Welcome

This is a collection of notes exploring a number of topics in Quantitative Finance (QF). The idea is to use Python 🐍to illustrate the theoretical concepts and help you to get a better understanding of each topic.

My aim is to provide an open-source repository where people interested in a career in QF can find these concepts covered in a rigorous manner while keeping the practitioners point of view into consideration.

Contents

Stochastic Processes

• 1. Brownian Motion
• 2. Arithmetic Brownian Motion
• 3. Geometric Brownian Motion
• 4. Vasicek Model/Process
• 5. Cox–Ingersoll–Ross process
• 6. Bessel Processes Part I
• 7. Bessel Processes Part II
• 8. Bessel Processes Part III

Other Topics

• American Options Pricing using the Longstaff-Schwartz Algorithm
• Malliavin Greeks under Black-Scholes Dynamics

Author

I am Dialid Santiago, also known as Quant Girl —a mathematician with nine years of experience working as a Quant (short for Financial Quantitative Analyst).

My work focuses on designing and implementing mathematical models to price financial instruments and manage risk across a broad range of asset classes, including Equities, Credit, Commodities, and Rates.

I hold a PhD in Statistics from the University of Warwick, where I spent some amazing years researching non-linear stochastic processes. Prior to that, I earned an M.Sc. in Probability and Statistics and a B.Sc. in Mathematics.

I regularly post here about diverse topics.

Connect with me via:

• 🦜 Twitter

• 👩🏽‍💼 Linkedin

• 📸 Instagram

• 👾 Personal Website

Note

• This project is under construction 🦺 and notes will be released on an ongoing basis 🌱

• If you like this project, please give it a star in GitHub ⭐️

Thanks for visiting ✨