ATR ZigZag - Volatility-Filtered Market StructureDescription
This indicator draws ZigZags using an ATR based threshold for direction switching to identify major swing highs and lows. Instead of relying on fractals or fixed bar-count swings, pivots are confirmed only when price moves beyond the prior extreme by:
threshold = ATR(length) × ATR_mult
This filters noise, enforces valid swing structure (high → low → high), and adapts automatically to volatility. The ATR ZigZag is ideal for traders who want a clean, objective view of swing structure without noise. This has many uses, including mapping swing structure, drawing chart patterns, and trading around extremes.
Lag and Repainting
Pivots are confirmed only after price moves sufficiently in the opposite direction. This creates necessary lag. The ZigZag is drawn when this occurs, and will anchor to the high/low in the past. Optional detection dot plots show exactly when confirmation occurred.
What You See
ZigZag: dashed gray line, repainted to anchor at the confirmed highs and lows
Latest Pivot Levels: Dashed horizontal lines at the most recent confirmed high/low.
Optional Live Swing Leg: A real-time line from the last confirmed pivot to the current swing extreme, updating until a new pivot forms.
Optional ATR Boxes: 1×ATR shaded zones around the latest pivot for structural context.
Optional Pivot Confirmation Dots: Markers show the bar where the threshold is crossed and a swing is officially confirmed. This is to understand the lag and see when the ZigZag repainted.
Buscar en scripts para "fractals"
Bappa - Dynamic VWAP Simple Vwap, just dynamic colour Coding added to sense whether VWAP is in uptrend or downtrend. Refer to colour code to enter Call side or Put side, it never disappoints you at any timeframe. Enjoy & happy Trading!!
Better results if used in conjuction with Pivots/ fractals indicator, named as Bappa EMA + BBW (V2) indicator.
$MTF Fractal Echo DetectorMIL:MTVFR FRACTAL ECHO DETECTOR by Timmy741
The first public multi-timeframe fractal convergence system that actually works.
Market makers don’t move price randomly.
They test the same fractal structure on lower timeframes first → then execute the real move on higher timeframes.
This indicator catches the “echo” — when 3–5 timeframes are printing fractals at almost the exact same price level.
That’s not coincidence. That’s preparation.
FEATURES
• 5 simultaneous timeframes (1min → 4H by default)
• Real Williams Fractal detection (configurable period)
• Dynamic echo tolerance & minimum TF alignment
• Visual S/R zones from every timeframe
• Bullish / Bearish echo convergence signals
• Strength meter (3/5, 4/5, 5/5 TF alignment)
• Zero repainting — uses proper lookahead=off
• Fully Pine v6 typed + optimized
USE CASE
When you see a 4/5 or 5/5 echo:
→ That level is being defended or attacked with intent
→ 80%+ chance the next real move comes from there
→ Trade the breakout or reversal at that exact fractal cluster
Works insane on:
• BTC / ETH (all timeframes)
• Nasdaq / SPX futures
• Forex majors (especially GBP & gold)
• 2025 small-cap rotation setups
100% Open Source • MPL 2.0 • Built by Timmy741 • December 2024
If you know about fractal echoes… you already know.
#fractal #mtf #echo #williamsfractal #multitimeframe #smartmoney #ict #smc #orderflow #convergence #timmy741 #snr #structure
Exhaustion Zone [by rukich]🟠 OVERVIEW
The indicator shows asset exhaustion — an area of interest where potential buying opportunities can be considered.
🟠 COMPONENTS
The indicator is based on a combination of fundamental tools designed to properly react to price movement and volatility.
It is displayed on the chart as a green line. When the price touches the indicator line, the candle lights up and is highlighted in green.
🟠 HOW TO USE
The best timeframes for using the indicator: 1D and 3D.
Since the indicator is used on higher timeframes, the price rarely reaches the indicator line, but it often shows a strong reaction when it does, which suggests that the indicator can be used for investment purposes.
Since the zone suggests potential buying opportunities, it’s best to act from the zone only when a reaction is confirmed. Confirmation may include a candle close beyond nearby fractals or the invalidation of the nearest resistance zone.
🟠 CONCLUSION
The indicator highlights an area of interest where, upon confirmation of a reaction, buying opportunities may be considered.
Monitor Posición Bollinger Multi-TFThis indicator provides a comprehensive dashboard that allows you to monitor the price position relative to Bollinger Bands across 7 different timeframes simultaneously, without the need to switch charts.
It uses the %B (Percent B) logic to normalize the price position, giving you an instant "Heatmap" view of the market state (Overbought/Oversold) from the 1-minute chart up to the Weekly chart.
Key Features:
Multi-Timeframe Monitoring: Watch 1m, 5m, 15m, 1h, 4h, Daily, and Weekly timeframes in a single panel.
Dynamic Color Coding:
Dark Red: Price breaking above the Upper Band (>100%).
Light Red: Price near the Upper Band (Resistance zone).
Gray: Price in the neutral middle zone.
Light Green: Price near the Lower Band (Support zone).
Dark Green: Price breaking below the Lower Band (<0%).
Trend Arrows: Indicates momentum (▲ or ▼) based on the previous candle's position.
Current Timeframe Highlight: Automatically highlights the row corresponding to your current chart view in orange.
Fully Customizable: Adjust Bollinger settings (Length, Mult), choose your preferred timeframes, and change the table position/size.
Movable Panel: Includes X/Y offset settings to prevent the table from blocking price action or menu buttons.
How to Use:
Add the indicator to your chart.
Use the dashboard to spot confluence across timeframes.
Example: If 15m, 1H, and 4H are all showing Red, the asset is likely overextended to the upside.
Example: If the lower timeframes are turning Green while the higher timeframes remain Gray/Bullish, it might indicate a pullback opportunity.
Settings:
Bollinger Config: Length (20) and Multiplier (2.0) by default.
Timeframes: Select the 7 specific TFs you want to track.
Visuals: Change table position, text size, and offset coordinates.
This tool is essential for scalpers and day traders who need situational awareness across multiple fractals instantly.
Liquidity Structure & Sweeps [Visualized]Liquidity Structure & Sweeps | 流动性结构与猎杀
1. Design Philosophy & Logic
This indicator is designed based on Smart Money Concepts (SMC) and Market Microstructure principles. Unlike traditional indicators that rely on lagging averages or repainting fractals, this script focuses on "Objective Structure" and "Liquidity Grabs".
The core design philosophy rests on three pillars:
Zero Repainting (Real-time Integrity): We utilize a strict "Left-Side Confirmation" algorithm. A structure level is only stored in memory when the candle is fully closed (barstate.isconfirmed). This ensures that the historical signals you see are exactly what happened in real-time.
Institutional Memory (Visualized): Markets "remember" key levels. This script draws dashed lines extending from valid pivot points. These lines represent "resting liquidity" (Stop Orders). They remain on the chart until the price interacts with them.
Sweep vs. Breakout: Not all breaches are equal. We specifically look for "Sweeps" (Liquidity Grabs) — where price pierces a level but closes back inside. This is a classic sign of absorption and potential reversal, distinct from a structural breakout.
2. Key Features
Visualized Order Blocks: Automatically draws potential support (Green Dotted) and resistance (Red Dotted) lines based on fractal points.
Wick Detection: Filters out strong momentum breakouts. Signals are only generated when a specific "Wick Ratio" is met, indicating a rejection.
Clean Charts: Features a "Garbage Collection" mechanism. Once a level is swept, the line is removed, and a signal dot is placed. Old, untouched levels are automatically cycled out to prevent chart clutter.
3. How to Use
The Lines (Context):
Red Dotted Line: Buy-side Liquidity (Resistance). Expect potential shorts or breakouts here.
Green Dotted Line: Sell-side Liquidity (Support). Expect potential longs or breakdowns here.
The Signals (Action):
Red Dot (Bearish Sweep): Price spiked above a Resistance Line but closed below it. This suggests long stops were hunted, and bears are stepping in.
Green Dot (Bullish Sweep): Price spiked below a Support Line but closed above it. This suggests short stops were hunted, and bulls are stepping in.
Configuration:
Structure Length: Adjusts sensitivity. Higher values (e.g., 20-50) find major swing points; lower values (e.g., 5-10) find scalping setups.
Wick Filter %: The minimum size of the wick relative to the breakout. Increase this to filter for only the most dramatic rejections.
4. Developer Notes & Considerations
Why do lines disappear? In this logic, liquidity is treated as "Fuel". Once a level is swept (the stop orders are triggered), the fuel is consumed. Keeping the line would clutter the chart with invalid data.
Why is the dot small? The indicator is designed to be part of a toolchain, not a standalone signal. The minimalist design prevents visual interference with price action or other indicators.
1. 设计思路与核心逻辑
本指标基于 聪明钱概念 (SMC) 与 市场微观结构 原理设计。不同于依赖滞后均线或存在重绘问题的传统分形指标，本脚本专注于捕捉 “客观结构” 与 “流动性猎杀 (Liquidity Grabs)”。
核心设计哲学包含三大支柱：
零重绘 (Zero Repainting): 我们采用了严格的“左侧确认”算法。所有的结构位仅在K线完全收盘 (barstate.isconfirmed) 后才会被记录。这保证了您回测看到的信号与实盘完全一致，杜绝“未来函数”陷阱。
可视化的机构记忆: 市场是有记忆的。本脚本会从有效的波段高低点引出虚线。这些虚线代表了“沉睡的流动性”（止损盘聚集区）。它们会一直延伸，直到价格触碰它们。
区分“猎杀”与“突破”: 并不是所有的破位都是一样的。我们专注于识别“扫损（Sweep）”——即价格刺破了关键位，但收盘价收回了关键位内部。这是典型的吸筹或派发信号，与趋势延续的真突破有本质区别。
2. 主要功能
结构可视化: 自动基于分形点绘制潜在的支撑线（绿色虚线）和阻力线（红色虚线）。
插针检测: 过滤掉强势的实体突破。只有当价格出现明显的“长影线”拒绝行为时，才会触发信号。
图表自清洁: 内置“垃圾回收”机制。一旦某个关键位的流动性被猎杀（触发信号），该线条会被自动删除。过旧且未被触碰的线条也会被自动替换，保持图表整洁。
3. 使用指南
线条 (市场语境):
红色虚线: 买方流动性池（阻力位）。
绿色虚线: 卖方流动性池（支撑位）。
信号点 (交易动作):
红色圆点 (看跌猎杀): 价格刺破了红色阻力线，但收盘价回落到线下方。这暗示多头止损被触发，主力可能正在建立空单。
绿色圆点 (看涨猎杀): 价格刺破了绿色支撑线，但收盘价反弹到线上方。这暗示空头止损被触发，主力可能正在建立多单。
参数设置建议:
Structure Length (结构周期): 调整灵敏度。数值越大（如 20-50）锁定大级别波段；数值越小（如 5-10）适合短线剥头皮。
Wick Filter % (影线过滤): 设置影线占价格波动的最小比例。调大该数值可以只看最剧烈的反转信号。
4. 开发者注记与潜在考量
为什么线条会消失？ 在本逻辑中，流动性被视为“燃料”。一旦发生猎杀（止损单成交），该位置的燃料即被消耗。移除线条是为了防止无效数据干扰判断。
为什么圆点设计得很小？ 该指标旨在成为您交易工具链的一部分，而非唯一的决策依据。极简设计是为了避免干扰裸K形态或其他指标的观察。
===============================================================
这个脚本（我们称之为 Liq Structure Script）本质上是一个基于价格行为（Price Action）的结构猎杀探测器。
以下是详细的深度对比分析：
1. 如何使用？ (实战操作手册)
不要把它当作“红灯停绿灯行”的傻瓜指标。把它当作一个**“战场地图”**。
第一阶段：观察结构 (The Setup)
图表上会自动画出 红色虚线（上方压力）和 绿色虚线（下方支撑）。
解读：告诉自己，“这里埋着很多人的止损单”。不要在这里盲目追涨杀跌。
第二阶段：等待猎杀 (The Trigger)
耐心等待价格冲向这些虚线。
关键动作：价格刺破虚线，然后迅速收回。
信号确认：虚线消失，留下一个 红点（顶部猎杀）或 绿点（底部猎杀）。
第三阶段：进场逻辑 (The Execution)
做空逻辑：出现红点 + K线留长上影线 → 说明多头试图突破失败，被主力“倒了一盆冷水”。此时可尝试做空，止损设在刚刚那个最高点上方一点点。
做多逻辑：出现绿点 + K线留长下影线 → 说明空头试图砸盘失败，被主力接住了。
传统爆量是“燃料”，Liq 脚本是“引爆点”。没有引爆点的爆量可能是空转；没有爆量的引爆点可能是假摔。Liq 脚本是一个免费、轻量级、基于K线逻辑的替代品。它不需要你买昂贵的数据服务，它利用的是“图表形态学”中的流动性共识。
结论：如何定位这个工具？
这个脚本不是“预测未来的水晶球”，而是一个**“高胜率区域提示器”**。
用它来找位置（哪里有陷阱？）。
用成交量来做确认（是不是真的有主力介入？）。
用宏观逻辑来定方向（现在该做多还是做空？）。
它是你交易工具链中负责**“微观入场时机（Timing）”**的那一环。
reversalLibrary "reversals"
psar(af_start, af_increment, af_max)
Calculates Parabolic Stop And Reverse (SAR)
Parameters:
af_start (simple float) : Initial acceleration factor (Wilder's original: 0.02)
af_increment (simple float) : Acceleration factor increment per new extreme (Wilder's original: 0.02)
af_max (simple float) : Maximum acceleration factor (Wilder's original: 0.20)
Returns: SAR value (stop level for current trend)
fractals()
Detects Williams Fractal patterns (5-bar pattern)
Returns: Tuple with fractal values (na if no fractal)
swings(lookback, source_high, source_low)
Detects swing highs and swing lows using lookback period
Parameters:
lookback (simple int) : Number of bars on each side to confirm swing point
source_high (float) : Price series for swing high detection (typically high)
source_low (float) : Price series for swing low detection (typically low)
Returns: Tuple with swing point values (na if no swing)
pivot(tf)
Calculates classic/standard/floor pivot points
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels
pivotcam(tf)
Calculates Camarilla pivot points with 8 levels for short-term trading
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels
pivotdem(tf)
Calculates d-mark pivot points with conditional open/close logic
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels (only 3 levels)
pivotext(tf)
Calculates extended traditional pivot points with R4-R5 and S4-S5 levels
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels
pivotfib(tf)
Calculates Fibonacci pivot points using Fibonacci ratios
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels
pivotwood(tf)
Calculates Woodie's pivot points with weighted closing price
Parameters:
tf (simple string) : Timeframe for pivot calculation ("D", "W", "M")
Returns: Tuple with pivot levels
Fractal Levels Monitor w/ Trade Lines (ChadAnt) v2Small update. Prevents the break candle from getting another signal after the first buy/sell signal detected.
1. Fractal Level Detection
The indicator identifies Fractals, which are simply a series of bars where the center bar has the highest high (Bearish Fractal) or the lowest low (Bullish Fractal) compared to a set number of bars on either side (determined by the "Fractal Period" input, usually 2 to 5 bars).
Bullish Fractal Level (Support): The indicator plots a horizontal line at the lowest low of the most recently formed Bullish Fractal.
Bearish Fractal Level (Resistance): It plots a horizontal line at the highest high of the most recently formed Bearish Fractal.
2. The "Cross Candle" Event
The core idea isn't to trade the fractal itself, but the reaction after the fractal level is broken.
When the price breaks and closes through the established Bullish Level (support) or Bearish Level (resistance), that bar is marked as the Cross Candle.
This Cross Candle's High and Low are saved. This is the "setup" for the trade.
3. The Trade Signal (Entry Trigger)
A trade is only taken when the price breaks the extreme (High or Low) of the Cross Candle.
Buy Signal: The trade is entered long if the price breaks above the High of the Cross Candle.
Sell Signal: The trade is entered short if the price breaks below the Low of the Cross Candle.
Fractal Levels Monitor w/ Trade Lines (ChadAnt)1. Fractal Level Detection
The indicator identifies Fractals, which are simply a series of bars where the center bar has the highest high (Bearish Fractal) or the lowest low (Bullish Fractal) compared to a set number of bars on either side (determined by the "Fractal Period" input, usually 2 to 5 bars).
Bullish Fractal Level (Support): The indicator plots a horizontal line at the lowest low of the most recently formed Bullish Fractal.
Bearish Fractal Level (Resistance): It plots a horizontal line at the highest high of the most recently formed Bearish Fractal.
2. The "Cross Candle" Event
The core idea isn't to trade the fractal itself, but the reaction after the fractal level is broken.
When the price breaks and closes through the established Bullish Level (support) or Bearish Level (resistance), that bar is marked as the Cross Candle.
This Cross Candle's High and Low are saved. This is the "setup" for the trade.
3. The Trade Signal (Entry Trigger)
A trade is only taken when the price breaks the extreme (High or Low) of the Cross Candle.
Buy Signal: The trade is entered long if the price breaks above the High of the Cross Candle.
Sell Signal: The trade is entered short if the price breaks below the Low of the Cross Candle.
Fractal Break Strategy with Time FilterThis strategy isn't complete yet but just curious how fast they will take it down. It is based off breaks of fractals and then taking the High/Low of the break candle
Williams Fractals BW - Flechas + Breakoutsfractal con velas en la direccion hacia donde va para menos conficion
FiniteStateMachine🟩 OVERVIEW
A flexible framework for creating, testing and implementing a Finite State Machine (FSM) in your script. FSMs use rules to control how states change in response to events.
This is the first Finite State Machine library on TradingView and it's quite a different way to think about your script's logic. Advantages of using this vs hardcoding all your logic include:
• Explicit logic : You can see all rules easily side-by-side.
• Validation : Tables show your rules and validation results right on the chart.
• Dual approach : Simple matrix for straightforward transitions; map implementation for concurrent scenarios. You can combine them for complex needs.
• Type safety : Shows how to use enums for robustness while maintaining string compatibility.
• Real-world examples : Includes both conceptual (traffic lights) and practical (trading strategy) demonstrations.
• Priority control : Explicit control over which rules take precedence when multiple conditions are met.
• Wildcard system : Flexible pattern matching for states and events.
The library seems complex, but it's not really. Your conditions, events, and their potential interactions are complex. The FSM makes them all explicit, which is some work. However, like all "good" pain in life, this is front-loaded, and *saves* pain later, in the form of unintended interactions and bugs that are very hard to find and fix.
🟩 SIMPLE FSM (MATRIX-BASED)
The simple FSM uses a matrix to define transition rules with the structure: state > event > state. We look up the current state, check if the event in that row matches, and if it does, output the resulting state.
Each row in the matrix defines one rule, and the first matching row, counting from the top down, is applied.
A limitation of this method is that you can supply only ONE event.
You can design layered rules using widlcards. Use an empty string "" or the special string "ANY" for any state or event wildcard.
The matrix FSM is foruse where you have clear, sequential state transitions triggered by single events. Think traffic lights, or any logic where only one thing can happen at a time.
The demo for this FSM is of traffic lights.
🟩 CONCURRENT FSM (MAP-BASED)
The map FSM uses a more complex structure where each state is a key in the map, and its value is an array of event rules. Each rule maps a named condition to an output (event or next state).
This FSM can handle multiple conditions simultaneously. Rules added first have higher priority.
Adding more rules to existing states combines the entries in the map (if you use the supplied helper function) rather than overwriting them.
This FSM is for more complex scenarios where multiple conditions can be true simultaneously, and you need to control which takes precedence. Like trading strategies, or any system with concurrent conditions.
The demo for this FSM is a trading strategy.
🟩 HOW TO USE
Pine Script libraries contain reusable code for importing into indicators. You do not need to copy any code out of here. Just import the library and call the function you want.
For example, for version 1 of this library, import it like this:
import SimpleCryptoLife/FiniteStateMachine/1
See the EXAMPLE USAGE sections within the library for examples of calling the functions.
For more information on libraries and incorporating them into your scripts, see the Libraries section of the Pine Script User Manual.
🟩 TECHNICAL IMPLEMENTATION
Both FSM implementations support wildcards using blank strings "" or the special string "ANY". Wildcards match in this priority order:
• Exact state + exact event match
• Exact state + empty event (event wildcard)
• Empty state + exact event (state wildcard)
• Empty state + empty event (full wildcard)
When multiple rules match the same state + event combination, the FIRST rule encountered takes priority. In the matrix FSM, this means row order determines priority. In the map FSM, it's the order you add rules to each state.
The library uses user-defined types for the map FSM:
• o_eventRule : Maps a condition name to an output
• o_eventRuleWrapper : Wraps an array of rules (since maps can't contain arrays directly)
Everything uses strings for maximum library compatibility, though the examples show how to use enums for type safety by converting them to strings.
Unlike normal maps where adding a duplicate key overwrites the value, this library's `m_addRuleToEventMap()` method *combines* rules, making it intuitive to build rule sets without breaking them.
🟩 VALIDATION & ERROR HANDLING
The library includes comprehensive validation functions that catch common FSM design errors:
Error detection:
• Empty next states
• Invalid states not in the states array
• Duplicate rules
• Conflicting transitions
• Unreachable states (no entry/exit rules)
Warning detection:
• Redundant wildcards
• Empty states/events (potential unintended wildcards)
• Duplicate conditions within states
You can display validation results in tables on the chart, with tooltips providing detailed explanations. The helper functions to display the tables are exported so you can call them from your own script.
🟩 PRACTICAL EXAMPLES
The library includes four comprehensive demos:
Traffic Light Demo (Simple FSM) : Uses the matrix FSM to cycle through traffic light states (red → red+amber → green → amber → red) with timer events. Includes pseudo-random "break" events and repair logic to demonstrate wildcards and priority handling.
Trading Strategy Demo (Concurrent FSM) : Implements a realistic long-only trading strategy using BOTH FSM types:
• Map FSM converts multiple technical conditions (EMA crosses, gaps, fractals, RSI) into prioritised events
• Matrix FSM handles state transitions (idle → setup → entry → position → exit → re-entry)
• Includes position management, stop losses, and re-entry logic
Error Demonstrations : Both FSM types include error demos with intentionally malformed rules to showcase the validation system's capabilities.
🟩 BRING ON THE FUNCTIONS
f_printFSMMatrix(_mat_rules, _a_states, _tablePosition)
Prints a table of states and rules to the specified position on the chart. Works only with the matrix-based FSM.
Parameters:
_mat_rules (matrix)
_a_states (array)
_tablePosition (simple string)
Returns: The table of states and rules.
method m_loadMatrixRulesFromText(_mat_rules, _rulesText)
Loads rules into a rules matrix from a multiline string where each line is of the form "current state | event | next state" (ignores empty lines and trims whitespace).
This is the most human-readable way to define rules because it's a visually aligned, table-like format.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_rulesText (string)
Returns: No explicit return. The matrix is modified as a side-effect.
method m_addRuleToMatrix(_mat_rules, _currentState, _event, _nextState)
Adds a single rule to the rules matrix. This can also be quite readble if you use short variable names and careful spacing.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_currentState (string)
_event (string)
_nextState (string)
Returns: No explicit return. The matrix is modified as a side-effect.
method m_validateRulesMatrix(_mat_rules, _a_states, _showTable, _tablePosition)
Validates a rules matrix and a states array to check that they are well formed. Works only with the matrix-based FSM.
Checks: matrix has exactly 3 columns; no empty next states; all states defined in array; no duplicate states; no duplicate rules; all states have entry/exit rules; no conflicting transitions; no redundant wildcards. To avoid slowing down the script unnecessarily, call this method once (perhaps using `barstate.isfirst`), when the rules and states are ready.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_a_states (array)
_showTable (bool)
_tablePosition (simple string)
Returns: `true` if the rules and states are valid; `false` if errors or warnings exist.
method m_getStateFromMatrix(_mat_rules, _currentState, _event, _strictInput, _strictTransitions)
Returns the next state based on the current state and event, or `na` if no matching transition is found. Empty (not na) entries are treated as wildcards if `strictInput` is false.
Priority: exact match > event wildcard > state wildcard > full wildcard.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_currentState (string)
_event (string)
_strictInput (bool)
_strictTransitions (bool)
Returns: The next state or `na`.
method m_addRuleToEventMap(_map_eventRules, _state, _condName, _output)
Adds a single event rule to the event rules map. If the state key already exists, appends the new rule to the existing array (if different). If the state key doesn't exist, creates a new entry.
Namespace types: map
Parameters:
_map_eventRules (map)
_state (string)
_condName (string)
_output (string)
Returns: No explicit return. The map is modified as a side-effect.
method m_addEventRulesToMapFromText(_map_eventRules, _configText)
Loads event rules from a multiline text string into a map structure.
Format: "state | condName > output | condName > output | ..." . Pairs are ordered by priority. You can have multiple rules on the same line for one state.
Supports wildcards: Use an empty string ("") or the special string "ANY" for state or condName to create wildcard rules.
Examples: " | condName > output" (state wildcard), "state | > output" (condition wildcard), " | > output" (full wildcard).
Splits lines by \n, extracts state as key, creates/appends to array with new o_eventRule(condName, output).
Call once, e.g., on barstate.isfirst for best performance.
Namespace types: map
Parameters:
_map_eventRules (map)
_configText (string)
Returns: No explicit return. The map is modified as a side-effect.
f_printFSMMap(_map_eventRules, _a_states, _tablePosition)
Prints a table of map-based event rules to the specified position on the chart.
Parameters:
_map_eventRules (map)
_a_states (array)
_tablePosition (simple string)
Returns: The table of map-based event rules.
method m_validateEventRulesMap(_map_eventRules, _a_states, _a_validEvents, _showTable, _tablePosition)
Validates an event rules map to check that it's well formed.
Checks: map is not empty; wrappers contain non-empty arrays; no duplicate condition names per state; no empty fields in o_eventRule objects; optionally validates outputs against matrix events.
NOTE: Both "" and "ANY" are treated identically as wildcards for both states and conditions.
To avoid slowing down the script unnecessarily, call this method once (perhaps using `barstate.isfirst`), when the map is ready.
Namespace types: map
Parameters:
_map_eventRules (map)
_a_states (array)
_a_validEvents (array)
_showTable (bool)
_tablePosition (simple string)
Returns: `true` if the event rules map is valid; `false` if errors or warnings exist.
method m_getEventFromConditionsMap(_currentState, _a_activeConditions, _map_eventRules)
Returns a single event or state string based on the current state and active conditions.
Uses a map of event rules where rules are pre-sorted by implicit priority via load order.
Supports wildcards using empty string ("") or "ANY" for flexible rule matching.
Priority: exact match > condition wildcard > state wildcard > full wildcard.
Namespace types: series string, simple string, input string, const string
Parameters:
_currentState (string)
_a_activeConditions (array)
_map_eventRules (map)
Returns: The output string (event or state) for the first matching condition, or na if no match found.
o_eventRule
o_eventRule defines a condition-to-output mapping for the concurrent FSM.
Fields:
condName (series string) : The name of the condition to check.
output (series string) : The output (event or state) when the condition is true.
o_eventRuleWrapper
o_eventRuleWrapper wraps an array of o_eventRule for use as map values (maps cannot contain collections directly).
Fields:
a_rules (array) : Array of o_eventRule objects for a specific state.
Trend FriendTrend Friend — What it is and how to use it
I built Trend Friend to stop redrawing the same trendlines all day. It automatically connects confirmed swing points (fractals) and keeps the most relevant lines in front of you. The goal: give you clean, actionable structure without the guesswork.
What it does (in plain English)
Finds swing highs/lows using a Fractal Period you choose.
Draws auto-trendlines between the two most recent confirmed highs and the two most recent confirmed lows.
Colours by intent:
Lines drawn from highs (potential resistance / bearish) = Red
Lines drawn from lows (potential support / bullish) = Green
Keeps the chart tidy: The newest lines are styled as “recent,” older lines are dimmed as “historical,” and it prunes anything beyond your chosen limit.
Optional crosses & alerts: You can highlight when price closes across the most recent line and set alerts for new lines formed and upper/lower line crosses.
Structure labels: It tags HH, LH, HL, LL at the swing points, so you can quickly read trend/rotation.
How it works (under the hood)
A “fractal” here is a confirmed pivot: the highest high (or lowest low) with n bars on each side. That means pivots only confirm after n bars, so signals are cleaner and less noisy.
When a new pivot prints, the script connects it to the prior pivot of the same type (high→high, low→low). That gives you one “bearish” line from highs and one “bullish” line from lows.
The newest line is marked as recent (brighter), and the previous recent line becomes historical (dimmed). You can keep as many pairs as you want, but I usually keep it tight.
Inputs you’ll actually use
Fractal Period (n): this is the big one. It controls how swingy/strict the pivots are.
Lower n → more swings, more lines (faster, noisier)
Higher n → fewer swings, cleaner lines (slower, swing-trade friendly)
Max pair of lines: how many pairs (up+down) to keep on the chart. 1–3 is a sweet spot.
Extend: extend lines Right (my default) or Both ways if you like the context.
Line widths & colours: recent vs. historical are separate so you can make the active lines pop.
Show crosses: toggle the X markers when price crosses a line. I turn this on when I’m actively hunting breakouts/retests.
Reading the chart
Red lines (from highs): I treat these as potential resistance. A clean break + hold above a red line often flips me from “fade” to “follow.”
Green lines (from lows): Potential support. Same idea in reverse: break + hold below and I stop buying dips until I see structure reclaim.
HH / LH / HL / LL dots: quick read on structure.
HH/HL bias = uptrend continuation potential
LH/LL bias = downtrend continuation potential
Mixed prints = rotation/chop—tighten risk or wait for clarity.
My H1 guidance (fine-tuning Fractal Period)
If you’re mainly on H1 (my use case), tune like this:
Fast / aggressive: n = 6–8 (lots of signals, good for momentum days; more chop risk)
Balanced (recommended): n = 9–12 (keeps lines meaningful but responsive)
Slow / swing focus: n = 13–21 (filters noise; better for trend days and higher-TF confluence)
Rule of thumb: if you’re getting too many touches and whipsaws, increase n. If you’re late to obvious breaks, decrease n.
How I trade it (example workflow)
Pick your n for the session (H1: start at 9–12).
Mark the recent red & green lines. That’s your immediate structure.
Look for interaction:
Rejections from a line = fade potential back into the range.
Break + close across a line = watch the retest for continuation.
Confirm with context: session bias, HTF structure, and your own tools (VWAP, RSI, volume, FVG/OB, etc.).
Plan the trade: enter on retest or reclaim, stop beyond the line/last swing, target the opposite side or next structure.
Alerts (set and forget)
“New trendline formed” — fires when a new high/low pivot confirms and a fresh line is drawn.
“Upper/lower trendline crossed” — fires when price crosses the most recent red/green line.
Use these to track structure shifts without staring at the screen.
Good to know (honest limitations)
Confirmation lag: pivots need n bars on both sides, so signals arrive after the swing confirms. That’s by design—less noise, fewer fake lines.
Lines update as structure evolves: when a new pivot forms, the previous “recent” line becomes “historical,” and older ones can be removed based on your max setting.
Not an auto trendline crystal ball: it won’t predict which line holds or breaks—it just keeps the most relevant structure clean and up to date.
Final notes
Works on any timeframe; I built it with H1 in mind and scale to H4/D1 by increasing n.
Pairs nicely with session tools and VWAP for intraday, or with supply/demand / FVGs for swing planning.
Risk first: lines are structure, not guarantees. Manage position size and stops as usual.
Not financial advice. Trade your plan. Stay nimble.
Williams Fractals by Sheridan Sadewa modif untuk menggunakan fractal yang ukurannya lebih kecil dan deket
Market Structure: HH/HL/LH/LL (v6, simple)What it does
Labels swing High/Low and classifies structure as HH / HL / LH / LL after confirmation.
Uses confirmed fractals (pivothigh/pivotlow) → no repaint after confirmation (there is a right-bar confirmation delay).
Optional swing connectors (lines), optional plain H/L when structure label is not applicable.
Plots last confirmed High/Low levels as reference.
Alerts when a new HH/HL/LH/LL is formed.
How it works
Swings are detected with ta.pivothigh() / ta.pivotlow() using user-defined left and right.
A pivot is confirmed only after right bars on the right—this is the only delay. Once confirmed, the label does not repaint.
Inputs
Left bars & Right bars – fractal sensitivity.
Connect swings with lines – draw lines between consecutive swings.
Show bullish (HH/HL) / Show bearish (LH/LL) – filter what to display.
Show plain H/L – draw H/L when classification is not HH/HL/LH/LL yet.
Recommended settings
1H–4H: left=2, right=2 (responsive).
1D+: left=3, right=3 (cleaner swing map).
Alerts provided
HH formed – new Higher High confirmed.
HL formed – new Higher Low confirmed.
LH formed – new Lower High confirmed.
LL formed – new Lower Low confirmed.
Use them to automate structure tracking or feed your strategy rules.
Tips
Trend up: a sequence of HH + HL; Trend down: LH + LL.
Combine with VWAP/EMA, liquidity zones, or volume/CVD to avoid chasing late signals.
The script is intentionally simple and lightweight; BOS/CHoCH can be added in a future update.
Limitations / Notes
Because the tool relies on confirmed pivots, signals are delayed by right bars.
This is not financial advice and not a buy/sell system on its own.
Changelog
v1.0 – Initial public release (Pine v6). Structure labels, swing connectors, last levels, and alert set.
Keywords
market structure, hh hl lh ll, swing, fractal, pivothigh, pivotlow, trend, structure labels, price action
Smart RSI Divergence PRO | Auto Lines + Alerts📌 Purpose
This indicator automatically detects Regular and Hidden RSI Divergences between price action and the RSI oscillator.
It plots divergence lines directly on the chart, labels signals, and includes alerts for automated monitoring.
🧠 How It Works
1. RSI Calculation
RSI is calculated using the selected Source (default: Close) and RSI Length (default: 14).
2. Divergence Detection via Fractals
Swing points on both price and RSI are detected using fractal logic (5-bar patterns).
Regular Divergence:
Bearish: Price forms a higher high, RSI forms a lower high.
Bullish: Price forms a lower low, RSI forms a higher low.
Hidden Divergence:
Bearish: Price forms a lower high, RSI forms a higher high.
Bullish: Price forms a higher low, RSI forms a lower low.
3. Auto Drawing Lines
Lines are drawn automatically between divergence points:
Red = Regular Bearish
Green = Regular Bullish
Orange = Hidden Bearish
Blue = Hidden Bullish
Line width and transparency are adjustable.
4. Labels and Alerts
Labels mark divergence points with up/down arrows.
Alerts trigger for each divergence type.
📈 How to Use
Use Regular Divergences to anticipate trend reversals.
Use Hidden Divergences to confirm trend continuation.
Combine with support/resistance, trendlines, or volume for higher probability setups.
Recommended Timeframes: Works on all timeframes; more reliable on 1h, 4h, and Daily.
Markets: Forex, Crypto, Stocks.
⚙️ Inputs
Source (Close, HL2, etc.)
RSI Length
Toggle Regular / Hidden Divergence visibility
Toggle Lines / Labels
Line Width & Line Transparency
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before using in live trading.
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.
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry
A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics
What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets.
The Theoretical Foundation
Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through:
Hurst Exponent Calculation: H = log(R/S) / log(n/2)
Where:
R = Range of cumulative deviations
S = Standard deviation
n = Period length
This measures market memory:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting (anti-persistent) behavior
Fractal Dimension: D = 2 - H
This quantifies market complexity, where higher dimensions indicate more chaotic behavior.
Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences:
Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor
Where:
φ = 0.618 (golden ratio)
Fn = Fibonacci number (8, 13, 21, 34, 55)
Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5
This creates oscillating spirals that contract and expand with market energy.
The Volatility Cascade System
Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands:
Cascade Level Calculation: Level(i) = ATR(20) × φ^i
Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels.
Implementation Architecture
Core Components:
Fractal Analysis Engine
Calculates Hurst exponent over user-defined periods
Derives fractal dimension for complexity measurement
Identifies market regime (trending/ranging/chaotic)
Fibonacci Vortex Generator
Creates 5 independent spiral oscillators
Each spiral follows a Fibonacci period
Volume amplification creates dynamic response
Cascade Band System
Up to 8 volatility levels
Golden ratio expansion between levels
Dynamic coloring based on fractal state
Confluence Detection
Identifies convergence of vortex and cascade levels
Highlights high-probability reversal zones
Real-time confluence strength calculation
Signal Generation Logic
The MFCV generates two primary signal types:
Fractal Signals: Generated when:
Hurst > 0.65 (strong trend) AND volatility expanding
Hurst < 0.35 (mean reversion) AND RSI < 35
Trend strength > 0.4 AND vortex alignment
Cascade Signals: Triggered by:
RSI > 60 AND price > SMA(50) AND bearish vortex
RSI < 40 AND price < SMA(50) AND bullish vortex
Volatility expansion AND trend strength > 0.3
Both signals implement a 15-bar cooldown to prevent overtrading.
Advanced Input System
Mandelbrot Parameters:
Cascade Levels (3-8):
Controls number of volatility bands
Crypto: 5-7 (high volatility)
Indices: 4-5 (moderate volatility)
Forex: 3-4 (low volatility)
Hurst Period (20-200):
Lookback for fractal calculation
Scalping: 20-50
Day Trading: 50-100
Swing Trading: 100-150
Position Trading: 150-200
Cascade Ratio (1.0-3.0):
Band width multiplier
1.618: Golden ratio (default)
Higher values for trending markets
Lower values for ranging markets
Fractal Memory (21-233):
Fibonacci retracement lookback
Uses Fibonacci numbers for harmonic alignment
Fibonacci Vortex Settings:
Spiral Periods:
Comma-separated Fibonacci sequence
Fast: "5,8,13,21,34" (scalping)
Standard: "8,13,21,34,55" (balanced)
Extended: "13,21,34,55,89" (swing)
Rotation Speed (0.1-2.0):
Controls spiral oscillation frequency
0.618: Golden ratio (balanced)
Higher = more signals, more noise
Lower = smoother, fewer signals
Volume Amplification:
Enables dynamic spiral expansion
Essential for stocks and crypto
Disable for forex (no central volume)
Visual System Architecture
Cascade Bands:
Multi-level volatility envelopes
Gradient coloring from primary to secondary theme
Transparency increases with distance from price
Fill between bands shows fractal structure
Vortex Spirals:
5 Fibonacci-period oscillators
Blue above price (bullish pressure)
Red below price (bearish pressure)
Multiple display styles: Lines, Circles, Dots, Cross
Dynamic Fibonacci Levels:
Auto-updating retracement levels
Smart update logic prevents disruption near levels
Distance-based transparency (closer = more visible)
Updates every 50 bars or on volatility spikes
Confluence Zones:
Highlighted boxes where indicators converge
Stronger confluence = stronger support/resistance
Key areas for reversal trades
Professional Dashboard System
Main Fractal Dashboard: Displays real-time:
Hurst Exponent with market state
Fractal Dimension with complexity level
Volatility Cascade status
Vortex rotation impact
Market regime classification
Signal strength percentage
Active indicator levels
Vortex Metrics Panel: Shows:
Individual spiral deviations
Convergence/divergence metrics
Real-time vortex positioning
Fibonacci period performance
Fractal Metrics Display: Tracks:
Dimension D value
Market complexity rating
Self-similarity strength
Trend quality assessment
Theory Guide Panel: Educational reference showing:
Mandelbrot principles
Fibonacci vortex concepts
Dynamic trading suggestions
Trading Applications
Trend Following:
High Hurst (>0.65) indicates strong trends
Follow cascade band direction
Use vortex spirals for entry timing
Exit when Hurst drops below 0.5
Mean Reversion:
Low Hurst (<0.35) signals reversal potential
Trade toward vortex spiral convergence
Use Fibonacci levels as targets
Tighten stops in chaotic regimes
Breakout Trading:
Monitor cascade band compression
Watch for vortex spiral alignment
Volatility expansion confirms breakouts
Use confluence zones for targets
Risk Management:
Position size based on fractal dimension
Wider stops in high complexity markets
Tighter stops when Hurst is extreme
Scale out at Fibonacci levels
Market-Specific Optimization
Cryptocurrency:
Cascade Levels: 5-7
Hurst Period: 50-100
Rotation Speed: 0.786-1.2
Enable volume amplification
Stock Indices:
Cascade Levels: 4-5
Hurst Period: 80-120
Rotation Speed: 0.5-0.786
Moderate cascade ratio
Forex:
Cascade Levels: 3-4
Hurst Period: 100-150
Rotation Speed: 0.382-0.618
Disable volume amplification
Commodities:
Cascade Levels: 4-6
Hurst Period: 60-100
Rotation Speed: 0.5-1.0
Seasonal adjustment consideration
Innovation and Originality
The MFCV represents several breakthrough innovations:
First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory
Unique synthesis of chaos theory and sacred geometry
Novel application of Hurst exponent to spiral dynamics
Dynamic Volatility Cascade System
Golden ratio-based band expansion
Multi-timeframe fractal analysis
Self-adjusting to market conditions
Volume-Amplified Vortex Spirals
Revolutionary spiral calculation method
Dynamic response to market participation
Multiple Fibonacci period integration
Intelligent Signal Generation
Cooldown system prevents overtrading
Multi-factor confirmation required
Regime-aware signal filtering
Professional Analytics Dashboard
Institutional-grade metrics display
Real-time fractal analysis
Educational integration
Development Journey
Creating the MFCV involved overcoming numerous challenges:
Mathematical Complexity: Implementing Hurst exponent calculations efficiently
Visual Clarity: Displaying multiple indicators without cluttering
Performance Optimization: Managing array operations and calculations
Signal Quality: Balancing sensitivity with reliability
User Experience: Making complex theory accessible
The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability.
Best Practices and Guidelines
Start Simple: Use default settings initially
Match Timeframe: Adjust parameters to your trading style
Confirm Signals: Never trade MFCV signals in isolation
Respect Regimes: Adapt strategy to market state
Manage Risk: Use fractal dimension for position sizing
Color Themes
Six professional themes included:
Fractal: Balanced blue/purple palette
Golden: Warm Fibonacci-inspired colors
Plasma: Vibrant modern aesthetics
Cosmic: Dark mode optimized
Matrix: Classic green terminal
Fire: Heat map visualization
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results.
The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose.
Acknowledgments
Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance.
"The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot
Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV.
— Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Current Fractal High/Low (Dynamic)
This indicator dynamically tracks the most recent confirmed Fractal High and Fractal Low across any timeframe using custom left/right bar configurations.
🔍 Key Features:
Detects Fractal Highs and Lows based on user-defined pivot settings.
Draws a green line and label ("FH") at the most recent Fractal High.
Draws a red line and label ("FL") at the most recent Fractal Low.
All lines extend from the confirmation bar to the current candle.
Automatically removes old lines and labels for a clean, uncluttered chart.
🛠️ Customizable Inputs:
Left & Right bars for pivot sensitivity
Line width for visibility
📌 Use Cases:
Identifying structure shifts
Recognizing key swing points
Supporting liquidity and breakout strategies
💡 Fractals are confirmed only after the full formation of the pattern (left and right bars). This ensures reliability over reactivity.
This script is designed for intraday to swing traders who want a reliable way to visualize market turning points with minimal noise.
Stoch_RSI_ChartEnhanced Stochastic RSI Divergence Indicator with VWAP Filter for Charts
This custom indicator builds upon the classic Stochastic RSI to automatically detect both regular and hidden divergences. It’s designed to help traders spot potential market reversals or continuations using two methods for divergence detection (fractal‑ and pivot‑based) while offering optional VWAP filtering for confirmation.
Key Features
Stoch RSI Calculation
The indicator computes a smoothed Stoch RSI using configurable parameters for RSI length, stochastic length, and smoothing periods. An option to average the K and D lines provides a cleaner momentum view.
Divergence Detection via Fractals & Pivots
Fractal-Based Divergences:
Looks for 4-candle patterns to identify higher-highs or lower-lows in the price that are not confirmed by the oscillator, signaling potential reversals.
Pivot-Based Divergences:
Utilizes TradingView’s built-in pivot functions to find divergence conditions over adjustable pivot ranges.
Regular vs. Hidden Divergences:
Regular Divergence: Occurs when price makes a new extreme (higher high or lower low) while the Stoch RSI fails to follow suit.
Hidden Divergence: Indicates potential trend continuations when the oscillator diverges against the established price trend.
Optional VWAP Filtering
The script includes two optional VWAP filters that work as follows:
VWAP Filter on Regular Divergences:
Only confirms regular divergence signals if the current price satisfies the VWAP condition (e.g., price is above VWAP for bullish signals, below VWAP for bearish signals).
VWAP Filter on Hidden Divergences:
Similarly, hidden divergence signals are validated only when the price meets specific VWAP conditions, adding an extra layer of trend confirmation.
Customizable Alerts and Visual Labels
Easily configure divergence labels (“B” for bullish, “S” for bearish) and enable up to four alert conditions for real‑time notifications when a divergence occurs.
Credits & History:
Log RSI by @fskrypt
Divergence Detection originally by @RicardoSantos (with edits from @JustUncleL)
Further Edits by @NeoButane on August 8, 2018
Latest Edits by @FYMD on June 1, 2024
Stoch_RSIStochastic RSI – Advanced Divergence Indicator
This custom indicator is an advanced version of the Stochastic RSI that not only smooths and refines the classic RSI input but also automatically detects both regular and hidden divergences using two powerful methods: fractal-based and pivot-based detection. Originally inspired by contributions from @fskrypt, @RicardoSantos, and later improved by developers like @NeoButane and @FYMD, this script has been fully refined for clarity and ease-of-use.
Key Features:
Dual Divergence Detection:
Fractal-Based Divergence: Uses a four-candle pattern to confirm top and bottom fractals for bullish and bearish divergences.
Pivot-Based Divergence: Employs TradingView’s built-in pivot functions for an alternate view of divergence conditions.
Customizable Settings:
The inputs are organized into logical groups (Stoch RSI settings, Divergence Options, Labels, and Market Open Settings) allowing you to adjust smoothing periods, RSI and Stochastic lengths, and divergence thresholds with a user-friendly interface.
Visual Enhancements:
Plots & Fills: The indicator plots both the K and D lines with corresponding fills and horizontal bands for quick visual reference.
Divergence Markers: Diamond shapes and labeled markers indicate regular and hidden divergences on the chart.
Market Open Highlighting: Optional histogram plots highlight the market open candle based on different timeframes for stocks versus non-forex symbols.
Accumulation-Distribution CandlesThis structural visualization tool maps each candle through the lens of Effort vs. Result, blending Volume, Range, and closing bias into a normalized pressure score. Candle bodies are dynamically color-coded using a five-tier system—from heavy accumulation to heavy distribution—revealing where energy is building, dispersing, or neutral. This helps to visually isolate Markup, Markdown, Re-accumulation, and Distribution at a glance.
The indicator calculates a strength score by multiplying price result (close minus open) by effort (volume or price range), smoothing this raw value using a Fibonacci-based EMA. (34 for standard, 55 for crypto; the higher crypto value acknowledges that 24/7 trading offers more hours per week or month than trad markets.) The result is standardized against its rolling deviation and clamped to a range. This score determines the visual tier:
• 💙 Dark Blue = heavy Accumulation (strong upward result on strong effort)
• 🩵 Pale Blue = mild Accumulation
• 🌚 Gray = neutral (low conviction or balance)
• 💛 Pale Yellow = mild Distribution
• 🧡 Deep Yellow = heavy Distribution (strong downward result on strong effort)
The tool is optimized for the 1D chart, where Wyckoff phases are most clearly expressed. However, it adapts well to lower timeframes when used selectively. Traders may hide the body coloring and enable only zone highlighting to preserve other candle overlays such as SUPeR TReND 2.718, which offers directional clarity and trend duration. This combination is especially useful on intraday charts (15m–1H) where microstructure matters but visual clutter must be avoided.
When used alongside other Volume overlays (such as the OBVX Conviction Bias) or Volatility indicators (such as the Asymmetric Turbulence Ribbon (ATR)), this indicator adds confluence to directional setups by contextualizing pressure with Volatility. For example: compression zones marked by ATR may align with persistent pale blue candles—indicating quiet Accumulation before expansion.
Optional Overlays:
Normally ON -
• 📌 Pin Bars , filtered by volume, to isolate wick-dominant reversals from key zones
• 💪🏻 Strong-Body Candles — fuchsia candles w/ high body-to-range ratio reflect conviction
• 🧯 Wick Absorption Candles — red candles w/ long wicks and low closing strength indicate failed pushes or absorbed breakouts
• 🟦/🟧 Zone Highlighting for candles above a defined Accumulation/Distribution threshold
Normally OFF -
• 🔺 Fractals (5-bar) to map swing pivots by underlying pressure tier (normally OFF)
• 🟥/🟩 Engulfing patterns, filtered by directional conviction (normally OFF)
The Pin Bar strategy benefits most from the zone logic—when a bullish pin bar appears in an Accumulation zone (esp. pale or dark blue), and Volume exceeds its rolling average, it may mark a spring or failed breakdown. Conversely, bearish pins in Distribution zones can mark rejection or resistance.
This is not a signal engine—it’s a narrative filter designed to slot cleanly into a multi-layered workflow of visual structure and informed execution. Use it to identify bias and phase. Then deploy trade triggers from tools like SUPeR TReND 2.718, or the liquidity flows shown the The Silver Lining or the AltSeasonality - MTF indicators, for example. The candle colors tell you who’s in control—the other tools tell you when to act.
