90cycle @joshuuu90 minute cycle is a concept about certain time windows of the day.
This indicator has two different options. One uses the 90 minute cycle times mentioned by traderdaye, the other uses the cls operational times split up into 90 minutes session.
e.g. we can often see a fake move happening in the 90 minute window between 2.30am and 4am ny time.
The indicator draws vertical lines at the start/end of each session and the user is able to only display certain sessions (asia, london, new york am and pm)
For the traderdayes option, the indicator also counts the windows from 1 to 4 and calls them q1,q2,q3,q4 (q-quarter)
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
ابحث في النصوص البرمجية عن "wind+芯片行业+市盈率+财经数据"
Nadaraya-Watson CombineThis is a combination of the Lux Algo Nadaraya-Watson Estimator and Envelope. Please note the repainting issue.
In addition, I've added a plot of the actual values of the current barstate of
the Nadaraya-Watson windows as they are computed (lines 92-95). It only plots values for the current data at
each time update. It is interesting to compare the trajectory of the end points of the Estimator and
Envelope to the smoothing function at each time update. Due to the kernel smoothing at each update the
history is lost at each update (repaint).
I've added a feature to allow adjustment to the kernel smoothing algorithm as suggested by thomsonraja (line 59).
The settings and usage are repeated from Lux Algo below.
Settings
Window Size: Determines the number of recent price observations to be used to fit the Nadaraya-Watson Estimator.
Bandwidth: Controls the degree of smoothness of the envelopes , with higher values returning smoother results.
Mult: Controls the envelope width.
Src: Input source of the indicator.
Kernel power: See line 59, adjusts the exponential power (powh) as suggested by thomsonraja
Kernel denominator: See line 59, adjusts the denominator (den) as suggested by thomsonraja
Usage
This tool outlines extremes made by the prices within the selected window size.
This is achieved by estimating the underlying trend in the price using kernel smoothing,
calculating the mean absolute deviations from it, and adding/subtracting it
from the estimated underlying trend.
I repeat Lux Algo's caution: 'we do not recommend this tool to be used alone
or solely for real time applications.'
z_scoreStand-alone Z-score indicator for volatile currency pairs, showing STRONG BUY, BUY, SELL, STRONG SELL zones.
The use can define their own "window" or moving average length, which will affect the frequency and magnitude of trades.
Higher windows reduce trade size but increase frequency and vice versa.
The suggested window values are intended for the daily time-frame. They are selected to maximise returns.
ETHBTC . 64 days.
SOLBTC . 40 days.
Trading decisions must be confirmed by multiple indicators and other factors.
getSeries█ OVERVIEW
This library is a Pine programmer’s tool containing functions that build an array of values meeting specific conditions. Its functions use concepts from our ConditionalAverages library , but instead of returning a single value, they return an array containing all the values meeting the conditions, which can then be processed as needed. This provides more flexibility to the programmer than a single value.
The "getSeries" name of the library stems from the fact that is uses arrays to build the equivalent of custom series which can then be operated on using array-specific functions in the `array.*` namespace, looped through using a for...in structure to implement custom logic, or sent to functions designed to process arrays such as those in these libraries: ArrayStatistics , ArrayOperations , arrayutils or Averages .
The eight examples illustrated in the library's code showcase the diversity of scenarios where the functions can be used.
Look first. Then leap.
█ FUNCTIONS
The library contains the following functions:
whenSince(src, whenCond, sinceCond, length)
Creates an array containing the `length` last `src` values where `whenCond` is true, since the last occurence of `sinceCond`.
Parameters:
src : (series int/float) The source of the values to be included.
whenCond : (series bool) The condition determining which values are included. Optional. The default is `true`.
sinceCond : (series bool) The condition determining when the accumulated series resets. Optional. The default is false, which will not reset.
length : (simple int) The number of last values to return. Optional. The default is all values.
Returns: (float ) The array ID of the accumulated `src` values.
rollOnTimeWhen(src, timeWindow, cond, minBars)
Creates an array of `src` values where `cond` is true, over a moving window of length `timeWindow` milliseconds.
Parameters:
src : (series int/float) The source of the values to be included.
timeWindow : (simple int) The time duration in milliseconds defining the size of the moving window.
cond : (series bool) The condition determining which values are included. Optional. The default is `true`.
minBars : (simple int) The minimum number of values to maintain in the moving window. Optional. The default is 1.
Returns: (float ) The array ID of the accumulated `src` values.
Note that the functions must be called on each bar to work correctly. They must thus be pre-evaluated before using their results in conditional branches.
Simple scalping strategy for SOLThis is a simple scalping strategy for trading SOL made on top of the Rebalance Oscillator and the Rebalance Bear/Bull market indicators.
It is intended mostly as proof that these two indicators have their benefits even in simpler strategies.
This strategy in particular works well for the Bear months (check Nov. in the data window) but considerably underperforms Buy&Hold for the Bull months.
It tries to do a market operation per candle whenever the candle happens in a buy/sell trading window of the
Rebalance Bear/Bull indicator ().
It always buys/sells the same amount by default (you can set it in the cog menu in the option "Base Crypto Amount To Trade"),
for SOL this is set to 1.0SOL.
This is my first attempt at scalping, it differs slightly from the standards because it does not require fast
response candles or immediate market operations (it can work well with limit trading) and on top of this it also
does not require a stop loss since it uses an indicator that provides the trading windows (surprises can still happen though).
The profit that this strategy tries to take for each buy/sell pair is not configurable and is set at 12% each way when it happens.
KLemurs DeviationMarket: Stocks and ETF's
This overlay shows the deviation of the exponential moving average of the mid candle price of the currently loaded chart, away from the exponential moving average of the S&P and DOW combined and averaged mid candle price. The top and bottom lines also give a visual perspective of what a certain percentage (default 1%) looks like on the current charts window. This may help with making quick decisions for things like setting trailing stop trades with a percentage. This can be used for stocks, ETF's, and index's and It may be useful in finding potential stocks or ETF's if you are interested in these kinds of deviations. Defaults are set for a dark screen but can be edited to your taste. It's optimized to be an overlay on the current chart window as opposed to being a separate window.
Percentage Lines (editable)
This is three lines. The upper line (default green) plots the set percentage (default 1%) above the current chart’s ema. The middle line (default white) plots the current chart’s ema. The lower line (default red) plots the set percentage (default 1%) below the current chart’s ema.
Deviation Band (editable)
This is the colored band on the overlay between the upper and lower percentage lines. The band’s fill color indicates the deviation of the current charts ema from the ema of the combined S&P and DOW’s ema as follows:
- Red (default) = Current Chart’s ema is descending and the S&P/DOW ema is descending OR the Current Chart’s ema is below (underperforming) the S&P/DOW ema.
- Orange (default) = The Current Chart and S&P/DOW ema’s are both either ascending or descending together.
- Green (default) = The Current Chart’s ema is ascending but the S&P/DOW ema is descending.
To Set Line Colors
BY default, the upper line color uses the same colors as the ascending band color and the lower line uses the same color as the descending band color. To set the line colors, see "plotColor", "plotColorUp", or" plotColorDown" in variable settings within the script or use the “Central Plot Line”, “Upper Plot Line, or “Lower Plot Line” in the input dialogue to change this.
To Set Band Colors
To set the band colors, see "plotColor", "plotColorUp", or "plotColorDown" in variable settings within the script or use the “Color0”, “Color1", or “Color2” in the input dialogue to change this.
To Set EMA Lookback Period
The ema lookback period defaults to 5. This is the number of candles back that the script will use to determine the ema. See “CCemaN” in variable settings within the script or use the “EMA Period” in the input dialogue to change this.
To Set Percentage
To set the percentage that plots the upper and lower lines, see "CCP" in variable settings within the script or use “Upper/Lower Bands Percentage” in the input dialogue to change this. The default is .01 (or 1%).
Order Blocks + Order-Flow ProxiesOrder Blocks + Order-Flow Proxies
This indicator combines structural analysis of order blocks with lightweight order-flow style proxies, providing a tool for chart annotation and contextual study. It is designed to help users visualize where significant structural shifts occur and how simple volume-based signals behave around those areas. The script does not guarantee profitable outcomes, nor does it issue financial advice. It is intended purely for research, learning, and discretionary use.
Conceptual Background
Order Blocks
An “order block” is a term often used to describe a zone on the chart where price left behind a significant reversal or imbalance before continuing strongly in the opposite direction. In practice, this can mean the last bullish or bearish candle before a strong breakout. Traders sometimes study these regions because they believe that unfilled resting orders may exist there, or simply because they mark important pivots in price structure. This indicator detects such moments by scanning for breaks of structure (BOS). When price pushes above or below recent swing levels with sufficient displacement, the script identifies the prior opposite candle as the potential order block.
Break of Structure
A break of structure in this context is defined when the closing price moves beyond the highest high or lowest low of a short lookback window. The script compares the magnitude of this break to an ATR-based displacement filter. This helps ensure that only meaningful moves are marked rather than small, random fluctuations.
Order-Flow Proxies
Traditional order flow analysis may use bid/ask data, footprint charts, or volume profiles. Because TradingView scripts cannot access true order-book data, this indicator instead uses proxy signals derived from standard chart data:
Delta (proxy): Estimated imbalance of buying vs. selling pressure, approximated using bar direction and volume.
Imbalance ratio: Normalizes delta by total volume, ranging between -1 and +1 in theory.
Cumulative Delta (CVD): Running sum of delta over time.
Effort vs. Result (EvR): A comparison between volume and actual bar movement, highlighting cases where large effort produced little result (or vice versa).
These are not real order-flow measurements, but rather simple mathematical constructs that mimic some of its logic.
How the Script Works
Detecting Break of Structure
The user specifies a swing length. When price closes above the recent high (for bullish BOS) or below the recent low (for bearish BOS), a potential shift is recorded.
To qualify, the breakout must exceed a displacement filter proportional to the ATR. This helps filter out weak moves.
Locating the Order Block Candle
Once a BOS is confirmed, the script looks back within a short window to find the last opposite-colored candle.
The high/low or open/close of that candle (depending on user settings) is marked as the potential order block zone.
Drawing and Maintaining Zones
Each order block is represented as a colored rectangle extending forward in time.
Bullish zones are teal by default, bearish zones are red.
Zones extend until invalidated (price closing or wicking beyond them, depending on user preference) or until a user-defined lifespan expires.
A pruning mechanism ensures that only the most recent set number of zones remain, preventing chart overload.
Monitoring Touches
The script checks whether the current bar’s range overlaps any existing order block.
If so, the “closest” zone is considered touched, and a label may appear on the chart.
Confirmation Filters
Touches can optionally be confirmed by order-flow proxies.
For a bullish confirmation, the following must align:
Imbalance ratio above threshold,
Delta EMA positive,
Effort vs. Result positive.
For a bearish confirmation, the opposite holds true.
Optionally, a higher-timeframe EMA slope filter can gate these confirmations. For example, a bullish confirmation may only be accepted if the higher-timeframe EMA is sloping upward.
Alerts
Users may create alerts based on conditions such as “bullish touch confirmed” or “bearish touch confirmed.”
Alerts can be gated to only fire after bar close, reducing intrabar noise.
Standard alertcondition calls are provided, and optional inline alert() calls can be enabled.
Inputs and Customization
Structure & OB
Swing length: Defines how many bars back to check for BOS.
ATR length & displacement factor: Adjust sensitivity for structural breaks.
Body vs. wick reference: Choose whether zones are based on candle bodies or full ranges.
Invalidation rule: Pick between wick breach or close beyond the level.
Lifespan (bars): Limit how long a zone remains active.
Max keep: Cap the number of zones stored to reduce clutter.
Order-Flow Proxies
Delta mode: Choose between “Close vs Previous Close” or “Body” for delta calculation.
EMA length: Smooths the delta/imbalance series.
Z-score lookback: Defines the averaging window for EvR.
Confirmation thresholds: Adjust the imbalance levels required for long/short confirmation.
Higher Timeframe Filter
Enable HTF gate: Optional filter requiring higher-timeframe EMA slope alignment.
HTF timeframe & EMA length: Configurable for context alignment.
Style
Colors and transparency for bullish and bearish zones.
Border color customization.
Alerts
Enable inline alerts: Optional direct calls to alert().
Alerts on bar close only: Helps avoid multiple firings during bar formation.
Practical Use
This tool is best seen as a way to annotate charts and to study how simple volume-derived signals behave near important structural levels. Some users may:
Observe whether order blocks line up with later price reactions.
Study how imbalance or cumulative delta conditions align with these zones.
Use it in a discretionary workflow to highlight areas of interest for deeper analysis.
Because the proxies are based only on candle OHLCV data, they are approximations. They cannot replace true depth-of-market analysis. Similarly, order block detection here is one specific algorithmic interpretation; other traders may define order blocks differently.
Limitations and Disclaimers
This indicator does not predict future price movement.
It does not access real order book or tick-by-tick data. All signals are derived from bar OHLCV.
Past performance of signals or zones does not guarantee future results.
The script is for educational and informational purposes only. It is not financial advice.
Users should test thoroughly, adjust parameters to their own instruments and timeframes, and use it in combination with broader analysis.
Summary
The Order Blocks + Order-Flow Proxies script is an experimental study tool that:
Detects potential order blocks using a displacement-filtered break of structure.
Marks these zones as boxes that persist until invalidation or expiry.
Provides lightweight order-flow-style proxies such as delta, imbalance, CVD, and effort vs. result.
Allows confirmation of zone touches through these proxies and optional higher-timeframe context.
Offers flexible customization, alerting, and chart-style options.
It is not a trading system by itself but rather a framework for studying price/volume behavior around structurally significant areas. With careful exploration, it can give users new ways to visualize market structure and to understand how simple flow-like measures behave in those contexts.
Order Blocks + Order-Flow ProxiesOrder Blocks + Order-Flow Proxies
This indicator combines structural analysis of order blocks with lightweight order-flow style proxies, providing a tool for chart annotation and contextual study. It is designed to help users visualize where significant structural shifts occur and how simple volume-based signals behave around those areas. The script does not guarantee profitable outcomes, nor does it issue financial advice. It is intended purely for research, learning, and discretionary use.
Conceptual Background
Order Blocks
An “order block” is a term often used to describe a zone on the chart where price left behind a significant reversal or imbalance before continuing strongly in the opposite direction. In practice, this can mean the last bullish or bearish candle before a strong breakout. Traders sometimes study these regions because they believe that unfilled resting orders may exist there, or simply because they mark important pivots in price structure. This indicator detects such moments by scanning for breaks of structure (BOS). When price pushes above or below recent swing levels with sufficient displacement, the script identifies the prior opposite candle as the potential order block.
Break of Structure
A break of structure in this context is defined when the closing price moves beyond the highest high or lowest low of a short lookback window. The script compares the magnitude of this break to an ATR-based displacement filter. This helps ensure that only meaningful moves are marked rather than small, random fluctuations.
Order-Flow Proxies
Traditional order flow analysis may use bid/ask data, footprint charts, or volume profiles. Because TradingView scripts cannot access true order-book data, this indicator instead uses proxy signals derived from standard chart data:
Delta (proxy): Estimated imbalance of buying vs. selling pressure, approximated using bar direction and volume.
Imbalance ratio: Normalizes delta by total volume, ranging between -1 and +1 in theory.
Cumulative Delta (CVD): Running sum of delta over time.
Effort vs. Result (EvR): A comparison between volume and actual bar movement, highlighting cases where large effort produced little result (or vice versa).
These are not real order-flow measurements, but rather simple mathematical constructs that mimic some of its logic.
How the Script Works
Detecting Break of Structure
The user specifies a swing length. When price closes above the recent high (for bullish BOS) or below the recent low (for bearish BOS), a potential shift is recorded.
To qualify, the breakout must exceed a displacement filter proportional to the ATR. This helps filter out weak moves.
Locating the Order Block Candle
Once a BOS is confirmed, the script looks back within a short window to find the last opposite-colored candle.
The high/low or open/close of that candle (depending on user settings) is marked as the potential order block zone.
Drawing and Maintaining Zones
Each order block is represented as a colored rectangle extending forward in time.
Bullish zones are teal by default, bearish zones are red.
Zones extend until invalidated (price closing or wicking beyond them, depending on user preference) or until a user-defined lifespan expires.
A pruning mechanism ensures that only the most recent set number of zones remain, preventing chart overload.
Monitoring Touches
The script checks whether the current bar’s range overlaps any existing order block.
If so, the “closest” zone is considered touched, and a label may appear on the chart.
Confirmation Filters
Touches can optionally be confirmed by order-flow proxies.
For a bullish confirmation, the following must align:
Imbalance ratio above threshold,
Delta EMA positive,
Effort vs. Result positive.
For a bearish confirmation, the opposite holds true.
Optionally, a higher-timeframe EMA slope filter can gate these confirmations. For example, a bullish confirmation may only be accepted if the higher-timeframe EMA is sloping upward.
Alerts
Users may create alerts based on conditions such as “bullish touch confirmed” or “bearish touch confirmed.”
Alerts can be gated to only fire after bar close, reducing intrabar noise.
Standard alertcondition calls are provided, and optional inline alert() calls can be enabled.
Inputs and Customization
Structure & OB
Swing length: Defines how many bars back to check for BOS.
ATR length & displacement factor: Adjust sensitivity for structural breaks.
Body vs. wick reference: Choose whether zones are based on candle bodies or full ranges.
Invalidation rule: Pick between wick breach or close beyond the level.
Lifespan (bars): Limit how long a zone remains active.
Max keep: Cap the number of zones stored to reduce clutter.
Order-Flow Proxies
Delta mode: Choose between “Close vs Previous Close” or “Body” for delta calculation.
EMA length: Smooths the delta/imbalance series.
Z-score lookback: Defines the averaging window for EvR.
Confirmation thresholds: Adjust the imbalance levels required for long/short confirmation.
Higher Timeframe Filter
Enable HTF gate: Optional filter requiring higher-timeframe EMA slope alignment.
HTF timeframe & EMA length: Configurable for context alignment.
Style
Colors and transparency for bullish and bearish zones.
Border color customization.
Alerts
Enable inline alerts: Optional direct calls to alert().
Alerts on bar close only: Helps avoid multiple firings during bar formation.
Practical Use
This tool is best seen as a way to annotate charts and to study how simple volume-derived signals behave near important structural levels. Some users may:
Observe whether order blocks line up with later price reactions.
Study how imbalance or cumulative delta conditions align with these zones.
Use it in a discretionary workflow to highlight areas of interest for deeper analysis.
Because the proxies are based only on candle OHLCV data, they are approximations. They cannot replace true depth-of-market analysis. Similarly, order block detection here is one specific algorithmic interpretation; other traders may define order blocks differently.
Limitations and Disclaimers
This indicator does not predict future price movement.
It does not access real order book or tick-by-tick data. All signals are derived from bar OHLCV.
Past performance of signals or zones does not guarantee future results.
The script is for educational and informational purposes only. It is not financial advice.
Users should test thoroughly, adjust parameters to their own instruments and timeframes, and use it in combination with broader analysis.
Summary
The Order Blocks + Order-Flow Proxies script is an experimental study tool that:
Detects potential order blocks using a displacement-filtered break of structure.
Marks these zones as boxes that persist until invalidation or expiry.
Provides lightweight order-flow-style proxies such as delta, imbalance, CVD, and effort vs. result.
Allows confirmation of zone touches through these proxies and optional higher-timeframe context.
Offers flexible customization, alerting, and chart-style options.
It is not a trading system by itself but rather a framework for studying price/volume behavior around structurally significant areas. With careful exploration, it can give users new ways to visualize market structure and to understand how simple flow-like measures behave in those contexts.
Relative Volatility Mass [SciQua]The ⚖️ Relative Volatility Mass (RVM) is a volatility-based tool inspired by the Relative Volatility Index (RVI) .
While the RVI measures the ratio of upward to downward volatility over a period, RVM takes a different approach:
It sums the standard deviation of price changes over a rolling window, separating upward volatility from downward volatility .
The result is a measure of the total “volatility mass” over a user-defined period, rather than an average or normalized ratio.
This makes RVM particularly useful for identifying sustained high-volatility conditions without being diluted by averaging.
────────────────────────────────────────────────────────────
╭────────────╮
How It Works
╰────────────╯
1. Standard Deviation Calculation
• Computes the standard deviation of the chosen `Source` over a `Standard Deviation Length` (`stdDevLen`).
2. Directional Separation
• Volatility on up bars (`chg > 0`) is treated as upward volatility .
• Volatility on down bars (`chg < 0`) is treated as downward volatility .
3. Rolling Sum
• Over a `Sum Length` (`sumLen`), the upward and downward volatilities are summed separately using `math.sum()`.
4. Relative Volatility Mass
• The two sums are added together to get the total volatility mass for the rolling window.
Formula:
RVM = Σ(σ up) + Σ(σ down)
where σ is the standard deviation over `stdDevLen`.
╭────────────╮
Key Features
╰────────────╯
Directional Volatility Tracking – Differentiates between volatility during price advances vs. declines.
Rolling Volatility Mass – Shows the total standard deviation accumulation over a given period.
Optional Smoothing – Multiple MA types, including SMA, EMA, SMMA (RMA), WMA, VWMA.
Bollinger Band Overlay – Available when SMA is selected, with adjustable standard deviation multiplier.
Configurable Source – Apply RVM to `close`, `open`, `hl2`, or any custom source.
╭─────╮
Usage
╰─────╯
Trend Confirmation: High RVM values can confirm strong trending conditions.
Breakout Detection: Spikes in RVM often precede or accompany price breakouts.
Volatility Cycle Analysis: Compare periods of contraction and expansion.
RVM is not bounded like the RVI, so absolute values depend on market volatility and chosen parameters.
Consider normalizing or using smoothing for easier visual comparison.
╭────────────────╮
Example Settings
╰────────────────╯
Short-term volatility detection: `stdDevLen = 5`, `sumLen = 10`
Medium-term trend volatility: `stdDevLen = 14`, `sumLen = 20`
Enable `SMA + Bollinger Bands` to visualize when volatility is unusually high or low relative to recent history.
╭───────────────────╮
Notes & Limitations
╰───────────────────╯
Not a directional signal by itself — use alongside price structure, volume, or other indicators.
Higher `sumLen` will smooth short-term fluctuations but reduce responsiveness.
Because it sums, not averages, values will scale with both volatility and chosen window size.
╭───────╮
Credits
╰───────╯
Based on the Relative Volatility Index concept by Donald Dorsey (1993).
TradingView
SciQua - Joshua Danford
Renko Price TrackerRenko Sequential Signal – qLine + Moneyball Confirmation
This indicator is designed for Renko chart traders who want to combine price action relative to a key line (qLine) with Moneyball buy/sell signals as a confirmation. It helps filter trades so you only get signals when both conditions align within a chosen time window.
How It Works
First Event – Price Trigger
Detects when the Renko close crosses above/below your selected qLine plot from the qPro indicator.
You can choose between:
Cross – only triggers on an actual crossover/crossunder.
State (Close) – triggers whenever price closes above/below qLine.
Second Event – Moneyball Confirmation
Waits for Moneyball’s Buy Signal (for long) or Bear/Sell Signal (for short) plot to fire.
You select the exact Moneyball plot from the source menu.
You can specify how the Moneyball signal is interpreted (== 1, >= 1, or any nonzero value).
Sequential Logic
The Moneyball signal must occur within N Renko bricks after the price event.
The final buy/sell signal is printed on the Moneyball bar.
Key Features
Works natively on Renko charts.
Adjustable confirmation window (0–5 bricks).
Flexible detection for both qLine and Moneyball signals.
Customizable label sizes, arrow display, and alerts.
Alerts fire for both buy and sell conditions:
BUY: qLine ➜ Moneyball Buy
SELL: qLine ➜ Moneyball Sell
Inputs
qLine Source – Pick the qPro qLine plot.
Price Event Type – Cross or State.
Moneyball Buy/Sell Signal Plots – Select the correct plots from your Moneyball indicator.
Confirmation Window – Bars allowed between events.
Visual Settings – Label size, arrow visibility, etc.
Use Case
Ideal for traders who:
Want a double-confirmation entry system.
Use Renko charts for cleaner trend detection.
Already have qPro and Moneyball loaded, but want an automated, rule-based confluence check.
Fibonacci Sequence Moving Average [BackQuant]Fibonacci Sequence Moving Average with Adaptive Oscillator
1. Overview
The Fibonacci Sequence Moving Average indicator is a two‑part trading framework that combines a custom moving average built from the famous Fibonacci number set with a fully featured oscillator, normalisation engine and divergence suite. The moving average half delivers an adaptive trend line that respects natural market rhythms, while the oscillator half translates that trend information into a bounded momentum stream that is easy to read, easy to compare across assets and rich in confluence signals. Everything from weighting logic to colour palettes can be customised, so the tool comfortably fits scalpers zooming into one‑minute candles as well as position traders running multi‑month trend following campaigns.
2. Core Calculation
Fibonacci periods – The default length array is 5, 8, 13, 21, 34. A single multiplier input lets you scale the whole family up or down without breaking the golden‑ratio spacing. For example a multiplier of 3 yields 15, 24, 39, 63, 102.
Component averages – Each period is passed through Simple Moving Average logic to produce five baseline curves (ma1 through ma5).
Weighting methods – You decide how those five values are blended:
• Equal weighting treats every curve the same.
• Linear weighting applies factors 1‑to‑5 so the slowest curve counts five times as much as the fastest.
• Exponential weighting doubles each step for a fast‑reacting yet still smooth line.
• Fibonacci weighting multiplies each curve by its own period value, honouring the spirit of ratio mathematics.
Smoothing engine – The blended average is then smoothed a second time with your choice of SMA, EMA, DEMA, TEMA, RMA, WMA or HMA. A short smoothing length keeps the result lively, while longer lengths create institution‑grade glide paths that act like dynamic support and resistance.
3. Oscillator Construction
Once the smoothed Fib MA is in place, the script generates a raw oscillator value in one of three flavours:
• Distance – Percentage distance between price and the average. Great for mean‑reversion.
• Momentum – Percentage change of the average itself. Ideal for trend acceleration studies.
• Relative – Distance divided by Average True Range for volatility‑aware scaling.
That raw series is pushed through a look‑back normaliser that rescales every reading into a fixed −100 to +100 window. The normalisation window defaults to 100 bars but can be tightened for fast markets or expanded to capture long regimes.
4. Visual Layer
The oscillator line is gradient‑coloured from deep red through sky blue into bright green, so you can spot subtle momentum shifts with peripheral vision alone. There are four horizontal guide lines: Extreme Bear at −50, Bear Threshold at −20, Bull Threshold at +20 and Extreme Bull at +50. Soft fills above and below the thresholds reinforce the zones without cluttering the chart.
The smoothed Fib MA can be plotted directly on price for immediate trend context, and each of the five component averages can be revealed for educational or research purposes. Optional bar‑painting mirrors oscillator polarity, tinting candles green when momentum is bullish and red when momentum is bearish.
5. Divergence Detection
The script automatically looks for four classes of divergences between price pivots and oscillator pivots:
Regular Bullish, signalling a possible bottom when price prints a lower low but the oscillator prints a higher low.
Hidden Bullish, often a trend‑continuation cue when price makes a higher low while the oscillator slips to a lower low.
Regular Bearish, marking potential tops when price carves a higher high yet the oscillator steps down.
Hidden Bearish, hinting at ongoing downside when price posts a lower high while the oscillator pushes to a higher high.
Each event is tagged with an ℝ or ℍ label at the oscillator pivot, colour‑coded for clarity. Look‑back distances for left and right pivots are fully adjustable so you can fine‑tune sensitivity.
6. Alerts
Five ready‑to‑use alert conditions are included:
• Bullish when the oscillator crosses above +20.
• Bearish when it crosses below −20.
• Extreme Bullish when it pops above +50.
• Extreme Bearish when it dives below −50.
• Zero Cross for momentum inflection.
Attach any of these to TradingView notifications and stay updated without staring at charts.
7. Practical Applications
Swing trading trend filter – Plot the smoothed Fib MA on daily candles and only trade in its direction. Enter on oscillator retracements to the 0 line.
Intraday reversal scouting – On short‑term charts let Distance mode highlight overshoots beyond ±40, then fade those moves back to mean.
Volatility breakout timing – Use Relative mode during earnings season or crypto news cycles to spot momentum surges that adjust for changing ATR.
Divergence confirmation – Layer the oscillator beneath price structure to validate double bottoms, double tops and head‑and‑shoulders patterns.
8. Input Summary
• Source, Fibonacci multiplier, weighting method, smoothing length and type
• Oscillator calculation mode and normalisation look‑back
• Divergence look‑back settings and signal length
• Show or hide options for every visual element
• Full colour and line width customisation
9. Best Practices
Avoid using tiny multipliers on illiquid assets where the shortest Fibonacci window may drop under three bars. In strong trends reduce divergence sensitivity or you may see false counter‑trend flags. For portfolio scanning set oscillator to Momentum mode, hide thresholds and colour bars only, which turns the indicator into a heat‑map that quickly highlights leaders and laggards.
10. Final Notes
The Fibonacci Sequence Moving Average indicator seeks to fuse the mathematical elegance of the golden ratio with modern signal‑processing techniques. It is not a standalone trading system, rather a multi‑purpose information layer that shines when combined with market structure, volume analysis and disciplined risk management. Always test parameters on historical data, be mindful of slippage and remember that past performance is never a guarantee of future results. Trade wisely and enjoy the harmony of Fibonacci mathematics in your technical toolkit.
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
Normalized Open InterestNormalized Open Interest (nOI) — Indicator Overview
What it does
Normalized Open Interest (nOI) transforms raw futures open-interest data into a 0-to-100 oscillator, so you can see at a glance whether participation is unusually high or low—similar in spirit to an RSI but applied to open interest. The script positions today’s OI inside a rolling high–low range and paints it with contextual colours.
Core logic
Data source – Loads the built-in “_OI” symbol that TradingView provides for the current market.
Rolling range – Looks back a user-defined number of bars (default 500) to find the highest and lowest OI in that window.
Normalization – Calculates
nOI = (OI – lowest) / (highest – lowest) × 100
so 0 equals the minimum of the window and 100 equals the maximum.
Visual cues – Plots the oscillator plus fixed horizontal levels at 70 % and 30 % (or your own numbers). The line turns teal above the upper level, red below the lower, and neutral grey in between.
User inputs
Window Length (bars) – How many candles the indicator scans for the high–low range; larger numbers smooth the curve, smaller numbers make it more reactive.
Upper Threshold (%) – Default 70. Anything above this marks potentially crowded or overheated interest.
Lower Threshold (%) – Default 30. Anything below this marks low or capitulating interest.
Practical uses
Spot extremes – Values above the upper line can warn that the long side is crowded; values below the lower line suggest disinterest or short-side crowding.
Confirm breakouts – A price breakout backed by a sharp rise in nOI signals genuine engagement.
Look for divergences – If price makes a new high but nOI does not, participation might be fading.
Combine with volume or RSI – Layer nOI with other studies to filter false signals.
Tips
On intraday charts for non-crypto symbols the script automatically fetches daily OI data to avoid gaps.
Adjust the thresholds to 80/20 or 60/40 to fit your market and risk preferences.
Alerts, shading, or additional signal logic can be added easily because the oscillator is already normalised.
CGMALibrary "CGMA"
This library provides a function to calculate a moving average based on Chebyshev-Gauss Quadrature. This method samples price data more intensely from the beginning and end of the lookback window, giving it a unique character that responds quickly to recent changes while also having a long "memory" of the trend's start. Inspired by reading rohangautam.github.io
What is Chebyshev-Gauss Quadrature?
It's a numerical method to approximate the integral of a function f(x) that is weighted by 1/sqrt(1-x^2) over the interval . The approximation is a simple sum: ∫ f(x)/sqrt(1-x^2) dx ≈ (π/n) * Σ f(xᵢ) where xᵢ are special points called Chebyshev nodes.
How is this applied to a Moving Average?
A moving average can be seen as the "mean value" of the price over a lookback window. The mean value of a function with the Chebyshev weight is calculated as:
Mean = /
The math simplifies beautifully, resulting in the mean being the simple arithmetic average of the function evaluated at the Chebyshev nodes:
Mean = (1/n) * Σ f(xᵢ)
What's unique about this MA?
The Chebyshev nodes xᵢ are not evenly spaced. They are clustered towards the ends of the interval . We map this interval to our lookback period. This means the moving average samples prices more intensely from the beginning and the end of the lookback window, and less intensely from the middle. This gives it a unique character, responding quickly to recent changes while also having a long "memory" of the start of the trend.
Volatility Bias ModelVolatility Bias Model
Overview
Volatility Bias Model is a purely mathematical, non-indicator-based trading system that detects directional probability shifts during high volatility market phases. Rather than relying on classic tools like RSI or moving averages, this strategy uses raw price behavior and clustering logic to determine potential breakout direction based on recent market bias.
How It Works
Over a defined lookback window (default 10 bars), the strategy counts how many candles closed in the same direction (i.e., bullish or bearish).
Simultaneously, it calculates the price range during that window.
If volatility is above a minimum threshold and a clear directional bias is detected (e.g., >60% of closes are bullish), a trade is opened in the direction of that bias.
This approach assumes that when high volatility is coupled with directional closing consistency, the market is probabilistically more likely to continue in that direction.
ATR-based stop-loss and take-profit levels are applied, and trades auto-exit after 20 bars if targets are not hit.
Key Features
- 100% non-indicator-based logic
- Statistically-driven directional bias detection
- Works across all timeframes (1H, 4H, 1D)
- ATR-based risk management
- No pyramiding, slippage and commissions included
- Compatible with real-world backtesting conditions
Realism & Assumptions
To make this strategy more aligned with actual trading environments, it includes 0.05% commission per trade and a 1-point slippage on every entry and exit.
Additionally, position sizing is set at 10% of a $10,000 starting capital, and no pyramiding is allowed.
These assumptions help avoid unrealistic backtest results and make the performance metrics more representative of live conditions.
Parameter Explanation
Bias Window (10 bars): Number of past candles used to evaluate directional closings
Bias Threshold (0.60): Required ratio of same-direction candles to consider a bias valid
Minimum Range (1.5%): Ensures the market is volatile enough to avoid noise
ATR Length (14): Used to dynamically define stop-loss and target zones
Risk-Reward Ratio (2.0): Take-profit is set at twice the stop-loss distance
Max Holding Bars (20): Trades are closed automatically after 20 bars to prevent stagnation
Originality Note
Unlike common strategies based on oscillators or moving averages, this script is built on pure statistical inference. It models the market as a probabilistic process and identifies directional intent based on historical closing behavior, filtered by volatility. This makes it a non-linear, adaptive model grounded in real-world price structure — not traditional technical indicators.
Disclaimer
This strategy is for educational and experimental purposes only. It does not constitute financial advice. Always perform your own analysis and test thoroughly before applying with real capital.
Real Time Swing Trap DetectorThe Real Time Swing Trap Detector is a minimalist, pro-grade tool for instantly spotting classic “bull traps” and “bear traps” on any chart.
This indicator identifies swing traps in real time by tracking significant swing highs and lows, then watching for fast, false breakouts (bull traps) and breakdowns (bear traps) within a user-defined window.
How it works:
Detects when price breaks a major swing high/low (using configurable lookback).
If price quickly reclaims the broken level within X bars (trap window), a trap is confirmed and a subtle icon (🐂 for bull, 🐻 for bear) is displayed on the chart—no labels, no clutter.
You can enable/disable alerts for bull/bear traps individually or together, and receive notifications the moment a trap is detected.
Use cases:
Spot and avoid classic market “fakeouts” that trap breakout traders.
Confirm SMC/ICT “Judas swing” setups, or filter for high-probability reversals.
Works on all timeframes and assets: stocks, crypto, forex, indices.
Inputs:
Swing Lookback Bars: How far back to define swing points (default: 50)
Major Swing Filter: Additional filter for only the most significant highs/lows (default: 200)
Trap Bars (Look Ahead): Window in which a trap must be confirmed (default: 10)
Enable Bull/Bear Trap Alerts: Toggle real-time alerts for each trap type.
Visuals:
🐻 icon below bar for bear trap (short squeeze/reversal)
🐂 icon above bar for bull trap (long squeeze/reversal)
How to set up alerts:
Add the indicator to your chart, open TradingView’s Alerts panel, and choose “Bear Trap Alert,” “Bull Trap Alert,” or “Any Trap Alert” for instant notifications.
Market Manipulation Index (MMI)The Composite Manipulation Index (CMI) is a structural integrity tool that quantifies how chaotic or orderly current market conditions are, with the aim of detecting potentially manipulated or unstable environments. It blends two distinct mathematical models that assess price behavior in terms of both structural rhythm and predictability.
1. Sine-Fit Deviation Model:
This component assumes that ideal, low-manipulation price behavior resembles a smooth oscillation, such as a sine wave. It generates a synthetic sine wave using a user-defined period and compares it to actual price movement over an adaptive window. The error between the real price and this synthetic wave—normalized by price variance—forms the Sine-Based Manipulation Index. A high error indicates deviation from natural rhythm, suggesting structural disorder.
2. Predictability-Based Model:
The second component estimates how well current price can be predicted using recent price lags. A two-variable rolling linear regression is computed between the current price and two lagged inputs (close and close ). If the predicted price diverges from the actual price, this error—also normalized by price variance—reflects unpredictability. High prediction error implies a more manipulated or erratic environment.
3. Adaptive Mechanism:
Both components are calculated using an adaptive smoothing window based on the Average True Range (ATR). This allows the indicator to respond proportionally to market volatility. During high volatility, the analysis window expands to avoid over-sensitivity; during calm periods, it contracts for better responsiveness.
4. Composite Output:
The two normalized metrics are averaged to form the final CMI value, which is then optionally smoothed further. The output is scaled between 0 and 1:
0 indicates a highly structured, orderly market.
1 indicates complete structural breakdown or randomness.
Suggested Interpretation:
CMI < 0.3: Market is clean and structured. Trend-following or breakout strategies may perform better.
CMI > 0.7: Market is structurally unstable. Choppy price action, fakeouts, or manipulative behavior may dominate.
CMI 0.3–0.7: Transitional zone. Caution or reduced risk may be warranted.
This indicator is designed to serve as a contextual filter, helping traders assess whether current market conditions are conducive to structured strategies, or if discretion and defense are more appropriate.
PumpC Opening Range Breakout (ORB) 5min Range📄 PumpC ORB 5-Minute Opening Range Breakout Indicator
✨ Overview
The PumpC ORB 5-Minute Opening Range Breakout indicator captures early session price action by tracking the high, low, and open of a defined 5-minute window at market open (customized for Futures or Stocks).
It plots breakout levels, extension targets, average range calculations, volume tracking, and provides visual and table-based data summaries.
This indicator is designed for traders seeking a complete, clean visualization of Opening Range Breakouts (ORB) with flexible customization.
⚙️ Main Features
Opening Range Box (ORB Box) Draws a box around the high and low of the first 5-minute session (8:30–8:35 ET for Futures, 9:30–9:35 ET for Stocks). Box extends from the session open to the session close (4:00 PM ET). Option to enable/disable historical boxes. Box color and opacity are customizable. Core ORB Levels Open Level: Plots the open price of the 5-minute ORB window. ORB Levels: Plots breakout levels at multiples: +0.5x the range +1.5x the range (customizable factor) Each level has independent color settings and visibility toggles. Option to show or hide historic extension levels. Table Display Compact table in the top-right corner showing: ORB ATR (average range) ORB ATR in ticks Today's ORB range ORB Volume ATR (average volume during ORB) Today's ORB Volume Volume is formatted automatically into "K" (thousands) or "M" (millions) for readability. Background Highlights After the ORB window closes: Blue highlight if today's ORB range is greater than the 10-day ATR average. Orange highlight if today's ORB range is smaller than the 10-day ATR average. Helps quickly assess relative strength or weakness compared to historical behavior. Alerts Breakout Confirmations: Fires when price closes above ORB High or below ORB Low. Fallout Traps: Alerts when price wick crosses ORB High/Low but closes back inside the range. Alerts use clean titles and simple messages for easy identification.
🔧 Inputs and Customization
Mode Toggle: Choose between Futures (8:30 ET open) or Stocks (9:30 ET open). Show/Hide Labels: Control label visibility for ORB and extension levels. Line Width Control: Customize thickness for ORB lines and extension levels. ORB Level Level Visibility: Independently enable or disable each extension line. Table Appearance: Customize table background color, font color, and padding. ORB Box Settings: Customize box color and control whether historical boxes are drawn.
📚 How to Use
Select Mode: Choose Futures or Stocks depending on your instrument. Observe the Opening Range: Focus on the ORB High and ORB Low during the first 5 minutes after the open. Monitor Breakouts: Breakout alerts will fire when price closes outside the ORB range, signaling potential continuation. Watch for Fallout Traps: Fallout alerts signal when price briefly wicks above/below but closes back inside the ORB range. Use Table Metrics: Instantly compare today's ORB range and volume versus historical averages to assess session strength or weakness.
🛡️ Notes
Best used on the 1-minute or 5-minute chart for intraday trading. Ensure your TradingView chart time zone is set to New York for correct functioning. Alerts must be manually configured after adding the indicator to your chart.
Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
RSI SiaThis script is a custom indicator for TradingView written in Pine Script version 5. It calculates the Relative Strength Index (RSI) and uses it to generate trading signals. Here's a breakdown of what the script does:
Key Features:
RSI Calculation:
The script calculates the RSI using a 14-period window.
It also calculates the momentum of the RSI over a 9-period window (rsi delta) and a simple moving average (SMA) of the RSI over a 3-period window (rsi sma).
Composite Index (CI):
The composite index is calculated as the sum of rsi delta and rsi sma.
Horizontal Lines and Zones:
Several horizontal lines are plotted at different levels (e.g., 20, 40, 60, 80, 120, 150, 180) to indicate overbought and oversold conditions.
Filled zones are created between certain levels to highlight areas of interest.
Moving Averages:
The script plots SMA and EMA of the RSI when Enable RSI ma is set to true.
It also plots moving averages of the composite index.
Crossover Signals:
The script detects bullish and bearish crossovers between the SMA and EMA of the RSI.
It plots shapes (labels) on the chart to indicate buy (BUY) and sell (SELL) signals based on these crossovers.
Usage:
Enable RSIma: This input allows you to enable or disable the plotting of RSI moving averages.
i1: This variable is used to adjust the vertical position of the composite index and its moving averages.
Visualization:
The RSI is plotted in black.
The RSI fast trigger line (SMA of RSI) is plotted in green when enabled.
The RSI slow trigger line (EMA of RSI) is plotted in orange when enabled.
The composite index and its moving averages are plotted in red, green, and orange.
Buy and sell signals are indicated with green and red labels, respectively.
This script can be used to identify potential trading opportunities based on RSI crossovers and the composite index.
volume profile ranking indicator📌 Introduction
This script implements a volume profile ranking indicato for TradingView. It is designed to visualize the distribution of traded volume over price levels within a defined historical window. Unlike TradingView’s built-in Volume Profile, this script gives full customization of the profile drawing logic, binning, color gradient, and the ability to anchor the profile to a specific date.
⚙️ How It Works (Logic)
1. Inputs
➤POC Lookback Days (lookback): Defines how many bars (days) to look back from a selected point to calculate the volume distribution.
➤Bin Count (bin_count): Determines how many price bins (horizontal levels) the price range will be divided into.
➤Use Custom Lookback Date (useCustomDate): Enables/disables manually selecting a backtest start date.
➤Custom Lookback Date (customDate): When enabled, the profile will calculate volume based on this date instead of the most recent bar.
2. Target Bar Determination
➤If a custom date is selected, the script searches for the bar closest to that date within 1000 bars.
➤If not, it defaults to the latest bar (bar_index).
➤The profile is drawn only when the current bar is close to the target bar (within ±2 bars), to avoid unnecessary recalculations and performance issues.
3. Volume Binning
➤The price range over the lookback window is divided into bin_count segments.
➤For each bar within the lookback window, its volume is added to the appropriate bin based on price.
➤If the price falls outside the expected range, it is clamped to the first or last bin.
4. Ranking and Sorting
➤A bubble sort ranks each bin by total volume.
➤The most active bin (POC, or Point of Control) is highlighted with a thicker bar.
5. Rendering
➤Horizontal bars (line.new) represent volume intensity in each price bin.
➤Each bar is color-coded by volume heat: more volume = more intense color.
➤Labels (label.new) show:
➤Total volume
➤Rank
➤Percentage of total volume
➤Price range of the bin
🧑💻 How to Use
1. Add the Script to Your Chart
➤Copy the code into TradingView’s Pine Script editor and add it to your chart.
2. Set Lookback Period
➤Default is 252 bars (about one year for daily charts), but can be changed via the input.
3. (Optional) Use Custom Date
●Toggle "Use Custom Lookback Date" to true.
➤Pick a date in the "Custom Lookback Date" input to anchor the profile.
4. Analyze the Volume Distribution
➤The longest (thickest) red/orange bar represents the Point of Control (POC) — the price with the most volume traded.
➤Other bars show volume distribution across price.
➤Labels display useful metrics to evaluate areas of high/low interest.
✅ Features
🔶 Customizable anchor point (custom date).
🔶Adjustable bin count and lookback length.
🔶 Clear visualization with heatmap coloring.
🔶 Lightweight and performance-optimized (especially with the shouldDrawProfile filter)
SnowdexUtilsLibrary "SnowdexUtils"
the various function that often use when create a strategy trading.
f_backtesting_date(train_start_date, train_end_date, test_date, deploy_date)
Backtesting within a specific window based on deployment and testing dates.
Parameters:
train_start_date (int) : the start date for training the strategy.
train_end_date (int) : the end date for training the strategy.
test_date (bool) : if true, backtests within the period from `train_end_date` to the current time.
deploy_date (bool) : if true, the strategy backtests up to the current time.
Returns: given time falls within the specified window for backtesting.
f_init_ma(ma_type, source, length)
Initializes a moving average based on the specified type.
Parameters:
ma_type (simple string) : the type of moving average (e.g., "RMA", "EMA", "SMA", "WMA").
source (float) : the input series for the moving average calculation.
length (simple int) : the length of the moving average window.
Returns: the calculated moving average value.
f_init_tp(side, entry_price, rr, sl_open_position)
Calculates the target profit based on entry price, risk-reward ratio, and stop loss. The formula is `tp = entry price + (rr * (entry price - stop loss))`.
Parameters:
side (bool) : the trading side (true for long, false for short).
entry_price (float) : the entry price of the position.
rr (float) : the risk-reward ratio.
sl_open_position (float) : the stop loss price for the open position.
Returns: the calculated target profit value.
f_round_up(number, decimals)
Rounds up a number to a specified number of decimals.
Parameters:
number (float)
decimals (int)
Returns: The rounded-up number.
f_get_pip_size()
Calculates the pip size for the current instrument.
Returns: Pip size adjusted for Forex instruments or 1 for others.
f_table_get_position(value)
Maps a string to a table position constant.
Parameters:
value (string) : String representing the desired position (e.g., "Top Right").
Returns: The corresponding position constant or `na` for invalid values.
Bjorgum Double Tap█ OVERVIEW
Double Tap is a pattern recognition script aimed at detecting Double Tops and Double Bottoms. Double Tap can be applied to the broker emulator to observe historical results, run as a trading bot for live trade alerts in real time with entry signals, take profit, and stop orders, or to simply detect patterns.
█ CONCEPTS
How Is A Pattern Defined?
Doubles are technical formations that are both reversal patterns and breakout patterns. These formations typically have a distinctive “M” or a “W” shape with price action breaking beyond the neckline formed by the center of the pattern. They can be recognized when a pivot fails to break when tested for a second time and the retracement that follows breaks beyond the key level opposite. This can trap entrants that were playing in the direction of the prior trend. Entries are made on the breakout with a target projected beyond the neckline equal to the height of the pattern.
Pattern Recognition
Patterns are recognized through the use of zig-zag; a method of filtering price action by connecting swing highs and lows in an alternating fashion to establish trend, support and resistance, or derive shapes from price action. The script looks for the highest or lowest point in a given number of bars and updates a list with the values as they form. If the levels are exceeded, the values are updated. If the direction changes and a new significant point is made, a new point is added to the list and the process starts again. Meanwhile, we scan the list of values looking for the distinctive shape to form as previously described.
█ STRATEGY RESULTS
Back Testing
Historical back testing is the most common method to test a strategy due in part to the general ease of gathering quick results. The underlying theory is that any strategy that worked well in the past is likely to work well in the future, and conversely, any strategy that performed poorly in the past is likely to perform poorly in the future. It is easy to poke holes in this theory, however, as for one to accept it as gospel, one would have to assume that future results will match what has come to pass. The randomness of markets may see to it otherwise, so it is important to scrutinize results. Some commonly used methods are to compare to other markets or benchmarks, perform statistical analysis on the results over many iterations and on differing datasets, walk-forward testing, out-of-sample analysis, or a variety of other techniques. There are many ways to interpret the results, so it is important to do research and gain knowledge in the field prior to taking meaningful conclusions from them.
👉 In short, it would be naive to place trust in one good backtest and expect positive results to continue. For this reason, results have been omitted from this publication.
Repainting
Repainting is simply the difference in behaviour of a strategy in real time vs the results calculated on the historical dataset. The strategy, by default, will wait for confirmed signals and is thus designed to not repaint. Waiting for bar close for entires aligns results in the real time data feed to those calculated on historical bars, which contain far less data. By doing this we align the behaviour of the strategy on the 2 data types, which brings significance to the calculated results. To override this behaviour and introduce repainting one can select "Recalculate on every tick" from the properties tab. It is important to note that by doing this alerts may not align with results seen in the strategy tester when the chart is reloaded, and thus to do so is to forgo backtesting and restricts a strategy to forward testing only.
👉 It is possible to use this script as an indicator as opposed to a full strategy by disabling "Use Strategy" in the "Inputs" tab. Basic alerts for detection will be sent when patterns are detected as opposed to complex order syntax. For alerts mid-bar enable "Recalculate on every tick" , and for confirmed signals ensure it is disabled.
█ EXIT ORDERS
Limit and Stop Orders
By default, the strategy will place a stop loss at the invalidation point of the pattern. This point is beyond the pattern high in the case of Double Tops, or beneath the pattern low in the case of Double Bottoms. The target or take profit point is an equal-legs measurement, or 100% of the pattern height in the direction of the pattern bias. Both the stop and the limit level can be adjusted from the user menu as a percentage of the pattern height.
Trailing Stops
Optional from the menu is the implementation of an ATR based trailing stop. The trailing stop is designed to begin when the target projection is reached. From there, the script looks back a user-defined number of bars for the highest or lowest point +/- the ATR value. For tighter stops the user can look back a lesser number of bars, or decrease the ATR multiple. When using either Alertatron or Trading Connector, each change in the trail value will trigger an alert to update the stop order on the exchange to reflect the new trail price. This reduces latency and slippage that can occur when relying on alerts only as real exchange orders fill faster and remain in place in the event of a disruption in communication between your strategy and the exchange, which ensures a higher level of safety.
👉 It is important to note that in the case the trailing stop is enabled, limit orders are excluded from the exit criteria. Rather, the point in time that the limit value is exceeded is the point that the trail begins. As such, this method will exit by stop loss only.
█ ALERTS
Five Built-in 3rd Party Destinations
The following are five options for delivering alerts from Double Tap to live trade execution via third party API solutions or chat bots to share your trades on social media. These destinations can be selected from the input menu and alert syntax will automatically configure in alerts appropriately to manage trades.
Custom JSON
JSON, or JavaScript Object Notation, is a readable format for structuring data. It is used primarily to transmit data between a server and a web application. In regards to this script, this may be a custom intermediary web application designed to catch alerts and interface with an exchange API. The JSON message is a trade map for an application to read equipped with where its been, where its going, targets, stops, quantity; a full diagnostic of the current state and its previous state. A web application could be configured to follow the messages sent in this format and conduct trades in sync with alerts running on the TV server.
Below is an example of a rendered JSON alert:
{
"passphrase": "1234",
"time": "2022-05-01T17:50:05Z",
"ticker": "ETHUSDTPERP",
"plot": {
"stop_price": 2600.15,
"limit_price": 3100.45
},
"strategy": {
"position_size": 0.1,
"order_action": "buy",
"market_position": "long",
"market_position_size": 0,
"prev_market_position": "flat",
"prev_market_position_size": 0
}
}
Trading Connector
Trading Connector is a third party fully autonomous Chrome extension designed to catch alert webhooks from TradingView and interface with MT4/MT5 to execute live trades from your machine. Alerts to Trading Connector are simple; just select the destination from the input drop down menu, set your ticker in the "TC Ticker" box in the "Alert Strings" section and enter your URL in the alert window when configuring your alert.
Alertatron
Alertatron is an automated algo platform for cryptocurrency trading that is designed to automate your trading strategies. Although the platform is currently restricted to crypto, it offers a versatile interface with high flexibility syntax for complex market orders and conditions. To direct alerts to Alertatron, select the platform from the 3rd party drop down, configure your API key in the ”Alertatron Key” box and add your URL in the alert message box when making alerts.
3 Commas
3 Commas is an easy and quick to use click-and-go third party crypto API solution. Alerts are simple without overly complex syntax. Messages are simply pasted into alerts and executed as alerts are triggered. There are 4 boxes at the bottom of the "Inputs" tab where the appropriate messages to be placed. These messages can be copied from 3 Commas after the bots are set up and pasted directly into the settings menu. Remember to select 3 Commas as a destination from the third party drop down and place the appropriate URL in the alert message window.
Discord
Some may wish to share their trades with their friends in a Discord chat via webhook chat bot. Messages are configured to notify of the pattern type with targets and stop values. A bot can be configured through the integration menu in a Discord chat to which you have appropriate access. Select Discord from the 3rd party drop down menu and place your chat bot URL in the alert message window when configuring alerts.
👉 For further information regarding alert setup, refer to the platform specific instructions given by the chosen third party provider.
█ IMPORTANT NOTES
Setting Alerts
For alert messages to be properly delivered on order fills it is necessary to place the following placeholder in the alert message box when creating an alert.
{{strategy.order.alert_message}}
This placeholder will auto-populate the alert message with the appropriate syntax that is designated for the 3rd party selected in the user menu.
Order Sizing and Commissions
The values that are sent in alert messages are populated from live metrics calculated by the strategy. This means that the actual values in the "Properties" tab are used and must be set by the user. The initial capital, order size, commission, etc. are all used in the calculations, so it is important to set these prior to executing live trades. Be sure to set the commission to the values used by the exchange as well.
👉 It is important to understand that the calculations on the account size take place from the beginning of the price history of the strategy. This means that if historical results have inflated or depleted the account size from the beginning of trade history until now, the values sent in alerts will reflect the calculated size based on the inputs in the "Properties" tab. To start fresh, the user must set the date in the "Inputs" tab to the current date as to remove trades from the trade history. Failure to follow this instruction can result in an unexpected order size being sent in the alert.
█ FOR PINECODERS
• With the recent introduction of matrices in Pine, the script utilizes a matrix to track pivot points with the bars they occurred on, while tracking if that pivot has been traded against to prevent duplicate detections after a trade is exited.
• Alert messages are populated with placeholders ; capability that previously was only possible in alertcondition() , but has recently been extended to `strategy.*()` functions for use in the `alert_message` argument. This allows delivery of live trade values to populate in strategy alert messages.
• New arguments have been added to strategy.exit() , which allow differentiated messages to be sent based on whether the exit occurred at the stop or the limit. The new arguments used in this script are `alert_profit` and `alert_loss` to send messages to Discord
