We develop a novel firm-level measure of cybersecurity risk using textual analysis of cybersecurity-risk disclosures in corporate filings. The measure successfully identifies firms extensively discussing cybersecurity risk in their 10-K, displays intuitive relations with quantitative measures of...

We construct novel text-based measures of firm-level cyber risk exposure based on quarterly earnings calls of 12,000+ firms from 85 countries over 20+ years. We categorize each cyber-related discussion into topics that capture sentiment, monetary loss, country names, etc. We document new facts...

The amount of computational power devoted to anonymous, decentralized blockchains such as Bitcoin's must simultaneously satisfy two conditions in equilibrium: (1) a zero-profit condition among miners, who engage in a rent-seeking competition for the prize associated with adding the next block to...

This paper provides an empirical analysis of the risk of trading revenues of U.S. commercial banks. We collect quarterly data on trading revenues, broken down by business line, as well as the Value at Risk-based market risk charge. The overall picture from these preliminary results is that there...

This paper examines how governance and risk management affect risk-taking in banks. It distinguishes between good risks, which are risks that have an ex ante private reward for the bank on a stand-alone basis, and bad risks, which do not have such a reward. A well-governed bank takes the amount...

Current practice largely follows restrictive approaches to market risk measurement, such as historical simulation or RiskMetrics. In contrast, we propose flexible methods that exploit recent developments in financial econometrics and are likely to produce more accurate risk assessments, treating...

While the advent of cryptocurrencies and digital assets holds promise for improving and disrupting financial systems by offering cheap, quick, and secure transfer of value, it also opens up new payment channels for cybercrimes. A prerequisite to solving a problem is understanding the nature of...

A prominent challenge when drawing causal inference using observational data is the ubiquitous presence of endogenous regressors. The classical econometric method to handle regressor endogeneity requires instrumental variables that must satisfy the stringent condition of exclusion restriction,...

This paper presents a new multivariate copula-based modeling approach for analyzing cost-offsets between drug and nondrug expenditures. Estimates are based on panel data from the Medical Expenditure Panel Survey (MEPS) with quarterly measures of medical expenditures. The approach allows for...

Causal inference is of central interests in many empirical applications yet often challenging because of the presence of endogenous regressors. The classical approach to the problem requires using instrumental variables that must satisfy the stringent condition of exclusion restriction. At the...