fills for different volatility levels, making it easy to visually interpret price action relative to its typical range.
Customizable Color Themes: Choose from a variety of pre-set color themes, including "Rainbow," "Wild," and "Monochrome," or stick with classic options to suit your visual preference.
Optional Basis Line Plots: Display the EMA or KAMA basis lines (used in Keltner Channel calculations) separately on the chart for additional analysis.
Understanding the Profiles:
The indicator comes with several pre-configured "Settings Profiles" that adjust the internal parameters (Keltner Channel/KAMA Channel/Standard Deviation band blend, and band smoothing) to suit different trading styles or market environments.
1. Standard Profile:
Blend: 60% Keltner Channel, 40% Standard Deviation.
Smoothing: EMA smoothing of 3 periods.
Purpose: A balanced, general-purpose profile suitable for a wide range of market conditions. It offers a good blend of trend following and volatility awareness.
2. Responsive Profile:
Blend: 40% Keltner Channel, 60% Standard Deviation.
Smoothing: EMA smoothing of 2 period.
Purpose: Designed for traders who need quick reactions to price changes. The higher Standard Deviation blend and minimal smoothing make it highly sensitive to immediate volatility shifts, ideal for short-term analysis or identifying early moves.
3. Ranging Market Profile:
Blend: 80% KAMA ATR Channel, 20% Standard Deviation.
Smoothing: KAMA smoothing.
Purpose: Optimized for sideways or consolidating markets. By utilizing KAMA-based ATR bands and KAMA for band smoothing, this profile adapts its responsiveness to reduce whipsaws in choppy conditions, providing clearer boundaries for range-bound price action.
4. Trend Following Profile:
Blend: 90% Keltner Channel, 10% Standard Deviation.
Smoothing: EMA smoothing of 5 periods.
Purpose: Tailored for riding strong trends. The heavy emphasis on the Keltner Channel and slightly smoother bands help filter out minor fluctuations, allowing traders to focus on the dominant directional movement.
5. Conservative Profile:
Blend: 65% KAMA ATR Channel, 35% Standard Deviation.
Smoothing: EMA smoothing of 10 periods.
Purpose: Aims to provide more filtered signals and reduce noise. The KAMA basis for the Keltner Channel combined with a longer EMA smoothing period offers a slower, more confirmed view of volatility, suitable for traders seeking higher conviction entries or exits.
Example of the Ranging Market Profile
How to Use:
The volatility cloud can be interpreted in various ways:
Price within the inner bands: May indicate consolidation or a period of lower volatility.
Price pushing into outer bands: Suggests increasing volatility and potential for a strong move.
Price breaking out of extreme outer bands: Can signal significant momentum and the start or continuation of a strong trend.
Cloud expansion/contraction: Visually indicates periods of increasing or decreasing market energy.
Experiment with different profiles and settings to find the combination that best suits your trading strategy and the instruments you trade.
Predictive Order Blocks [CryptoSea]The Predictive Order Blocks Indicator is a unique and innovative tool that enhances market analysis by identifying support and resistance blocks based on standard deviations from a median line. Unlike traditional indicators that rely solely on the close price, this indicator leverages the median line and standard deviations to form areas of interest, rather than targeting a single price point. This approach provides a more accurate representation of market structure, especially during periods of consolidation and expansion.
Key Features
Multi-Term Length Analysis: The indicator offers short, medium, and long-term settings, allowing traders to customise the analysis based on their preferred trading strategy and timeframe. This flexibility ensures that the tool is adaptable to various market conditions and trading styles.
Standard Deviation-Based Order Blocks: The core functionality of the indicator revolves around calculating standard deviations from a median line to form support and resistance blocks. These blocks provide a clearer and more reliable picture of market structure compared to single-point levels. By focusing on areas rather than exact price levels, the indicator helps traders identify zones where price is likely to react, leading to more informed trading decisions.
Dynamic Box Creation: The indicator dynamically creates breakout boxes based on user-selected standard deviation ranges. These boxes are formed at the start of market expansion following periods of consolidation. This feature is particularly useful because it highlights key levels where price is likely to retrace after breaking out, providing traders with actionable insights during market transitions.
Proximity-Based Gradient Colors: The indicator features gradient colors that change based on the price's proximity to the standard deviation bands. This visual aid helps traders quickly assess the current market condition and the potential significance of the support and resistance blocks.
Adaptive Display Options: To accommodate different trading preferences, the indicator includes options to toggle the display of the trend line (median line) and the standard deviation bands. This flexibility allows traders to customise their chart view to match their analysis style, whether they prefer a more clutter-free view or a detailed breakdown of market levels.
In the example below, the indicator shows the bands compressing during a period of consolidation, highlighting the potential for a breakout.
How it Works
Median Line Calculation: The indicator calculates the median line using a user-defined period. This line serves as the central reference point from which the standard deviations are calculated. By using the median line instead of just the close price, the indicator provides a more stable and reliable baseline for identifying support and resistance areas.
Standard Deviation Bands: Around the median line, the indicator calculates multiple standard deviation bands. These bands represent areas where price is statistically likely to find support or resistance. By focusing on these areas, traders can better anticipate where price might react, rather than relying on arbitrary levels.
Dynamic Box Creation and Expansion Detection: The indicator monitors the compression and expansion of the standard deviation bands. During periods of low volatility (squeeze), the bands compress, indicating consolidation. Once the bands start expanding, it signals the potential for a breakout. At this point, the indicator dynamically creates predictive order blocks based on the selected standard deviation range. These blocks highlight key levels where price might retrace or react, providing traders with valuable entry and exit points.
Color-Coded Proximity Alerts: To further enhance usability, the indicator uses color gradients to indicate how close the current price is to the calculated bands. This visual representation helps traders quickly assess the potential significance of the price's current position relative to the support and resistance areas.
In the example below, the indicator shows the bands expanding with the price, triggering the formation of the predictive order block.
In the final example, the price retraces into the order block before bouncing back to the upside, demonstrating the effectiveness of the identified support area.
Alerts
Trend Line Alerts: The indicator provides alerts when the price crosses above or below the trend line (median line). This feature is crucial for traders looking to identify potential trend changes early, allowing them to act quickly on emerging opportunities.
Band Alerts: Alerts are also triggered when the price crosses above or below the upper or lower bands for each standard deviation level. This helps traders identify potential breakout or breakdown scenarios, ensuring they are notified of significant market movements as they happen.
Customisable Alert Conditions: To cater to different trading strategies, the indicator allows users to set alert conditions for each standard deviation band and the trend line. This level of customisation ensures that traders receive alerts that are relevant to their specific trading style and market analysis.
Application
Strategic Decision-Making: The Predictive Order Blocks Indicator assists traders in making informed decisions by providing detailed analysis of potential breakout zones. By identifying key support and resistance areas, the indicator helps traders plan their entries and exits with greater precision.
Trend Confirmation: The indicator reinforces trading strategies by identifying key levels where price is likely to react. This confirmation is crucial for traders looking to enter trades with higher confidence.
Customized Analysis: The indicator adapts to various trading styles with extensive input settings that control the display and calculation of order blocks. Whether you're a day trader, swing trader, or long-term investor, the indicator can be tailored to meet your specific needs.
Visual Clarity: With customizable color settings and display options, the indicator enhances chart readability, allowing traders to quickly and easily interpret market data.
The Predictive Order Blocks Indicator by CryptoSea is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
Volume MAs Oscillator | Lyro RSVolume MAs Oscillator | Lyro RS
Overview
The Volume MAs Oscillator is a powerful volume‑adjusted momentum tool that combines custom‑weighted moving averages on volume‑weighted price with smoothed deviation bands. It offers dynamic insights into trend direction, overbought/oversold conditions, and relative valuation — all within a single indicator
Key Features
Volume‑Adjusted Moving Averages: Moving averages can be volume‑weighted using the following formula: a moving average of (Price × Volume) divided by a moving average of Volume. This formula is applied across more than 14 different moving averages; however, it is not used with the VWMA, as VWMA is inherently a volume-weighted moving average.
Percentage Oscillator: Displays the normalized difference: (source – MA) / MA * 100, centered around zero for easy interpretation of strength and direction.
Deviation Bands: Builds upper and lower bands from standard deviation of the oscillator over a selected lookback, with distinct positive/negative multipliers and optional smoothing to reduce noise.
Inputs: Band Length, Band Smoothing, Positive Band Multiplier, Negative Band Multiplier.
Multi‑Mode Signal System:
1. Trend Mode – Colors oscillator according to breaks above (bullish) or below (bearish) respective bands.
2. Reversion Mode – Inverses color logic: signals overextensions beyond bands as reversion opportunities, greys inside the bands.
3. Valuation Mode – Applies a gradient color scale (UpC ⇄ DnC) to reflect relative valuation strength.
Customizable Visuals: Select from 5 pre‑set palettes—Classic, Mystic, Major Themes, Accented, Royal—or define your own custom bullish/bearish colors.
Chart enhancements include color‑coded oscillator line, deviation bands, glow‑effect midline at zero, background shading and candlestick/bar coloring aligned to signal mode.
Built‑In Signals: Automatically plots ▲ oversold and ▼ overbought markers upon crosses of lower/upper bands (in trend or reversion modes), enhancing signal clarity.
How It Works
MA Calculation – Applies the selected MA type to price × volume (normalized by MA of volume) or direct VWMA.
Oscillator Output – Calculates the % difference of source vs. derived MA.
Band Construction – Computes rolling standard deviation; applies user‑defined multipliers; smooths bands with exponential blending.
Mode-Dependent Coloring & Signals –
• Trend: Highlights strength trends via band cross coloring.
• Reversion: Flags extremes beyond bands as potential pullbacks.
• Valuation: Uses gradient to reflect oscillator’s position relative to recent range.
Signal Markers – Deploys arrows and color rules to flag overbought (▼) or oversold (▲) conditions when bands are breached.
Practical Use
Trend Confirmation – In Trend Mode, use upward price_diff cross above upper band as bullish; downward cross below lower band as bearish.
Mean Reversion – In Reversion Mode, fading extremes beyond bands may precede a retracement.
Relative Valuation – Valuation Mode shines when assessing how extended price_diff is, with gradient colors indicating valuation zones.
Bars/candles color‑coded to oscillator state boosts clarity of market tone and allows for rapid visual scanning.
Customization
Adjust MA type/length to tune responsiveness vs. smoothing.
Configure band settings for volatility sensitivity.
Toggle between signal modes for trend-following or reversion strategies.
Stylish visuals: pick or customize color schemes to match your chart setup.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Triple SRSI-MFI Ⅲ - Multi TimeframeTriple SRSI-MFI Ⅲ - Multi Timeframe Indicator
Description
The Triple SRSI-MFI Ⅲ - Multi Timeframe indicator is a powerful tool designed to combine Stochastic RSI (SRSI) and Money Flow Index (MFI) across multiple timeframes (higher, current, and lower). It provides a comprehensive view of market momentum and potential overbought/oversold conditions by calculating a weighted hybrid of SRSI-MFI values from three different timeframes. The indicator also integrates Bollinger Bands to help identify trend direction and volatility.
This indicator is ideal for traders who want to analyze market conditions across multiple timeframes without switching charts. It automatically adjusts settings based on the current timeframe and includes a dynamic weighting system optimized for Bitcoin volatility. Additionally, a real-time information panel displays the market state (buy/sell) and signal strength.
Key Features
Multi-Timeframe Analysis: Combines SRSI-MFI from higher, current, and lower timeframes for a holistic view.
Dynamic Weighting: Automatically adjusts weights for each timeframe based on Bitcoin volatility, with an option for manual customization.
Bollinger Bands Integration: Visualizes trend direction and volatility using Bollinger Bands, with customizable source selection.
Real-Time Info Panel: Displays market state (buy/sell) and signal strength (%) in the top-right corner of the chart.
Customizable Settings: Allows users to tweak MFI source, Bollinger Bands parameters, and visibility of individual components.
How to Use
Add to Chart: Add the "Triple SRSI-MFI Ⅲ - Multi Timeframe" indicator to your chart.
Interpret Signals:
Market State (Buy/Sell): Shown in the info panel. "Buy" when the average SRSI-MFI is above the Bollinger Bands basis, "Sell" when below.
Strength (%): The relative position of the average SRSI-MFI within the Bollinger Bands, scaled from 0% to 100%.
Overbought/Oversold Levels: The indicator plots horizontal lines at 80 (overbought) and 20 (oversold). Use these as potential reversal zones.
Combine with Price Action: Use the indicator in conjunction with price action or other tools for better decision-making.
Adjust Settings: Customize the settings (e.g., Bollinger Bands length, weights, visibility) to match your trading style.
Settings
MFI Source: Select the source for MFI calculation (default: "hlc3"). Options include "close", "open", "high", "low", "hl2", "hlc3", "ohlc4".
Bollinger Bands:
Length: Period for Bollinger Bands calculation (default: 20).
Multiplier: Standard deviation multiplier for the bands (default: 2.0).
Source: Choose which SRSI-MFI value to use for Bollinger Bands ("averageHybrid", "hybrid_higher", "hybrid_current", "hybrid_lower"; default: "hybrid_higher").
Weights:
Auto Weight Enabled: Enable/disable automatic weights based on Bitcoin volatility (default: true).
Higher/Current/Lower Weights: Manually set weights for each timeframe if auto-weight is disabled (defaults: 1.5, 1.0, 0.5).
Indicator On/Off:
Toggle visibility for Higher SRSI-MFI, Current SRSI-MFI, Lower SRSI-MFI, Average SRSI-MFI, and Bollinger Bands.
How It Works
SRSI-MFI Calculation:
Stochastic RSI (SRSI) and Money Flow Index (MFI) are calculated for three timeframes: higher, current, and lower.
The hybrid value (SRSI * (MFI / 100)) is computed for each timeframe.
Weighted Average:
The hybrid values are combined into a weighted average (averageHybrid) using dynamic or manual weights.
Bollinger Bands:
Bollinger Bands are applied to the selected source (e.g., hybrid_higher) to identify trend direction and volatility.
Relative Position:
The position of averageHybrid within the Bollinger Bands is scaled to a percentage (0% to 100%) for strength assessment.
Visualization:
Plots individual SRSI-MFI lines, Bollinger Bands, and overbought/oversold levels.
A real-time info panel provides market state and signal strength.
Notes
This indicator is best used as part of a broader trading strategy. It is not a standalone signal generator and should be combined with other forms of analysis.
The automatic weights are optimized for Bitcoin (BTC) volatility. For other assets, you may need to adjust the weights manually.
The indicator may require sufficient historical data to calculate higher and lower timeframe values accurately.
Multi-Band Trend LineThis Pine Script creates a versatile technical indicator called "Multi-Band Trend Line" that builds upon the concept of the popular "Follow Line Indicator" by Dreadblitz. While the original Follow Line Indicator uses simple trend detection to place a line at High or Low levels, this enhanced version combines multiple band-based trading strategies with dynamic trend line generation. The indicator supports five different band types and provides more sophisticated buy/sell signals based on price breakouts from various technical analysis bands.
Key Features
Multi-Band Support
The indicator supports five different band types:
- Bollinger Bands: Uses standard deviation to create bands around a moving average
- Keltner Channels: Uses ATR (Average True Range) to create bands around a moving average
- Donchian Channels: Uses the highest high and lowest low over a specified period
- Moving Average Envelopes: Creates bands as a percentage above and below a moving average
- ATR Bands: Uses ATR multiplier to create bands around a moving average
Dynamic Trend Line Generation (Enhanced Follow Line Concept)
- Similar to the Follow Line Indicator, the trend line is placed at High or Low levels based on trend direction
- Key Enhancement: Instead of simple trend detection, this version uses band breakouts to trigger trend changes
- When price breaks above the upper band (bullish signal), the trend line is set to the low (optionally adjusted with ATR) - similar to Follow Line's low placement
- When price breaks below the lower band (bearish signal), the trend line is set to the high (optionally adjusted with ATR) - similar to Follow Line's high placement
- The trend line acts as dynamic support/resistance, following the price action more precisely than the original Follow Line
ATR Filter (Follow Line Enhancement)
- Like the original Follow Line Indicator, an ATR filter can be selected to place the line at a more distance level than the normal mode settled at candles Highs/Lows
- When enabled, it adds/subtracts ATR value to provide more conservative trend line placement
- Helps reduce false signals in volatile markets
- This feature maintains the core philosophy of the Follow Line while adding more precision through band-based triggers
Signal Generation
- Buy Signal: Generated when trend changes from bearish to bullish (trend line starts rising)
- Sell Signal: Generated when trend changes from bullish to bearish (trend line starts falling)
- Signals are displayed as labels on the chart
Visual Elements
- Upper and lower bands are plotted in gray
- Trend line changes color based on direction (green for bullish, red for bearish)
- Background color changes based on trend direction
- Buy/sell signals are marked with labeled shapes
How It Works
Band Calculation: Based on the selected band type, upper and lower boundaries are calculated
Signal Detection: When price closes above the upper band or below the lower band, a breakout signal is generated
Trend Line Update: The trend line is updated based on the breakout direction and previous trend line value
Trend Direction: Determined by comparing current trend line with the previous value
Alert Generation: Buy/sell conditions trigger alerts and visual signals
Use Cases
Enhanced trend following strategies: More precise than basic Follow Line due to band-based triggers
Breakout trading: Multiple band types provide various breakout opportunities
Dynamic support/resistance identification: Combines Follow Line concept with band analysis
Multi-timeframe analysis with different band types: Choose the most suitable band for your timeframe
Reduced false signals: Band confirmation provides better entry/exit points compared to simple trend following
Trendilo ARTrendilo AR is a custom trading indicator designed to identify market trends using advanced techniques such as the Arnaud Legoux Moving Average (ALMA), volume confirmations, and dynamic volatility bands. This indicator provides a clear visualization of trends, including significant changes and custom alerts.
Review of Indicators Used
1. ALMA
Description:
ALMA is a moving average that applies an advanced filter to smooth price data, reducing noise and focusing on actual trends.
Usage in the Indicator:
Used to calculate the smoothed percentage price change and determine trend direction. Customizable parameters include:
- Length: Defines the number of bars to consider.
- Offset: Adjusts sensitivity toward recent prices.
- Sigma: Controls the degree of smoothing.
Advantages:
- Reduced lag in trend detection.
- Resistance to market noise.
2. ATR
Description:
ATR measures the market’s average volatility by considering the range between high and low prices over a given period.
Usage in the Indicator:
ATR is used to calculate "dynamic smoothing", adjusting the indicator’s sensitivity based on current market volatility.
Advantages:
- Adapts to high or low volatility conditions.
- Helps define dynamic support and resistance levels.
3. SMA
Description:
SMA calculates the average of prices or volume over a specific time period.
Usage in the Indicator:
Used to calculate the volume moving average (Volume SMA) to confirm whether the current volume supports the detected trend.
Advantages:
- Easy to understand and calculate.
- Provides volume-based trend confirmation.
4. RMS Bands
Description:
RMS Bands calculate the standard deviation of percentage price changes, creating upper and lower levels that act as overbought and oversold indicators.
Usage in the Indicator:
- Define the range within which the market is considered neutral.
- Crosses above or below the bands indicate trend changes.
Advantages:
- Visual identification of strong trends.
- Helps filter false signals.
Colors and Visuals Used in the Indicator
1. ALMA Line
Colors:
- Green: Indicates a confirmed uptrend (with sufficient volume).
- Red: Indicates a confirmed downtrend (with sufficient volume).
- Gray: Indicates a neutral phase or insufficient volume to confirm a trend.
2. RMS Bands
- Upper and Lower Lines:
- Purple (with transparency): These lines represent the RMS bands (upper and lower) and
adjust opacity based on trend strength.
- Stronger trends result in less transparency (more solid colors).
3. Highlighted Background (Strong Trends)
- Color:
- Light Green (transparent): Highlights a strong trend when the smoothed percentage change (ALMA) exceeds 1.5 times the RMS.
4. Horizontal Lines
- Baseline (0):
- Dark Gray: Serves as a central reference to identify the directionality of percentage changes.
- Additional Line (0.1):
- Blue: A customizable line to mark user-defined key levels.
5. Bar Colors
- Bar Colors:
- Green: When the price is in a confirmed uptrend.
- Red: When the price is in a confirmed downtrend.
- No color: When there is insufficient volume or no clear trend.
How to Use the Indicator
1. Initial Setup
1. Add the Indicator to Your Chart: Copy the code into the Pine Editor on TradingView and apply it to your chart.
2. Customize Parameters: Adjust values based on your trading strategy:
- Smoothing: Controls the level of smoothing for percentage changes.
- Lookback Length: Defines the observation period for calculations.
- Band Multiplier: Adjusts the width of RMS bands.
2. Signal Interpretation
1. Indicator Colors:
- Green: Confirmed uptrend.
- Red: Confirmed downtrend.
- Gray: No clear trend or insufficient volume.
2. RMS Bands:
- If the ALMA line (smoothed percentage change) crosses above the upper RMS band, it signals a potential uptrend.
- If it crosses below the lower RMS band, it signals a potential downtrend.
3. Volume Confirmation:
- The indicator's color activates only if the current volume exceeds the Volume SMA.
3. Alerts and Decisions
1. Trend Change Alerts:
- The indicator automatically triggers alerts when an uptrend or downtrend is detected.
- Configure these alerts to receive real-time notifications.
2. Strong Trend Signals:
- When the magnitude of the percentage change exceeds 1.5 times the RMS, the chart background highlights the strong trend.
4. Trading Strategies
1. Buy:
- Enter long positions when:
- The indicator turns green.
- Volume confirms the trend.
- Consider placing a stop-loss just below the lower RMS band.
2. Sell:
- Enter short positions when:
- The indicator turns red.
- Volume confirms the trend.
- Consider placing a stop-loss just above the upper RMS band.
3. Neutral:
- Avoid trading when the indicator is gray, as no clear trend or insufficient volume is present.
Disclaimer: As this is my first published indicator, please use it with caution. Feedback is highly appreciated to improve its performance.
Happy Trading!
Auto-Length Adaptive ChannelsIntroduction
The key innovation of the ALAC is the implementation of dynamic length identification, which allows the indicator to adjust to the "market beat" or dominant cycle in real-time.
The Auto-Length Adaptive Channels (ALAC) is a flexible technical analysis tool that combines the benefits of five different approaches to market band and price deviation calculations.
Traders often tend to overthink of what length their indicators should use, and this is the main idea behind this script. It automatically calculates length based on pivot points, averaging the distance that is in between of current market highs and lows.
This approach is very helpful to identify market deviations, because deviations are always calculated and compared to previous market behavior.
How it works
The indicator uses a Detrended Rhythm Oscillator (DRO) to identify the dominant cycle in the market. This length information is then used to calculate different market bands and price deviations. The ALAC combines five different methodologies to compute these bands:
1 - Bollinger Bands
2 - Keltner Channels
3 - Envelope
4 - Average True Range Channels
5 - Donchian Channels
By averaging these calculations, the ALAC produces an overall market band that generalizes the approaches of these five methods into a single, adaptive channel.
How to Use
When the price is at the upper band, this might suggest that the asset is overbought and may be due for a price correction. Conversely, when the price is at the lower band, the asset may be oversold and due for a price increase.
The space between the bands represents the market's volatility. Wider bands indicate higher volatility, while narrower bands suggest lower volatility.
Indicator Settings
The settings of the ALAC allow for customization to suit different trading strategies:
Use Autolength?: This allows the indicator to automatically adjust the length of the dominant cycle.
Usual Length: If "Use Autolength?" is disabled, this setting allows the user to manually specify the length of the cycle.
Moving Average Type: This selects the type of moving average to be used in the calculations. Options include SMA, EMA, ALMA, DEMA, JMA, KAMA, SMMA, TMA, TSF, VMA, VAMA, VWMA, WMA, and ZLEMA.
Channel Multiplier: This adjusts the distance between the bands.
Channel Multiplier Step: This changes the step size of the channel multiplier. Each next market band will be multiplied by a previous one. You can potentially use values below 1, which will plot bands inside the first, main channel.
Use DPO instead of source data?: This setting uses the DPO for calculations instead of the source data. Basically, this is how you can add or eliminate trend from calculation of an average leg-up / leg-down move.
Fast: This adjusts the fast length of the DPO.
Slow: This adjusts the slow length of the DPO.
Zig-zag Period: This adjusts the period of the zig-zag pattern used in the DPO.
(!) For more information about DPO visit official TradingView description here: link
Also, I want to say thanks to @StockMarketCycles for initial idea of Detrended Rhythm Oscillator (DRO) that I use in this script.
The Adaptive Average Channel is a powerful and versatile indicator that combines the strengths of multiple technical analysis methods.
In summary, with the ALAC, you can:
1 - Dynamically adapt to any asset and price action with automatic calculation of dominant cycle lengths.
2 - Identify potential overbought and oversold conditions with the adaptive market bands.
3 - Customize your analysis with various settings, including moving average type and channel multiplier.
4 - Enhance your trading strategy by using the indicator in conjunction with other forms of analysis.
S/R Clouds Overview
The S/R Clouds Indicator is a sophisticated TradingView tool designed to visualize support and resistance levels through dynamic cloud formations. Built on the principles of Keltner Channels, it employs a central moving average enveloped by volatility-based bands to highlight potential price reversal zones. This indicator enhances chart analysis with customizable aesthetics and practical alerts, making it suitable for traders across various strategies and timeframes.
Key Features
Dynamic Bands: Calculates upper and lower bands using a configurable moving average (SMA or EMA) offset by multiples of the average true range (derived from high-low ranges), capturing volatility deviations for precise S/R identification.
Cloud Visualization: Renders semi-transparent clouds between primary and extended bands, providing a clear, layered view of support (lower) and resistance (upper) areas.
Trend Detection: Incorporates a trend state logic based on price position relative to bands and moving average direction, aiding in bullish/bearish market assessments.
Customization Options:
Select from multiple color themes (e.g., Neon, Grayscale) or use custom colors for bands.
Enable glow effects for enhanced visual depth and adjust opacity for chart clarity.
Volatility Insights: Monitors band width to detect squeezes (low volatility) and expansions (high volatility), signaling potential breakouts.
Alerts System: Triggers notifications for price crossings of bands, trend changes, and other key events to support timely decision-making.
How It Works
At its core, the indicator centers on a user-defined period moving average. Volatility is measured via an exponential moving average of the high-low range, multiplied by adjustable factors to form the bands. This setup creates adaptive clouds that expand/contract with market volatility, offering a more responsive alternative to static S/R lines. The result is a clean, professional overlay that integrates seamlessly with other technical tools.
This high-quality indicator prioritizes usability and visual appeal, ensuring traders can focus on analysis without distraction.
GCM Volatility-Adaptive Trend ChannelScript Description
Name: GCM Volatility-Adaptive Trend Channel (GCM VATC)
Overview
The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB).
By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change.
Core Components:
JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts.
Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility).
How to Use It
By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to:
Identify the primary trend direction using the smooth JMA lines.
Gauge the strength and stability of that trend.
See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend.
A Note on Originality & House Rules Compliance
This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis.
This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code.
Settings
All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset.
I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength
Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to.
Thank You and Happy Trading
Log Regression Channel [UAlgo]The "Log Regression Channel " channel is useful for analyzing price trends and volatility in a financial instrument over a specified period. By using logarithmic scaling, this indicator can more effectively handle the wide range of price movements seen in many financial markets, making it particularly valuable for assets with exponential growth characteristics.
The indicator plots the central regression line along with upper and lower deviation bands, providing a visual representation of potential support and resistance levels.
🔶 Key Features
Logarithmic Regression Line: The central line represents the logarithmic regression, which fits the price data over the specified length using a logarithmic scale. This helps in identifying the overall trend direction.
Deviation Bands: The upper and lower bands are plotted at a specified multiple of the standard deviation from the regression line, highlighting areas of potential overbought and oversold conditions.
Customizable Parameters: Users can adjust the length of the regression, the deviation multiplier, the color of the labels, and the size of the text labels to suit their preferences.
R-Squared Display: The R-squared value, which measures the goodness of fit of the regression model, is displayed on the chart. This helps traders assess the reliability of the regression line.
🔶 Calculations
The indicator performs several key calculations to plot the logarithmic regression channel:
Logarithmic Transformation: The prices and time indices are transformed using the natural logarithm to handle exponential growth in price data.
Regression Coefficients: The slope and intercept of the regression line are calculated using the least squares method on the transformed data.
Predicted Values: The regression equation is used to calculate predicted values for each data point.
Standard Deviation: The standard deviation of the residuals (differences between actual and predicted values) is computed to determine the width of the deviation bands.
Deviation Bands: Upper and lower bands are plotted at a specified multiple of the standard deviation above and below the regression line.
R-Squared Value: The R-squared value is calculated to measure how well the regression line fits the data. This value is displayed on the chart to inform the user of the model's reliability.
🔶 Disclaimer
The "Log Regression Channel " indicator is provided for educational and informational purposes only.
It is not intended as investment advice or a recommendation to buy or sell any financial instrument. Trading financial instruments involves substantial risk and may not be suitable for all investors.
Past performance is not indicative of future results. Users should conduct their own research.
Adaptive RSI | Lyro RSThe Adaptive RSI | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator enhances the traditional Relative Strength Index (RSI) by integrating adaptive smoothing techniques and dynamic bands. This design aims to provide traders with a nuanced view of market momentum, highlighting potential trend shifts and overbought or oversold conditions.
Key Features
Adaptive RSI Calculation: Combines fast and slow Exponential Moving Averages (EMAs) of the RSI to capture momentum shifts effectively.
Dynamic Bands: Utilizes a smoothed standard deviation approach to create upper and lower bands around the adaptive RSI, aiding in identifying extreme market conditions.
Signal Line: An additional EMA of the adaptive RSI serves as a signal line, assisting in confirming trend directions.
Customizable Color Schemes: Offers multiple predefined color palettes, including "Classic," "Mystic," "Accented," and "Royal," with an option for users to define custom colors for bullish and bearish signals.
How It Works
Adaptive RSI Computation: Calculates the difference between fast and slow EMAs of the RSI, producing a responsive oscillator that adapts to market momentum.
Band Formation: Applies a smoothing factor to the standard deviation of the adaptive RSI, generating dynamic upper and lower bands that adjust to market volatility.
Signal Line Generation: Computes an EMA of the adaptive RSI to act as a signal line, providing additional confirmation for potential entries or exits.
Visualization: Plots the adaptive RSI as color-coded columns, with colors indicating bullish or bearish momentum. The dynamic bands are filled to visually represent overbought and oversold zones.
How to Use
Identify Momentum Shifts: Observe crossovers between the adaptive RSI and the signal line to detect potential changes in trend direction.
Spot Overbought/Oversold Conditions: Monitor when the adaptive RSI approaches or breaches the dynamic bands, signaling possible market extremes.
Customize Visuals: Select from predefined color palettes or define custom colors to align the indicator's appearance with personal preferences or chart themes.
Customization Options
RSI and EMA Lengths: Adjust the lengths of the RSI, fast EMA, slow EMA, and signal EMA to fine-tune the indicator's sensitivity.
Band Settings: Modify the band length, multiplier, and smoothing factor to control the responsiveness and width of the dynamic bands.
Color Schemes: Choose from predefined color modes or enable custom color settings to personalize the indicator's appearance.
⚠️ DISCLAIMER ⚠️: This indicator alone is not reliable and should be combined with other indicator(s) for a stronger signal.
Adaptive Kalman Trend Filter (Zeiierman)█ Overview
The Adaptive Kalman Trend Filter indicator is an advanced trend-following tool designed to help traders accurately identify market trends. Utilizing the Kalman Filter—a statistical algorithm rooted in control theory and signal processing—this indicator adapts to changing market conditions, smoothing price data to filter out noise. By focusing on state vector-based calculations, it dynamically adjusts trend and range measurements, making it an excellent tool for both trend-following and range-based trading strategies. The indicator's adaptive nature is enhanced by options for volatility adjustment and three unique Kalman filter models, each tailored for different market conditions.
█ How It Works
The Kalman Filter works by maintaining a model of the market state through matrices that represent state variables, error covariances, and measurement uncertainties. Here’s how each component plays a role in calculating the indicator’s trend:
⚪ State Vector (X): The state vector is a two-dimensional array where each element represents a market property. The first element is an estimate of the true price, while the second element represents the rate of change or trend in that price. This vector is updated iteratively with each new price, maintaining an ongoing estimate of both price and trend direction.
⚪ Covariance Matrix (P): The covariance matrix represents the uncertainty in the state vector’s estimates. It continuously adapts to changing conditions, representing how much error we expect in our trend and price estimates. Lower covariance values suggest higher confidence in the estimates, while higher values indicate less certainty, often due to market volatility.
⚪ Process Noise (Q): The process noise matrix (Q) is used to account for uncertainties in price movements that aren’t explained by historical trends. By allowing some degree of randomness, it enables the Kalman Filter to remain responsive to new data without overreacting to minor fluctuations. This noise is particularly useful in smoothing out price movements in highly volatile markets.
⚪ Measurement Noise (R): Measurement noise is an external input representing the reliability of each new price observation. In this indicator, it is represented by the setting Measurement Noise and determines how much weight is given to each new price point. Higher measurement noise makes the indicator less reactive to recent prices, smoothing the trend further.
⚪ Update Equations:
Prediction: The state vector and covariance matrix are first projected forward using a state transition matrix (F), which includes market estimates based on past data. This gives a “predicted” state before the next actual price is known.
Kalman Gain Calculation: The Kalman gain is calculated by comparing the predicted state with the actual price, balancing between the covariance matrix and measurement noise. This gain determines how much of the observed price should influence the state vector.
Correction: The observed price is then compared to the predicted price, and the state vector is updated using this Kalman gain. The updated covariance matrix reflects any adjustment in uncertainty based on the latest data.
█ Three Kalman Filter Models
Standard Model: Assumes that market fluctuations follow a linear progression without external adjustments. It is best suited for stable markets.
Volume Adjusted Model: Adjusts the filter sensitivity based on trading volume. High-volume periods result in stronger trends, making this model suitable for volume-driven assets.
Parkinson Adjusted Model: Uses the Parkinson estimator, accounting for volatility through high-low price ranges, making it effective in markets with high intraday fluctuations.
These models enable traders to choose a filter that aligns with current market conditions, enhancing trend accuracy and responsiveness.
█ Trend Strength
The Trend Strength provides a visual representation of the current trend's strength as a percentage based on oscillator calculations from the Kalman filter. This table divides trend strength into color-coded segments, helping traders quickly assess whether the market is strongly trending or nearing a reversal point. A high trend strength percentage indicates a robust trend, while a low percentage suggests weakening momentum or consolidation.
█ Trend Range
The Trend Range section evaluates the market's directional movement over a specified lookback period, highlighting areas where price oscillations indicate a trend. This calculation assesses how prices vary within the range, offering an indication of trend stability or the likelihood of reversals. By adjusting the trend range setting, traders can fine-tune the indicator’s sensitivity to longer or shorter trends.
█ Sigma Bands
The Sigma Bands in the indicator are based on statistical standard deviations (sigma levels), which act as dynamic support and resistance zones. These bands are calculated using the Kalman Filter's trend estimates and adjusted for volatility (if enabled). The bands expand and contract according to market volatility, providing a unique visualization of price boundaries. In high-volatility periods, the bands widen, offering better protection against false breakouts. During low volatility, the bands narrow, closely tracking price movements. Traders can use these sigma bands to spot potential entry and exit points, aiming for reversion trades or trend continuation setups.
Trend Based
Volatility Based
█ How to Use
Trend Following:
When the Kalman Filter is green, it signals a bullish trend, and when it’s red, it indicates a bearish trend. The Sigma Cloud provides additional insights into trend strength. In a strong bullish trend, the cloud remains below the Kalman Filter line, while in a strong bearish trend, the cloud stays above it. Expansion and contraction of the Sigma Cloud indicate market momentum changes. Rapid expansion suggests an impulsive move, which could either signal the continuation of the trend or be an early sign of a possible trend reversal.
Mean Reversion: Watch for prices touching the upper or lower sigma bands, which often act as dynamic support and resistance.
Volatility Breakouts: Enable volatility-adjusted sigma bands. During high volatility, watch for price movements that extend beyond the bands as potential breakout signals.
Trend Continuation: When the Kalman Filter line aligns with a high trend strength, it signals a continuation in that direction.
█ Settings
Measurement Noise: Adjusts how sensitive the indicator is to price changes. Higher values smooth out fluctuations but delay reaction, while lower values increase sensitivity to short-term changes.
Kalman Filter Model: Choose between the standard, volume-adjusted, and Parkinson-adjusted models based on market conditions.
Band Sigma: Sets the standard deviation used for calculating the sigma bands, directly affecting the width of the dynamic support and resistance.
Volatility Adjusted Bands: Enables bands to dynamically adapt to volatility, increasing their effectiveness in fluctuating markets.
Trend Strength: Defines the lookback period for trend strength calculation. Shorter periods result in more responsive trend strength readings, while longer periods smooth out the calculation.
Trend Range: Specifies the lookback period for the trend range, affecting the assessment of trend stability over time.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band
The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean.
Key Concepts and Principles
1. Dollar-Cost Averaging (DCA)
DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time.
In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly.
2. Mean Reversion
Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order.
Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling.
3. Bollinger Bands
Bollinger Bands are a technical analysis tool that consists of three lines:
Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline.
Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions.
Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions.
In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion.
4. Time-Based Entry and Exit
The strategy has specific entry and exit points defined by time parameters:
Open Date: The date when the strategy begins opening positions.
Close Date: The date when all positions are closed.
This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame.
5. Position Sizing
Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price.
6. Closing All Positions
The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe.
7. Background Color Based on Price Relative to Bollinger Bands
The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands:
Red background indicates the price is above the upper band, signaling overbought conditions.
Green background indicates the price is below the lower band, signaling oversold conditions.
This provides an easy-to-interpret visual cue for traders to assess the current market environment.
Postscript: Configuring Initial Capital for Backtesting
To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance:
If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD.
Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD.
This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses.
Conclusion
The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
