gilded-python

byonlytrading 009

Here is a structured AI prompt designed to build your prediction tool. You can copy and paste this into an advanced LLM (like Claude 3.5 Sonnet or GPT-4o) to execute your three-step plan. ## AI Tool Development Prompt Role: You are a Quantitative Trading Developer and Technical Analyst. Objective: Create a Python-based predictive model that forecasts the next period's High and Low prices based on the previous High/Low data, following the three steps outlined below. [1] ------------------------------ ## Step 1: Literature Analysis (Free Ebooks & Knowledge) Research and synthesize advanced technical analysis concepts from authoritative trading literature available online (e.g., John J. Murphy’s Technical Analysis of the Financial Markets, James Dalton’s [Mind Over Markets](https://www.google.com/search?q=Mind+Over+Markets&kgmid=/hkb/Cg4KCGxhbmd1YWdlEgJlbgoMCgR0eXBlEgRCT09LCiAKC2VudGl0eV9uYW1lEhFtaW5kIG92ZXIgbWFya2V0cw%3D%3D#sv=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_77EH), or Steve Nison’s [Candlestick Charting](https://www.google.com/search?q=Candlestick+Charting&kgmid=/hkb/Cg4KCGxhbmd1YWdlEgJlbgoMCgR0eXBlEgRCT09LCiMKC2VudGl0eV9uYW1lEhRjYW5kbGVzdGljayBjaGFydGluZw%3D%3D#sv=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)). Specifically, extract: * Price Action Rules: How "Previous Day High/Low" (PDH/PDL) act as "kill zones" or liquidity pivots. * Mean Reversion: Using Z-score or Bollinger Band deviations to predict when an extreme high/low will snap back to the mean. * Sequence of Highs/Lows: Logic for identifying trend continuation (Higher Highs/Higher Lows) vs. reversals (Lower Highs/Lower Bottoms). [2, 3, 4, 5, 6] ## Step 2: Database & Model Preparation Create a Python blueprint to handle a historical OHLC (Open, High, Low, Close) database. * Technical Indicator Layer: Integrate code for EMA (20/50/200), RSI (momentum signals), and ATR (volatility for range prediction). * Predictive Logic: Implement an LSTM (Long Short-Term Memory) or Random Forest framework to process the sequence of previous lows/highs and output a predicted range for the next candle. * Risk Management: Add a module to calculate stop-loss levels based on a "7% rule" or ATR-based volatility. [7, 8, 9, 10, 11] ## Step 3: Asset Selection (Indian & Forex Markets) Present a list of the most liquid and "technically clean" assets for analysis. Use the following as a baseline of popular choices for 2026: Indian Market (NSE/BSE) Top Picks: * Blue-chips: Reliance Industries (RELIANCE), HDFC Bank (HDFCBANK), and ICICI Bank (ICICIBANK). * Momentum/Growth: Bajaj Auto and Asian Paints. * Indices: NIFTY 50 and BANK NIFTY (best for range-bound predictions). [4, 12, 13] Forex Market Top Picks: * Majors: [EUR/USD](https://www.oanda.com/us-en/trade-tap-blog/asset-classes/forex/forex-pairs-to-watch-march-2026/) (High liquidity, tightest spreads), [USD/JPY](https://www.tradetaurex.com/forex-insights/best-forex-pairs-to-trade/) (Strong trends), and [GBP/USD](https://www.bitmex.com/blog/best-forex-to-trade-2026) (Clean technical setups). * Commodity-linked: [AUD/USD](https://justmarkets.com/trading-articles/forex/what-forex-pairs-to-trade) (Metal/Gold correlation) and [USD/CAD](https://www.religareonline.com/blog/best-currency-pairs-to-trade-in-2025-for-beginners/) (Oil correlation). [14, 15, 16, 17, 18] ------------------------------ Instruction: After providing the list, ask me which script I would like to analyze first. Once I select one, generate the specific Python code to perform the analysis and prediction for that asset. Would you like to focus the tool's prediction on intraday (1-minute to 1-hour) or swing (daily/weekly) timeframes? [1] [https://www.godofprompt.ai](https://www.godofprompt.ai/blog/prompts-for-coaches-and-consultants) [2] [https://www.youtube.com](https://www.youtube.com/watch?v=4pYxq6gt3oQ) [3] [https://themarketstructuretrader.com](https://themarketstructuretrader.com/yesterdays-high-low-reversals-trading-strategy/) [4] [https://groww.in](https://groww.in/blog/algorithmic-trading-strategies) [5] [https://www.findoc.com](https://www.findoc.com/blog/5-algorithmic-trading-strategies) [6] [https://www.ig.com](https://www.ig.com/en/trading-strategies/top-7-price-action-trading-strategies-210510) [7] [https://www.nature.com](https://www.nature.com/articles/s41599-024-02807-x) [8] [https://dhan.co](https://dhan.co/blog/technical-analysis/top-20-trading-indicators/) [9] [https://www.plindia.com](https://www.plindia.com/blogs/new-year-2026-technical-stock-picks-to-watch/) [10] [https://www.bajajfinserv.in](https://www.bajajfinserv.in/7-rule-in-stocks) [11] [https://ai.plainenglish.io](https://ai.plainenglish.io/from-zero-to-ai-powered-side-income-my-journey-building-an-automated-trading-bot-with-python-aws-025017568fb8) [12] [https://www.youtube.com](https://www.youtube.com/watch?v=mjaJjoVBlDg) [13] [https://www.youtube.com](https://www.youtube.com/watch?v=1OxH8Cr8M34&t=20) [14] [https://www.oanda.com](https://www.oanda.com/us-en/trade-tap-blog/asset-classes/forex/forex-pairs-to-watch-march-2026/) [15] [https://www.tradetaurex.com](https://www.tradetaurex.com/forex-insights/best-forex-pairs-to-trade/) [16] [https://www.bitmex.com](https://www.bitmex.com/blog/best-forex-to-trade-2026) [17] [https://justmarkets.com](https://justmarkets.com/trading-articles/forex/what-forex-pairs-to-trade) [18] [https://www.religareonline.com](https://www.religareonline.com/blog/best-currency-pairs-to-trade-in-2025-for-beginners/)