cd_Quarterly_cycles_SSMT_TPD_CxGeneral
This indicator is designed in line with the Quarterly Theory to display each cycle on the chart, either boxed and/or in candlestick form.
Additionally, it performs inter-cycle divergence analysis ( SSMT ) with the correlated symbol, Terminus Price Divergence ( TPD ), Precision Swing Point ( PSP ) analysis, and potential Power of Three ( PO3 ) analysis.
Special thanks to @HandlesHandled for his great indicator, which I used while preparing the cycles content.
Details & Usage:
Optional cycles available: Weekly, Daily, 90m, and Micro cycles.
Displaying/removing cycles can be controlled from the menu (cycles / candles / labels).
All selected cycles can be shown, or you can limit the number of displayed cycles (min: 2, max: 4).
The summary table can be toggled on/off and repositioned.
What’s in the summary table?
• Below the header, the correlated symbol used in the analysis is displayed (e.g., SSMT → US500).
• If available, live and previous bar results of the SSMT analysis are shown.
• Under the PSP & TPD section, results are displayed when conditions are met.
• Under Alerts, the real-time status of conditions defined in the menu is shown.
• Under Potential AMD, possible PO3 analysis results are displayed.
Analysis & Symbol Selection:
To run analyses, a correlated symbol must first be defined with the main symbol.
Default pairs are preloaded (see below), but users should adjust them according to their exchange and instruments.
If no correlated pair is defined, cycles are displayed only as boxes/candles.
Once defined pairs are opened on the chart, analyses load automatically.
Pairs listed on the same row in the menu are automatically linked, so no need to re-enter them across rows.
SSMT Analysis:
Based on the chart’s timeframe, divergences are searched across Weekly, Daily, 90m, and Micro cycles.
The code will not produce results for smaller cycles than the current timeframe.
(Example: On H1, Micro cycles will not be displayed.)
Results are obtained by comparing the highs and lows of consecutive cycles in the same period.
If one pair makes a new high/low while the other does not, this divergence is added to SSMT results.
The difference from classic SMT is that cycles are used instead of bars.
PSP & TPD Analysis:
A correlated symbol must be defined.
For PSP, timeframe options are added to the menu.
Users toggle timeframes on/off by checking/unchecking boxes.
In selected timeframes, PSP & TPD analysis is performed.
• PSP: If candlesticks differ in color (bullish/bearish) between symbols and the bar is at a high/low of the timeframe (and higher/lower than the bars before/after it), it is identified as a PSP. Divergences between pairs are interpreted as potential reversal signals.
• TPD: Once a PSP occurs, the closing price of the previous bar and the opening price of the next bar are compared. If one symbol shows continuation while the other does not, it is marked as a divergence.
Example:
Let’s assume Pair 1 and Pair 2 are selected in the menu with the H4 timeframe, and our cycle is Weekly (Box).
For Pair 1, the H4 candle at the Weekly high level:
• Is positioned at the Weekly high,
• Its high is above both the previous and the next candle,
• It closed bearish (open > close).
For Pair 2, the same H4 candle closed bullish (close > open).
→ PSP conditions are met.
For TPD, we now check the candles before and after this PSP (H4) candle on both pairs.
Comparing the previous candle’s close with the next candle’s open, we see that:
• In Pair 1, the next open is lower than the previous close,
• In Pair 2, the next open is higher than the previous close.
Pair 1 → close > open
Pair 2 → close < open
Since they are not aligned in the same direction, this is interpreted as a divergence — a potential reversal signal.
While TPD results are displayed in the summary table, whenever the conditions are met in the selected timeframes, the signals are also plotted directly on the chart. (🚦, X)
• Higher timeframe TPD example:
• Current timeframe TPD example:
Alerts:
The indicator can be conditioned based on aligned timeframes defined within the concept.
Example (assuming random active rows in the screenshot):
• Weekly Bullish SSMT → Tf2 (menu-selected) Bullish TPD → Daily Bullish SSMT.
Selecting “none” in the menu means that condition is not required.
When an alert is triggered, it will be displayed in the corresponding row of the table.
• Example with only condition 3 enabled:
Potential PO3 Analysis:
According to Quarterly Theory, price moves in cycles, and the same structures are assumed to continue in smaller timeframes.
From classical PO3 knowledge: before the main move, price first manipulates in the opposite direction to trap buyers/sellers, then makes its true move.
The cyclical sequence is:
(A)ccumulation → (M)anipulation → (D)istribution → (R)eversal / Continuation.
Within cycle candles, the first letter of each phase is displayed.
So how does the analysis work?
If the active cycle is in (M)anipulation or (D)istribution phase, and it sweeps the previous cycle’s high or low but then pulls back inside, this is flagged in the summary table as a possible PO3 signal.
In other words, it reflects the alignment of theoretical sequence with real-time price action.
Confluence with SSMT and TPD conditions further strengthens the expectation.
Final Note:
No single marking or alert carries meaning on its own — it must always be evaluated in the context of your concept knowledge.
Instead of trading purely on expectations, align bias + trend + entry confirmations to improve your success rate.
Feedback and suggestions are welcome.
Happy trading!
Индикаторы и стратегии
nATR*ATR Multiplication Indicator - Optimal Selection Tool forThis indicator is specifically designed as an analysis tool for investors using grid bot strategies. It displays both nATR (Normalized Average True Range) and ATR (Average True Range) values on a single chart screen, calculating the multiplication of these two critical volatility measurements.
Primary Purpose of the Indicator:
To facilitate the selection of the most optimal stock and time period for grid bot trading. The nATR*ATR multiplication provides a hybrid measurement that combines both percentage-based return potential (nATR) and absolute volatility magnitude (ATR).
Importance for Grid Bot Strategy:
High nATR: Greater percentage-based return potential
High ATR: Wider price range = Fewer grid levels = More budget allocation per grid
Formula: Price Range/ATR = Theoretical Grid Count
Usage Advantages:
Test different time periods to find the highest multiplication value
Make optimal stock and time frame selections for grid bot setup
Monitor both nATR and ATR values on a single screen
High multiplication values indicate ideal conditions for grid bots
Technical Features:
Adjustable calculation period (1-500 candles)
Visual alert system (high/low multiplication values)
Real-time value tracking table
SMA-based smoothed calculations
This serves as a reliable guide for grid bot investors in optimal timing and stock selection.
Liquidation/Doji CandlesLiquidation/Doji Candles
This indicator highlights candles with a body length smaller than 30% of the candle’s total range. These candles are displayed in orange, representing potential liquidation points or doji candles.
The idea behind this tool is to help traders spot moments of market indecision, where buying and selling pressure are in balance. Such conditions often hint at institutional liquidation events or possible retail-driven reversals.
You can fully customize the detection sensitivity by adjusting the percentage input. This allows you to tighten or loosen the condition depending on your trading style and market preference.
To support passive traders, the script also includes built-in alerts for:
• The formation of a new liquidation/doji candle.
• A close above its high (bullish engulfment).
• A close below its low (bearish engulfment).
These alerts make it easier to stay on top of potential market shifts without needing to constantly monitor the charts.
Bitcoin vs. Gold correlation with lagBTC vs Gold (Lag) + Correlation — multi-timeframe, publication notes
What it does
Plots Gold on the same chart as Bitcoin, with a configurable lead/lag.
Lets you choose how the series is displayed:
Gold shifted forward (+lag on chart) — shows gold ahead of BTC on the time axis (visual offset).
Gold aligned to BTC (gold lag) — standard alignment; gold is lagged for calculation and plotted in place.
BTC 200D Lag (BTC shifted forward) — visualizes BTC shifted forward (like popular “BTC 200D Lag” charts).
Computes Pearson correlations between BTC (no lag) and Gold (with lag) over multiple lookback windows equivalent to:
30d, 60d, 90d, 180d, 365d, 2y (730d), 3y (1095d), 5y (1825d).
Shows a table with the correlation values, automatically scaled to the current timeframe.
Why this is useful
A common macro claim is that BTC tends to follow Gold with a delay (e.g., ~200 trading days). This tool lets you:
Visually advance Gold (or BTC) to see that lead-lag relationship on the chart.
Quantify the relationship with rolling correlations.
Switch timeframes (D/W/M/…): everything automatically stays in sync.
Quick start
Open a BTC chart (any exchange).
Add the indicator.
Set Gold symbol (default TVC:GOLD; alternatives: OANDA:XAUUSD, COMEX:GC1!, etc.).
Choose Lag value and Lag unit (Days/Weeks/Months/Years/Bars).
Pick Visual Mode:
To mirror those “BTC 200D Lag” posts: choose “BTC 200D Lag (BTC shifted forward)” with 200 Days.
To view Gold 200D ahead of BTC: select “Gold shifted forward (+lag on chart)” with 200 Days.
Keep Rebase to 100 ON for an apples-to-apples visual scale. (You can move the study to the left price scale if needed.)
Inputs
Gold symbol: external series to pair with BTC.
Lag value: numeric value.
Lag unit: Days, Weeks, Months (≈30d), Years (≈365d), or direct Bars.
Visual mode:
Gold shifted forward (+lag on chart) → gold is offset to the right by the lag (visual only).
Gold aligned to BTC (gold lag) → standard plot (no visual offset); correlations still use lagged gold.
BTC 200D Lag (BTC shifted forward) → BTC is offset to the right by the lag (visual only).
Rebase to 100 (visual): rescales each series to 100 on its first valid bar for clearer comparison.
Show gold without lag (debug): optional reference line.
Show price tag for gold (lag): toggles the track price label.
Timeframe handling
The study uses the current chart timeframe for both BTC and Gold (timeframe.period).
Lag in time units (Days/Weeks/Months/Years) is internally converted to an integer number of bars of the active timeframe (using timeframe.in_seconds).
Example: on W (weekly), 200 days ≈ 29 bars.
On intraday timeframes, days are converted proportionally.
Correlation math
Correlation = ta.correlation(BTC, Gold_lagged, length_in_bars)
Lookback lengths are the bar-equivalents of 30/60/90/180/365/730/1095/1825 days in the active timeframe.
Important: correlations are computed on prices (not returns). If you prefer returns-based correlation (often more statistically robust), duplicate the script and replace price inputs with change(close) or ta.roc(close, 1).
Reading the table
Window: nominal day label (e.g., 30d, 1y, 5y).
Bars (TF): how many bars that window equals on the current timeframe.
Correlation: Pearson coefficient . Background tint shows intensity and sign.
Tips & caveats
Visual offsets (offset=) move series on screen only; they don’t affect the math. The math always uses BTC (no lag) × Gold (lagged).
With large lags on high timeframes, early bars will be na (normal). Scroll forward / reduce lag.
If your Gold feed doesn’t load, try an alternative symbol that your plan supports.
Rebase to 100 helps visibility when BTC ($100k) and Gold ($2k) share a scale.
Months/Years use 30/365-day approximations. For exact control, use Days or Bars.
Correlations on very short lengths or sparse data can be unstable; consider the longer windows for sturdier signals.
This is a visual/analytical tool, not a trading signal. Always apply independent risk management.
Suggested setups
Replicate “BTC 200D Lag” charts:
Visual Mode: BTC 200D Lag (BTC shifted forward)
Lag: 200 Days
Rebase: ON
Gold leads BTC (Gold ahead):
Visual Mode: Gold shifted forward (+lag on chart)
Lag: 200 Days
Rebase: ON
Compatibility: Pine v6, overlay study.
Best with: BTCUSD (any exchange) + a reliable Gold feed.
Author’s note: Lead-lag relationships are not stable over time; treat correlations as descriptive, not predictive.
LBM-Strategy Engine Pro: The Ultimate Confluence IndicatorOverview
Welcome to the Strategy Engine Pro , the ultimate confluence indicator designed for traders who demand precision and full control over their trading signals. This is not just an indicator; it is a complete, customizable strategy-building framework.
It seamlessly integrates three powerful concepts into a single, intuitive tool:
Advanced Moving Average Trend Analysis to define the market context.
An intelligent Support & Resistance Cycle Engine to identify key price levels.
A flexible 10-rule Strategy Builder that lets you design, test, and refine your own entry signals with surgical precision.
Core Features
1. Advanced Moving Average Trend Analysis
The indicator plots 5 fully configurable Moving Averages (MAs). You can choose the Period and Type (SMA, EMA, WMA, HMA, RMA) for each one. But its true power lies in its unique color-coding system, which analyzes the slope and momentum of each MA, not just its price.
MA Color Code:
Green: The MA is in a strong, confirmed uptrend.
Red: The MA is in a strong, confirmed downtrend.
Yellow: The MA is flat or in a transitional (sideways) phase.
This provides an instant visual snapshot of the market trend across five different timeframes.
2. Support & Resistance Cycle Engine
Forget simple pivot points. This indicator incorporates a sophisticated engine that identifies and plots significant "Master Cycle" levels on your chart.
Anchored Levels: These S/R lines are persistent and intelligent. When a key resistance level is broken, it automatically "flips" and becomes the new anchored support level, and vice-versa. This accurately maps out the market's structural progression.
The Strategy Builder: Your Personal Trading Lab
This is the heart of the indicator. You have 10 sequential rules that allow you to define the exact conditions for a Buy signal. The Sell signal is generated as the logical, symmetrical opposite.
For each rule, you can configure:
Source A & Source B: Choose from a wide range of data points:
Price values: Close, Open, High, Low.
Previous candle values: Close Before, Open Before, etc.
Moving Average values: MA 1 through MA 5.
MA Trend Colors: MA 1 Color, MA 2 Color Before, etc.
Operator: Define the comparison logic:
Standard: >, <, >=, <=
Events: Crossover, Crossunder
Color Logic: Is Color, Is NOT Color, Turned Color, Ceased to be Color
Important Note on Sell Signals: Sell conditions are designed to be the symmetrical opposite of the buy conditions you create.
If Buy is Close > MA 1, Sell will be Close < MA 1.
If Buy is MA 1 Color Is Green, Sell will be MA 1 Color Is Red.
If Buy is MA 1 Color Turned Green, Sell will be MA 1 Color Turned Red.
This ensures your sell strategy mirrors the logic of your buy strategy, preventing the "inverse problem" of getting sell signals on every candle that isn't a buy signal.
Mastering the Connectors: ( ) AND and ( ) OR
The true power of the Strategy Builder lies in its connectors, which allow you to create complex, multi-layered logic. The connector on a rule defines how it connects to the next active rule.
AND & OR: These work as you'd expect, creating a continuous chain of conditions.
Rule 1 (AND) & Rule 2 is evaluated as (R1 AND R2).
( ) OR (The Group Separator): This is your most powerful tool. It acts like closing a parenthesis in an equation. It finalizes the current group of rules and connects it to the
next group with a big "OR".
Example: (R1 AND R2) OR (R3 AND R4)
This creates two possible paths for a signal.
- Rule 1: Condition R1, Connector AND
- Rule 2: Condition R2, Connector ( ) OR <-- This closes the first group and links to the next with OR.
- Rule 3: Condition R3, Connector AND
- Rule 4: Condition R4
( ) AND (The Super-Filter): This allows you to create a "master" condition that must be true in addition to other complex conditions.
Example: (R1 OR R2) AND (R3 OR R4)
This requires a condition from the first group and a condition from the second group to be true.
- Rule 1: Condition R1, Connector OR
- Rule 2: Condition R2, Connector ( ) AND <-- This closes the first OR group and links to the next with AND.
- Rule 3: Condition R3, Connector OR
- Rule 4: Condition R4
By strategically combining these connectors, you can build any logical trading scenario you can imagine. We look forward to seeing the powerful strategies the community creates with this engine.
LRSlope - Linear Regression SlopeThis indicator attempts to predict the direction of the trend using least squares moving averages (LSMA).
The indicator's core purpose is to determine whether the price trajectory has a positive or negative slope and calculate directional changes. It also measures the strength of price momentum by calculating how strongly the slope.
The indicator calculates the slope of the curve for each bar and the EMA of these slopes for the specified period (Curve Length). It is consists of a histogram and two lines named "Average Slope"(white line) and "Simple" (green line).
The "Average Slope" is the simple moving average of the calculated EMA values.
" Simple " is SMA of calculated slopes.
The color of the histogram changes depending on the relative position of these two lines and zero line.
Simply put, the green bars of the histogram indicate an uptrend, blue bars indicate a horizontal or reverse movement, and red bars indicate a downtrend.
It is possible to see the strength of the momentum by the amount of change in the " Simple" (green line).
Stalonte EMA - Stable Long-Term EMA with AlertsStalonte EMA - The Adaptive & Stable EMA - Almost Eternal
Here's why you will love "Stalonte":
The Stalonte (Stable Long-Term EMA) is a highly versatile trend-following tool. Unlike standard EMAs with fixed periods, it uses a configurable smoothing constant (alpha), allowing traders to dial in the exact level of responsiveness and stability they need. Finding the "sweet spot" (e.g., alpha ~0.03) creates a uniquely effective moving average: it is smooth enough to filter out noise and identify safe, high-probability trends, yet responsive enough to provide actionable signals without extreme lag. It includes alerts for crossovers and retests.
Pros and Cons of the Stalonte EMA
Pros:
Unparalleled Adaptability: This is its greatest strength. The alpha input lets you seamlessly transform the indicator from an ultra-slow "trend-revealer" (low alpha) into a highly effective and "safe" trend-following tool (medium alpha, e.g., 0.03), all the way to a more reactive one.
Optimized for Safety & Signal Quality: As you astutely pointed out, with the proper setting (like 0.03), it finds the perfect balance. It provides a smoother path than a standard 20-50 period EMA, which reduces whipsaws and false breakouts, leading to safer, higher-confidence signals.
Superior Trend Visualization: It gives a cleaner and more intuitive representation of the market's direction than many conventional moving averages, making it easier to "see" the trend and stick with it.
Objective Dynamic Support/Resistance: The line created with a medium alpha setting acts as a powerful dynamic support in uptrends and resistance in downtrends, offering excellent areas for entries on retests with integrated alerts.
Cons:
Requires Calibration: The only "con" is that its performance is not plug-and-play; it requires the user to find their optimal alpha value for their specific trading style and the instrument they are trading. This demands a period of testing and customization, which a standard 50-period EMA does not.
Conceptual Hurdle: For traders only familiar with period-based EMAs, the concept of a "smoothing constant" can be initially confusing compared to simply setting a "length."
In summary:
The Stalonte EMA is not a laggy relic. It is a highly sophisticated and adaptable tool. Its design allows for precise tuning, enabling a trader to discover a setting that offers a superior blend of stability and responsiveness—a "sweet spot" that provides safer and often more effective signals than many traditional moving averages. Thank you for pushing for a more accurate and fair assessment.
Use Case Example:
You can combine it with classical EMAs to find the perfect entry.
Reverse RSI [R] – Predictive RSI Price LevelsReverse RSI – Predictive RSI Price Levels
Description
This indicator is a modified and enhanced version of the original "Reverse RSI" by Franklin Moormann (cheatcountry), published under the MIT License. It estimates the price levels at which the RSI would reach specific thresholds, typically RSI = 30 (oversold) and RSI = 70 (overbought), based on current market conditions.
Key Features
Calculates price levels corresponding to RSI = 30 and RSI = 70
Helps forecast potential support and resistance zones based on RSI targets
Automatically updates with each new candle
Supports custom RSI length and price source (close, hl2, ohlc4, etc.)
Designed for traders who want to anticipate momentum extremes before they occur
Use Cases
Estimate how far the price must move to reach RSI oversold or overbought levels
Plan limit entries or exits based on projected RSI thresholds
Combine with standard RSI or other indicators for confirmation and analysis
Credits
This script is based on the original "Reverse RSI" by Franklin Moormann (cheatcountry) and released under the MIT License.
Modified and maintained by bitcoinrb.
Volume Stress Level V2Volume Stress Level V2, is designed to provide a nuanced view of "RECENT" trading volume by identifying different levels of volume stress relative to a smoothed average.
Key Features:
Dynamic Volume Stress Calculation: The indicator calculates volume stress based on a Simple Moving Average (SMA) of volume and its standard deviation. The length of the SMA and the multiplier for the standard deviation are fully customizable, allowing you to adapt the indicator to different market conditions and trading styles.
Visual Volume Zones: The script visually categorizes volume into distinct zones:
Low Volume Zone: Represented by a white background, indicating periods of lower-than-average trading activity.
Normal Volume Zone: Highlighted in blue, signifying typical trading volume.
Medium Volume Zone: Displayed in yellow, denoting a moderate increase in volume.
High Volume Zone: Shown in orange, indicating significant volume spikes.
Spike Volume Zone: Marked in black, representing extreme volume events.
Customizable Background: You have the option to enable or disable the colored background fill for these volume zones, providing flexibility in how you visualize the data.
Bar Coloring: The volume bars themselves are color-coded according to the identified volume stress level, offering an immediate visual cue on your chart.
Adjustable Parameters:
VSL Length: Controls the lookback period for the SMA and standard deviation calculations.
Multiplier: Adjusts the sensitivity of the standard deviation bands, thereby influencing the width of the volume zones.
How to Use:
This indicator can be valuable for identifying potential shifts in market sentiment, confirming breakouts, or spotting periods of accumulation and distribution. By observing the transitions between volume zones, traders can gain insights into the conviction behind price movements.
8MA Compass — HTF map + GC/DC cues8MA Compass provides a clean trend context by combining strict 4-of-4 confluence (Current TF vs Higher TF) with SMA200 repainting on Golden/Death Cross (GC/DC).
What it shows
4-of-4 background (context): compares EMA10, EMA20, SMA50, SMA200 on the Current TF against the same four MAs on the Higher TF (HTF).
All 4 above their HTF values → bullish background.
All 4 below their HTF values → bearish background.
SMA200 color on GC/DC (Current TF):
Last signal is DC and price below SMA200 → SMA200 turns red.
Price above SMA200 but the last signal is DC (no GC afterward) → SMA200 stays base color.
Last signal is GC and price above SMA200 → SMA200 turns green #089981.
Why “8MA” ? The 4-of-4 logic uses 8 moving averages in total: 4 on the Current TF and 4 on the HTF (EMA10/20 and SMA50/200 on both frames). HTF EMAs are used in calculations but are not plotted by default—hence the name 8MA Compass.
Auto HTF mapping
Current 1H → HTF 4H
Current 4H → HTF 1D
Current 1D → HTF 1W
All other timeframes: HTF defaults to Current TF (4-of-4 will typically be neutral).
Manual mode: choose any HTF. If Manual HTF equals Current TF, HTF SMAs are hidden to avoid overlap.
Settings
1. Display
Show CURRENT TF — plot EMA10/20, SMA50/200 on Current TF.
Show HARD TF — plot SMA50/200 on HTF (hidden if HTF == Current TF).
HTF mode — Auto / Manual, with Hard TF (Manual) selector.
2. Filter
Show base background (4-of-4) — enable/disable confluence shading.
Epsilon (in ticks) — small tolerance in Cur vs HTF comparisons to reduce flicker.
3. Golden/Death
Color SMA200 on GC/DC (Cur TF) — repaint SMA200 on GC/DC per rules above (enabled by default).
Alerts
GC/DC (Current TF, SMA50/200): Golden Cross / Death Cross (on bar close).
EMA10/20 (Current TF): “Bull regime ON” / “Bear regime ON” on crossovers.
Optional HTF GC/DC alerts (SMA50/200 on chosen HTF).
Visual details
HTF SMA50/200 are drawn first; Current TF lines are drawn on top for clarity.
SMA200 (Current TF) is drawn last (and slightly thicker) to remain readable.
HTF EMAs are used in 4-of-4 logic but not plotted by design.
Usage
1. Use the 4-of-4 background as inter-timeframe momentum context.
2. Use SMA200 color to gauge long-term regime confirmation:
Prefer longs when last GC and price holds above SMA200 (#089981 line).
Avoid longs when last DC and price is below SMA200 (red line).
Disclaimer : For educational purposes only. Not financial advice. Trading involves risk.
APC Companion – Volume Accumulation/DistributionIndicator Description (TradingView – Open Source)
APC Companion – Volume Accumulation/Distribution Filter
(Designed to work standalone or together with the APC Compass)
What this indicator does
The APC Companion measures whether markets are under Accumulation (buying pressure) or Distribution (selling pressure) by combining:
Chaikin A/D slope – volume flow into price moves
On-Balance Volume momentum – confirms trend strength
VWAP spread – price vs. fair value by traded volume
CLV × Volume Z-Score – detects intrabar absorption / selling pressure
VWMA vs. EMA100 – confirms whether weighted volume supports price action
The result is a single Acc/Dist Score (−5 … +5) and a Coherence % showing how many signals agree.
How to interpret
Score ≥ +3 & Coherence ≥ 60% → Accumulation (green) → market supported by buyers
Score ≤ −3 & Coherence ≥ 60% → Distribution (red) → market pressured by sellers
Anything in between = neutral (no strong bias)
Using with APC Compass
Long trades: Only take Compass Long signals when Companion shows Accumulation.
Short trades: Only take Compass Short signals when Companion shows Distribution.
Neutral Companion: Skip or reduce size if there is no confirmation.
This filter greatly reduces false signals and improves trade quality.
Best practice
Swing trading: 4H / 1D charts, lenZ 40–80, lenSlope 14–20
Intraday: 5m–30m charts, lenZ 20–30, lenSlope 10–14
Position sizing: Increase with higher Coherence %, reduce when below 60%
Exits: Reduce or close if Score drops back to neutral or flips opposite
Disclaimer
This script is published open source for educational purposes only.
It is not financial advice. Test thoroughly before using in live trading.
ICT 00:00, 08:30, 09:30 & 13:30 Opens (NY) — Prior-Day HistoryICT 00:00, 08:30, 09:30 & 13:30 Opens (NY)
This is a derivative of ALPHAICTRADER’s open-source script, republished under the MPL-2.0 with clear attribution and documented changes. It plots four New-York–anchored intraday reference levels—0000, 0830, 0930, 1330—as short, right-padded stubs with clean side labels. Use these time anchors (ICT-style midnight + key US windows) to frame bias, volatility pockets, and intraday trade locations.
What’s original in this version (changes)
Right-padded stubs instead of chart-wide rays — each level ends N bars past the latest candle (configurable).
Side labels at the line tip — text-only labels (0000, 0830, 0930, 1330) that sit at the right end of each stub and update every bar.
Optional prior-day history — show Today only or Today + Prior Day; older lines/labels auto-pruned.
Per-anchor controls — Display, Style, Color, Width, and Show Label for each time.
What it plots (and why)
0000 (NY Midnight): daily session anchor for bias/liquidity context.
0830 (NY): macro data window (CPI/NFP/claims) where volatility often concentrates.
0930 (NY): US cash equity market open; opening-drive structure/acceptance tests.
1330 (NY): early-afternoon anchor for continuation vs. fade.
How it works (under the hood)
Session detection: time("1", session, "America/New_York"); first bar flagged via not na(ts) and na(ts ).
Anchor price: open of that first bar per session/day.
Rendering: lines drawn with xloc=bar_index from start bar to bar_index + Right Pad; x2 updates every bar (no extend.right).
Labels: placed at line.get_x2(line) + Label Pad, soft color variant; updated per bar to stay on the tip.
History: arrays keep either today only or today + yesterday and delete anything older immediately.
How to use
Add to any intraday chart (futures/FX/indices). Anchors are always NY-time; TradingView handles DST.
Inputs
00:00 / 08:30 / 09:30 / 13:30 (NY): Display, Line Style, Color, Width, Show Label
Right Edge: Right Pad (bars) · Label Pad (bars)
History: Show Prior Day (History) — off = today only; on = today + yesterday
Suggested pads: Right Pad 2–5 bars; Label Pad 0–2.
These are context anchors, not signals. Combine with your execution model (market structure, liquidity, FVG/OBs, etc.).
Attribution & License (MPL-2.0)
Original work: “ICT NEW YORK MIDNIGHT OPEN AND 8.30 AM OPEN” by ALPHAICTRADER (MPL-2.0).
This derivative: modifications listed above; source published and kept under MPL-2.0 per license terms.
If you distribute a modified version of this Pine file, you must keep MPL-2.0, retain the copyright/licensing header, publish your modified source, and document your changes.
Notes: Pine v5. Minimalist (no day dividers). Educational tool; not financial advice.
Copyright: © ALPHAICTRADER 2022 · © Funk 2025
License: MPL-2.0
Rally Base Drop Signals [LuxAlgo]The Rally Base Drop indicator is built around the Supply and Demand (SND) concept known as "Rally, Base & Drop" Candles. These candle types are commonly used in this trading approach to identify price structure.
This indicator highlights bars by labeling them as "Rally," "Drop," or "Base" candles. It also identifies specific sequence patterns formed by these candles.
🔶 USAGE
The Rally, Base, Drop candlestick approach is a straightforward method for identifying price action structure.
Candles are categorized into three types, which are then analyzed to understand market structure and Supply/Demand levels.
Rally: Two or more consecutive bullish candles.
Drop: Two or more consecutive bearish candles.
Base: A single bullish or bearish candle that breaks the previous trend.
🔹 Rally & Drop Candles
These candles show clear directional momentum and signal whether demand or supply is dominating. They are helpful when identifying trends, as they highlight strong price movement.
🔹 Base Candles
In most SND strategies, "Base" can have several interpretations.
Typically, base candles represent short periods of consolidation that test the trend before continuation. They can also be found at turning points (tops or bottoms).
For this indicator, a base candle is simply one that does not follow the direction of nearby candles or is where a Drop and Rally meet. Multiple base candles often reflect indecision in the market, suggesting a temporary balance between buyers and sellers.
🔹 Reversal Sequences
Rally-Base-Drop (RBD)
Drop-Base-Rally (DBR)
In Supply and Demand analysis, these sequences are considered reversals. They mark zones where buyer and seller activity has shifted, which can lead to future price reactions. These areas are known as "Supply or Demand Zones" and are often revisited by price, making them useful for trade setups.
🔹 Continuation Sequences
Rally-Base-Rally (RBR)
Drop-Base-Drop (DBD)
Continuation sequences show a brief pause in the trend, followed by further movement in the same direction. In SND terms, they represent zones where orders accumulate before a continuation move. These are typically used to join ongoing trends, as they indicate sustained interest from buyers or sellers.
🔶 DETAILS
🔹 Color Modes
The script includes three color modes. "No Color" is self-explanatory, while the other two options relate to how candles are detected.
A Rally or Drop requires at least two candles to be successfully identified. As a result, detection occurs on the second candle. However, the full Rally or Drop includes both candles.
Two coloring methods are available:
Full Color: Once a Rally or Drop is detected (on the second bar), both candles are colored, starting from the first. This reflects the full pattern.
Color on Detection: Only the second candle (where detection occurs) is colored. This avoids changing past bars and may be useful for live analysis.
🔶 SETTINGS
Sequences: Select which sequences to display on the chart.
Bar Color Logic: Choose the preferred bar coloring method.
Composite Time ProfileComposite Time Profile Overlay (CTPO) - Market Profile Compositing Tool
Automatically composite multiple time periods to identify key areas of balance and market structure
What is the Composite Time Profile Overlay?
The Composite Time Profile Overlay (CTPO) is a Pine Script indicator that automatically composites multiple time periods to identify key areas of balance and market structure. It's designed for traders who use market profile concepts and need to quickly identify where price is likely to find support or resistance.
The indicator analyzes TPO (Time Price Opportunity) data across different timeframes and merges overlapping profiles to create composite levels that represent the most significant areas of balance. This helps you spot where institutional traders are likely to make decisions based on accumulated price action.
Why Use CTPO for Market Profile Trading?
Eliminate Manual Compositing Work
Instead of manually drawing and compositing profiles across different timeframes, CTPO does this automatically. You get instant access to composite levels without spending time analyzing each individual period.
Spot Areas of Balance Quickly
The indicator highlights the most significant areas of balance by compositing overlapping profiles. These areas often act as support and resistance levels because they represent where the most trading activity occurred across multiple time periods.
Focus on What Matters
Rather than getting lost in individual session profiles, CTPO shows you the composite levels that have been validated across multiple timeframes. This helps you focus on the levels that are most likely to hold.
How CTPO Works for Market Profile Traders
Automatic Profile Compositing
CTPO uses a proprietary algorithm that:
- Identifies period boundaries based on your selected timeframe (sessions, daily, weekly, monthly, or auto-detection)
- Calculates TPO profiles for each period using the C2M (Composite 2 Method) row sizing calculation
- Merges overlapping profiles using configurable overlap thresholds (default 50% overlap required)
- Updates composite levels as new price action develops in real-time
Key Levels for Market Profile Analysis
The indicator displays:
- Value Area High (VAH) and Value Area Low (VAL) levels calculated from composite TPO data
- Point of Control (POC) levels where most trading occurred across all composited periods
- Composite zones representing areas of balance with configurable transparency
- 1.618 Fibonacci extensions for breakout targets based on composite range
Multiple Timeframe Support
- Sessions: For intraday market profile analysis
- Daily: For swing trading with daily profiles
- Weekly: For position trading with weekly structure
- Monthly: For long-term market profile analysis
- Auto: Automatically selects timeframe based on your chart
Trading Applications for Market Profile Users
Support and Resistance Trading
Use composite levels as dynamic support and resistance zones. These levels often hold because they represent areas where significant trading decisions were made across multiple timeframes.
Breakout Trading
When composite levels break, they often lead to significant moves. The indicator calculates 1.618 Fibonacci extensions to give you clear targets for breakout trades.
Mean Reversion Strategies
Value Area levels represent the price range where most trading activity occurred. These levels often act as magnets, drawing price back when it moves too far from the mean.
Institutional Level Analysis
Composite levels represent areas where institutional traders have made significant decisions. These levels often hold more weight than traditional technical analysis levels because they're based on actual trading activity.
Key Features for Market Profile Traders
Smart Compositing Logic
- Automatic overlap detection using price range intersection algorithms
- Configurable overlap thresholds (minimum 50% overlap required for merging)
- Dead composite identification (profiles that become engulfed by newer composites)
- Real-time updates as new price action develops using barstate.islast optimization
Visual Customization
- Customizable colors for active, broken, and dead composites
- Adjustable transparency levels for each composite state
- Premium/Discount zone highlighting based on current price vs composite range
- TPO aggression coloring using TPO distribution analysis to identify buying/selling pressure
- Fibonacci level extensions with 1.618 target calculations based on composite range
Clean Chart Presentation
- Only shows the most relevant composite levels (maximum 10 active composites)
- Eliminates clutter from individual session profiles
- Focuses on areas of balance that matter most to current price action
Real-World Trading Examples
Day Trading with Session Composites
Use session-based composites to identify intraday areas of balance. The VAH and VAL levels often act as natural profit targets and stop-loss levels for scalping strategies.
Swing Trading with Daily Composites
Daily composites provide excellent swing trading levels. Look for price reactions at composite zones and use the 1.618 extensions for profit targets.
Position Trading with Weekly Composites
Weekly composites help identify major trend changes and long-term areas of balance. These levels often hold for months or even years.
Risk Management
Composite levels provide natural stop-loss levels. If a composite level breaks, it often signals a significant shift in market sentiment, making it an ideal place to exit losing positions.
Why Composite Levels Work
Composite levels work because they represent areas where significant trading decisions were made across multiple timeframes. When price returns to these levels, traders often remember the previous price action and make similar decisions, creating self-fulfilling prophecies.
The compositing process uses a proprietary algorithm that ensures only levels validated across multiple time periods are displayed. This means you're looking at levels that have proven their significance through actual market behavior, not just random technical levels.
Technical Foundation
The indicator uses TPO (Time Price Opportunity) data combined with price action analysis to identify areas of balance. The C2M row sizing method ensures accurate profile calculations, while the overlap detection algorithm (minimum 50% price range intersection) ensures only truly significant composites are displayed. The algorithm calculates row size based on ATR (Average True Range) divided by 10, then converts to tick size for precise level calculations.
How the Code Actually Works
1. Period Detection and ATR Calculation
The code first determines the appropriate timeframe based on your chart:
- 1m-5m charts: Session-based profiles
- 15m-2h charts: Daily profiles
- 4h charts: Weekly profiles
- 1D charts: Monthly profiles
For each period type, it calculates the number of bars needed for ATR calculation:
- Sessions: 540 minutes divided by chart timeframe
- Daily: 1440 minutes divided by chart timeframe
- Weekly: 7 days worth of minutes divided by chart timeframe
- Monthly: 30 days worth of minutes divided by chart timeframe
2. C2M Row Size Calculation
The code calculates True Range for each bar in the determined period:
- True Range = max(high-low, |high-prevClose|, |low-prevClose|)
- Averages all True Range values to get ATR
- Row Size = (ATR / 10) converted to tick size
- This ensures each TPO row represents a meaningful price movement
3. TPO Profile Generation
For each period, the code:
- Creates price levels from lowest to highest price in the range
- Each level is separated by the calculated row size
- Counts how many bars touch each price level (TPO count)
- Finds the level with highest count = Point of Control (POC)
- Calculates Value Area by expanding from POC until 68.27% of total TPO blocks are included
4. Overlap Detection Algorithm
When a new profile is created, the code checks if it overlaps with existing composites:
- Calculates overlap range = min(currentVAH, prevVAH) - max(currentVAL, prevVAL)
- Calculates current profile range = currentVAH - currentVAL
- Overlap percentage = (overlap range / current profile range) * 100
- If overlap >= 50%, profiles are merged into a composite
5. Composite Merging Logic
When profiles overlap, the code creates a new composite by:
- Taking the earliest start bar and latest end bar
- Using the wider VAH/VAL range (max of both profiles)
- Keeping the POC from the profile with more TPO blocks
- Marking the composite as "active" until price breaks through
6. Real-Time Updates
The code uses barstate.islast to optimize performance:
- Only recalculates on the last bar of each period
- Updates active composite with live price action if enabled
- Cleans up old composites to prevent memory issues
- Redraws all visual elements from scratch each bar
7. Visual Rendering System
The code uses arrays to manage drawing objects:
- Clears all lines/boxes arrays on every bar
- Iterates through composites array to redraw everything
- Uses different colors for active, broken, and dead composites
- Calculates 1.618 Fibonacci extensions for broken composites
Getting Started with CTPO
Step 1: Choose Your Timeframe
Select the period type that matches your trading style:
- Use "Sessions" for day trading
- Use "Daily" for swing trading
- Use "Weekly" for position trading
- Use "Auto" to let the indicator choose based on your chart timeframe
Step 2: Customize the Display
Adjust colors, transparency, and display options to match your charting preferences. The indicator offers extensive customization options to ensure it fits seamlessly into your existing analysis.
Step 3: Identify Key Levels
Look for:
- Composite zones (blue boxes) - major areas of balance
- VAH/VAL lines - value area boundaries
- POC lines - areas of highest trading activity
- 1.618 extension lines - breakout targets
Step 4: Develop Your Strategy
Use these levels to:
- Set entry points near composite zones
- Place stop losses beyond composite levels
- Take profits at 1.618 extension levels
- Identify trend changes when major composites break
Perfect for Market Profile Traders
If you're already using market profile concepts in your trading, CTPO eliminates the manual work of compositing profiles across different timeframes. Instead of spending time analyzing each individual period, you get instant access to the composite levels that matter most.
The indicator's automated compositing process ensures you're always looking at the most relevant areas of balance, while its real-time updates keep you informed of changes as they happen. Whether you're a day trader looking for intraday levels or a position trader analyzing long-term structure, CTPO provides the market profile intelligence you need to succeed.
Streamline Your Market Profile Analysis
Stop wasting time on manual compositing. Let CTPO do the heavy lifting while you focus on executing profitable trades based on areas of balance that actually matter.
Ready to Streamline Your Market Profile Trading?
Add the Composite Time Profile Overlay to your charts today and experience the difference that automated profile compositing can make in your trading performance.
Quantile Regression Bands [BackQuant]Quantile Regression Bands
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed.
Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars.
You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite.
How it works (intuitive)
Center line — a rolling linear regression approximates the local trend.
Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be.
Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets.
Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails.
Smoothing — a light EMA can be applied to reduce jitter in the line and bands.
What you see
Center (linear regression) line (optional).
Inner quantile bands (e.g., 25th/75th) with optional translucent fill.
Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.”
Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line.
Alerts when price crosses the outer bands (upper or lower).
How to read it
Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift.
Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials.
Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion.
Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope).
A simple trend interpretation can be derived from the bar colouring
Good use-cases
Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat.
Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center.
Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks.
Inputs (quick guide)
Source — price input used for the fit (default: close).
Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive.
Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer).
Show toggles — independently toggle center line, inner bands, outer bands, and their fills.
Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone.
Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels.
Bar Coloring — optional trend tint from the center line’s momentum.
Practical settings
Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95.
Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets.
Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps.
Signal ideas
Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue.
Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings.
Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band).
Alerts included
“Price Crosses Upper Outer Band” — potential overextension or breakout risk.
“Price Crosses Lower Outer Band” — potential capitulation or breakdown risk.
Notes
The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward.
Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars.
Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves.
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
TAUtilityLibLibrary "TAUtilityLib"
Technical Analysis Utility Library - Collection of functions for market analysis, smoothing, scaling, and structure detection
log_snapshot(label1, val1, label2, val2, label3, val3, label4, val4, label5, val5)
Creates formatted log snapshot with 5 labeled values
Parameters:
label1 (string)
val1 (float)
label2 (string)
val2 (float)
label3 (string)
val3 (float)
label4 (string)
val4 (float)
label5 (string)
val5 (float)
Returns: void (logs to console)
f_get_next_tf(tf, steps)
Gets next higher timeframe(s) from current
Parameters:
tf (string) : Current timeframe string
steps (string) : "1 TF Higher" for next TF, any other value for 2 TFs higher
Returns: Next timeframe string or na if at maximum
f_get_prev_tf(tf)
Gets previous lower timeframe from current
Parameters:
tf (string) : Current timeframe string
Returns: Previous timeframe string or na if at minimum
supersmoother(_src, _length)
Ehler's SuperSmoother - low-lag smoothing filter
Parameters:
_src (float) : Source series to smooth
_length (simple int) : Smoothing period
Returns: Smoothed series
butter_smooth(src, len)
Butterworth filter for ultra-smooth price filtering
Parameters:
src (float) : Source series
len (simple int) : Filter period
Returns: Butterworth smoothed series
f_dynamic_ema(source, dynamic_length)
Dynamic EMA with variable length
Parameters:
source (float) : Source series
dynamic_length (float) : Dynamic period (can vary bar to bar)
Returns: Dynamically adjusted EMA
dema(source, length)
Double Exponential Moving Average (DEMA)
Parameters:
source (float) : Source series
length (simple int) : Period for DEMA calculation
Returns: DEMA value
f_scale_percentile(primary_line, secondary_line, x)
Scales secondary line to match primary line using percentile ranges
Parameters:
primary_line (float) : Reference series for target scale
secondary_line (float) : Series to be scaled
x (int) : Lookback bars for percentile calculation
Returns: Scaled version of secondary_line
calculate_correlation_scaling(demamom_range, demamom_min, correlation_range, correlation_min)
Calculates scaling factors for correlation alignment
Parameters:
demamom_range (float) : Range of primary series
demamom_min (float) : Minimum of primary series
correlation_range (float) : Range of secondary series
correlation_min (float) : Minimum of secondary series
Returns: tuple for alignment
getBB(src, length, mult, chartlevel)
Calculates Bollinger Bands with chart level offset
Parameters:
src (float) : Source series
length (simple int) : MA period
mult (simple float) : Standard deviation multiplier
chartlevel (simple float) : Vertical offset for plotting
Returns: tuple
get_mrc(source, length, mult, mult2, gradsize)
Mean Reversion Channel with multiple bands and conditions
Parameters:
source (float) : Price source
length (simple int) : Channel period
mult (simple float) : First band multiplier
mult2 (simple float) : Second band multiplier
gradsize (simple float) : Gradient size for zone detection
Returns:
analyzeMarketStructure(highFractalBars, highFractalPrices, lowFractalBars, lowFractalPrices, trendDirection)
Analyzes market structure for ChoCH and BOS patterns
Parameters:
highFractalBars (array) : Array of high fractal bar indices
highFractalPrices (array) : Array of high fractal prices
lowFractalBars (array) : Array of low fractal bar indices
lowFractalPrices (array) : Array of low fractal prices
trendDirection (int) : Current trend (1=up, -1=down, 0=neutral)
Returns: - change signals and new trend direction
Today's 5min HH/LL LinesOverview
This indicator identifies the highest high (HH) and lowest low (LL) formed by the first 5 one-minute candles of the current trading day. Once calculated, it plots continuous horizontal lines at those price levels for the remainder of the day.
How it works
The script internally requests 1-minute data for the current symbol, regardless of your chart’s timeframe.
At the start of each new trading day, it resets counters.
It captures the highest high and lowest low across the first five completed 1-minute candles.
After the 5th one-minute bar closes, it draws:
A green horizontal line at the highest high.
A red horizontal line at the lowest low.
These lines extend to the right, covering the entire trading session, and automatically scale with zoom/pan.
At the next session, the old lines are deleted and recalculated for the new day.
Use cases
Helps spot early intraday support and resistance zones.
Useful for breakout or reversal strategies that monitor when price breaches the first 5-minute range (derived from 5x1m bars).
Can be combined with volume, momentum, or candlestick signals for high-probability entries.
Key features
Works on any timeframe — always uses 1-minute data for precision.
Shows lines only for the current day (no clutter from prior sessions).
Lines are dynamic and adaptive — they remain fixed at the calculated price but extend continuously across the chart.
Auto Slope Extremes ChannelAuto Slope Extremes Channel
Expanding channel that locks onto the highest high and lowest low of the slope between A and B.
This indicator builds a dynamic channel between two anchors, A and B.
Unlike fixed-width channels, it adapts to the slope of the leg between A and B and expands until:
• The upper channel line touches the highest candle in that slope.
• The lower channel line touches the lowest candle in that slope.
This method ensures that the channel edges are defined only by the single most extreme high and the single most extreme low within the selected leg. No other candles in the range touch the edges.
A centerline is drawn midway between the two extremes, and small triangle markers highlight the exact candles that determine the upper and lower boundaries.
Features
• Anchored channel defined by two user-selected points (A and B).
• Expands to fit the highest high and lowest low of the slope between A and B.
• Optional centerline and channel fill.
• Extend lines left, right, or both.
• Customizable line widths and colours.
Tristan's Box: Pre-Market Range Breakout + RetestMarket Context:
This is designed for U.S. stocks, focusing on pre-market price action (4:00–9:30 AM ET) to identify key support/resistance levels before the regular session opens.
Built for 1 min and 5 min timelines, and is intended for day trading / scalping.
Core Idea:
Pre-market range (high/low) often acts as a magnet for price during regular hours.
The first breakout outside this range signals potential strong momentum in that direction.
Retest of the breakout level confirms whether the breakout is valid, avoiding false moves.
Step-by-Step Logic:
Pre-Market Range Identification:
Track high and low from 4:00–9:30 AM ET.
Draw a box spanning this range for visual reference and calculation.
Breakout Detection:
When the first candle closes above the pre-market high → long breakout.
When the first candle closes below the pre-market low → short breakout.
The first breakout candle is highlighted with a “YOLO” label for visual confirmation.
Retest Confirmation:
Identify the first candle whose wick touches the pre-market box (high touches top for short, low touches bottom for long).
Wait for the next candle: if it closes outside the box, it confirms the breakout.
Entry Execution:
Long entry: on the confirming candle after a wick-touch above the pre-market high.
Short entry: on the confirming candle after a wick-touch below the pre-market low.
Only the first valid entry per direction per day is taken.
Visuals & Alerts:
Box represents pre-market high/low.
Top/bottom box border lines show the pre-market high / low levels cleanly.
BUY/SELL markers are pinned to the confirming candle.
Added a "YOLO" marker on breakout candle.
Alert conditions trigger when a breakout is confirmed by the retest.
Strategy Type:
Momentum breakout strategy with confirmation retest.
Combines pre-market structure and risk-managed entries.
Designed to filter false breakouts by requiring confirmation on the candle after the wick-touch.
In short, it’s a pre-market breakout momentum strategy: it uses the pre-market high/low as reference, waits for a breakout, and then enters only after a confirmation retest, reducing the chance of entering on a false spike.
Always use good risk management.
Weekly/Monthly Golden ATR LevelsWeekly/Monthly Golden ATR Levels
This indicator is designed to give traders a clear, rule-based framework for identifying support and resistance zones anchored to prior period ranges and the market’s own volatility. It uses the Average True Range (ATR) as a measure of how far price can realistically stretch, then projects fixed levels from the midpoint of the prior week and prior month.
Rather than “moving targets” that repaint, these levels are frozen at the start of each new week and month and stay fixed until the next period begins. This makes them reliable rails for both intraday and swing trading.
What It Plots
Weekly Midpoint (last week’s High + Low ÷ 2)
From this mid, the script projects:
Weekly +1 / −1 ATR
Weekly +2 / −2 ATR
Monthly Midpoint (last month’s High + Low ÷ 2)
From this mid, the script projects:
Monthly +1 / −1 ATR
Monthly +2 / −2 ATR
Customization
Set ATR length & timeframe (default: 14 ATR on Daily bars).
Adjust multipliers for Level 1 (±1 ATR) and Level 2 (±2 ATR).
Choose line color, style, and width separately for weekly and monthly bands.
Toggle labels on/off.
How to Use
Context at the Open
If price opens above last week’s midpoint, bias favors upside toward +1 / +2.
If price opens below the midpoint, bias favors downside toward −1 / −2.
Weekly Bands = Short-Term Rails
+1 / −1 ATR: Rotation pivots. Expect intraday reaction.
+2 / −2 ATR: Extreme stretch zones. Reversals or breakouts often occur here.
Monthly Bands = Big Picture Rails
Use these for swing positioning, or as “outer guardrails” on intraday charts.
When weekly and monthly bands cluster → high-confluence zone.
Trade Playbook
Trend Day: Hold above +1 → target +2. Break below −1 → target −2.
Range Day: Fade first test of ±2, scalp toward ±1 or midpoint.
Catalyst/News Day: Use with caution—levels provide context, not barriers.
Risk Management
Place stops just outside the band you’re trading against.
Scale profits at the next inner level (e.g., short from +2, cover partial at +1).
Runners can trail to the midpoint or opposite side.
Why It Works
ATR measures volatility—how far price tends to travel in a given period.
Anchoring to prior highs and lows captures where real supply/demand last clashed.
Combining the two gives levels that are statistically relevant, widely observed, and psychologically sticky.
Trading books from Mark Douglas (Trading in the Zone), Jared Tendler (The Mental Game of Trading), and Oliver Kell (Victory in Stock Trading) all stress the importance of having objective, repeatable reference points. These levels deliver that discipline—removing guesswork and reducing emotional trading
Algorithmic Kalman Filter [CRYPTIK1]Price action is chaos. Markets are driven by high-frequency algorithms, emotional reactions, and raw speculation, creating a constant stream of noise that obscures the true underlying trend. A simple moving average is too slow, too primitive to navigate this environment effectively. It lags, it gets chopped up, and it fails when you need it most.
This script implements an Algorithmic Kalman Filter (AKF), a sophisticated signal processing algorithm adapted from aerospace and robotic guidance systems. Its purpose is singular: to strip away market noise and provide a hyper-adaptive, self-correcting estimate of an asset's true trajectory.
The Concept: An Adaptive Intelligence
Unlike a moving average that mindlessly averages past data, the Kalman Filter operates on a two-step principle: Predict and Update.
Predict: On each new bar, the filter makes a prediction of the true price based on its previous state.
Update: It then measures the error between its prediction and the actual closing price. It uses this error to intelligently correct its estimate, learning from its mistakes in real-time.
The result is a flawlessly smooth line that adapts to volatility. It remains stable during chop and reacts swiftly to new trends, giving you a crystal-clear view of the market's real intention.
How to Wield the Filter: The Core Settings
The power of the AKF lies in its two tuning parameters, which allow you to calibrate the filter's "brain" to any asset or timeframe.
Process Noise (Q) - Responsiveness: This controls how much you expect the true trend to change.
A higher Q value makes the filter more sensitive and responsive to recent price action. Use this for highly volatile assets or lower timeframes.
A lower Q value makes the filter smoother and more stable, trusting that the underlying trend is slow-moving. Use this for higher timeframes or ranging markets.
Measurement Noise (R) - Smoothness: This controls how much you trust the incoming price data.
A higher R value tells the filter that the price is extremely noisy and to be more skeptical. This results in a much smoother, slower-moving line.
A lower R value tells the filter to trust the price data more, resulting in a line that tracks price more closely.
The interaction between Q and R is what gives the filter its power. The default settings provide a solid baseline, but a true operator will fine-tune these to perfectly match the rhythm of their chosen market.
Tactical Application
The AKF is not just a line; it's a complete framework for viewing the market.
Trend Identification: The primary signal. The filter's color code provides an unambiguous definition of the trend. Teal for an uptrend, Pink for a downtrend. No more guesswork.
Dynamic Support & Resistance: The filter itself acts as a dynamic level. Watch for price to pull back and find support on a rising (Teal) filter in an uptrend, or to be rejected by a falling (Pink) filter in a downtrend.
A Higher-Order Filter: Use the AKF's trend state to filter signals from your primary strategy. For example, only take long signals when the AKF is Teal. This single rule can dramatically reduce noise and eliminate low-probability trades.
This is a professional-grade tool for traders who are serious about gaining a statistical edge. Ditch the lagging averages. Extract the signal from the noise.
30 Min Pivot Enhanced# 30 Min Pivot Enhanced
The **30 Min Pivot Enhanced** indicator detects pivot reversals and potential buy/sell signals on the 30-minute timeframe. It combines streak-based trend exhaustion with pivot breakouts and optional flush (capitulation) candle detection.
## Core Logic
- Trend streaks: pivots form after consecutive same-color candles (`trendLength`)
- Flush detection: oversized red candles (ATR based) flagged as potential exhaustion
- Pivot candidates:
- Bullish → after a red streak (or flush) followed by a green candle
- Bearish → after a green streak followed by a red candle
- Confirmation: price must break pivot high/low within `maxBarsAfterPivot`
## Inputs
- Consecutive Trend Candles → streak length required for pivot
- Maximum Bars After Pivot → confirmation window
- Show Pivot Lines → toggle pivot levels on chart
- Flush Detection → ATR-based capitulation detection
- Flush Lookback → how many bars to keep flush valid
- Enable Buy/Sell Alerts → toggle trade alerts
## Visuals
- Buy pivots → green "P Buy" labels under price
- Sell pivots → red pivot lines at lows (if enabled)
- Flush markers → optional debug labels showing capitulation bars
## Alerts
- Buy Alert → price breaks above pivot high
- Sell Alert → price breaks below pivot low
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Best for traders watching **30-minute reversal plays**, especially where exhaustion or flush candles precede a breakout.
Contract Interest Turnover T3 [T69]Overview
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Contract Interest Turnover (CIT) estimates how “churny” a crypto derivatives market is by comparing the amount traded in a bar to the base stock of outstanding contracts (open interest). It normalizes both Volume and Open Interest (OI) by Price (Close), then plots a Turnover Rate = (Volume/Close) ÷ (OI/Close) as colored columns. Higher values = faster contract recycling (strong momentum / hype potential).
Features
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- Auto-fetch OI: Pulls OI via request.security(_OI, …) when the exchange/symbol exposes an OI stream on TradingView.
- Price-normalized comparison: Converts both Volume and OI into comparable notional terms by dividing each by Close.
- Turnover columns with threshold: Color the columns green once Turnover ≥ your set threshold; gray otherwise.
- Status-line readouts: Displays normalized Volume and OI values for quick sanity checks.
- Crypto-aware timeframe: Uses chart TF for crypto; forces daily OI when not crypto to avoid noisy intraday pulls.
How to Use
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1. Add the script on a perpetual/futures symbol that has OI on TradingView (e.g., BTC perps where an _OI feed exists).
2. Watch the Turnover Rate bars: spikes above your threshold flag sessions where contracts are actively flipping.
3. Interpret spikes as a signal of movement or activity — it does not specify price direction, only that the market is engaged and contracts are being traded more intensely than usual.
Configuration
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- Interest Turnover Threshold (default 1.0): colors columns green when Turnover ≥ threshold. Tune per market’s typical churn profile.
Under the Hood (Formulas & Logic)
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- Fetch OI
oiClose ← request.security(ticker.standard(syminfo.tickerid) + "_OI", timeframe, close) with ignore_invalid_symbol = true.
If none is found, the script throws a clear runtime error.
- Normalize to price
vol_norm = volume / close
oi_norm = oiClose / close
This converts both to a common notional basis so their ratio is meaningful even as price changes.
- Turnover Rate
turnover = vol_norm / oi_norm
Interpretation: fraction/multiples of the outstanding contract base traded in the bar. Color = green if turnover ≥ threshold.
Why Open Interest ≈ “Float” Proxy
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In stocks, float ≈ shares the public can trade. In derivatives, there are no “shares,” so Open Interest acts as the live stock of active contracts. It’s the best proxy for “what’s available in play” because it counts open positions that persist across bars. Using Volume ÷ OI mirrors stock float-turnover logic: how fast the tradable base is being recycled each period.
Why Normalize by Price
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Derivatives volume and OI may be reported in contracts, not notional value. One contract’s economic weight changes with price (especially on inverse contracts). Dividing both Volume and OI by Close:
- Puts them on a comparable notional footing.
- Prevents false spikes purely from price moves.
- Makes Turnover comparable across time even as price trends.
Advanced Tips
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- Calibrate threshold: Start from the 80th–90th percentile of the last 60–90 bars of Turnover; set the threshold a touch below that to surface early heat.
- Add OI-delta: Layer an OI change histogram (current − prior) to separate new positioning from pure churn.
- Linear vs inverse: For linear (USDT-margined) contracts, the normalization still works and keeps visuals consistent; for inverse, it’s essential.
Limitations
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- Data availability: Works only if your symbol exposes an _OI feed on TradingView; otherwise it errors out.
- Exchange conventions: Volume units differ by venue (contracts, coin, notional). Normalization mitigates, but cross-symbol comparisons still need caution.
- Intrabar gaps: OI is typically end-of-bar; rapid intrabar shifts won’t appear until the bar closes.
Notes
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- Designed primarily for crypto derivatives. For non-crypto, the script blanks OI to avoid misleading plots and uses a daily TF when needed.
Credit
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- Concept & data: Built for TradingView data feeds.
- Acknowledgment: Credit to TradingView default indicator as requested.
- Source: This write-up reflects the logic present in your uploaded script.
Disclaimer
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Markets move; indicators simplify. Use with position sizing, hard stops, and catalyst awareness. The Turnover Rate flags activity, not direction.
