Overview

Financial markets are rapidly evolving to exploit powerful computational and statistical tools to construct both risk management and alpha strategies. This research seeks to develop new tools to identify efficient trading strategies through the use of genetic programming and some mathematical optimisation methods such as adaptive elastic net regularisation while leveraging the powerful hardware acceleration capabilities of Field Programmable Gate Array technology. The first contribution of this thesis represents a Field Programmable Gate Array based algorithmic trading system which supports multiple trading strategies that can be either run in parallel or switched at run-time according to changes in market volatility, for more elaborate trading strategies.

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