BOOK
Probability, Coding, Trading Games, and the Full Modern Question Stack
Equip technically strong candidates with a single, structured system covering probability, Python coding, brainteasers, mental math, market making.
This book is a structured preparation system for modern quantitative finance interviews across trader, researcher, and developer tracks. It is designed to sharpen probability, coding, trading games, mental math, statistics, stochastic processes, machine learning fundamentals, and interview communication under real interview pressure.
Built for
A practical guide for a STEM graduate (MFE student, PhD in math/physics/CS/engineering, or career-switching software engineer/data scientist) preparing for quantitative trader, researcher, or developer interviews at top prop-trading firms and quantitative hedge funds.
What makes it useful
Equip technically strong candidates with a single, structured system covering probability, Python coding, brainteasers, mental math, market making.
THE DIFFERENCE
Solve probability puzzles under time pressure using structured frameworks (conditioning, symmetry, recursion, indicator variables) rather than memorized solutions
Implement Monte Carlo simulations in Python to verify any probability or expected value result from the book
Complete a mental math speed drill at the pace required by timed assessments (targeting the Optiver 80-in-8 format)
Play a market making game with sound bid-ask strategy, position management, and expected value reasoning
THE FULL BRIEF
This book is a structured preparation system for modern quantitative finance interviews across trader, researcher, and developer tracks. It is designed to sharpen probability, coding, trading games, mental math, statistics, stochastic processes, machine learning fundamentals, and interview communication under real interview pressure.
This book is a structured preparation system for modern quantitative finance interviews across trader, researcher, and developer tracks. It is designed to sharpen probability, coding, trading games, mental math, statistics, stochastic processes, machine learning fundamentals, and interview communication under real interview pressure.
What this book gives you: Equip technically strong candidates with a single, structured system covering probability, Python coding, brainteasers, mental math, market making.
What you will be able to do:
Solve probability puzzles under time pressure using structured frameworks (conditioning, symmetry, recursion, indicator variables) rather than memorized solutions
Implement Monte Carlo simulations in Python to verify any probability or expected value result from the book
THE TABLE OF CONTENTS
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Read before you commit.
Explain their reasoning out loud while solving a problem, demonstrating structured thinking even when stuck
Identify which topics to prioritize based on their target role (trader, researcher, or developer) and target firm
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