Closing Keynote
summary
An AI-powered trading machine is presented that standardizes data ingestion, backtesting and live execution for mid-frequency (5–10 minute) algo strategies built with Python using numpy pandas and scikit‑learn and fed by Thomson Reuters tick and news APIs. A prototype runs in test mode and shows a live profitable trade but cautions no guarantees. Robustness testing covers 288 algorithm configurations with transaction costs eroding returns, and the platform specifically targets the deployment gap so research actually reaches production.
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chapters (34)
- 0:00Introduction
- 3:36Agenda
- 4:18Python Points
- 5:03My Personal Web Page
- 6:36Term Finance
- 7:15Thomson Reuters
- 10:17Financial Data
- 12:00Big Data
- 12:15Machine Learning
- 14:28Big Trading
- 15:21Pattern Recognition
- 16:34The Beauty Myth
- 18:38The Financial Markets
- 21:32Machine and Deep Learning
- 26:34Scientific Stack
- 28:05Robust Strategy
- 29:55Green Field
- 30:16Space
- 30:46Next 5 years
- 34:14Program
- 34:40Deployment Gap
- 35:10The Machine
- 35:40The Rocket
- 36:34The AI Machine
- 36:46Trading
- 38:53Live Model
- 39:05Risk Management
- 39:35Selfdriving car
- 40:53Backend
- 41:11Industrial Chain
- 42:07Outlook Key
- 42:23Financial Industry
- 43:36Superintelligence
- 46:15Questions
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