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 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...

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...

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...

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 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)...

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...

This paper analyzes whether the convergence of European economies and the introduction of the euro has produced some effects on European Stock Market volatilities. Using multivariate switching regime models we test this issue for stable European economies, such as Germany and France, and...

Are Italian Mutual Funds able to generate extra-return? Are some of them able to persistently beat the competitors? In this paper we address these questions and provide a detailed and systematic performance and return persistence analysis of the Italian equity mutual funds. The implications of...