Portfolio Management Research
A list of important resources in my research on the portfolio management problem.
Books
Background
- Vector Calculus, Susan Jane Colley
- Introduction to Probability, Bertsekas & Tsitsiklis
- Hands on Machine Learning with Scikit Learn and Tensorflow, Aurelien Geron
- Fluent Python, Luciano Ramalho
- Refactoring, Martin Fowler
- Clean Code: A Handbook of Agile Software Craftsmanship, Robert C. Martin
- Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville
Reinforcement Learning
- Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
- Reinforcement Learning: State-of-the-Art, Marco Wiering
Finance
- Python for Finance: Analyze Big Financial Data, Yves Hilpisch
- The Black Swan, Nassim Nicholas Taleb
- Antifragile, Nassim Nicholas Taleb
- Denationalisation of Money, Friedrich A. Hayek
Papers
Background
Algorithms
- Proximal Policy Optimization Algorithms
- IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
- Trust Region Policy Optimization
- Approximately Optimal Approximate Reinforcement Learning
- Benchmarking Deep Reinforcement Learning for Continuous Control
- Proximal Policy Optimization Algorithms
- Emergence of Locomotion Behaviours in Rich Environments
- High-Dimensional Continuous Control Using Generalized Advantage Estimation
- Policy Gradient Methods for Reinforcement Learning with Function Approximation
- Asynchronous Methods for Deep Reinforcement Learning
- Addressing Function Approximation Error in Actor-Critic Methods
- Equivalence Between Policy Gradients and Soft Q-Learning
- Continuous control with deep reinforcement learning
- Deterministic Policy Gradient Algorithms
- Reinforcement Learning Algorithm for Partially Observable MDP
Portfolio Management
- Portfolio Selection, Harry Markowitz
- A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
Lectures
Background
Reinforcement Learning
- MIT Deep Learning
- Reinforcement Learning
- Advanced Deep Learning & Reinforcement Learning
- CS 294-112 at UC Berkeley
- Deep RL Bootcamp 2017
- Stanford University CS231n / youtube
- Stanford University CS229
- Technical talks
- Foreign exchange and trade
- ANTS #2)
- ANTS #3)
- ANTS #2)
- Quantopian / youtube
- OpenAI - Spinning Up in Deep RL Workshop