From 42626cef9d8aed2d06bb96a50f9cae197b381af7 Mon Sep 17 00:00:00 2001 From: Toh4iem9 Date: Tue, 3 Feb 2026 12:49:20 +0100 Subject: [PATCH] new files added --- Scripts/MyScripts/Market_Scanner_Pro.md | 72 +++++++++++++++++++++++++ 1 file changed, 72 insertions(+) create mode 100644 Scripts/MyScripts/Market_Scanner_Pro.md diff --git a/Scripts/MyScripts/Market_Scanner_Pro.md b/Scripts/MyScripts/Market_Scanner_Pro.md new file mode 100644 index 0000000..d1e880c --- /dev/null +++ b/Scripts/MyScripts/Market_Scanner_Pro.md @@ -0,0 +1,72 @@ +# Market Scanner Pro (Script) + +## 1. Summary (Introduction) + +The `Market_Scanner_Pro` is a high-performance quantitative analysis tool designed to bridge the gap between technical charting and AI-assisted trading. It performs a multi-timeframe, multi-indicator scan across a portfolio of assets and exports the "Market State" into a structured CSV format suitable for Large Language Models (LLMs) or statistical analysis tools (Python/Excel). + +Instead of relying on basic price data, this script generates **"QuantScan 2.0"** metrics: it converts raw indicator values into normalized scores (e.g., Z-Score, Efficiency Ratio), providing a deep insight into Trend Quality, Momentum, and Statistical Extremes. + +## 2. Methodology and Logic + +The script employs a **Hybrid Analysis Model**, splitting metrics into two logical timeframes: + +1. **Context Layer (H1):** Analyzes the "Big Picture". It determines the dominant trend direction, the structural quality of that trend, and key support/resistance zones. +2. **Trigger Layer (M15):** Analyzes the "Execution Timing". It looks for momentum shifts, volume anomalies, and statistical reversion signals. + +### Key Metrics Calculated + +* **Trend Score (Z-Score Proxy):** Measures how far the price is from the mean (DSMA) in units of volatility (ATR). A score of +2.0 means the price is 2 standard deviations above the trend. +* **Trend Quality (Efficiency Ratio):** Differentiates between a smooth, tradeable trend (High ER) and a choppy, dangerous market (Low ER). +* **Volatility Regime (Squeeze):** Identifies periods of low volatility (Bollinger Bands inside Keltner Channels) that often precede explosive moves. +* **Volume Quality (RVOL):** Checks if the current move is supported by institutional volume (Relative Volume > 1.0). + +## 3. MQL5 Implementation Details + +The script is built upon the **"Professional Indicator Suite"** architecture, ensuring mathematical precision and performance. + +* **Calculation Engines (`.mqh`):** + Instead of using slow `iCustom` calls, the script directly instantiates the optimized Calculation Classes (e.g., `CDSMACalculator`, `CVWAPCalculator`) used by our indicators. This guarantees that the CSV data matches the chart visuals 100%. +* **Defensive Programming:** + The implementation includes rigorous "Safety Checks" (e.g., array bounds checking in ATR, data availability validation) to prevent runtime crashes, even when scanning hundreds of symbols. +* **Smart Data Fetching:** + It utilizes `FetchData` wrappers that efficiently retrieve OHLCV data and organize it into chronological arrays (`ArraySetAsSeries(false)`), optimized for our incremental calculation engines. + +## 4. Parameters + +* **Scanner Config:** + * `InpUseMarketWatch`: If `true`, scans every active symbol in the Market Watch window. + * `InpSymbolList`: A comma-separated list of symbols to scan if Market Watch is disabled (e.g., `EURUSD, BTCUSD, US500`). +* **Timeframes:** + * `InpTFFast`: The timeframe for Trigger metrics (Default: `M15`). + * `InpTFSlow`: The timeframe for Context metrics (Default: `H1`). +* **Metric Settings:** + * Allows fine-tuning of indicators (e.g., `InpDSMAPeriod`, `InpLaguerreGamma`, `InpRVOLPeriod`). +* **Squeeze Settings:** + * Controls the sensitivity of the volatility squeeze detection (`BB Multiplier`, `KC Multiplier`). + +## 5. Output Data Structure (CSV) + +The script generates a file named `QuantScan_YYYY.MM.DD_HHMM.csv` in the `MQL5\Files` folder. + +### Columns Explanation + +| Header | Description | Interpretation | +| :--- | :--- | :--- | +| **`TIME`** | Timestamp | `YYYY.MM.DD HH:MM` format. | +| **`SYMBOL`** | Asset Name | e.g. `EURUSD`. | +| **`PRICE`** | Current Bid | The snapshot price at scan time. | +| **`TREND_SCORE`** | **H1 Trend Strength** | Normalized deviation from trend.
• `> +1.0`: Strong Bull
• `< -1.0`: Strong Bear | +| **`TREND_QUAL`** | **H1 Efficiency** | Quality of the trend (Kaufman ER).
• `> 0.6`: Clean Trend
• `< 0.3`: Noise/Chop | +| **`ZONE`** | **H1 Structure** | Murrey Math Level.
• `Extreme`: Reversal likely.
• `Range`: Trading Zone. | +| **`MOMENTUM`** | **M15 Laguerre** | Fast momentum (0.0 - 1.0).
• `> 0.8`: Bullish Pressure
• `< 0.2`: Bearish Pressure | +| **`VOL_QUAL`** | **M15 RVOL** | Instant Institutional Interest.
• `> 1.5`: High Activity
• `< 0.8`: No interest | +| **`SQUEEZE`** | **M15 Vola State** | TTM Squeeze status.
• `ON`: Energy building (Prepare for breakout). | +| **`TSI_DIR`** | **M15 Cycle** | True Strength Index direction (`BULL` / `BEAR`). | + +## 6. Usage Workflow + +1. **Run the Script:** Drag `Market_Scanner_Pro` onto any chart. +2. **Wait for Completion:** Check the "Experts" tab for progress. It usually takes a few seconds to scan 20-30 symbols. +3. **Locate File:** Open "File -> Open Data Folder -> MQL5 -> Files". +4. **Process with AI:** Upload the `QuantScan_....csv` file to your LLM (GPT-4 / Claude 3) with a prompt like: + > *"Analyze this market data. Identify high-quality trend setups where TREND_QUANT > 0.6 and SQUEEZE is ON. Also, warn me about mean reversion risks where Z_SCORE > 2.5."*