Quantitative Analysis

Master the math of finance. Learn Stochastic Calculus, Monte Carlo simulations, and Options Pricing models like Black-Scholes.

Quantitative Analysts (Quants) use math to price complex financial derivatives. This advanced course covers the mathematical foundations of modern finance. You will learn Stochastic Calculus (Brownian Motion), the Black-Scholes option pricing model, and how to implement Monte Carlo simulations in Python to price exotic options. We also cover risk metrics like Value at Risk (VaR) and Greeks (Delta, Gamma). This is rigorous math applied to money.

✅ 100% Free & Lifetime Access

⏱️ 5-Minute Lessons (Bite-sized learning)

🚀 21-Lesson Path (Independent modules)

📱 Mobile Friendly (Learn anywhere)

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Complete Course Syllabus

1

Math Fundamentals

Probability distributions and normal distribution properties.
2

Stochastic Processes

Random walks and Geometric Brownian Motion.
3

Black-Scholes

The formula that changed finance and how to code it.
4

The Greeks

Measuring sensitivity to price, time, and volatility.
5

Monte Carlo

Simulating thousands of future paths to find value.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary

$140k - $250k

Career Paths

Quantitative Analyst $150k-$250k

Risk Quant $130k-$180k

Financial Engineer $140k-$200k

What You Will Learn

Derive and apply the Black-Scholes pricing formula

Implement Monte Carlo simulations for risk assessment

Calculate Option Greeks (Delta, Gamma, Theta) for hedging

Model asset prices using Geometric Brownian Motion

Compute Value at Risk (VaR) for portfolios

Skills You Will Gain

Stochastic Calculus Options Pricing Monte Carlo Python Scientific Stack Risk Modeling

Who Is This For

Math/Physics Grads

Aspiring Quants

Risk Managers

Prerequisites

Calculus

Probability

Python