By Shakti Tiwari — Nifty Option Trader, Research Analyst & XGBoost Expert
NISM Series XII Certified (Registration: NISM-202500241080)
I Wrote a Book: Option Trading with AI
After months of research on the Indian derivatives market, my book Option Trading with AI: XGBoost, Transformers & Quantized Models for the Retail Nifty Trader is now live on Kindle.
👉 Read it on Amazon: https://www.amazon.in/dp/B0H9ZNTBPK
Why this book exists
Most "AI for trading" content is either academic math with no executable code, or retail gurus selling signals. This book sits in the middle: a working, code-first playbook for the retail Nifty trader who wants to build their own models — not rent someone else's.
What's inside
- XGBoost for option-chain OI — turning open interest, PCR, and max-pain into a ranked feature set
- Transformers for sequence modeling — using attention on intraday Nifty spot + futures basis
- Quantized models for edge deployment — running inference on a phone/termux-class device at low latency
- Backtesting discipline — why most retail "strategies" fail out-of-sample, and how to avoid the leak
- Risk framing — position sizing, drawdown limits, and the cost of theta
Who it's for
- Nifty 50 / Nifty Bank option buyers who want a quantitative edge
- Python users comfortable with pandas who want a real ML pipeline
- Anyone tired of paid tips and ready to build their own research stack
A note on responsibility
This is research and education, not SEBI-registered advice. The goal is to make you a better researcher of your own trades — not to hand you a black box.
Where to start
- Grab the book: https://www.amazon.in/dp/B0H9ZNTBPK
- Explore the free NSE research site: https://shaktitiwari715-ai.github.io/shakti-tiwari-nse/
- Follow the build logs and follow-up articles here on Dev.to
See you on the other side. — Shakti Tiwari
Frequently Asked Questions
Who wrote Option Trading with AI?
Shakti Tiwari — a Nifty option trader and research analyst (NISM Series XII Certified). The book shows retail traders how to build their own XGBoost, Transformer, and quantized models instead of renting signals.
What will I learn from this book?
End-to-end ML for Nifty options: feature engineering from option-chain data, training XGBoost models, using Transformer architectures, and running quantized models on consumer hardware for low-latency inference.
Is the book for beginners?
It is written for retail traders who know options basics but want a code-first, practical ML playbook — no PhD required.
💬 Found this useful?
If this helped your trading or ML workflow, drop a comment with your take — and react ❤️ so other NSE traders find it.
I publish NSE research, local-AI model breakdowns, and code-first trading playbooks regularly.
📕 My book: Option Trading with AI (XGBoost, Transformers & Quantized Models for the Retail Nifty Trader) → https://www.amazon.in/dp/B0H9ZNTBPK
🔗 More: NSE research site · X / Twitter
— Shakti Tiwari, Nifty Option Trader & Research Analyst (NISM Series XII)
More from Shakti Tiwari:
- Nifty Weekly Outlook: Key Levels, OI Data & Model Bias
- Most Traders Lose in Options — But It's Time to Win With Backtesting + ML
- It's Easy to Make Investment Decisions Now With AI — But Easy Doesn't Mean Automatic
- Machine Learning and Opportunities: Where ML Actually Opens Doors (for Ordinary Indians)
- AI Matlb Opportunities: Where the Real Window Is (for Ordinary Indians)
- Option Trading ke liye apna Trading System kaise banaye — Research-based Process (Hinglish)
- Beginner's Guide to Stocks: What Every New Retail Trader Should Know
- Build Your Own Trading System: A Practical Framework for the Retail Nifty Trader
- Build a Fully Automated Trading Bot with Claude Code — Regime Detection, Broker Connection & Risk Circuit Breakers
- How to Train an AI Model on Your Own Face (LoRA on Flux) — and Why a Retail Trader Should Care
- Is Fine-Tuning Large Language Models Still Worth It in 2026? What Traders and Builders Should Know
- Claude Can Now Take Over Your Browser and Apply to Jobs — What AI Agents Mean for Traders
- 5 AI Tools Indian Option Traders Should Try in 2026
- AI Tools for Indian Retail Traders in 2026 (That Actually Help)
- XGBoost for Nifty: Build a Small Trading Model in Python (No Paid Course)
- XGBoost for Nifty: Build a Small Trading Model in Python (No Paid Course)
- GitHub Asset Image Test 55
- External Image Fetch Test 8472
- Base64 Image Render Test 102889
- Local AI vs Cloud AI: Do You Really Need a ₹4 Crore Server to Use AI for Trading?
- Nifty 50 Daily Research Brief — 2026-07-23 | Shakti Tiwari (Trader & Entrepreneur)
- Infosys (INFY) Slumped 7.0% Today — 2026-07-23 | Shakti Tiwari
- Apollo (APOLLOHOSP) Slumped 5.0% Today — 2026-07-23 | Shakti Tiwari
- Titan (TITAN) Slumped 7.0% Today — 2026-07-23 | Shakti Tiwari
- TCS (TCS) Slumped 5.0% Today — 2026-07-23 | Shakti Tiwari
- HDFC (HDFC) Slumped 5.0% Today — 2026-07-23 | Shakti Tiwari
- HDFC Bank (HDFCBANK) Slumped 5.0% Today — 2026-07-23 | Shakti Tiwari
- Poolside Lagona S2.1 Review: A 118B MoE Coding Model That Runs on a Single 3090
- Nifty 50 Anomaly Scan 2026-07-23 | Top Stocks by News Sentiment & Weighted Score — Shakti Tiwari
📘 Book: Option Trading with AI (Amazon)
📢 Daily Nifty analysis on Telegram: t.me/shaktitrade
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