*🎲 Free College: Stochastic Processes Course Materials* ___________________________________________ *🧮 Quantitative Investments for an Intelligent Future* *📈 Interactive Brokers for Algorithmic Trading* *👾 Join the Quant Guild Discord server here* ___________________________________________ *🪐 Free Jupyter Notebook Library 👇* *👤 Video Setting Up Interactive Brokers 👇* *🔗 How to Read Options Chains 👇* TL;DR Executive Summary: - Free 16-Week Stochastic Processes Course: Learn probability theory, Markov chains, Poisson processes, Brownian motion, and quantitative finance with Roman Paolucci, founder of Quant Guild. - Probability and Expected Value: Understand how probability models quantify uncertainty, identify statistical edges, and improve trading decisions. - Probability Fundamentals: Explore random experiments, sample spaces, events, probability measures, and the three axioms of probability. - Probability Rules: Learn unions, intersections, complements, mutually exclusive events, and probability addition rules. - Combinations and Permutations: Master essential counting techniques for solving probability problems. - Conditional Probability: Understand how new information changes event probabilities. - Bayes' Theorem: Introduction to Bayesian probability, the multiplication rule, partitions, and the law of total probability. - Quantitative Finance Applications: Apply expected value, market-making simulations, volatility regimes, and probability models to financial markets. - Hands-On Learning: Follow Python simulations, weekly homework, solutions, lecture notes, and GitHub course materials. - Upcoming Topics: Discrete-time and continuous-time Markov chains, random walks, Poisson processes, queueing theory, and Brownian motion. I hope you enjoyed, and I hope you learned something! - Roman ___________________________________________ *📖 Chapters:* 00:00 - Course Introduction and Materials 04:47 - Why Study Stochastic Processes 12:38 - Def(n) Random Experiments 15:07 - Def(n) Probability Model 21:11 - Def(n) Sample Space 24:35 - Def(n) Event 25:57 - Def(n) Set Operations 30:44 - Def(n) Probability Measure 35:59 - Rules of Probability 39:35 - Def(n) Equally Likely Outcomes 48:48 - Combinations & Permutations 55:00 - Def(n) Conditional Probability 59:07 - Rules of Conditional Probability ___________________________________________ *▶️ Related Videos* *Quant Builds 🔨* How to Build a Live Volatility Surface in Python (Interactive Brokers) *Statistics and Trading Profitability Over Time (Edge) 📈* Time Series Analysis for Quant Finance Quant Trader on Retail vs Institutional Trading Quant on Trading and Investing Why Poker Pros Make the Best Traders (It's NOT Luck) Quant vs. Discretionary Trading ___________________________________________ *🗂️ Resources* *📚 Quant Guild Library:* *🌎 GitHub:* *📝 Medium (Blog):* ___________________________________________ *🛠️ Projects* *The Gaussian Cookbook:* *Recipes for simulating stochastic processes:* ___________________________________________ *💬 Socials* *TikTok:* @quantguild *Instagram:* *X/Twitter:* *LinkedIn (personal):* *LinkedIn (company):* ___________________________________________