Global climate change and warming and unplanned urbanization have resulted in industrial facilities and livelihoods encroaching on wildlands. Wildfire risks are increasing globally, and concerns about natural hazards triggering technological accidents (Natech) caused by wildfires in...

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...

This paper investigates the performance of different parametric models, stable and tempered stable distributions, for capturing the tail behaviour of the log-returns. We first define and discuss the properties of the stable and tempered stable random variables. We then show how to estimate their...

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...

If the closed-form formula for the probability density function is not available, implementing the maximum likelihood estimation is challenging. We introduce a simple, fast, and accurate way for the estimation of numerous distributions that belong to the class of tempered stable probability...

We develop a multivariate Lévy model and apply the bivariate model for the pricing of quanto options that captures three characteristics observed in real-world markets for stock prices and currencies: jumps, heavy tails and skewness. The model is developed by using a bottom-up approach from a...

A multi-layer, multi-node ReLU network is a powerful, efficient, and popular tool in statistical prediction tasks. However, in contrast to the great emphasis on its empirical applications, its statistical properties are rarely investigated which is mainly due to its severe nonlinearity and heavy...

We study the investor beliefs, sentiment and disagreement, about stock market returns during the COVID-19 pandemic using a large number of messages of investors -- about 3.7 million messages -- on a social media investing platform,StockTwits. The rich and multimodal features of StockTwits data...