Using a connectedness-measurement technology fundamentally grounded in modern network theory, we measure real output connectedness for a set of six developed countries, 1962-2010. We show that global connectedness is sizable and time-varying over the business cycle, and we study the nature of...

Notwithstanding its impressive contributions to empirical financial economics, there remains a significant gap in the volatility literature, namely its relative neglect of the connection between macroeconomic fundamentals and asset return volatility. We progress by analyzing a broad...

We use variance decompositions from high-dimensional vector autoregressions to characterize connectedness in 19 key commodity return volatilities, 2011-2016. We study both static (full-sample) and dynamic (rolling-sample) connectedness. We summarize and visualize the results using tools from...

We use lasso methods to shrink, select and estimate the network linking the publicly-traded subset of the world's top 150 banks, 2003-2014. We characterize static network connectedness using full-sample estimation and dynamic network connectedness using rolling-window estimation. Statistically,...

We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness among financial asset returns and volatilities. We also show that variance decompositions define weighted, directed networks, so...

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes,...

We argue for incorporating the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise,...

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...

I investigate the origins of the now-ubiquitous term ”Big Data," in industry and academics, in computer science and statistics/econometrics. Credit for coining the term must be shared. In particular, John Mashey and others at Silicon Graphics produced highly relevant (unpublished,...

The Diebold-Mariano (DM) test was intended for comparing forecasts; it has been, and remains, useful in that regard. The DM test was not intended for comparing models. Unfortunately, however, much of the large subsequent literature uses DM-type tests for comparing models, in (pseudo-)...