On Quant Interviews - 150 Most Frequently Asked Questions

On Quant Interviews - 150 Most Frequently Asked Questions

. The third edition is highly recommended to stay current with the increasing focus on data science and machine learning in quant interviews. What programming languages are covered in this book? Tell me more about the book's authors

: What does "volatility of volatility" mean, and how does it manifest in the pricing of exotic structures and VIX derivatives?

: Why does iterating through a contiguous 2D array row-by-row run faster than iterating column-by-column? Explain CPU caching.

What is Value at Risk (VaR)? Explain its limitations during systemic market selloffs. 150 Most Frequently Asked Questions On Quant Interviews

: What makes a matrix Positive Definite (PD)? Why must a covariance matrix always be positive semi-definite?

: We take turns flipping a coin. First to get Heads wins. You go first. How much would you pay to play this game if the payout is $100? Additional Logic Prompts How many zeros are at the end of (100 factorial)?

"That’s the mean of a truncated normal. E[X | X>0] = √(2/π) ≈ 0.798." Tell me more about the book's authors :

: You have 1,000 bottles of wine, and exactly one is poisoned. You have 10 rats to test the wine. If a rat drinks poison, it dies in 24 hours. How do you find the poisoned bottle in 24 hours?

: What are the classic Ordinary Least Squares (OLS) assumptions? What happens to your estimates if these assumptions are violated?

Master the fundamentals of probability and linear algebra before diving into complex derivative pricing models. What is Value at Risk (VaR)

Modern quant strategies process massive datasets requiring computational efficiency.

: A trading opportunity has a 60% chance of making and a 40% chance of losing . If your current capital base is

How do you implement a robust historical stress-testing framework for a multi-asset quantitative portfolio? Numerical Methods and Simulations

: Game theory, lateral thinking, and market-making puzzles.

You have 10 bags of coins. One bag contains only fake coins, which weigh 0.9g each. The other bags contain real coins weighing 1g each. Given a digital scale, how can you find the fake bag in exactly one weighing?