The code presented here relates to the following book chapter:
The Alpha Engine: Designing an Automated Trading Algorithm
Golub, Anton and Glattfelder, James B. and Olsen, Richard B.
High Performance Computing in Finance
Chapman & Hall/CRC Series in Mathematical Finance
2017
A preprint is available at SSRN.
We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in financial markets, based on intrinsic events. This definition lead to the uncovering of a large set of scaling laws. An additional guiding principle was found by embedding the trading model construction in an agent-base framework, inspired by the study of complex systems. This new approach to designing automated trading algorithms is a parsimonious method for building a new type of investment strategy that not only generates profits, but also provides liquidity to financial markets and does not have a priori restrictions on the amount of assets that are managed.