CDZV Enhanced Coppock CurveThis indicator is a part of the CDZV toolkit (backtesting and automation)
The Enhanced Coppock Curve is an upgraded version of the classic Coppock Curve indicator. It incorporates several additional features for greater flexibility and analysis capabilities. This indicator is used to analyze market trends by plotting a weighted moving average (WMA) of the sum of two Rate of Change (ROC) values.
Key Features of the Indicator:
Base Calculation of the Coppock Curve:
The Coppock Curve is calculated as a weighted moving average (WMA) of the sum of two ROC values (long and short periods).
The source for the calculation is customizable (default is close).
Added Custom Moving Average:
The indicator supports three types of moving averages:
EMA (Exponential Moving Average),
SMA (Simple Moving Average),
HMA (Hull Moving Average).
Users can choose the type and length of the moving average via input settings.
The selected moving average values are displayed in the Data Window for easier analysis.
Dynamic Coloring of the Coppock Curve:
The Coppock Curve line changes color based on its value:
Green if the value is positive,
Red if the value is negative.
The line's color is also displayed in the Data Window as a numeric value:
1 for green (positive),
-1 for red (negative).
Data Window Output:
The values of the selected moving average are displayed in the Data Window.
The Coppock Curve line's color state (1 or -1) is also shown in the Data Window.
Visual Representation:
The Coppock Curve is plotted with dynamic color coding.
The selected moving average is overlaid on the Coppock Curve for deeper trend analysis.
Usage Instructions:
Add the indicator to your chart on TradingView.
Configure the inputs:
Smoothing length for the Coppock Curve,
Long and short periods for ROC,
Type and length of the moving average.
Analyze the chart:
A green Coppock Curve line indicates a bullish trend, while a red line signals a bearish trend.
The selected moving average helps further filter and confirm signals.
Use the Data Window to view numeric values for the moving average and the Coppock Curve line color.
Applications:
This indicator is ideal for assessing trend direction and strength. The added customization options and additional data make it a versatile tool for traders, enabling them to tailor the Coppock Curve to their strategies.
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[MAD] Acceleration based dampened SMA projectionsThis indicator utilizes concepts of arrays inside arrays to calculate and display projections of multiple Smoothed Moving Average (SMA) lines via polylines.
This is partly an experiment as an educational post, on how to work with multidimensional arrays by using User-Defined Types
------------------
Input Controls for User Interaction:
The indicator provides several input controls, allowing users to adjust parameters like the SMA window, acceleration window, and dampening factors.
This flexibility lets users customize the behavior and appearance of the indicator to fit their analysis needs.
sma length:
Defines the length of the simple moving average (SMA).
acceleration window:
Sets the window size for calculating the acceleration of the SMA.
Input Series:
Selects the input source for calculating the SMA (typically the closing price).
Offset:
Determines the offset for the input source, affecting the positioning of the SMA. Here it´s possible to add external indicators like bollinger bands,.. in that case as double sma this sma should be very short.
(Thanks Fikira for that idea)
Startfactor dampening:
Initial dampening factor for the polynomial curve projections, influencing their starting curvature.
Growfactor dampening:
Growth rate of the dampening factor, affecting how the curvature of the projections changes over time.
Prediction length:
Sets the length of the projected polylines, extending beyond the current bar.
cleanup history:
Boolean input to control whether to clear the previous polyline projections before drawing new ones.
Key technologies used in this indicator include:
User-Defined Types (UDT) :
This indicator uses UDT to create a custom type named type_polypaths.
This type is designed to store information for each polyline, including an array of points (array), a color for the polyline, and a dampening factor.
UDTs in Pine Script enable the creation of complex data structures, which are essential for organizing and manipulating data efficiently.
type type_polypaths
array polyline_points = na
color polyline_color = na
float dampening_factor= na
Arrays and Nested Arrays:
The script heavily utilizes arrays.
For example, it uses a color array (colorpreset) to store different colors for the polyline.
Moreover, an array of type_polypaths (polypaths) is used, which is an array consisting of user-defined types. Each element of this array contains another array (polyline_points), demonstrating nested array usage.
This structure is essential for handling multiple polylines, each with its set of points and attributes.
var type_polypaths polypaths = array.new()
Polyline Creation and Manipulation:
The core visual aspect of the indicator is the creation of polylines.
Polyline points are calculated based on a dampened polynomial curve, which is influenced by the SMA's slope and acceleration.
Filling initial dampening data
array_size = 9
middle_index = math.floor(array_size / 2)
for i = 0 to array_size - 1
damp_factor = f_calculate_damp_factor(i, middle_index, Startfactor, Growfactor)
polyline_color = colorpreset.get(i)
polypaths.push(type_polypaths.new(array.new(0, na), polyline_color, damp_factor))
The script dynamically generates these polyline points and stores them in the polyline_points array of each type_polypaths instance based on those prefilled dampening factors
if barstate.islast or cleanup == false
for damp_factor_index = 0 to polypaths.size() - 1
GET_RW = polypaths.get(damp_factor_index)
GET_RW.polyline_points.clear()
for i = 0 to predictionlength
y = f_dampened_poly_curve(bar_index + i , src_input , sma_slope , sma_acceleration , GET_RW.dampening_factor)
p = chart.point.from_index(bar_index + i - src_off, y)
GET_RW.polyline_points.push(p)
polypaths.set(damp_factor_index, GET_RW)
Polyline Drawout
The polyline is then drawn on the chart using the polyline.new() function, which uses these points and additional attributes like color and width.
for pl_s = 0 to polypaths.size() - 1
GET_RO = polypaths.get(pl_s)
polyline.new(points = GET_RO.polyline_points, line_width = 1, line_color = GET_RO.polyline_color, xloc = xloc.bar_index)
If the cleanup input is enabled, existing polylines are deleted before new ones are drawn, maintaining clarity and accuracy in the visualization.
if cleanup
for pl_delete in polyline.all
pl_delete.delete()
------------------
The mathematics
in the (ABDP) indicator primarily focuses on projecting the behavior of a Smoothed Moving Average (SMA) based on its current trend and acceleration.
SMA Calculation:
The indicator computes a simple moving average (SMA) over a specified window (sma_window). This SMA serves as the baseline for further calculations.
Slope and Acceleration Analysis:
It calculates the slope of the SMA by subtracting the current SMA value from its previous value. Additionally, it computes the SMA's acceleration by evaluating the sum of differences between consecutive SMA values over an acceleration window (acceleration_window). This acceleration represents the rate of change of the SMA's slope.
sma_slope = src_input - src_input
sma_acceleration = sma_acceleration_sum_calc(src_input, acceleration_window) / acceleration_window
sma_acceleration_sum_calc(src, window) =>
sum = 0.0
for i = 0 to window - 1
if not na(src )
sum := sum + src - 2 * src + src
sum
Dampening Factors:
Custom dampening factors for each polyline, which are based on the user-defined starting and growth factors (Startfactor, Growfactor).
These factors adjust the curvature of the projected polylines, simulating various future scenarios of SMA movement.
f_calculate_damp_factor(index, middle, start_factor, growth_factor) =>
start_factor + (index - middle) * growth_factor
Polynomial Curve Projection:
Using the SMA value, its slope, acceleration, and dampening factors, the script calculates points for polynomial curves. These curves represent potential future paths of the SMA, factoring in its current direction and rate of change.
f_dampened_poly_curve(index, initial_value, initial_slope, acceleration, damp_factor) =>
delta = index - bar_index
initial_value + initial_slope * delta + 0.5 * damp_factor * acceleration * delta * delta
damp_factor = f_calculate_damp_factor(i, middle_index, Startfactor, Growfactor)
Have fun trading :-)
vol_coneDraws a volatility cone on the chart, using the contract's realized volatility (rv). The inputs are:
- window: the number of past periods to use for computing the realized volatility. VIX uses 30 calendar days, which is 21 trading days, so 21 is the default.
- stdevs: the number of standard deviations that the cone will cover.
- periods to project: the length of the volatility cone.
- periods per year: the number of periods in a year. for a daily chart, this is 252. for a thirty minute chart on a contract that trades 23 hours a day, this is 23 * 2 * 252 = 11592. for an accurate cone, this input must be set correctly, according to the chart's time frame.
- history: show the lagged projections. in other words, if the cone is set to project 21 periods in the future, the lines drawn show the top and bottom edges of the cone from 23 periods ago.
- rate: the current interest or discount rate. this is used to compute the forward price of the underlying contract. using an accurate forward price allows you to compare the realized volatility projection to the implied volatility projections derived from options prices.
Example settings for a 30 minute chart of a contract that trades 23 hours per day, with 1 standard deviation, a 21 day rv calculation, and half a day projected:
- stdevs: 1
- periods to project: 23
- window: 23 * 2 * 21 = 966
- periods per year: 23 * 2 * 252 = 11592
Additionally, a table is drawn in the upper right hand corner, with several values:
- rv: the contract's current realized volatility.
- rnk: the rv's percentile rank, compared to the rv values on past bars.
- acc: the proportion of times price settled inside, versus outside, the volatility cone, "periods to project" into the future. this should be around 65-70% for most contracts when the cone is set to 1 standard deviation.
- up: the upper bound of the cone for the projection period.
- dn: the lower bound of the cone for the projection period.
Limitations:
- pinescript only seems to be able to draw a limited distance into the future. If you choose too many "periods to project", the cone will start drawing vertically at some limit.
- the cone is not totally smooth owing to the facts a) it is comprised of a limited number of lines and b) each bar does not represent the same amount of time in pinescript, as some cross weekends, session gaps, etc.
probability_of_touchBased on historical data (rather than theory), calculates the probability of a price level being "touched" within a given time frame. A "touch" means that price exceeded that level at some point. The parameters are:
- level: the "level" to be touched. it can be a number of points, percentage points, or standard deviations away from the mark price. a positive level is above the mark price, and a negative level is below the mark price.
- type: determines the meaning of the "level" parameter. "price" means price points (i.e. the numbers you see on the chart). "percentage" is expressed as a whole number, not a fraction. "stdev" means number of standard deviations, which is computed from recent realized volatlity.
- mark: the point from which the "level" is measured.
- length: the number of days within which the level must be touched.
- window: the number of days used to compute realized volatility. this parameter is only used when "type" is "stdev".
- debug: displays a fuchsia "X" over periods that touched the level. note that only a limited number of labels can be drawn.
- start: only include data after this time in the calculation.
- end: only include data before this time in the calculation.
Example: You want to know how many times Apple stock fell $1 from its closing price the next day, between 2020-02-26 and today. Use the following parameters:
level: -1
type: price
mark: close
length: 1
window:
debug:
start: 2020-02-26
end:
How does the script work? On every bar, the script looks back "length" days and sees if any day exceeded the "mark" price from "length" days ago, plus the limit. The probability is the ratio of such periods wherein price exceeded the limit to the total number of periods.
trend_vol_forecastNote: The following description is copied from the script's comments. Since TradingView does not allow me to edit this description, please refer to the comments and release notes for the most up-to-date information.
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USAGE
This script compares trend trading with a volatility stop to "buy and hold".
Trades are taken with the trend, except when price exceeds a volatility
forecast. The trend is defined by a moving average crossover. The forecast
is based on projecting future volatility from historical volatility.
The trend is defined by two parameters:
- long: the length of a long ("slow") moving average.
- short: the length of a short ("fast") moving average.
The trend is up when the short moving average is above the long. Otherwise
it is down.
The volatility stop is defined by three parameters:
- volatility window: determines the number of periods in the historical
volatility calculation. More periods means a slower (smoother)
estimate of historical volatility.
- stop forecast periods: the number of periods in the volatility
forecast. For example, "7" on a daily chart means that the volatility
will be forecasted with a one week lag.
- stop forecast stdev: the number of standard deviations in the stop
forecast. For example, "2" means two standard deviations.
EXAMPLE
The default parameters are:
- long: 50
- short: 20
- volatility window: 30
- stop forecast periods: 7
- stop forecast standard deviations: 1
The trend will be up when the 20 period moving average is above the 50
period moving average. On each bar, the historical volatility will be
calculated from the previous 30 bars. If the historical volatility is 0.65
(65%), then a forecast will be drawn as a fuchsia line, subtracting
0.65 * sqrt(7 / 365) from the closing price. If price at any point falls
below the forecast, the volatility stop is in place, and the trend is
negated.
OUTPUTS
Plots:
- The trend is shown by painting the slow moving average green (up), red
(down), or black (none; volatility stop).
- The fast moving average is shown in faint blue
- The previous volatility forecasts are shown in faint fuchsia
- The current volatility forecast is shown as a fuchsia line, projecting
into the future as far as it is valid.
Tables:
- The current historical volatility is given in the top right corner, as a
whole number percentage.
- The performance table shows the mean, standard deviation, and sharpe
ratio of the volatility stop trend strategy, as well as buy and hold.
If the trend is up, each period's return is added to the sample (the
strategy is long). If the trend is down, the inverse of each period's
return is added to the sample (the strategy is short). If there is no
trend (the volatility stop is active), the period's return is excluded
from the sample. Every period is added to the buy-and-hold strategy's
sample. The total number of periods in each sample is also shown.
DRACO Tomas Delta (Custom/Monthly)🐉 DRACO Delta SessionBox (Custom / Monthly)
Overview
The DRACO Delta SessionBox is an advanced visual and analytical tool designed to measure and display cumulative buying and selling pressure (Δ — delta) within a user-defined time window, such as a specific custom date range, a recurring monthly period, or the entire current month.
It visually represents market accumulation or distribution phases by calculating an approximate delta — the imbalance between bullish and bearish volume — and then aggregates it inside a dynamic “box” that spans only the selected time window.
Core Concept
Delta in this context is an approximation of the real order-flow delta (buy vs sell volume difference).
Since TradingView doesn’t provide raw tick-by-tick trade direction data, this indicator uses a proxy formula based on OHLC and volume data:
Δ per bar
=
Volume
×
(
Close
−
Open
)
max
(
High
−
Low
,
Tick Size
)
Δ per bar=Volume×
max(High−Low,Tick Size)
(Close−Open)
This gives a very effective approximation of intrabar directional pressure — whether volume was dominated by buyers (Δ > 0) or sellers (Δ < 0).
Modes
The indicator can operate in three distinct modes:
🕒 Custom DateTime
The user manually sets an exact date & time range (From – To).
The box only measures delta and volume accumulation within this window.
Ideal for analyzing specific events, like FOMC weeks, quarterly earnings, or macro periods.
📆 Monthly Window
The user selects start and end days of the month (e.g. 5–20).
The same window repeats automatically every month.
Useful for identifying recurring accumulation or distribution cycles within months.
🧭 Whole Month
Automatically measures and visualizes delta for the entire current calendar month.
The box resets when a new month begins.
Provides a macro-level view of monthly directional bias.
Outside Candle Session Breakout [CHE]Outside Candle Session Breakout
Session - anchored HTF levels for clear market-structure and precise breakout context
Summary
This indicator is a relevant market-structure tool. It anchors the session to the first higher-timeframe bar, then activates only when the second bar forms an outside condition. Price frequently reacts around these anchors, which provides precise breakout context and a clear overview on both lower and higher timeframes. Robustness comes from close-based validation, an adaptive volatility and tick buffer, first-touch enforcement, optional retest, one-signal-per-session, cooldown, and an optional trend filter.
Pine version: v6. Overlay: true.
Motivation: Why this design?
Short-term breakout tools often trigger during noise, duplicate within the same session, or drift when volatility shifts. The core idea is to gate signals behind a meaningful structure event: a first-bar anchor and a subsequent outside bar on the session timeframe. This narrows attention to structurally important breaks while adaptive buffering and debouncing reduce false or mid-run triggers.
What’s different vs. standard approaches?
Baseline: Simple high-low breaks or fixed buffers without session context.
Architecture: Session-anchored first-bar high/low; outside-bar gate; close-based confirmation with an adaptive ATR and tick buffer; first-touch enforcement; optional retest window; one-signal-per-session and cooldown; optional EMA trend and slope filter; higher-timeframe aggregation with lookahead disabled; themeable visuals and a range fill between levels.
Practical effect: Cleaner timing at structurally relevant levels, fewer redundant or late triggers, and better multi-timeframe situational awareness.
How it works (technical)
The chart timeframe is mapped to an analysis timeframe and a session timeframe.
The first session bar defines the anchor high and low. The setup becomes active only after the next bar forms an outside range relative to that first bar.
While active, the script tracks these anchors and checks for a breakout beyond a buffered threshold, using closing prices or wicks by preference.
The buffer scales with volatility and is limited by a minimum tick floor. First-touch enforcement avoids mid-run confirmations.
Optional retest requires a pullback to the raw anchor followed by a new close beyond the buffered level within a user window.
Optional trend gating uses an EMA on the analysis timeframe, including an optional slope requirement and price-location check.
Higher-timeframe data is requested with lookahead disabled. Values can update during a forming higher-timeframe bar; waiting and confirmation mitigate timing shifts.
Parameter Guide
Enable Long / Enable Short — Direction toggles. Default: true / true. Reduces unwanted side.
Wait Candles — Minimum bars after outside confirmation before entries. Default: five. More waiting increases stability.
Close-based Breakout — Confirm on candle close beyond buffer. Default: true. For wick sensitivity, disable.
ATR Buffer — Enables adaptive volatility buffer. Default: true.
ATR Multiplier — Buffer scaling. Default: zero point two. Increase to reduce noise.
Ticks Buffer — Minimum buffer in ticks. Default: two. Protects in quiet markets.
Cooldown Bars — Blocks new signals after a trigger. Default: three.
One Signal per Session — Prevents duplicates within a session. Default: true.
Require Retest — Pullback to raw anchor before confirming. Default: false.
Retest Window — Bars allowed for retest completion. Default: five.
HTF Trend Filter — EMA-based gating. Default: false.
EMA Length — EMA period. Default: two hundred.
Slope — Require EMA slope direction. Default: true.
Price Above/Below EMA — Require price location relative to EMA. Default: true.
Show Levels / Highlight Session / Show Signals — Visual controls. Default: true.
Color Theme — “Blue-Green” (default), “Monochrome”, “Earth Tones”, “Classic”, “Dark”.
Time Period Box — Visibility, size, position, and colors for the info box. (Optional)
Reading & Interpretation
The two level lines represent the session’s first-bar high and low. The filled band illustrates the active session range.
“OUT” marks that the outside condition is confirmed and the setup is live.
“LONG” or “SHORT” appears only when the breakout clears buffer, debounce, and optional gates.
Background tint indicates sessions where the setup is valid.
Alerts fire on confirmed long or short breakout events.
Practical Workflows & Combinations
Trend-following: Keep close-based validation, ATR buffer near the default, one-signal-per-session enabled; add EMA trend and slope for directional bias.
Retest confirmation: Enable retest with a short window to prioritize cleaner continuation after a pullback.
Lower-timeframe scalping: Reduce waiting and cooldown slightly; keep a small tick buffer to filter micro-whips.
Swing and position context: Increase ATR multiplier and waiting; maintain once-per-session to limit duplicates.
Timeframe Tiers and Trader Profiles
The script adapts its internal mapping based on the chart timeframe:
Under fifteen minutes → Analysis: one minute; Session: sixty minutes. Useful for scalpers and high-frequency intraday reads.
Between fifteen and under sixty minutes → Analysis: fifteen minutes; Session: one day. Suits day traders who need intraday alignment to the daily session.
Between sixty minutes and under one day → Analysis: sixty minutes; Session: one week. Serves intraday-to-swing transitions and end-of-day planning.
Between one day and under one week → Analysis: two hundred forty minutes; Session: two weeks. Fits swing traders who monitor multi-day structure.
Between one week and under thirty days → Analysis: one day; Session: three months. Supports position traders seeking quarterly context.
Thirty days and above → Analysis: one day; Session: twelve months. Provides a broad annual anchor for macro context.
These tiers are designed to keep anchors meaningful across regimes while preserving responsiveness appropriate to the trader profile.
Behavior, Constraints & Performance
Signals can be validated on closed bars through close-based logic; enabling this reduces intrabar flicker.
Higher-timeframe values may evolve during a forming bar; waiting parameters and the outside-bar gate reduce, but do not remove, this effect.
Resource footprint is light; the script uses standard indicators and a single higher-timeframe request per stream.
Known limits: rare setups during very quiet periods, sensitivity to gaps, and reduced reliability on illiquid symbols.
Sensible Defaults & Quick Tuning
Start with close-based validation on, ATR buffer on with a multiplier near zero point two, tick buffer two, cooldown three, once-per-session on.
Too many flips: increase the ATR multiplier and cooldown; consider enabling the EMA filter and slope.
Too sluggish: reduce the ATR multiplier and waiting; disable retest.
Choppy conditions: keep close-based validation, increase tick buffer, shorten the retest window.
What this indicator is—and isn’t
This is a visualization and signal layer for session-anchored breakouts with stability gates. It is not a complete trading system, risk framework, or predictive engine. Combine it with structured analysis, position sizing, and disciplined risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Triple Close Indicator (TCI)Triple Close Indicator (TCI)
Overview:
The Triple Close Indicator (TCI) is a trend-following and entry signal tool designed to simplify market decision-making. Using a 50-period moving average (MA) as the primary trend filter, TCI identifies consecutive close patterns to generate high-probability bullish and bearish entry signals. Its clean design ensures minimal chart clutter while highlighting actionable points.
How It Works:
Trend Identification
The 50 MA is the core trend filter:
Price above 50 MA → bullish trend
Price below 50 MA → bearish trend
Signal Lines (Green/Red Lines)
Green Line: Marks every 3rd consecutive higher close
Red Line: Marks every 3rd consecutive lower close
Signal lines extend 6 bars forward for reference
Users can customize line width, transparency, and style (solid/dotted)
Entry Signals (Triangles)
Bullish Entry:
Green line above 50 MA → look for a candle closing above this line within the next configurable lookback window (default 5 bars)
Red line above 50 MA → if a candle closes above this line within the lookback window, bullish entry is triggered
Bearish Entry:
Red line below 50 MA → look for a candle closing below this line within the lookback window
Green line below 50 MA → if a candle closes below this line within the lookback window, bearish entry is triggered
Visuals
50 MA line – yellow, main trend filter
Signal lines – green/red with customizable width, transparency, and style
Entry triangles – lime for bullish, red for bearish
Alerts are available for real-time notifications
How to Use Effectively:
Trend Confirmation
Only take long entries above 50 MA and short entries below 50 MA
Avoid counter-trend entries to reduce false signals
Signal Validation
Wait for a candle close beyond the signal line to confirm the entry
Use the configurable lookback window to capture the most recent valid candle
Combine with Other Filters (Optional)
Use volume, ATR, or RSI to filter low-probability setups
Multi-timeframe analysis can enhance signal reliability
Alerts
Use built-in TradingView alerts for real-time execution
Customize messages for notifications on mobile, email, or webhook
Inputs & Customization:
MA Type & Length: Choose SMA, EMA, WMA, or VWMA for 50 MA
Signal Line Colors: Green (bullish), Red (bearish)
Line Width & Transparency: Adjust visual clarity
Line Style: Solid or Dotted
Lookback Window: Number of bars to check for valid entry after a signal line
Best Practices:
Use higher timeframes (1H, 4H, daily) for more reliable signals
Avoid trading in tight consolidation zones; the indicator works best in trending markets
Combine with risk management: define stop-loss below/above signal lines or ATR multiples
Hour/Day/Month Optimizer [CHE] Hour/Day/Month Optimizer — Bucketed seasonality ranking for hours, weekdays, and months with additive or compounded returns, win rate, simple Sharpe proxy, and trade counts
Summary
This indicator profiles time-of-day, day-of-week, and month-of-year behavior by assigning every bar to a bucket and accumulating its return into that bucket. It reports per-bucket score (additive or compounded), win rate, a dispersion-aware return proxy, and trade counts, then ranks buckets and highlights the current one if it is best or worst. A compact on-chart table shows the top buckets or the full ranking; a last-bar label summarizes best and worst. Optional hour filtering and UTC shifting let you align buckets with your trading session rather than exchange time.
Motivation: Why this design?
Traders often see repetitive timing effects but struggle to separate genuine seasonality from noise. Static averages are easily distorted by sample size, compounding, or volatility spikes. The core idea here is simple, explicit bucket aggregation with user-controlled accumulation (sum or compound) and transparent quality metrics (win rate, a dispersion-aware proxy, and counts). The result is a practical, legible seasonality surface that can be used for scheduling and filtering rather than prediction.
What’s different vs. standard approaches?
Reference baseline: Simple heatmaps or average-return tables that ignore compounding, dispersion, or sample size.
Architecture differences:
Dual aggregation modes: additive sum of bar returns or compounded factor.
Per-bucket win rate and trade count to expose sample support.
A simple dispersion-aware return proxy to penalize unstable averages.
UTC offset and optional custom hour window.
Deterministic, closed-bar rendering via a lightweight on-chart table.
Practical effect: You see not only which buckets look strong but also whether the observation is supported by enough bars and whether stability is acceptable. The background tint and last-bar label give immediate context for the current bucket.
How it works (technical)
Each bar is assigned to a bucket based on the selected dimension (hour one to twenty-four, weekday one to seven, or month one to twelve) after applying the UTC shift. An optional hour filter can exclude bars outside a chosen window. For each bucket the script accumulates either the sum of simple returns or the compounded product of bar factors. It also counts bars and wins, where a win is any bar with a non-negative return. From these, it derives:
Score: additive total or compounded total minus the neutral baseline.
Win rate: wins as a percentage of bars in the bucket.
Dispersion-aware proxy (“Sharpe” column): a crude ratio that rises when average return improves and falls when variability increases.
Buckets are sorted by a user-selected key (score, win rate, dispersion proxy, or trade count). The current bar’s bucket is tinted if it matches the global best or worst. At the last bar, a table is drawn with headers, an optional info row, and either the top three or all rows, using zebra backgrounds and color-coding (lime for best, red for worst). Rendering is last-bar only; no higher-timeframe data is requested, and no future data is referenced.
Parameter Guide
UTC Offset (hours) — Shifts bucket assignment relative to exchange time. Default: zero. Tip: Align to your local or desk session.
Use Custom Hours — Enables a local session window. Default: off. Trade-off: Reduces noise outside your active hours but lowers sample size.
Start / End — Inclusive hour window one to twenty-four. Defaults: eight to seventeen. Tip: Widen if rankings look unstable.
Aggregation — “Additive” sums bar returns; “Multiplicative” compounds them. Default: Additive. Tip: Use compounded for long-horizon bias checks.
Dimension — Bucket by Hour, Day, or Month. Default: Hour. Tip: Start Hour for intraday planning; switch to Day or Month for scheduling.
Show — “Top Three” or “All”. Default: Top Three. Trade-off: Clarity vs. completeness.
Sort By — Score, Win Rate, Sharpe, or Trades. Default: Score. Tip: Use Trades to surface stable buckets; use Win Rate for skew awareness.
X / Y — Table anchor. Defaults: right / top. Tip: Move away from price clusters.
Text — Table text size. Default: normal.
Light Mode — Light palette for bright charts. Default: off.
Show Parameters Row — Info header with dimension and span. Default: on.
Highlight Current Bucket if Best/Worst — Background tint when current bucket matches extremes. Default: on.
Best/Worst Barcolor — Tint colors. Defaults: lime / red.
Mark Best/Worst on Last Bar — Summary label on the last bar. Default: on.
Reading & Interpretation
Score column: Higher suggests stronger cumulative behavior for the chosen aggregation. Compounded mode emphasizes persistence; additive mode treats all bars equally.
Win Rate: Stability signal; very high with very low trades is unreliable.
“Sharpe” column: A quick stability proxy; use it to down-rank buckets that look good on score but fluctuate heavily.
Trades: Sample size. Prefer buckets with adequate counts for your timeframe and asset.
Tinting: If the current bucket is globally best, expect a lime background; if worst, red. This is context, not a trade signal.
Practical Workflows & Combinations
Trend following: Use Hour or Day to avoid initiating trades during historically weak buckets; require structure confirmation such as higher highs and higher lows, plus a momentum or volatility filter.
Mean reversion: Prefer buckets with moderate scores but acceptable win rate and dispersion proxy; combine with deviation bands or volume normalization.
Exits/Stops: Tighten exits during historically weak buckets; relax slightly during strong ones, but keep absolute risk controls independent of the table.
Multi-asset/Multi-TF: Start with Hour on liquid intraday assets; for swing, use Day. On monthly seasonality, require larger lookbacks to avoid overfitting.
Behavior, Constraints & Performance
Repaint/confirmation: Calculations use completed bars only; table and label are drawn on the last bar and can update intrabar until close.
security()/HTF: None used; repaint risk limited to normal live-bar updates.
Resources: Arrays per dimension, light loops for metric building and sorting, `max_bars_back` two thousand, and capped label/table counts.
Known limits: Sensitive to sample size and regime shifts; ignores costs and slippage; bar-based wins can mislead on assets with frequent gaps; compounded mode can over-weight streaks.
Sensible Defaults & Quick Tuning
Start: Hour dimension, Additive, Top Three, Sort by Score, default session window off.
Too many flips: Switch to Sort by Trades or raise sample by widening hours or timeframe.
Too sluggish/over-smoothed: Switch to Additive (if on compounded) or shorten your chart timeframe while keeping the same dimension.
Overfit risk: Prefer “All” view to verify that top buckets are not isolated with tiny counts; use Day or Month only with long histories.
What this indicator is—and isn’t
This is a seasonality and scheduling layer that ranks time buckets using transparent arithmetic and simple stability checks. It is not a predictive model, not a complete trading system, and it does not manage risk. Use it to plan when to engage, then rely on structure, confirmation, and independent risk management for entries and exits.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
Shifted Buy PressureDifferentiated Buy Pressure Indicator Documentation
Overview: The Differentiated Buy Pressure indicator is a custom Pine Script™ indicator designed to measure and visualize buy and sell pressure in the market. It calculates buy pressure based on a combination of volume, range, and gap, and provides a differentiated buy pressure which is shifted by 90°, offering predictive insights.
Inputs:
Window Size: The window size for average calculation (default: 20).
Show Overlay: Option to show the price overlay (default: false).
Overlay Boost Factor: Boosting factor for overlaying the price (default: 0.01).
Calculations:
Relative Range: Calculated as (high - low) / close.
Average Range: Simple moving average of the relative range over the specified window.
Average Volume: Simple moving average of the volume over the specified window.
Relative Gap: Calculated as open / close .
Average Gap: Simple moving average of the relative gap over the specified window.
Buy Pressure: Calculated using the formula: buy_pressure = -math.log(relative_range / avg_range * volume / avg_volume * relative_gap / avg_gap)
Differentiated Buy Pressure: Calculated as the difference between the current and previous buy pressure: diff_buy_pressure = buy_pressure - buy_pressure
Plots:
Zero Line: A horizontal line at zero for reference.
Buy Pressure: Plotted in blue, representing the calculated buy pressure.
Differentiated Buy Pressure: Plotted in red, representing the differentiated buy pressure.
Overlay: Optionally plots the price overlay boosted by the differentiated buy pressure.
Labels:
Labels are created to display the buy pressure and differentiated buy pressure values on the chart.
Usage: This indicator helps traders visualize the buy and sell pressure in the market. Positive values indicate buy pressure, while negative values indicate sell pressure. The differentiated buy pressure, shifted by 90°, provides predictive insights into future market movements.
This documentation provides a comprehensive overview of the Differentiated Buy Pressure indicator, explaining its purpose, inputs, calculations, and usage.
PaddingThe Padding library is a comprehensive and flexible toolkit designed to extend time series data within TradingView, making it an indispensable resource for advanced signal processing tasks such as FFT, filtering, convolution, and wavelet analysis. At its core, the library addresses the common challenge of edge effects by "padding" your data—that is, by appending additional data points beyond the natural boundaries of your original dataset. This extension not only mitigates the distortions that can occur at the endpoints but also helps to maintain the integrity of various transformations and calculations performed on the series. The library accomplishes this while preserving the ordering of your data, ensuring that the most recent point always resides at index 0.
Central to the functionality of this library are two key enumerations: Direction and PaddingType. The Direction enum determines where the padding will be applied. You can choose to extend the data in the forward direction (ahead of the current values), in the backward direction (behind the current values), or in both directions simultaneously. The PaddingType enum defines the specific method used for extending the data. The library supports several methods—including symmetric, reflect, periodic, antisymmetric, antireflect, smooth, constant, and zero padding—each of which has been implemented to suit different analytical scenarios. For instance, symmetric padding mirrors the original data across its boundaries, while reflect padding continues the trend by reflecting around endpoint values. Periodic padding repeats the data, and antisymmetric padding mirrors the data with alternating signs to counterbalance it. The antireflect and smooth methods take into account the derivatives of your data, thereby extending the series in a way that preserves or smoothly continues these derivative values. Constant and zero padding simply extend the series using fixed endpoint values or zeros. Together, these enums allow you to fine-tune how your data is extended, ensuring that the padding method aligns with the specific requirements of your analysis.
The library is designed to work with both single variable inputs and array inputs. When using array-based methods—particularly with the antireflect and smooth padding types—please note that the implementation intentionally discards the last data point as a result of the delta computation process. This behavior is an important consideration when integrating the library into your TradingView studies, as it affects the overall data length of the padded series. Despite this, the library’s structure and documentation make it straightforward to incorporate into your existing scripts. You simply provide your data source, define the length of your data window, and select the desired padding type and direction, along with any optional parameters to control the extent of the padding (using both_period, forward_period, or backward_period).
In practical application, the Padding library enables you to extend historical data beyond its original range in a controlled and predictable manner. This is particularly useful when preparing datasets for further signal processing, as it helps to reduce artifacts that can otherwise compromise the results of your analytical routines. Whether you are an experienced Pine Script developer or a trader exploring advanced data analysis techniques, this library offers a robust solution that enhances the reliability and accuracy of your studies by ensuring your algorithms operate on a more complete and well-prepared dataset.
Library "Padding"
A comprehensive library for padding time series data with various methods. Supports both single variable and array inputs, with flexible padding directions and periods. Designed for signal processing applications including FFT, filtering, convolution, and wavelets. All methods maintain data ordering with most recent point at index 0.
symmetric(source, series_length, direction, both_period, forward_period, backward_period)
Applies symmetric padding by mirroring the input data across boundaries
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with symmetric padding applied
method symmetric(source, direction, both_period, forward_period, backward_period)
Applies symmetric padding to an array by mirroring the data across boundaries
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with symmetric padding applied
reflect(source, series_length, direction, both_period, forward_period, backward_period)
Applies reflect padding by continuing trends through reflection around endpoint values
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with reflect padding applied
method reflect(source, direction, both_period, forward_period, backward_period)
Applies reflect padding to an array by continuing trends through reflection around endpoint values
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with reflect padding applied
periodic(source, series_length, direction, both_period, forward_period, backward_period)
Applies periodic padding by repeating the input data
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with periodic padding applied
method periodic(source, direction, both_period, forward_period, backward_period)
Applies periodic padding to an array by repeating the data
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with periodic padding applied
antisymmetric(source, series_length, direction, both_period, forward_period, backward_period)
Applies antisymmetric padding by mirroring data and alternating signs
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with antisymmetric padding applied
method antisymmetric(source, direction, both_period, forward_period, backward_period)
Applies antisymmetric padding to an array by mirroring data and alternating signs
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with antisymmetric padding applied
antireflect(source, series_length, direction, both_period, forward_period, backward_period)
Applies antireflect padding by reflecting around endpoints while preserving derivatives
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with antireflect padding applied
method antireflect(source, direction, both_period, forward_period, backward_period)
Applies antireflect padding to an array by reflecting around endpoints while preserving derivatives
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with antireflect padding applied. Note: Last data point is lost when using array input
smooth(source, series_length, direction, both_period, forward_period, backward_period)
Applies smooth padding by extending with constant derivatives from endpoints
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with smooth padding applied
method smooth(source, direction, both_period, forward_period, backward_period)
Applies smooth padding to an array by extending with constant derivatives from endpoints
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with smooth padding applied. Note: Last data point is lost when using array input
constant(source, series_length, direction, both_period, forward_period, backward_period)
Applies constant padding by extending endpoint values
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with constant padding applied
method constant(source, direction, both_period, forward_period, backward_period)
Applies constant padding to an array by extending endpoint values
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with constant padding applied
zero(source, series_length, direction, both_period, forward_period, backward_period)
Applies zero padding by extending with zeros
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with zero padding applied
method zero(source, direction, both_period, forward_period, backward_period)
Applies zero padding to an array by extending with zeros
Namespace types: array
Parameters:
source (array) : Array of values to pad
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with zero padding applied
pad_data(source, series_length, padding_type, direction, both_period, forward_period, backward_period)
Generic padding function that applies specified padding type to input data
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
padding_type (series PaddingType) : Type of padding to apply (see PaddingType enum)
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with specified padding applied
method pad_data(source, padding_type, direction, both_period, forward_period, backward_period)
Generic padding function that applies specified padding type to array input
Namespace types: array
Parameters:
source (array) : Array of values to pad
padding_type (series PaddingType) : Type of padding to apply (see PaddingType enum)
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to array length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to array length if not specified
Returns: Array ordered with most recent point at index 0, containing original data with specified padding applied. Note: Last data point is lost when using antireflect or smooth padding types
make_padded_data(source, series_length, padding_type, direction, both_period, forward_period, backward_period)
Creates a window-based padded data series that updates with each new value. WARNING: Function must be called on every bar for consistency. Do not use in scopes where it may not execute on every bar.
Parameters:
source (float) : Input value to pad from
series_length (int) : Length of the data window
padding_type (series PaddingType) : Type of padding to apply (see PaddingType enum)
direction (series Direction) : Direction to apply padding
both_period (int) : Optional - periods to pad in both directions. Overrides forward_period and backward_period if specified
forward_period (int) : Optional - periods to pad forward. Defaults to series_length if not specified
backward_period (int) : Optional - periods to pad backward. Defaults to series_length if not specified
Returns: Array ordered with most recent point at index 0, containing windowed data with specified padding applied
Price Prediction With Rolling Volatility [TradeDots]The "Price Prediction With Rolling Volatility" is a trading indicator that estimates future price ranges based on the volatility of price movements within a user-defined rolling window.
HOW DOES IT WORK
This indicator utilizes 3 types of user-provided data to conduct its calculations: the length of the rolling window, the number of bars projecting into the future, and a maximum of three sets of standard deviations.
Firstly, the rolling window. The algorithm amasses close prices from the number of bars determined by the value in the rolling window, aggregating them into an array. It then calculates their standard deviations in order to forecast the prospective minimum and maximum price values.
Subsequently, a loop is initiated running into the number of bars into the future, as dictated by the second parameter, to calculate the maximum price change in both the positive and negative direction.
The third parameter introduces a series of standard deviation values into the forecasting model, enabling users to dictate the volatility or confidence level of the results. A larger standard deviation correlates with a wider predicted range, thereby enhancing the probability factor.
APPLICATION
The purpose of the indicator is to provide traders with an understanding of the potential future movement of the price, demarcating maximum and minimum expected outcomes. For instance, if an asset demonstrates a substantial spike beyond the forecasted range, there's a significantly high probability of that price being rejected and reversed.
However, this indicator should not be the sole basis for your trading decisions. The range merely reflects the volatility within the rolling window and may overlook significant historical price movements. As with any trading strategies, synergize this with other indicators for a more comprehensive and reliable analysis.
Note: In instances where the number of predicted bars is exceedingly high, the lines may become scattered, presumably due to inherent limitations on the TradingView platform. Consequently, when applying three SD in your indicator, it is advised to limit the predicted bars to fewer than 80.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Rebalance as a Bear/Bull indicatorCheck if the current market has a Bear tendency or a Bull tendency.
Bear areas are marked as red squares going down from 0.
Bull areas are marked as green squares going up from 0.
Buying/Selling windows of opportunity
On top of the Bear/Bull squares, this indicator tries to show you the windows where to look for good buying/selling opportunities.
These are marked as full columns:
Blue columns represent a window to look out for good buying opportunities
Pink columns represent a window to look out for good selling opportunities
How is this possible?
This is an indicator of a simple idea to check if the market has a Bear or Bull tendency:
1. Start with a virtual portfolio of 60/40 tokens per fiat.
2. Rebalance it when its ratio oscillates by a given % (first input)
3. Count the number of times the rebalancer buys, and sells
4. When the number of buys is greater than the number of sells => the market is going down
5. When the number of sells is greater than the number of buys => the market is going up
This is shown as the "Bear/Bull Strength" squares (red when bear, green when bull)
An extra rebalancer is also kept that works at each bar (regardless of the input %).
This is used to calculate an amount of tokens beying sold/bought and used as a "market force" coefficient.
Another extra: based on both the bear/bull strengh and market force an attempt is made to
provide good buying/selling windows of analysis.
The blue background is a buying opportunity, the red background is a sell opportunity.
In a bear market sales are delayed, and in a bull market buys are delayed.
Future Ichimoku Cloud - HorizonIchimoku Horizon is an advanced Ichimoku indicator that projects future cloud formations and component lines, giving traders unprecedented visibility into potential support/resistance zones before they form.
1. Future Ichimoku Projections
Project Ichimoku components forward in time using simulated price evolution based on rolling Tenkan/Kijun windows
Manual forecast periods up to 125 bars (all 4 components) or 500 bars (cloud only)
Smart limit management automatically adjusts to TradingView's drawing object limits while maximizing visible projections
2. Preset & Custom Ichimoku Configurations
Choose from multiple common Ichimoku presets or fully customize your own
3. Multi-Timeframe Display & Projections
Display Ichimoku from higher/lower timeframes directly on your current timeframe chart
Automatic scaling adjusts Ichimoku periods correctly across timeframes
Intelligent handling of 24/7 markets (crypto/forex) vs traditional session-based markets
Built-in detection of problematic timeframe combinations with optional MTF cloud fetching for accuracy
Automatic notifications when future projections are unavailable due to MTF constraints
4. Tenkan & Kijun Range Windows
Visual range windows that display the exact high/low range used for Tenkan and Kijun calculations
Optional High/Low markers placed at the exact bars they occur
Optional countdown labels show how many bars remain until the current High/Low expires from the rolling window
Range windows scale up and down dynamically to match display timeframe
5. Comprehensive Alert Suite
Built-in alerts for all major Ichimoku events: TK crosses, E2E entires, Kumo breakouts, etc.
All alerts are cloud-aware and displacement-correct.
How It Works
The indicator uses the traditional Donchian channel method to calculate Ichimoku components, then extends this logic forward by simulating future price action within the calculation windows (no new highs or lows). This creates a forward-looking projection of where support and resistance zones will form.
The range display feature helps traders understand why the lines are where they are by showing the exact high/low points and countdown timers for when these points will expire from the calculation.
Who This Indicator Is For:
Ichimoku traders who want future-aware context
Multi-timeframe analysts seeking correctly aligned clouds
Traders who want to understand Tenkan/Kijun mechanics
Users who need precision without manual recalculation
Notes:
Maximum 500 drawing objects limit managed automatically
Due to Pinescript/TradingView limitations, future Tenkan/Kijun line width is only modifiable in the source code.
Session Sweep System – WarRoomXYZ V1WarRoom Session Sweep System v1 is a open-source institutional trading framework built to identify liquidity behavior across Asia, London, and New York sessions.
It combines session-based liquidity mapping, sweep detection, daily expansion modeling, and trend confirmation into a unified, timing-driven system optimized for XAUUSD, FX pairs, indices, and any instrument with session-dependent volatility.
This tool does not attempt to predict direction with arbitrary oscillators.
Instead, it focuses on the underlying market mechanisms that drive price:
liquidity, timing, expansion, and trend alignment.
Below is a detailed explanation of what the script does, how its components work, and how traders can use it effectively.
🔹 1. Session Liquidity Mapping
The script automatically identifies the Asia (00:00–06:00 GMT), London (07:00–12:00 GMT), and New York (13:00–17:00 GMT) sessions and builds real-time session ranges.
Each session creates a liquidity pool.
Trading institutions frequently sweep the high or low of one session before delivering the real move in the next session.
This script captures that behavior by:
►Drawing session range boxes
►Tracking previous session highs/lows
►Highlighting high-probability sweep locations
These ranges are essential reference points for timing entries and exits.
🔹 2. Liquidity Sweep Detection (Buy & Sell Sweeps)
The indicator identifies when price runs a previous session high/low and rejects back inside the range, which is commonly interpreted as a liquidity sweep.
The following sweep types are monitored:
►London sweeping Asia
►New York sweeping London
►Asia sweeping New York
►Daily sweep of PDH/PDL
Sweeps signal that liquidity has been collected and that a potential reversal or continuation is likely.
These are marked clearly on the chart for real-time decision-making.
🔹 3. Killzone Timing Model (GMT Time)
Market manipulation and expansion often occur during specific time windows.
The script highlights these institutional killzones:
►London Killzone: 07:00–10:00 GMT
►New York Killzone: 13:30–15:30 GMT
►NY PM Session: 19:00–21:00 GMT
Sweeps occurring inside these windows carry a significantly higher probability.
The timing layer helps filter out low-quality setups.
🔹 4. Daily Range & ADR Expansion Engine
A dedicated panel displays:
►Current day range
►ADR (Average Daily Range)
►Expansion stage (Early / Developed / Extended)
►PDH/PDL swept or intact
►Overall session bias
This allows traders to understand whether the daily move is likely to continue or reverse.
For example:
►Early expansion → trend continuation likely
►Extended expansion → reversal setups become more probable
This is useful for intraday targets and risk management.
🔹 5. MA Cloud Trend Model (Fast/Slow Structure)
To align liquidity behavior with directional conviction, the script includes a configurable MA engine:
►Fast & slow MA
►MA cloud
►Slope-based trend coloring
►Trend background
►MA cross alerts
The cloud provides trend confirmation without relying on oscillators.
Trades are higher quality when the sweep direction aligns with the MA trend.
🔹 6. How the Components Work Together
The script integrates several institutional concepts into one coherent model:
►Sessions define liquidity pools
►Sweeps identify stop-hunts and reversals
►Killzones define optimal timing
►MA Cloud confirms directional bias
►ADR engine indicates expansion potential
This creates a structured framework:
Sweep → Timing → Trend → Expansion → Execution
Each component strengthens the others, forming a robust decision-making model.
🔹 7. How to Use the Indicator (Practical Guide)
✔ Look for a sweep of a previous session level
When price runs a session high/low and closes back inside, liquidity has likely been collected.
✔ Confirm timing
Sweeps inside London or NY killzones tend to produce the strongest moves.
✔ Confirm trend
Use MA cloud direction and slope:
►Cloud green → long setups preferred
►Cloud red → short setups preferred
✔ Check ADR panel
If the day has already expanded significantly, reversal setups are more likely.
If expansion is still early, continuation setups are favored.
✔ Plan your trade
Common targets include:
►Opposite side of session range
►ADR High/Low
►PDH/PDL
Stops are typically placed beyond the sweep wick.
This creates a repeatable, rule-based approach to intraday liquidity trading.
🔹 8. Why This Script Is Original
This is not a mashup of existing open-source indicators.
It introduces:
►A custom session-linked liquidity sweep engine
►A structured daily expansion model
►Integrated killzone timing aligned with GMT
►A unified bias panel merging sweeps, ADR, and session manipulation
►A trend confirmation layer designed around session behavior
While it uses known institutional concepts, their integration, execution, and timing framework are unique, purpose-built, and not directly found in open-source scripts.
🔹 9. Suitable Markets
This indicator works best on:
►XAUUSD
►Major FX pairs
►US indices
►Synthetic markets with session cycles
Ideal timeframes: 1m, 5m, 15m, 30m
🔹 10. Limitations / Notes
This is an analytical tool, not a buy/sell signal generator
All sweeps are confirmed at candle close (non-repaint)
The tool assumes GMT session windows unless chart time differs
Users must practice risk management and entry triggers manually
Disclaimer
This script is provided for informational and educational purposes only. It does not provide financial, investment, or trading advice, and it does not guarantee profits or future performance. All decisions made based on this script are solely the responsibility of the user.
This script does not execute trades, manage risk, or replace the need for trader discretion. Market behavior can change quickly, and past behavior detected by the script does not ensure similar future outcomes.
Users should test the script on demo or simulation environments before applying it to live markets and must maintain full responsibility for their own risk management, position sizing, and trade execution.
Trading involves risk, and losses can exceed deposits. By using this script, you acknowledge that you understand and accept all associated risks.
🗓️ FTD Cycle Lite Tracker🗓️ FTD Cycle Lite Tracker (Open Source)This is the simplified, open-source companion to the premium FTD SPIKE PREDICTOR - ML Model.This Lite version focuses purely on time-based cyclic analysis, highlighting the periods when the market is approaching the most well-known FTD-related time windows, based on historical, cyclic patterns.It's the perfect tool for traders who want clean, visual confirmation of anticipated cyclic dates without the complexity or predictive power of a multi-factor model.Key Features of the Lite Version:T+35 Cycle Tracking: Highlights the approximate 49-day calendar cycle (representing 35 trading days) often associated with mandatory Failures-to-Deliver clearing.147-Day Major Cycle: Highlights the long-term institutional cycle commonly observed in assets with complex contract deadlines, anchored from the January 28, 2021 date.Custom Anchor Points: Both cycles allow you to adjust the anchor date to suit different ticker-specific patterns.Visual Windows: Provides clear background shading and shape markers to indicate when the critical 5-day cycle windows are active.👑 Upgrade to the Full Prediction Engine!The open-source Lite version only gives you the calendar dates. The full, proprietary indicator goes far beyond simple calendar counting by telling you how probable a spike is on those dates, and which other factors are confirming the risk.Why Upgrade?FeatureFTD Cycle Lite (Free)FTD SPIKE PREDICTOR (Premium)OutputCalendar Dates0-100% Probability ScoreLogic2 Time Cycles Only7 Weighted Features (ML Model)ConfirmationNoneVolume, Price, Volatility, OPEX, Swap RollConfidenceNone95% Confidence IntervalsSignalsDate MarkersCritical Alerts & Feature BreakdownUnlock the Full PowerYou can get the FTD SPIKE PREDICTOR - ML Model for a one-time fee of $50.00.Since TradingView's invite-only feature is not available, you can contact me directly to gain access:TradingView: Timmy741X.com (Twitter): TimmyCrypto78
Session Open Range, Breakout & Trap Framework - TrendPredator OBSession Open Range, Breakout & Trap Framework — TrendPredator Open Box
Stacey Burke’s trading approach combines concepts from George Douglas Taylor, Tony Crabel, Steve Mauro, and Robert Schabacker. His framework focuses on reading price behaviour across daily templates and identifying how markets move through recurring cycles of expansion, contraction, and reversal. While effective, much of this analysis requires real-time interpretation of session-based behaviour, which can be demanding for traders working on lower intraday timeframes.
The TrendPredator indicators formalize parts of this methodology by introducing mechanical rules for multi-timeframe bias tracking and session structure analysis. They aim to present the key elements of the system—bias, breakouts, fakeouts, and range behaviour—in a consistent and objective way that reduces discretionary interpretation.
The Open Box indicator focuses specifically on the opening behaviour of major trading sessions. It builds on principles found in classical Open Range Breakout (ORB) techniques described by Tony Crabel, where a defined time window around the session open forms a structural reference range. Price behaviour relative to this range—breaking out, failing back inside, or expanding—can highlight developing session bias, potential trap formation, and directional conviction.
This indicator applies these concepts throughout the major equity sessions. It automatically maps the session’s initial range (“Open Box”) and tracks how price interacts with it as liquidity and volatility increase. It also incorporates related structural references such as:
* the first-hour high and low of the futures session
* the exact session open level
* an anchored VWAP starting at the session open
* automated expansion levels projected from the Open Box
In combination, these components provide a unified view of early session activity, including breakout attempts, fakeouts, VWAP reactions, and liquidity targeting. The Open Box offers a structured lens for observing how price transitions through the major sessions (Asia → London → New York) and how these behaviours relate to higher-timeframe bias defined in the broader TrendPredator framework.
Core Features
Open Box (Session Structure)
The indicator defines an initial session range beginning at the selected session open. This “Open Box” represents a fixed time window—commonly the first 30 minutes, or any user-defined duration—that serves as a structural reference for analysing early session behaviour.
The range highlights whether price remains inside the box, breaks out, or rejects the boundaries, providing a consistent foundation for interpreting early directional tendencies and recognising breakout, continuation, or fakeout characteristics.
How it works:
* At the session open, the indicator calculates the high and low over the specified time window.
* This range is plotted as the initial structure of the session.
* Price behaviour at the boundaries can illustrate emerging bias or potential trap formation.
* An optional secondary range (e.g., 15-minute high/low) can be enabled to capture early volatility with additional precision.
Inputs / Options:
* Session specifications (Tokyo, London, New York)
* Open Box start and end times (e.g., equity open + first 30 minutes, or any custom length)
* Open Box colour and label settings
* Formatting options for Open Box high and low lines
* Optional secondary range per session (e.g., 15-minute high/low)
* Forward extension of Open Box high/low lines
* Number of historic Open Boxes to display
Session VWAPs
The indicator plots VWAPs for each major trading session—Asia, London, and New York—anchored to their respective session opens. These session-specific VWAPs assist in tracking how value develops through the day and how price interacts with session-based volume distributions.
How it works:
* At each session open, a VWAP is anchored to the open price.
* The VWAP updates throughout the session as new volume and price data arrive.
* Deviations above or below the VWAP may indicate balance, imbalance, or directional control.
* Viewed together, session VWAPs help identify transitions in value across sessions.
Inputs / Options:
* Enable or disable VWAP per session
* Adjustable anchor and end times (optionally to end of day)
* Line styling and label settings
* Number of historic VWAPs to draw
First Hour High/Low Extensions
The indicator marks the high and low formed during the first hour of each session. These reference points often function as early control levels and provide context for assessing whether the session is establishing bias, consolidating, or exhibiting reversal behaviour.
How it works:
* After the session starts, the indicator records the highest and lowest prices during the first hour.
* These levels are plotted and extended across the session.
* They provide a visual reference for observing reactions, targets, or rejection zones.
Inputs / Options:
* Enable or disable for each session
* Line style, colour, and label visibility
* Number of historic sessions displayed
EQO Levels (Equity Open)
The indicator plots the opening price of each configured session. These “Equity Open” levels represent short-term reference points that can attract price early in the session.
Once the level is revisited after the Open Box has formed, it is automatically cut to avoid clutter. If not revisited, the line remains as an untested reference, similar to a naked point of control.
How it works:
* At session open, the open price is recorded.
* The level is plotted as a local reference.
* If price interacts with the level after the Open Box completes, the line is cut.
* Untested EQOs extend forward until interacted with.
Inputs / Options:
* Enable/disable per session
* Line style and label settings
* Optional extension into the next day
* Option for cutting vs. hiding on revisit
* Number of historic sessions displayed
OB Range Expansions (Automatic)
Range expansions are calculated from the height of the Open Box. These levels provide structured reference zones for identifying potential continuation or exhaustion areas within a session.
How it works:
* After the Open Box is formed, multiples of the range (e.g., 1×, 2×, 3×) are projected.
* These expansion levels are plotted above and below the range.
* Price reactions near these areas can illustrate continuation, hesitation, or potential reversal.
Inputs / Options:
* Enable or disable per session
* Select number of multiples
* Line style, colour, and label settings
* Extension length into the session
Stacey Burke 12-Candle Window Marker
The indicator can highlight the 12-candle window often referenced in Stacey Burke’s session methodology. This window represents the key active period of each session where breakout attempts, volatility shifts, and reversal signatures often occur.
How it works:
* A configurable window (default 12 candles) is highlighted from each session open.
* This window acts as a guide for observing active session behaviour.
* It remains visible throughout the session for structural context.
Inputs / Options:
* Enable/disable per session
* Configurable window duration (default: 3 hours)
* Colour and transparency controls
Concept and Integration
The Open Box is built around the same multi-timeframe logic that underpins the broader TrendPredator framework.
While higher-timeframe tools track bias and setups across the H8–D–W–M levels, the Open Box focuses on the H1–M30 domain to define session structure and observe how early intraday behaviour aligns with higher-timeframe conditions.
The indicator integrates with the TrendPredator FO (Breakout, Fakeout & Trend Switch Detector), which highlights microstructure signals on lower timeframes (M15/M5). Together they form a layered workflow:
* Higher timeframes: context, bias, and developing setups
* TrendPredator OB: intraday and intra-session structure
* TrendPredator FO: microstructure confirmation (e.g., FOL/FOH, switches)
This alignment provides a structured way to observe how daily directional context interacts with intraday behaviour.
See the public open source indicator TP FO here (click on it for access):
Practical Application
Before Session Open
* Review previous session Open Box, Open level, and VWAPs
* Assess how higher-timeframe bias aligns with potential intraday continuation or reversal
* Note untested EQO levels or VWAPs that may function as liquidity attractors
During Session Open
* Observe behaviour around the first-hour high/low and higher-timeframe reference levels
* Monitor how the M15 and 30-minute ranges close
* Track reactions relative to the session open level and the session VWAP
After the Open Box completes
* Assess price interaction with Open Box boundaries and first-hour levels
* Use microstructure signals (e.g., FOH/FOL, switches) for potential confirmation
* Refer to expansion levels as reference zones for management or target setting
After Session
* Review how price behaved relative to the Open Box, EQO levels, VWAPs, and expansion zones
* Analyse breakout attempts, fakeouts, and whether intraday structure aligned with the broader daily move
Example Workflow and Trade
1. Higher-timeframe analysis signals a Daily Fakeout Low Continuation (bullish context).
2. The New York session forms an Open Box; price breaks above and holds above the first-hour high.
3. A Fakeout Low + Switch Bar appears on M5 (via FO), after retesting the session VWAP triggering the entry.
4. 1x expansion level serves as reference targets for take profit.
Relation to the TrendPredator Ecosystem
The Open Box is part of the TrendPredator Indicator Family, designed to apply multi-timeframe logic consistently across:
* higher-timeframe context and setups
* intraday and session structure (OB)
* microstructure confirmation (FO)
Together, these modules offer a unified structure for analysing how daily and intraday cycles interact.
Disclaimer
This indicator is for educational purposes only and does not guarantee profits.
It does not provide buy or sell signals but highlights structural and behavioural areas for analysis.
Users are solely responsible for their trading decisions and outcomes.
CandelaCharts - Session Opening📝 Overview
The CandelaCharts – Session Opening indicator highlights a custom session window, builds the live high/low as the session unfolds, and then publishes finalized Range High , Range Low , and Consequent Encroachment (Mid) levels once the window closes. A subtle one‑bar divider marks each new session start, and a shaded box visualizes the evolving range while the session is active.
📦 Features
Discover the core tools this indicator provides—from live range tracking to post‑session levels and alerts.
Custom Session Window – Track any intraday opening window you define (e.g., 09:00–10:00).
Timezone Control – Align sessions precisely with your market using selectable timezones (e.g., America/New_York, GMT±X).
Live Session Box – A translucent box expands in real time as highs/lows update during the session.
Post‑Session Levels – Finalized Range High , Range Low , and CE (Mid) lines print only after the session completes to avoid interim noise.
Session Divider – A one‑bar background tint clearly marks the first bar of each session.
Alerts – Receive notifications at session start and end.
⚙️ Settings
Configure timing, timezone alignment, visuals, and toggles to match your market and workflow.
Session – Defines the specific time range for the session window (e.g., 0900-1000). During this window the indicator tracks the running high/low.
Timezone – Specifies the timezone used to interpret the session window, ensuring alignment with exchange hours.
Colors – Selects the colors for Range High (Up), Range Low (Down), and the session Background box/divider.
Session Range – Shows the finalized Range High/Low/Mid lines outside of the session; lines appear starting one bar after the session closes.
Session Dividers – Enables the one‑bar background tint on the session’s first bar.
⚡️ Showcase
Preview a simple chart example with Session Opening applied.
🚨 Alerts
Set notifications for key moments: when a session begins and when it ends.
Session Start : Triggers on the first bar inside the configured session window.
Session End : Triggers on the first bar after the session window closes.
⚠️ Disclaimer
This section clarifies the risks and intended use.
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Fish OrbThis indicator marks and tracks the first 15-minute range of the New York session open (default 9:30–9:45 AM ET) — a critical volatility period for futures like NQ (Nasdaq).
It helps you visually anchor intraday price action to that initial opening range.
Core Functionality
1. Opening Range Calculation
It measures the High, Low, and Midpoint of the first 15 minutes after the NY market opens (default 09:30–09:45 ET).
You can change the window or timezone in the inputs.
2. Visual Overlays
During the 15-minute window:
A teal shaded box highlights the open range period.
Live white lines mark the current High and Low.
A red line marks the midpoint (mid-range).
These update in real-time as each bar forms.
3. Post-Window Behavior
When the 15-minute window ends:
The High, Low, and Midpoint are locked in.
The indicator draws persistent horizontal lines for those values.
4. Historical Days
You can keep today + a set number of previous days (configurable via “Previous Days to Keep”).
Older days automatically delete to keep charts clean.
5. Line Extension Control
Each day’s lines extend to the right after they form.
You can toggle “Stop Lines at Next NY Open”:
ON: Yesterday’s lines stop exactly at the next NY session open (09:30 ET).
OFF: Lines extend indefinitely across the chart.
Quantile-Based Adaptive Detection🙏🏻 Dedicated to John Tukey. He invented the boxplot, and I finalized it.
QBAD (Quantile-Based Adaptive Detection) is ‘the’ adaptive (also optionally weighted = ready for timeseries) boxplot with more senseful fences. Instead of hardcoded multipliers for outer fences, I base em on a set of quantile-based asymmetry metrics (you can view it as an ‘algorithmic’ counter part of central & standardized moments). So outer bands are Not hardcoded, not optimized, not cross-validated etc, simply calculated at O(nlogn).
You can use it literally everywhere in any context with any continuous data, in any task that requires statistical control, novelty || outlier detection, without worrying and doubting the sense in arbitrary chosen thresholds. Obviously, given the robust nature of quantiles, it would fit best the cases where data has problems.
The thresholds are:
Basis: the model of the data (median in our case);
Deviations: represent typical spread around basis, together form “value” in general sense;
Extensions: estimate data’s extremums via combination of quantile-based asymmetry metrics without relying on actual blunt min and max, together form “range” / ”frame”. Datapoints outside the frame/range are novelties or outliers;
Limits: based also on quantile asymmetry metrics, estimate the bounds within which values can ‘ever’ emerge given the current data generating process stays the same, together form “field”. Datapoints outside the field are very rare, happen when a significant change/structural break happens in current data-generating process, or when a corrupt datapoint emerges.
…
The first part of the post is for locals xd, the second is for the wanderers/wizards/creators/:
First part:
In terms of markets, mostly u gotta worry about dem instruments that represent crypto & FX assets: it’s either activity hence data sources there are decentralized, or data is fishy.
For a higher algocomplexity cost O(nlong), unlike MBAD that is 0(n), this thing (a control system in fact) works better with ishy data (contaminated with wrong values, incomplete, missing values etc). Read about the “ breakdown point of an estimator ” if you wanna understand it.
Even with good data, in cases when you have multiple instruments that represent the same asset, e.g. CL and BRN futures, and for some reason you wanna skip constructing a proper index of em (while you should), QBAD should be better put on each instrument individually.
Another reason to use this algo-based rather than math-based tool, might be in cases when data quality is all good, but the actual causal processes that generate the data are a bit inconsistent and/or possess ‘increased’ activity in a way. SO in high volatility periods, this tool should provide better.
In terms of built-ins you got 2 weightings: by sequence and by inferred volume delta. The former should be ‘On’ all the time when you work with timeseries, unless for a reason you want to consciously turn it off for a reason. The latter, you gotta keep it ‘On’ unless you apply the tool on another dataset that ain’t got that particular additional dimension.
Ain’t matter the way you gonna use it, moving windows, cumulative windows with or without anchors, that’s your freedom of will, but some stuff stays the same:
Basis and deviations are “value” levels. From process control perspective, if you pls, it makes sense to Not only fade or push based on these levels, but to also do nothing when things are ambiguous and/or don’t require your intervention
Extensions and limits are extreme levels. Here you either push or fade, doing nothing is not an option, these are decisive points in all the meanings
Another important thing, lately I started to see one kind of trend here on tradingview as well and in general in near quant sources, of applying averages, percentiles etc ‘on’ other stationary metrics, so called “indicators”. And I mean not for diagnostic or development reasons, for decision making xd
This is not the evil crime ofc, but hillbilly af, cuz the metrics are stationary it means that you can model em, fit a distribution, like do smth sharper. Worst case you have Bayesian statistics armed with high density intervals and equal tail intervals, and even some others. All this stuff is not hard to do, if u aint’t doing it, it’s on you.
So what I’m saying is it makes sense to apply QBAD on returns ‘of your strategy’, on volume delta, but Not on other metrics that already do calculations over their own moving windows.
...
Second part:
Looks like some finna start to have lil suspicions, that ‘maybe’ after all math entities in reality are more like blueprints, while actual representations are physical/mechanical/algorithmic. Std & centralized moments is a math entity that represents location, scale & asymmetry info, and we can use it no problem, when things are legit and consistent especially. Real world stuff tho sometimes deviates from that ideal, so we need smth more handy and real. Add to the mix the algo counter part of means: quantiles.
Unlike the legacy quantile-based asymmetry metrics from the previous century (check quantile skewness & kurtosis), I don’t use arbitrary sets of quantiles, instead we get a binary pattern that is totally geometric & natural (check the code if interested, I made it very damn explicit). In spirit with math based central & standardized moments, each consequent pair is wider empathizing tail info more and more for each higher order metric.
Unlike the classic box plot, where inner thresholds are quartiles and the rest are based on em, here the basis is median (minimises L1), I base inner thresholds on it, and we continue the pattern by basing the further set of levels on the previous set. So unlike the classic box plot, here we have coherency in construction, symmetry.
Another thing to pay attention to, tho for some reason ain’t many talk about it, it’s not conceptually right to think that “you got data and you apply std moments on it”. No, you apply it to ‘centered around smth’ data. That ‘smth’ should minimize L2 error in case of math, L1 error in case of algo, and L0 error in case of learning/MLish/optimizational/whatever-you-cal-it stuff. So in the case of L0, that’s actually the ‘mode’ of KDE, but that’s for another time. Anyways, in case of L2 it’s mean, so we center data around mean, and apply std moments on residuals. That’s the precise way of framing it. If you understand this, suddenly very interesting details like 0th and 1st central moments start to make sense. In case of quantiles, we center data around the median, and do further processing on residuals, same.
Oth moment (I call it init) is always 1, tho it’s interesting to extrapolate backwards the sequence for higher order moments construction, to understand how we actually end up with this zero.
1st moment (I call it bias) of residuals would be zero if you match centering and residuals analysis methods. But for some reason you didn’t do that (e.g centered data around midhinge or mean and applied QBAD on the centered data), you have to account for that bias.
Realizing stuff > understanding stuff
Learning 2981234 human invented fields < realizing the same unified principles how the Universe works
∞
Auto Darvas Boxes## AUTO DARVAS BOXES
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### OVERVIEW
**Auto Darvas Boxes** is a fully-automated, event-driven implementation of Nicolas Darvas’s 1950s box methodology.
The script tracks consolidation zones in real time, verifies that price truly “respects” those zones for a fixed validation window, then waits for the first decisive range violation to mark a directional breakout.
Every box is plotted end-to-end—from the first candle of the sideways range to the exact candle that ruptures it—giving you an on-chart, visually precise record of accumulation or distribution and the expansion that follows.
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### HISTORICAL BACKGROUND
* Nicolas Darvas was a professional ballroom dancer who traded U.S. equities by telegram while touring the world.
* Without live news or Level II, he relied exclusively on **price** to infer institutional intent.
* His core insight: true market-moving entities leave footprints in the form of tight ranges; once their buying (or selling) is complete, price erupts out of the “box.”
* Darvas’s original procedure was manual—he kept notebooks, drew rectangles around highs and lows, and entered only when price punched out of the roof of a valid box.
* This indicator distills that logic into a rolling, self-resetting state machine so you never miss a box or breakout on any timeframe.
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### ALGORITHM DETAIL (FOUR-STATE MACHINE)
**STATE 0 – RANGE DEFINITION**
• Examine the last *N* candles (default 7).
• Record `rangeHigh = highest(high, N) + tolerance`.
• Record `rangeLow = lowest(low, N) – tolerance`.
• Remember the index of the earliest bar in this window (`startBar`).
• Immediately transition to STATE 1.
**STATE 1 – RANGE VALIDATION**
• Observe the next *N* candles (again default 7).
• If **any** candle prints `high > rangeHigh` or `low < rangeLow`, the validation fails and the engine resets to STATE 0 **beginning at the violating candle**—no halfway boxes, no overlap.
• If all *N* candles remain inside the range, the box becomes **armed** and we transition to STATE 2.
**STATE 2 – ARMED (LIVE VISUAL FEEDBACK)**
• Draw a **green horizontal line** at `rangeHigh`.
• Draw a **red horizontal line** at `rangeLow`.
• Lines are extended in real time so the user can see the “live” Darvas ceiling and floor.
• Engine waits indefinitely for a breakout candle:
– **Up-Breakout** if `high > rangeHigh`.
– **Down-Breakout** if `low < rangeLow`.
**STATE 3 – BREAKOUT & COOLDOWN**
• Upon breakout the script:
1. Deletes the live range lines.
2. Draws a **filled rectangle (box)** from `startBar` to the breakout bar.
◦ **Green fill** when price exits above the ceiling.
◦ **Red fill** when price exits below the floor.
3. Optionally prints two labels at the left edge of the box:
◦ Dollar distance = `rangeHigh − rangeLow`.
◦ Percentage distance = `(rangeHigh − rangeLow) / rangeLow × 100 %`.
• After painting, the script waits a **user-defined cooldown** (default = 7 bars) before reverting to STATE 0. The cooldown guarantees separation between consecutive tests and prevents overlapping rectangles.
---
### INPUT PARAMETERS (ALL ADJUSTABLE FROM THE SETTINGS PANEL)
* **BARS TO DEFINE RANGE** – Number of candles used for both the definition and validation windows. Classic Darvas logic uses 7 but feel free to raise it on higher timeframes or volatile instruments.
* **OPTIONAL TOLERANCE** – Absolute price buffer added above the ceiling and below the floor. Use a small tolerance to ignore single-tick spikes or data-feed noise.
* **COOLDOWN BARS AFTER BREAKOUT** – How long the engine pauses before hunting for the next consolidation. Setting this equal to the range length produces non-overlapping, evenly spaced boxes.
* **SHOW BOX DISTANCE LABELS** – Toggle on/off. When on, each completed box displays its vertical size in both dollars and percentage, anchored at the box’s left edge.
---
### REAL-TIME VISUALISATION
* During the **armed** phase you see two extended, colour-coded guide-lines showing the exact high/low that must hold.
* When the breakout finally occurs, those lines vanish and the rectangle instantly appears, coloured to match the breakout direction.
* This immediate visual feedback turns any chart into a live Darvas tape—no manual drawing, no lag.
---
### PRACTICAL USE-CASES & BEST-PRACTICE WORKFLOWS
* **INTRADAY MOMENTUM** – Drop the script on 1- to 15-minute charts to catch tight coils before they explode. The coloured box marks the precise origin of the expansion; stops can sit just inside the opposite side of the box.
* **SWING & POSITION TRADING** – On 4-hour or daily charts, boxes often correspond to accumulation bases or volatility squeezes. Waiting for the box-validated breakout filters many false signals.
* **MEAN-REVERSION OR “FADE” STRATEGIES** – If a breakout immediately fails and price re-enters the box, you may have trapped momentum traders; fading that failure can be lucrative.
* **RISK MANAGEMENT** – Box extremes provide objective, structure-based stop levels rather than arbitrary ATR multiples.
* **BACK-TEST RESEARCH** – Because each box is plotted from first range candle to breakout candle, you can programmatically measure hold time, range height, and post-breakout expectancy for any asset.
---
### CUSTOMISATION IDEAS FOR POWER USERS
* **VOLATILITY-ADAPTIVE WINDOW** – Replace the fixed 7-bar length with a dynamic value tied to ATR percentile so the consolidation window stretches or compresses with volatility.
* **MULTI-TIMEFRAME LOGIC** – Only arm a 5-minute box if the 1-hour trend is aligned.
* **STRATEGY WRAPPER** – Convert the indicator to a full `strategy{}` script, automate entries on breakouts, and benchmark performance across assets.
* **ALERTS** – Create TradingView alerts on both up-breakout and down-breakout conditions; route them to webhook for broker automation.
---
### FINAL THOUGHTS
**Auto Darvas Boxes** packages one of the market’s oldest yet still potent price-action frameworks into a modern, self-resetting indicator. Whether you trade equities, futures, crypto, or forex, the script highlights genuine contraction-expansion sequences—Darvas’s original “boxes”—with zero manual effort, letting you focus solely on execution and risk.
RSI from Rolling VWAP [CHE]Introducing the RSI from Rolling VWAP Indicator
Elevate your trading strategy with the RSI from Rolling VWAP —a cutting-edge indicator designed to provide unparalleled insights and enhance your decision-making on TradingView. This advanced tool seamlessly integrates the Relative Strength Index (RSI) with a Rolling Volume-Weighted Average Price (VWAP) to deliver precise and actionable trading signals.
Why Choose RSI from Rolling VWAP ?
- Clear Trend Detection: Our enhanced algorithms ensure accurate identification of bullish and bearish trends, allowing you to capitalize on market movements with confidence.
- Customizable Time Settings: Tailor the time window in days, hours, and minutes to align perfectly with your unique trading strategy and market conditions.
- Flexible Moving Averages: Select from a variety of moving average types—including SMA, EMA, WMA, and more—to smooth the RSI, providing clearer trend analysis and reducing market noise.
- Threshold Alerts: Define upper and lower RSI thresholds to effortlessly spot overbought or oversold conditions, enabling timely and informed trading decisions.
- Visual Enhancements: Enjoy a visually intuitive interface with color-coded RSI lines, moving averages, and background fills that make interpreting market data straightforward and efficient.
- Automatic Signal Labels: Receive immediate bullish and bearish labels directly on your chart, signaling potential trading opportunities without the need for constant monitoring.
Key Features
- Inspired by Proven Tools: Building upon the robust foundation of TradingView's Rolling VWAP, our indicator offers enhanced functionality and greater precision.
- Volume-Weighted Insights: By incorporating volume into the VWAP calculation, gain a deeper understanding of price movements and market strength.
- User-Friendly Configuration: Easily adjust settings to match your trading preferences, whether you're a novice trader or an experienced professional.
- Hypothesis-Driven Analysis: Utilize hypothetical results to backtest strategies, understanding that past performance does not guarantee future outcomes.
How It Works
1. Data Integration: Utilizes the `hlc3` (average of high, low, and close) as the default data source, with customization options available to suit your trading needs.
2. Dynamic Time Window: Automatically calculates the optimal time window based on an auto timeframe or allows for fixed time periods, ensuring flexibility and adaptability.
3. Rolling VWAP Calculation: Accurately computes the Rolling VWAP by balancing price and volume over the specified time window, providing a reliable benchmark for price action.
4. RSI Analysis: Measures momentum through RSI based on Rolling VWAP changes, smoothed with your chosen moving average for enhanced trend clarity.
5. Actionable Signals: Detects and labels bullish and bearish conditions when RSI crosses predefined thresholds, offering clear indicators for potential market entries and exits.
Seamless Integration with Your TradingView Experience
Adding the RSI from Rolling VWAP to your TradingView charts is straightforward:
1. Add to Chart: Simply copy the Pine Script code into TradingView's Pine Editor and apply it to your desired chart.
2. Customize Settings: Adjust the Source Settings, Time Settings, RSI Settings, MA Settings, and Color Settings to align with your trading strategy.
3. Monitor Signals: Watch for RSI crossings above or below your set thresholds, accompanied by clear labels indicating bullish or bearish trends.
4. Optimize Your Trades: Leverage the visual and analytical strengths of the indicator to make informed buy or sell decisions, maximizing your trading potential.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Get Started Today
Transform your trading approach with the RSI from Rolling VWAP indicator. Experience the synergy of momentum and volume-based analysis, and unlock the potential for more accurate and profitable trades.
Download now and take the first step towards a more informed and strategic trading journey!
For further inquiries or support, feel free to contact
Best regards
Chervolino
Inspired by the acclaimed Rolling VWAP by TradingView
