Abstract
Equity auctions display several distinctive characteristics in contrast to continuous trading. As the auction time approaches, the rate of events accelerates causing a substantial liquidity buildup around the indicative price. This, in turn, results in a reduced price impact and decreased volatility of the indicative price. In this study, we adapt the latent/revealed order book framework to the specifics of equity auctions. We provide precise measurements of the model parameters, including order submissions, cancelations, and diffusion rates. Our setup allows us to describe the full dynamics of the average order book during closing auctions in Euronext Paris. These findings support the relevance of the latent liquidity framework in describing limit order book dynamics. Lastly, we analyze the factors contributing to a sub-diffusive indicative price and demonstrate the absence of indicative price predictability.
Acknowledgments
We thank Michele Vodret for fruitful discussions and acknowledge the use of the EUROFIDAI BEDOFIH's database acquired through ‘Equipex PLADIFES ANR-21-ESRE-0036 (France 2030)’.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 In the 28th of September 2015, Euronext introduced a random clearing window of thirty-second length for its equity auctions. The clearing randomly happens between 09:00:00 and 09:00:30 for the opening auction and 17:35:00 and 17:35:30 for the closing auction. This prevents fast agents from using low latency to take advantage of slower agents.
2 A participant is considered a high-frequency trader (HFT) if he meets one of the two following conditions:
The average lifetime of its canceled orders is less than the average lifetime of all orders in the book, and it has canceled at least 100 000 orders during the year.
The participant must have canceled at least 500,000 orders with a lifetime of fewer than 0.1 seconds, and the top percentile of the lifetime of its canceled orders must be less than 500 microseconds.
An investment bank meeting one of these conditions is described as mixed-HFT (MIX). If a participant does not meet any of the above conditions, it is a non-HFT (NON).