Probability Theory for Quantitative Finance: Lecture 1 | Complete Foundations Masterclass

Welcome to the ultimate foundational masterclass on Axiomatic and Combinatorial Probability, designed specifically for quantitative researchers, financial engineers, and data scientists.

[Course Overview & Value Prop]
In this comprehensive lecture, we establish the absolute mathematical foundations required for advanced quantitative finance, algorithmic trading, and stochastic modeling. We skip the high-school shortcuts and focus entirely on the rigorous theoretical build-up and mathematical derivations used to build high-fidelity risk frameworks and market simulators.

🚀 The Complete Implementation Series:
If you want to see how this theory translates into production-grade Python code, check out the dedicated coding sessions:
🔹 Basic Coding Edition - https://youtu.be/dDpXN0uEEGc?si=omAK9Jb5teK6_oR3
💥 Advanced Coding Edition

Timestamps:
00:00 Introduction
00:20 Sample space and market states
04:09 kolmogorov's three axioms
06:12 counting for portfolio choice
09:29 pigeon hold principle
13:43 conditional probability
15:38 independence vs correlation
18:36 law of total probability
22:35 bayes theorem

Видео Probability Theory for Quantitative Finance: Lecture 1 | Complete Foundations Masterclass канала Surbhi Verma | IIT PhD | Quant Trading India