Data Before Analysis
Verify the instrument, timestamp, timeframe, expiry, source and data health before building a market narrative.
Stocks, Indices, Options & MCX — a practical framework for AI-assisted market research, data analysis, derivatives intelligence, risk management and trading decision support. Extra benefit: after purchase, you will also be added to our PK Market Labs WhatsApp Community for future eBook updates, announcements and product updates.
Author: Bikash Kundu • Published by: PK Market Labs. Educational and research use only. The framework is designed for disciplined market analysis and decision support; it does not promise guaranteed trades, returns or outcomes.

The book is built around one core problem: traders often have plenty of data but no disciplined method for deciding what matters, what confirms the thesis, what contradicts it, and when risk should veto an otherwise attractive setup.
Verify the instrument, timestamp, timeframe, expiry, source and data health before building a market narrative.
Read market structure, acceptance, regime and location first; use indicators as supporting evidence rather than isolated instructions.
A strong research grade can still result in Wait or Reject when location, liquidity, event risk or portfolio risk is unacceptable.
The book deliberately separates deterministic calculation from AI interpretation. Code calculates measurable facts, the state engine classifies the market, risk determines permission, AI explains the evidence, and the human remains responsible for the final decision.
“CODE CALCULATES. AI EXPLAINS. RISK CAN VETO. HUMAN DECIDES.”
The system is designed to preserve contradictions, acknowledge missing data, avoid false probability language, and accept No Clear Edge as a legitimate decision state.
The material covers intraday stocks, Nifty and Bank Nifty, futures positioning, options intelligence, MCX research, swing workflows, risk governance, backtesting and system architecture.
Nifty, Bank Nifty, broader NSE equities, market breadth and multi-timeframe structure.
Futures OI, option-chain dynamics, OI migration, PCR, Max Pain, IV and Greeks.
Prompt architecture, decision engines, alerts, watchlists and professional dashboard logic.
Position sizing, portfolio heat, event risk, robustness testing and backtest discipline.
The book progresses from foundations and market internals to scanners, dashboards, MCX intelligence, swing workflows, risk engines and full system architecture.
Chapters 1–6: data, structure, indicators, participation and breakout logic.
Chapters 7–12: breadth, futures OI, options intelligence and confluence logic.
Chapters 13–18: intraday stock scanners, watchlists and depth intelligence.
Chapters 19–24: OI migration, PCR, Max Pain, IV regimes and cross-assets.
Chapters 25–30: relative strength, day classification and dashboard architecture.
Chapters 31–36: decision engines, ranking, no-trade logic and AI learning loops.
Chapters 37–42: event states, Gold, Crude Oil, Natural Gas and Copper frameworks.
Chapters 43–48: swing workflows, overnight risk and options contract selection.
Chapters 49–54: risk engine, backtesting, correlation and the intraday workflow.
Chapters 55–60: swing workflow, robustness, platform design and full framework.
13 simulated case studies covering trend days, gap failures, OI, MCX and no-trade conditions.
AI prompts, checklists, formula reference, glossary, references, version info and disclaimer.
The eBook standardizes Direction, Grade, Location, Risk and Status so the user can separate setup quality from timing quality and permission to take risk.
The book includes a full AI Prompt Library covering intraday stocks, indices, options, MCX, swing research, risk review and validation. Below is a sample prompt card in the same style used across the appendix.
Analyze the supplied Nifty and Bank Nifty data using this framework: (1) market structure, (2) breadth, (3) futures positioning, (4) options positioning, (5) volatility and (6) contradictions. Return: Direction, Regime, Grade, Location, Risk, Status, What Changed, and the main contradiction. If required information is unavailable, clearly state 'Data Unavailable' instead of inventing a value.
Use the scanner, breadth, breakout, options and intraday decision-engine chapters to create a structured daily workflow.
Use the relative-strength, market→sector→stock, overnight risk and portfolio-heat framework for multi-day decisions.
Use the data, architecture, prompt, dashboard and validation sections to build AI-assisted research products.
Pay securely using the QR code on the payment page. After payment, send the successful payment screenshot on WhatsApp. The eBook will be delivered digitally within 24 hours after payment verification, and you will also be added to our PK Market Labs WhatsApp Community for future eBook updates, announcements and product updates.
Click the payment image below to open the secure eBook payment instructions. Introductory price: ₹299 (Regular Price: ₹499).
The examples focus on Indian markets—NSE, Nifty, Bank Nifty, stocks, options and MCX—but many of the frameworks for data discipline, state engines, risk and validation are globally applicable.
No. The framework is educational and research-oriented. It explains how to build disciplined market analysis. It does not guarantee profits, predictions or regulatory approvals.
It combines AI workflow design, market structure, derivatives intelligence, MCX analysis, risk governance and system architecture into one consistent professional framework.
Yes. It is especially useful as a conceptual blueprint for indicators, dashboards, scanners, watchlists, AI prompt systems and research software.
Introductory price ₹299 (regular price ₹499). After payment, send the payment screenshot on WhatsApp. The eBook will be delivered within 24 hours after verification, and you will also be added to our WhatsApp Community for future updates, announcements and product updates.