Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which...

Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which...

This paper examines the dynamic relationship between credit risk and liquidity in the sovereign bond market in the context of the European Central Bank (ECB) interventions. Using a comprehensive set of liquidity measures obtained from a detailed, quote-level dataset of the largest interdealer...

We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on...

We show that bond purchases undertaken in the context of quantitative easing efforts by the European Central Bank created a large mispricing between the market for German and Italian government bonds and their respective futures contracts. On top of the direct effect the buying pressure exerted...

Through the lens of market participants' objective to minimize counterparty risk, we investigate central clearing in derivatives markets, and its interaction with systematic risk, portfolio directionality, and loss sharing. Previous studies suggest that central clearing always reduces...

We examine the strategic behavior of High Frequency Traders (HFTs) during the pre-opening phase and the opening auction of the NYSE-Euronext Paris exchange. HFTs actively participate, and profitably extract information from the order flow. They also post "flash crash" orders, to gain time...

The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the "Natural Language Toolkit" that uses machine...

Market fragmentation and technological advances increasing the speed of trading altered the functioning and stability of global equity limit order markets. Taking market resiliency as an indicator of market quality, we investigate how resilient are trading venues in a high-frequency environment...