A computing platform for pairs-trading online implementation via a blended Kalman-HMM filtering approach

A computing platform for pairs-trading online implementation via a blended Kalman-HMM filtering approach

Abstract This paper addresses the problem of designing an efficient platform for pairs-trading implementation in real time. Capturing the stylised features of a spread process, i.e., the evolution of the differential between the returns from a pair of stocks, exhibiting a heavy-tailed mean-reverting...

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Bibliographic Details
Main Authors: Anton Tenyakov, Rogemar Mamon
Format: Article
Language:English
Published: SpringerOpen 2017-12-01
Series:Journal of Big Data
Subjects:
algorithm fusion
investment
financial signal processing
change of measure
Ornstein–Uhlenbeck process
Online Access:http://link.springer.com/article/10.1186/s40537-017-0106-3

Internet

http://link.springer.com/article/10.1186/s40537-017-0106-3

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