Quantitative Finance & Algorithmic Trading in Python (Udemy.com)
Stock Market, Bonds, Markowitz-Portfolio Theory, CAPM, Black-Scholes Model, Value at Risk and Monte-Carlo Simulations
Created by: Holczer Balazs
Last updated March 2026
What you will learn
- 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)
How it compares
Against the other 388 rated Udemy courses in Python on CourseDuck:
- Rating4.6 out of 5higher than 70% of them
- Reviews2,714#115 of 389 by number of reviews
- Length18.3 hourslonger than 73% of them
- Last updatedMarch 2026more recently than 82% of them
Course Description
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.
Instructor Details
- 4.6 Rating
2,714 Reviews
Holczer Balazs
My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model.
Take a look at my website if you are interested in these topics!
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Reviews
By Carlos Alfonso Meléndez Vanegas on 5/8/2025
It is a very good course, that may lead to a lot more topics like stochastic calculus, stochastic volatility, exotic options, etc. Holzcer is a good profesor offering clear explanations for every topic and providing useful and easy to follow implementations. You might want to refresh your calculus, and programming skills.
By André Coelho on 8/21/2024
The course is well designed and provides a thorough account of several topics related to quantitative finance. Sometimes the contents are redundant, but it’s better to be that way than to be superficial, like other courses. The implementations in python, in particular, are quite interesting, albeit sometimes there are some aspects that could be better discussed.
By Anonymized User on 1/17/2024
The Balashekar course has proven to be exceptionally valuable, particularly for its strong emphasis on mathematical concepts related to stocks. I genuinely appreciate how the course is structured to provide a comprehensive understanding of the mathematical intricacies involved in stock analysis. The focus on mathematical principles not only enhances the overall learning experience but also equips students with a solid foundation for making informed decisions in the realm of stocks. Kudos to the Balashekar team for creating such a commendable course!
By Tom Konstantin Walter on 6/16/2023
The course "Quantitative Finance and Algorithmic Trading with Python" has high quality and educational value. The course struck a good balance between mathematical explanations and hands-on tutorials, making it an invaluable resource for anyone interested in the intersection of finance and programming. The mathematical explanations provided in the course were clear and concise. The instructors skillfully broke down complex financial concepts, ensuring that even someone with limited mathematical background could grasp the fundamentals. The step-by-step approach to explaining quantitative finance theories helped me develop a solid understanding of the underlying principles. The hands-on tutorials for implementation were a highlight of the course. Through a series of practical exercises, I was able to apply the theoretical knowledge gained and dive into the world of quantitative finance using Python. The tutorials were thoughtfully designed, guiding me through the process of building financial models and obtaining the data needed. The hands-on approach not only solidified my understanding but also provided a practical skill set that I can apply in my professional endeavors. Overall, the "Quantitative Finance with Python" course exceeded my expectations, offering an exceptional learning experience through its insightful mathematical explanations and invaluable hands-on tutorials.
By Sanskar Sandeep Unkule on 5/26/2023
The author had a tremendous knowledge about the topic even I got to learn more about Quantitative Finance and also got a clarity about this field and would be looking it to pursue as a career and also I would like to take a deep dive into this world of Quantitative Finance Thank you sir
By Dx on 5/22/2023
the small course for python is not enough, yo can get something much better at youtube , the financial part is much better explain in a financial part, the author does not explain concepts just copy an paste definitions and formulas, and the algorithms? yeah in his course of algorithms not this one, I recommend you take a python course for free at youtube and buy a financial course here, with a financial expert, you can program formulas in python by your self , because is all that you'll see here
By Jay Pedersen on 2/6/2023
Very satisfied with this course. I came into the course wanting to understand the various financial instruments that are available and to understand how their future values might be estimated. This course has delivered on that. The only caveat I would say is that you have to be willing to go through some college level calculus discussions and non-trivial python coding to understand the course. Even if you don't understand the calculus, the provided python code will work.
By Aditi Garg on 6/2/2022
It's a great course ! I have read Finacial derivatives theory but after watching actual real-life implementation in this course, I am able to understand the theory better. Strongly suggested course for anyone in quantitative finance field.
By Antonio de Jesus Campos Rodriguez on 10/8/2021
Very useful to learn the basics. I found the Python section too long and math too little in my opinion. Almost no machine learning although the instructor explains the reason, but overall very useful as introduction to quantitative finance.
By Mizamo Mjekula on 12/20/2020
I hope the course does not assume that we have prior knowledge of python. Otherwise content and delivery are perfect for the time being.
By Stanley Lee on 10/3/2020
Concepts lack explanation. Example are also a bit too simple.
By Samuel Groth on 9/27/2020
Good content. The slides could be a bit neater and with fewer errors.
Quality Score
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Overall Score : 92 / 100









