Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Stock Market Volatility and Macroeconomic Fundamentals
2012776 citationsRobert F. Engle, Éric Ghysels et al.The Review of Economics and Statisticsprofile →
This map shows the geographic impact of Éric Ghysels's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Éric Ghysels with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éric Ghysels more than expected).
This network shows the impact of papers produced by Éric Ghysels. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Éric Ghysels. The network helps show where Éric Ghysels may publish in the future.
Co-authorship network of co-authors of Éric Ghysels
This figure shows the co-authorship network connecting the top 25 collaborators of Éric Ghysels.
A scholar is included among the top collaborators of Éric Ghysels based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Éric Ghysels. Éric Ghysels is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Brownlees, Christian T., Benjamin Chabot, Éric Ghysels, & C Kurz. (2015). Backtesting Systemic Risk Measures During Historical Bank Runs. Econstor (Econstor).5 indexed citations
6.
Engle, Robert F., Éric Ghysels, & Bumjean Sohn. (2012). Stock Market Volatility and Macroeconomic Fundamentals. The Review of Economics and Statistics. 95(3). 776–797.776 indexed citations breakdown →
Ghysels, Éric, Denise R. Osborn, & Paulo M.M. Rodrigues. (2006). Forecasting Seasonal Time Series. RePEc: Research Papers in Economics. 1. 659–711.16 indexed citations
10.
Ghysels, Éric, Norman R. Swanson, & Mark W. Watson. (2001). Essays in econometrics: Collected Papers of Clive W. J. Granger Volume 1, Spectral Analysis, Seasonality, Nonlinearity, Methodology, and Forecasting. Cambridge University Press eBooks.7 indexed citations
11.
Granger, Clive W. J., Éric Ghysels, Norman R. Swanson, & Mark W. Watson. (2001). Causality, integration and cointegration, and long memory. Cambridge University Press eBooks.3 indexed citations
12.
Granger, Clive W. J., Éric Ghysels, Norman R. Swanson, & Mark W. Watson. (2001). Spectral analysis, seasonality, nonlinearity, methodology, and forecasting. Cambridge University Press eBooks.1 indexed citations
13.
Gouriéroux, Christian, Joann Jasiak, & Éric Ghysels. (2000). Causality between Returns and Traded Volumes. Annals of Economics and Statistics. 189–206.8 indexed citations
14.
Jasiak, Joann & Éric Ghysels. (1998). Stochastic Volatility and Time Deformation: An Application to Trading Volume and Leverage Effects. SSRN Electronic Journal.4 indexed citations
Ghysels, Éric, et al.. (1995). Simulation Based Inference in Moving Average Models. Annals of Economics and Statistics. 85–99.14 indexed citations
18.
Ghysels, Éric & Offer Lieberman. (1993). Dynamic Regression and Filtered Data Series: a Laplace Approximation to the Effects of Filtering in Small Samples. Papyrus : Institutional Repository (Université de Montréal).1 indexed citations
Ghysels, Éric. (1986). A Study Towards a Dynamic Theory of Seasonality for Economic Time Series. RePEc: Research Papers in Economics.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.