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

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.

Dynamic information spillover between Chinese carbon and stock markets under extreme weather shocks

“…Following Ren et al (2022), we construct a portfolio strategy based on the above information spillover relationship between carbon and stock markets, as well as the return characteristics of different markets under extreme risk conditions. We buy 1 unit of carbon emission allowance on the carbon market at time t and sell short unit β of asset i when the net extreme risk spillover of the carbon market is greater than its 90% quartile due to the carbon market trading from a risk receiver to a risk transmitter under extremely hot temperatures.…”

“…The complex relationship between time series caused by exogenous events (Ren et al, 2022) such as extreme weather events may be the main reason for the inconsistent conclusions in the above literature. With the severity of global warming and the frequent occurrence of extreme weather events, such as floods, extreme drought, and heat waves, climate risks have garnered attention from government and people (Zeng et al, 2023), and becoming one of the important risk sources driving financial markets (Venturini, 2022).…”

Social media information diffusion and excess stock returns co-movement

“…Due to the inherent complexity and frictions present in real financial markets, there typically exists a complex non-linear relationship between stock prices and other financial variables (Ren, Cai, Li, Xiong, & Chen, 2023). In this section, we delve further into the non-linear association between information diffusion and excess co-movement, employing the Thermal Optimal Path (TOP) method.…”

“…The TOP method's fundamental purpose is to reveal the dynamic leadlag structure between time series X and Y, making it a widely adopted tool for investigating non-linear relationships among financial variables (Wang, Tu, Chang, & Li, 2017;Chen et al, 2020;Gao et al, 2020;Yang & Shao, 2020;Yao & Li, 2020;Ren et al, 2023;Chen, Ren, Yang, Lu, & Li, 2023). Following the methodology outlined by Chen et al (2023), we construct a matrix of 19 × 19 thermal paths, each characterized by distinct starting and ending points.…”