Tetris with Auto-PlayThis indicator is implemented in Pine Script™ v6 and serves as a demonstration of TradingView's capabilities. The core concept is to simulate a classic Tetris game by creating a grid-based environment and managing game state entirely within Pine Script.
Key Technical Aspects:
Grid Representation:
The script defines a custom grid structure using a user-defined type that holds the grid’s dimensions and a one-dimensional array to simulate a two-dimensional board. This structure is used to track occupied cells, clear full rows, and determine stack height.
Piece Management:
A second custom type is used to represent the state of a tetromino piece, including its type, rotation, and position. The code includes functions to calculate the block offsets for each tetromino based on its rotation state.
Collision Detection and Piece Locking:
Dedicated functions check for collisions against the grid borders and existing blocks. When a collision is detected during a downward move, the piece is locked into the grid, and any complete lines are cleared.
AIgo-Driven Placement:
The script incorporates a simple heuristic to determine the best placement for the next tetromino. It simulates different rotations and horizontal positions, evaluating each based on aggregated column height, cleared lines, holes, and bumpiness. This decision-making process is encapsulated in an AI-like function that returns the optimal rotation and placement.
Rendering Using Tables:
The visual representation is managed via TradingView’s table objects. The game board is rendered with a bordered layout, while a separate preview table displays the next piece and the current score. Each cell is updated with text and background colors that correspond to the state of the game.
Execution Flow and Timing:
The main execution loop handles real-time updates by dropping pieces at set intervals and checking for game-over conditions. The code leverages persistent variables and time comparisons to control game speed and manage transitions between piece drops.
Executing:
Add the indicator to the chart
It starts playing itself till game over
There are no parameters to change in this version but the grid in the code directly
p.s. Sadly we have no interactive buttons in the current pinescript versions to play ourself, but its about the possibilitys what we could do ;-)
Maybe in a future version there is more possible, if i find time to enhance and expand the idea
Have fun :-)
Search in scripts for "grid"
CE - 42MACRO Equity Factor Table This is Part 1 of 2 from the 42MACRO Recreation Series
The CE - 42MACRO Equity Factor Table is a whole toolbox packaged in a single indicator.
It aims to provide a probabilistic insight into the market realized GRID Macro Regime, use a multiplex of important Assets and Indices to form a high probability Implied Correlation expectation and allows to derive extra market insights by showing the most important aggregates and their performance over multiple timeframes... and what that might mean for the whole market direction, as well as the underlying asset.
WARNING
By the nature of the macro regimes, the outcomes are more accurate over longer Chart Timeframes (Week to Months).
However, it is also a valuable tool to form a proper,
market realized, short to medium term bias.
NOTE
This Indicator is intended to be used alongside the 2nd part "CE - 42MACRO Yield and Macro"
for a more wholistic approach and higher accuracy.
Due to coding limitations they can not be merged into one Indicator.
Methodology:
The Equity Factor Table tracks specifically chosen Assets to identify their performance and add the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below Assets, with more to come:
Dividend Compounders ( AMEX:SPHD )
Mid Caps ( AMEX:VO )
Emerging Markets ( AMEX:EEM )
Small Caps ( AMEX:IWM )
Mega Cap Growth ( NASDAQ:QQQ )
Brazil ( AMEX:EWZ )
United Kingdom ( AMEX:EWU )
Growth ( AMEX:IWF )
United States ( AMEX:SPY )
Japan ( AMEX:DXJ )
Momentum ( AMEX:MTUM )
China ( AMEX:FXI )
Low Beta ( AMEX:SPLV )
International ex-US ( NASDAQ:ACWX )
India ( AMEX:INDA )
Eurozone ( AMEX:EZU )
Quality ( AMEX:QUAL )
Size ( AMEX:OEF )
Functionalities:
1. Correlations
Takes a measure of Cross Market Correlations
2. Implied Trend
Calculates the trend for each Asset and uses the Correlation to obtain the Implied Trend for the underlying Asset
There are multiple functionalities to enhance Signal Speed and precision...
Reading a signal only over a certain threshold, otherwise being colored in gray to signal noise or unclear market behavior
Normalization of Signal
Double Normalization of Signal for more Speed... ideal for the Crypto Market
Using an additional Hull Moving Average to enhance Signal Speed
Additional simple Background coloring to get a Signal from the HMA
Barcoloring based on the Implied Correlation
3. Equity Factor Table
Shows market realized Asset performance
Provides the approximate realized GRID market regimes
Informs about "Risk ON" and "Risk OFF" market states
Now into the juicy stuff...
Visuals:
There is a variety of options to change visual settings of what is plotted and where
+ additional considerations.
Everything that is relevant in the underlying logic which can improve comprehension can be visualized with these options.
More to come
Market Correlation:
The Market Correlation Table takes the Correlation of all the Assets to the Asset on the Chart,
it furthermore uses the Normalized KAMA Oscillator by IkkeOmar to analyse the current trend of every single Asset.
(To enhance the Signal you can apply the mentioned Indicator on the relevant Assets to find your target Asset movements that you intend to capture...
and then change the length of the Indicator in here)
It then Implies a Correlation based on the Trend and the Correlation to give a probabilistically adjusted expectation for the future Chart Asset Movement.
This is strengthened by taking the average of all Implied Trends.
Thus the Correlation Table provides valuable insights about probabilistically likely Movement of the Asset over the defined time duration,
providing alpha for Traders and Investors alike.
Equity Factors:
The table provides valuable information about the current market environment (whether it's risk on or risk off),
the rough GRID models from 42MACRO and the actual market performance.
This allows you to obtain a deeper understanding of how the market works and makes it simple to identify the actual market direction,
makes it possible to derive overall market Health and shows market strength or weakness.
Utility:
The Equity Factor Table is divided in 4 Sections which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Equity Factors:
Are the values green for a specific Column?
If so then the market reflects the corresponding GRID behavior.
Bottom 5 Equity Factors:
Are the values red for a specific Column?
If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
This whole Indicator, as well as the second part, is based to a majority on 42MACRO's models.
I only brought them into TV and added things on top of it.
If you have questions or need a more in-depth guide DM me.
Will make a guide to all functionalities if necessity becomes apparent.
GM
Kirill ChannelThis indicator shows overbought and oversold zones. Can be used on all time frames. I personally use 15m - 30m.
How to apply ?:
- There can be many strategies for use! I use this indicator to buy an asset in the green zone and then sell it in the middle of the channel or in the red zone.
- I strongly advise against entering counter-trend positions in a growing market if you have little trading experience and understanding of price action.
How do I place orders ?:
- I place orders in a grid.
- If the price is very close to the edge, but it is difficult to reach it, then it is better to open a position on the market and place orders deep into the grid.
- If the price is at the edge of the channel for a very long time, then you need to look at a higher timeframe.
Algorithm composition:
- ALMA
- Keltner Channel
- Fibonacci Retracement
- Custom price percent offset calculations and manipulations.
Settings:
- I strongly do not recommend changing ALMA. These numbers have been specially calculated.
- It's better not to change Borders either. The current algorithm dynamically changes the width of the extreme channels depending on the price movement.
- The Keltner Channel was specially selected.
- Fibonacci Retracement can be changed. This part of the algorithm can be modified to suit your needs. At the moment, there are settings for aggressive trading.
Channel type:
- Conservative: Fibonacci Retracement settings (100 ma, 100 atr, 8 mult, 100 smooth)
- Aggressive: Fibonacci Retracement settings (25 ma, 25 atr, 3.5 mult, 100 smooth)
Сonservative channel does not allow a large number of points to enter positions, however, it is more straightforward and safer for very large movements.
I prefer aggressive settings because they allow me to make more profit on the number of trades.
Try to use both modes and choose what is preferable for you.
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex)
# Short Description
Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX.
---
# What it does (Quick)
* **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle.
* **Real-time** — accumulates intrabar volume live by tick-direction.
* **History Mode** — splits Up/Down on closed bars via simple or range-aware logic.
* **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend).
* **Contextual opacity** — stronger signals appear bolder.
* **Label density** — draw every N-th bar and limit to last X bars for performance.
* **Alerts** — thresholds for |Δ|, Δ%, and UpShare%.
---
# How it works (Real-Time vs History)
* **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available.
* **History (closed bars):**
* **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history.
* **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars.
* **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low.
* **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**.
---
# Rows & Meaning
* **Volume** — total bar volume (no split).
* **UpVol / DownVol** — directional intrabar volume.
* **Delta (Δ)** — UpVol − DownVol.
* **Absolute**: raw units
* **Relative (Δ%)**: Δ / (Up+Down) × 100
* **Both**: shows both formats
* **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish.
* Helpful icons: ▲ (>65%), ▼ (<35%).
---
# MTF Dashboard (🔧 Enable Dashboard)
A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons.
---
# Inputs (Grouped)
## Display
* Toggle rows: **Volume / Up / Down / Delta / UpShare**
* **Delta Display**: Absolute / Relative / Both
## Realtime & History
* **History Mode**: Auto / None / Approx / Price Action Based
* **Compact Numbers**: 1.2k, 1.25M, 3.4B…
## Theme & UI
* **Theme Mode**: Auto / Light / Dark
* **Row Spacing**: vertical spacing between rows
* **Top Row Y**: moves the whole grid vertically
* **Draw Guide Lines**: faint dotted guides
* **Text Size**: Tiny / Small / Normal / Large
## 🔧 Dashboard Settings
* **Enable Dashboard**
* **📏 Table Text Size**: Tiny…Huge
* **🦓 Zebra Rows**
* **🔲 Table Border**
## ⏰ Timeframes (for Dashboard)
* **M1…D1** toggles
## Contextual Coloring
* **Enable Contextual Coloring**: opacity by signal strength
* **Δ% cap / Share offset cap**: saturation caps
* **Min/Max transparency**: solid vs faint extremes
## Label Density & Size
* **Show every N-th bar**: draw labels only every Nth bar
* **Limit to last X bars**: keep labels only in the most recent X bars
## Colors
* Up / Down / Text / Guide
## Alerts
* **Delta Threshold (abs)** — |Δ| in volume units
* **UpShare > / <** — bullish/bearish thresholds
* **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels
---
# How to use (Quick Start)
1. Add the indicator to your chart (overlay=false → separate pane).
2. **History Mode**:
* Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history.
* Stocks/Index → prefer **None** or **Price Action Based** for safer splits.
3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**.
4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves.
5. **Dashboard**: enable and pick only the TFs you actually use.
6. **Alerts**: set thresholds (ideas below).
---
# Alerts (in TradingView)
Add alert → pick this indicator → choose any of:
* **Delta exceeds threshold** (|Δ| > X)
* **UpShare above threshold** (UpShare% > X)
* **UpShare below threshold** (UpShare% < X)
* **Relative Delta above +X%**
* **Relative Delta below −X%**
**Starter thresholds (tune per symbol & TF):**
* **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish)
* **FX (tick volume)**: UpShare > 60–65% or < 40–35%
* **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k)
---
# Notes by Market Type
* **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx.
* **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday.
* **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx.
---
# “All Timeframes” accuracy
* Works on **any TF** (M1 → D1/W1).
* **Real-time accuracy** is strong for the open bar (live accumulation).
* **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced).
* The MTF dashboard uses `request.security` and therefore follows the same logic per TF.
---
# Trade Ideas (Use-Cases)
* **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries.
* **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend.
* **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias.
---
# Advantages
* **True-feeling live flow** on the open bar.
* **Adaptable history** (three modes) to match data quality.
* **Clean visual layout** with guides, compact numbers, contextual opacity.
* **MTF snapshot** for quick bias read.
* **Performance controls** (last X bars, every N-th bar).
---
# Limitations & Care
* **FX uses tick volume** — interpret Δ/Share accordingly.
* **History Mode is an approximation** — confirm with trend/structure/liquidity context.
* **Illiquid symbols** can produce noisy or contradictory signals.
* **Too many labels** can slow charts → raise N, lower X, or disable guides.
---
# Best Practices (Checklist)
* Crypto/Futures: prefer **Price Action Based** for history.
* Stocks: **None** or **Price Action Based**; be cautious with **Approx**.
* FX: pair Δ% & UpShare% with session context (London/NY) and volatility.
* If labels overlap: tweak **Row Spacing** and **Text Size**.
* In the dashboard, keep only the TFs you actually act on.
* Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset.
---
# FAQ
**1) Why do some closed bars show 0%/100% UpShare?**
You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits.
**2) Δ% looks strong but price doesn’t move — why?**
Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations.
**3) Performance slowdown — what to do?**
Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**.
**4) Dashboard values don’t “match” the grid exactly?**
Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal.
---
# Short “Store” Marketing Blurb
Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
Chart-Only Scanner — Pro Table v2.5.1Chart-Only Scanner — Pro Table v2.5
User Manual (Pine Script v6)
What this tool does (in one line)
A compact, on-chart table that scores the current chart symbol (or an optional override) using momentum, volume, trend, volatility, and pattern checks—so you can quickly decide UP, DOWN, or WAIT.
Quick Start (90 seconds)
Add the indicator to any chart and timeframe (1m…1M).
Leave “Override chart symbol” = OFF to auto-use the chart’s symbol.
Choose your layout:
Row (wide horizontal strip), or Grid (title + labeled cells).
Pick a size preset (Micro, Small, Medium, Large, Mobile).
Optional: turn on “Use Higher TF (EMA 20/50)” and set HTF Multiplier (e.g., 4 ⇒ if chart is 15m, HTF is 60m).
Watch the table:
DIR (↑/↓/→), ROC%, MOM, VOL, EMA stack, HTF, REV, SCORE, ACT.
Add an alert if you want: the script fires when |SCORE| ≥ Action threshold.
What to expect
A small table appears on the chart corner you choose, updating each bar (or only at bar close if you keep default smart-update).
The ACT cell shows 🔥 (strong), 👀 (medium), or ⏳ (weak).
Panels & Settings (every option explained)
Core
Momentum Period: Lookback for rate-of-change (ROC%). Shorter = more reactive; longer = smoother.
ROC% Threshold: Minimum absolute ROC% to call direction UP (↑) or DOWN (↓); otherwise →.
Require Volume Confirmation: If ON and VOL ≤ 1.0, the SCORE is forced to 0 (prevents low-volume false positives).
Override chart symbol + Custom symbol: By default, the indicator uses the chart’s symbol. Turn this ON to lock to a specific ticker (e.g., a perpetual).
Higher TF
Use Higher TF (EMA 20/50): Compares EMA20 vs EMA50 on a higher timeframe.
HTF Multiplier: Higher TF = (chart TF × multiplier).
Example: on 3H chart with multiplier 2 ⇒ HTF = 6H.
Volatility & Oscillators
ATR Length: Used to show ATR% (ATR relative to price).
RSI Length: Standard RSI; colors: green ≤30 (oversold), red ≥70 (overbought).
Stoch %K Length: With %D = SMA(%K, 3).
MACD Fast/Slow/Signal: Standard MACD values; we display Line, Signal, Histogram (L/S/H).
ADX Length (Wilder): Wilder’s smoothing (internal derivation); also shows +DI / −DI if you enable the ADX column.
EMAs / Trend
EMA Fast/Mid/Slow: We compute EMA(20/50/200) by default (editable).
EMA Stack: Bull if Fast > Mid > Slow; Bear if Fast < Mid < Slow; Flat otherwise.
Benchmark (optional, OFF by default)
Show Relative Strength vs Benchmark: Displays RS% = ROC(symbol) − ROC(benchmark) over the Momentum Period.
Benchmark Symbol: Ticker used for comparison (e.g., BTCUSDT as a market proxy).
Columns (show/hide)
Toggle which fields appear in the table. Hiding unused fields keeps the layout clean (especially on mobile).
Display
Layout Mode:
Row = a single two-row strip; each column is a metric.
Grid = a title row plus labeled pairs (label/value) arranged in rows.
Size Preset: Micro, Small, Medium, Large, Mobile change text size and the grid density.
Table Corner: Where the panel sits (e.g., Top Right).
Opaque Table Background: ON = dark card; OFF = transparent(ish).
Update Every Bar: ON = update intra-bar; OFF = smart update (last bar / real-time / confirmed history).
Action threshold (|score|): The cutoff for 🔥 and alert firing (default 70).
How to read each field
CHART: The active symbol name (or your custom override).
DIR: ↑ (ROC% > threshold), ↓ (ROC% < −threshold), → otherwise.
ROC%: Rate of change over Momentum Period.
Formula: (Close − Close ) / Close × 100.
MOM: A scaled momentum score: min(100, |ROC%| × 10).
VOL: Volume ratio vs 20-bar SMA: Volume / SMA(Volume,20).
1.5 highlights as yellow (significant participation).
ATR%: (ATR / Close) × 100 (volatility relative to price).
RSI: Colored for extremes: ≤30 green, ≥70 red.
Stoch K/D: %K and %D numbers.
MACD L/S/H: Line, Signal, Histogram. Histogram color reflects sign (green > 0, red < 0).
ADX, +DI, −DI: Trend strength and directional components (Wilder). ADX ≥ 25 is highlighted.
EMA 20/50/200: Current EMA values (editable lengths).
STACK: Bull/Bear/Flat as defined above.
VWAP%: (Close − VWAP) / Close × 100 (premium/discount to VWAP).
HTF: ▲ if HTF EMA20 > EMA50; ▼ if <; · if flat/off.
RS%: Symbol’s ROC% − Benchmark ROC% (positive = outperforming).
REV (reversal):
🟢 Eng/Pin = bullish engulfing or bullish pin detected,
🔴 Eng/Pin = bearish engulfing or bearish pin,
· = none.
SCORE (absolute shown as a number; sign shown via DIR and ACT):
Components:
base = MOM × 0.4
volBonus = VOL > 1.5 ? 20 : VOL × 13.33
htfBonus = use_mtf ? (HTF == DIR ? 30 : HTF == 0 ? 15 : 0) : 0
trendBonus = (STACK == DIR) ? 10 : 0
macdBonus = 0 (placeholder for future versions)
scoreRaw = base + volBonus + htfBonus + trendBonus + macdBonus
SCORE = DIR ≥ 0 ? scoreRaw : −scoreRaw
If Require Volume Confirmation and VOL ≤ 1.0 ⇒ SCORE = 0.
ACT:
🔥 if |SCORE| ≥ threshold
👀 if 50 < |SCORE| < threshold
⏳ otherwise
Practical examples
Strong long (trend + participation)
DIR = ↑, ROC% = +3.2, MOM ≈ 32, VOL = 1.9, STACK = Bull, HTF = ▲, REV = 🟢
SCORE: base(12.8) + volBonus(20) + htfBonus(30) + trend(10) ≈ 73 → ACT = 🔥
Action idea: look for longs on pullbacks; confirm risk with ATR%.
Weak long (no volume)
DIR = ↑, ROC% = +1.0, but VOL = 0.8 and Require Volume Confirmation = ON
SCORE forced to 0 → ACT = ⏳
Action: wait for volume > 1.0 or turn off confirmation knowingly.
Bearish reversal warning
DIR = →, REV = 🔴 (bearish engulfing), RSI = 68, HTF = ▼
SCORE may be mid-range; ACT = 👀
Action: watch for breakdown and rising VOL.
Alerts (how to use)
The script calls alert() whenever |SCORE| ≥ Action threshold.
To receive pop-ups, sounds, or emails: click “⏰ Alerts” in TradingView, choose this indicator, and pick “Any alert() function call.”
The alert message includes: symbol, |SCORE|, DIR.
Layout, Size, and Corner tips
Row is best when you want a compact status ribbon across the top.
Grid is clearer on big screens or when you enable many columns.
Size:
Mobile = one pair per row (tall, readable)
Micro/Small = dense; good for many fields
Large = presentation/screenshots
Corner: If the table overlaps price, change the corner or set Opaque Background = OFF.
Repaint & timeframe behavior
Default smart update prefers stability (last bar / live / confirmed history).
For a stricter, “close-only” behavior (less repaint): turn Update Every Bar = OFF and avoid Heikin Ashi when you want raw market OHLC (HA modifies price inputs).
HTF logic is derived from a clean, integer multiple of your chart timeframe (via multiplier). It works with 3H/4H and any TF.
Performance notes
The script analyzes one symbol (chart or override) with multiple metrics using efficient tuple requests.
If you later want a multi-symbol grid, do it with pages (10–15 per page + rotate) to stay within platform limits (recommended future add-on).
Troubleshooting
No table visible
Ensure the indicator is added and not hidden.
Try toggling Opaque Background or switch Corner (it might be behind other drawings).
Keep Columns count reasonable for the chosen Size.
If you turned ON Override, verify the Custom symbol exists on your data provider.
Numbers look different on HA candles
Heikin Ashi modifies OHLC; switch to regular candles if you need raw price metrics.
3H/4H issues
Use integer HTF Multiplier (e.g., 2, 4). The tool builds the correct string internally; no manual timeframe strings needed.
Power user tips
Volume gating: keeping Require Volume Confirmation = ON filters most fake moves; if you’re a scalper, reduce strictness or turn it off.
Action threshold: 60–80 is typical. Higher = fewer but stronger signals.
Benchmark RS%: great for spotting leaders/laggards; positive RS% = outperformance vs benchmark.
Change policy & safety
This version doesn’t alter your historical logic you tested (no radical changes).
Any future “radical” change (score weights, HTF logic, UI hiding data) will ship with a toggle and an Impact Statement so you can keep old behavior if you prefer.
Glossary (quick)
ROC%: Percent change over N bars.
MOM: Scaled momentum (0–100).
VOL ratio: Volume vs 20-bar average.
ATR%: ATR as % of price.
ADX/DI: Trend strength / direction components (Wilder).
EMA stack: Relationship between EMAs (bullish/bearish/flat).
VWAP%: Premium/discount to VWAP.
RS%: Relative strength vs benchmark.
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV)
Where Pure Mathematics Meets Market Reality
A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics
🎓 THEORETICAL FOUNDATION
The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis:
The Langlands Program: Harmonic Analysis in Markets
Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator:
L-Function Implementation:
- Utilizes the Möbius function μ(n) for weighted price analysis
- Applies Riemann zeta function convergence principles
- Calculates quantum harmonic resonance between -2 and +2
- Measures deep mathematical patterns invisible to traditional analysis
The L-Function core calculation employs:
L_sum = Σ(return_val × μ(n) × n^(-s))
Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness.
Operadic Composition Theory: Multi-Strategy Democracy
Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using:
Strategy Composition Arity (2-5 strategies):
- Momentum analysis via RSI transformation
- Mean reversion through Bollinger Band mathematics
- Order Flow Polarity Index (revolutionary T3-smoothed volume analysis)
- Trend detection using Directional Movement
- Higher timeframe momentum confirmation
Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty.
Möbius Function: Number Theory in Action
The Möbius function μ(n) forms the mathematical backbone:
- μ(n) = 1 if n is a square-free positive integer with even number of prime factors
- μ(n) = -1 if n is a square-free positive integer with odd number of prime factors
- μ(n) = 0 if n has a squared prime factor
This creates oscillating weights that reveal hidden market periodicities and harmonic structures.
🔧 COMPREHENSIVE INPUT SYSTEM
Langlands Program Parameters
Modular Level N (5-50, default 30):
Primary lookback for quantum harmonic analysis. Optimized by timeframe:
- Scalping (1-5min): 15-25
- Day Trading (15min-1H): 25-35
- Swing Trading (4H-1D): 35-50
- Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45
L-Function Critical Strip (0.5-2.5, default 1.5):
Controls Riemann zeta convergence precision:
- Higher values: More stable, smoother signals
- Lower values: More reactive, catches quick moves
- High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3
Frobenius Trace Period (5-50, default 21):
Galois representation lookback for price-volume correlation:
- Measures harmonic relationships in market flows
- Scalping: 8-15, Day Trading: 18-25, Swing: 25-40
HTF Multi-Scale Analysis:
Higher timeframe context prevents trading against major trends:
- Provides market bias and filters signals
- Improves win rates by 15-25% through trend alignment
Operadic Composition Parameters
Strategy Composition Arity (2-5, default 4):
Number of algorithms composed for final signal:
- Conservative: 4-5 strategies (higher confidence)
- Moderate: 3-4 strategies (balanced approach)
- Aggressive: 2-3 strategies (more frequent signals)
Category Agreement Threshold (2-5, default 3):
Democratic voting minimum for signal generation:
- Higher agreement: Fewer but higher quality signals
- Lower agreement: More signals, potential false positives
Swiss-Cheese Mixing (0.1-0.5, default 0.382):
Golden ratio φ⁻¹ based blending of trend factors:
- 0.382 is φ⁻¹, optimal for natural market fractals
- Higher values: Stronger trend following
- Lower values: More contrarian signals
OFPI Configuration:
- OFPI Length (5-30, default 14): Order Flow calculation period
- T3 Smoothing (3-10, default 5): Advanced exponential smoothing
- T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control
Unified Scoring System
Component Weights (sum ≈ 1.0):
- L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis
- Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity
- Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus
- Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment
Signal Threshold (0.5-10.0, default 5.0):
Quality filter producing:
- 8.0+: EXCEPTIONAL signals only
- 6.0-7.9: STRONG signals
- 4.0-5.9: MODERATE signals
- 2.0-3.9: WEAK signals
🎨 ADVANCED VISUAL SYSTEM
Multi-Dimensional Quantum Aura Bands
Five-layer resonance field showing market energy:
- Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.)
- Expansion: Dynamic based on score intensity and volatility
- Function: Multi-timeframe support/resistance zones
Morphism Flow Portals
Category theory visualization showing market topology:
- Green/Cyan Portals: Bullish mathematical flow
- Red/Orange Portals: Bearish mathematical flow
- Size/Intensity: Proportional to signal strength
- Recursion Depth (1-8): Nested patterns for flow evolution
Fractal Grid System
Dynamic support/resistance with projected L-Scores:
- Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows
- Smart Spacing: Prevents level overlap using ATR-based minimum distance
- Projections: Estimated signal scores when price reaches levels
- Usage: Precise entry/exit timing with mathematical confirmation
Wick Pressure Analysis
Rejection level prediction using candle mathematics:
- Upper Wicks: Selling pressure zones (purple/red lines)
- Lower Wicks: Buying pressure zones (purple/green lines)
- Glow Intensity (1-8): Visual emphasis and line reach
- Application: Confluence with fractal grid creates high-probability zones
Regime Intensity Heatmap
Background coloring showing market energy:
- Black/Dark: Low activity, range-bound markets
- Purple Glow: Building momentum and trend development
- Bright Purple: High activity, strong directional moves
- Calculation: Combines trend, momentum, volatility, and score intensity
Six Professional Themes
- Quantum: Purple/violet for general trading and mathematical focus
- Holographic: Cyan/magenta optimized for cryptocurrency markets
- Crystalline: Blue/turquoise for conservative, stability-focused trading
- Plasma: Gold/magenta for high-energy volatility trading
- Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading
📊 INSTITUTIONAL-GRADE DASHBOARD
Unified AI Score Section
- Total Score (-10 to +10): Primary decision metric
- >5: Strong bullish signals
- <-5: Strong bearish signals
- Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK
- Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions
Order Flow Analysis
Revolutionary OFPI integration:
- OFPI Value (-100% to +100%): Real buying vs selling pressure
- Visual Gauge: Horizontal bar chart showing flow intensity
- Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK
- Trading Application: Flow shifts often precede major moves
Signal Performance Tracking
- Win Rate Monitoring: Real-time success percentage with emoji indicators
- Signal Count: Total signals generated for frequency analysis
- Current Position: LONG, SHORT, or NONE with P&L tracking
- Volatility Regime: HIGH, MEDIUM, or LOW classification
Market Structure Analysis
- Möbius Field Strength: Mathematical field oscillation intensity
- CHAOTIC: High complexity, use wider stops
- STRONG: Active field, normal position sizing
- MODERATE: Balanced conditions
- WEAK: Low activity, consider smaller positions
- HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL)
- Strategy Agreement: Multi-algorithm consensus level
Position Management
When in trades, displays:
- Entry Price: Original signal price
- Current P&L: Real-time percentage with risk level assessment
- Duration: Bars in trade for timing analysis
- Risk Level: HIGH/MEDIUM/LOW based on current exposure
🚀 SIGNAL GENERATION LOGIC
Balanced Long/Short Architecture
The indicator generates signals through multiple convergent pathways:
Long Entry Conditions:
- Score threshold breach with algorithmic agreement
- Strong bullish order flow (OFPI > 0.15) with positive composite signal
- Bullish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bullish OFPI (>0.3) with any positive score
Short Entry Conditions:
- Score threshold breach with bearish agreement
- Strong bearish order flow (OFPI < -0.15) with negative composite signal
- Bearish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bearish OFPI (<-0.3) with any negative score
Exit Logic:
- Score deterioration below continuation threshold
- Signal quality degradation
- Opposing order flow acceleration
- 10-bar minimum between signals prevents overtrading
⚙️ OPTIMIZATION GUIDELINES
Asset-Specific Settings
Cryptocurrency Trading:
- Modular Level: 15-25 (capture volatility)
- L-Function Precision: 0.8-1.3 (reactive to price swings)
- OFPI Length: 10-20 (fast correlation shifts)
- Cascade Levels: 5-7, Theme: Holographic
Stock Index Trading:
- Modular Level: 25-35 (balanced trending)
- L-Function Precision: 1.5-1.8 (stable patterns)
- OFPI Length: 14-20 (standard correlation)
- Cascade Levels: 4-5, Theme: Quantum
Forex Trading:
- Modular Level: 35-45 (smooth trends)
- L-Function Precision: 1.6-2.1 (high smoothing)
- OFPI Length: 18-25 (disable volume amplification)
- Cascade Levels: 3-4, Theme: Crystalline
Timeframe Optimization
Scalping (1-5 minute charts):
- Reduce all lookback parameters by 30-40%
- Increase L-Function precision for noise reduction
- Enable all visual elements for maximum information
- Use Small dashboard to save screen space
Day Trading (15 minute - 1 hour):
- Use default parameters as starting point
- Adjust based on market volatility
- Normal dashboard provides optimal information density
- Focus on OFPI momentum shifts for entries
Swing Trading (4 hour - Daily):
- Increase lookback parameters by 30-50%
- Higher L-Function precision for stability
- Large dashboard for comprehensive analysis
- Emphasize HTF trend alignment
🏆 ADVANCED TRADING STRATEGIES
The Mathematical Confluence Method
1. Wait for Fractal Grid level approach
2. Confirm with projected L-Score > threshold
3. Verify OFPI alignment with direction
4. Enter on portal signal with quality ≥ STRONG
5. Exit on score deterioration or opposing flow
The Regime Trading System
1. Monitor Aether Flow background intensity
2. Trade aggressively during bright purple periods
3. Reduce position size during dark periods
4. Use Möbius Field strength for stop placement
5. Align with HTF trend for maximum probability
The OFPI Momentum Strategy
1. Watch for momentum shifting detection
2. Confirm with accelerating flow in direction
3. Enter on immediate portal signal
4. Scale out at Fibonacci levels
5. Exit on flow deceleration or reversal
⚠️ RISK MANAGEMENT INTEGRATION
Mathematical Position Sizing
- Use Galois Rank for volatility-adjusted sizing
- Möbius Field strength determines stop width
- Fractal Dimension guides maximum exposure
- OFPI momentum affects entry timing
Signal Quality Filtering
- Trade only STRONG or EXCEPTIONAL quality signals
- Increase position size with higher agreement levels
- Reduce risk during CHAOTIC Möbius field periods
- Respect HTF trend alignment for directional bias
🔬 DEVELOPMENT JOURNEY
Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable.
The Mathematical Challenge
Implementing the Langlands Program required deep research into:
- Number theory and the Möbius function
- Riemann zeta function convergence properties
- L-function analytical continuation
- Galois representations in finite fields
The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application.
The Computational Complexity
Operadic composition theory demanded:
- Category theory implementation in Pine Script
- Multi-dimensional array management for strategy composition
- Real-time democratic voting algorithms
- Performance optimization for complex calculations
The Integration Breakthrough
Bringing together three disparate mathematical frameworks required:
- Novel approaches to signal weighting and combination
- Revolutionary Order Flow Polarity Index development
- Advanced T3 smoothing implementation
- Balanced signal generation preventing directional bias
Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility.
🎯 PRACTICAL IMPLEMENTATION
Getting Started
1. Apply indicator with default settings
2. Select appropriate theme for your markets
3. Observe dashboard metrics during different market conditions
4. Practice signal identification without trading
5. Gradually adjust parameters based on observations
Signal Confirmation Process
- Never trade on score alone - verify quality rating
- Confirm OFPI alignment with intended direction
- Check fractal grid level proximity for timing
- Ensure Möbius field strength supports position size
- Validate against HTF trend for bias confirmation
Performance Monitoring
- Track win rate in dashboard for strategy assessment
- Monitor component contributions for optimization
- Adjust threshold based on desired signal frequency
- Document performance across different market regimes
🌟 UNIQUE INNOVATIONS
1. First Integration of Langlands Program mathematics with practical trading
2. Revolutionary OFPI with T3 smoothing and momentum detection
3. Operadic Composition using category theory for signal democracy
4. Dynamic Fractal Grid with projected L-Score calculations
5. Multi-Dimensional Visualization through morphism flow portals
6. Regime-Adaptive Background showing market energy intensity
7. Balanced Signal Generation preventing directional bias
8. Professional Dashboard with institutional-grade metrics
📚 EDUCATIONAL VALUE
The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to:
- Pure mathematics applications in markets
- Category theory and operadic composition
- Number theory through Möbius function implementation
- Harmonic analysis via L-function calculations
- Advanced signal processing through T3 smoothing
⚖️ RESPONSIBLE USAGE
This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable.
Key Principles:
- Use as part of comprehensive trading strategy
- Implement proper risk management at all times
- Backtest thoroughly before live implementation
- Understand that past performance does not guarantee future results
- Never risk more than you can afford to lose
The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator.
🔮 CONCLUSION
The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability.
From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos.
This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure.
Trade with mathematical precision. Trade with the LOMV.
*"Mathematics is the language with which God has written the universe." - Galileo Galilei*
*In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.*
— Dskyz, Trade with insight. Trade with anticipation.
Market Cap Landscape 3DHello, traders and creators! 👋
Market Cap Landscape 3D. This project is more than just a typical technical analysis tool; it's an exploration into what's possible when code meets artistry on the financial charts. It's a demonstration of how we can transcend flat, two-dimensional lines and step into a vibrant, three-dimensional world of data.
This project continues a journey that began with a previous 3D experiment, the T-Virus Sentiment, which you can explore here:
The Market Cap Landscape 3D builds on that foundation, visualizing market data—particularly crypto market caps—as a dynamic 3D mountain range. The entire landscape is procedurally generated and rendered in real-time using the powerful drawing capabilities of polyline.new() and line.new() , pushed to their creative limits.
This work is intended as a guide and a design example for all developers, born from the spirit of learning and a deep love for understanding the Pine Script™ language.
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🧐 Core Concept: How It Works
The indicator synthesizes multiple layers of information into a single, cohesive 3D scene:
The Surface: The mountain range itself is a procedurally generated 3D mesh. Its peaks and valleys create a rich, textured landscape that serves as the canvas for our data.
Crypto Data Integration: The core feature is its ability to fetch market cap data for a list of cryptocurrencies you provide. It then sorts them in descending order and strategically places them onto the 3D surface.
The Summit: The highest point on the mountain is reserved for the asset with the #1 market cap in your list, visually represented by a flag and a custom emblem.
The Mountain Labels: The other assets are distributed across the mountainside, with their rank determining their general elevation. This creates an intuitive visual hierarchy.
The Leaderboard Pole: For clarity, a dedicated pole in the back-right corner provides a clean, ranked list of the symbols and their market caps, ensuring the data is always easy to read.
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🧐 Example of adjusting the view
To evoke the feeling of flying over mountains
To evoke the feeling of looking at a mountain peak on a low plain
🧐 Example of predefined colors
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🚀 How to Use
Getting started with the Market Cap Landscape 3D:
Add to Chart: Apply the "Market Cap Landscape 3D" indicator to your active chart.
Open Settings: Double-click anywhere on the 3D landscape or click the "Settings" icon next to the indicator's name.
Customize Your Crypto List: The most important setting is in the Crypto Data tab. In the "Symbols" text area, enter a comma-separated list of the crypto tickers you want to visualize (e.g., BTC,ETH,SOL,XRP ). The indicator supports up to 40 unique symbols.
> Important Note: This indicator exclusively uses TradingView's `CRYPTOCAP` data source. To find valid symbols, use the main symbol search bar on your chart. Type `CRYPTOCAP:` (including the colon) and you will see a list of available options. For example, typing `CRYPTOCAP:BTC` will confirm that `BTC` is a valid ticker for the indicator's settings. Using symbols that do not exist in the `CRYPTOCAP` index will result in a script error. or, to display other symbols, simply type CRYPTOCAP: (including the colon) and you will see a list of available options.
Adjust Your View: Use the settings in the Camera & Projection tab to rotate ( Yaw ), tilt ( Pitch ), and scale the landscape until you find a view you love.
Explore & Customize: Play with the color palettes, flag design, and other settings to make the landscape truly your own!
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⚙️ Settings & Customization
This indicator is highly customizable. Here’s a breakdown of what each setting does:
#### 🪙 Crypto Data
Symbols: Enter the crypto tickers you want to track, separated by commas. The script automatically handles duplicates and case-insensitivity.
Show Market Cap on Mountain: When checked, it displays the full market cap value next to the symbol on the mountain. When unchecked, it shows a cleaner look with just the symbol and a colored circle background.
#### 📷 Camera & Projection
Yaw (°): Rotates the camera view horizontally (side to side).
Pitch (°): Tilts the camera view vertically (up and down).
Scale X, Y, Z: Stretches or compresses the landscape in width, depth, and height, respectively. Fine-tune these to get the perfect perspective.
#### 🏞️ Grid / Surface
Grid X/Y resolution: Controls the detail level of the 3D mesh. Higher values create a smoother surface but may use more resources.
Fill surface strips: Toggles the beautiful color gradient on the surface.
Show wireframe lines: Toggles the visibility of the grid lines.
Show nodes (markers): Toggles the small dots at each grid intersection point.
#### 🏔️ Peaks / Mountains
Fill peaks volume: Draws vertical lines on high peaks, giving them a sense of volume.
Fill peaks surface: Draws a cross-hatch pattern on the surface of high peaks.
Peak height threshold: Defines the minimum height for a peak to receive the fill effect.
Peak fill color/density: Customizes the appearance of the fill lines.
#### 🚩 Flags (3D)
Show Flag on Summit: A master switch to show or hide the flag and emblem entirely.
Flag height, width, etc.: Provides full control over the dimensions and orientation of the flag on the highest peak.
#### 🎨 Color Palette
Base Gradient Palette: Choose from 13 stunning, pre-designed color themes for the landscape, from the classic SUNSET_WAVE to vibrant themes like NEON_DREAM and OCEANIC .
#### 🛡️ Emblem / Badge Controls
This section gives you granular control over every element of the custom emblem on the flag. Tweak rotation, offsets, and scale to design your unique logo.
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👨💻 Developer's Corner: Modifying the Core Logic
If you're a developer and wish to customize the indicator's core data source, this section is for you. The script is designed to be modular, making it easy to change what data is being ranked and visualized.
The heart of the data retrieval and ranking logic is within the f_getSortedCryptoData() function. Here’s how you can modify it:
1. Changing the Data Source (from Market Cap to something else):
The current logic uses request.security("CRYPTOCAP:" + syms.get(i), ...) to fetch market capitalization data. To change this, you need to modify this line.
Example: Ranking by RSI (14) on the Daily timeframe.
First, you'll need a function to calculate RSI. Add this function to the script:
f_getRSI(symbol, timeframe, length) =>
request.security(symbol, timeframe, ta.rsi(close, length))
Then, inside f_getSortedCryptoData() , find the `for` loop that populates the `caps` array and replace the `request.security` call:
// OLD LINE:
// caps.set(i, request.security("CRYPTOCAP:" + syms.get(i), timeframe.period, close))
// NEW LINE for RSI:
// Note: You'll need to decide how to format the symbol name (e.g., "BINANCE:" + syms.get(i) + "USDT")
caps.set(i, f_getRSI("BINANCE:" + syms.get(i) + "USDT", "D", 14))
2. Changing the Data Formatting:
The ranking values are formatted for display using the f_fmtCap() function, which currently formats large numbers into "M" (millions), "B" (billions), etc.
If you change the data source to something like RSI, you'll want to change the formatting. You can modify f_fmtCap() or create a new formatting function.
Example: Formatting for RSI.
// Modify f_fmtCap or create f_fmtRSI
f_fmtRSI(float v) =>
str.tostring(v, "#.##") // Simply format to two decimal places
Remember to update the calls to this function in the main drawing loop where the labels are created (e.g., str.format("{0}: {1}", crypto.symbol, f_fmtCap(crypto.cap)) ).
By modifying these key functions ( f_getSortedCryptoData and f_fmtCap ), you can adapt the Market Cap Landscape 3D to visualize and rank almost any dataset you can imagine, from technical indicators to fundamental data.
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We hope you enjoy using the Market Cap Landscape 3D as much as we enjoyed creating it. Happy charting! ✨
Mikula's Master 360° Square of 12Mikula’s Master 360° Square of 12
An educational W. D. Gann study indicator for price and time. Anchor a compact Square of 12 table to a start point you choose. Begin from a bar’s High or Low (or set a manual start price). From that anchor you can progress or regress the table to study how price steps through cycles in either direction.
What you’re looking at :
Zodiac rail (far left): the twelve signs.
Degree rail: 24 rows in 15° steps from 15° up to 360°/0°.
Transit rail and Natal rail: track one planet per rail. Each planet is placed at its current row (℞ shown when retrograde). As longitude advances, the planet climbs bottom → top, then wraps to the bottom at the next sign; during retrograde it steps downward.
Hover a planet’s cell to see a tooltip with its exact longitude and sign (e.g., 152.4° ♌︎). The linked price cell in the grid moves with the planet’s row so you can follow a planet’s path through the zodiac as a path through price.
Price grid (right): the 12×24 Square of 12. Each column is a cycle; cells are stepped price levels from your start price using your increment.
Bottom rail: shows the current square number and labels the twelve columns in that square.
How the square is read
The square always begins at the bottom left. Read each column bottom → top. At the top, return to the bottom of the next column and read up again. One square contains twelve cycles. Because the anchor can be a High or a Low, you can progress the table upward from the anchor or regress it downward while keeping the same bottom-to-top reading order.
Iterate Square (shifting)
Iterate Square shifts the entire 12×24 grid to the next set of twelve cycles.
Square 1 shows cycles 1–12; Square 2 shows 13–24; Square 3 shows 25–36, etc.
Visibility rules
Pivot cells are table-bound. If you shift the square beyond those prices, their highlights won’t appear in the table.
A/B levels and Transit/Natal planetary lines are chart overlays and can remain visible on the table as you shift the square.
Quick use
Choose an anchor (date/time + High/Low) or enable a manual start price .
Set the increment. If you anchored with a Low and want the table to step downward from there, use a negative value.
Optional: pick Transit and Natal planets (one per rail), toggle their plots, and hover their cells for longitude/sign.
Optional: turn on A/B levels to display repeating bands from the start price.
Optional: enable swing pivots to tint matching cells after the anchor.
Use Iterate Square to shift to later squares of twelve cycles.
Examples
These are exploratory examples to spark ideas:
Overview layout (zodiac & degree rails, Transit/Natal rails, price grid)
A-levels plotted, pivots tinted on the table, real-time price highlighted
Drawing angles from the anchor using price & time read from the table
Using a TradingView Gann box along the A-levels to study reactions
Attribution & originality
This script is an original implementation (no external code copied). Conceptual credit to Patrick Mikula, whose discussion of the Master 360° Square of 12 inspired this study’s presentation.
Further reading (neutral pointers)
Patrick Mikula, Gann’s Scientific Methods Unveiled, Vol. 2, “W. D. Gann’s Use of the Circle Chart.”
W. D. Gann’s Original Commodity Course (as provided by WDGAN.com).
No affiliation implied.
License CC BY-NC-SA 4.0 (non-commercial; please attribute @Javonnii and link the original).
Dependency AstroLib by @BarefootJoey
Disclaimer Educational use only; not financial advice.
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
00 Averaging Down Backtest Strategy by RPAlawyer v21FOR EDUCATIONAL PURPOSES ONLY! THE CODE IS NOT YET FULLY DEVELOPED, BUT IT CAN PROVIDE INTERESTING DATA AND INSIGHTS IN ITS CURRENT STATE.
This strategy is an 'averaging down' backtester strategy. The goal of averaging/doubling down is to buy more of an asset at a lower price to reduce your average entry price.
This backtester code proves why you shouldn't do averaging down, but the code can be developed (and will be developed) further, and there might be settings even in its current form that prove that averaging down can be done effectively.
Different averaging down strategies exist:
- Linear/Fixed Amount: buy $1000 every time price drops 5%
- Grid Trading: Placing orders at price levels, often with increasing size, like $1000 at -5%, $2000 at -10%
- Martingale: doubling the position size with each new entry
- Reverse Martingale: decreasing position size as price falls: $4000, then $2000, then $1000
- Percentage-Based: position size based on % of remaining capital, like 10% of available funds at each level
- Dynamic/Adaptive: larger entries during high volatility, smaller during low
- Logarithmic: position sizes increase logarithmically as price drops
Unlike the above average costing strategies, it applies averaging down (I use DCA as a synonym) at a very strong trend reversal. So not at a certain predetermined percentage negative PNL % but at a trend reversal signaled by an indicator - hence it most closely resembles a dynamically moving grid DCA strategy.
Both entering the trade and averaging down assume a strong trend. The signals for trend detection are provided by an indicator that I published under the name '00 Parabolic SAR Trend Following Signals by RPAlawyer', but any indicator that generates numeric signals of 1 and -1 for buy and sell signals can be used.
The indicator must be connected to the strategy: in the strategy settings under 'External Source' you need to select '00 Parabolic SAR Trend Following Signals by RPAlawyer: Connector'. From this point, the strategy detects when the indicator generates buy and sell signals.
The strategy considers a strong trend when a buy signal appears above a very conservative ATR band, or a sell signal below the ATR band. The conservative ATR is chosen to filter ranging markets. This very conservative ATR setting has a default multiplier of 8 and length of 40. The multiplier can be increased up to 10, but there will be very few buy and sell signals at that level and DCA requirements will be very high. Trade entry and DCA occur at these strong trends. In the settings, the 'ATR Filter' setting determines the entry condition (e.g., ATR Filter multiplier of 9), and the 'DCA ATR' determines when DCA will happen (e.g., DCA ATR multiplier of 6).
The DCA levels and DCA amounts are determined as follows:
The first DCA occurs below the DCA Base Deviation% level (see settings, default 3%) which acts as a threshold. The thick green line indicates the long position avg price, and the thin red line below the green line indicates the 3% DCA threshold for long positions. The thick red line indicates the short position avg price, and the thin red line above the thick red line indicates the short position 3% DCA threshold. DCA size multiplier defines the DCA amount invested.
If the loss exceeds 3% AND a buy signal arrives below the lower ATR band for longs, or a sell signal arrives above the upper ATR band for shorts, then the first DCA will be executed. So the first DCA won't happen at 3%, rather 3% is a threshold where the additional condition is that the price must close above or below the ATR band (let's say the first DCA occured at 8%) – this is why the code resembles a dynamic grid strategy, where the grid moves such that alongside the first 3% threshold, a strong trend must also appear for DCA. At this point, the thick green/red line moves because the avg price is modified as a result of the DCA, and the thin red line indicating the next DCA level also moves. The next DCA level is determined by the first DCA level, meaning modified avg price plus an additional +8% + (3% * the Step Scale Multiplier in the settings). This next DCA level will be indicated by the modified thin red line, and the price must break through this level and again break through the ATR band for the second DCA to occur.
Since all this wasn't complicated enough, and I was always obsessed by the idea that when we're sitting in an underwater position for days, doing DCA and waiting for the price to correct, we can actually enter a short position on the other side, on which we can realize profit (if the broker allows taking hedge positions, Binance allows this in Europe).
This opposite position in this strategy can open from the point AFTER THE FIRST DCA OF THE BASE POSITION OCCURS. This base position first DCA actually indicates that the price has already moved against us significantly so time to earn some money on the other side. Breaking through the ATR band is also a condition for entry here, so the hedge position entry is not automatic, and the condition for further DCA is breaking through the DCA Base Deviation (default 3%) and breaking through the ATR band. So for the 'hedge' or rather opposite position, the entry and further DCA conditions are the same as for the base position. The hedge position avg price is indicated by a thick black line and the Next Hedge DCA Level is indicated by a thin black line.
The TPs are indicated by green labels for base positions and red labels for hedge positions.
No SL built into the strategy at this point but you are free to do your coding.
Summary data can be found in the upper right corner.
The fantastic trend reversal indicator Machine learning: Lorentzian Classification by jdehorty can be used as an external indicator, choose 'backtest stream' for the external source. The ATR Band multiplicators need to be reduced to 5-6 when using Lorentz.
The code can be further developed in several aspects, and as I write this, I already have a few ideas 😊
TrippleMACDCryptocurrency Scalping Strategy for 1m Timeframe
Introduction:
Welcome to our cutting-edge cryptocurrency scalping strategy tailored specifically for the 1-minute timeframe. By combining three MACD indicators with different parameters and averaging them, along with applying RSI, we've developed a highly effective strategy for maximizing profits in the cryptocurrency market. This strategy is designed for automated trading through our bot, which executes trades using hooks. All trades are calculated for long positions only, ensuring optimal performance in a fast-paced market.
Key Components:
MACD (Moving Average Convergence Divergence):
We've utilized three MACD indicators with varying parameters to capture different aspects of market momentum.
Averaging these MACD indicators helps smooth out noise and provides a more reliable signal for trading decisions.
RSI (Relative Strength Index):
RSI serves as a complementary indicator, providing insights into the strength of bullish trends.
By incorporating RSI, we enhance the accuracy of our entry and exit points, ensuring timely execution of trades.
Strategy Overview:
Long Position Entries:
Initiate long positions when all three MACD indicators signal bullish momentum and the RSI confirms bullish strength.
This combination of indicators increases the probability of successful trades, allowing us to capitalize on uptrends effectively.
Utilizing Linear Regression:
Linear regression is employed to identify consolidation phases in the market.
Recognizing consolidation periods helps us avoid trading during choppy price action, ensuring optimal performance.
Suitability for Grid Trading Bots:
Our strategy is well-suited for grid trading bots due to frequent price fluctuations and opportunities for grid activation.
The strategy's design accounts for price breakthroughs, which are advantageous for grid trading strategies.
Benefits of the Strategy:
Consistent Performance Across Cryptocurrencies:
Through rigorous testing on various cryptocurrency futures contracts, our strategy has demonstrated favorable results across different coins.
Its adaptability makes it a versatile tool for traders seeking consistent profits in the cryptocurrency market.
Integration of Advanced Techniques:
By integrating multiple indicators and employing linear regression, our strategy leverages advanced techniques to enhance trading performance.
This strategic approach ensures a comprehensive analysis of market conditions, leading to well-informed trading decisions.
Conclusion:
Our cryptocurrency scalping strategy offers a sophisticated yet user-friendly approach to trading in the fast-paced environment of the 1-minute timeframe. With its emphasis on automation, accuracy, and adaptability, our strategy empowers traders to navigate the complexities of the cryptocurrency market with confidence. Whether you're a seasoned trader or a novice investor, our strategy provides a reliable framework for achieving consistent profits and maximizing returns on your investment.
Gann Square of 144This indicator will create lines on the chart based on W.D. Gann's Square of 144. All the inputs will be detailed below
Why create this indicator?
I didn't find it on Tradingview (at least with open source). But the main reason is to study the strategy and be able to draw it fast. Manually drawing the square is not hard, but moving all together to the right spots and scale was time-consuming.
It has a lot of inputs...
Yes, each square point divisible by 6 has information with some options, so the user can create any configuration he wants. Also, it has the advantage of having the square built in seconds and adjusting itself on each new calculation.
About the inputs
Starting Date
This input will be used when the "Set Upper/Lower Prices and Start Bar Automatically" checkbox is not selected. The indicator will calculate all the line locations on the chart using the selected start date. When selecting this input, change the Manual Max and Min Prices to the better calculation
Manual Max/Min Price
This input will be used when the "Set Upper/Lower Prices and Start Bar Automatically" checkbox is not selected. The indicator will calculate all the line's locations on the chart using these prices
Set Upper/Lower Prices and Start Bar Automatically
Selects if the starting date will be automatically selected by the system or based on the input data. When it's set, the indicator will use the most recent bar as the middle point of the square, using the higher price as the Upper Price and the lowest price as the Lower Price in the latest 72 bars (or more based on the Candles Per Division parameter)
Update at a new bar
When this option is market, the indicator will update all created lines to match the new bar position, together with all the possible new Upper/Lower prices. Let it unchecked to watch the progression of the price while the square remains fixed in the chart.
Top X-Axis
When checked, it will display the labels on the Top of the square
Bottom X-Axis
When checked, it will display the labels on the Bottom of the square
Left X-Axis
When checked, it will display the labels on the left of the square
Right X-Axis
When checked, it will display the labels on the right of the square
Show Prices on the Right Y-Axis
When checked, it will display the prices together with the labels on the right of the square
Show Vertical Divisions
Show the lines that will divide the square into 9 equal parts
Show Extra Lines
Show unique lines that will come from the Top and bottom middle of the square, connecting the center to the 36 and 108 levels
Show Grid
When selected, it will display a grid in the square
Line Patterns
A selector with some options of built-in lines configuration. When any option besides None is selected, it will override the lines inputs below
Numbers Color
Select the color of each number on the Axis
Vertical Lines Color
Select the color of the vertical lines
Grid Color
Select the grid line color
Connections from corners to N
Each corner is represented by 2 characters, so they all fit in a single line
It will indicate where the line starts and where it ends
┏ ↓ = Top Left to Bottom
┏ → = Top Left to Right
┗ ↑ = Bottom Left to Top
┗ → = Bottom Left to Right
┓ ← = Top Right to Left
┓ ↓ = Top Right to Bottom
┛ ← = Bottom Right to Left
┛ ↑ = Bottom Right to Top
Besides selecting what line will be created, it's possible to select the color, the style, and the extension
How to use this indicator
When you dig into Gann's books for more information about the square of 144, you find that it was part of his setup with multiple indicators (technical and fundamental, and astrological). It is not a "one indicator" setup, so it's hard to say that you will find entries, exits, stop loss, and take profit in this. Still, it will help see trendiness, support, and resistance levels.
Mixing this with other indicators is probably a good idea, but some may find this indicator the only one needed.
Some aspects of the square
The end of the square is important, so where it starts is crucial. The end is important because it is where the price and time expire. The other parts of the square are defined based on their start and end, so placing them right is essential.
So, where to set the start of the square?
The last major low is the most indicated. The minimum price will be the lowest, and the max price will be the last major Top. Note that the indicator uses 1 candle on each point.
After finding the start, the minimum, and the maximum prices for the square, it will draw all lines. Another essential part of the square is The Midpoint.
The midpoint is the most crucial part of the square and is the best way to see if you positioned the square correctly. When the price is inside the square, using the starting candle as the start, a second higher low or a lower high occurs in that spot. When using the Vertical lines in the indicator, it's the middle square inside Gann's square.
The other divisions will be opposing each other most of the time. So if the price is rising in the 1/3 of the square, it's common to see the price fall in the 3/3 of the square.
More information about these aspects here
Considerations
This indicator was meant for price targets and a time calculator for possible support/resistances in the chart. It was created by William Delbert Gann and was part of his setup for trading almost a century ago. The lines will form geometric figures, which Gann used with high accuracy to predict tops/bottoms and when they would occur.
Murrey Math SMA up to 32s Murrey Math SMA up to 32s is a highly advanced Pine Script v5 indicator that combines Murrey Math Lines (MML) with a customizable moving average (MA) — including a non-repainting Rolling VWAP (RVWAP) — and dynamic color-coded support/resistance bands up to 1/32 subdivisions. It projects octave-based geometric price levels (like Gann) centered on your chosen MA, with adaptive scaling, angle-based trend coloring, and absolute/extended MML bands. Includes 1/8, 1/16, and 1/32 grid lines, shaded zones, labels, and a live increment display.Core FeaturesFeature
Description
MA Types
SMA, VWMA, VWAP, Period VWAP, RVWAP (rolling VWAP over fixed or adaptive time window)
Murrey Math Grid
Auto-scaled 0/8 to 8/8 + extensions (±3/8), with 1/16 & 1/32 subdivisions
Dynamic Coloring
Bands colored by MA slope angle (bullish/bearish) or absolute MML shift
RVWAP Engine
Non-repainting volume-weighted average over user-defined or adaptive time steps
Wick Filtering
Optional ignore wicks for cleaner MML framing
Resolution Support
Works with higher timeframe data via request.security()
Key Use Cases Use Case
How to Use
1. Precision Support & Resistance
Treat 4/8 (mid) as pivot, 0/8 & 8/8 as extremes. Price often reverses or accelerates at these levels.
2. Mean Reversion Trades
Buy near 0/8–1/8 (oversold), sell near 7/8–8/8 (overbought) when MA is flat or sloping mildly.
3. Trend Continuation
When MA angle > threshold and price breaks 5/8, expect move to 8/8. Confirm with volume.
4. Breakout Entries
Watch for close beyond 8/8 or 0/8 + MA angle steep → strong momentum breakout.
5. Scalping with 1/32 Grid
Use 1/32 lines as micro-targets in ranging markets or after news spikes.
6. Volume-Weighted Fair Value
RVWAP = true average price paid over time → anchor for institutional fair value.
Visual Layout (MA-Centered)
+3/8 ───┐
+2/8 ───┤ ← Strong resistance
+1/8 ───┤
8/8 ███┤ ← Overbought (red zone)
7/8 ───┤
6/8 ███┤
5/8 ───┤
4/8 ███┤ ← Midline (pivot)
3/8 ───┤
2/8 ███┤
1/8 ───┤
0/8 ███┤ ← Oversold (green zone)
-1/8 ───┤
-2/8 ───┤
-3/8 ───┘
Shaded: 0/8–1/8 (buy), 7/8–8/8 (sell), 3/8–5/8 (neutral/consolidation)
MA Line: Orange (RVWAP) or hidden
Labels: Bottom, 1/4, Mid, 3/4, Top (offset to the right)
Table: Shows current Increment size
Best For Swing & scalp traders on stocks, forex, crypto
Volume-based strategies (RVWAP shines in high-volume moves)
Gann/Murrey Math enthusiasts wanting automation + modern MA anchoring
EM Visible Range Volume Profile█ OVERVIEW
ᴇᴍ VRVP (Visible Range Volume Profile) indicator calculates the volume profile within the visible range of prices.
Volume Profile is an advanced technical analysis indicator that shows trading activity over a specified period of time at certain price levels.
The indicator plots a histogram on the chart that reflects dominant or significant price levels based that are based on volume.
VP concept
VP Components
Open, High, Low, Close:
There are different types of volume profile indicators but the majority of them will designate the OHLC.
Point of Control:
A price level with the most traded volume during one session, also known as POC.
High Volume Node (HVN):
Area of high volume relative to surrounding price action.
Low Volume Node (LVN):
Area of low volume relative to surrounding price action.
Analysis of price in relation to high and low volume nodes is useful when building context around your trades.
█ VOLUME PROFILE STRATEGIES
The distribution of a volume profile can help you determine the strength of a trend and spot potential reversal zones. Let’s take a look at the five different distribution types.
Neutral D
In order for price to break away from value, either the buyers or the sellers will have to become more aggressive than the other side. When this occurs, it gives us with a vital piece of information.
Now we know who were the agressors at this price level: either the buyers or the sellers. That's why this is a good level for a trading setup if the price bounces back.
Bearish P and Bullish P
Bearish P — reversal. Bullish P — confirmation.
Bearish Ь and Bullish Ь
Bearish Ь — confirmation. Bullish Ь — reversal.
Examples
█ INPUTS
Width — amplitude of the VP histogram.
Grid — the number of columns of the VP histogram.
Delta of volumes — combinatorial determination of the ratios of sellers and buyers.
In quoted units — conversion in units of quoted currency.
Logarithmic scale — recalculation the grid step to the logarithmic scale of the chart.
HTF — (Higher Timeframe) calculation of VP for the period of the selected timeframe. ISO: Isolated computation in HTF period.
Palette: Total volume, Volume of buyers, Volume of sellers, HTF bars.
Warnings: colour of the «⚠» icon, language of information in the Tooltip.
Addition: ᴇᴍ CHN-RMA — a grid of moving averages with periods of centered hexagonal numbers.
█ ОБЩИЕ СВЕДЕНИЯ
ᴇᴍ VRVP (Visible Range Volume Profile) рассчитывает профиль объёма в видимом диапазоне цен.
Профиль объёма — это продвинутый индикатор технического анализа, который показывает торговую активность за условленный период времени на определённых ценовых уровнях.
Индикатор строит на графике гистограмму, отражающую доминирующие или значимые ценовые уровни, основанные на объёме.
█ НАСТРОЙКИ
Ширина — амплитуда гистограммы VP.
Сетка — количество колонок гистограммы VP.
Дельта объёмов — комбинаторное определение соотношений продаж и покупок.
В котируемых единицах — пересчёт в единицах котируемой валюты.
Логарифмическая шкала — пересчёт шага сетки на логарифмическую шкалу графика.
HTF — (Higher Timeframe) расчёт VP за период выбранного таймфрейма. ISO: Изолированное вычисление в HTF-периоде.
Палитра: Суммарный объём, Объём покупок, Объём продаж, Бары HTF.
Предупреждения: цвет значка «⚠», язык информации в Tooltip.
Дополнение: ᴇᴍ CHN-RMA — сетка скользящих средних с периодами центрированных гексагональных чисел.
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
Daily Buy/Sell Triggers + ATR TargetsThis tool gives you a once-per-day, objective ATR map: Buy Trigger above the open, Sell Trigger below the open, clean ATR targets, and FULL ATR extremes. It’s designed for clarity, precision, and zero intraday repainting so you can plan the session and execute with confidence.
This indicator prints a new, static grid of intraday levels every New York 18:00 (end of the NY trading day). The grid is anchored at the day’s open and spaced by the Daily ATR so you get tick-precise Buy Trigger, Sell Trigger, intermediate ATR targets, and the FULL ATR bounds for the session.
The levels act as objective support/resistance and intraday measuring sticks for continuation, mean-reversion, and range expansion trades.
What you see on the chart
A thin midline at the Daily Open (anchor).
Green lines above, red lines below, spaced at your chosen ATR multiples.
Text at the far right for:
Buy trigger
Sell trigger
FULL ATR (both sides)
Intermediate targets are unlabeled to keep the chart clean (they’re still tradable S/R).
Visually Layered OscillatorVisually Layered Oscillator User's Manual
Visually Layered Oscillator is a multi-oscillator designed to provide an intuitive visualization of RSI, MACD, ADX + DMI, allowing traders to interpret multiple signals at a glance.
It is designed to allow comparison within the same panel while maintaining the inherent meaning of each oscillator and compensating for visual distortion issues caused by size differences.
Component Overview
Item Description
RSI (x10) Displays relative buy/sell strength. Values above 70 are overbought; values below 30 are oversold.
MACD (3,16,10) Momentum indicator showing the difference between moving averages. Consists of lines and histograms
ADX ×50 + DMI Indicates the strength of the trend; ADX determines the strength of the trend and DMI determines whether it is buy/sell dominant.
White background color treatment Removes difficult-to-see grid lines to improve visibility.
🖥️ Screen Example
The panel is divided into the following three layers
mathematica
Copy
Edit
Top: ⬆️ RSI (purple)
Middle: 📈 MACD, Signal, Histogram + Color Fill
Bottom: 📉 ADX × 50, DMI+ / DMI- (Red, Blue, Orange)
TIP: If you zoom in on the indicators at a larger scale, you can see that each indicator is drawn at a different height level and placed in such a way that they do not overlap.
⚙️ Settings
Fast Length: MACD Quick Line Duration (Basic 3)
Slow Length: MACD slow line period (basic 16)
Smoothing: Signal line smoothing value (basic 10)
Notes and Tips
RSI × 10 and ADX × 50 are for visualization purposes only multiplied by multiples of the actual values. It does not affect the calculation and maintains the original RSI/ADX characteristics.
The MACD fill color visually highlights crossing conditions.
The background is treated in full white, making the indicator look clean without grid lines.
Candle % High/Low Bar + HL Order + MA by Barty&PitPapcioWhat does the indicator show?
The "Candle % High/Low Bar + HL Order + MA by Barty&PitPapcio" indicator displays the percentage deviation of each candle’s high and low relative to its open price. The zero line represents the candle’s open — bars above zero show upward movement from the open (to high), bars below zero show downward movement (to low).
Additionally, the indicator plots a dot above or below each bar indicating which came first during the candle — the high or the low — based on data from a lower timeframe two steps below the current chart (for example, on a 1-hour chart it uses 15-minute data).
Finally, the indicator calculates and plots a user-selectable moving average (EMA, SMA, or WMA) of these "first high or low" signals, helping identify trends whether the first move is more often upwards or downwards.
Where do the data come from?
Percentage values are calculated directly from the current chart’s candles:
highPerc=(High−Open)/Open×100%,
lowPerc=(Low−Open)/Open×100%
The timing of the first high or low for each candle is retrieved from a lower timeframe, stepping down two levels from the current timeframe (e.g. from 1H to 15 min), providing better precision in detecting the order of highs and lows that may be blurred on higher timeframes.
Additional features:
Full customization of colors for bars, dots, zero line, grid, and thicknesses.
Background grid with adjustable scale and style.
Safety checks for missing lower timeframe data.
A moving average smoothing the sequence of first high/low signals to reveal directional tendencies.
Suggested strategy for technical analysis support
Identify dominant candle direction: If the dot often appears above the bar (first high), it indicates buying pressure; if below (first low), selling pressure dominates.
Use percentage deviations: Large percent bars indicate heightened volatility and potential reversal points.
Moving average on order signals: The EMA of high/low first signals smooths the noise, showing the dominant trend in the sequence of price moves, useful for filtering other signals.
Combine with other tools: This indicator can act as a directional filter on multiple timeframes, synergizing well with momentum indicators, RSI, or support/resistance levels to confirm move strength.
Lots of love, Bartosz
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Gann & Fibonacci Analysis for MSTRYes! Below is a step-by-step guide to performing Gann Analysis on MSTR in TradingView for the last year.
Step 1: Set Up the Chart
Open TradingView and search for MSTR (MicroStrategy).
Select the 1-day (D) timeframe to analyze the past year.
Set your chart to logarithmic scale (⚙ Settings → Scale → Log).
Enable grid lines for alignment (⚙ Settings → Appearance → Grid Lines).
Step 2: Identify Key Highs and Lows (Last Year)
Find the 52-week high and 52-week low for MSTR.
As of now:
52-Week High: ~$999 (March 2024).
52-Week Low: ~$280 (October 2023).
Step 3: Plot Gann Angles
Using TradingView's Gann Fan Tool:
Select "Gann Fan" (Press / and type “Gann Fan” to find it).
Start at the 52-week low (~$280, October 2023) and drag upwards.
Adjust the angles to match key levels:
1x1 (45°) → Main trendline
2x1 (26.5°) → Strong uptrend
4x1 (15°) → Weak trendline
1x2 (63.75°) → Strong resistance
Repeat the process from the 52-week high (~$999, March 2024) downward to see bearish angles.
Step 4: Apply Fibonacci & Gann Retracement Levels
Using Fibonacci Retracement:
Select "Fibonacci Retracement" tool.
Draw from 52-week high ($999) to 52-week low ($280).
Enable key Fibonacci levels:
23.6% ($816)
38.2% ($678)
50% ($640)
61.8% ($550)
78.6% ($430)
Watch for price reactions near these levels.
Using Gann Retracement Levels:
Select "Gann Box" in TradingView.
Draw from 52-week high ($999) to low ($280).
Enable key Gann retracement levels:
12.5% ($912)
25% ($850)
37.5% ($768)
50% ($640)
62.5% ($550)
75% ($480)
87.5% ($350)
Identify confluences with Gann angles and Fibonacci levels.
Step 5: Identify Significant Dates & Time Cycles
Use "Date Range" Tool in TradingView.
Mark major turning points:
High → Low: ~180 days (Half-year cycle).
Low → High: ~90 days (Quarter cycle).
Use Square-Outs (Time = Price method):
Example: If MSTR hit $500, check 500 days from key events.
Mark key anniversaries of past highs/lows for possible reversals.
Step 6: Analyze and Trade Execution
✅ If MSTR is at a Gann angle + Fibonacci level + key date → Expect a reaction.
✅ Use RSI, MACD, and Volume for extra confirmation.
✅ Set Stop-Loss at nearest Gann support/resistance.
Watchlist & Symbols Distribution [Daveatt]TLDR;
I got bored so I just coded the TradingView watchlist interface in Pinescript :)
TLDR 2:
Sharing it open-source what took me 1 full day to code - haven't coded in Pinescript in a long time, so I'm a bit slow for now :)
█ OVERVIEW
This script offers a comprehensive market analysis tool inspired by TradingView's native watchlist interface features.
It combines an interactive watchlist with powerful distribution visualization capabilities and a performance comparison panel.
The script was developed with a focus on providing multiple visualization methods while working within PineScript's limitations.
█ DEVELOPMENT BACKGROUND
The pie chart implementation was greatly inspired by the ( "Crypto Map Dashboard" script / )
adapting its circular visualization technique to create dynamic distribution charts. However, due to PineScript's 500-line limitation per script, I had to optimize the code to allow users to switch between pie chart analysis and performance comparison modes rather than displaying both simultaneously.
█ SETUP AND DISPLAY
For optimal visualization, users need to adjust the chart's display settings manually.
This involves:
Expanding the indicator window vertically to accommodate both the watchlist and graphical elements
Adjusting the Y-axis scale by dragging it to ensure proper spacing for the comparison panel grid
Modifying the X-axis scale to achieve the desired time window display
Fine-tuning these adjustments whenever switching between pie chart and comparison panel modes
These manual adjustments are necessary due to PineScript's limitations in controlling chart scaling programmatically. While this requires some initial setup, it allows users to customize the display to their preferred viewing proportions.
█ MAIN FEATURES
Distribution Analysis
The script provides three distinct distribution visualization modes through a pie chart.
Users can analyze their symbols by exchanges, asset types (such as Crypto, Forex, Futures), or market sectors.
If you can't see it well at first, adjust your chart scaling until it's displayed nicely.
Asset Exchanges
www.tradingview.com
Asset Types
Asset Sectors
The pie charts feature an optional 3D effect with adjustable depth and angle parameters. To enhance visual customization, four different color schemes are available: Default, Pastel, Dark, and Neon.
Each segment of the pie chart includes interactive tooltips that can be configured to show different levels of detail. Importantly, the pie chart only visualizes the distribution of selected assets (those marked with a checkmark in the watchlist), providing a focused view of the user's current interests.
Interactive Watchlist
The watchlist component displays real-time data for up to 10 user-defined symbols. Each entry shows current price, price changes (both absolute and percentage), volume metrics, and a comparison toggle.
The table is dynamically updated and features color-coded entries that correspond to their respective performance lines in the comparison chart. The watchlist serves as both an information display and a control panel for the comparison feature.
Performance Comparison
One of the script's most innovative features is its performance comparison panel.
Using polylines for smooth visualization, it tracks the 30-day performance of selected symbols relative to a 0% baseline.
The comparison chart includes a sophisticated grid system with 5% intervals and a dynamic legend showing current performance values.
The polyline implementation allows for fluid, continuous lines that accurately represent price movements, providing a more refined visual experience than traditional line plots. Like the pie charts, the comparison panel only displays performance lines for symbols that have been selected in the watchlist, allowing users to focus on their specific assets of interest.
█ TECHNICAL IMPLEMENTATION
The script utilizes several advanced PineScript features:
Dynamic array management for symbol tracking
Polyline-based charting for smooth performance visualization
Real-time data processing with security calls
Interactive tooltips and labels
Optimized drawing routines to maintain performance
Selective visualization based on user choices
█ CUSTOMIZATION
Users can personalize almost every aspect of the script:
Symbol selection and comparison preferences
Visual theme selection with four distinct color schemes
Pie chart dimensions and positioning
Tooltip information density
Component visibility toggles
█ LIMITATIONS
The primary limitation stems from PineScript's 500-line restriction per script.
This constraint necessitated the implementation of a mode-switching system between pie charts and the comparison panel, as displaying both simultaneously would exceed the line limit. Additionally, the script relies on manual chart scale adjustments, as PineScript doesn't provide direct control over chart scaling when overlay=false is enabled.
However, these limitations led to a more focused and efficient design approach that gives users control over their viewing experience.
█ CONCLUSION
All those tools exist in the native TradingView watchlist interface and they're better than what I just did.
However, now it exists in Pinescript... so I believe it's a win lol :)






















