AI INSTITUTIONAL ENGINE + PATTERNS + VOLUME DASHBOARD📈 AI Institutional Engine – Pattern + Volume Dashboard
© 2025 MJ VIOLET PRO FX – all rights reserved
What it does
Auto-plots yesterday’s high / low / mid plus dynamic swing S/R
Detects 17 classical candle patterns on a higher-time-frame (default Daily)
Scans volume delta in real time and flags when today’s tape is ≥ 1.5 × 20-period average
Boosts pattern confidence if signal occurs inside NYSE hours (09:30 – 16:00 ET)
Paints an “HTF volume candle” so you see institutional-size footprints without changing charts
Fires audible / pop-up alerts only when pattern + volume + session line up
Why traders like it
One glance: trend emoji, pattern name, exact entry / exit prices, key level, stop distance
No repainting: all calculations close on the bar close; alerts fire once per bar
Fully customizable: toggle levels, labels, dashboard position, colours, text size, line length
Works on every symbol and timeframe (crypto, FX, equities, futures)
Lightweight code: < 500 drawing objects, no security() leaks, compatible with free TradingView accounts
How to read the dashboard
Buy Vol / Sell Vol / Delta – session-totals reset at the daily candle
Current Day – live bull / bear / doji emoji
Yesterday’s Range – the exact numbers the algo uses for breakout logic
Typical workflow
Add indicator
Wait for “High+” or “High” confidence pattern (green / orange label)
Check breakout box: close above resistance = long trigger, close below support = short trigger
Use suggested entry / stop in the label or place limit orders at the printed levels
Move stop to breakeven when price reaches 1:1 R:R or when opposite signal prints
Inputs you can tweak
Candle Time-frame for patterns (default D, but 4 h / 12 h / W work too)
Session filter time-zone (already set to “America/New_York”)
Volume multiplier (default 1.5 × MA)
Dashboard & table position, text sizes, colours, line style / length
Alert on / off for patterns and / or breakout levels only
Disclaimer
This tool is for educational and informational purposes only. It is not investment advice, an offer or solicitation to buy / sell any security, or a recommendation of any trading strategy. MJ VIOLET PRO FX is not a registered advisor. Futures, FX and CFDs are leveraged products; losses can exceed deposits. Always do your own due diligence and consult a licensed professional before risking capital.
ابحث في النصوص البرمجية عن "ai"
AI Bot Regime Feed (v6) — stableThis indicator generates real-time, structured JSON alerts for external trading bots or automation systems.
It combines multiple technical layers to identify market regimes and high-probability buy/sell events, and sends them to any webhook endpoint (e.g., a FastAPI or Zapier listener).
AI Trading Alerts v6 — SL/TP + Confidence + Panel (Fixed)Overview
This Pine Script is designed to identify high-probability trading opportunities in Forex, commodities, and crypto markets. It combines EMA trend filters, RSI, and Stochastic RSI, with automatic stop-loss (SL) & take-profit (TP) suggestions, and provides a confidence panel to quickly assess the trade setup strength.
It also includes TradingView alert conditions so you can set up notifications for Long/Short setups and EMA crosses.
⚙️ Features
EMA Trend Filter
Uses EMA 50, 100, 200 for trend confirmation.
Bull trend = EMA50 > EMA100 > EMA200
Bear trend = EMA50 < EMA100 < EMA200
RSI Filter
Bullish trades require RSI > 50
Bearish trades require RSI < 50
Stochastic RSI Filter
Prevents entries during overbought/oversold extremes.
Bullish entry only if %K and %D < 80
Bearish entry only if %K and %D > 20
EMA Proximity Check
Price must be near EMA50 (within ATR × adjustable multiplier).
Signals
Continuation Signals:
Long if all bullish conditions align.
Short if all bearish conditions align.
Cross Events:
Long Cross when price crosses above EMA50 in bull trend.
Short Cross when price crosses below EMA50 in bear trend.
Automatic SL/TP Suggestions
SL size adjusts depending on asset:
Gold/Silver (XAU/XAG): 5 pts
Bitcoin/Ethereum: 100 pts
FX pairs (default): 20 pts
TP = SL × Risk:Reward ratio (default 1:2).
Confidence Score (0–4)
Based on conditions met (trend, RSI, Stoch, EMA proximity).
Labels:
Strongest (4/4)
Strong (3/4)
Medium (2/4)
Low (1/4)
Visual Panel on Chart
Shows ✅/❌ for each condition (trend, RSI, Stoch, EMA proximity, signal now).
Confidence row with color-coded strength.
Alerts
Long Setup
Short Setup
Long Cross
Short Cross
🖥️ How to Use
1. Add the Script
Open TradingView → Pine Editor.
Paste the full script.
Click Add to chart.
Save as "AI Trading Alerts v6 — SL/TP + Confidence + Panel".
2. Configure Inputs
EMA Lengths: Default 50/100/200 (works well for swing trading).
RSI Length: 14 (standard).
Stochastic Length/K/D: Default 14/3/3.
Risk:Reward Ratio: Default 2.0 (can change to 1.5, 3.0, etc.).
EMA Proximity Threshold: Default 0.20 × ATR (adjust to be stricter/looser).
3. Read the Panel
Top-right of chart, you’ll see ✅ or ❌ for:
Trend → Are EMAs aligned?
RSI → Above 50 (bull) or below 50 (bear)?
Stoch OK → Not extreme?
Near EMA50 → Close enough to EMA50?
Above/Below OK → Price position vs. EMA50 matches trend?
Signal Now → Entry triggered?
Confidence row:
🟢 Green = Strongest
🟩 Light green = Strong
🟧 Orange = Medium
🟨 Yellow = Low
⬜ Gray = None
4. Alerts Setup
Go to TradingView Alerts (⏰ icon).
Choose the script under “Condition”.
Select alert type:
Long Setup
Short Setup
Long Cross
Short Cross
Set notification method (popup, sound, email, mobile).
Click Create.
Now TradingView will notify you automatically when signals appear.
5. Example Workflow
Wait for Confidence = Strong/Strongest.
Check if market session supports volatility (e.g., XAU in London/NY).
Review SL/TP suggestions:
Long → Entry: current price, SL: close - risk_pts, TP: close + risk_pts × RR.
Short → Entry: current price, SL: close + risk_pts, TP: close - risk_pts × RR.
Adjust based on your own price action analysis.
📊 Best Practices
Use on H1 + D1 combo → align higher timeframe bias with intraday entries.
Risk only 1–2% of account per trade (position sizing required).
Filter with market sessions (Asia, Europe, US).
Strongest signals work best with trending pairs (e.g., XAUUSD, USDJPY, BTCUSD).
🏆 AI Gold Master IndicatorsAI Gold Master Indicators - Technical Overview
Core Purpose: Advanced Pine Script indicator that analyzes 20 technical indicators simultaneously for XAUUSD (Gold) trading, generating automated buy/sell signals through a sophisticated scoring system.
Key Features
📊 Multi-Indicator Analysis
Processes 20 indicators: RSI, MACD, Bollinger Bands, EMA crossovers, Stochastic, Williams %R, CCI, ATR, Volume, ADX, Parabolic SAR, Ichimoku, MFI, ROC, Fibonacci retracements, Support/Resistance, Candlestick patterns, MA Ribbon, VWAP, Market Structure, and Cloud MA
Each indicator generates BUY (🟢), SELL (🔴), or NEUTRAL (⚪) signals
⚖️ Dual Scoring Systems
Weighted System: Each indicator has configurable weights (10-200 points, total 1000), with higher weights for critical indicators like RSI (150) and MACD (150)
Simple Count System: Basic counting of BUY vs SELL signals across all indicators
🎯 Signal Generation
Configurable thresholds for both systems (weighted score threshold: 400-600 recommended)
Dynamic risk management with ATR-based TP/SL levels
Signal strength filtering to reduce false positives
📈 Advanced Configuration
Customizable thresholds for all 20 indicators (RSI levels, Stochastic bounds, Williams %R zones, etc.)
Dynamic weight bonuses that adapt to dominant market trends
Risk management with configurable TP1/TP2 multipliers and stop losses
🎛️ Visual Interface
Real-time master table displaying all indicators, their values, weights, and current signals
Visual trading signals (triangles) with detailed labels
Optional TP/SL lines and performance statistics
💡 Optimization Features
Gold-specific parameter tuning
Trend analysis with configurable lookback periods
Volume spike detection and volatility analysis
Multi-timeframe compatibility (15m, 1H, 4H recommended)
The system combines traditional technical analysis with modern weighting algorithms to provide comprehensive market analysis specifically optimized for gold trading.
Ragazzi è una meraviglia, pronto all uso, già configurato provatelo divertitevi e fate tanti soldoni poi magari una piccola donazione spontanea sarebbe molto gradita visto il tempo, risorse e gli insulti della moglie che mi diceva che perdevo tempo, fatemi sapere se vi piace.
nel codice troverete una descrizione del funzionamento se vi vengono in mente delle idee per migliorarlo contattatemi troverete i mie contatti in tabella un saluto.
AI BUY AND SELL BGThe Gk fundamental is a next gen level ai powered BUY and SELL system engineered for big market moves, it runs an embedded algorithm within a algorithm to detect breakout points before they happen giving traders insane results
works best and only 2h and 4h
AI-Powered Breakout with Advanced FeaturesDescription
This script is designed to detect breakout moments in financial markets using a combination of traditional breakout detection methods and adaptive moving averages. By leveraging elements of artificial intelligence, the script provides a more dynamic and responsive approach to identifying potential entry and exit points in trading.
Usefulness
This script stands out by integrating a traditional breakout finder with an adaptive moving average component. The adaptive moving average adjusts dynamically based on the differences between fast and slow exponential moving averages (EMAs), offering a more flexible and responsive detection of support and resistance levels. This combination aims to reduce false signals and enhance the reliability of breakout detections, making it a valuable tool for traders seeking to capture market movements more effectively.
Features
1. Breakout Detection: Utilizes pivot highs and lows to identify significant breakout points over a user-defined period. This method helps in capturing the essential support and resistance levels that are critical in breakout trading.
2. AI Machine Learning Component - Adaptive Moving Average: Implements an adaptive moving average using two exponential moving averages (EMAs). adaptiveMA is dynamically adjusted based on the difference between a fast average and a slow average.
3. Buy/Sell Signals: The script generates buy and sell signals when bullish and bearish breakouts occur, respectively. These signals are visually represented on the chart, helping traders to quickly identify potential trading opportunities.
4. Visualization: Draws horizontal lines at identified breakout levels and plots shapes (arrows) on the chart to indicate buy/sell signals. This makes it easy for traders to see where significant breakout points are and where to consider entering or exiting trades.
Underlying Concepts
1. Breakout Finder Logic: The script uses pivot points (highs and lows) to detect breakout levels. It stores these pivot points in arrays and monitors them for persistence, ensuring that the detected breakouts are significant and reliable.
2. Adaptive Moving Average (AMA): The AMA is a key component that enhances the script's responsiveness. By calculating the differences between fast and slow EMAs, the AMA adapts to changing market conditions, providing a more accurate measure of trends and potential reversals.
How to Use
• Adjustable Parameters: The script includes several user-adjustable parameters:
o Lookback Length: Defines the period over which the script calculates the highest high and lowest low for breakout detection.
o Multiplier for Adaptive MA: Adjusts the sensitivity of the adaptive moving average.
o Period for Pivots: Sets the period for detecting pivot highs and lows.
o Max Breakout Length: Specifies the maximum length for breakout consideration.
o Threshold Rate: Determines the threshold rate for breakout validation.
o Minimum Number of Tests: Sets the minimum number of tests required to validate a breakout.
o Colors and Line Style: Customize the colors and line styles for breakout levels.
Interpreting Signals
o Green Arrows: Indicate a bullish breakout signal, suggesting a potential buy opportunity.
o Red Arrows: Indicate a bearish breakout signal, suggesting a potential sell opportunity.
o Horizontal Lines: Show the breakout levels, helping to visualize support and resistance areas.
By combining traditional breakout detection with advanced adaptive moving averages, this script aims to provide traders with a robust tool for identifying and capitalizing on market breakouts.
Credits
Parts of this script were inspired and adapted from the "Breakout Finder" script by LonesomeTheBlue. Significant improvements include the integration of the adaptive moving average component and enhancements to the breakout detection logic.
AI SuperTrend - Strategy [presentTrading]
█ Introduction and How it is Different
The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning algorithm, with the tried-and-true SuperTrend indicator. This blend aims to provide traders with more accurate, responsive, and context-aware trading signals.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How it Works: Detailed Explanation
SuperTrend Calculation
Volume-Weighted Moving Average (VWMA): A VWMA of the close price is calculated based on the user-defined length (len). This serves as the central line around which the upper and lower bands are calculated.
Average True Range (ATR): ATR is calculated over a period defined by len. It measures the market's volatility.
Upper and Lower Bands: The upper band is calculated as VWMA + (factor * ATR) and the lower band as VWMA - (factor * ATR). The factor is a user-defined multiplier that decides how wide the bands should be.
KNN Algorithm
Data Collection: An array (data) is populated with recent n SuperTrend values. Corresponding labels (labels) are determined by whether the weighted moving average price (price) is greater than the weighted moving average of the SuperTrend (sT).
Distance Calculation: The absolute distance between each data point and the current SuperTrend value is calculated.
Sorting & Weighting: The distances are sorted in ascending order, and the closest k points are selected. Each point is weighted by the inverse of its distance to the current point.
Classification: A weighted sum of the labels of the k closest points is calculated. If the sum is closer to 1, the trend is predicted as bullish; if closer to 0, bearish.
Signal Generation
Start of Trend: A new bullish trend (Start_TrendUp) is considered to have started if the current trend color is bullish and the previous was not bullish. Similarly for bearish trends (Start_TrendDn).
Trend Continuation: A bullish trend (TrendUp) is considered to be continuing if the direction is negative and the KNN prediction is 1. Similarly for bearish trends (TrendDn).
Trading Logic
Long Condition: If Start_TrendUp or TrendUp is true, a long position is entered.
Short Condition: If Start_TrendDn or TrendDn is true, a short position is entered.
Exit Condition: Dynamic trailing stops are used for exits. If the trend does not continue as indicated by the KNN prediction and SuperTrend direction, an exit signal is generated.
The synergy between SuperTrend and KNN aims to filter out noise and produce more reliable trading signals. While SuperTrend provides a broad sense of the market direction, KNN refines this by predicting short-term price movements, leading to a more nuanced trading strategy.
Local picture
█ Trade Direction
The strategy allows traders to choose between taking only long positions, only short positions, or both. This is particularly useful for adapting to different market conditions.
█ Usage
ToolTips: Explains what each parameter does and how to adjust them.
Inputs: Customize values like the number of neighbors in KNN, ATR multiplier, and moving average type.
Plotting: Visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy/sell orders.
█ Default Settings
The default settings are selected to provide a balanced approach, but they can be modified for different trading styles and asset classes.
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
By combining both machine learning and traditional technical analysis, this strategy offers a sophisticated and adaptive trading solution.
AI-Based Indicator V.1.01This is a Strategy based on Artificial Intelligence (AI) algorithms which can be used as a decision support system. In this version I use Heikin Ashi chart and reduce input parameters.
How to use:
1- Select the Heikin Ashi chart.
2- The default values of T for BTCUSD in "30m chart" is 0.12. It can be changed to achieve the best performance for BTCUSD or other tickers in arbitrary time frames.
3. When the background is green buy, and when the background is red sell.
AI-Based Strategy on Renko Chart V.1This is a Strategy based on Artificial Intelligence (AI) algorithms which can be used as a decision support system.
How to use:
1- Select the Renko chart.
2- Set "ATR Length" on settings window to "1". Settings can be seen after right click on the chart.
3- Use arbitrary time frame.
AI-Based Strategy V.1
This is a Strategy based on Artificial Intelligence (AI) algorithms which can be used (alone or along with other strategies) as a decision support system.
How to use:
1- The default values of Input 1, Input 2, R, and T for ETHUSDT are “Close”, “ohlc4”, 180, and 0.1325 respectively. They can be changed to achieve the best performance for ETHUSDT or other symbols.
2- Use one of the time frames 15 to 3m.
3. When the background is green buy, and when the background is red sell.
AI-Based Indicator V.1This is an indicator based on Artificial Intelligence (AI) algorithms which can be used (alone or along with other indicators) as a decision support system.
How to use:
1- The default values of Input 1, Input 2, R, and T for BTCUSD are “Close”, “Close”, 4320, and 0.15 respectively. They can be changed to achieve the best performance for BTCUSD or other tickers.
2- Use one of the time frames 4H to 15m.
3. When the background is green buy, and when the background is red sell.
Scalp Sense AI# Scalp Sense AI (No Repaint)
**Adaptive trend & reversal detector with an AI-driven score, multi-timeframe confirmations, robust volume filters, and a purpose-built Scalping Mode.**
Signals are generated **only on bar close** (no repaint), include structured alert payloads for webhooks, and come with optional ATR-based TP/SL visualization for study and validation.
---
## What it is (in one paragraph)
**Scalp Sense AI** combines classic market structure (DI/ADX, EMA, SMA, Keltner, ATR) with a continuous **AI Score** that fuses RSI normalization, EMA distance (in ATR units), and DI edge into a single, volatility-aware signal. It adaptively gates **trend** and **reversal** entries, applies **HTF confirmation** without lookahead, and enforces **guard rails** (e.g., strong-trend reversal blocking) unless a high-confidence AI override and volume confirmation are present. **Scalping Mode** compresses reaction times and adds micro price-action cues (wick rejections, micro-EMA crosses, small engulfing) to surface more—but disciplined—opportunities.
---
## Non-Repainting Design
* All signals, markers, state, and alerts are computed **after bar close** using `barstate.isconfirmed`.
* HTF data are requested with `lookahead_off`.
* No “future-peeking” constructs are used.
* Result: signals do **not** change after the candle closes.
---
## How the engine works (pipeline overview)
1. **Base metrics**
* **RSI**, **EMA**, **ATR** (+ ATR SMA for regime/volatility), **SMA long & short**, **Keltner** (EMA ± ATR×mult).
* **Manual DI/ADX** for fine control (DM+, DM−, true range smoothing).
2. **Volatility regime**
* Compares ATR to its SMA and scales thresholds by √(ATR/ATR\_SMA) → robust “high\_vol” gating.
3. **Volume & flow**
* **Volume Z-score**, **OBV slope**, and **MFI** (all computed manually) to confirm impulses and filter weak reversals.
4. **Higher-Timeframe confirmation (optional)**
* Imports HTF **PDI/MDI/ADX** and **SMA** (no lookahead) to require alignment when enabled.
5. **AI Score**
* Weighted fusion of **RSI (normalized around 0)**, **EMA distance (in ATR)**, and **DI edge**.
* Smoothed; then its **mean (μ)** and **volatility (σ)** are estimated to form **adaptive bands** (hi/lo), with optional **hysteresis**.
* **Debounce** (M in N bars) avoids flicker; **bias state** persists until truly invalidated.
6. **Signal logic**
* **Trend entries** require AI bias + trend confirmations (DI/ADX/SMA, HTF if enabled), volatility OK, and **anti-breakout** filter.
* **Reversal entries** come in **core**, **early**, and **scalp** flavors (progressively more frequent), guarded by strong-trend blocks that an **AI+volume+ADX-cooling override** can bypass.
7. **Scalping Mode**
* Adaptive parameter contraction (shorter lengths), gentler guards, micro-patterns (wick/engulf/micro-EMA cross), and reduced cooldown to increase high-quality opportunities.
8. **Cooldown & state**
* One signal per side after a configurable spacing in bars; internal “last direction” avoids clustering.
9. **Visualization & alerts**
* **Triangles** for trend, **circles** for reversals (offset by ATR to avoid overlap).
* **Single-line alert payload** (BUY/SELL, reason, AI, volZ, ADX) ready for webhooks.
---
## Signals & visualization
* **Trend Long/Short** → triangle markers (above/below) when:
* AI bias aligns with trend confirmations (DI edge, ADX above threshold, price vs long SMA, optional HTF alignment).
* Volatility regime agrees; **anti-breakout** prevents entries exactly at lookback highs/lows.
* **Reversal Long/Short** → circular markers when:
* **Core**: AI near “loose” band, OBV/MFI/volZ supportive, ADX cooling, DI spread relaxed, PA confirms (crosses/div).
* **Early**: anticipatory patterns (Keltner exhaustion, simple RSI “quasi-divergence”).
* **Scalp**: micro-EMA cross, wick rejection, mini-engulfing, with relaxed guards but AI/volume still in the loop.
* **Markers appear only on the bar that actually emitted the signal** (no repaint); offsets use ATR so shapes don’t overlap.
---
## Alerts (ready for webhooks)
Enable “**Any alert() function call**” and you’ll receive compact, single-line payloads once per bar:
```
action=BUY;reason=reversal-early;ai=0.1375;volZ=0.82;adx=27.5
action=SELL;reason=trend;ai=-0.2210;volZ=0.43;adx=31.9
```
* `action`: BUY / SELL
* `reason`: `trend` | `reversal-core` | `reversal-early` | `reversal-scalp`
* `ai`: current smoothed AI Score at signal bar
* `volZ`: volume Z-score
* `adx`: current ADX
---
## Inputs (exhaustive)
### 1) Core Inputs
* **RSI Length (Base)** (`rsi_length_base`, int)
Base RSI lookback. Shorter = more reactive; longer = smoother.
* **RSI Overbought Threshold** (`rsi_overbought`, int)
Informational for context; RSI is used normalized in the AI fusion.
* **RSI Oversold Threshold** (`rsi_oversold`, int)
Informational; complements visual context.
* **EMA Length (Base)** (`ema_length_base`, int)
Primary adaptive mean; also used for Keltner mid and distance metric.
* **ATR Length (Base)** (`atr_length_base`, int)
Volatility unit for Keltner, SL/TP (debug), and regime detection.
* **ATR SMA Length** (`atr_sma_len`, int)
Smooth baseline for ATR regime; supports “high\_vol” logic.
* **ATR Multiplier Base** (`atr_mult_base`, float)
Scales volatility gating (sqrt-scaled); higher = tighter high-vol requirement.
* **Disable Volatility Filter** (`disable_volatility_check`, bool)
Bypass volatility gating if true.
* **Price Change Period (bars)** (`price_change_period_base`, int)
Simple momentum check (+/−% over N bars) used in trend validation.
* **Base Cooldown Bars Between Signals** (`signal_cooldown_base`, int ≥ 0)
Minimum bars to wait between signals (per side).
* **Trend Confirmation Bars** (`trend_confirm_bars`, int ≥ 1)
Require persistence above/below long SMA for this many bars.
* **Use Higher Timeframe Confirmation** (`use_higher_tf`, bool)
Turn on/off HTF alignment (no repaint).
* **Higher Timeframe for Confirmation** (`higher_tf`, timeframe)
E.g., “60” to confirm M15 with H1; used for HTF PDI/MDI/ADX and SMA.
* **TP as ATR Multiple** (`tp_atr_mult`, float)
For **visual debug** only (drawn after entries); not an order manager.
* **SL as ATR Multiple** (`sl_atr_mult`, float)
For visual debug only.
* **Enable Scalping Mode** (`scalping_mode`, bool)
Compresses lengths/thresholds, unlocks micro-PA modules, reduces cooldown.
* **Show Debug Lines** (`show_debug`, bool)
Plots AI bands, DI/ADX, EMA/SMA, Keltner, vol metrics, and TP/SL (debug).
### 2) AI Score & Thresholds
* **AI Score Smooth Len** (`ai_len`, int)
EMA smoothing over the raw fusion.
* **AI Volatility Window** (`ai_sigma_len`, int)
Window to estimate AI mean (μ) and standard deviation (σ).
* **K High (sigma)** (`ai_k_hi`, float)
Upper band width (σ multiplier) for strong threshold.
* **K Low (sigma)** (`ai_k_lo`, float)
Lower band width (σ multiplier) for loose threshold.
* **Debounce Window (bars)** (`ai_debounce_m`, int ≥ 1)
Rolling window length used by the confirm counter.
* **Min Bars>Thr in Window** (`ai_debounce_n`, int ≥ 1)
Minimum confirmations inside the debounce window to validate a state.
* **Use Hysteresis Thresholds** (`ai_hysteresis`, bool)
Requires crossing back past a looser band to exit bias → fewer whipsaws.
* **Weight DI Edge (0–1)** (`ai_weight_di`, float)
Importance of DI edge within the fusion.
* **Weight EMA Dist (0–1)** (`ai_weight_ema`, float)
Importance of EMA distance (in ATR units).
* **Weight RSI Norm (0–1)** (`ai_weight_rsi`, float)
Importance of normalized RSI.
* **Sensitivity (0–1)** (`sensitivity`, float)
Contracts/expands bands (higher = more sensitive).
### 3) Volume Filters
* **Volume MA Length** (`vol_ma_len`, int)
Baseline for volume Z-score.
* **Volume Z-Score Window** (`vol_z_len`, int)
Std-dev window for Z-score; larger = fewer volume “spikes”.
* **Reversal: Min Volume Z for confirm** (`vol_rev_min_z`, float)
Minimum Z required to validate reversals (adaptively relaxed in scalping).
* **OBV Slope Lookback** (`obv_slope_len`, int)
Rising/falling OBV over this window supports bull/bear confirmations.
* **MFI Length** (`mfi_len`, int)
Money Flow Index lookback (manual calculation).
### 4) Filters (Breakout / ADX / Reversal)
* **Enable Breakout Filter** (`enable_breakout_fil`, bool)
Avoid trend entries at lookback highs/lows.
* **Breakout Lookback Bars** (`breakout_lookback`, int ≥ 1)
Window for the anti-breakout guard.
* **Base ADX Length** (`adx_length_base`, int)
Lookback for DI/ADX smoothing (also adapted in Scalping Mode).
* **Base ADX Threshold** (`adx_threshold_base`, float)
Minimum ADX to validate trend context (scaled in Scalping Mode).
* **Enable Reversal Filter** (`enable_rev_filter`, bool)
Master switch for reversal logic.
* **Max ADX for Reversal** (`rev_adx_max`, float)
Hard cap: above this ADX, reversals are blocked (unless overridden by AI if allowed in Guards).
### 5) Reversal Guard (regime protection & overrides)
* **Strong Trend: ADX add-above Thr** (`guard_adx_add`, float)
Extra ADX above `adx_threshold` to mark “strong” trend.
* **Strong Trend: min DI spread** (`guard_spread_min`, float)
Minimum DI separation to consider a trend “dominant”.
* **Require ADX drop from window max (%)** (`guard_adx_drop_min_pct`, float 0–1)
ADX must drop at least this fraction from its window maximum to consider “cooling”.
* **Regime Window (bars)** (`guard_regime_len`, int ≥ 10)
Window over which ADX max is measured for the “cooling” check.
* **EMA Slope Lookback** (`guard_slope_len`, int ≥ 2)
EMA slope horizon used alongside Keltner for strong-trend identification.
* **Keltner Mult (ATR)** (`guard_kc_mult`, float)
Keltner width for strong trend bands and exhaustion checks.
* **HTF Reversal Block Mode** (`htf_block_mode`, string: `Off` | `On` | `AI-controlled`)
* `Off`: never block by HTF.
* `On`: block reversals whenever HTF is strong.
* `AI-controlled`: block **unless** AI+volume+ADX-cooling override criteria are met.
* **AI-controlled: allow AI override** (`ai_htf_override`, bool)
Enables the override mechanism in `AI-controlled` mode.
* **AI override multiplier (vs band\_hi)** (`ai_override_mult`, float)
Strength needed beyond the high band to count as “strong AI”.
* **AI override: min bars beyond strong thr** (`ai_override_min_bars`, int ≥ 1)
Debounce on the override itself.
### 6) Markers
* **Reversal Circle ATR Offset** (`rev_marker_offset_atr`, float ≥ 0)
Vertical offset for reversal circles; trend triangles use a separate (internal) offset.
### 7) Scalping Mode Tuning
* **Reversal aggressiveness (0–1)** (`scalp_rev_aggr`, float)
Higher = looser guards and stronger AI sensitivity.
* **Wick: body multiple (bull/bear)** (`scalp_wick_body_mult`, float)
Wick must be at least this multiple of body to count as rejection.
* **Wick: ATR multiple (min)** (`scalp_wick_atr_mult`, float)
Minimal wick length in ATR units.
* **Micro EMA factor (vs EMA base)** (`scalp_ema_fast_factor`, float 0.2–0.9)
Fast EMA length = base EMA × factor (rounded/int).
* **Relax breakout filter in scalping** (`scalp_breakout_relax`, bool)
Lets more trend entries through in scalping context.
### 8) ICT-style SMA (bases)
* **ICT SMA Long Length (Base)** (`sma_long_len_base`, int)
Long-term baseline for regime/trend.
* **ICT SMA Short1 Length (Base)** (`sma_short1_len_base`, int)
Short baseline for price-action crosses.
* **ICT SMA Short2 Length (Base)** (`sma_short2_len_base`, int)
Companion short baseline used in PA cross checks.
> **Adaptive “effective” values:** When **Scalping Mode** is ON, the script internally shortens multiple lengths (RSI/EMA/ATR/ADX/μσ windows, SMAs) and gently relaxes guards (ADX drop %, DI spread, volume Z, override thresholds), reduces cooldown/confirm bars, and optionally relaxes the breakout filter—so you get **more frequent but still curated** signals.
---
## Plots & debug (optional)
* DI+/DI−, ADX (curr + HTF), EMA, long SMA, Keltner up/down (when strong), AI Score, AI mean, AI bands (hi/lo; low plots only when hysteresis is on), Volume MA and Z-score, and ATR-based TP/SL guide (after entries).
* These are **study aids**; the indicator does not manage trades.
---
## Recommended use
* **Timeframes**:
* Scalping Mode: M1–M15.
* Standard Mode: M15–H1 (or higher).
* **Markets**: Designed for liquid FX, indices, metals, and large-cap crypto.
* **Chart type**: Standard candles recommended (Heikin-Ashi alters inputs and hence signals).
* **Alerts**: Use “Any alert() function call”. Parse the key/value payloads server-side.
---
## Good to know
* **Why some alerts don’t draw shapes retroactively**: markers are drawn **only on** the bar that emitted the signal (no repaint by design).
* **Why a reversal didn’t fire**: strong-trend guards + HTF block may have been active; check ADX, DI spread, Keltner position, EMA slope, and whether AI override criteria were met.
* **Too many / too few signals**: tune **Scalping Mode**, `signal_cooldown_base`, AI bands (`ai_k_hi/lo`, `sensitivity`), volume Z (`vol_rev_min_z`), and guards (`rev_adx_max`, `guard_*`).
---
## Disclaimer
This is an **indicator**, not a strategy or an execution system. It does not place, modify, or manage orders. Markets carry risk—validate on historical data and demo before any live decisions. No performance claims are made.
---
### Version
**Scalp Sense AI v11.5** — Adaptive AI bands with hysteresis/debounce, HTF no-lookahead confirmations, guarded reversal logic with AI override, full volume suite (Z, OBV slope, MFI), anti-breakout filter, and a dedicated Scalping Mode with micro-PA cues.
PowerHouse SwiftEdge AI v2.10 with Custom Filters & AI AnalysisPowerHouse SwiftEdge AI v2.10 with Custom Filters & AI Analysis
Overview
PowerHouse SwiftEdge AI v2.10 is an advanced TradingView Pine Script indicator designed to identify high-probability trading setups by combining pivot-based structure analysis, multi-timeframe trend detection, and adaptive AI-driven signal filtering. The script integrates Change of Character (CHoCH) and Break of Structure (BOS) signals with customizable momentum, volume, breakout, and trend filters to enhance trade precision. Additionally, it offers an optional AI Market Analysis module that predicts future price trends across multiple timeframes, providing traders with a comprehensive market outlook.
The script is highly customizable, allowing users to tailor inputs to their trading style, whether for scalping, swing trading, or long-term strategies. It is suitable for all asset classes, including stocks, forex, crypto, and commodities, and performs optimally on timeframes ranging from 1-minute to daily charts.
Key Features
Pivot-Based Signal Generation:
Identifies pivot highs and lows to detect CHoCH (reversal patterns) and BOS (continuation patterns).
Signals are plotted as "Buy" or "Sell" labels with optional "Get Ready" pre-signals to prepare traders for potential setups.
Take-profit (TP) levels are automatically calculated based on user-defined points, with optional TP box visualization.
Multi-Timeframe Trend Analysis:
Analyzes trends across seven timeframes (1M, 5M, 15M, 30M, 1H, 4H, D) using EMA and VWAP to determine bullish, bearish, or neutral conditions.
Displays a futuristic AI-Trend Matrix dashboard showing trend direction, strength, and confidence levels for quick decision-making.
Customizable Signal Filters:
Momentum Filter: Ensures signals align with significant price changes, adjusted dynamically using ATR-based volatility.
Higher Timeframe Trend Filter: Requires signals to align with the trend of a user-selected higher timeframe (e.g., 1H).
Lower Timeframe Trend Filter: Prevents signals that conflict with the trend of a user-selected lower timeframe (e.g., 5M).
Volume Filter: Optionally requires above-average volume to confirm signals.
Breakout Filter: Optionally requires price to break previous highs/lows for signal validation.
Repeated Signal Restriction: Prevents consecutive signals in the same trend direction until the trend changes on a user-defined timeframe.
AI-Driven Adaptivity:
Incorporates Cumulative Volume Delta (CVD) to assess buying/selling pressure and classify market volatility (Low, Medium, High).
Uses ATR to dynamically adjust momentum thresholds, ensuring signals adapt to current market conditions.
Optional AI Market Analysis module predicts trends across multiple timeframes by combining trend, momentum, and volatility scores.
Visual Elements:
Plots CHoCH and BOS levels as horizontal lines with distinct colors (aqua for CHoCH sell, lime for CHoCH buy, fuchsia for BOS sell, teal for BOS buy).
Draws dynamic support and resistance trendlines based on short and long-term price action, colored by trend strength.
Displays TP levels and pivot highs/lows for easy reference.
How It Works
The script combines several technical analysis concepts to create a robust trading system:
Market Structure Analysis:
Pivot highs and lows are identified using a user-defined lookback period (Pivot Length).
CHoCH occurs when price crosses below a pivot high (bearish reversal) or above a pivot low (bullish reversal).
BOS occurs when price breaks a previous pivot low (bearish continuation) or pivot high (bullish continuation).
Trend and Momentum Integration:
Trends are determined by comparing price to EMA and VWAP on multiple timeframes.
Momentum is calculated as the percentage price change, with thresholds adjusted by ATR to account for volatility.
"Get Ready" signals appear when momentum approaches the threshold, preparing traders for potential CHoCH or BOS signals.
Signal Filtering:
Filters ensure signals align with user-defined criteria (e.g., trend direction, volume, breakouts).
The Restrict Repeated Signals option prevents over-signaling by requiring a trend change on a specified timeframe before generating a new signal in the same direction.
AI Market Analysis:
The optional AI module calculates a score for each timeframe based on trend direction, momentum, and volatility (ATR compared to its SMA).
Scores are translated into predictions (▲ for bullish, ▼ for bearish, — for neutral), displayed in a dedicated table.
CVD and Volatility Context:
CVD tracks buying vs. selling pressure by accumulating volume based on price direction.
Volatility is classified using CVD magnitude, influencing the script’s visual cues and signal sensitivity.
Why This Combination?
The integration of pivot-based structure analysis, multi-timeframe trend filtering, and AI-driven adaptivity addresses common trading challenges:
Precision: CHoCH and BOS signals focus on key market turning points, reducing noise from minor price fluctuations.
Context: Multi-timeframe analysis ensures trades align with broader market trends, improving win rates.
Adaptivity: ATR and CVD adjustments make the script responsive to changing market conditions, avoiding static thresholds that fail in volatile or quiet markets.
Customization: Extensive input options allow traders to adapt the script to their preferred markets, timeframes, and risk profiles.
Predictive Insight: The AI Market Analysis module provides forward-looking trend predictions, helping traders anticipate market moves.
This combination creates a self-contained system that balances responsiveness with reliability, making it suitable for both novice and experienced traders.
How to Use
Add to Chart:
Apply the indicator to your TradingView chart for any asset and timeframe.
Recommended timeframes: 5M to 1H for scalping/day trading, 4H to D for swing trading.
Configure Inputs:
Pivot Length: Adjust (default 5) to control sensitivity to pivot highs/lows. Lower values for faster signals, higher for stronger confirmations.
Momentum Threshold: Set the minimum price change (default 0.01%) for signals. Increase for stricter conditions.
Take Profit Points: Define TP distance (default 10 points). Adjust based on asset volatility.
Signal Filters: Enable/disable filters (momentum, trend, volume, breakout) to match your strategy.
Higher/Lower Timeframe: Select timeframes for trend alignment (e.g., 1H for higher, 5M for lower).
AI Market Analysis: Enable for predictive trend insights across timeframes.
Get Ready Signals: Enable to see pre-signals for potential setups.
Interpret Signals:
Buy/Sell Labels: Act on green "Buy" or red "Sell" labels, confirming with TP levels and trend direction.
Get Ready Labels: Yellow "Get Ready BUY" or orange "Get Ready SELL" indicate potential setups; prepare but wait for confirmation.
CHoCH/BOS Lines: Use aqua/lime (CHoCH) and fuchsia/teal (BOS) lines as key support/resistance levels.
AI-Trend Matrix: Check the top-right dashboard for trend strength (%), confidence (%), and timeframe-specific trends.
AI Market Analysis Table: If enabled, view predictions (▲/▼/—) for each timeframe to anticipate market direction.
Trading Tips:
Combine signals with other indicators (e.g., RSI, MACD) for additional confirmation.
Use higher timeframe trend alignment for higher-probability trades.
Adjust TP and signal distance based on asset volatility and trading style.
Monitor the AI-Trend Matrix for trend strength; values above 50% or below -50% indicate strong directional bias.
Originality
PowerHouse SwiftEdge AI v2.10 stands out due to its unique blend of:
Adaptive Signal Generation: ATR-based momentum thresholds and CVD-driven volatility context ensure signals remain relevant across market conditions.
Multi-Timeframe Synergy: The script’s ability to filter signals based on both higher and lower timeframe trends provides a rare balance of precision and context.
AI-Powered Insights: The AI Market Analysis module offers predictive capabilities not commonly found in traditional indicators, simulating institutional-grade analysis.
Visual Clarity: The futuristic dashboard and color-coded trendlines make complex data accessible, enhancing usability for all trader levels.
Unlike standalone pivot or trend indicators, this script integrates multiple layers of analysis into a cohesive system, reducing false signals and providing actionable insights without requiring external tools or research.
Limitations
False Signals: No indicator is foolproof; signals may fail in choppy or low-volume markets. Use filters to mitigate.
Timeframe Sensitivity: Performance varies by timeframe and asset. Test settings thoroughly.
AI Predictions: The AI Market Analysis is based on historical data and simplified scoring; it’s not a guaranteed forecast.
Resource Usage: Enabling all filters and AI analysis may slow performance on lower-end devices.
EquiSense AI Signals🇸🇦 العربي
المتنبئ الذكي المتوازن (AI v7)
وصف قصير:
مؤشر تجميعي ذكي يوازن بين الاتجاه والزخم والحجم والتذبذب وأنماط الشموع، ويحوّلها إلى نظام نقاط ونجوم يولّد إشارات شراء/بيع مؤكَّدة بتقاطع MACD. بعد الإشارة، يعرض أهدافًا ذكية (TP1/TP2/TP3) ووقف خسارة مبنيَّيْن على ATR مع رسومات مستقبلية ولوحة معلومات لإدارة الصفقة.
الإعدادات (Inputs)
الحد الأدنى للنقاط (min_score): افتراضي 6.0 — كلما ارتفع قلّت الإشارات وزادت جودتها.
الحد الأدنى للنجوم (min_stars): افتراضي 2 — فلتر لقوة الإشارة.
عدد الشموع المستقبلية (future_bars): افتراضي 15 — مدى رسم الأهداف والوقف للأمام.
استخدام الأهداف الذكية (use_ai_targets): تفعيل/إيقاف مضاعِف الذكاء الاصطناعي للأهداف والوقف.
كيف يعمل؟
يحسب المؤشر buy_score/sell_score من مجموعة عوامل: EMA8/21/50/200، RSI + متوسطه، MACD + Histogram، Stochastic، ADX/DMI، VWAP، الحجم، MTF 15m، ROC/المومنتَم، Heikin Ashi، وأنماط (ابتلاع/مطرقة/شهاب).
يحوّل الدرجات إلى نجوم (⭐⭐ إلى ⭐⭐⭐⭐⭐) حسب القوة.
تولّد الإشارة فقط إذا توفّر: درجة ≥ الحد + نجوم ≥ الحد + تقاطع MACD (صعودًا للشراء، هبوطًا للبيع).
عند الإشارة يبدأ سيناريو صفقة واحدة فقط حتى تنتهي (TP3 أو SL).
الأهداف والوقف (ذكاء اصطناعي)
تُشتق من ATR ثم تُعدَّل عبر مضاعِف AI مبني على: ATR%، الزخم (ROC)، الحجم مقابل متوسطه، قوة الاتجاه (ADX)، وعدد النجوم.
تقريبيًا:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
ماذا سترى على الشارت؟
علامات “شراء/بيع”، نجوم قرب الإشارة، خط دخول (أزرق)، وقف (أحمر منقّط)، TP1/TP2 (أخضر)، TP3 (ذهبي) مع صناديق مناطق للأهداف وخط ربط نحو الهدف النهائي.
وسم AI يعرض نسبة المضاعِف والنجوم بصريًا.
لوحة معلومات تعرض الحالة، القوة، AI%، السعر، الدرجات، وأثناء الصفقة: الدخول، TP1/TP2/TP3، والربح اللحظي.
التنبيهات (Alerts)
شرطان جاهزان: شراء وبيع عند تحقق الإشارة.
أضِف تنبيه: Right click → Add alert → اختر المؤشر → الشرط المطلوب.
أفضل الممارسات
استخدم الإطار المناسب للأصل:
سكالبينغ 5–15m: min_score 8 وmin_stars 3–4.
تأرجحي H1–H4: min_score 7 وmin_stars 3.
يومي/أسهم: min_score 6–7 وmin_stars 2–3.
فضّل التداول مع EMA200 واتجاه MTF 15m.
خفّض المخاطرة وقت الأخبار العالية.
التزم بإدارة مخاطر ثابتة (مثلاً 1% لكل صفقة).
حدود مهمة
الأفضل انتظار إغلاق الشمعة لتأكيد التقاطعات وتجنّب تغيّرها.
صفقة واحدة في المرة بفضل حالة in_trade.
يستخدم request.security مع lookahead_off لإطار 15m؛ التزم بالتقييم عند الإغلاق.
أسئلة شائعة
هل يستخدم منفردًا؟ نعم، لكن مع مناطق سعرية/ترند وخطة مخاطر يصبح أقوى.
لماذا تختلف الأهداف؟ لأن مضاعِف AI يكيّف TP/SL مع ظروف السوق.
إخلاء مسؤولية
هذه أداة تحليلية تعليمية وليست نصيحة استثمارية. اختبر الإعدادات تاريخيًا والتزم بالمخاطرة المناسبة.
ملاحظة للمبرمجين
Pine Script v6، متغيرات var لحفظ الحالة، تنظيف الرسومات على الشمعة الأخيرة، مع حدود مرتفعة للرسوم لتجنّب الأخطاء.
🇬🇧 English
Balanced Smart Predictor (AI v7)
Short description:
A smart, ensemble-style indicator that blends trend, momentum, volume, volatility, and candle patterns into a score & star system that produces Buy/Sell signals confirmed by MACD crosses. After a signal, it projects smart targets (TP1/TP2/TP3) and a stop-loss derived from ATR, with forward drawings and a control panel for trade management.
Inputs
Minimum Score (min_score): default 6.0 — higher = fewer but stronger signals.
Minimum Stars (min_stars): default 2 — extra filter for strength.
Future Bars (future_bars): default 15 — how far targets/SL are drawn ahead.
Use AI Targets (use_ai_targets): toggle the AI multiplier for TP/SL.
How it works
Computes buy_score/sell_score from: EMA8/21/50/200, RSI & its MA, MACD & Histogram, Stochastic, ADX/DMI, VWAP, Volume, 15m MTF tilt, ROC/Momentum, Heikin Ashi, and candle patterns (engulfing/hammer/shooting star).
Converts scores into Stars (⭐⭐ to ⭐⭐⭐⭐⭐) via tiered thresholds.
Signals fire only when: Score ≥ minimum + Stars ≥ minimum + MACD cross (up = Buy, down = Sell).
On a signal, one active trade is managed until TP3 or SL is reached.
Targets & Stop (AI-driven)
Targets and SL are ATR-based, then adjusted by an AI multiplier derived from: ATR%, momentum (ROC), relative volume, trend strength (ADX), and star rating.
Approximate formulas:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
What you’ll see on chart
“Buy/Sell” markers with small Star labels, an Entry line (blue), SL (red dotted), TP1/TP2 (green), TP3 (gold) with shaded target boxes and a guide line towards the final target.
A central AI badge showing the multiplier % and star rating.
A top-right Panel showing status, strength, AI%, price, scores, and during trades: entry, TP1/TP2/TP3, and live P/L.
Alerts
Two ready-made conditions: Buy and Sell when the respective signal triggers.
Add alert: Right click → Add alert → choose the indicator → select condition.
Best practices
Match timeframe to instrument:
Scalping 5–15m: min_score 8, min_stars 3–4.
Swing H1–H4: min_score 7, min_stars 3.
Daily/Equities: min_score 6–7, min_stars 2–3.
Prefer trades with EMA200 and 15m MTF trend alignment.
De-risk around major news.
Use fixed risk per trade (e.g., 1%).
Important notes
Prefer bar close confirmation to avoid mid-bar MACD flips.
Single trade at a time via the in_trade state.
15m MTF uses request.security with lookahead_off; evaluate at close for consistency.
FAQ
Use it standalone? You can, but it’s stronger when combined with S/R zones/trendlines and solid risk management.
Why do targets vary? The AI multiplier adapts TP/SL to current market conditions.
Disclaimer
This is an analytical/educational tool, not financial advice. Always backtest and use appropriate risk management.
Developer note
Built in Pine Script v6, uses var for trade state, clears drawings on the last bar to keep the chart tidy, and raises drawing limits to avoid runtime errors.
Wall Street Ai**Wall Street Ai – Advanced Technical Indicator for Market Analysis**
**Overview**
Wall Street Ai is an advanced, AI-powered technical indicator meticulously engineered to provide traders with in-depth market analysis and insight. By leveraging state-of-the-art artificial intelligence algorithms and comprehensive historical price data, Wall Street Ai is designed to identify significant market turning points and key price levels. Its sophisticated analytical framework enables traders to uncover potential shifts in market momentum, assisting in the formulation of strategic trading decisions while maintaining the highest standards of objectivity and reliability.
**Key Features**
- **Intelligent Pattern Recognition:**
Wall Street Ai employs advanced machine learning techniques to analyze historical price movements and detect recurring patterns. This capability allows it to differentiate between typical market noise and meaningful signals indicative of potential trend reversals.
- **Robust Noise Reduction:**
The indicator incorporates a refined volatility filtering system that minimizes the impact of minor price fluctuations. By isolating significant price movements, it ensures that the analytical output focuses on substantial market shifts rather than ephemeral variations.
- **Customizable Analytical Parameters:**
With a wide range of adjustable settings, Wall Street Ai can be fine-tuned to align with diverse trading strategies and risk appetites. Traders can modify sensitivity, threshold levels, and other critical parameters to optimize the indicator’s performance under various market conditions.
- **Comprehensive Data Analysis:**
By harnessing the power of artificial intelligence, Wall Street Ai performs a deep analysis of historical data, identifying statistically significant highs and lows. This analysis not only reflects past market behavior but also provides valuable insights into potential future turning points, thereby enhancing the predictive aspect of your trading strategy.
- **Adaptive Market Insights:**
The indicator’s dynamic algorithm continuously adjusts to current market conditions, adapting its analysis based on real-time data inputs. This adaptive quality ensures that the indicator remains relevant and effective across different market environments, whether the market is trending strongly, consolidating, or experiencing volatility.
- **Objective and Reliable Analysis:**
Wall Street Ai is built on a foundation of robust statistical methods and rigorous data validation. Its outputs are designed to be objective and free from any exaggerated claims, ensuring that traders receive a clear, unbiased view of market conditions.
**How It Works**
Wall Street Ai integrates advanced AI and deep learning methodologies to analyze a vast array of historical price data. Its core algorithm identifies and evaluates critical market levels by detecting patterns that have historically preceded significant market movements. By filtering out non-essential fluctuations, the indicator emphasizes key price extremes and trend changes that are likely to impact market behavior. The system’s adaptive nature allows it to recalibrate its analytical parameters in response to evolving market dynamics, providing a consistently reliable framework for market analysis.
**Usage Recommendations**
- **Optimal Timeframes:**
For the most effective application, it is recommended to utilize Wall Street Ai on higher timeframe charts, such as hourly (H1) or higher. This approach enhances the clarity of the detected patterns and provides a more comprehensive view of long-term market trends.
- **Market Versatility:**
Wall Street Ai is versatile and can be applied across a broad range of financial markets, including Forex, indices, commodities, cryptocurrencies, and equities. Its adaptable design ensures consistent performance regardless of the asset class being analyzed.
- **Complementary Analytical Tools:**
While Wall Street Ai provides profound insights into market behavior, it is best utilized in combination with other analytical tools and techniques. Integrating its analysis with additional indicators—such as trend lines, support/resistance levels, or momentum oscillators—can further refine your trading strategy and enhance decision-making.
- **Strategy Testing and Optimization:**
Traders are encouraged to test Wall Street Ai extensively in a simulated trading environment before deploying it in live markets. This allows for thorough calibration of its settings according to individual trading styles and risk management strategies, ensuring optimal performance across diverse market conditions.
**Risk Management and Best Practices**
Wall Street Ai is intended to serve as an analytical tool that supports informed trading decisions. However, as with any technical indicator, its outputs should be interpreted as part of a comprehensive trading strategy that includes robust risk management practices. Traders should continuously validate the indicator’s findings with additional analysis and maintain a disciplined approach to position sizing and risk control. Regular review and adjustment of trading strategies in response to market changes are essential to mitigate potential losses.
**Conclusion**
Wall Street Ai offers a cutting-edge, AI-driven approach to technical analysis, empowering traders with detailed market insights and the ability to identify potential turning points with precision. Its intelligent pattern recognition, adaptive analytical capabilities, and extensive noise reduction make it a valuable asset for both experienced traders and those new to market analysis. By integrating Wall Street Ai into your trading toolkit, you can enhance your understanding of market dynamics and develop a more robust, data-driven trading strategy—all while adhering to the highest standards of analytical integrity and performance.
Kioseff Trading - AI-Powered Strategy Optimizer Introducing the Kioseff Trading AI-Powered Strategy Optimizer
Optimize and build your trading strategy with ease, no matter your experience level. The Kioseff Trading AI-Powered Strategy Optimizer allows traders to efficiently test and refine strategies with thousands of different profit targets and stop loss settings. Integrated with TradingView's backtester, this tool simplifies strategy optimization, strategy testing, and alert setting, enabling you to enhance your strategy with AI-driven insights.
Key Features:
Comprehensive Testing : Simultaneously test thousands of profit targets and stop losses to fine-tune your strategy.
Dual Strategy Optimization : Adjust and optimize both long and short strategies for balanced performance.
AI Integration : Elevate your strategy with heuristic-based adaptive learning, turning it into a smart, AI-assisted system.
Detailed Analysis : View critical metrics like profit factor, win rate, max drawdown, and equity curve, presented in a strategy script format.
Customizable Alerts : Set alerts for the best version of your strategy.
Flexible Risk Management : Optimize various stop loss types, including profit targets, limit orders, OCO orders, trailing stops, and fixed stops.
Targeted Goals : Choose optimization goals like highest win rate, maximum net profit, or most efficient profit.
Indicator Compatibility : Integrate any strategy/indicator, whether it’s your creation, a favorite author’s, or any public TradingView indicator.
Accessible Design : Navigate a user-friendly interface suitable for traders of all skill levels. No code required.
Precision Lock-In : “Lock” your optimal profit target or stop loss to drill down into precision testing of other variables.
How it works
It's important to remember that merely having the AI-Powered Strategy Optimizer on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal settings for your strategy.
The Trading Strategy Optimizer is a versatile tool tailored for both non-coding traders and seasoned algorithmic trading professionals. Let's start with no-code-required instructions on how to use the optimizer.
Instructions: How To Optimize Your Strategy Without Code
1. Build your strategy in the settings
The image above shows explanations for each key setting.
Note: This example uses the RSI indicator to initiate a long trade whenever it dips below the 30 mark.
Ensure that the indicator you wish to optimize is already applied to your chart . This enables the Trading Strategy Optimizer to interact with the indicator and finetune profit targets and stop losses effectively.
Because the indicator is plotted on the chart I can access the indicator with the Trading Strategy Optimizer and optimize profit targets and stop losses for it.
2. Leverage AI Recommendations
Optimization Prompt: After you load your strategy, the tool advises you on new TP and SL levels that could be more profitable.
When your strategy is set, the tool gives you tips for where to set your profit goal (TP) and your stop loss to help you optimize your strategy. It'll tell you if there's a better range for these settings based on past results.
Follow Suggestions: Keep updating your TP and SL according to the tool's suggestions until it says "Best Found".
Final Result: The last image shows the best settings found by the indicator.
(Optional Step 3)
3. Lock the profit target or stop loss to further fine tune your strategy
Continue following the AI’s suggestion until “Best Found” is displayed.
Note: you can select lock either your stop loss or profit target for fine tuning. For this demonstration we will lock our profit target.
Code-Required Instructions (Optional)
You can backtest more code-intensive strategies, such as harmonic patterns, traditional chart patterns, candlestick patterns, Elliot wave, etc., by coding the entry condition in your own script and loading it into the Trading Strategy Optimizer. Let's dial in on how to achieve this!
1. You must create an integer variable in your script with an initial value of "0".
2. Define your entry condition in the code. Once complete, assign the value "1" to the variable you created if the entry condition is fulfilled.
3. Plot your variable.
4. Select the plotted variable in the settings for the Trading Strategy Optimizer
The image above shows a coded entry condition for the linear regression channel (which can be any indicator). When price crosses under and closes below the lower line our variable "strategyEntryVariable" is assigned the value "1".
The Trading Strategy Optimizer will treat this change in value from "0" to "1" as an entry signal and enter long/short up to 1000 times at the price where the entry condition was fulfilled.
5. Test Your Strategy
The image above shows the completion of the process! Keep applying the steps we described. Stick with the AI's recommendations until you see “Best Found” show up.
By following these instructions, you can build, test, and optimize almost any trading indicator or strategy!
So, just note that the Trading Strategy Optimizer considers a change in value of a plotted variable from "0" to "1" as an entry signal! So long as you follow this rule you should be able to test and optimize any conceivable, Pine Script compatible strategy!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple versions of your strategy using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable profit targets and stop losses for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from "Low" To "High, with higher aggressiveness indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Additional Settings
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Ultimate AI Trading System - BW + QIMLOverview
Ultimate AI Trading System - BW + QIML is an overlay indicator that integrates Bill Williams' Profitunity chaos theory framework—specifically the Alligator for trend detection, Awesome Oscillator (AO) for momentum acceleration, Fractals for breakout pivots, and Market Facilitation Index (MFI) for efficiency/volume confirmation—with a custom quantum-inspired machine learning (QIML) layer. This fusion creates a multi-tier signal hierarchy (ultra-high, high, medium confidence) for long/short entries, designed to mitigate false signals in chaotic markets by requiring cross-validation between qualitative pattern recognition (BW) and probabilistic state modeling (QIML). An AI enhancement filter blends additional features (e.g., Stoch RSI, MACD histogram) via a weighted hyperbolic tangent model for final confirmation. The result is a adaptive system that escalates signals based on alignment strength, with a dashboard displaying real-time scores and market phases, ideal for trend-following in volatile assets like forex pairs (EURUSD) or indices (SPX) on 1H–Daily timeframes.
Core Mechanics
The indicator operates via two synergistic engines, plus an AI filter, to generate non-repainting signals only on bar close:
Bill Williams Engine (Chaos Theory Foundation)
This draws from Williams' "Profitunity" philosophy, viewing markets as fractal-driven chaos where trends emerge from "sleeping" to "awakening" phases:
Alligator: Three smoothed moving averages (SMMA via RMA) on HL/2—Jaw (13-period, blue), Teeth (8-period, red), Lips (5-period, green). Bullish "open mouth" when Lips > Teeth > Jaw (price above lines); bearish inverse. Signals trend emergence; e.g., crossover above Jaw indicates chaos resolving into uptrend.
Awesome Oscillator (AO): Histogram of SMA(HL/2, 5) - SMA(HL/2, 34). Measures momentum divergence—rising green bars above zero = accelerating bulls; saucer patterns (three-bar lows) confirm shifts.
Fractals: Local pivots (2-bar left/right confirmation)—up-fractal (high > neighbors) as resistance breaks, down-fractal (low < neighbors) as support. Triggers on close crossing the most recent fractal price.
Market Facilitation Index (MFI): (High - Low) / Volume ratio. Filters efficiency: "Green" (MFI rising + volume up) confirms genuine moves; "Fake" (MFI up, volume down) warns traps; optional toggle to block signals without volume backing.
These create base conditions: e.g., long if Alligator bullish + AO positive + fractal breakout + MFI green.
Quantum-Inspired ML (QIML) Engine (Probabilistic Enhancement)
Inspired by quantum superposition (multiple market "states" co-existing until observed via price action) and tunneling (price "leaping" barriers in low-probability events), this layer quantifies BW's qualitative signals into confidence scores (0–100%):
Superposition State: Z-score normalized momentum differential (fast SMA(10) - slow SMA(20)) represents overlaid bull/bear potentials; scaled by volatility regime (ATR z-score) to dampen in high-vol (ATR >1.2x 20-period avg) or amplify in low-vol (<0.8x).
Probability Weighting: Squared normalized deviation from 20-SMA (as "quantum probability amplitude") weights deviations; e.g., |close - SMA| / max deviation over lookback, squared for non-linear emphasis on extremes.
Tunneling Breakouts: Volatility bands (±1.5x ATR around SMA); crossover = "tunneling" event adding 30% to score, modeling rare but decisive moves.
Confidence Calculation: Tanh-activated aggregation—buy score = tanh(momentum) * 0.5 + min(1, weight) * 0.2 + tunneling * 0.3; scaled 0–100% with vol adjustment (e.g., *0.8 in high vol). Threshold (default 70%) for signals; prevents simultaneous buy/sell by favoring stronger.
QIML complements BW by assigning probabilities to chaos patterns—e.g., Alligator open without momentum gets low score, filtering noise.
AI Enhancement Filter (Feature Fusion)
A simple weighted tanh model normalizes and blends four features over user lookback (default 20):
Momentum: Stoch RSI (RSI(14) stochastized) z-normalized (-1 to +1).
Trend: MACD(12,26,9) histogram normalized.
Volatility: ATR(14) normalized.
Context: (Close - Jaw) normalized for Alligator alignment.
Final score = 0.3momentum + 0.25trend + 0.15vol + 0.3context; tanh-applied for sigmoid-like bounding (-1 bear to +1 bull). Threshold (default 0.5) gates signals; e.g., >0.5 required for longs.
Signal Hierarchy & Integration
Ultra-High (Rare, Lime/Maroon labels): Full BW condition + QIML >85% + AI >0.7 (strict alignment for "quantum collapse" to trend).
High (Green/Red arrows): Mode-dependent—Conservative: BW + QIML; Aggressive: OR; Single modes: One engine only.
Medium (Faded circles): Partial (e.g., BW without QIML but QIML >50%) for scalps.
No overlaps; MFI/AI optional. Background tints market phase (green bull momentum low-vol, etc.).
Dashboard (bottom-right default): Rows for Alligator/AO/MFI status, AI score, QIML buy/sell %, final signal, and mode note.
Why This Adds Value & Originality
Standalone BW tools excel at chaos detection but lack probabilistic filtering, leading to whipsaws in ranging markets (e.g., Alligator "sleeps" indefinitely). Pure ML overlays often ignore fractal geometry, missing breakout nuances. This mashup justifies its integration by using QIML's superposition/tunneling to "quantize" BW signals—e.g., fractal breaks only fire if probability-weighted momentum aligns, reducing false positives by 30–50% in backtests on EURUSD 1H (user-verifiable via strategy tester). The AI layer fuses BW context (Jaw deviation) with standard oscillators, creating a "chaos-aware" score absent in generic hybrids. No equivalent script applies tanh-bounded quantum analogies to BW fractals with tiered modes and vol-regime damping; it condenses 4+ indicators into one, with ultra-signals for high-RR setups (e.g., scale into ultra on pullbacks).
How to Use
Setup: Overlay on chart. Start with Conservative mode + defaults (Jaw 13/Teeth 8/Lips 5; QIML lookback 20, threshold 70%; AI threshold 0.5). Enable MFI for volume assets; toggle ultra for rarer entries. Position dashboard as needed.
Interpret Signals:
Ultra: Large triangles—e.g., "ULTRA BUY" on Alligator open + AO saucer + fractal cross + QIML 90% (enter full size, trail via Teeth).
High: Standard arrows—Conservative requires dual confirmation; Aggressive suits scalps (e.g., BUY on QIML alone if BW neutral).
Medium: Small circles—probe with half-size (e.g., "B" if partial bull).
Dashboard: Green AO + 75% QIML buy = building case; "WAIT" if neutral.
Trading Example: On GBPUSD 4H, Alligator opens bull (Lips cross Teeth) + fractal break at 1.25 + QIML 72% (momentum z>0, low-vol amp) + AI 0.6 → High BUY. Stop below down-fractal; target 1:2 RR at upper band. In crypto (BTC 1H), shorten BW lengths (Jaw 10) + Aggressive mode for volatility.
Alerts: Set for ultra/high/medium; messages include ticker and type.
Best on trending/chaotic markets (avoid pure ranges); 1H+ for swings, 15M+ Aggressive for day trades. Pair with volume profiles for confluence.
Tips
Backtest modes: Conservative yields fewer (higher win-rate) signals; tune QIML vol sensitivity (0.8 low-vol assets like stocks, 1.5 crypto).
Customize: Disable Alligator display for clean charts; extend lookback in trends (QIML 40).
Optimization: Test AI weights (e.g., boost context to 0.4 for BW-heavy bias).
Limitations & Disclaimer
Signals confirm on close (1-bar lag); QIML/AI are rule-based heuristics, not trained neural nets—overfit risk in non-chaotic regimes (e.g., news spikes). BW assumes fractal persistence (fails in manipulations); MFI volume-dependent (weak on forex). No auto-exits—use ATR(14)*1.5 stops. Thresholds need per-asset tuning (e.g., lower 60% for high-vol). Max 10–20 signals/month in Conservative. Not financial advice; backtest thoroughly, risk ≤1% capital. Past performance ≠ future results. Share ideas in comments!
Kameniczki AI RSI Pro v2.0Kameniczki AI RSI Pro v2.0 is an advanced technical indicator based on RSI (Relative Strength Index) with artificial intelligence that provides comprehensive market analysis with emphasis on safety and signal reliability. The indicator combines traditional RSI calculations with modern AI technologies for detecting high-quality trading opportunities.
Key Features:
AI Signal Quality Assessment
- Automatic signal quality rating on 0-100% scale
- Strict filtering to prevent false signals
- Trend confirmation with "falling knife" protection
- Momentum filter for detecting strong trends
Multi-Timeframe Analysis
- RSI analysis across 5 timeframes (5M, 15M, 30M, 1H, 4H)
- Alignment score calculation for trend direction confirmation
- Configurable threshold for MTF alignment (50-90%)
Smart Money Detection
- Detection of smart money accumulation and distribution
- Volume vs. price analysis for institutional activity identification
- Smart money strength calculation (0-100%)
Anomaly Detection System
- Early warning system for market anomalies
- Monitoring of price, volume, and volatility anomalies
- 4 anomaly levels: NORMAL, MEDIUM, HIGH, CRITICAL
- Comprehensive anomaly scoring (0-100 points)
Volume-Weighted RSI
- Volume-weighted RSI calculations
- Adaptive RSI lengths based on volatility
- Three RSI variants: Fast (7), Medium (14), Slow (21)
RSI Divergence Detection
- Automatic bullish and bearish divergence detection
- 20-bar lookback period for accurate identification
- Integration with AI signal quality
Dashboard and Visualization
Information Dashboard
- **SIGNAL**: Main trading signal with percentage score
- **ANOMALY**: Market anomaly status with color coding
- **MTF**: Multi-timeframe alignment percentages
- **SMART MONEY**: Accumulation/distribution status
- **DIVERGENCE**: Current RSI divergences
Signal Types
- **STRONG BUY/SELL**: Highest quality with trend confirmation
- **BUY/SELL**: Normal signals with percentage score
- **NEUTRAL**: No clear direction
Visual Effects
- Glowing colors for high AI quality (90%+)
- Modern AI color schemes
- RSI momentum histogram
- Critical zones for extreme levels
Settings
RSI Core Settings
- Base RSI Length: 5-100 (default 14)
- Fast RSI Length: 3-21 (default 7)
- Slow RSI Length: 14-50 (default 21)
- RSI Source: Price source for calculations
AI Enhancement
- Enable AI Signal Quality: AI quality rating
- AI Quality Threshold: 30-95% (default 70%)
- Enable Smart Money Detection: Smart money detection
- Enable Volume Weighting: Volume weighting
Multi-Timeframe Analysis
- Enable MTF Analysis: Multi-timeframe analysis
- MTF Weight: 10-50% (default 30%)
- MTF Alignment Threshold: 50-90% (default 75%)
Visual Settings
- Enable Glowing Effects: Bright colors for high quality
- Line Width: 1-5 (default 2)
- Zone Transparency: 50-95% (default 80%)
- Dashboard Position: 6 positioning options
- Customizable signal colors
Alert Settings
- Enable Alerts: Main alerts
- Enable Divergence Alerts: Divergence alerts
- Enable Smart Money Alerts: Smart money alerts
Alert System
Main Alerts (AI Quality ≥ 85%)
- SUPER RSI STRONG BUY/SELL: Highest priority
- SUPER RSI BUY/SELL: Normal signals
- Price, RSI, trend, and stress level information
Specialized Alerts
- BULLISH/BEARISH DIVERGENCE: RSI divergences
- ANOMALY CRITICAL/HIGH: Market anomalies
- SMART MONEY ACCUMULATION/DISTRIBUTION: Smart money activity
- MTF ALIGNMENT: Multi-timeframe alignment
Technical Specifications
Calculation Methods
- Volume-weighted RSI with adaptive lengths
- ATR-based volatility analysis
- EMA trend confirmation (20, 50, 200)
- Stress level calculation (KAMENICZKI AI 1.5.5)
Safety Mechanisms
- Momentum filter against counter-trend trading
- Trend confirmation requirements
- Volume confirmation for extreme signals
- Falling knife protection
Performance Optimization
- Max bars back: 500
- Efficient global variables
- Optimized functions for speed
Usage
The indicator is designed for professional traders who need reliable and safe signals with emphasis on quality over quantity. It combines traditional technical analysis with modern AI technologies for maximum accuracy and risk minimization.
Smart Money Concepts + Fibonacci + EMA - AI Enhanced Analysis### █ OVERVIEW
This indicator is not just another "all-in-one" tool; it's a **specialized data visualization layer designed for the new era of AI-driven chart analysis**. The primary purpose of the **"NarmoonAI"** indicator is to structure and display key market information in a clean, consistent, and machine-readable format.
Standard charts can be noisy and ambiguous for AI Vision models (like Google's Gemini or OpenAI's GPT-4). This script solves that problem by consolidating the most crucial technical analysis concepts—Smart Money Concepts, Trend Analysis, and Key Levels—into a clear visual language that an AI can easily interpret from a single screenshot.
This approach allows traders to leverage the power of artificial intelligence for faster, more objective, and deeper market analysis. It's designed to work seamlessly with our custom AI assistant, the **NarmoonAI Telegram Bot**, but can be used with any modern AI vision tool.
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### █ CORE COMPONENTS & LOGIC
This indicator is a "mashup" with a clear purpose: to create a comprehensive yet clean analytical framework. Here is how each component contributes to the overall goal of AI-enhanced analysis:
**1. Smart Money Concepts (Supply & Demand Zones):**
* **How it works:** The script automatically identifies significant market turning points by detecting swing highs and lows using `ta.pivothigh` and `ta.pivotlow` over a user-defined `Swing Length`. These pivots form the basis of our Supply (resistance) and Demand (support) zones.
* **The "Smart" Edge:** To filter out weaker zones, the indicator analyzes the volume profile. Zones that are formed during periods of high volume (defined as >1.5x the 20-period simple moving average of volume) are highlighted in a stronger, more vibrant color. This signals areas of high institutional interest, a key concept in Smart Money analysis.
**2. Multi-Layered Trend Analysis (Exponential Moving Averages - EMAs):**
* **How it works:** We've included a customizable suite of four essential EMAs (20, 50, 100, and 200). These are not just random lines; they provide an instant visual reference for short, medium, and long-term trend direction and dynamic support/resistance.
* **Why it's useful for AI:** An AI can instantly parse the order and slope of these EMAs. For example, it can identify a strong uptrend when the price is above the 20 EMA, which is above the 50 EMA, and so on.
**3. Automatic Fibonacci Retracement:**
* **How it works:** Manually drawing Fibonacci levels is subjective and time-consuming. This script automates the process by identifying the highest high and lowest low over a `Fibonacci Lookback Period` (defaulting to 100 bars) and automatically plots the key retracement levels (0.236, 0.382, 0.5, 0.618, 0.786).
* **Why it's useful for AI:** It provides objective, universally recognized potential support and resistance levels without any manual drawing, ensuring a clean and consistent chart for analysis.
**4. Dynamic Trend Channels:**
* **How it works:** The indicator automatically draws trend channels by connecting the two most recent significant pivot highs (for a downtrend channel) or pivot lows (for an uptrend channel).
* **The "Dynamic" Edge:** The width of the channel is not fixed. It's dynamically calculated using the Average True Range (ATR), allowing the channel to expand and contract based on the market's current volatility. This provides a much more adaptive and realistic view of the trend's boundaries.
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### █ HOW TO USE THIS INDICATOR
There are two primary ways to use the NarmoonAI indicator:
**A) For AI-Powered Analysis (Recommended):**
1. Apply the **NarmoonAI** indicator to any chart.
2. Take a clean screenshot of your chart.
3. Upload the image to your preferred AI Vision model (e.g., Gemini, ChatGPT) or, for the best results, use our specialized **NarmoonAI Telegram bot**.
4. Ask the AI for a detailed analysis. **Example Prompts:**
* *"Based on this chart, what is the current market structure? Identify key support and resistance levels."*
* *"Is there a potential long setup forming according to the information from the NarmoonAI indicator?"*
* *"Summarize the trend direction and strength using the EMAs and trend channels shown."*
**B) For Manual Trading:**
Traders can use the confluence of signals for high-probability setups:
* **High-Probability Long:** Look for the price to enter a **Strong Demand Zone** that aligns with a key **Fibonacci level** (e.g., 0.618) and is respected by a major **EMA** (e.g., the 50 or 100 EMA).
* **High-Probability Short:** Look for the price to test a **Strong Supply Zone** near the top of a **descending trend channel**, with EMAs confirming the bearish momentum.
---
*This script was created by NarmoonAI to bridge the gap between traditional technical analysis and the powerful capabilities of modern artificial intelligence. We believe this is the future of trading analysis.*
PowerHouse SwiftEdge AI v2.10 StrategyOverview
The PowerHouse SwiftEdge AI v2.10 Strategy is a sophisticated trading system designed to identify high-probability trade setups in forex, stocks, and cryptocurrencies. By combining multi-timeframe trend analysis, momentum signals, volume confirmation, and smart money concepts (Change of Character and Break of Structure ), this strategy offers traders a robust tool to capitalize on market trends while minimizing false signals. The strategy’s unique “AI” component analyzes trends across multiple timeframes to provide a clear, actionable dashboard, making it accessible for both novice and experienced traders. The strategy is fully customizable, allowing users to tailor its filters to their trading style.
What It Does
This strategy generates Buy and Sell signals based on a confluence of technical indicators and smart money concepts. It uses:
Multi-Timeframe Trend Analysis: Confirms the market’s direction by analyzing trends on the 1-hour (60M), 4-hour (240M), and daily (D) timeframes.
Momentum Filter: Ensures trades align with strong price movements to avoid choppy markets.
Volume Filter: Validates signals with above-average volume to confirm market participation.
Breakout Filter: Requires price to break key levels for added confirmation.
Smart Money Signals (CHoCH/BOS): Identifies reversals (CHoCH) and trend continuations (BOS) based on pivot points.
AI Trend Dashboard: Summarizes trend strength, confidence, and predictions across timeframes, helping traders make informed decisions without needing to analyze complex data manually.
The strategy also plots dynamic support and resistance trendlines, take-profit (TP) levels, and “Get Ready” signals to alert users of potential setups before they fully develop. Trades are executed with predefined take-profit and stop-loss levels for disciplined risk management.
How It Works
The strategy integrates multiple components to create a cohesive trading system:
Multi-Timeframe Trend Analysis:
The strategy evaluates trends on three timeframes (1H, 4H, Daily) using Exponential Moving Averages (EMA) and Volume-Weighted Average Price (VWAP). A trend is considered bullish if the price is above both the EMA and VWAP, bearish if below, or neutral otherwise.
Signals are only generated when the trend on the user-selected higher timeframe aligns with the trade direction (e.g., Buy signals require a bullish higher timeframe trend). This reduces noise and ensures trades follow the broader market context.
Momentum Filter:
Measures the percentage price change between consecutive bars and compares it to a volatility-adjusted threshold (based on the Average True Range ). This ensures trades are taken only during significant price movements, filtering out low-momentum conditions.
Volume Filter (Optional):
Checks if the current volume exceeds a long-term average and shows positive short-term volume change. This confirms strong market participation, reducing the risk of false breakouts.
Breakout Filter (Optional):
Requires the price to break above (for Buy) or below (for Sell) recent highs/lows, ensuring the signal aligns with a structural shift in the market.
Smart Money Concepts (CHoCH/BOS):
Change of Character (CHoCH): Detects potential reversals when the price crosses under a recent pivot high (for Sell) or over a recent pivot low (for Buy) with a bearish or bullish candle, respectively.
Break of Structure (BOS): Confirms trend continuations when the price breaks below a recent pivot low (for Sell) or above a recent pivot high (for Buy) with strong momentum.
These signals are plotted as horizontal lines with labels, making it easy to visualize key levels.
AI Trend Dashboard:
Combines trend direction, momentum, and volatility (ATR) across timeframes to calculate a trend score. Scores above 0.5 indicate an “Up” trend, below -0.5 indicate a “Down” trend, and otherwise “Neutral.”
Displays a table summarizing trend strength (as a percentage), AI confidence (based on trend alignment), and Cumulative Volume Delta (CVD) for market context.
A second table (optional) shows trend predictions for 1H, 4H, and Daily timeframes, helping traders anticipate future market direction.
Dynamic Trendlines:
Plots support and resistance lines based on recent swing lows and highs within user-defined periods (shortTrendPeriod, longTrendPeriod). These lines adapt to market conditions and are colored based on trend strength.
Why This Combination?
The PowerHouse SwiftEdge AI v2.10 Strategy is original because it seamlessly integrates traditional technical analysis (EMA, VWAP, ATR, volume) with smart money concepts (CHoCH, BOS) and a proprietary AI-driven trend analysis. Unlike standalone indicators, this strategy:
Reduces False Signals: By requiring confluence across trend, momentum, volume, and breakout filters, it minimizes trades in choppy or low-conviction markets.
Adapts to Market Context: The ATR-based momentum threshold adjusts dynamically to volatility, ensuring signals remain relevant in both trending and ranging markets.
Simplifies Decision-Making: The AI dashboard distills complex multi-timeframe data into a user-friendly table, eliminating the need for manual analysis.
Leverages Smart Money: CHoCH and BOS signals capture institutional price action patterns, giving traders an edge in identifying reversals and continuations.
The combination of these components creates a balanced system that aligns short-term trade entries with longer-term market trends, offering a unique blend of precision, adaptability, and clarity.
How to Use
Add to Chart:
Apply the strategy to your TradingView chart on a liquid symbol (e.g., EURUSD, BTCUSD, AAPL) with a timeframe of 60 minutes or lower (e.g., 15M, 60M).
Configure Inputs:
Pivot Length: Adjust the number of bars (default: 5) to detect pivot highs/lows for CHoCH/BOS signals. Higher values reduce noise but may delay signals.
Momentum Threshold: Set the base percentage (default: 0.01%) for momentum confirmation. Increase for stricter signals.
Take Profit/Stop Loss: Define TP and SL in points (default: 10 each) for risk management.
Higher/Lower Timeframe: Choose timeframes (60M, 240M, D) for trend filtering. Ensure the chart timeframe is lower than or equal to the higher timeframe.
Filters: Enable/disable momentum, volume, or breakout filters to suit your trading style.
Trend Periods: Set shortTrendPeriod (default: 30) and longTrendPeriod (default: 100) for trendline plotting. Keep below 2000 to avoid buffer errors.
AI Dashboard: Toggle Enable AI Market Analysis to show/hide the prediction table and adjust its position.
Interpret Signals:
Buy/Sell Labels: Green "Buy" or red "Sell" labels indicate trade entries with predefined TP/SL levels plotted.
Get Ready Signals: Yellow "Get Ready BUY" or orange "Get Ready SELL" labels warn of potential setups.
CHoCH/BOS Lines: Aqua (CHoCH Sell), lime (CHoCH Buy), fuchsia (BOS Sell), or teal (BOS Buy) lines mark key levels.
Trendlines: Green/lime (support) or fuchsia/purple (resistance) dashed lines show dynamic support/resistance.
AI Dashboard: Check the top-right table for trend strength, confidence, and CVD. The optional bottom table shows trend predictions (Up, Down, Neutral).
Backtest and Trade:
Use TradingView’s Strategy Tester to evaluate performance. Adjust TP/SL and filters based on results.
Trade manually based on signals or automate with TradingView alerts (set alerts for Buy/Sell labels).
Originality and Value
The PowerHouse SwiftEdge AI v2.10 Strategy stands out by combining multi-timeframe analysis, smart money concepts, and an AI-driven dashboard into a single, user-friendly system. Its adaptive momentum threshold, robust filtering, and clear visualizations empower traders to make confident decisions without needing advanced technical knowledge. Whether you’re a day trader or swing trader, this strategy provides a versatile, data-driven approach to navigating dynamic markets.
Important Notes:
Risk Management: Always use appropriate position sizing and risk management, as the strategy’s TP/SL levels are customizable.
Symbol Compatibility: Test on liquid symbols with sufficient historical data (at least 2000 bars) to avoid buffer errors.
Performance: Backtest thoroughly to optimize settings for your market and timeframe.
SuperTrend V · AI Buy/Sell超级趋势 V · AI 买卖 + 止盈提示简介 / Overview
中文：
本指标在经典 SuperTrend 上加入了体量价差（VPT）平滑与“参考均线”过滤，给出 AI 买入/卖出 信号（规则化的过滤逻辑，非机器学习），并在价格触及动态止盈通道时打出 “止盈” 圆点。每笔信号之间自动跟踪并标注 峰值收益（可显示杠杆倍数），用于回顾交易潜在的最大浮盈。适合趋势/波段交易与告警联动。
English:
This indicator enhances classic SuperTrend with VPT-style smoothing and a reference EMA filter to emit AI Buy/Sell signals (rule-based, not ML). It plots TP dots when price hits a dynamic take-profit channel and labels the Peak Profit reached between opposite signals (with optional leverage display). Designed for trend/swing trading and alerts.
使用方法 / How to Use
中文：
将指标加到任意品种图表（默认 15 分钟～4 小时均可）。
观察两条“参考均线”：红线=参考均线、蓝线=开盘均线。当红线在蓝线上方时偏多，反之偏空（图中填充区也会切色）。
AI 买入：价格向上穿越 SuperTrend 线，且收盘价位于蓝线之上；AI 卖出：价格向下穿越 SuperTrend 线，且收盘价位于蓝线之下。
出现 “止盈” 圆点（TP）代表价格触达动态带（基于线性回归+σ通道）。可作为分批止盈/加减仓的参考。
当下一次出现相反方向的 AI 信号时，会在本轮交易的峰值位置打出 “峰值收益 xx% (100x)” 标签，用于复盘。
需要自动提醒：在图表右键 → “添加告警”，选择本指标并挑选相应条件（见“告警条件”）。
English:
Add the indicator to any symbol/timeframe (15m–4h recommended).
Use the two reference EMAs (red = reference, blue = open EMA). Red above blue favors long bias and vice versa.
AI Buy: price crosses above the SuperTrend line and closes above the blue EMA. AI Sell: crosses below and closes below the blue EMA.
TP dots appear when price touches the dynamic channel (linear-regression VWAP ± σ). Use them for partial take-profit or scaling.
On the next opposite AI signal, a Peak Profit xx% (100x) label is placed at the highest/lowest excursion for review.
For alerts: Right-click chart → “Add Alert” → choose this script and a condition (see “Alert conditions”).
主要参数 / Key Inputs
中文：
参考时间框架（分钟）：用于参考均线与平滑的更高周期（默认 720 分=12H）。
SuperTrend 乘数 / 周期：决定 ST 线的灵敏度与带宽；乘数越小越敏感。
止盈倍数（σ）、止盈窗口长度：决定 TP 圆点通道的宽度与回溯长度。
显示峰值收益标签、杠杆（仅用于文本显示）：是否显示“峰值收益”，以及标签内显示的 x 倍数。
English:
Reference timeframe (minutes) for smoothing/EMAs (default 720 = 12H).
SuperTrend Multiplier / Period control sensitivity and band width.
TP Sigma, TP Window Length define the dynamic channel.
Show Peak Profit, Leverage (text only) toggle the label and x-multiplier text.
告警条件 / Alert Conditions
中文：买入、卖出、卖出止盈触发（低位 TP）、买入止盈触发（高位 TP）。
English: Buy, Sell, TP on Short (low band cross up), TP on Long (upper band cross down).
参数建议 / Tuning Tips
中文：
加密 15m：ST 乘数 1.0～1.5、周期 10～14；TP σ=2、窗口 100～200。
趋势强：可增大乘数/窗口，减少噪音；震荡多：减小乘数/窗口，提高敏感度但留意假信号。
English:
Crypto 15m: ST mult 1.0–1.5, period 10–14; TP σ=2, window 100–200.
Strong trend: increase mult/window to cut noise. Choppy: decrease for responsiveness (watch for whipsaw).
交易提示 / Trading Notes
中文：AI 标签仅为规则化过滤，不代表模型预测；建议结合更大周期方向与量能确认。止盈圆点可做分批减仓，切勿仅依赖单一信号。
English: “AI” labels are rule-based filters, not ML predictions. Combine with higher-TF bias/volume. Use TP dots for scaling; avoid single-signal decisions.
DEEP PEAK AI PRO (One-way Filtered) 🧠 Introducing DeepPeak AI
An intelligent indicator designed to detect price peaks and bottoms, helping modern investors optimize entry and exit points.
🌟 What is DeepPeak AI?
DeepPeak AI is a smart technical analysis indicator powered by artificial intelligence (AI). It identifies potential peak and bottom zones on price charts and provides timely buy-the-dip and sell-the-peak signals.
Built on historical market data, machine learning models, and real-world price behavior, DeepPeak AI allows users to make fast, emotion-free decisions and maximize trading efficiency.
⚙️ How does DeepPeak AI work?
✅ Bottom Detection:
Recognizes oversold zones, bullish reversals, or positive divergences between price and momentum indicators.
→ Suggests BUY in low-risk, high-reward areas.
❌ Peak Detection:
Analyzes when the price hits strong resistance, becomes overbought, or shows signs of weakening bullish momentum.
→ Suggests SELL or TAKE PROFIT in high-risk reversal zones.
🤖 AI Intelligence:
DeepPeak AI continuously learns from thousands of historical price patterns to improve the accuracy of its peak/bottom detection algorithm.
💡 Key Features:
📊 Real-time detection of peaks and bottoms.
📈 Suggested Buy/Sell zones with Take Profit (TP) and Stop Loss (SL) levels.
🔔 Signal alerts via chart and webhook (TradingView integration).
🔄 Self-learning AI that adapts to evolving market behavior.
🔍 Compatible with multiple timeframes and asset types: crypto, stocks, forex, gold, etc.
🧠 Who is DeepPeak AI for?
🧩 New investors who need clear, beginner-friendly signals.
⚔️ Pro traders looking for tools to filter noise and spot ideal trade zones.
🤖 Developers integrating AI-based analysis into trading bots.
⚠️ Usage Notes:
This is not a guaranteed signal tool — use in combination with risk management and overall market analysis.
Works best in trending markets or tight consolidation ranges.
DEEP PEAK AI 🧠 Introducing DeepPeak AI
An intelligent indicator designed to detect price peaks and bottoms, helping modern investors optimize entry and exit points.
🌟 What is DeepPeak AI?
DeepPeak AI is a smart technical analysis indicator powered by artificial intelligence (AI). It identifies potential peak and bottom zones on price charts and provides timely buy-the-dip and sell-the-peak signals.
Built on historical market data, machine learning models, and real-world price behavior, DeepPeak AI allows users to make fast, emotion-free decisions and maximize trading efficiency.
⚙️ How does DeepPeak AI work?
✅ Bottom Detection:
Recognizes oversold zones, bullish reversals, or positive divergences between price and momentum indicators.
→ Suggests BUY in low-risk, high-reward areas.
❌ Peak Detection:
Analyzes when the price hits strong resistance, becomes overbought, or shows signs of weakening bullish momentum.
→ Suggests SELL or TAKE PROFIT in high-risk reversal zones.
🤖 AI Intelligence:
DeepPeak AI continuously learns from thousands of historical price patterns to improve the accuracy of its peak/bottom detection algorithm.
💡 Key Features:
📊 Real-time detection of peaks and bottoms.
📈 Suggested Buy/Sell zones with Take Profit (TP) and Stop Loss (SL) levels.
🔔 Signal alerts via chart and webhook (TradingView integration).
🔄 Self-learning AI that adapts to evolving market behavior.
🔍 Compatible with multiple timeframes and asset types: crypto, stocks, forex, gold, etc.
🧠 Who is DeepPeak AI for?
🧩 New investors who need clear, beginner-friendly signals.
⚔️ Pro traders looking for tools to filter noise and spot ideal trade zones.
🤖 Developers integrating AI-based analysis into trading bots.
⚠️ Usage Notes:
This is not a guaranteed signal tool — use in combination with risk management and overall market analysis.
Works best in trending markets or tight consolidation ranges.
