This paper extends the classic factor-based asset pricing model by including network linkages in linear factor models. We assume that the network linkages are exogenously provided. This extension of the model allows a better understanding of the causes of systematic risk and shows that (i)...

We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated...

We propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic...

We propose the "President reacts to news" channel of stock returns by studying the financial market impact of the Twitter account of the 45th president of the United States, Donald Trump. We use machine learning algorithms to classify topic and textual sentiment of 1,400 economy-related tweets...

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...

We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of...

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...

We show that (electronic) designated market makers are not necessarily beneficial to the stock market during ash crashes. They actually consume liquidity when it is most needed, even if they are rewarded by the exchange to provide immediacy. This behavior exacerbates the transient price impact,...

This paper investigates the interdependence between the risk-pooling activity of the financial sector and: output, consumption, risk-free rate, and Sharpe ratio in a dynamic general equilibrium model of a productive economy. Due to their exposure to idiosyncratic shocks and market segmentation,...

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...