High Performance Computing in Finance, Chapman & Hall/CRC Series in Mathematical Finance, 2017
29 Pages Posted: 12 Apr 2017 Last revised: 3 May 2017
Date Written: April 5, 2017
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.
Keywords: asset management, trading, algorithm
JEL Classification: G110, G120, C1
Suggested Citation: Suggested Citation
Golub, Anton and Glattfelder, James and Olsen, Richard B., The Alpha Engine: Designing an Automated Trading Algorithm (April 5, 2017). High Performance Computing in Finance, Chapman & Hall/CRC Series in Mathematical Finance, 2017. Available at SSRN: https://ssrn.com/abstract=2951348