Ultra High Frequency Algorithmic Arbitrage Across International Index Futures
Ultra High Frequency Algorithmic Arbitrage Across International Index Futures
We show that persistent lead-lag relationships spanning mere fractions of a seccond exist in all three possible pairings of the S&P500, FTSE100, and DAX futures contracts. These relationships exhibit clear intraday patterns which help us to forecast mid-quote changes in lagging contracts with directional accuracy in excess of 85%. A simple algorithmic trading strategy exploiting these relations yields economically significant profits which are robust to market impact costs and the bid-ask spread. We find that price slippage and infrastructure costs are our most important limits to arbitrage. Our results support the Grossman and Stiglitz (1976, 1980) view that informational ine?fficiencies incentivize arbitrageurs to eliminate mispricings.
Alsayed, Hamad
ed2e7197-cd6c-4c36-b495-a2a3da525855
McGroarty, Frank
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Alsayed, Hamad
ed2e7197-cd6c-4c36-b495-a2a3da525855
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Alsayed, Hamad and McGroarty, Frank
(2014)
Ultra High Frequency Algorithmic Arbitrage Across International Index Futures.
Journal of Forecasting.
(In Press)
Abstract
We show that persistent lead-lag relationships spanning mere fractions of a seccond exist in all three possible pairings of the S&P500, FTSE100, and DAX futures contracts. These relationships exhibit clear intraday patterns which help us to forecast mid-quote changes in lagging contracts with directional accuracy in excess of 85%. A simple algorithmic trading strategy exploiting these relations yields economically significant profits which are robust to market impact costs and the bid-ask spread. We find that price slippage and infrastructure costs are our most important limits to arbitrage. Our results support the Grossman and Stiglitz (1976, 1980) view that informational ine?fficiencies incentivize arbitrageurs to eliminate mispricings.
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Accepted/In Press date: 22 February 2014
Organisations:
Centre for Digital, Interactive & Data Driven Marketing
Identifiers
Local EPrints ID: 341452
URI: http://eprints.soton.ac.uk/id/eprint/341452
ISSN: 0277-6693
PURE UUID: 08160cbc-dc30-4159-8bef-a1c58ee31f01
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Date deposited: 25 Jul 2012 11:48
Last modified: 11 Dec 2021 03:53
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Contributors
Author:
Hamad Alsayed
Author:
Frank McGroarty
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