A Multi-market Comparison of the Intraday Lead–Lag Relations Among Stock Index-Based Spot, Futures and Options

Fei Ren (), Mei-Ling Cai (), Sai-Ping Li (), Xiong Xiong () and Zhang-HangJian Chen ()
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Fei Ren: East China University of Science and Technology
Mei-Ling Cai: East China University of Science and Technology
Sai-Ping Li: Academia Sinica
Xiong Xiong: Tianjin University
Zhang-HangJian Chen: Anhui University

Computational Economics, 2023, vol. 62, issue 1, No 1, 28 pages

Abstract: Abstract Using 1-min data, we explore the dynamic variation of the intraday lead–lag relations between stock indices and their derivatives through a comprehensive study with broader coverage of research objectives and methodologies. This paper provides explicit evidence that the futures and options exhibit price leadership over the spot market, and the options is ahead of the futures on most trading days in all three markets. This paper also reports a new finding that the relation between the derivative and its underlying index reverses when the index return has a significantly larger mean value, and the reversal phenomenon is also observed in the relations between the futures and the options, which enriches the empirical results of intraday lead–lag relations. Moreover, these conclusions still hold under the impact of extreme events, e.g., the outbreak of the Covid-19. Finally, we construct a pair trading strategy based on the intraday lead–lag relationships, which can get better performance than the corresponding spot index. Our findings can potentially help regulators understand the price discovery process between the index and its derivatives, and also be of great value for timely adjustment of investors intraday trading strategies.

Keywords: Lead–lag relation; Thermal optimal path; Information share model; High-frequency data; SSE 50 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10614-022-10268-0

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