The Quant Learning Platform
Personalized roadmaps. Real projects. Daily practice. Master the math and code that quant firms hire for.
9
Projects
800+
Problems
14,000+
Learners
Learners placed at Morgan Stanley NYC · Optiver AMS
$ python backtest.py --strategy momentum
running 10,000 simulations...
>>> roadmap.next_topic()
'Stochastic Calculus'
Probability & Random Variables
Take a 5-minute assessment. Your personalized path adapts to your level - complete beginner to experienced.
Structured lessons, quizzes, and exams. Learn the math and programming that quant firms actually test.
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?
Positive expected value. But this alone is not enough - we need to understand risk.
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:
The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.
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:
When Cov(A,B) < 0, the cross-term is negative - diversification benefit.
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?
Positive expected value. But this alone is not enough - we need to understand risk.
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:
The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.
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:
When Cov(A,B) < 0, the cross-term is negative - diversification benefit.
Practice with real questions from top firms. Probability, coding, brainteasers - exactly what you'll face.
A fair coin is flipped until two consecutive heads appear. What is the expected number of flips?
Apply your skills to real quant projects. Download notebooks and add them to your portfolio.
Take a 5-minute assessment. Your personalized path adapts to your level - complete beginner to experienced.
Structured lessons, quizzes, and exams. Learn the math and programming that quant firms actually test.
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?
Positive expected value. But this alone is not enough - we need to understand risk.
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:
The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.
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:
When Cov(A,B) < 0, the cross-term is negative - diversification benefit.
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?
Positive expected value. But this alone is not enough - we need to understand risk.
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:
The standard deviation is $88.18 - meaning high volatility relative to our $28 edge. This is a risky bet despite positive EV.
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:
When Cov(A,B) < 0, the cross-term is negative - diversification benefit.
Apply your skills to real quant projects. Add them to your portfolio to stand out in applications.
Practice with real questions from top firms. Probability, coding, brainteasers - exactly what you'll face.
A fair coin is flipped until two consecutive heads appear. What is the expected number of flips?
Math for Quants
9 modules · 66 lessons
Exam + certificate per module
Code for Quants
5 modules · 29 lessons
Exam + certificate per module
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.
CS + Math Major
Honestly quantframe really gave me the ability to grasp complex financial concepts while making the learning process genuinely fun. I'd def recommend it to anyone looking to break into quant finance!
Hugues B.
Analyst at Morgan Stanley
What I appreciate most about QuantFrame is the high-quality content across quantitative finance topics. The platform consistently evolves, offering hands-on Python projects, personalized roadmap, math problems, and in-depth articles that cover everything you need to build a strong foundation in quant finance.
Marien R.
MSc Financial Engineering
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.
CS + Math Major
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