1How to Actually Learn Quant & Algo Trading in 2026 (Full Programme Breakdown)8:36
2How Reinforcement Learning Actually Works in Trading7:51
3How to Backtest a Trading Strategy That Survives Live (Event-Driven, Step by Step)7:43
4How Hedge Funds Trade News Data: What NLP Can Really Extract From Text7:07
5How to Trade the News: Turning Noisy Sentiment Data Into a Real Signal (Python)9:03
6Algo Trading Without Coding: How an IAS Officer Did It #shorts #algotrading0:55
7Drawdown & Profit Factor Explained: The Backtest Metrics That Actually Matter5:11
8How to Backtest an Options Strategy in Python (Start With the Data Nobody Cleans)5:49
9What Your Trading Model's Q-Values Actually Mean (Q-Learning Explained Step by Step)8:32
10TCS to a European Hedge Fund 🤯 #algotrading #quant0:35
11Market Microstructure Explained: Terminology Every Algo Trader Must Know1:46
12Order Types Explained: How Algo Traders Blend Passive & Aggressive Execution4:19
13AI in Algorithmic Trading: 2 New Modules Added to EPAT5:58
14VWAP Explained: The Right Way to Buy 30,000 Shares (Institutional Execution)8:42
15Generative AI in Risk Management: How It Detects Outliers in Finance | Dr Ernest Chan2:58
16Not Enough Financial Data? Here's How GenAI Models Fix That | Dr Ernest Chan2:12
17GenAI for Trading Strategy Simulation | Stress Testing & Risk Management Made Easy | Dr. Ernest Chan1:12
18Scenario Testing with Generative AI - Preparing for the Future1:15
19Why Traditional Risk Models Are Not Enough: GenAI Explains What VaR Misses1:40
20Feature Distribution Modeling in Finance | Dr. Ernest Chan on Risk & Regime Shifts2:40
21What is Generative AI for Trading? Dr. Ernest Chan Explains1:49
