The Quant Learning Platform

Everything You Need to
Break Into Quant

Personalized roadmaps. Real projects. Daily practice.Master the math and code that quant firms hire for.

6+

Projects

300+

Problems

7,000+

Learners

How It Works

From Zero to
Portfolio-Ready

01

Get Your Roadmap

Take a 5-minute assessment. Your personalized path adapts to your level - complete beginner to experienced.

Calculus
Linear Algebra
ProbabilityIn Progress
Statistics
Stochastic Calc
02

Master the Theory

Structured lessons, quizzes, and exams. Learn the math and programming that quant firms actually test.

expected_value.md

Why Expected Value Matters in Trading

Before placing any trade, a quant asks: "What is my expected P&L?" This is the foundation of every strategy evaluation.

Consider a simple bet: 60% chance to win $100, 40% chance to lose $80. Should you take it?

E[P&L]=0.6($100)+0.4($80)=$28\mathbb{E}[\text{P\&L}] = 0.6(\$100) + 0.4(-\$80) = \$28

Positive expected value. But this alone is not enough - we need to understand risk.

Variance: Quantifying Uncertainty

Two strategies can have identical expected returns but wildly different risk profiles. Variance captures this spread.

For our bet above, the variance tells us how much our actual returns will deviate from $28 on average:

σ2=0.6(10028)2+0.4(8028)2=7776\sigma^2 = 0.6(100-28)^2 + 0.4(-80-28)^2 = 7776

The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.

Portfolio Construction

The key insight of modern portfolio theory: combining assets with low correlation reduces overall risk without sacrificing returns.

For two assets A and B, portfolio variance depends on their covariance:

σp2=w2σA2+(1w)2σB2+2w(1w)Cov(A,B)\sigma_p^2 = w^2\sigma_A^2 + (1-w)^2\sigma_B^2 + 2w(1-w)\text{Cov}(A,B)

When Cov(A,B) < 0, the cross-term is negative - diversification benefit.

Why Expected Value Matters in Trading

Before placing any trade, a quant asks: "What is my expected P&L?" This is the foundation of every strategy evaluation.

Consider a simple bet: 60% chance to win $100, 40% chance to lose $80. Should you take it?

E[P&L]=0.6($100)+0.4($80)=$28\mathbb{E}[\text{P\&L}] = 0.6(\$100) + 0.4(-\$80) = \$28

Positive expected value. But this alone is not enough - we need to understand risk.

Variance: Quantifying Uncertainty

Two strategies can have identical expected returns but wildly different risk profiles. Variance captures this spread.

For our bet above, the variance tells us how much our actual returns will deviate from $28 on average:

σ2=0.6(10028)2+0.4(8028)2=7776\sigma^2 = 0.6(100-28)^2 + 0.4(-80-28)^2 = 7776

The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.

Portfolio Construction

The key insight of modern portfolio theory: combining assets with low correlation reduces overall risk without sacrificing returns.

For two assets A and B, portfolio variance depends on their covariance:

σp2=w2σA2+(1w)2σB2+2w(1w)Cov(A,B)\sigma_p^2 = w^2\sigma_A^2 + (1-w)^2\sigma_B^2 + 2w(1-w)\text{Cov}(A,B)

When Cov(A,B) < 0, the cross-term is negative - diversification benefit.

03

Build Projects

Apply your skills to real quant projects. Add them to your portfolio to stand out in applications.

portfolio_optimizer.py
 
04

Ace Interviews

Practice with real questions from top firms. Probability, coding, brainteasers - exactly what you'll face.

Jane StreetProbability

A fair coin is flipped until two consecutive heads appear. What is the expected number of flips?

What You'll Build

Projects That
Get You Hired

vol_surface.py

Volatility Surface

Advanced

Model the implied volatility smile across strikes and expiries. Build the foundation for options pricing and risk management.

 
OptionsBlack-ScholesNumPy
regime_detection.py

Market Regime Detection

Intermediate

Analyze return data as geometric structure. Use vectors, matrices, and SVD to identify recurring market patterns.

 
Linear AlgebraSVDNumPy
monte_carlo.py

Monte Carlo Simulator

Intermediate

Evaluate trading strategies using expected value, break-even analysis, and stress testing with simulation.

 
ProbabilityMonte CarloNumPy

Success Stories

From Learners to
Quant Professionals

QuantFrame has helped me grasp the mathematical concepts and actually use them in applications. The coding exercises really give a feel on how to go about grabbing the equations and applying them accordingly to your needs. Best platform for practice.

Jaime C.

Jaime C.

CS + Math Major

Pricing

Simple Pricing

Monthly

$29/month

3-day free trial. Cancel anytime.

  • All 6+ projects
  • 300+ problems
  • Personalized roadmap
  • Daily challenges
  • Downloadable notebooks
Start Free Trial
BEST VALUE

Annual

$29$19/month

3-day free trial, then $228/year. Cancel anytime.

  • Everything in Monthly
  • Priority support
  • Early access to new projects
  • Best for serious learners
Start Free Trial
Start with a 3-day free trial. No commitment, cancel anytime.

FAQ

Questions

Ready to Start?

Take a 5-minute assessment. Get your personalized roadmap.
Start learning today. No credit card required.

Get Started Now