Title: Striving to make better decision quicker in cloud: big data event trading in high frequency trading perspective

Authors: Arodh Lal Karn; Niranjan Sapkota; Rakshha Kumari Karna; Muhammad Rafiq

Addresses: School of Management, Harbin Institute of Technology, 150001, Harbin, China ' University of Vaasa, Wolffintie 34, 65200 Vaasa, Finland ' School of Management, Harbin Institute of Technology, 150001, Harbin, China ' School of Management, Harbin Institute of Technology, 150001, Harbin, China

Abstract: In the world of big data, cloud computing in trading and rapid development in computing hardware and software; cloud computing and high frequency trading (HFT) unconditionally turn to be tightly related as the way market is changing rapidly. We find the practicability of event trading strategy of HFT in the Finnish stock market based on auto regressive empirical test and comparative ratios insinuating the impression on positive recovers of event trading. A specialised version of cloud trading system is then architected after discovering and exploring the feasibility of HFT in event-based trading in the Finnish stock market so that afresh get going HFT firms who are speculating what tact to exercise with what holding period and not capable to get micro second favours of news feed earlier than their adversaries; can practice this discipline and the proposed cloud trading architect for alpha generation.

Keywords: high frequency trading; HFT; event trading; limit order book; LOB; big data; cloud architect.

DOI: 10.1504/IJSTM.2020.106684

International Journal of Services Technology and Management, 2020 Vol.26 No.2/3, pp.215 - 236

Received: 08 Oct 2016
Accepted: 15 Feb 2017
Published online: 20 Apr 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article