大阪大学　数理・データ科学教育研究センター
Center for Mathematical Modeling and Data Science,Osaka University

Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

宇野 淳 （早稲田大学大学院ファイナンス研究科）

1. ホーム
2. セミナー・集中講義
3. セミナー
4. Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

大阪大学 数理・データ科学セミナー 金融・保険セミナーシリーズ 第72回

Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods

宇野 淳 （早稲田大学大学院ファイナンス研究科）

We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to price discovery and liquidity provision in the subsequent opening call auction. We empirically investigate these questions using a unique dataset based on server IDs provided by the Tokyo Stock Exchange (TSE), one of the largest stock markets in the world. Our data allow us to develop a more comprehensive classification of traders than in the prior literature, and to investigate the behavior of the different categories of traders, based on their speed of trading and inventory holdings.
We find that HFTs dynamically change their presence in different stocks and on different days; therefore, we focus on HFT activity only when they use the low latency capacity is utilized. We find that, in spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and significantly contribute to price discovery. They also contribute to liquidity provision in the opening call auction. In line with the previous literature, we also document that HFTs contribute to price discovery and are liquidity consumers during the continuous period. However, this result is driven by the three quarters of HFTs that were inactive in the pre-opening period. Instead, those that were active in the pre-opening period contribute to liquidity provision in the subsequent continuous session. This indicates that while HFTs contribute to price discovery and liquidity provision, there is considerable heterogeneity in their contribution to price discovery and liquidity provision. We also show that speed matters more than inventory holdings in predicting the contribution of HFTs to price discovery.
(with Mario Bellia, Loriana Pelizzon, Marti G. Subrahmanyam and Darya Yuferova)