Order Blocks Zones with Signals█ OVERVIEW
“Order Blocks Zones with Signals” is a technical analysis tool that automatically identifies Order Blocks (OB) and optionally Fair Value Gaps (FVG) on the chart.
The script visualizes these zones as colored rectangles, offering full customization of style, transparency, and signal display.
It also generates entry and exit signals (Break & Exit) that can serve as confirmations in strategies based on price action and market structure.
Thanks to flexible candle size filters and rich visual options, the indicator maintains chart clarity and readability.
█ CONCEPTS
Order Blocks (OB) are key zones on the chart where significant price movements previously occurred — areas where large market participants (institutions, so-called smart money) initiated or closed positions.
An OB is the last candle that followed the prior trend before the market reversed (e.g., for a Bullish OB: the last bearish candle before a pivot low and a strong upward impulse).
The script detects these levels using local price pivots, analyzing candle direction to filter out less significant movements.
FVG (Fair Value Gaps) represent areas of imbalance between buyers and sellers — price gaps formed by a sharp impulse where full trading did not occur due to one-sided order dominance (e.g., excess buy or sell orders).
Why combine OB and FVG in one indicator?
Combining OB and FVG analysis is essential because these phenomena often occur sequentially in the institutional market cycle:
1. Order Block — institutions enter the market in the OB zone, absorbing orders and building positions.
2. Strong impulse — after smart money entry, a rapid price move creates an FVG (imbalance gap).
3. Retest — price naturally returns to these zones (OB or FVG), drawn by unfilled orders and the search for equilibrium.
Such areas strongly attract price, as they represent not only historical institutional levels but also open “holes” in the order book. Retests of OB and FVG are ideal entry opportunities with high reaction probability (rebound or breakout). The indicator combines these two interconnected elements, enabling comprehensive market structure analysis in a single tool.
Order Blocks are labeled as:
Bullish OB – demand zones, often accumulation areas before an upmove.
Bearish OB – supply zones, signaling potential impulse end or correction start.
█ FEATURES
Order Block Detection (OB Detection):
- Automatic identification of demand and supply zones based on pivots.
- OB is the last candle aligned with the prior trend, just before the market reversal — precisely identified through candle sequence analysis around the pivot.
- OB zones appear with a delay equal to Pivot Length (default 10 bars).
- Break signals trigger when a candle’s body (close) fully pierces the zone, causing the zone to disappear immediately (e.g., close < low of Bullish OB → Break Down and zone deletion).
- Minimum size filtering via OB Size Multiplier.
- Option to create OB without wicks (Include Wicks in OB): when disabled, OB zones are based solely on candle bodies (open/close), ignoring wicks (high/low).
Fair Value Gap Detection (FVG Detection):
- Optional, with enable/disable capability.
- FVG are detected without delay — immediately upon gap occurrence.
- Size filtering via Candle Size Period and FVG Size Multiplier.
Customizable Styling:
- Separate colors and border styles (Solid / Dashed / Dotted) for each zone type.
- Adjustable transparency and border thickness.
- Unified color for box, border, and signal of the same type.
Breakout and Exit Signals:
- Break Up – triggered when a candle’s close breaks above a Bearish OB, causing the zone to disappear.
- Break Down – triggered when a candle’s close breaks below a Bullish OB, causing the zone to disappear.
- Exit Up / Exit Down – temporary exit from the zone without full breakout (price leaves the zone but doesn’t close beyond it). Signal type selection: Break, Exit, or Both.
- Alerts: built-in alerts for all signal types — triggered automatically on candle close confirming breakout or exit from OB.
█ HOW TO USE
Adding to chart: import the code into Pine Editor and run the script on TradingView.
Settings configuration:
- Pivot Length: controls swing detection sensitivity and OB display delay (default 10).
- Include Wicks in OB: enabled (default) – OB includes wicks; disabled – OB uses bodies only.
- Size Filter: adjust Candle Size Period and OB/FVG Size Multiplier to filter out small zones.
- Colors & Styles: set colors, styles, and transparency for each zone type.
- Signal Type: choose which signals to display (Break, Exit, or Both).
Signal interpretation:
- OB Break Up: price closes above Bearish OB → zone disappears → potential bullish continuation.
- OB Break Down: price closes below Bullish OB → zone disappears → potential bearish continuation.
- Exit Signals: price leaves the zone temporarily without breakout — often signals impending reversal or pullback.
Tips:
- Use OB signals alongside other indicators like RSI, MACD, SMI, or trend filters.
- Order Blocks from higher timeframes (e.g., 4H, 1D) carry greater significance and reaction strength.
- Remember: FVG are detected immediately, OB with delay — a complementary approach!
█ APPLICATIONS
- Smart Money Concepts (SMC): use OB zones as dynamic support and resistance levels. In an uptrend, look for buy opportunities in bullish OBs, which price often retests before further gains. Combining with RSI, MACD, or Fibonacci levels enhances zone significance, confirming institutional demand.
- Breakout Trading: trade based on OB breakout signals. A buy signal after breaking a bearish OB may indicate a strong upward impulse, especially if supported by rising MACD or RSI above 50. Similarly for sell signals after Break Down.
- Reversal Zones: Exit signals may indicate the end of a move or correction. Safest to use in alignment with higher-timeframe trend and confirmed by another indicator (e.g., RSI divergence, Fibonacci levels).
- Confluence Analysis: combine OB and FVG for deeper market structure and equilibrium insight. When an Order Block overlaps or borders an FVG, we get confluence of two institutional phenomena — OB (smart money entry) + FVG (imbalance) — making these areas particularly strong price magnets, increasing retest and reaction probability.
█ NOTES
- FVG can be fully disabled for a cleaner chart view.
- In consolidation periods, signals may appear more frequently — always confirm with additional trend filters.
- Works on all markets and timeframes (crypto, forex, indices, stocks).
指标和策略
Funded Gang IndiciCustomized indicator to detect the opening bias of Indexes.
Timeframe 14:30 - 15:30
Mirpapa_Lib_boxLibrary   "Mirpapa_Lib_box" 
 AddFVG(boxes, htfTimeframe, htfBarIndex, top, bottom, isBull, _text) 
  AddFVG
@description FVG 박스 데이터 추가
  Parameters:
     boxes (array) : array 박스 배열
     htfTimeframe (string) : string HTF 시간대 ("60", "240", "D")
     htfBarIndex (int) : int HTF bar_index
     top (float) : float 상단 가격
     bottom (float) : float 하단 가격
     isBull (bool) : bool 방향 (true=상승, false=하락)
     _text (string) 
  Returns: void
 AddOB(boxes, htfTimeframe, htfBarIndex, top, bottom, isBull, _text) 
  AddOB
@description OB 박스 데이터 추가
  Parameters:
     boxes (array) : array 박스 배열
     htfTimeframe (string) : string HTF 시간대
     htfBarIndex (int) : int HTF bar_index
     top (float) : float 상단 가격
     bottom (float) : float 하단 가격
     isBull (bool) : bool 방향
     _text (string) 
  Returns: void
 AddBB(boxes, htfTimeframe, htfBarIndex, top, bottom, isBull, _text) 
  AddBB
@description BB 박스 데이터 추가
  Parameters:
     boxes (array) : array 박스 배열
     htfTimeframe (string) : string HTF 시간대
     htfBarIndex (int) : int HTF bar_index
     top (float) : float 상단 가격
     bottom (float) : float 하단 가격
     isBull (bool) : bool 방향
     _text (string) 
  Returns: void
 AddRB(boxes, htfTimeframe, htfBarIndex, top, bottom, isBull, _text) 
  AddRB
@description RB 박스 데이터 추가
  Parameters:
     boxes (array) : array 박스 배열
     htfTimeframe (string) : string HTF 시간대
     htfBarIndex (int) : int HTF bar_index
     top (float) : float 상단 가격
     bottom (float) : float 하단 가격
     isBull (bool) : bool 방향
     _text (string) 
  Returns: void
 ProcessBoxes(boxes, boxType, colorBull, colorBear, closeCount, useLine, textAlignH, textAlignV, closeColor) 
  ProcessBoxes
@description 박스 배열 처리 (생성→확장→터치→종료)
  Parameters:
     boxes (array) : array 박스 배열
     boxType (string) : string 박스 타입 ("FVG", "OB", "BB", "RB")
     colorBull (color) : color 상승 색상
     colorBear (color) : color 하락 색상
     closeCount (int) : int 터치 종료 횟수
     useLine (bool) : bool 중간라인 사용 여부
     textAlignH (string) : string 수평 정렬
     textAlignV (string) : string 수직 정렬
     closeColor (color) : color 종료 색상
  Returns: void
 GetActiveBoxCount(boxes) 
  GetActiveBoxCount
@description 활성 박스 개수 반환
  Parameters:
     boxes (array) : array 박스 배열
  Returns: int 활성 박스 개수
 ClearInactiveBoxes(boxes) 
  ClearInactiveBoxes
@description 비활성 박스 제거 (메모리 절약)
  Parameters:
     boxes (array) : array 박스 배열
  Returns: void
 BoxData 
  BoxData
  Fields:
     _isActive (series bool) : 박스 활성화 상태
     _isBull (series bool) : 방향 (true=상승, false=하락)
     _boxTop (series float) : 상단 가격
     _boxBot (series float) : 하단 가격
     _basePoint (series float) : 터치 감지 기준점
     _stage (series int) : 터치 횟수 카운터
     _type (series string) : 박스 타입 ("FVG", "OB", "BB", "RB")
     _htfTimeframe (series string) : HTF 시간대 ("60", "240", "D")
     _htfBarIndex (series int) : HTF 기준 bar_index
     _text (series string) : 사용자 추가 텍스트
     _box (series box) : 박스 객체 (ProcessBoxes에서 생성)
     _line (series line) : 라인 객체 (ProcessBoxes에서 생성)
AutoPivot Levels with Alerts [ChartWhizzperer] – Dynamic EditionAuto-Pivot Levels 4 methods with alerts   – Dynamic Edition 
Now with
- Live Mode
- 4 Pivot Methods
- 7 Session Types (5m, 15m, 30m, Hourly, Daily, Weekly, Monthly)
- PineConnector-Ready Alerts!
Free, Open Source, Pine Script v6-compliant.
NEW: Live Mode (Ultra-Dynamic, Repainting) – Switchable in UI!
Instantly switch between Classic (session-based, repaint-free) and Live (rolling window, real-time, repainting) using the simple checkbox in the settings!
Live Mode recalculates all pivots on every tick/bar, using the current high/low/close for the chosen session (5m, 15m, 30m, hourly, daily, weekly, monthly).
 Perfect for: 
- Scalping and high-frequency trading
- Real-time bot/automation setups (PineConnector-ready)
- Fast-moving or breakout markets
Classic Mode: For traditional, stable levels based on confirmed session data – ideal for backtesting and trading history.
 Four Calculation Methods (Choose What Fits YOU) 
1.  Classic 
   Standard pivot calculation.
   Based on previous session’s High, Low, Close.
   Simple, proven, and suitable for any asset.
2.  Fibonacci 
   Projects levels using Fibonacci ratios of the prior session’s range.
   Great for traders who want to align pivots with fib retracements and extensions.
3.  Camarilla 
   Uses unique multipliers for support/resistance, focusing on mean reversion and volatility.
   Popular among futures and forex day traders.
4.  Woodie 
   Puts extra weight on previous Close for more responsive pivots.
   Often used in trending or choppy conditions.
Switch methods anytime  in the UI  – the script recalculates instantly and keeps your chart clean!
 Level-Specific Alerts – PineConnector Ready! 
Dedicated alert for EVERY level and direction (Up/Down):
 Pivot (P), R1, R2, R3, S1, S2, S3 
 No configuration hassle: 
All alerts are pre-defined in the TradingView Alert Panel and work across all session types (5m → monthly).
 Machine-readable message format: 
PIVOT=R1 DIR=UP SYMBOL={{ticker}} PRICE={{close}}
Direct plug-and-play with PineConnector, webhooks, Discord, Telegram, bots, and other automation tools.
 Never miss a breakout, reversal, or key support/resistance touch! 
 Powerful Customization & Performance 
- Session selection: 5m, 15m, 30m, Hourly, Daily, Weekly, Monthly (choose what suits your trading style).
- Show/hide any level (Pivot, R1–R3, S1–S3) for minimal chart clutter.
- Color selection for each level to match your theme or highlight key pivots.
- Auto-cleanup: Old lines and labels are cleared on every recalculation or session change for maximum performance and visual clarity.
- Zero runtime errors: Strict Pine Script v6 practices for stability.
 How To Use – Quick Start 
1) Add the indicator to your TradingView chart.
2) Pick your calculation method (Classic, Fibonacci, Camarilla, Woodie).
3) Set session type (5m, 15m, 30m, Hourly, Daily, Weekly, Monthly).
4) Switch between Classic and Live Mode with a single click in settings.
5) Customize your levels (on/off, colors).
6) Open the Alert Panel, select any pre-configured alert (e.g. "R2 Cross Down"), and go live!
7) Connect with PineConnector or any webhook system instantly using the pre-formatted alert messages.
 Who Is It For? 
- Active scalpers & bot traders: Live Mode + PineConnector-ready alerts = instant, automated reactions.
- Swing and position traders: Use Classic Mode for stable, repaint-free levels.
- Strategy developers: Seamless integration into automated and manual trading workflows.
 License & Community 
Open Source, Non-Commercial:
Free for personal & educational use under CC BY-NC-SA 4.0.
 Feedback, bug reports & ideas: 
Drop a comment, or contact me for feature requests.
Trade smart. Trade dynamic. Unlock the true power of pivots – with ChartWhizzperer!
Aperturas Semanales Precisas (corregido)Identifica aperturas semanales del precio y resalta aperturas mensuales
PARTH Gold Profit IndicatorWhat's Inside:
✅ What is gold trading (XAU/USD explained)
✅ Why trade gold (5 major reasons)
✅ How to make money (buy/sell mechanics)
✅ Complete trading setup using your indicator
✅ Entry rules (when to buy/sell with examples)
✅ Risk management (THE MOST IMPORTANT)
✅ Best trading times (London-NY overlap)
✅ 3 trading styles (scalping, swing, position)
✅ 6 common mistakes to avoid
✅ Realistic profit expectations
✅ Pre-trade checklist
✅ Step-by-step getting started guide
✅ Everything a beginner need
Apertura SemanalIdentifica las aperturas semanales de cada grafico y resalta las aperturas mensuales
21 SMA over 200 SMA Bullish Cross Highlighter21 SMA Over 200 SMA — Momentum Cross for BTC Scalpers
A precise and lightweight indicator designed to highlight when short-term momentum aligns with the broader Bitcoin trend.
It visualizes when the 21-period Simple Moving Average (SMA) crosses above the 200-period SMA, often signaling the beginning of a sustained directional move — especially effective on the 1-minute BTC chart during trending market conditions.
Core Concept
When the 21 SMA crosses above the 200 SMA on Bitcoin during an active uptrend, the probability increases that price will continue rising as short-term traders and algorithms join the move.
This indicator helps you identify that momentum shift in real time and react before the breakout gains full traction.
Features
Clear visual label for every bullish cross (21↑200)
Optional bearish cross labels (21↓200)
Optimized for 1m, 5m, and 15m BTC charts
Lightweight and efficient — ideal for multi-chart scalping layouts
Built-in alert conditions for manual alert setup
Excellent synergy with VRVP (Visible Range Volume Profile) for confirming volume-based breakout zones
Suggested Use
Focus on the 1-minute Bitcoin chart for early signals.
When a bullish cross appears, use VRVP to locate high-volume nodes or breakout levels for precise entries.
Confirm alignment on 5m or 15m charts before executing.
Combine with RSI, Stoch RSI, or volume analysis to refine timing and manage risk.
Trading Insight
The 21/200 SMA relationship has long been a trusted tool for trend identification.
When both averages slope upward and the cross occurs above a strong VRVP volume zone, it often marks the start of a new impulsive leg in BTC ideal for short-term scalps or the first confirmation of a broader trend continuation.
Created for disciplined BTC scalpers who value structured setups, clarity, and confirmation through data rather than noise.
Gold 15m: Trend + S/R + Liquidity Sweep (RR 1:2)This strategy is designed for short-term trading on XAUUSD (Gold) using the 15-minute timeframe. It combines trend direction, support/resistance pivots, liquidity sweep detection, and momentum confirmation to identify high-probability reversal setups in line with the dominant market trend.
⚙️ Core Logic:
Trend Filter (EMA 200):
The strategy only takes long positions when price is above the 200 EMA and short positions when price is below it.
Support/Resistance via Pivots:
Dynamic swing highs and lows are identified using pivot points. These act as local supply and demand levels where liquidity is likely to accumulate.
Liquidity Sweep Detection:
A bullish liquidity sweep occurs when price briefly breaks below the last pivot low (grabbing liquidity) and then closes back above it.
A bearish sweep occurs when price breaks above the last pivot high and then closes back below.
Momentum & Candle Strength:
The strategy filters signals based on candle range and body size to ensure entries occur during strong price reactions, not weak retracements.
Risk Management (1:2 RR):
Stop-loss is placed slightly beyond the last pivot level using ATR-based buffers, and take-profit is set at 2× the risk distance, maintaining a reward-to-risk ratio of 1:2.
💼 Trade Logic Summary:
Long Entry:
After a bullish liquidity sweep & reclaim, momentum confirmation, and trend alignment (above EMA 200).
Short Entry:
After a bearish sweep & reclaim, momentum confirmation, and trend alignment (below EMA 200).
Exit:
Automated via ATR-based Stop Loss and Take Profit targets.
📊 Customization Options:
Adjustable EMA length, pivot settings, ATR multipliers, and RR ratio.
Option to enable/disable trend filter.
Toggle display of S/R zones on chart.
🧠 Best Use:
Works best during London and New York sessions when Gold shows strong momentum.
Can be adapted for forex pairs and indices by tuning ATR and pivot parameters.
INDIAN INTRADAY BEASTThe Indian Intraday Beast is a precision-built intraday strategy optimized for the 15-minute timeframe.
It captures high-probability momentum shifts and trend reversals using adaptive price-action logic and proprietary confirmation filters.
Designed for traders who demand clarity, speed, and consistency in India’s fast-paced markets.
Dynamic Fractal Flow [Alpha Extract]An advanced momentum oscillator that combines fractal market structure analysis with adaptive volatility weighting and multi-derivative calculus to identify high-probability trend reversals and continuation patterns. Utilizing sophisticated noise filtering through choppiness indexing and efficiency ratio analysis, this indicator delivers entries that adapt to changing market regimes while reducing false signals during consolidation via multi-layer confirmation centered on acceleration analysis, statistical band context, and dynamic omega weighting—without any divergence detection.
🔶 Fractal-Based Market Structure Detection
Employs Williams Fractal methodology to identify pivotal market highs and lows, calculating normalized price position within the established fractal range to generate oscillator signals based on structural positioning. The system tracks fractal points dynamically and computes relative positioning with ATR fallback protection, ensuring continuous signal generation even during extended trending periods without fractal formation.
🔶 Dynamic Omega Weighting System
Implements an adaptive weighting algorithm that adjusts signal emphasis based on real-time volatility conditions and volume strength, calculating dynamic omega coefficients ranging from 0.3 to 0.9. The system applies heavier weighting to recent price action during high-conviction moves while reducing sensitivity during low-volume environments, mitigating lag inherent in fixed-period calculations through volatility normalization and volume-strength integration.
🔶 Cascading Robustness Filtering
Features up to five stages of progressive EMA smoothing with user-adjustable robustness steps, each layer systematically filtering microstructure noise while preserving essential trend information. Smoothing periods scale with the chosen fractal length and robustness steps using a fixed smoothing multiplier for consistent, predictable behavior.
🔶 Adaptive Noise Suppression Engine
Integrates dual-component noise filtering combining Choppiness Index calculation with Kaufman’s Efficiency Ratio to detect ranging versus trending market conditions. The system applies dynamic damping that maintains full signal strength during trending environments while suppressing signals during choppy consolidation, aligning output with the prevailing regime.
🔶 Acceleration and Jerk Analysis Framework
Calculates second-derivative acceleration and third-derivative jerk to identify explosive momentum shifts before they fully materialize on traditional indicators. Detects bullish acceleration when both acceleration and jerk turn positive in negative oscillator territory, and bearish acceleration when both turn negative in positive territory, providing early entry signals for high-velocity trend initiation phases.
🔶 Multi-Layer Signal Generation Architecture
Combines three primary signal types with hierarchical validation: acceleration signals, band crossover entries, and threshold momentum signals. Each signal category includes momentum confirmation, trend-state validation, and statistical band context; signals are further conditioned by band squeeze detection to avoid low-probability entries during compression phases. Divergence is intentionally excluded for a purely structure- and momentum-driven approach.
🔶 Dynamic Statistical Band System
Utilizes Bollinger-style standard deviation bands with configurable multiplier and length to create adaptive threshold zones that expand during volatile periods and contract during consolidation. Includes band squeeze detection to identify compression phases that typically precede expansion, with signal suppression during squeezes to prevent premature entries.
🔶 Gradient Color Visualization System
Features color gradient mapping that dynamically adjusts line intensity based on signal strength, transitioning from neutral gray to progressively intense bullish or bearish colors as conviction increases. Includes gradient fills between the signal line and zero with transparency scaling based on oscillator intensity for immediate visual confirmation of trend strength and directional bias.
All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.
FluidTrades - SMC Lite - AlertsThe FluidTrades - SMC Lite indicator has been fixed, now you can send notifications when price levels are indicated.
Multi Pivot Trend [BigBeluga]🔵 OVERVIEW   
The  Multi Pivot Trend   is an advanced market-structure-driven trend engine that evaluates trend strength by scanning multiple pivot breakouts simultaneously.  
Instead of relying on a single swing length, it tracks breakouts across ten increasing pivot lengths — then averages their behavior to produce a smooth, reliable trend reading.  
Mitigation logic (close, wick, or HL2 touches) controls how breakouts are confirmed, giving traders institutional-style flexibility similar to BOS/CHoCH validation rules.
This indicator not only colors candles based on trend strength, but also extends trend strength and volatility-scaled projection candles to show where trend pressure may expand next.  
Pivot breakout lines and labels mark key changes, making the trend transitions extremely clear.
 🔵 CONCEPTS   
 
  Market trend strength is reflected by multiple pivot breakouts, not just one.
  
  The indicator analyzes ten pivot structures from smaller to larger swings.
  
  Each bullish or bearish pivot breakout contributes to trend score.
  
  Mitigation options (close / wick / HL2) imitate smart-money breakout confirmation logic.
  
  Trend score is averaged and translated into colors and extension bars.
  
  Neutral regime ≈ weak trend or transition zone (trend compression).
  
 
 🔵 FEATURES   
 
   Multi-Pivot Engine  — tracks 10 pivot-based trend signals simultaneously.
   Mitigation Modes :  
   • Close — breakout requires candle close beyond pivot  
   • Wicks — breakout requires wick violation  
   • HL2 — breakout confirmed when average (H+L)/2 crosses level  
   Dynamic Color System :  
   • Blue → confirmed bullish rotation  
   • Red → confirmed bearish rotation  
   • Orange → neutral / transition state  
   Breakout Visualization  — draws pivot breakout lines in real-time.
   Trend Labels  — prints trend %.
  
   Trend Volatility-Scaled Extension Candles  — ATR/trend strength based candle projections show momentum continuation strength.
  
   Gradient Pivot Encoding  — higher pivot lengths = deeper structure considered.
  
 
 🔵 HOW TO USE   
 
  Use strong blue/red periods to follow dominant structural trend.
  
  Watch for color transition into orange — possible trend change or consolidation.
  
  Pivot breakout lines help validate structure shifts without clutter.
  Wick mitigation catches aggressive liquidity-sweep based breaks.
  Close/HL2 mitigation catches cleaner market structure rotations.
  Extension bars visualize trend pressure — large extensions = strong push.
  Best paired with volume or volatility confirmation tools.
 
 🔵 CONCLUSION   
The  Multi Pivot Trend   is a structural trend recognition system that blends multiple pivot breakouts into one clean trend score — with institutional-style mitigation logic and volatility-projected trend extensions.  
It gives traders a powerful, visually intuitive way to track momentum, spot trend rotations early, and understand true structural flow beyond simple MA-based approaches.  
Use it to stay aligned with the dominant swing direction while avoiding noise and false flips.  
mysourcetypesncsLibrary   "mysourcetypes" 
Libreria personale per sorgenti estese (Close, Open, High, Low, Median, Typical, Weighted, Average, Average Median Body, Trend Biased, Trend Biased Extreme, Volume Body, Momentum Biased, Volatility Adjusted, Body Dominance, Shadow Biased, Gap Aware, Rejection Biased, Range Position, Adaptive Trend, Pressure Balanced, Impulse Wave)
 rclose() 
  Regular Close
  Returns: Close price
 ropen() 
  Regular Open
  Returns: Open price
 rhigh() 
  Regular High
  Returns: High price
 rlow() 
  Regular Low
  Returns: Low price
 rmedian() 
  Regular Median (HL2)
  Returns: (High + Low) / 2
 rtypical() 
  Regular Typical (HLC3)
  Returns: (High + Low + Close) / 3
 rweighted() 
  Regular Weighted (HLCC4)
  Returns: (High + Low + Close + Close) / 4
 raverage() 
  Regular Average (OHLC4)
  Returns: (Open + High + Low + Close) / 4
 ravemedbody() 
  Average Median Body
  Returns: (Open + Close) / 2
 rtrendb() 
  Trend Biased Regular
  Returns: Trend-weighted price
 rtrendbext() 
  Trend Biased Extreme
  Returns: Extreme trend-weighted price
 rvolbody() 
  Volume Weighted Body
  Returns: Body midpoint weighted by volume intensity
 rmomentum() 
  Momentum Biased
  Returns: Price biased towards momentum direction
 rvolatility() 
  Volatility Adjusted
  Returns: Price adjusted by candle's volatility
 rbodydominance() 
  Body Dominance
  Returns: Emphasizes body over wicks
 rshadowbias() 
  Shadow Biased
  Returns: Price biased by shadow length
 rgapaware() 
  Gap Aware
  Returns: Considers gap between candles
 rrejection() 
  Rejection Biased
  Returns: Emphasizes price rejection levels
 rrangeposition() 
  Range Position
  Returns: Where close sits within the candle range (0-100%)
 radaptivetrend() 
  Adaptive Trend
  Returns: Adapts based on recent trend strength
 rpressure() 
  Pressure Balanced
  Returns: Balances buying/selling pressure within candle
 rimpulse() 
  Impulse Wave
  Returns: Detects impulsive moves vs corrections
Option Buying Strategy By Raj PandyaThis strategy is designed for intraday trading on BankNifty using a powerful confluence of trend, structure and momentum. It combines the 9-period Exponential Moving Average (EMA) with Daily Traditional Pivot Points to identify high-probability breakout trades.
A Long (CALL) signal is generated when price crosses and closes above both the 9 EMA and the Daily Pivot Point (PP), confirming upward trend strength. A Short (PUT) signal triggers when price crosses and closes below the 9 EMA and PP, signaling downside momentum. To reduce false signals, the strategy uses RSI with a moving average filter to ensure momentum aligns with price action.
Risk management is built-in with previous candle high/low stop-loss, a fixed 50-point target, and an automatic trailing stop system to protect profits on trending days. This helps capitalize on strong momentum while managing risk effectively.
This strategy works best on the 5-minute timeframe and is optimized for BankNifty futures/options. It aims to capture clean directional moves around key intraday value levels used by institutional traders.
MTF Multi EMA - IntradayMTF Multi EMA – Intraday
Purpose:
To quickly analyze trend direction and alignment across multiple timeframes (1m, 3m, 5m, 15m, 30m, and 60m) using fast and slow EMAs for each timeframe — and combine them into a simple “stack score” for easy visual decision-making. The script is tuned for Intraday Trading indicator by default.
Concept
Each timeframe (TF) — like 1m, 3m, 5m, etc. — has two EMAs:
A fast EMA (shorter length)
A slow EMA (longer length)
When the fast EMA > slow EMA, that timeframe is bullish.
When the fast EMA < slow EMA, that timeframe is bearish.
By combining multiple timeframes together, the indicator helps you:
Identify when all trends align bullishly (strong buy bias)
Identify when all trends align bearishly (strong sell bias)
Stay out during mixed or sideways phases
Inputs Explained
Setting	Description
1m / 3m / 5m / 15m / 30m / 60m EMA Lengths	Controls the EMA period for each timeframe’s fast and slow EMAs.
Fast EMA Color	Color for all fast EMAs plotted on chart.
Slow EMA Color	Color for all slow EMAs plotted on chart.
Use Smooth Interpolation	Ensures smoother plots when merging higher TF data into a smaller chart (recommended ON).
Show  	Toggle visibility of each timeframe’s EMAs.
Table Position	Lets you move the mini dashboard to any chart corner.
Stack Score
The Stack Score measures how many timeframes are bullish vs bearish:
Stack Score	Meaning
+6	All timeframes bullish → Strong Uptrend
+3 to +5	Majority bullish → Bullish Bias
0	Neutral / Mixed → Sideways Market
−3 to −5	Majority bearish → Bearish Bias
−6	All timeframes bearish → Strong Downtrend
Table Display
At the chosen chart corner, you’ll see:
TF	Direction
1m	🟢 B (Bullish) / 🔴 S (Bearish)
3m	🟢 B (Bullish) / 🔴 S (Bearish)
5m	🟢 B (Bullish) / 🔴 S (Bearish)
15m	🟢 B (Bullish) / 🔴 S (Bearish)
30m	🟢 B (Bullish) / 🔴 S (Bearish)
60m	🟢 B (Bullish) / 🔴 S (Bearish)
Score	Final alignment score (color-coded)
Color meanings:
🟢 Green cell = bullish for that TF
🔴 Red cell = bearish for that TF
The Score cell background color changes with strength:
Bright green → strong bull
Yellow → neutral
Red / Maroon → strong bear
How to Use for Trading (Intraday NIFTY 5m)
Recommended Chart: 5-minute timeframe on NIFTY Futures or major index stocks.
🔹 1. Identify Trend Alignment
When Score ≥ +3 → Market bias is bullish.
→ Look for long entries (buy breakouts or EMA retests).
When Score ≤ −3 → Market bias is bearish.
→ Look for short entries (sell breakdowns or retests).
When Score is between −2 and +2 → Trend is mixed.
→ Best to wait — avoid trading in choppy conditions.
🔹 2. Combine with Price Action
Use it with:
Trendline breaks or retests
Candle confirmation (e.g. bullish engulfing or rejection)
Volume surge
Example:
On NIFTY 5m — if score = +5, price breaks above a descending trendline, and 1m–15m EMAs are all rising → strong long signal.
🔹 3. Avoid Conflicts
If lower timeframes (1m/3m/5m) are bullish but higher ones (30m/60m) are bearish,
→ Trend is short-term bullish but larger bias is down — scalps only, not swings.
Optional Alerts
If you add alert conditions (as suggested earlier):
“Strong Bullish Alignment” triggers when score ≥ +5
“Strong Bearish Alignment” triggers when score ≤ −5
This gives you early alerts when full trend alignment occurs — ideal for breakout setups.
Some more Tips
Use 5m or 15m chart as your main view.
Use Stack Score as a trend filter — trade with it, not against it.
Combine with Breakout + Retest strategy or Trendline color-coded system you’re building.
In sideways days (score near 0), reduce risk or skip trades.
Serenity Model VIPI — by yuu_iuHere’s a concise, practical English guide for Serenity Model VIPI (Author: yuu_iu). It covers what it is, how to set it up for daily trading, how to tune it, and how we guarantee non-repainting.
Serenity Model VIPI — User Guide (Daily Close, Non‑Repainting)
Credits
- Author: yuu_iu
- Producer: yuu_iu
- Platform: TradingView (Pine Script v5)
1) What it is
Serenity Model VIPI is a multi‑module, context‑aware trading model that fuses signals from:
- Entry modules: VCP, Flow, Momentum, Mean Reversion, Breakout
- Exit/risk modules: Contrarian, Breakout Sell, Volume Delta Sell, Peak Detector, Overbought Exit, Profit‑Take
- Context/memory: Learns per Ticker/Sector/Market Regime and adjusts weights/aggression
- Learning engine: Runs short “fake trades” to learn safely before scaling real trades
It produces a weighted, context‑adjusted score and a final decision: BUY, SELL, TAKE_PROFIT, or WAIT.
2) How it works (high level)
- Each module computes a score per bar.
- A fusion layer combines module scores using accuracy and base weights, then adjusts by:
  - Market regime (Bull/Bear/Sideways) and optional higher‑timeframe (HTF) bias
  - Risk control neuron
  - Context memory (ticker/sector/regime)
- Optional LLM mode can override marginal cases if context supports it.
- Final decision is taken at bar close only (no intrabar repaint).
3) Non‑repainting guarantee (Daily)
- Close‑only execution: All key actions use barstate.isconfirmed, so signals/entries/exits only finalize after the daily candle closes.
- No lookahead on HTF data: request.security() reads prior‑bar values (series ) for HTF close/EMA/RSI.
- Alerts at bar close: Alerts are fired once per bar close to prevent mid‑bar changes.
What this means: Once the daily bar closes, the decision and alert won’t be repainted.
4) Setup (TradingView)
- Paste the Pine v5 code into Pine Editor, click Add to chart.
- Timeframe: 1D (Daily).
- Optional: enable a date window for training/backtest
  - Enable Custom Date Filter: ON
  - Set Start Date / End Date
- Create alert (non‑repainting)
  - Condition: AI TRADE Signal
  - Options: Once Per Bar Close
  - Webhook (optional): Paste your URL into “System Webhook URL (for AI events)”
- Watch the UI
  - On‑chart markers: AI BUY / AI SELL / AI TAKE PROFIT
  - Right‑side table: Trades, Win Rate, Avg Profit, module accuracies, memory source, HTF trend, etc.
  - “AI Thoughts” label: brief reasoning and debug lines.
5) Daily trading workflow
- The model evaluates at daily close and may:
  - Enter long (BUY) when buy votes + total score exceed thresholds, after context/risk checks
  - Exit via trailing stop, hard stop, TAKE_PROFIT, or SELL decision
- Learning mode:
  - Triggers short “fake trades” every N bars (default 3) and measures outcome after 5 bars
  - Improves module accuracies and adjusts aggression once stable (min fake win% threshold)
- Memory application:
  - When you change tickers, the model tries to apply Ticker or Sector memory for the current market regime to pre‑bias module weights/aggression.
6) Tuning (what to adjust and why)
Core controls
- Base Aggression Level (default 1.0): Higher = more trades and stronger decisions; start conservative on Daily (1.0–1.2).
- Learning Speed Multiplier (default 3): Faster adaptation after fake/real trades; too high can overreact.
- Min Fake Win Rate to Exit Learning (%) (default 10–20%): Raises the bar before trusting more real trades.
- Fake Trade Every N Bars (default 3): Frequency of learning attempts.
- Learning Threshold Win Rate (default 0.4): Governs when the learner should keep learning.
- Hard Stop Loss (%) (default 5–8%): Global emergency stop.
Multi‑Timeframe (MTF)
- Enable Multi‑Timeframe Confirmation: ON (recommended for Daily)
- HTF Trend Source: HOSE:VNINDEX for VN equities (or CURRENT_SYMBOL if you prefer)
- HTF Timeframe: D or 240 (for a strong bias)
- MTF Weight Adjustment: 0.2–0.4 (0.3 default is balanced)
Module toggles and base weights
- In strong uptrends: increase VCP, Momentum, Breakout (0.2–0.3 typical)
- In sideways low‑vol regimes: raise MeanRev (0.2–0.3)
- For exits/defense: Contrarian, Peak, Overbought Exit, Profit‑Take (0.1–0.2 each)
- Keep Flow on as a volume‑quality filter (≈0.2)
Memory and control
- Enable Shared Memory Across Tickers: ON to share learning
- Enable Sector‑Based Knowledge Transfer: ON to inherit sector tendencies
- Manual Reset Learning: Use sparingly to reset module accuracies if regime changes drastically
Risk management
- Hard Stop Loss (%): 5–8% typical on Daily
- Trailing Stop: ATR‑ and volatility‑adaptive; tightens faster in Bear/High‑Vol regimes
- Max hold bars: Shorter in Bear or Sideways High‑Vol to cut risk
Alerts and webhook
- Use AI TRADE Signal with Once Per Bar Close
- Webhook payload is JSON, including event type, symbol, time, win rates, equity, aggression, etc.
7) Recommended Daily preset (VN equities)
- MTF: Enable, Source: HOSE:VNINDEX, TF: D, Weight Adj: 0.3
- Aggression: 1.1
- Learning Speed: 3
- Min Fake Win Rate to Exit Learning: 15%
- Hard SL: 6%
- Base Weights:
  - VCP 0.25, Momentum 0.25, Breakout 0.15, Flow 0.20
  - MeanRev 0.20 (raise in sideways)
  - Contrarian/Peak/Overbought/Profit‑Take: 0.10–0.20
- Leave other defaults as is, then fine‑tune by symbol/sector.
8) Reading the UI
- Table highlights: Real Trades, Win Rate, Avg Profit, Fake Actions/Win%, VCP Acc, Aggression, Equity, Score, Status (LEARNING/TRADING/REFLECTION), Last Real, Consec Loss, Best/Worst Trade, Pattern Score, Memory Source, Current Sector, AI Health, HTF Trend, Scheduler, Memory Loaded, Fake Active.
- Shapes: AI BUY (below bar), AI SELL/TAKE PROFIT (above bar)
- “AI Thoughts”: module contributions, context notes, debug lines
9) Troubleshooting
- No trades?
  - Ensure timeframe is 1D and the date filter covers the chart range
  - Check Scheduler Cooldown (3 bars default) and that barstate.isconfirmed (only at close)
  - If MTF is ON and HTF is bearish, buy bias is reduced; relax MTF Weight Adjustment or module weights
- Too many/too few trades?
  - Lower/raise Base Aggression Level
  - Adjust base weights on key modules (raise entry modules to be more active; raise exit/defense modules to be more selective)
- Learning doesn’t end?
  - Increase Min Fake Win Rate to Exit Learning only after it’s consistently stable; otherwise lower it or reduce Fake Trade Every N Bars
10) Important notes
- The strategy is non‑repainting at bar close by design (confirmed bars + HTF series  + close‑only alerts).
- Backtest fills may differ from live fills due to slippage and broker rules; this is normal for all TradingView strategies.
- Always validate settings across multiple symbols and regimes before going live.
If you want, I can bundle this guide into a README section in your Pine code and add a small on‑chart signature (Author/Producer: yuu_iu) in the top‑right corner.
RSI with SMA + 70/60/50/40/30 LevelsIndicator Name:
RSI with SMA + 70/60/50/40/30 Levels
🧩 Concept Overview:
यह indicator दो popular tools को combine करता है:
RSI (Relative Strength Index) – momentum indicator जो market ke overbought aur oversold zones ko identify karta hai.
SMA (Simple Moving Average) – trend smoother jo RSI ke movement ko average karke lagging confirmation deta hai.
इन दोनों के साथ 70, 60, 50, 40, और 30 की multiple reference lines draw की जाती हैं, ताकि trader को RSI ke swings aur reversals easily samajh aaye.
⚙️ Indicator Components:
RSI Line:
Default Period: 14 (customize kar sakte ho).
Show karta hai price momentum – agar RSI 70 ke upar jaata hai to market overbought zone me hota hai; agar 30 ke niche jaata hai to oversold zone me.
SMA on RSI:
RSI ka smooth version (usually 9-period SMA).
Trend confirmation ke liye – jab RSI line SMA ke upar cross karti hai to bullish signal, aur neeche cross kare to bearish signal.
Horizontal Levels:
70: Overbought zone (potential sell area).
60: Strong bullish momentum line (trend confirmation).
50: Neutral / midline (trend direction flip area).
40: Weak bearish zone (trend losing strength).
30: Oversold zone (potential buy area).
💡 How to Use:
Trend Identification:
RSI > 60 aur SMA ke upar → Bullish trend.
RSI < 40 aur SMA ke neeche → Bearish trend.
Reversal Spotting:
RSI 70 ke upar jaake wapas niche aaye → Sell signal.
RSI 30 ke neeche jaake wapas upar aaye → Buy signal.
Confirmation Using SMA:
RSI cross SMA from below → Confirmed bullish reversal.
RSI cross SMA from above → Confirmed bearish reversal.
Balanced Delta Volume Profile (Zeiierman)█  Overview 
 Balanced Delta Volume Profile (Zeiierman)  builds a vertical, price-by-price profile that blends total participation with balance quality. Instead of plotting raw volume alone, it weights each price bin by: 
 
 how balanced buyers vs. sellers were, 
 how compressed price was inside that bin, 
 how often price revisited it. 
 
The result spotlights fair value and acceptance zones while still revealing momentum/imbalance areas—ideal for reading rotation vs. trend, continuation vs. exhaustion, and the prices that truly matter.
   
 Highlights 
 
 Balanced score that fuses delta symmetry, price compression, and hit frequency.
 Optional heat spectrum for instant read of participation density and balance strength.
 POC-like auto highlight of the dominant price level within the lookback window.
 Works across timeframes for session profiling, swing context, or regime shifts.
 
█  How It Works 
 ⚪ Profile Construction 
The script scans a fixed History Length and divides the full high–low span into Bin Count price bins. For every bar in the window, its volume is proportionally distributed across the bins it overlaps, so wide-range bars contribute across multiple bins, while narrow bars concentrate where they traded most. This yields per-bin totals for:
 
 Total Volume (participation)
 Positive / Negative Volume (up vs. down bar contribution)
 Hit Count (how often price touched the bin)
 Average Price Range (mean bar range inside the bin; a proxy for compression)
 
⚪ Delta & Direction 
For each bin, delta symmetry is measured via the ratio of |pos − neg| to total volume. Bins with balanced two-sided flow score higher than one-sided, runaway bins. This curbs the tendency of raw volume profiles to over-reward impulsive bursts.
⚪ Balance Score 
Each price bin gets a balance score that multiplies three normalized components:
 
 Delta Balance:   rewards bins where buy/sell pressure is symmetrical (configurable via Volume Momentum Weight).
 Price Compression:  rewards bins where average bar range is relatively small (configurable via Price Momentum Weight).
 Durability:  rewards bins revisited often (configurable via Hits Weight).
 
A Min Hits Filter removes flimsy, single-touch bins from dominating the score. The profile can display pure totals or Average Mode (Vol/Hit) to compare bins fairly when hit counts differ.
⚪ Display & Heat Spectrum 
The final plotted bar length per bin is the display volume (total or average) weighted by the balance score and normalized to 100.
 
 POC-like Highlight:  The 100% bin is outlined (and labeled) when Highlight Max Volume Bin is ON.
 Heat Spectrum (optional):  A background gradient scales with normalized bar length and balance hue.
 Balance Hue:  Interpolates between Balance Low/High Colors so high-balance bins visually pop as “accepted value.”
 
█  How to Use 
The profile is effectively a map of price acceptance:
 
 High, bright bars  = strong participation at balanced prices → fair value/rotation zones.
 Thin, muted bars  = poor acceptance → imbalance or transition areas.
 POC-style level  = most influential price in the lookback window.
 
⚪ Find Fair Value & Acceptance 
Thick, high-balance bins mark value. Expect rotation: price often revisits or oscillates around these areas. They’re prime zones for mean-reversion fades, scale-ins, and risk-defined trades against the edges.
  
⚪ Identify Imbalance & Funnels 
Low-balance, low-hit bins often act like air pockets—price can move through them quickly. These zones are helpful for continuation trades into thin areas or for timing breakout pulls back into acceptance.
  
 
⚪ POC Dynamics 
When price leaves the POC and returns, watch for re-acceptance (price comes back into the POC or high-balance zone and stays there.) vs. rejection (trend continuation away from value). The auto-highlight makes this quick to judge.
   
█  Settings 
 
 History Length –  Bars scanned for the profile. Longer = broader context, slower to adapt.
 Bin Count –  Vertical resolution of bins between the window’s min and max price.
 Display Shift –  Offsets the rendering rightward for clarity.
 Average Mode (Vol/Hit) –  ON uses average volume per visit; OFF uses total volume.
 Volume Momentum Weight –  Emphasizes two-way flow; higher values favor balanced bins over one-sided deltas.
 Price Momentum Weight –  Emphasizes compression; higher values favor narrow-range, coiling price action.
 Hits Weight –  Rewards bins revisited often; higher values favor durable acceptance.
 Min Hits Filter –  Minimum visits a bin needs to qualify for the balance score.
 Show Heat Spectrum –  Background gradient for quick read of density and balance.
 Highlight Max Volume Bin –  Outline + raw volume label for the dominant bin.
 Max Volume Color –  Color used for that highlight.
 Balance Low/High Colors –  Gradient endpoints for balance hue across the profile.
 
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Daily Range Zone This indicator shows the daily range (high to low) for each day.
Every day has its own unique color, making it easy to see each day’s price range at a glance.
Weis Wave Volume MTF 🎯 Indicator Name
Weis Wave Volume (Multi‑Timeframe) — adapted from the original “Weis Wave Volume by LazyBear.”
This version adds multi‑timeframe (MTF) readings, configurable colors, font size, and screen position for clear dashboard‑style display.
🧠 Concept Background — What is Weis Wave Volume (WWV)?
The Weis Wave Volume indicator originates from Wyckoff and David Weis’ techniques.
Its purpose is to link price movement “waves” with the amount of traded volume to reveal how strong or weak each wave is.
Instead of showing bars one by one, WWV accumulates the total volume while price keeps moving in the same direction.
When price direction changes (up → down or down → up), it:
Finishes the previous wave volume total.
Starts a new wave and begins accumulating again.
Those wave volumes help traders see:
Effort vs Result: Big volume with small price move ⇒ absorption; low volume with big move ⇒ weak participation.
Trend confirmation or exhaustion: High volume waves in trend direction strengthen it, while low‑volume waves hint exhaustion.
⚙️ How this Script Works
Trend & Wave Detection
Compares close with the previous bar to determine up or down movement (mov).
Detects trend reversals (when mov direction changes).
Builds “waves,” each representing a continuous run of bars in one direction.
Volume Accumulation
While price keeps the same direction, the script adds each bar’s volume to the running total (vol).
When direction flips, it resets that total and starts a new wave.
Multi‑Timeframe Computation
Calculates these wave volumes on three timeframes at once, chosen dynamically:
Active Chart Timeframe	Displays WWV for:
1 min	 1 min  
5 min	 5 min  
15 min	 15 min  
Any other	 Chart TF  
It uses request.security() to pull each timeframe’s latest WWV value and current wave direction.
Visual Output
Instead of plotting histogram bars, it shows a table with three numeric values:
WWV (1): 25.3 M | (15): 312 M | (240): 2.46 B
Each value is color‑coded:
user‑selected Uptrend Color when price wave = up
user‑selected Downtrend Color when wave = down
You can position this small table in any corner/center (top / bottom × left / center / right).
Font size is user‑adjustable (Tiny → Huge).
📈 How Traders Use It
Quickly gauge buying vs selling effort across multiple horizons.
Compare short‑term wave volume to higher‑timeframe waves to spot:
Alignment → all up and big volumes = strong trend
Divergence → small or opposite‑colored higher‑TF wave = potential reversal or pause
Combine with Wyckoff, VSA, or standard trend analysis to judge if a breakout or pullback has real participation.
🧩 Key Features of This Version
Feature	Description
Multi‑Timeframe Panel	Displays WWV values for 3 selected TFs at once
Dynamic TF Mapping	Auto‑adjusts which TFs to use based on chart
Up/Down Color Coding	Customizable colors for wave direction
Adjustable Font and Placement	Set font size (Tiny→Huge) and screen corner/center
No Histograms	Keeps chart clean; acts as a compact WWV dashboard
チャットGPTimport yfinance as yf
import pandas as pd
import requests
from bs4 import BeautifulSoup
# 株たんのスクリーニング結果URL(例:200日線以下)
url = "https://kabutan.jp/warning/?mode=3_1"
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
# 銘柄コードと企業名を抽出
stocks =  
for link in soup.select("td a "):
    code = link .split('=') 
    name = link.text.strip()
    if code.isdigit():
        stocks.append({"code": code, "name": name})
results =  
for stock in stocks :  # ←テスト用に10銘柄まで
    ticker = f"{stock }.T"
    df = yf.download(ticker, period="1y", interval="1d")
    # EMA200
    df  = df .ewm(span=200, adjust=False).mean()
    below_ema200 = df .iloc  < df .iloc 
    # 株たんの個別ページからPER・成長率を取得
    stock_url = f"https://kabutan.jp/stock/?code={stock }"
    res = requests.get(stock_url)
    s = BeautifulSoup(res.text, "html.parser")
    try:
        per = s.find(text="PER").find_next("td").text
        growth = s.find(text="売上高増減率").find_next("td").text
    except:
        per, growth = "N/A", "N/A"
    results.append({
        "銘柄コード": stock ,
        "企業名": stock ,
        "200EMA以下": below_ema200,
        "PER": per,
        "売上成長率": growth
    })
# 結果をCSV出力
df_result = pd.DataFrame(results)
df_result.to_csv("割安EMA200以下銘柄.csv", index=False, encoding="utf-8-sig")
print(df_result)






















