Quant Handbook

About

I’m Aleksandr Babarika, a final-year computer science student at King’s College London. This handbook is where I explain the trading and quant ideas I’ve spent the most time trying to understand properly.

Why it exists

Ideas like volume profile, dealer gamma exposure, the volatility surface and how an order book matches orders took me far longer to understand than they should have. What’s online is scattered. Most of it is either confident videos and paid signal services that promise more than they explain, or papers and textbooks that assume you already know the mechanism. Very little of it lets you change the inputs and watch what happens.

So every chapter is built around a model you can play with. It starts with the intuition, gives you a toy market to experiment with, shows the maths for anyone who wants it, then looks for the effect in real market data. Sometimes the real data doesn’t show it, and the chapter says so.

How I keep it correct

  • Every model behind a simulator is ordinary, tested code. Option prices and Greeks are checked against textbook values, and gamma exposure against a small option chain worked out by hand.
  • Every formula is checked against a source, cited at the end of its chapter.
  • Simulators are seeded: the same settings and seed always give the same result. The settings are kept in the page address, so you can link to a specific setup.
  • When an idea rests on a contested assumption, the chapter says so. Gamma exposure, for example, depends on a guess about who holds each option, and that guess is often wrong.
  • I review and rewrite every chapter myself before it’s published.

If you find a mistake, I want to hear about it. You can reach me through GitHub.

Data sources and licences

Simulator data is generated in your browser from seeded random numbers. Case studies use real market data, published only as derived figures, such as gamma exposure by strike, never as a vendor’s raw files. Each case study credits its data sources on its own page, and I check each source’s terms before publishing anything built from it.

When the repository goes public, the code will be MIT-licensed and the writing will be licensed under CC BY-NC 4.0.

Disclaimer

Educational content only. Not financial advice. Nothing here is a recommendation to buy or sell anything, and no technique is presented as a way to make money. The models are simplified on purpose, so they leave out things that matter in real markets.

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