PDT AI✅ Features
Multi-indicator fusion: RSI + MACD + EMA + higher timeframe RSI
Signal strength (%): Each signal gets a confidence score (0–100)
Dynamic ATR-based targets and stops
Alerts: Buy/Sell triggers for real-time notifications
Fully customizable inputs
Search in scripts for "ai"
Trend Strength Confidence Gauge LiteMost traders don’t fail from bad charts — they fail from bad timing. Jumping in too early, bailing too soon, or freezing when the move finally comes.
The Trend Strength Confidence Meter strips away the noise and highlights the three factors that matter most:
Trend → The confirmed direction of the market
Confidence → Concise tool clarity providing quick entries
Strength → Strength Score shows the underlying battle between buyers and sellers
How to Use It:
Watch the Moving Average Ribbon (Hull MA) for a flip: green = uptrend, red = downtrend.
Act only when ribbon color matches the Confidence thumbs-up.
Confirm with Strength 3+ before entry.
When trend, confidence, and strength align, you reduce risk and step in at tighter entry points — giving clarity for entries and conviction to hold through stronger moves.
Advanced Indicators Made Simple — Provided by The AI Trading Desk
TitanFlow Position CalculatorTitanFlow Position Calculator - Professional Risk Management Tool
Transform your trading with precision position sizing and advanced risk management
The TitanFlow Position Calculator is a comprehensive Pine Script indicator designed for serious traders who demand professional-grade risk management tools. Whether you're trading forex, commodities, indices, or crypto, this calculator ensures you never risk more than intended while maximizing your profit potential.
🎯 Key Features:
SMART POSITION SIZING
Automatic lot size calculation based on your risk parameters
Support for percentage risk, fixed amount, or losing streak buffer modes
Real-time position size updates as market conditions change
Double-up mode for aggressive trading strategies
MULTI-ASSET SUPPORT
Pre-configured settings for Forex Major/Minor pairs
Commodities: Gold, Silver, Oil with accurate pip values
Stock indices with proper contract specifications
Cryptocurrency trading support
Custom instrument configuration for any asset
ADVANCED RISK MANAGEMENT
Visual risk level categorization (Conservative, Moderate, Aggressive, Extreme)
Color-coded risk warnings with threshold alerts
Margin requirement calculations with leverage integration
Take profit level planning with lot distribution
PROFESSIONAL THEMES
TitanFlow Dark theme matching the professional trading platform
TitanFlow Light theme for bright chart environments
Classic dark/light themes for traditional traders
Full custom colour control for personalized setups
COMPREHENSIVE LEVERAGE SUPPORT
Complete leverage options from 1:1 to 1:500 including:
1:1, 1:10, 1:15, 1:20, 1:30, 1:50, 1:100, 1:200, 1:300, 1:400, 1:500
📊 What You'll See:
REAL-TIME CALCULATIONS
Position size in lots displayed prominently
Risk level percentage with color coding
Margin requirements in your account currency
Stop loss distance in pips
Take profit distribution across multiple levels
CLEAN INFORMATION TABLE
Account balance and currency display
Current risk amount being wagered
Calculated position size and margin needs
Risk categorization with visual indicators
Leverage ratio confirmation
SMART ALERTS
Extreme risk warnings (>5% per trade)
Large position alerts (>10 lots)
High margin usage notifications (>50% account)
Real-time risk assessment updates
🚀 Take Your Trading Further with TitanFlow
Want more than just position sizing?
Visit titanflow.co.uk to discover the complete TitanFlow trading ecosystem:
✅ Advanced Trading Dashboard - Comprehensive portfolio tracking and analytics
✅ Trade Journal Integration - Log and analyze every trade automatically
✅ AI-Powered Coaching - Get personalized trading insights and recommendations
✅ Monthly Performance Reports - Detailed analytics delivered to your inbox
✅ Risk Management Suite - Professional tools for serious traders
✅ Trading Calendar - Never miss important market events
✅ Community Access - Connect with successful traders worldwide
Special Offer: TradingView users get exclusive access to premium features. Transform your trading from guesswork to systematic success. coming soon
🎨 Customization Options:
Theme Selection
Choose from 5 professional themes
Customize every colour element
Match your chart aesthetic perfectly
Professional branding options
Display Controls
Position table in any corner
Show/hide alerts and warnings
Adjustable text sizes
Clean, distraction-free interface
💡 Perfect For:
Day Traders who need quick position sizing decisions
Swing Traders planning multi-level exits
Scalpers requiring precise risk control
Portfolio Managers overseeing multiple accounts
Risk Managers monitoring exposure levels
Trading Educators teaching proper risk management
🚀 How to Use:
Set Your Account - Enter balance and currency
Choose Risk Mode - Percentage (recommended 1-2%), fixed amount, or losing streak buffer
Configure Instrument - Select asset type or use custom settings
Set Stop Loss - Enter your stop distance in pips
Read Results - Get instant position size and risk analysis
⚠️ Risk Management Excellence:
This calculator embodies the core principle that successful trading is about risk management, not just profit hunting. By using proper position sizing, you'll:
Survive losing streaks with capital intact
Compound profits systematically
Sleep better knowing your risk is controlled
Build consistent trading habits
Protect your trading capital long-term
Ready to elevate your entire trading operation? Start with this position calculator, then visit titanflow.co.uk to unlock the full potential of systematic, professional trading.
This indicator is part of the TitanFlow trading ecosystem. titanflow.co.uk coming soon here you'll be able to obtain the complete professional trading platform.
🎯 Super MA Arrows with Trend Bands🎯 Core Structure of the Indicator
1. Input Parameters Configuration
One of the most comprehensive indicators, featuring 50+ configurable variables, categorized into:
MA Settings: Define MA types and periods
Signal Settings: Customize signal conditions
Display Settings: Manage visual outputs
AI Settings: Enable/disable learning module
Multi-Timeframe Settings: Analyze across multiple timeframes
2. Moving Average & Envelope Calculations
The indicator employs multiple moving averages and an adaptive envelope:
Fast MA: Captures short-term movement (default: 9)
Slow MA: Reflects overall trend direction (default: 21)
Filter MA: Filters market noise (default: 50)
Envelope: Auto-adjusting support/resistance zones
3. Market Structure Analysis
Purpose: Confirm the market’s directional bias by evaluating swing highs/lows, breakouts, and consolidation zones.
Super MA Arrows with Trend Bands1. Input Parameters Configuration
One of the most comprehensive indicators, featuring 50+ configurable variables, categorized into:
MA Settings: Define MA types and periods
Signal Settings: Customize signal conditions
Display Settings: Manage visual outputs
AI Settings: Enable/disable learning module
Multi-Timeframe Settings: Analyze across multiple timeframes
2. Moving Average & Envelope Calculations
The indicator employs multiple moving averages and an adaptive envelope:
Fast MA: Captures short-term movement (default: 9)
Slow MA: Reflects overall trend direction (default: 21)
Filter MA: Filters market noise (default: 50)
Envelope: Auto-adjusting support/resistance zones
3. Market Structure Analysis
Purpose: Confirm the market’s directional bias by evaluating swing highs/lows, breakouts, and consolidation zones.
Altcoin Market Share vs ETH/BTCIdea from x.com on X
Each colored line represents the percentage share of different altcoin baskets (excluding stablecoins) or ETH relative to either the ETH or BTC market cap (can add more, e.g. SOL or create different dashboards with Memes, AI, DeFi, you name it)
I know: At first glance, this may seem noisy and complex, but it all depends on the questions you want to answer. Once you define those, much of the noise becomes irrelevant, allowing you to simplify the analysis and focus only on what matters to you. What I’ve done here is provide a few initial insights that I found useful (will isolate a couple of them in future).
This analysis doesn’t tell you which specific coins to buy, but rather provides a broad market overview as a foundation. It helps guide you toward areas of relative strength or weakness.
I’ve included a lot of information here, but the key is to extract the signal from the noise by asking the right questions, for example: At what point do altcoins become overvalued or undervalued against Ethereum? However, when asking these questions, it's important to remember that an overvaluation or undervaluation of Ethereum relative to altcoins tells you little about its valuation against Bitcoin or USD. These are separate questions further down the process.
권재용 ai 시그널(단타, 스윙모드 버전)기존 보조지표들에 문제점이 많이 느낌.
한 보조지표에 한가지 밖에 적용못한다는 점과 선물용 시그널이 없다는점.
모든 보조지표를 뒤져봐도, 롱,숏,청산 까지 나오는 보조지표가 없어서, 답답해서 직접 알고리즘 구현함.
아직은 베타버전. 지속적 업데이트 예정(스윙모드 값 최적화 덜됨.)
1. 현재 비트코인과 이더리움 최적화되게 세팅값 자동 조정되게 구현함.
2. 시간봉에 따라 세팅값 자동으로 조정되게 많듦.
3. 여러 신뢰도 높은 보조지표들 알고리즘 통합하여 알고리즘 구현.
간단 알고리즘
1)추세 레짐 감지
ADX(평균 방향성 지수) + 200EMA 기울기(Slope) + ST 안정도(Trend Stability) + HTF 방향 일치 4개 요소 합산 → Trend Score 산출.
점수 기반으로 추세장 / 박스장 / 전이구간 분류, 상태 전환시 히스테리시스(Hysteresis) 적용해 딸깍거리 방지함.
즉, 한번 추세로 들어가면 일정 조건 만족해야만 박스로 전환됨 → Noise Filtering 핵심.
2)다층 청산 로직
Give-back Limit: MFE(최대유리구간) 대비 일정 비율 되돌리면 청산 → 익절 보호.
ADX Weakness Counter: ADX가 약해지는 횟수 카운팅 → 모멘텀 사라질 때 청산.
HTF Flip Exit: 상위TF 추세 뒤집힘 시 강제 청산.
Structure Exit: 스윙 저점/고점 깨지면 구조 붕괴로 판단해 청산.
Time Stop: 스윙에서 일정 시간 진전 없으면 자동 청산.
이 모든 걸 OR 조건으로 묶음 → Multi-factor Exit Engine.
3). Adaptive Parameter Scaling (적응형 파라미터 스케일링)
사용자가 정한 공격성(aggressiveness) 값 + 실시간 레짐 상태 합쳐서
트레일링 폭(k)
되돌림 한계(gb)
ADX 문턱값
타임스톱 시간
다이나믹하게 바뀜.
결과: 시장이 고변동 추세장이면 청산 늦추고, 저변동 박스장이면 빨리 털고 나옴.
이게 Risk-Adjusted Exit Control 핵심.
4) State Machine Position Handling (포지션 상태 머신)
포지션 열림/닫힘/쿨다운 주기 관리.
진입 후 entryPrice, slPrice, mfe, noProgBars 등 상태변수 실시간 업데이트.
일종의 Finite State Machine(FSM) 구조라서 로직 충돌 없이 깔끔하게 동작함.
7. Hysteresis & Persistence Filters
추세/변동성 상태 바뀔 때 Persistence Counter로 연속성 요구함.
예: 한두 봉 노이즈로는 추세 안바뀜 → Signal Debouncing 기법.
간단 사용 루틴(단타)
1~15분봉 추천, 단타 + Auto + Auto + 공격성 50~60.
우상단 시장이 추세장·고변동이면 시그널↑. 박스장·저변동이면 진입 빈도↓.
KJY-L/S 뜨면 진입, 회색선=진입가/빨간선=SL 확인.
KJY-E 뜨면 미련 없이 정리. 알림 연동해두면 실전 편함.
간단 사용 루틴(스윙)
2H~4H, 스윙 + Auto + Auto + 공격성 45~55 + 스윙 최적화 ON.
구조 붕괴/타임스톱/HTF 뒤집힘 오면 자동으로 E 라벨로 정리.
레짐 감지: ADX 스무딩, 200EMA 기울기, ST 안정도, HTF 정합로 점수화 → 추세/박스 자동 분류.
변동성 적응: TR 비율로 고/저변동 인식 → 트레일 폭, 되돌림 한계, 타임스톱 스케일 조정.
스윙 가드: 1D 구조/기울기/정체시간 3중 안전장치.
공격성 슬라이더: 사용자 성향 한 방에 반영(트레일·되돌림·ADX 문턱 동시 스케일링).
I felt a lot of limitations with existing indicators.
Most indicators can only handle one thing at a time, and none of them provide signals specifically for futures trading.
After digging through all indicators, I realized there wasn’t a single one that gave me long, short, and exit signals all in one — so I built my own algorithm out of frustration.
This is still a beta version, with continuous updates planned.
Automatically optimized for Bitcoin and Ethereum.
Parameters auto-adjust based on timeframe.
Combines multiple high-reliability indicators into one unified algorithm.
1) Trend Regime Detection
Uses ADX (Average Directional Index) + 200EMA Slope + ST Stability (Trend Stability) + HTF Direction Alignment.
Combines the four elements into a Trend Score.
Classifies markets into Trending / Ranging / Transitional phases.
Applies Hysteresis during regime switching to prevent rapid signal flipping.
Once in a trend, it only switches to range mode after strict conditions are met → core Noise Filtering logic.
2) Multi-Layer Exit Logic
Give-back Limit: Exits if price retraces beyond a set % of MFE (Maximum Favorable Excursion) → protects profits.
ADX Weakness Counter: Counts consecutive ADX weakening periods → exits when momentum dies.
HTF Flip Exit: Forces exit if higher-timeframe trend reverses.
Structure Exit: Exits when swing high/low breaks = structural failure.
Time Stop: Auto exit if no progress after a set number of bars in swing mode.
All combined via OR conditions → Multi-factor Exit Engine.
3) Adaptive Parameter Scaling
Combines user-defined aggressiveness + real-time regime state to dynamically adjust:
Trailing stop width (k)
Give-back limit (gb)
ADX threshold
Time-stop duration
Result: In high-volatility trending markets, exits trail further; in low-volatility ranging markets, exits tighten quickly → key to Risk-Adjusted Exit Control.
4) State Machine Position Handling
Manages open/close/cooldown cycles for positions.
Updates variables like entryPrice, slPrice, mfe, noProgBars in real-time.
Built as a Finite State Machine (FSM) → avoids logic conflicts, ensures clean execution.
5) Hysteresis & Persistence Filters
Adds Persistence Counters for regime switching.
Prevents a single noisy candle from flipping states → Signal Debouncing technique.
Recommended: 1–15min charts, Settings: Scalp + Auto + Auto + Aggressiveness 50–60.
Top-right panel: Trending + High-Volatility → More Signals, Ranging + Low-Volatility → Fewer Entries.
When KJY-L/S appears → enter trade. Gray line = entry price, red line = SL.
When KJY-E appears → exit with no hesitation. Alerts make it seamless in real trading.
Recommended: 2H–4H charts, Settings: Swing + Auto + Auto + Aggressiveness 45–55 + Swing Optimization ON.
Structural breaks / Time-stop / HTF trend reversals → auto exit with E label.
Regime Detection: ADX smoothing + 200EMA slope + ST stability + HTF alignment → auto classifies Trend vs Range.
Volatility Adaptation: TR ratio detects high/low volatility → adjusts trail, give-back, and time-stop levels.
Swing Guard: 1D structure, slope, and time-stop → triple safety filter.
Aggressiveness Slider: Instantly applies user preference to trail width, give-back, ADX thresholds
Long Elite Squeeze (LES) — H.H 22 Lindsay (AI)LES (Long Elite Squeeze)
LES (Long Elite Squeeze) is a trading framework designed to capture the highest-probability long setups. It’s not just another signal script — it’s a structured system built to filter noise, manage risk, and keep you aligned with real momentum.
🔹 Core Logic
Breakout Confirmation – Ensures moves have structure, not just random spikes.
Relative Volume (RVOL) – Confirms participation and fuel behind the move.
RSI Alignment – Avoids overextended traps and fakeouts.
Squeeze Momentum – The backbone of LES. Signals fire only after a defined squeeze pattern shift (6+ dark green bars followed by a light green bar).
🔹 Trade Management Built In
Automated Sell Signals – Trigger on either:
2 consecutive dark green bars on Squeeze Momentum
WaveTrend cross down
(only valid after a Buy signal — no random shorts)
HUD Entry Checklist – Live conditions shown on chart.
Status Tracker HUD – Flips between “Waiting for Entry” and “In Trade” for clear context.
🔹 Flexibility
3 switchable squeeze versions (V1, V2, V3) for different market conditions.
Customizable EMA & ATR settings (with color options).
Session-aware logic — filter signals to prime trading hours.
🔹 Blueprint & Credits
LES is a fusion of proven concepts, standing on the shoulders of respected creators:
-Squeeze Momentum – LazyBear
-WaveTrend Oscillator – LazyBear
-Relative Volume – LonesomeTheBlue
Breakout/structural logic – refined from classic frameworks
Their work laid the foundation — LES expands and integrates them into a complete trading system.
⚡ Why LES Stands Out
LES wasn’t coded overnight. It’s the result of countless hours of live testing, rebuilding, and refining. Every feature earned its place by proving value in real trading, not theory.
LES is more than an indicator. It’s a disciplined framework — crafted to turn chaos into structure, randomness into probability, and noise into clarity.
⚠️ Disclaimer: This is a trading framework, not financial advice. Performance depends on trader discipline, risk management, and market conditions.
Pump & Dump Strategy (seconds) w/ Candle Confirmation + ReverseStrategy for pump and dump. Look for > 1% price increment in seconds.
Alexmoku Genesis v0.2.6 — Runtime BulletproofAlexmoku Genesis v0.2.6 – Reinventing Ichimoku with Precision and Intelligence
Built by Alex • Engineered for traders who demand more than lagging clouds
🔬 Overview
Alexmoku Genesis is a ground-up reimagining of the traditional Ichimoku system — retaining its philosophical foundations of harmony, balance, and structure, while infusing it with modern logic, advanced volatility modeling, and AI-aligned signal classification.
This is not your grandfather’s Ichimoku. Genesis transforms it into a forward-sensing, volatility-aware system that adapts in real time and guides discretionary and algorithmic traders alike with smarter signals, predictive structure, and built-in trade intelligence.
⚙️ Core Enhancements
📐 Volatility-Responsive Smoothing
Tenkan-sen and Kijun-sen lengths are dynamically adjusted based on recent price volatility (ATR-based).
Prevents overreaction in choppy markets and improves responsiveness during strong trends.
🌀 Adaptive Cloud Projection
Span A and Span B are still projected 52 periods forward — but cloud width adapts to market rhythm, not just static values.
🕵️ Enhanced Chikou Span (CKS+)
Chikou logic is upgraded to emphasize structure interaction, not just simple price overlay.
Useful for identifying support/resistance echoes and divergence validation.
🌐 Multi-Timeframe Cloud Awareness (Genesis Core)
Internal alignment checks between higher and lower timeframe Kumo positioning.
Future module support for overlaying MTF clouds.
🔖 Signal Classifier Engine (Experimental)
Each major structure event is tagged with signal intent:
📦 prep
🚀 launch
🔁 reversion
🪤 trap
Enables faster discretionary reads or future automation.
🧠 Trust Score Logic (Coming soon)
Future versions will assign numerical trust scores (1–10) to trade setups based on confluence.
🧰 Settings
🔧 Volatility Scaling Factor – Adjusts how reactive the indicator is to volatility. Default: 300.
🌫 Displacement (Kumo) – Cloud projection forward. Default (and required): 52.
⛅ Cloud Display Toggle – Show/hide Kumo visuals without affecting logic.
⚡️ Future expansion modules already scaffolded (MTF overlays, color-coded signal classifiers, Trust Score engine, etc.)
🧘 Philosophy Behind the System
"This isn’t just about catching runners — it’s about becoming the kind of person who can trade with clarity, peace, and precision."
Alexmoku Genesis reflects the W.E.A.L.T.H. System's holistic philosophy:
Wealth
Engineered
Algorithmic
Leveraged
Trading
Holistically
Trading isn't just a strategy. It's a mirror. Genesis is designed to train both your execution and your awareness.
⚠️ Disclaimer
This tool is designed for experienced technical traders and is still in active development. Use judgment and proper risk management. This is not financial advice.
Comet C/2025 N1 (ATLAS) Ephemeris☄️ Ephemeris How-To: Plot JPL Horizons Data on TradingView (Educational)
Overview
This open-source Pine Script™ v6 indicator demonstrates how to bring external astronomical ephemeris into TradingView and plot it on a daily chart. Using Comet C/2025 N1 (ATLAS) as an example dataset, it shows the mechanics of structuring arrays, indexing by date, and drawing past and forward ( future projections ) values—strictly as an educational visualization of celestial motion.
Why This Approach
Data is generated from NASA JPL Horizons, a mission-grade, publicly available ephemeris service ( (ssd.jpl.nasa.gov)). On the daily timeframe, Horizons provides high-precision positions you can regenerate whenever solutions update—useful for educational accuracy in exploring orbital data.
What’s Plotted
- Geocentric ecliptic longitude (Earth-view)
- Heliocentric ecliptic longitude (Sun-centered)
- Declination (deg from celestial equator)
Features
- Simple arrays + date indexing (no per-row timestamps)
- Circles for historical/current bars; polylines to connect forward points, emphasizing future projections
- Toggle any series on/off via inputs
- Daily timeframe enforced (runtime error if not 1D)
- Optional table with zodiac conversion (AstroLib by BarefootJoey)
Data & Updates
The example arrays span 2025-07-01 (discovery date) → 2026-01-01. You can refresh them anytime from JPL Horizons (Observer: Geocentric; daily step; include ecliptic lon/lat and declination) and paste the new values into the script.
How we pulled the ephemeris from JPL Horizons (quick guide):
0) Open ssd.jpl.nasa.gov System
1. Ephemeris Type: Observer Table
2. Target Body: C/2025 N1 (ATLAS) (or any object you want)
3. Observer Location: Geocentric
4. Time Specification: set Start, Stop, Step = 1 day
5. Table Settings → Quantities:
* Astrometric RA & Dec
* Heliocentric ecliptic longitude & latitude
* Observer (geocentric) ecliptic longitude & latitude
6. Additional Table Settings:
* Calendar format: Gregorian
* Date/Time: calendar (UTC), Hours & Minutes (HH:MM)
* Angle format: Decimal degrees
* Refraction model: No refraction / airless
* Range units: Astronomical units (au)
7. Generate → Download results (CSV or text).
8. Use AI or a small script to parse columns (e.g., Obs ecliptic lon, Helio ecliptic lon, Declination) into arrays, then paste them into your Pine script.
Educational Note
This indicator’s goal is to show how to prepare and plot ephemeris—so you can adapt the method for other comets or celestial bodies, or swap in data from existing astro libraries, for learning about astronomical projections using JPL daily data.
Credits & License
- Ephemeris: Solar System Dynamics Group, Horizons On-Line Ephemeris System, 4800 Oak Grove Drive, Jet Propulsion Laboratory, Pasadena, CA 91109, USA.
- Zodiac conversion: AstroLib by BarefootJoey
- License: MIT
- For educational use only.
권재용AI 업데이트 버전한 줄 압축: ‘추세,수급,변동성의 교집합에서만 거래하게 강제하는 보조지표 만듦
-슈퍼트렌드에 다중TF·수급·레짐 합의점수 얹어 재도색 없이 ‘자리 좋은’ 신호만 뽑는 엔진 만듦
-Flip·Pullback을 켈트너·RSI·OBV/MFI·ADX로 교차검증해 노이즈 싹 걷어내는 NRP 신호 설계함
-추세판단→엔트리→S/R·VWAP 컨텍스트→TP/SL·알림까지 지표 하나로 풀스택 자동화함
-상위TF 확정봉+ATR 레짐+EMA 정렬로 허접 및 가짜 신호 전부 필터링하고 남은 것만 화살표로 뽑게 만듦
-트렌드·수급·변동성 3요소를 점수화해 신호 질·빈도 동시에 컨트롤하는 합의형 엔진 제작함
-NRP ST에 S/R 존과 앵커 VWAP 붙여 ‘보이는 자리만’ 눌러 담게 만드는 실전형 지표임
-알고리즘이 허락하고 사람은 자리만 고르게 만드는 엔트리 시스템으로 구조 갈아엎음
-Flip+Pullback을 ‘의미 있는 눌림/돌파’만 통과시키는 확률적 알고리즘임
-신호 뜨면 TP/SL/시간청산까지 경로가 자동 깔리는 엔드투엔드 트레이딩 레일 만들었음
-케이스 바이 케이스를 규칙으로 압축해 클릭 전에 이미 선별 끝내는 지표임
-빈도는 살리고(Flip+PB) 질은 점수로 묶은, 레버리지 장에서도 버티는 엔진임
0) 보조지표 구분
초록 굵은 선 = 상승 추세(롱 바이어스)
빨강 굵은 선 = 하락 추세(숏 바이어스)
청록 채움 = 지지 존(S1~S3)
적갈 채움 = 저항 존(R1~R3)
주황 실선 + 연한 띠 = 앵커 VWAP + 밴드
파랑/보라 얇은 선 = 전일/전주 고저
초록/빨강 라벨 = 권재용 B/S 신호
회색 선 = TP1/TP2, 검정 선 = SL 가이드
옅은 노랑 배경 = 신호 직후 경계 구간
1) 사용법(초보→중급→고급)
A) 초보자(그대로 따라 하기)
보는 법:
ST 색 먼저 봄(초록=롱, 빨강=숏). 상위TF(4H) 같은 방향인지 확인함.
화살표 뜨면 후보. 바로 위/아래 S/R 존·앵커 VWAP 있는지 확인.
저항 겹치면 롱 지연/축소, 지지 겹치면 숏 지연/축소.
진입:
Flip 신호면 추세 시작 자리.
Pullback 신호면 눌림/반등 자리(켈트너+RSI 재진입 충족).
청산:
TP1에서 절반, TP2에서 나머지(취향).
SL은 가이드 라인 참조하되 실제 손절은 주문으로 확정함.
알림: BUY/SELL만 봉 마감으로 켜두면 충분함.
B) 중급자(필터/점수로 빈도·질 조절)
빈도 늘리고 싶음: preset=공격적 또는 scoreExtra=-0.5, cooldownBars=0~1, minDistATR=0~0.2, adxMin=18~20, atrZmin=0.0/atrZmax=1.0
질 올리고 싶음: preset=보수적, scoreExtra=+0.5~+1.0, cooldownBars≥3, minDistATR=0.3~0.5, adxMin=22~25, chopMax=50
주의: OBV/MFI 끄면 최대점수 1점임. 중립(3)/보수(4)로 두면 신호 안 뜸 → 프리셋 낮추거나 OBV/MFI 켬.
C) 고급자(레짐·TF·자금관리)
레짐 매핑:
추세장: adxMin↑, chopMax↓, minDistATR↑(추격 줄임)
박스장: useCHOP=OFF 고려, kelMult↑로 밴드 넓혀 과매수/과매도만 노림
TF 분리 운용:
엔트리 5/15m + confTF=60m(1H)로 더 타이트하게 확정
스윙이면 res="", confTF="D" / confirmBars=1~2
앵커 VWAP: Flip마다 리셋됨. 추세 추종이면 VWAP 위 롱/아래 숏 기본. 역추세는 밴드 터치→재관통만 부분 진입.
3) 목적별 프리셋(붙여 쓰기)
스캘핑(신호 많게, 1~5m)
entryMode=Flip+Pullback
preset=공격적 또는 중립 + scoreExtra=-0.5
adxMin=18~20, cooldownBars=0~1, minDistATR=0~0.2
atrZmin=0.0 / atrZmax=1.0, chopMax=58~60
청산: tp1ATR=0.6~0.8, tp2ATR=1.2~1.6, timeExit=20~30
데이(균형, 5~15m)
초기 기본값 세트 그대로
손절 좁히려면 slATR=0.8~1.0, 리스크 허용 크면 tp2ATR=2.2~2.5
스윙(정확도 우선, 1H~4H/Day)
entryMode=Flip only
preset=보수적, scoreExtra=+0.5~+1.0
adxMin=22~25, cooldownBars=3~5, minDistATR=0.3~0.5
confTF="D"(혹은 W), confirmBars=1~2
청산: tp1ATR=1.5, tp2ATR=3.0, timeExit=0~20(장세 따라)
돌파 전문(Flip만, 저항 상단 체결 줄임)
entryMode=Flip only
minDistATR=0.4~0.6, cooldownBars=2~3, chopMax=48~52
눌림 전문(Pullback만, VWAP/지지부근)
entryMode=Pullback only
kelMult=1.6~1.8, rsiBand=6~8(더 확실한 재진입만)
tp1ATR 살짝 낮춤(0.8~1.2) → 빈도 대비 체결·수익 확보
2) 차트 읽는 법(초간단)
색: 초록=롱 바이어스, 빨강=숏 바이어스
화살표: “권재용 B/S” 뜨면 후보. 상위TF도 같은 방향이어야 유효
존: 청록=S(지지), 적갈=R(저항). 존 위는 저항라인, 아래는 지지라인
주황선: 앵커 VWAP(마지막 Flip 기준 평균가).
3) 진입법(딱 두 개만 기억)
Flip 진입: 색이 바뀌는 순간 화살표 → 바로 위/아래 R/S 겹침 있나 보고 들어감
Pullback 진입: 추세 진행 중, 켈트너 밴드 꼬리 터치 + 중선 재관통 + RSI 재진입 → 들어감
4) 청산/손절(기본값 그대로)
TP1/TP2: 회색 라인 목표. 반절/전량 취향대로
SL: 검정 라인(가이드). ST 라인과 ATR 기준 중 더 보수적으로 잡힘
시간청산: 오래 끌리면 자동 신호(TIME_EXIT). 트렌딩장엔 꺼도 됨
5) 목적별 빠른 프리셋
스캘핑(신호 많이)
entryMode = Flip+Pullback
preset = 공격적 또는 중립 + scoreExtra = -0.5
cooldownBars = 0~1, minDistATR = 0~0.2, adxMin = 18~20
필요하면 useCHOP = OFF, atrZmin=0.0/atrZmax=1.0
데이(균형형)
위 “3분 설정” 그대로 쓰면 됨
스윙(정확도 우선)
entryMode = Flip only
preset = 보수적, scoreExtra = +0.5~+1.0
cooldownBars ≥ 3, minDistATR = 0.3~0.5, adxMin = 22~25
필터 전부 ON 유지
6) 자리 고르는 요령
롱이면 VWAP 위, 아래서 위로 재관통 시 더 좋음
바로 위 R1/R2/R3 겹치면 대기 or 사이즈 축소
Pullback은 S1~S3 근처 눌림 + 재관통 조합이 질 높음
7) 신호 안 뜰 때 체크리스트
OBV/MFI 끄고 preset=중립/보수적 → 점수 모자람
상위TF 불일치 or confirmBars 너무 큼
cooldownBars 때문에 막힘
minDistATR 너무 큼(가격이 ST와 너무 가까워야 함)
atrZ 범위 과도(레짐 필터 너무 빡셈)
EMA 정렬(20/50) 안 맞음
res로 다른 TF 계산 중인데 까먹음
8) 초간단 용어
ST(슈퍼트렌드): 추세선. 색이 바이어스
Flip: ST 색 전환
Pullback: 추세 중 되돌림 진입(켈트너+RSI 재진입)
S/R 존: 지지/저항 영역(청록/적갈 채움)
앵커 VWAP: 마지막 Flip부터 계산한 평균가
9) 안전수칙
알림은 봉 마감만 신뢰
지표는 허락장치, 자리는 S/R·VWAP로 판단
레버리지/사이즈는 따로 규칙 만들고 지킬 것
What it is (in plain English)
This is a non-repainting Supertrend system. It gives you two kinds of entries (trend flip and pullback), checks a bunch of sanity filters so you don’t click junk, confirms with a higher timeframe, draws nearby support/resistance zones, anchors a VWAP at the last regime change, and shows simple TP/SL guides. It also pushes JSON alerts you can feed to a bot.
How I’d read it on a chart
Trend first
The thick Supertrend line is the boss: green = long bias, red = short bias.
Signals only count when the higher TF agrees for a few confirmed candles.
Entries
Flip: the Supertrend flips color. That’s your fresh trend start.
Pullback: in an existing trend, price wicks to the Keltner band, then closes back through the midline, and RSI snaps back through its mid level. That’s your “buy the dip / sell the pop”.
Where you are
Teal filled zones = supports (S1–S3). Maroon filled zones = resistances (R1–R3).
Blue/purple lines are yesterday/last week high/low.
Orange line is the anchored VWAP from the last flip (with a soft band). If price hugs it, you’re near “fair”.
Getting out
After a signal, it paints TP1/TP2 by ATR and a guide SL (it respects Supertrend so it doesn’t sit unrealistically tight). There’s also an optional “time exit” if a trade drags on.
What keeps signals honest (filters)
EMA alignment: longs want EMA20 > EMA50 and price above the fast EMA (mirror for shorts).
ADX: wants trend strength above a floor and rising.
Choppiness: avoids heavy range conditions.
Distance to Supertrend: blocks entries that fire right on top of the line.
ATR regime: ignores dead volatility and panic volatility.
OBV/MFI: quick check that flow isn’t fighting you.
Cooldown: don’t fire twice in a row.
There’s also a tiny score: EMA(1pt) + OBV(1) + MFI(1). Your preset sets how many points you demand (Aggressive=2, Neutral=3, Conservative=4). If you turn OBV/MFI off but keep a high demand, you’ll get no signals—easy to forget.
Two ways I’d run it
More trades (scalpy):
Mode: Flip+Pullback
Preset: Aggressive (or Neutral with scoreExtra = -0.5)
Cooldown: 0–1 bars
Min distance to ST: 0–0.2 ATR
ADX min: ~18–20
ATR regime: loosen it if you feel filtered out
Optional: turn off Choppiness if you’re okay with rangy action
Pickier (day/swing):
Mode: Flip only (or Pullback only if you like mean-revert entries)
Preset: Conservative (+ scoreExtra +0.5 to +1.0 if needed)
Cooldown: ≥3 bars
Min distance to ST: 0.3–0.5 ATR
Keep CHOP/ADX/RSI/Keltner/OBV/MFI on
ADX min: ~22–25
Small habits that help
Set alerts on bar close to match the non-repainting logic.
Treat S/R zones and anchored VWAP as context, not hard rules. If a Flip long triggers into stacked resistances and above VWAP, size lighter or wait for a pullback signal.
Don’t forget the score vs. enabled filters. If OBV/MFI are off, max score is 1.
Quick checklist before you click
Higher TF lined up and confirmed?
Entry is Flip or valid Pullback (wick → midline re-cross + RSI re-entry)?
EMA/ADX/CHOP pass? Not sitting on the ST line?
Score meets the preset? ATR regime okay?
Any nasty R1/R2/R3 right in front of you? Where’s anchored VWAP?
TP/SL sensible for the timeframe you’re trading?
TTE Elite Market SignalsWelcome to TTE Elite Market Signals Your very own personal trading assistant
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Revolutionary Signal Intelligence
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Elite Analysis Modes
Our platform adapts its signal generation to match market personalities:
- Institutional Flow Mode (MM-hybrid): Identifies manipulation patterns and tracks smart money movement with exclusive institutional-grade precision
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Comprehensive Signal Intelligence
TTE Elite Market Signals integrates multiple sophisticated analytical systems:
- Volume Profile analysis for exclusive institutional-level market insights
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- Fibonacci based reversal logic
Perfect for Your Trading Evolution
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Two Elite Service Modes
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What makes TTE Elite Market Signals exceptional: it maintains a comprehensive trade memory and identifies the highest-probability signals, adapts to changing volatility patterns, and continuously refines(does not repaint) its analysis to enhance your profit potential and trading accuracy.
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TTE gives you visuals on the chart of past trades and live metrics results to see what actually work and what fails, to minimize unrealistic expectations. Just sit back and watch sophisticated algorithms work tirelessly on your behalf, identifying opportunities that others miss and alerting you as signals are generated. Transforming the stressful, emotional battlefield of trading into a systematic analytical approach.
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While others struggle with analysis paralysis and emotional decision-making, you'll have access to signals that have already processed hundreds of data points, identified institutional patterns, and calculated optimal risk-reward scenarios for a far less stressful trading experience.
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TTE Elite Market Signals represents cutting-edge signal generation technology designed for serious market education and skill development, but it is not a black box, nor perfect for all markets. It must be adjusted to yield optimal results. While our advanced capabilities and institutional-grade features provide significant analytical advantages, trading success requires discipline and proper execution. Markets evolve, and optimal results demand understanding of signal context.
Success with TTE Elite Market Signals comes from mastering our analytical modes and using the proper entry types such as breakout entry, machine learning(ML) entry etc, utilizing and selecting the most effective risk control to optimize it, and maintaining disciplined risk management.
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Best TTE Settings
Trade Entry Types:
1st Best Breakout Entry(out perform all others when used alone)
2nd Best ML Entry by itself or + Pattern Entry Combined
Risk Management:
ATR Multiplier 2
Enable Master Size Control
Master Size Mode
Max Risk Per Trade % 2.5
Max Multiplier Cap 1.5
Enable Growth Scaling
Growth Scaling Mode-set to Time Based or Performance
Risk Management System- set to Hybrid
Enable ML System
ML Mode-set to Auto or Quantum Learning
ML Application Strategy-set to Universal All Entries
Enable Trend Continuation
Mode- Set to Standard
Independent Entry-stays unchecked(off)
Best Performing Instruments on TTE (will update list as more are adjusted and tested)
NVDA
AMD
AMZN
TSLA
SPY
QQQ
PLTR
ROPSON AI Ultra 3.27 How It Takes a Long (Buy) Position
The code will only enter a long position when two conditions are met simultaneously. Both must be true for a buy signal to be generated:
The current candle's close price crosses above the previous candle's high. This is the breakout signal. It indicates strong upward momentum.
The current candle's close price is above the 200 EMA. This is the trend filter. The 200 EMA (Exponential Moving Average) is a widely used indicator for long-term trend. If the price is above it, the market is considered to be in an uptrend.
By requiring both conditions, the strategy aims to enter trades that have both short-term momentum (the breakout) and long-term trend confirmation (the EMA filter).
How It Takes a Short (Sell) Position
Similarly, a short position is only entered when both of these conditions are true at the same time:
The current candle's close price crosses below the previous candle's low. This is the breakdown signal, indicating strong downward momentum.
The current candle's close price is below the 200 EMA. This confirms that the market is in a downtrend.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
Trend and verser AI indicator V1.01Declaration: NO REPAINTING, NO LAG, NO DISPLACEMENT – SIGNALS NEVER DISAPPEAR!
Indicator Usage Guide (Simple & Effective):
(1) Red Zone + UP Arrow → Go LONG
(2) Green Zone + DOWN Arrow → Go SHORT
(3) Alternating Red/Green Zones → Consolidation Phase (NO TRADING!)
Default parameters are optimized for reliable signals but can be customized as needed.
Instructions:
(1) This indicator is suitable for any trading instrument (stocks, futures, forex, cryptocurrencies, options, etc.) and any timeframe (minutes, hours, days, weeks, months).
(2) The indicator only provides entry signals (buy/sell signals). It does not provide exit signals. Profitability depends entirely on your holding period. This indicator does not guarantee profits.
(3) Arrows come in Red and Blue, representing two different signal types. Red signals may provide more precise reversal points on the candlestick chart compared to Blue signals.
(4) The indicator plots three distinct trend lines: a Red trend line, a Green trend line, and a Yellow trend line.
(5) * When the Red trend line is ABOVE the Yellow trend line, it signifies a Bullish (uptrend) market,consider taking LONG positions based on arrow signals.
* When the Green trend line is BELOW the Yellow trend line, it signifies a Bearish (downtrend) market,consider taking SHORT positions based on arrow signals.
* When the Red and Green trend lines are ALTERNATING (crossing frequently), it signifies a Ranging (sideways/consolidation) market, arrow signals are less reliable during this phase, and trading is NOT recommended.
Trend and Reverse AI indicator Declaration: NO REPAINTING, NO LAG, NO DISPLACEMENT – SIGNALS NEVER DISAPPEAR!
Indicator Usage Guide (Simple & Effective):
(1) Red Zone + UP Arrow → Go LONG
(2) Green Zone + DOWN Arrow → Go SHORT
(3) Alternating Red/Green Zones → Consolidation Phase (NO TRADING!)
Default parameters are optimized for reliable signals but can be customized as needed.
Instructions:
(1) This indicator is suitable for any trading instrument (stocks, futures, forex, cryptocurrencies, options, etc.) and any timeframe (minutes, hours, days, weeks, months).
(2) The indicator only provides entry signals (buy/sell signals). It does not provide exit signals. Profitability depends entirely on your holding period. This indicator does not guarantee profits.
(3) Arrows come in Red and Blue, representing two different signal types. Red signals may provide more precise reversal points on the candlestick chart compared to Blue signals.
(4) The indicator plots three distinct trend lines: a Red trend line, a Green trend line, and a Yellow trend line.
(5) * When the Red trend line is ABOVE the Yellow trend line, it signifies a Bullish (uptrend) market,consider taking LONG positions based on arrow signals.
* When the Green trend line is BELOW the Yellow trend line, it signifies a Bearish (downtrend) market,consider taking SHORT positions based on arrow signals.
* When the Red and Green trend lines are ALTERNATING (crossing frequently), it signifies a Ranging (sideways/consolidation) market, arrow signals are less reliable during this phase, and trading is NOT recommended.
New RSI📌 New RSI
The New RSI is a modern, enhanced version of the classic RSI created in 1978 — redesigned for today’s fast-moving markets, where algorithmic trading and AI dominate price action.
This indicator combines:
Adaptive RSI: Adjusts its calculation length in real time based on market volatility, making it more responsive during high volatility and smoother during calm periods.
Dynamic Bands: Upper and lower bands calculated from historical RSI volatility, helping you spot overbought/oversold conditions with greater accuracy.
Trend & Regime Filters: EMA and ADX-based detection to confirm signals only in favorable market conditions.
Volume Confirmation: Signals appear only when high trading volume supports the move — green volume for bullish setups and red volume for bearish setups — filtering out weak and unreliable trades.
💡 How it works:
A LONG signal appears when RSI crosses above the lower band and the volume is high with a bullish candle.
A SHORT signal appears when RSI crosses below the upper band and the volume is high with a bearish candle.
Trend and higher timeframe filters (optional) can help improve precision and adapt to different trading styles.
✅ Best Use Cases:
Identify high-probability reversals or pullbacks with strong momentum confirmation.
Avoid false signals by trading only when volume validates the move.
Combine with your own support/resistance or price action strategy for even higher accuracy.
⚙️ Fully Customizable:
Adjustable RSI settings (length, volatility adaptation, smoothing)
Dynamic band sensitivity
Volume threshold multiplier
Higher timeframe RSI filter
Color-coded background for market regime visualization
This is not just another RSI — it’s a complete, next-gen momentum tool designed for traders who want accuracy, adaptability, and confirmation in every signal.
Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input".
🔸 CONCEPTS
🔹 What are Prime Numbers?
A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers.
Wikipedia: Prime number
🔹 Prime Factorization
The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers.
Wikipedia: Fundamental theorem of arithmetic
Math Is Fun: Prime Factorization
We divide a given number by Prime Numbers until only Primes remain.
Example:
24 / 2 = 12 | 24 / 3 = 8
12 / 3 = 4 | 8 / 2 = 4
4 / 2 = 2 | 4 / 2 = 2
|
24 = 2 x 3 x 2 | 24 = 3 x 2 x 2
or | or
24 = 2² x 3 | 24 = 2² x 3
In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same.
🔸 USAGE
The Prime Numbers publication contains two use cases:
Prime Factorization: performed on "close" prices, or a manual chosen number.
List Prime Numbers: shows a list of Prime Numbers.
The other two options are discussed in the DETAILS chapter:
Prime Factorization Without Arrays
Find Prime Numbers
🔹 Prime Factorization
Users can choose to perform Prime Factorization on close prices or a manually given number.
❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1.
In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50).
The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar.
When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored.
Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings.
Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes.
Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown:
The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript.
For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7²
🔹 List Prime Numbers
The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200)
The highest shown Prime Number is 1,340,011.
One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20).
🔸 DETAILS
The Prime Numbers publication consists out of 4 parts:
Prime Factorization Without Arrays
Prime Factorization
List Prime Numbers
Find Prime Numbers
The usage of "Prime Factorization" and "List Prime Numbers" is explained above.
🔹 Prime Factorization Without Arrays
This option is only there to highlight a hurdle while performing Prime Factorization.
The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes.
The division should be done by primes, but then you need to know which one is a prime.
In practice, one performs a loop from 2 to the base number.
Example:
Base_number = input.int(24)
arr = array.new()
n = Base_number
go = true
while go
for i = 2 to n
if n % i == 0
if n / i == 1
go := false
arr.push(i)
label.new(bar_index, high, str.tostring(arr))
else
arr.push(i)
n /= i
break
Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error.
How to solve this?
If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes.
I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found).
🔹 Tokens
A hurdle was to fill the libraries with as many prime numbers as possible.
Initially, the maximum token limit of a library was 80K.
Very recently, that limit was lifted to 100K. Kudos to the TradingView developers!
What are tokens?
Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program.
I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens.
Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function.
In that way, one can experiment with the impact of each code addition in terms of tokens.
For example adding the following code in the library:
export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens.
Some more examples, some are straightforward, others are not )
// adding these lines in one of the arrays results in x tokens
, 1 // 2 tokens
, 111, 111, 111 // 12 tokens
, 1111 // 5 tokens
, 111111111 // 10 tokens
, 1111111111111111111 // 20 tokens
, 1234567890123456789 // 20 tokens
, 1111111111111111111 + 1 // 20 tokens
, 1111111111111111111 + 8 // 20 tokens
, 1111111111111111111 + 9 // 20 tokens
, 1111111111111111111 * 1 // 20 tokens
, 1111111111111111111 * 9 // 21 tokens
, 9999999999999999999 // 21 tokens
, 1111111111111111111 * 10 // 21 tokens
, 11111111111111111110 // 21 tokens
//adding these functions to the library results in x tokens
export f() => 1 // 4 tokens
export f() => v = 1 // 4 tokens
export f() => var v = 1 // 4 tokens
export f() => var v = 1, v // 4 tokens
//adding these functions to the library results in x tokens
export a() => const arraya = array.from(1) // 42 tokens
export a() => arraya = array.from(1) // 42 tokens
export a() => a = array.from(1) // 41 tokens
export a() => array.from(1) // 32 tokens
export a() => a = array.new() // 44 tokens
export a() => a = array.new(), a.push(1) // 56 tokens
What if we could lower the amount of tokens, so we can export more Prime Numbers?
Look at this example:
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
Eight numbers contain the same number 8291.
If we make a function that removes recurrent values, we get fewer tokens!
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
//is transformed to:
829111, 21, 23, 51, 59, 77, 87, 93
The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully.
This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc.
Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less.
The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4.
🔹 Find Prime Numbers
This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values).
To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime.
When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array.
Doing such calculations on one bar will result in a runtime error.
To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar.
This spreads the workload over several bars, making it possible to continue these calculations without a runtime error.
The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values.
These settings adjust the amount of workload per bar:
Max Size: maximum size of Primes array.
Max Bars Runtime: maximum amount of bars where the function is called.
Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers.
Max Iterations Per Bar: maximum loop calculations per bar.
🔹 The End
❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
Hull Moving Average Quantum Pro - Advanced Trading SystemThe Hull Moving Average Quantum Pro is a next-generation technical analysis tool that combines the legendary smoothness of Alan Hull's HMA formula with advanced quantum field visualization technology. This professional-grade indicator features three synchronized Hull Moving Average periods working in harmony to identify high-probability trading opportunities.
🎯 KEY FEATURES:
• Multi-Timeframe HMA Confluence - Triple HMA system (9, 21, 55 periods) for comprehensive trend analysis
• Quantum Field Visualization - Fibonacci-based dynamic support/resistance bands with 0.618, 1.0, and 1.618 ratios
• Energy Flow Momentum - Real-time visual representation of market momentum and directional bias
• Confluence Zone Detection - Automatically highlights areas where multiple HMAs converge for high-probability setups
• Professional Holographic Dashboard - Real-time trend strength, momentum, and market status display
• Three Visual Themes - Dark Intergalactic (Quantum Trading), Light Minimal (Clean Charts), Pro Modern (Low Saturation)
⚡ WHAT MAKES IT UNIQUE:
Unlike traditional moving average indicators, the HMA Quantum Pro eliminates lag while maintaining smoothness, providing traders with faster signals without sacrificing reliability. The quantum field visualization adds a new dimension to price action analysis by creating dynamic zones that adapt to market volatility.
📊 PERFECT FOR:
• Day Trading & Scalping - Fast HMA (9) provides quick entry/exit signals
• Swing Trading - Medium HMA (21) confirms trend continuation
• Position Trading - Slow HMA (55) identifies major trend changes
• All Markets - Forex, Stocks, Crypto, Futures, Indices
🔧 ADVANCED SETTINGS:
• Customizable HMA periods for any trading style
• Adjustable confluence threshold for precision filtering
• Visual intensity control for optimal chart clarity
• Field transparency settings for multi-indicator setups
💡 HOW TO USE:
1. Strong Bullish Signal - All three HMAs aligned upward with price above quantum fields
2. Strong Bearish Signal - All three HMAs aligned downward with price below quantum fields
3. Confluence Zones - High probability reversal/continuation areas
4. Energy Flow - Confirms momentum direction and strength
⭐ FREE VERSION FEATURES:
This free version includes all visual features and calculations. Premium version (coming soon) will add advanced alerts, multi-timeframe analysis, and AI-powered trade suggestions.
Created by professional traders for serious market participants. The Hull Moving Average formula was created by Alan Hull to reduce lag while maintaining smoothness - this indicator enhances that foundation with modern visualization technology.
BTC Correlation PercentagePurpose
This indicator displays the correlation percentage between the current trading instrument and Bitcoin (BTC/USDT) as a text label on the chart. It helps traders quickly assess how closely an asset's price movements align with Bitcoin's fluctuations.
Key Features
Precise Calculation: Shows correlation as a percentage with one decimal place (e.g., 25.6%).
Customizable Appearance: Allows adjustment of colors, position, and calculation period.
Clean & Simple: Displays only essential information without cluttering the chart.
Universal Compatibility: Works on any timeframe and with any trading pair.
Input Settings
Core Parameters:
BTC Symbol – Ticker for Bitcoin (default: BINANCE:BTCUSDT).
Correlation Period – Number of bars used for calculation (default: 50 candles).
Show Correlation Label – Toggle visibility of the correlation label.
Visual Customization:
Text Color – Label text color (default: white).
Background Color – Label background color (default: semi-transparent blue).
Border Color – Border color around the label (default: gray).
Label Position – Where the label appears on the chart (default: top-right).
Interpreting Correlation Values
70% to 100% → Strong positive correlation (asset moves in sync with BTC).
30% to 70% → Moderate positive correlation.
-30% to 30% → Weak or no correlation.
-70% to -30% → Moderate negative correlation (asset moves opposite to BTC).
-100% to -70% → Strong negative correlation.
Practical Use Cases
For Altcoins: A correlation above 50% suggests high dependence on Bitcoin’s price action.
For Futures Trading: Helps assess systemic risks tied to BTC movements.
During High Volatility: Determines whether an asset’s price change is driven by its own factors or broader market trends.
How It Works
The indicator recalculates automatically with each new candle. For the most reliable results, it is recommended for use on daily or higher timeframes.
This tool provides traders with a quick, visual way to gauge Bitcoin’s influence on other assets, improving decision-making in crypto markets. 🚀
This response is AI-generated, for reference only.
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