MTF VWAP Resonance [By Testeded]📈 MTF VWAP Resonance Hunter
(多级别 VWAP 共振捕猎者 - 终极版)
🇬🇧 English Description
1. Design Philosophy: The Institutional Edge
While typical indicators measure simple price action, VWAP (Volume Weighted Average Price) measures Value and Institutional Cost.
Professional traders and algorithms anchor their decisions to time-based benchmarks: Daily, Weekly, Monthly, and Quarterly. When prices return to these levels, they are testing the average cost basis of the market participants from that period.
The Logic of "Multi-Level Resonance" (MTF): A single VWAP line can be broken. However, when the Daily VWAP, Weekly Upper Band, and Quarterly Basis all overlap at the exact same price level, a "Market Consensus" is formed. This tool uses a background algorithm to detect these overlaps across 6 Timeframes (4H to Year) and visualizes them as "Resonance Boxes" instead of cluttering your chart with lines.
2. Key Features
⚓ Anchored VWAP Engine: Calculates VWAP + Standard Deviation Bands for 4H, Daily, Weekly, Monthly, Quarterly, and Yearly cycles simultaneously.
⚡ Smart Resonance Radar: Automatically detects when levels from different timeframes cluster together.
2-Line Confluence: ⚡ (Watch)
3-Line Confluence: ⚡⚡ (Strong)
4+ Line Confluence: ⚡⚡⚡ (Iron Wall)
🧘 Visual Modes (Zen / Focus):
Full Mode: Shows lines, dashboard, and resonance boxes.
Focus Mode: Hides lines, keeps dashboard and boxes.
Zen Mode: Hides EVERYTHING except the Resonance Boxes. Pure price action.
🏢 The Quarterly Line: Specifically designed to track the Quarterly VWAP, a critical level for institutional rebalancing and earnings cycles.
🎨 Customizable UI: Adjustable table text size (Small to Huge) and display styles.
3. How to Trade
Identify the Wall: Look for Red Boxes (Resistance) or Green Boxes (Support) with high star ratings (⚡⚡).
Read the Dashboard: Check the label (e.g., Q VWAP + W Lower). This tells you exactly who is defending this level (e.g., "Quarterly Buyers defending cost").
Sniper Entry: Wait for price to touch the Resonance Box. These levels often trigger sharp reversals or major breakouts.
🇨🇳 中文说明 (Chinese Description)
1. 设计哲学：多级别的全局视角
布林带反映的是波动率，而 VWAP（成交量加权平均价） 反映的是**“真金白银的持仓成本”**。
机构交易者和算法通常会锚定特定的时间周期进行交易：日内、周线、月线以及季度线。 “多级别共振”的逻辑： 单一周期的 VWAP 很容易失效。但是，当 日线 VWAP、周线上轨 和 季度线成本 在同一个价格位置重叠时，意味着短线、中线和长线资金在此处达成了**“价值共识”。 本指标通过后台算法，同时监控 6个时间周期 (4H - 年线)，将这些重叠的价位转化为可视化的“共振框”**，提供一个多级别的全局视角。
2. 核心功能
⚓ 全周期锚定 VWAP：后台实时计算 4H, 日线, 周线, 月线, 季度线, 年线 的 VWAP 及其标准差轨道。
⚡ 智能共振雷达：自动检测不同周期的关键位重叠。
2线共振：⚡ (关注)
3线共振：⚡⚡ (强力支撑/阻力)
4线以上：⚡⚡⚡ (核弹级/铁壁共振)
🧘 显示模式 (Zen / Focus)：
全面模式：显示所有线条 + 表格 + 共振框。
专注模式：隐藏线条，保留表格 + 共振框。
极简模式 (Zen)：隐藏一切干扰，只显示共振框。像狙击手一样只看目标。
🏢 季度线增强：特别加入了 Quarterly VWAP (季度线)，这是机构季末调仓和财报周期的重要防守线。
🎨 高度客制化：支持调整表格文字大小（从“小”到“巨大”），适配各种分辨率屏幕。
3. 实战用法
寻找“墙壁”：关注图表上的 红色共振框 (阻力) 或 绿色共振框 (支撑)，尤其是带有 ⚡⚡ 标志的区域。
解读筹码：看一眼右上角的仪表盘标签（例如 Q VWAP + W Lower）。这意味着“季度级别的平均成本”与“周线级别的超卖线”重合，支撑力度极强。
警报交易：开启警报功能。不需要盯着屏幕，当价格撞上共振框时，指标会自动通知你。
지표 및 전략
Dual TF Bearish Divergence (Working)//@version=6
indicator("Dual TF Bearish Divergence (Working)", overlay=true)
// ----------------- SIMPLE BEARISH DIVERGENCE FUNCTION -------------------
bearDiv(src, rsiLen, lookbackMin, lookbackMax) =>
r = ta.rsi(src, rsiLen)
ph = ta.pivothigh(src, lookbackMin, lookbackMin)
ph_rsi = ta.pivothigh(r, lookbackMin, lookbackMin)
ph2 = ph
ph2_rsi = ph_rsi
priceHH = not na(ph) and not na(ph2) and ph > ph2
rsiLH = not na(ph_rsi) and not na(ph2_rsi) and ph_rsi < ph2_rsi
barsOk = lookbackMin >= lookbackMin and lookbackMin <= lookbackMax
priceHH and rsiLH and barsOk
// ----------------- TF CALLS -------------------
b60 = request.security(syminfo.tickerid, "60", bearDiv(close, 14, 10, 15))
b240 = request.security(syminfo.tickerid, "240", bearDiv(close, 14, 10, 15))
dual = b60 and b240
// ----------------- PLOT -------------------
plotshape(dual, title="Dual Bear Div", style=shape.labeldown,
color=color.red, size=size.small, text="🔻BearDiv")
// ----------------- ALERT -------------------
alertcondition(dual, "Dual Bearish Div 60+240",
"Bearish Divergence on both 60m & 240m")
SMC Statistical Liquidity Walls [PhenLabs]📊 SMC Statistical Liquidity Walls
Version: PineScript™ v6
📌 Description
The SMC Statistical Liquidity Walls indicator is designed to visualize market volatility and potential reversal zones using advanced statistical modeling. Unlike traditional Bollinger Bands that use simple lines, this script utilizes an “Inverted Sigmoid” opacity function to create a “fog of war” effect. This visualizes the density of liquidity: the further price moves from the equilibrium (mean), the “harder” the liquidity wall becomes.
This tool solves the problem of over-trading in low-probability areas. By automatically mapping “Premium” (Resistance) and “Discount” (Support) zones based on Standard Deviation (SD), traders can instantly see when price is overextended. The result is a clean, intuitive overlay that helps you identify high-probability mean reversion setups without cluttering your chart with manual drawings.
🚀 Points of Innovation
Inverted Sigmoid Logic: A custom mathematical function maps Standard Deviation to opacity, creating a realistic “wall” density effect rather than linear gradients.
Dynamic “Solidity”: The indicator is transparent at the center (Equilibrium) and becomes visually solid at the edges, mimicking physical resistance.
Separated Directional Bias: distinct Red (Premium) and Green (Discount) coding helps SMC traders instantly recognize expensive vs. cheap pricing.
Smart “Safe” Deviation: Includes fallback logic to handle calculation errors if deviation hits zero, ensuring the indicator never crashes during data gaps.
🔧 Core Components
Basis Calculation: Uses a Simple Moving Average (SMA) to determine the market’s equilibrium point.
Standard Deviation Zones: Calculates 1SD, 2SD, and 3SD levels to define the statistical extremes of price action.
Sigmoid Alpha Calculation: Converts the SD distance into a transparency value (0-100) to drive the visual gradient.
🔥 Key Features
Automated Premium/Discount Zones: Red zones indicate overbought (Premium) areas; Green zones indicate oversold (Discount) areas.
Customizable Density: Users can adjust the “Steepness” and “Midpoint” of the sigmoid curve to control how fast the walls become solid.
Integrated Alerts: Built-in alert conditions trigger when price hits the “Solid” wall (2SD or higher), perfect for automated trading or notifications.
Visual Clarity: The center of the chart remains clear (high transparency) to keep focus on price action where it matters most.
🎨 Visualization
Equilibrium Line: A gray line representing the mean price.
Gradient Fills: The space between bands fills with color that increases in opacity as it moves outward.
Premium Wall: Upper zones fade from transparent red to solid red.
Discount Wall: Lower zones fade from transparent green to solid green.
📖 Usage Guidelines
Range Period: Default 20. Controls the lookback period for the SMA and Standard Deviation calculation.
Source: Default Close. The price data used for calculations.
Center Transparency: Default 100 (Clear). Controls how transparent the middle of the chart is.
Edge Transparency: Default 45 (Solid). Controls the opacity of the outermost liquidity wall.
Wall Steepness: Default 2.5. Adjusts how aggressively the gradient transitions from clear to solid.
Wall Start Point: Default 1.5 SD. The deviation level where the gradient shift begins to accelerate.
✅ Best Use Cases
Mean Reversion Trading: Enter trades when price hits the solid 2SD or 3SD wall and shows rejection wicks.
Take Profit Targets: Use the Equilibrium (Gray Line) as a logical first target for reversal trades.
Trend Filtering: Do not initiate new long positions when price is deep inside the Red (Premium) wall.
⚠️ Limitations
Lagging Nature: As a statistical tool based on Moving Averages, the walls react to past price data and may lag during sudden volatility spikes.
Trending Markets: In strong parabolic trends, price can “ride” the bands for extended periods; mean reversion should be used with caution in these conditions.
💡 What Makes This Unique
Physics-Based Visualization: We treat liquidity as a physical barrier that gets denser the deeper you push, rather than just a static line on a chart.
🔬 How It Works
Step 1: The script calculates the mean (SMA) and the Standard Deviation (SD) of the source price.
Step 2: It defines three zones above and below the mean (1SD, 2SD, 3SD).
Step 3: The custom `get_inverted_sigmoid` function calculates an Alpha (transparency) value based on the SD distance.
Step 4: Plot fills are colored dynamically, creating a seamless gradient that hardens at the extremes to visualize the “Liquidity Wall.”
💡 Note
For best results, combine this indicator with Price Action confirmation (such as pin bars or engulfing candles) when price touches the solid walls.
Signal Algo - Elephant EdgeDescription
Signal Algo - Advance Elephant Edge is a rule-based, intraday detection system that combines candle-pattern logic with session-driven support and resistance zones. creating a clean confluence-based signal that removes noise.
This tool is designed for traders who prefer structured rules over subjective drawing, and want clear, event-driven alerts without unrealistic promises or over-optimized behavior.
What This Script Does (Short & Simple)
1. Hammer-Type Candle Detection
The script looks for long-wick hammer or inverted hammer candles using your wick-ratio setting. It also checks candle size, body size, and doji conditions so that only clean and meaningful rejection candles are highlighted.
2. Session-Based Percentile Support & Resistance
The indicator calculates percentile levels from previous sessions and plots up to four upper and lower S/R lines around the daily open. These levels act as dynamic zones where price often reacts.
3. Optional Strike-Price Zones
For symbols that move around round numbers or strike intervals, the script can draw strike-based S/R lines (like 50 or 100 points) You can choose solid or dotted lines and select how many zones to show.
4.Higher-Timeframe Trend Background
A light green or red background shows the overall trend direction. Green = bullish bias, Red = bearish bias.
🔶 USAGE & EXAMPLES Elephant Support & Resistance
Elephant Support & Resistance creates intraday support and resistance levels using percentile data from previous sessions. Instead of drawing lines manually, calculates how far price usually moves above and below previous sessions. and then plots those levels automatically.
Each percentile pair (Level 1–4) gives one upper line and one lower line. These lines represent price zones where the market has reacted many times in the past. When price reaches these levels, it often pauses, reverses, or shows rejection candles.
🔶USAGE & EXAMPLES Strike Price Support & Resistance
Strike Price Zones are plotted because most markets naturally react around fixed strike levels. Every index, stock, or international market has its own commonly traded strike prices. These levels attract large traders and institutions, who often build positions around them.
When price moves toward one of these strike levels, big players frequently defend or reject that zone. As a result, price may pause, reverse, or show strong reactions at or near these strikes.
Because of this behavior, Strike Price Zones work as practical intraday support and resistance levels. They help traders see where important reactions can occur, where momentum may slow down, and where potential reversals may form.
These zones are not buy/sell signals by themselves, but they provide a simple, objective roadmap of key levels that the market respects during the session.
🔷 FEATURES
1. Hammer-Based Rejection Signals
2. Candle Size Filtering
3. Elephant Percentile Support & Resistance
4. Strike Price Support & Resistance Zones
5. Combined Confluence Logic
6. Higher-Timeframe Trend Background
7. Clean Visual Layout
8. Yellow Highlight Candle
9. Intraday Session Handling
10. Built-In Alerts
11. Fully Customizable Inputs
12. Lightweight & Rule-Driven Design
🔴 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by Signal Algo are purely for informational & educational purposes only. Past performance does not guarantee future results.
RSI Golden & Dead Cross AlertRSI 14 Golden And Dead Cross Indicator
It will give you an alert when there are rsi golden and dead cross.
It is a intergated signal: Crossing up and Crossing down of RSI.
HTF OHLC Candle + 50% @MaxMaserati 3.0HTF OHLC Candle + 50% MaxMaserati 3.0
This powerful, all-in-one indicator allows traders to visualize the Open, High, Low, Close (OHLC) structure and the critical 50% Midpoint (Equilibrium) of up to four different Higher Timeframes (HTFs) directly overlaid onto the current chart. Stop switching timeframes and start seeing the complete market structure at a glance!
✨ Core Features & Trader Benefits
1. 🌐 Comprehensive Multi-Timeframe Context
Visualize the past and present candle structure of four independently configurable timeframes (TF1, TF2, TF3, TF4). This eliminates manual charting and provides an immediate understanding of macro market ranges and directional bias.
TF1 OHLC LIVE: Focuses on the current, forming candle of a major timeframe (e.g., the current Daily candle) to show where price is trending relative to its open and range.
TF2-TF4 OHLC Boxes:Display both the closed historical candles (up to 10 previous boxes) and the current, forming candle for deep structural reference.
2. 🎯 Critical Level Projection (OHLC & 50%)
The indicator automatically projects and extends key price levels from each higher timeframe candle across your current chart, making them highly visible reference points.
|High (H) / Low (L): Marks the full structural range (wick to wick).
Open (O) / Close (C): Defines the body and the direction of the candle. Price magnet targets and momentum entry/retests.
50% Midpoint: The Equilibrium of the candle's range. Optimal Trade Entry (OTE) zones, potential support/resistance, and fair value flip points.
3. 🎨 Advanced Customization & Aesthetics
Every element of the indicator is highly customizable to match your preferred trading style and chart theme:
Custom Color Schemes: Independently set Bullish and Bearish body/wick colors for each of the four timeframes.
Aesthetic Clarity: Configure the size and placement of Timeframe Labels (e.g., "H4 50%") on the extended lines to maintain visual organization.
Line Styling: Adjust the color, transparency, and thickness for every individual level (Open, High, Low, 50%) across all four timeframes.
4. 🧹 Chart Management
With controls for `Max Boxes` and separate toggles for showing the current vs. closed OHLC lines, you can prevent chart clutter and focus only on the structural context relevant to your strategy.
SPY SRX S&R Levels - Premium EditionSRX SPY Predictive Support & Resistance Levels
SRX is not a typical TradingView support/resistance indicator.
These levels are not calculated on TradingView at all . Instead, every morning after market open, nearly 20,000 data points are analyzed externally to determine where SPY is statistically most likely to react.
This produces support and resistance levels that are hyper-accurate, mathematically derived, and consistently respected intraday , not hand-drawn guesses or generic indicator outputs.
On top of that, SRX plots dynamic volatility-based zones around each major level so you can catch moves that don’t hit the level penny-perfect.
SRX also generates Buy/Sell Arrows during trending conditions and Buy/Sell Circles during non-trending or early-trend conditions.
Arrows = higher-probability trend-aligned setups.
Circles = lower-confidence ideas that can often be scalped on 1m–3m charts.
This tool is built for traders who want clarity, precision, and the ability to anticipate key reactions on SPY with confidence.
Features:
Externally Calculated SRX Levels: Nearly 20,000 data points analyzed daily to produce statistically significant support & resistance levels.
Dynamic Volatility Zones: Capture moves that don’t hit levels perfectly with automatically adjusting upper/lower zones.
Expected Daily Range: Session high/low projections based on historical and current volatility.
Support Levels (S1–S4): Up to four graduated support zones for precision planning.
Resistance Levels (R1–R4): Up to four graduated resistance zones built from the same predictive model.
Premarket High/Low (PMH/PML): Toggleable levels from premarket session.
Previous Day High/Low (PDH/PDL): Quickly mark the prior day’s key reaction points.
Previous Day Open/Close (PDO/PDC): Additional contextual levels (toggle on/off).
Buy/Sell Arrows: Trigger when price interacts with both the EMA and an SRX level/zone in trending conditions.
Buy/Sell Circles: Trigger in non-trending environments — lower confidence but often scalp-friendly.
EMA Overlay: Adjustable EMA used for signal confirmation (default length 8).
Runway Filter: Optional filter that improves signal quality by measuring available “runway” before the next SRX level.
Near EMA Touch Logic: Helps detect momentum shifts and avoid false signals.
Bias Filter: Determines whether the market is trending up, trending down, or neutral — off by default but extremely powerful.
Historical Data Section: View previous SRX levels for backtesting and strategy review.
Customizable Appearance: Colors, transparency, labels, arrows, zone styling and more.
Built-In Alerts:
Zone/Level Touch or Cross
PMH/PML Touch or Cross
PDH/PDL Touch or Cross
PDO/PDC Touch or Cross
Max-Range High/Low Reached
Buy/Sell Arrow Signals
How to Use:
Copy the daily SRX data string from the official Discord channel.
Paste it into the “SRX Levels Input” field inside the indicator settings.
Customize colors, zones, EMA, signals, and filters to match your trading style.
Use SRX support/resistance levels as the foundation for intraday setups.
Use Arrows when the market is trending and the bias is clear.
Use Circles cautiously during choppy or unconfirmed conditions (often great for scalp entries on 1m/3m).
Optionally enable alerts for level reactions or signal prints.
Ideal For:
Intraday traders who rely on precise support/resistance
SPY scalpers seeking high-probability reaction zones
Momentum traders catching breakouts or bounces
Traders who want statistical structure, not subjective drawings
Important Notes:
SRX levels are calculated externally using proprietary models.
This indicator requires a paid subscription to access the daily SRX support/resistance data.
Daily levels are delivered through our private Discord.
Without the SRX daily data string, the indicator will not display levels.
You can join here to get access to the SRX Levels feed:
stockalertsreviewed.clickfunnels.com
SRX currently works exclusively with SPY (as of Dec 2025). We plan to expand to additional tickers in 2026.
Buy/Sell signals are trade ideas — always confirm with market context.
Discipline Box Trader — by chaitu50cDiscipline Box Trader — by chaitu50c is a rule-based price action tool built around alternating candle structures.
For each session, the indicator detects FIRST key alternating zone, marks it as a gray “Discipline Box”, and then tracks how price breaks and rotates through that zone with clear green/red segments.
The idea is simple:
The script continuously looks for alternating candle sequences:
Red → Green → Red → Green …
or
Green → Red → Green → Red …
When the sequence reaches your minimum required length (Min candles in alternate combo), it:
Finds the highest high and lowest low of that entire alternation combo.
Draws a gray rectangular box from the start of the combo to its end.
This gray region is named the “Discipline Box”.
After this Discipline Box is created:
Upside breakout → close > box high
Downside breakout → close < box low
For example if, Upside Breakout → Green Regime Segment
The gray box is visually closed at the previous bar.
A new green box segment starts from the breakout bar.
Box fill, border, and center line all turn green.
This green segment extends to the right until another breakout flips the regime.
There is a small visible gap between the gray box and the new coloured segment, clearly showing where the breakout actually occurred.
Within the same session, price may:
Break up → green segment.
Later break down through the same band → red segment.
Possibly flip again.
All of this happens inside the one original Discipline Box, giving a clean visual map of who is in control now without creating new zones.
Reset Mode
None
No automatic reset; box can persist across all data.
New Day
At each new trading day:
Current box and center line are closed.
All internal counters reset.
A completely fresh Discipline Box can form for the new day.
Gap Minutes
If time between candles exceeds Gap Threshold (minutes):
Treat this as a session break.
Close the current box and restart detection after the gap.
This ensures clarity and separation between sessions and prevents overlapping “old” structure from dominating new market conditions.
Trading Framework: 2 Trades per Discipline Box
⚠️ This is not financial advice. This is a structured usage idea to support discipline.
A suggested trading framework to pair with this indicator:
Trade 1 — First Breakout Trade
Wait for the first body-based breakout from the Discipline Box:
Upside breakout → consider a single long trade.
Downside breakout → consider a single short trade.
Use the box high, low, and midline as reference points for:
Stop placement, partial exits, or risk-reward zones.
Trade 2 — Opposite Regime Flip
If price later breaks the opposite side of the same box:
Consider exactly one more trade in the new direction (a failed breakout / reversal play).
Example: green regime first, later broken down into red → potential short trade.
After these maximum 2 trades per Discipline Box, you can:
Skip additional trades inside that session’s structure.
Wait patiently for the next session and next Discipline Box to form.
This hard rule helps avoid over-trading, revenge trades, and emotional interference — staying faithful to the “Discipline” theme.
The indicator has a built-in alert condition: Discipline Box Detected
Triggers Whenever a new gray Discipline Box is created (i.e., the first valid alternation zone for that session).
Practical Notes & Disclaimer
The indicator does not tell you when to buy or sell; it simply:
Marks a disciplined structure zone.
Shows live regime shifts (green/red).
Supports a clear “max 2 trades per box” framework.
Use on a demo first, adapt to your style, and always remember:
Your discipline matters more than the indicator.
VB-MainLiteVB-MainLite – v1.0 Initial Release
Overview
VB-MainLite is a consolidated market-structure and execution framework designed to streamline decision-making into a single chart-level view. The script combines multi-timeframe trend, volatility, volume, and liquidity signals into one cohesive visual layer, reducing indicator clutter while preserving depth of information for active traders.
Core Architecture
Trend Backbone – EMA 200
Dedicated EMA 200 acts as the primary trend filter and higher-timeframe bias reference.
Serves as the “spine” of the system for contextualizing all secondary signals (swings, reversals, volume events, etc.).
Custom MA Suite (Envelope Ready)
Four configurable moving averages with flexible source, length, and smoothing.
Default configuration (preset idea: “8/89 Envelope”):
MA #1: EMA 8 on high
MA #2: EMA 8 on low
MA #3: EMA 89 on high
MA #4: EMA 89 on low
All four are disabled by default to keep the chart minimal. Users can toggle them on from the Custom MAs group for envelope or cloud-style configurations.
Nadaraya–Watson Smoother (Swing Framework)
Gaussian-kernel Nadaraya–Watson regression applied to price (hl2) to build a smooth synthetic curve.
Two layers of functionality:
Swing labels (▲ / ▼) at inflection points in the smoothed curve.
Optional curve line that visually tracks the turning structure over the last ~500 bars.
Designed to surface early swing potential before standard MAs react.
Hull Moving Average (Trend Overlay)
Optional Hull MA (HMA) for faster trend visualization.
Color-coded by slope (buy/sell bias).
Default: off to prevent overloading the chart; can be enabled under Hull MA settings.
Momentum, Exhaustion & Pattern Engine
CCI-Based Bar Coloring
CCI applied to close with configurable thresholds.
Overbought / oversold CCI zones map directly into candle coloring to visually highlight short-term momentum extremes.
RSI Top / Bottom Exhaustion Finder
RSI logic applied separately to high-driven (tops) and low-driven (bottoms) sequences.
Plots:
Top arrows where high-side RSI stretches into high-risk territory.
Bottom arrows where low-side RSI indicates exhaustion on the downside.
Useful as confluence around the Nadaraya swing turns and EMA 200 regime.
Engulfing + MA Trend Engine (“Fat Bull / Fat Bear”)
Detects bullish and bearish engulfing patterns, then combines them with MA trend cross logic.
Only when both pattern and MA regime align does the engine flag:
Fat Bull (Engulf + MA aligned long)
Fat Bear (Engulf + MA aligned short)
Candles are marked via conditional barcolor to highlight strong, structured shifts in control.
Fat Finger Detection (Wick Spikes / Stop Runs)
Identifies abnormal wick extensions relative to the prior bar’s body range with configurable tolerance.
Supports detection of potential liquidity grabs, stop runs, or “excess” that may precede reversals or mean-reversion behavior.
Volume & Liquidity Intelligence
Bull Snort (Aggressive Buy Spikes)
Flags events where:
Volume is significantly above the 50-period average, and
Price closes in the upper portion of the bar and above prior close.
Plots a labeled marker below the bar to indicate aggressive upside initiative by buyers.
Pocket Pivots (Accumulation Flags)
Compares current volume vs prior 10 sessions with a filter on prior “up” days.
Highlights pocket pivot days where current green candle volume outclasses recent down-day volumes, suggesting stealth accumulation.
Delta Volume Core (Directional Volume by Price)
Internal volume-by-price style engine over a user-defined lookback.
Splits volume into up-close and down-close buckets across dynamic price bins.
Feeds into S&R and ICT zone logic to quantify where buying vs selling pressure built up.
Structural Context: S&R and ICT Zones
S&R Power Channel
Computes local high/low band over a configurable lookback window.
Renders:
Upper and lower S&R channel lines.
Shaded support / resistance zones using boxes.
Adds Buy Power / Sell Power metrics based on the ratio of up vs down bars inside the window, displayed directly in the zone overlays.
Drops ◈ markers where price interacts dynamically with the top or bottom band, highlighting reaction points.
ICT-Style Premium / Discount & Macro Zones
Two tiered structures:
Local Premium / Discount zones over a shorter SR window.
Macro Premium / Discount zones over a longer macro window.
Each zone:
Uses underlying directional volume to annotate accumulation vs distribution bias.
Provides Delta Volume Bias shading in the mid-band region, visually encoding whether local power flows are net-buying or net-selling.
Enables traders to quickly see whether current trade location is in a local/macro discount or premium context while still respecting volume profile.
Positioning Intelligence: PCD (Stocks)
Position Cost Distribution (PCD) – Stocks Only
Available for stock symbols on intraday up to daily timeframe (≤ 1D).
Uses:
TOTAL_SHARES_OUTSTANDING fundamentals,
Daily OHLCV snapshot, and
A bucketed distribution engine
to approximate cost basis distribution across price.
Outputs:
Horizontal “PCD bars” to the right of current price, density-scaled by estimated share concentration.
Color-coding by profitability relative to current price (profitable vs unprofitable positions).
Labels for:
Current price
Average cost
Profit ratio (share % below current price)
90% cost range
70% cost range
Range overlap as a measure of clustering / concentration.
Multi-Timeframe Trend: Two-Pole Gaussian Dashboard
Two-Pole Gaussian Filter (Line + Cloud)
Smooths a user-selected source (default: close) using a two-pole Gaussian filter with tunable alpha.
Plots:
A thin Gaussian trend line, and
A thick Gaussian “cloud” line with transparency, colored by slope vs past (offsetG).
Functions as a responsive trend backbone that is more sensitive than EMA 200 but less noisy than raw price.
Multi-Timeframe Gaussian Dashboard
Evaluates Gaussian trend direction across up to six timeframes (e.g., 1H / 2H / 4H / Daily / Weekly).
Renders a compact bottom-right table:
Header: symbol + overall bias arrow (up / down) based on average trend alignment.
Row of colored cells per timeframe (green for uptrend, magenta for downtrend) with human-readable TF labels (e.g., “60M”, “4H”, “1D”).
Gives an immediate read on whether intraday, swing, and higher-timeframe flows are aligned or fragmented.
Default Configuration & Usage Guidance
Default state after adding the script:
Enabled by default:
EMA 200 trend backbone
Nadaraya–Watson swing labels and curve
CCI bar coloring
RSI top/bottom arrows
Fat Bull / Fat Bear engine
Bull Snort & Pocket Pivots
S&R Power Channel
ICT Local + Macro zones
Two-pole Gaussian line + cloud + dashboard
PCD engine for stocks (auto-active where data is available)
Disabled by default (opt-in):
Custom MA suite (4x MAs, preset as EMA 8/8/89/89)
Hull MA overlay
How traders can use VB-MainLite in practice:
Use EMA 200 + Gaussian dashboard to define top-down directional bias and avoid trading directly against multi-TF trend.
Use Nadaraya swing labels, RSI exhaustion arrows, and CCI bar colors to time entries within that higher-timeframe bias.
Use Fat Bull / Fat Bear events as structured confirmation that both pattern and MA regime have flipped in the same direction.
Use Bull Snort, Pocket Pivots, and S&R / ICT zones to align execution with liquidity, volume, and location (premium vs discount).
On stocks, use PCD as a positioning map to understand trapped supply, support zones near crowded cost basis, and where profit-taking is likely.
HW XAU Capital Booster v4 – UltraClean LLR SystemHW XAU Capital Booster v4 是專為黃金 XAUUSD 設計的多因子交易系統。
包含 UltraClean LLR、趨勢強度、動能/波動/量能濾網、訊號強度與 SOP + Summary 決策面板。
如需啟用 VIP 進階版本，請透過 TradingView 私訊聯繫作者。
HW XAU Capital Booster v4 is a multi-factor trading system designed for XAUUSD.
Includes UltraClean LLR breakout detection, trend strength, momentum/volume/volatility filters, signal ranking, SOP workflow, and Summary final verdict.
For VIP activation and full features, contact the author via TradingView DM.
PurpleAlgo: Execution ModuleThis indicator is based on the Smart Money Concept. It analyzes price and volume data to identify the current trend direction.
BTC / XAU Calculator/Hesaplayıcı
USER GUIDE
BTC/XAU Calculator is a table-based indicator that displays Bitcoin price, Gold price (XAU/USD), and the BTC/XAU ratio simultaneously. It pulls real-time market data and calculates values based on your manual inputs.
⸻
Features
• Automatically fetches live BTCUSD and XAUUSD prices.
• Supports two-way manual calculations:
• BTC price → Ratio calculation
• Ratio → BTC price calculation
• Clear table layout showing Market vs Calculated values.
• Compatible with Binance, OANDA, and all brokers.
⸻
1. Settings
Gold Price (XAU/USD)
• When “Use live XAU price” is enabled, the indicator uses real-time XAU/USD.
• If disabled, you can enter your own gold price manually.
⸻
2. Calculation Modes
A) Calculate BTC from Ratio
BTC = Ratio × Gold price
Example:
XAU = 4200
Ratio = 19.08
→ BTC = 4200 × 19.08 = 80,136 USD
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B) Calculate Ratio from BTC
Ratio = BTC price ÷ Gold price
Example:
BTC = 90,000
XAU = 4250
→ Ratio = 90,000 / 4,250 = 21.18
3. Suggested Uses
• Evaluate BTC as cheap/expensive relative to gold
• BTC target projections based on gold
• Macro hedge and correlation analysis
• BTC/XAU ratio-based scenario modeling
⸻
Notes
• This indicator does not generate trading signals.
• It is intended for numerical comparison and scenario building only.
Source: The design and calculation logic of this indicator were created in collaboration with OpenAI’s ChatGPT model.
ATR Based Stoploss LineThis indicator dynamically plots a horizontal stop-loss level using an RMA-based Average True Range (ATR). The stop value is calculated from the current closing price minus ATR (with optional multiplier) to provide a systematic risk reference during active price movement. A fixed line extends across recent bars for clear visualization, with the stop-loss price displayed at the midpoint of that line for intuitive charting. This tool should be strictly used for breakout environments, aligned with your risk management protocol, and always confirmed with volume analysis before execution. The intent is to drive disciplined entries, strengthen downside protection, and support robust trade management in volatile market conditions.
XAUUSD ULTIMATE+BB 🥇 [GOLD OPTIMIZED]🥇 XAUUSD ULTIMATE 100% - Best Gold Indicator
The most complete trading system for GOLD (XAUUSD) - 20+ indicators in ONE tool!
🔥 WHAT YOU GET:
✅ COMPLETE TRADING SYSTEM
- Buy/Sell signals with 0-100% confidence score
- Automatic SL/TP levels (optimized for gold)
- Real-time profit tracking in $ and %
- Clean visual interface with live dashboard
✅ POWERFUL FEATURES
- 📊 Bollinger Bands - Full visualization
- 📈 SuperTrend - Dynamic trend line
- 🎯 Divergence Detection - Early reversals
- 🕯️ Candlestick Patterns - Hammer, Engulfing, etc
- 💎 Order Blocks - Smart Money levels
- 🕐 Session Lines - London/NY high volatility periods
✅ SMART SIGNAL SYSTEM
- Multi-indicator confirmation (EMAs, RSI, MACD, Stochastic, ADX)
- Fast Entry Mode - Catches early moves
- Aggressive Mode - More signals
- Volume confirmation included
- Psychological levels ($50 increments)
✅ EASY TO USE
1. Add to XAUUSD chart
2. Adjust sensitivity (1-10)
3. Wait for BUY/SELL arrows
4. Follow displayed SL/TP levels
✅ ALERTS INCLUDED
- Buy/Sell signals
- Divergence alerts
- Profit targets (0.15%, 0.30%)
- Bollinger Band extremes
🎯 BEST FOR:
- Gold scalping (M5-M15)
- Day trading (M15-H1)
- All experience levels
⚙️ FULLY CUSTOMIZABLE
- Adjustable sensitivity
- Show/hide any feature
- Custom SL/TP multipliers
- Choose your trading style
💡 WHY IT'S THE BEST:
- Gold-specific optimization
- 20+ indicators working together
- Professional-grade accuracy
- Clean, easy-to-read interface
- Works in all market conditions
Nova Trades | Opening Range IndicatorNova Trades | Opening Range With Confluences
Overview
The Nova Trades ORB Simple indicator is a clean, educational implementation of Opening Range Breakout (ORB) methodology combined with Exponential Moving Average (EMA) trend filtering. This script is designed to help traders visualize market structure during the critical opening session and identify high-probability breakout opportunities.
What Makes This Implementation Unique
1. Real-Time Dynamic ORB Tracking
Unlike static ORB indicators that plot fixed levels, this script:
Updates ORB high/low levels in real-time during the opening range period
Dynamically adjusts line positions as new highs/lows form within the ORB window
Uses line.set_y1() and line.set_y2() to provide smooth, live updates without cluttering the chart
Automatically extends ORB levels into the future for easy visual reference
2. Integrated Status Dashboard
The script includes a comprehensive real-time status table that shows:
Current ORB period status (ACTIVE vs COMPLETE)
Calculated ORB range size (useful for volatility assessment)
Current price position relative to ORB levels (ABOVE/BELOW/INSIDE)
Price position relative to EMA (trend context)
First breakout direction detection (BULLISH/BEARISH/PENDING)
This dashboard eliminates the need to manually assess market conditions and provides instant decision-making information.
3. Breakout Detection Logic
The script employs a first-breakout-only tracking system that:
Waits for the ORB period to complete before flagging breakouts
Records only the first directional break after ORB completion
Prevents false signals from intraday price whipsaws
Maintains breakout status throughout the trading session for consistency
4. EMA Confluence Filter
While many ORB scripts exist and EMA is a standard indicator, this script's value lies in how they work together:
Trading Edge: The combination provides a two-factor confirmation system:
ORB Breakout = Short-term momentum shift (microstructure)
EMA Position = Intermediate trend alignment (macrostructure)
Why This Matters:
ORB breakouts above ORB high + price above EMA = Aligned bullish momentum (highest probability long setups)
ORB breakouts below ORB low + price below EMA = Aligned bearish momentum (highest probability short setups)
Conflicting signals (e.g., ORB breakout up but price below EMA) = Lower probability, potential reversal zones
5. Customizable Time Periods
Supports multiple ORB timeframes (5m, 15m, 30m, 45m, 60m) because:
Different securities have different volatility profiles
Intraday traders may prefer shorter ORB periods (5-15m)
Position traders may prefer longer ORB periods (45-60m)
Allows optimization for specific trading styles and instruments
6. Clean Visual Design
Market open line clearly marks session start
Color-coded ORB levels (customizable) for instant visual recognition
Minimal chart clutter with toggle options for each component
Data window plots for programmatic strategy access
How It Works
Opening Range Breakout (ORB) Calculation
Initialization: At 9:30 AM NY time (market open), the script begins tracking
Range Formation: During the selected timeframe (default 30 minutes):
Continuously updates the highest high → ORB High
Continuously updates the lowest low → ORB Low
Range Completion: After the ORB period ends, levels are locked
Breakout Detection: Price breaking above ORB High (bullish) or below ORB Low (bearish) triggers the breakout flag
EMA Trend Filter
Calculates exponential moving average (default 50-period, customizable 1-500)
Provides trend context: Price > EMA = uptrend, Price < EMA = downtrend
Acts as dynamic support/resistance level
Combined Strategy Logic
Why Open Source?
This script is published as open source to:
Provide educational value to the trading community
Demonstrate clean coding practices for ORB implementations
Allow traders to customize and adapt to their specific needs
Serve as a foundation for more complex strategy development
The code uses standard Pine Script functions (ta.ema(), line.new(), table.new()) intentionally to maintain transparency and educational value.
Disclaimer
This indicator is for educational and informational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always practice proper risk management.
Custom MTF VWAP 5x This is a combination of all VWAPs I use to find high probability trade setups and targets by only taking trades when different VWAPs align
SMC & ICTSMC & ICT Concepts
Key Features:
• Real-time Market Structure: MSS (Market Structure Shift), BOS, CHOCH with labels
• Order Blocks (Bullish & Bearish) – auto-mitigation & breaker detection
• Fair Value Gaps (FVG), Implied FVG, Balance Price Range (BPR)
• Liquidity Grabs (Buyside/Sellside pools from equal highs/lows)
• Volume Imbalance (VI) detection
• Displacement candles
• Killzones: New York, London Open/Close, Asian session background highlight
• NWOG (New Week Opening Gap) & NDOG (New Day Opening Gap)
• Automatic Fibonacci Retracement & Extension between latest FVG, OB, Liquidity, or VI
• Two display modes:
→ Present Mode: Shows only recent & relevant structures (clean chart – recommended for live trading)
→ Historical Mode: Shows full structure history
Perfect confluence tool for scalping, day trading, and swing trading.
Hierarchical Hidden Markov ModelHierarchical Hidden Markov Models (HHMMs) are an advanced version of standard Hidden Markov Models (HMMs). While HMMs model systems with a single layer of hidden states, each transitioning to other states based on fixed probabilities, HHMMs introduce multiple layers of hidden states. This hierarchical structure allows for more complex and nuanced modeling of systems, making HHMMs particularly useful in representing systems with nested states or regimes. In HHMMs, the hidden states are organized into levels, where each state at a higher level is defined by a set of states at a lower level. This nesting of states enables the model to capture longer-term dependencies in the time series, as each state at a higher level can represent a broader regime, and the states within it can represent finer sub-regimes. For example, in financial markets, a high-level state might represent a general market condition like high volatility, while the nested lower-level states could represent more specific conditions such as trending or oscillating within the high volatility regime.
The hierarchical nature of HHMMs is facilitated through the concept of termination probabilities. A termination probability is the probability that a given state will stop emitting observations and transition control back to its parent state. This mechanism allows the model to dynamically switch between different levels of the hierarchy, thereby modeling the nested structure effectively. Beside the transition, emission and initial probabilities that generally define a HMM, termination probabilities distinguish HHMMs from HMMs because they define when the process in a sub-state concludes, allowing the model to transition back to the higher-level state and potentially move to a different branch of the hierarchy.
In financial markets, HHMMs can be applied similiarly to HMMs to model latent market regimes such as high volatility, low volatility, or neutral, along with their respective sub-regimes. By identifying the most likely market regime and sub-regime, traders and analysts can make informed decisions based on a more granular probabilistic assessment of market conditions. For instance, during a high volatility regime, the model might detect sub-regimes that indicate different types of price movements, helping traders to adapt their strategies accordingly.
MODEL FIT:
By default, the indicator displays the posterior probabilities, which represent the likelihood that the market is in a specific hidden state at any given time, based on the observed data and the model fit. These posterior probabilities strictly represent the model fit, reflecting how well the model explains the historical data it was trained on. This model fit is inherently different from out-of-sample predictions, which are generated using data that was not included in the training process. The posterior probabilities from the model fit provide a probabilistic assessment of the state the market was in at a particular time based on the data that came before and after it in the training sequence. Out-of-sample predictions, on the other hand, offer a forward-looking evaluation to test the model's predictive capability.
MODEL TESTING:
When the "Test Out of Sample" option is enabled, the indicator plots the selected display settings based on models' out-of-sample predictions. The display settings for out-of-sample testing include several options:
State Probability option displays the probability of each state at a given time for segments of data points not included in the training process. This is particularly useful for real-time identification of market regimes, ensuring that the model's predictive capability is tested on unseen data. These probabilities are calculated using the forward algorithm, which efficiently computes the likelihood of the observed sequence given the model parameters. Higher probabilities for a particular state suggest that the market is currently in that state. Traders can use this information to adjust their strategies according to the identified market regime and their statistical features.
Confidence Interval Bands option plots the upper, lower, and median confidence interval bands for predicted values. These bands provide a range within which future values are expected to lie with a certain confidence level. The width of the interval is determined by the current probability of different states in the model and the distribution of data within these states. The confidence level can be specified in the Confidence Interval setting.
Omega Ratio option displays a risk-adjusted performance measure that offers a more comprehensive view of potential returns compared to traditional metrics like the Sharpe ratio. It takes into account all moments of the returns distribution, providing a nuanced perspective on the risk-return tradeoff in the context of the HHMM's identified market regimes. The minimum acceptable return (MAR) used for the calculation of the omega can be specified in the settings of the indicator. The plot displays both the current Omega ratio and a forecasted "N day Omega" ratio. A higher Omega ratio suggests better risk-adjusted performance, essentially comparing the probability of gains versus the probability of losses relative to the minimum acceptable return. The Omega ratio plot is color-coded, green indicates that the long-term forecasted Omega is higher than the current Omega (suggesting improving risk-adjusted returns over time), while red indicates the opposite. Traders can use omega ratio to assess the risk-adjusted forecast of the model, under current market conditions with a specific target return requirement (MAR). By leveraging the HHMM's ability to identify different market states, the Omega ratio provides a forward-looking risk assessment tool, helping traders make more informed decisions about position sizing, risk management, and strategy selection.
Model Complexity option shows the complexity of the model, as well as complexity of individual states if the “complexity components” option is enabled. Model complexity is measured in terms of the entropy expressed through transition probabilities. The used complexity metric can be related to the models entropy rate and is calculated as the sum of the p*log(p) for every transition probability of a given state. Complexity in this context informs us on how complex the models transitions are. A model that might transition between states more often would be characterised by higher complexity, while a model that tends to transition less often would have lower complexity. High complexity can also suggest the model captures noise rather than the underlying market structure also known as overfitting, whereas lower complexity might indicate underfitting, where the model is too simplistic to capture important market dynamics. It is useful to assess the stability of the model complexity as well as understand where changes come from when a shift happens. A model with irregular complexity values can be strong sign of overfitting, as it suggests that the process that the model is capturing changes siginficantly over time.
Akaike/Bayesian Information Criterion option plots the AIC or BIC values for the model on both the training and out-of-sample data. These criteria are used for model selection, helping to balance model fit and complexity, as they take into account both the goodness of fit (likelihood) and the number of parameters in the model. The metric therefore provides a value we can use to compare different models with different number of parameters. Lower values generally indicate a better model. AIC is considered more liberal while BIC is considered a more conservative criterion which penalizes the likelihood more. Beside comparing different models, we can also assess how much the AIC and BIC differ between the training sets and test sets. A test set metric, which is consistently significantly higher than the training set metric can point to a drift in the models parameters, a strong drift of model parameters might again indicate overfitting or underfitting the sampled data.
Indicator settings:
- Source : Data source which is used to fit the model
- Training Period : Adjust based on the amount of historical data available. Longer periods can capture more trends but might be computationally intensive.
- EM Iterations : Balance between computational efficiency and model fit. More iterations can improve the model but at the cost of speed.
- Test Out of Sample : turn on predict the test data out of sample, based on the model that is retrained every N bars
- Out of Sample Display: A selection of metrics to evaluate out of sample. Pick among State probability, confidence interval, model complexity and AIC/BIC.
- Test Model on N Bars : set the number of bars we perform out of sample testing on.
- Retrain Model on N Bars: Set based on how often you want to retrain the model when testing out of sample segments
- Confidence Interval : When confidence interval is selected in the out of sample display you can adjust the percentage to reflect the desired confidence level for predictions.
- Omega forecast: Specifies the number of days ahead the omega ratio will be forecasted to get a long run measure.
- Minimum Acceptable Return : Specifies the target minimum acceptable return for the omega ratio calculation
- Complexity Components : When model complexity is selected in the out of sample display, this option will display the complexity of each individual state.
-Bayesian Information Criterion : When AIC/BIC is selected, turning this on this will ensure BIC is calculated instead of AIC.
Hidden Markov ModelHidden Markov Models (HMMs) are a class of statistical models used to represent systems that follow a Markov process with hidden states. In such models, the system being modeled transitions between a finite number of states, with the probability of each transition dependent only on the current state. The hidden states are not directly observable; instead, we observe a sequence of emissions or outputs generated by these states. HMMs are widely used in various fields, including speech recognition, bioinformatics, and financial market analysis. In the context of financial markets, HMMs can be utilized to model the latent market regimes (e.g., bullish, bearish, or neutral) that influence the observed market data such as asset prices or returns. By estimating the posterior probabilities of these hidden states, traders and analysts can identify the most likely market regime and make informed decisions based on the probabilistic assessment of market conditions.
The Hidden Markov Model (HMM) comprises several states that work together to model the hidden market dynamics. The states represent the unobservable market regimes such as bullish, bearish or neutral. The states are 'hidden' in nature because we need to infer them from the data and cannot directly observe them.
Model components:
Initial Probabilities: These denote the likelihood of starting in each hidden state. They can be related to long-run probabilities, reflecting the overall likelihood of each state across extended periods. In equilibrium, these initial probabilities may converge to the stationary distribution of the Markov chain.
Transition Probabilities: These capture the likelihood of moving between states, including the probability of remaining in the current state. They model how market regimes evolve over time, allowing the HMM to adapt to changing conditions.
Emission Probabilities: Also known as observation likelihoods, these represent the probability of observing specific market data (like returns) given each hidden state. Emission probabilities can be often represented by continuous probability distributions. In our case we are using a laplace distribution with its location parameter reflecting the central tendency of returns in each state and the scale reflecting the dispersion or the magnitude of the returns.
The power of HMMs in financial modeling lies in their ability to capture complex market dynamics probabilistically. By analyzing patterns in market, the model can estimate the likelihood of being in each state at any given time. This can reveal insights into market behavior and dynamics that might not be apparent from data alone.
MODEL FIT:
By default, the indicator displays the posterior probabilities, which represent the likelihood that the market is in a specific hidden state at any given time, based on the observed data and the model fit. It is crucial to understand that these posterior probabilities strictly represent the model fit, reflecting how well the model explains the historical data it was trained on. This model fit is inherently different from out-of-sample predictions, which are generated using data that was not included in the training process. The posterior probabilities from the model fit provide a probabilistic assessment of the state the market was in at a particular time based on the data that came before and after it in the training sequeence. Out-of-sample predictions on the other hand offer a forward-looking evaluation to test the model's predictive capability.
MODEL TEST:
When the "Test Out of Sample” option is enabled, the indicator plots the selected display settings based on models out-of-sample predictions. The display settings for out-of-sample testing include several options:
State Probability option displays the probability of each state at a given time for segments of datapoints that were not included in the traning process. This is particularly useful for real-time identification of market regimes, ensuring that the model's predictive capability is rigorously tested on unseen data. These probabilities are calculated using the forward algorithm, which efficiently computes the likelihood of the observed sequence given the model parameters. Higher probability for a particular state indicate a higher likelihood that the market is currently in that state. Traders can use this information to adjust their strategies according to the identified market regime and their statistical features.
Confidence Interval Bands option plots the upper, lower, and median confidence interval bands for predicted values. These bands provide a range within which future values are expected to lie with a certain confidence level. The width of the interval is determined by the current probability of different states in the model and the distribution of data within these states. The confidence level can be specified in the Confidence Interval setting.
Omega Ratio option displays a risk-adjusted performance measure that offers a more comprehensive view of potential returns compared to traditional metrics like the Sharpe ratio. It takes into account all moments of the returns distribution, providing a nuanced perspective on the risk-return tradeoff in the context of the HHMM's identified market regimes. The minimum acceptable return (MAR) used for the calculation of the omega can be specified in the settings of the indicator. The plot displays both the current Omega ratio and a forecasted "N day Omega" ratio. A higher Omega ratio suggests better risk-adjusted performance, essentially comparing the probability of gains versus the probability of losses relative to the minimum acceptable return. The Omega ratio plot is color-coded, green indicates that the long-term forecasted Omega is higher than the current Omega (suggesting improving risk-adjusted returns over time), while red indicates the opposite. Traders can use omega ratio to assess the risk-adjusted forecast of the model, under current market conditions with a specific target return requirement (MAR). By leveraging the HHMM's ability to identify different market states, the Omega ratio provides a forward-looking risk assessment tool, helping traders make more informed decisions about position sizing, risk management, and strategy selection.
Model Complexity option shows the complexity of the model, as well as complexity of individual states if the “complexity components” option is enabled. Model complexity is measured in terms of the entropy expressed through transition probabilities. The used complexity metric can be related to the models entropy rate and is calculated as the sum of the p*log(p) for every transition probability of a given state. Complexity in this context informs us on how complex the models transitions are. A model that might transition between states more often would be characterised by higher complexity, while a model that tends to transition less often would have lower complexity. High complexity can also suggest the model captures noise rather than the underlying market structure also known as overfitting, whereas too low complexity might indicate underfitting, where the model is too simplistic to capture important market dynamics. It is also useful to assess the stability of the model complexity. A model with irregular complexity values can be sign of overfitting, as it suggests that the process that the model is capturing changes significantly over time.
Akaike/Bayesian Information Criterion option plots the AIC or BIC values for the model on both the training and out-of-sample data. These criteria are used for model selection, helping to balance model fit and complexity, as they take into account both the goodness of fit (likelihood) and the number of parameters in the model. The metric therefore provides a value we can use to compare different models with different number of parameters. Lower values generally indicate a better model. AIC is considered more liberal while BIC is considered a more conservative criterion which penalizes the likelihood more. Beside comparing different models, we can also assess how much the AIC and BIC differ between the training sets and test sets. A test set metric, which is consistently significantly higher than the training set metric can point to a drift in the models parameters, a strong drift of model parameters might again indicate overfitting or underfitting the sampled data.
Indicator settings:
- Source : Data source which is used to fit the model
- Training Period : Adjust based on the amount of historical data available. Longer periods can capture more trends but might be computationally intensive.
- EM Iterations : Balance between computational efficiency and model fit. More iterations can improve the model but at the cost of speed.
- Test Out of Sample : turn on predict the test data out of sample, based on the model that is retrained every N bars
- Out of Sample Display: A selection of metrics to evaluate out of sample. Pick among State probability, confidence interval, model complexity and AIC/BIC.
- Test Model on N Bars : set the number of bars we perform out of sample testing on.
- Retrain Model on N Bars: Set based on how often you want to retrain the model when testing out of sample segments
- Confidence Interval : When confidence interval is selected in the out of sample display you can adjust the percentage to reflect the desired confidence level for predictions.
- Omega forecast: Specifies the number of days ahead the omega ratio will be forecasted to get a long run measure.
- Minimum Acceptable Return : Specifies the target minimum acceptable return for the omega ratio calculation
- Complexity Components : When model complexity is selected in the out of sample display, this option will display the complexity of each individual state.
-Bayesian Information Criterion : When AIC/BIC is selected, turning this on this will ensure BIC is calculated instead of AIC.
元宝均线趋势指标Yuanbao Moving Average Trend Indicator (元宝均线趋势指标)
A powerful, trend-following indicator designed to simplify market dynamics while capturing reliable trend signals—named for its "gold ingot" (Yuanbao) inspiration, symbolizing stability, precision, and wealth accumulation in trading. Built on optimized moving average (MA) logic, this tool filters noise, identifies trend direction, and highlights potential entry/exit zones, making it suitable for forex, stocks, cryptocurrencies, and commodities across all timeframes (from 1-minute scalping to daily swing trading).
Core Logic & Features
1. Multi-Layered MA Architecture
Combines short-term, medium-term, and long-term moving averages (customizable lengths) to balance responsiveness and reliability:
Short MA (e.g., 20-period): Tracks recent price momentum for timely signals.
Medium MA (e.g., 50-period): Confirms trend strength and filters false breakouts.
Long MA (e.g., 200-period): Acts as a dynamic support/resistance level and identifies major trend direction.
All MA types (SMA, EMA, WMA) are selectable—tailor to your trading style (EMA for faster reactions, SMA for smoother trends).
2. Trend Direction Visualization
Intuitive color-coding and line styling eliminate guesswork:
Bullish Trend: Short MA above Medium MA, and Medium MA above Long MA—lines turn green (customizable) to signal upward momentum.
Bearish Trend: Short MA below Medium MA, and Medium MA below Long MA—lines turn red (customizable) to indicate downward pressure.
Sideways/Consolidation: MAs cluster closely (with a built-in "range filter" to reduce noise)—lines turn blue (customizable) to alert neutral market conditions.
3. Dynamic Support/Resistance Zones
The indicator automatically highlights key levels based on MA crossovers and price interactions:
When price pulls back to the Medium/Long MA in a bullish trend: The MA line thickens to mark a potential "support zone" for long entries.
When price rallies to the Medium/Long MA in a bearish trend: The MA line thickens to mark a potential "resistance zone" for short entries.
Breaks above/below clustered MAs trigger "trend reversal alerts" (optional pop-up/alert conditions).
4. Customization for All Traders
Flexible parameters to adapt to any asset or strategy:
Adjust MA periods (short/medium/long) for different volatility levels (e.g., shorter periods for crypto, longer for blue-chip stocks).
Toggle MA type (SMA/EMA/WMA) to match your analysis style.
Customize color schemes, line thickness, and alert conditions (crossovers, trend shifts, price touches).
Enable/disable "noise reduction mode" (smoothes price data to filter choppy markets).
How to Use
Entry Signals
Long Entry:
Bullish trend confirmed (green MA stack: Short > Medium > Long).
Price pulls back to Medium MA (or Long MA for stronger trends) and bounces.
Optional: Confirm with volume or a candlestick pattern (e.g., hammer, bullish engulfing).
Short Entry:
Bearish trend confirmed (red MA stack: Short < Medium < Long).
Price rallies to Medium MA (or Long MA for stronger trends) and rejects.
Optional: Confirm with volume or a candlestick pattern (e.g., shooting star, bearish engulfing).
Exit Signals
Take Profit: Target next resistance/support level, or trail stop using the Short MA (exit if price crosses below Short MA in a bullish trend).
Stop Loss: Place below the Long MA (bullish trades) or above the Long MA (bearish trades) to limit downside.
Trend Reversal: Exit if the MA stack flips color (e.g., green → red for long trades).
Why Choose Yuanbao MA Trend Indicator?
Simplicity: No complex calculations—clear visual cues for trend direction and key levels.
Versatility: Works on all assets (forex, BTC, stocks, oil) and timeframes (1min, 15min, 4h, daily).
Reliability: Multi-MA confirmation reduces false signals, ideal for both beginners and experienced traders.
Customization: Adapt to your trading style, whether you’re a scalper, day trader, or swing trader.
Tips for Optimal Performance
For high-volatility assets (e.g., crypto), use shorter MA periods (e.g., 15/30/100) to stay responsive.
For low-volatility assets (e.g., bonds, blue-chip stocks), use longer MA periods (e.g., 50/100/200) for smoother trends.
Combine with oscillators (e.g., RSI, MACD) to avoid trading against overbought/oversold conditions.
Always test parameters on historical data before live trading—adjust based on asset-specific volatility.
BHA BUY SELLit will generate BUY SELL Signals and Support and Resistance levels and works on all instruments and all timeframes
