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...

To facilitate crossing from the "black box" to "glass box" in the application of neural networks (NNs), we develop a variable significant test for the multi-layer perceptrons. To derive the test statistic and its asymptotic distribution, we provide the consistency of the multi-layer perceptrons...

We empirically study sources of abnormal changes, henceforth jumps, simultaneously in investor beliefs and asset prices using 164 million tweets from a social media investing platform, StockTwits. Before the COVID-19 pandemic, we find that on average 4.88% (7.88%) jumps in asset prices (investor...