F
Francis X. Diebold
Researcher at University of Pennsylvania
Publications - 376
Citations - 82582
Francis X. Diebold is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Volatility (finance) & Exchange rate. The author has an hindex of 110, co-authored 368 publications receiving 74723 citations. Previous affiliations of Francis X. Diebold include International Monetary Fund & Duke University.
Papers
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Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics
Peter Christoffersen,Peter Christoffersen,Peter Christoffersen,Francis X. Diebold,Francis X. Diebold +4 more
TL;DR: In this article, the authors consider three sets of phenomena that feature prominently and separately in the financial economics literature: conditional mean dependence (or lack thereof) in asset returns, dependence (and hence forecastability) of asset return signs, and dependence in asset return volatilities, and explore the relationships in detail.
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Bootstrapping Multivariate Spectra
TL;DR: In this paper, the authors generalize the Franke-Hardle (1992) spectral density bootstrap to the multivariate case, which facilitates the use of the bootstrap in frequency-domain econometric work, which often centers on crossvariable dynamic interactions.
Posted Content
Equity Market Spillovers in the Americas
Francis X. Diebold,Kamil Yilmaz +1 more
TL;DR: In this paper, the authors provide an empirical analysis of return and volatility spillovers among five equity markets in the Americas: Argentina, Brazil, Chile, Mexico and the U.S.
Posted Content
On the Correlation Structure of Microstructure Noise: A Financial Economic Approach
TL;DR: In this paper, the authors introduce the financial economics of market microstructure into the financial econometrics of asset return volatility estimation, and derive model-based volatility estimators, which they apply to stock and oil prices.
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Global Yield Curve Dynamics and Interactions: A Dynamic Nelson-Siegel Approach
TL;DR: In this article, the authors extend the Diebold-Li model to a global context, modeling a potentially large set of country yield curves in a framework that allows for both global and country-specific factors.