Social interaction and information transmission are essential components of pricing and trading in financial markets. To investigate the behavior contagion and information cascades among investors and sectors, we deploy a jump-diffusion process on investor sentiment -- a novel dataset from...

To facilitate crossing from the "black box" to "glass box" in the application of neural net- works, we extend Horel and Giesecke (2020) and develop a variable/feature significant test for multi-layer perceptrons (MLP). The proposed test permits one to assess the statistical significance of the...

We empirically explore the role of investor disagreement and news for various types of stock jumps, where the dynamic of stock returns is captured by a contagion model. Our disagreement measure is derived from more than 173 million tweets from a social media investing platform, StockTwits, for...

Purpose This paper aims to propose a novel approach to constructing an economic taxonomy that demonstrates the complex relationships between firms, which are not fully revealed by traditional industry classification systems such as the NAICS or ICB. Design/methodology/approach Based on narrative...

This paper proposes a statistical framework in which artificial intelligence can assist human decision making. Using observational data we benchmark the performance of each decision maker against the machine predictions, and replace decision makers whose information process quality is dominated...