Quantitative Finance Interview Training

We will cover 100 interview questions in quantitative finance including desk quant, quantitative trading, quant researcher, quant strategist, and risk management position in both sell side and buy side.

START:
July 29, 2017
DURATION:
3 Weeks
PRICE
$3,000.00

Class Description:

Since quantitative finance interview focuses only on technical questions rather than your background (we saw many students studying English Literature, Public Relationship steps into this industry), the trickiest staff is to crack all the interview questions. But these questions are nightmare to rookies since they are made by Wall Street geniuses and smart people do not want you to solve it at first glance.

The interview course contains only interview questions and solutions—only questions! We focus on the a lot paper-based formulas, logic and math work. We will cover 100 interview questions in quantitative finance including desk quant, quantitative trading, quant researcher, quant strategist, and risk management position in both sell side and buy side.

We help you only on interview questions! NO textbook questions!

After class, you will:

  1. Solve the medium level interview questions, which are widely used in top banks.
  2. Understand deeply in quant finance and crack various interview from other math, stats, and programming-related positions
  3. Crack 80% interview questions from top banks and hedge funds! That is what we want to see!

Are you the right student who can enroll in this class?:

  1. Your background is from engineering(including Bio), math, stats
  2. You are not from STEM but actually you know how to do integration and derivatives
  3. Working people who seek for career change (like you are an engineer from energy industry, we have students working at BP as an engineer and go to Goldman Sachs!)

 

(Week 1) Lecture 1: Probability and Brainteaser

  1. Basic
  2. Conditional Probability and Bayes
  3. Discrete and Continuous Distribution
  4. Expectation, Variance and Covariance
  5. Order Statistics
  6. Brainteaser
  7. Root-find methods (Taylor, Newton, Secant, etc.)
  8. Linear Algebra (PCA, SVD, Cholesky Decomposition)

(Week 2) Lecture 2: Stats, Time Series, Martingale:

  1. Linear Regression and factor model
  2. Time series
  3. Logistic regression, Ridge and Lasso
  4. Markov Chain (probability and expectation)
  5. Martingale and Random Walk
  6. Dynamic programming
  7. Ito’s lemma and Ito’s isometry

 (Week 3) Lecture 3: Stochastic Calculus, Option Pricing and Greeks

  1. Stochastic differential equation
  2. From Stochastic Differential Equation to Partial Differential Equation
  3. Monte Carlo Simulation: Variance calculation and variance reduction
  4. Option pricing
  5. Greeks
  6. VaR and other risk term
  7. Portfolio Optimization
  8. Bond Basics