About the Faculty
Dr. Thomas Starke is the CEO of AAAQuants, where he leads the development of algorithmic trading systems. He has a diverse career spanning proprietary trading firms such as Vivienne Court and Genesis Trading, as well as engineering roles at Rolls-Royce Plc, where he managed strategic research projects. Dr. Starke also co-founded pSemi, a microchip design company, showcasing his expertise in both technology and finance.
Dr. Starke earned his Ph.D. in Physics from Nottingham University and holds master’s degrees in Fluid Dynamics from the University of Colorado Boulder and in Engineering Physics from Hochschule München. He has authored over 20 peer-reviewed papers and holds multiple patents. As a senior research fellow, he has lectured on computer simulation at Oxford University. He regularly explores emerging technologies such as quantum computing and blockchain, organizing meetups on these topics alongside algorithmic trading.
Dr. Starke’s interdisciplinary expertise, spanning engineering, finance, and technology, provides learners with a unique and practical perspective on algorithmic trading and the future of finance.
EPAT Teaching
Dr. Starke bridges statistical and machine learning techniques for quantitative trading, covering key topics like PCA, alpha factors, and advanced cointegration for portfolio optimization. Dive into deep reinforcement learning (RL) fundamentals, including the Bellman equation and gamified strategies, with hands-on Python implementation. He shares insights into RL's challenges and opportunities to master systematic trading.
Quantra Courses
Deep Reinforcement Learning in Trading
Offered by Dr. Thomas Starke, this course applies reinforcement learning to develop and optimize trading strategies using deep learning neural networks and replay memory. Learn to backtest, paper trade, and live trade strategies, while analyzing performance using synthetic and real-world data. The course includes hands-on Python implementation, with a capstone project in financial markets.
Trading Alphas: Mining, Optimisation, and System Design
Learn to build micro-alpha models by identifying market inefficiencies such as trends, mean reversion, and chart patterns. Analyze, backtest, optimize, and implement these strategies using efficient coding techniques. The course covers various aspects like portfolio optimization, machine learning alphas, and trading system implementation, along with real-world applications in live trading.
AI for Portfolio Management: LSTM Networks
Offered by Dr. Thomas Starke, this course uses LSTM networks to optimize portfolio management. You'll cover mean-variance optimization, AI algorithms for portfolio management, and practical techniques like walk-forward optimization and hyperparameter tuning. Gain hands-on experience with live trading templates and two capstone projects.
Webinars Conducted
Artificial Intelligence for Portfolio Management by Dr Thomas Starke | Webinar
2024
Trading Alpha: Developing A Micro-Alpha Generating System [Webinar]
2022
Artificial intelligence in trading [Q&A Session]
2021
The World of Trading with Deep Reinforcement Learning by Dr Thomas Starke [WEBINAR]
2020