This study introduces a new measure of ex ante litigation risk using scrutiny of SEC filings by the source of securities litigation—plaintiffs' lawyers—to reduce measurement error, relative to existing measures. We show that plaintiff-lawyer views proxy for the largely unobservable factors...

This note explores machine learning based modelling approach over classical quantitative methods with a focus on modelling realized volatility of asset price over time. Initially, a few modelling assumptions of classical quantitative finance are examined using recent market data. Daily stock...

Asset co-movement has attracted the increasing attention of researchers from traditional finance and emerging interdisciplinary disciplines. However, little is known about the consistency of market-wide co-movement proxies constructed from the two perspectives above. Employing Fama-French...

The study presents an analysis of the sediment thickness compared with bathymetric and geophysical settings in the Bay of Bengal and Andaman Sea, Indian Ocean. It uses a combination of the high-resolution data: topographic GEBCO, satellite and marine gravity anomalies, EGM2008 geoid and GlobSed...

In this document, we detail how to construct the Nielsen Ad Intel Database from the raw source filesprovided by the Kilts Center for Marketing at the University of Chicago Booth School of Business.Further, we detail our procedure for matching the Ad Intel data with the retail scanner data...

We propose a panel data approach to disentangle the impact of "one treatment" from the "other treatment" when the observed outcomes are subject to both treatments. We use the Great Hanshin-Awaji earthquake that took place on January 17, 1995 to illustrate our methodology. We find that there are...

We provide a methodology for testing a polynomial model hypothesis by extending the approach and results of Baek, Cho, and Phillips (2015; Journal of Econometrics; BCP) that tests for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We examine and...

We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature, including the different ways of constructing the set of priors that are the key input of the...

This paper advocates chaining the decomposition of shocks into contributions from forecast errors to the shock decomposition of the latent vector to better understand model inference about latent variables. Such a double decomposition allows us to gauge the inuence of data on latent variables,...

This paper establishes that when equations connecting coefficients from reduced forms with their structural counterparts are inconsistent, a necessary and sufficient condition standard in econometric textbooks for the identifiability of coefficients in linear simultaneous equations systems is...