High frequency trading strategy using the Hilbert transform

The recent escalation in computing power and database capacity in major financial exchanges has brought a substantial increase in both data and information availability. The ever faster development of computers, sensors, and information channels in financial IT has rendered trading data easier to be collected than ever before. The present study examines how the Hilbert transform may be used for the detection of financial market cycles and market trends. In particular, this paper focuses on measuring cyclic patterns of high frequency data to enhance intraday trading. The proposed approach exhibits several advantages over more traditional trading methods, attributed to its consideration of complex variables.