Quantitative Finance & Algorithmic Trading in Python

Descripción

Master Quantitative Finance with Python Turn mathematics, statistics, and programming into powerful tools for understanding—and modeling—the financial world. If you’ve ever wondered how professionals price options, manage portfolio risk, or build financial models used on Wall Street, this course will guide you step by step through the foundations of financial engineering using Python. In this course, you won’t just learn theory—you’ll implement real financial models in Python, gaining practical skills that quantitative analysts, traders, and financial engineers use every day. You’ll start with the building blocks of financial markets, including stocks, bonds, and derivatives. From there, we move into the mathematical models that revolutionized modern finance—from portfolio optimization to option pricing. Along the way, you’ll discover some of the most influential ideas in financial science, including: • Bond pricing and interest rate concepts • Modern Portfolio Theory and the Markowitz model • The Capital Asset Pricing Model (CAPM) • The Black–Scholes model, one of the most elegant breakthroughs in 20th-century finance • Risk management techniques such as Value-at-Risk • Monte Carlo simulations for pricing and risk analysis You’ll also explore how randomness shapes financial markets through stochastic processes, Brownian motion, and Ito’s calculus, and learn how these ideas are used to model asset prices. By the end of the course, you’ll understand how quantitative finance works both theoretically and computationally, and you’ll be able to build and implement these models yourself in Python. Important: This course is designed for learners who are genuinely interested in mathematics, statistics, and analytical thinking. If you enjoy working with numbers, models, and coding, you will find this journey incredibly rewarding. What You’ll Learn Section 1 – Introduction • Installing Python • Why Python is one of the most powerful tools in finance • The challenges of financial modeling and historical data Section 2 – Stock Market Basics • Present value and future value of money • Stocks and equity markets • Commodities and the FOREX market • Long and short positions explained Section 3 – Bond Theory and Implementation • What bonds are and how they work • Yield and yield to maturity • Macaulay duration • Bond pricing theory and Python implementation Section 4 – Modern Portfolio Theory (Markowitz Model) • Diversification in finance • Mean–variance optimization • Efficient frontier and Sharpe ratio • Capital Allocation Line (CAL) Section 5 – Capital Asset Pricing Model (CAPM) • Systematic vs. unsystematic risk • Beta and alpha • Linear regression and market risk • Why market risk is the most relevant risk Section 6 – Derivatives Basics • Introduction to derivatives • Options: calls and puts • Forward and futures contracts • Mark-to-market mechanism • Credit Default Swaps (CDS) • Interest rate swaps Section 7 – Random Behavior in Finance • Randomness in financial markets • Wiener processes • Stochastic calculus and Ito’s Lemma • Brownian motion theory and implementation Section 8 – Black-Scholes Model • Black-Scholes theory and implementation • Monte Carlo simulations for option pricing • The Greeks and risk sensitivities Section 9 – Value-at-Risk (VaR) • Understanding Value-at-Risk • Monte Carlo simulation for risk estimation Section 10 – Collateralized Debt Obligations (CDO) • What CDOs are • Lessons from the 2008 financial crisis Section 11 – Interest Rate Models • Mean-reverting stochastic processes • The Ornstein–Uhlenbeck process • The Vasicek interest rate model • Bond pricing with Monte Carlo simulation Section 12 – Value Investing • Long-term investing strategies • The Efficient Market Hypothesis Whether you want to become a quantitative analyst, improve your financial modeling skills, or simply understand the mathematics behind modern finance, this course will give you the tools to do it. Join now and start building real financial models with Python today.

Lo que aprenderás

• Understand stock market fundamentals
• Understand bonds and bond pricing
• Understand the Modern Portfolio Theory and Markowitz model
• Understand the Capital Asset Pricing Model (CAPM)
• Understand derivatives (futures and options)
• Understand credit derivatives (credit default swaps)
• Understand stochastic processes and the famous Black-Scholes model
• Understand Monte-Carlo simulations
• Understand Value-at-Risk (VaR)
• Understand CDOs and the financial crisis
• Understand interest rate models (Vasicek model)

Requisitos

• You should have an interest in quantitative finance as well as in mathematics and programming!