Limit Order Books and Liquidity around Scheduled and Non-Scheduled Announcements: Empirical Evidence from NASDAQ Nordic
By Milla Siikanen, Juho Kanniainen, Jaakko Valli. 2017
26 citations recorded by the source corpus.
Information arrivals may drive investors to require immediacy, generating sudden liquidity demand across multiple price levels in limit order books. We document significant intraday changes in stock limit order book characteristics and liquidity beyond the best levels around scheduled and non-scheduled company announcements. At aggregated level, liquidity beyond the best levels behaves quite differently from the bid–ask spread around scheduled announcements. Moreover, scheduled announcements improve multi-level liquidity to an exceptionally good level. We also provide evidence for pre-reactions in order books before non-scheduled announcements, which suggest the possibility of information leakage.
Subfields: Accounting, Finance
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Alexandros Iosifidis
- Moncef Gabbouj
- Anastasios Tefas
- Avraam Tsantekidis
- Nikolaos Passalis
- Juho Kanniainen
In Finance
- Alexandros Iosifidis
- Moncef Gabbouj
- Anastasios Tefas
- Avraam Tsantekidis
- Nikolaos Passalis
- Adamantios Ntakaris
- Juho Kanniainen
- Martin Magris
Citations in the corpus
- Using deep learning to detect price change indications in financial markets (2017, methodology): “The time period used for collecting that data ranges from the 1st to the 14th June 2010 (only business days are included), while the data are provided by the Nasdaq Nordic data feeds [14].”
- Benchmark Dataset for Mid-Price Prediction of Limit Order Book data (2017, background): “More information related to the above mentioned issues can be found in [48] and [47].”
- Time-series classification using neural Bag-of-Features (2017, methodology): “The dataset is provided by Nasdaq Nordic [22], [23].”
- Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks (2017, methodology): “The time period used for collecting that data ranges from the 1st to the 14th June 2010 (only business days are included), while the data are provided by the Nasdaq Nordic data feeds [14] [15].”