Paul Labys
Impact in
- Finance top 0.1%
- Financial Risk and Volatility Modeling
- Stochastic processes and financial applications
- Financial Markets and Investment Strategies
-
- Monetary Policy and Economic Impact
Papers in
- Finance 7
- Financial Risk and Volatility Modeling 7
- Stochastic processes and financial applications 2
-
- Complex Systems and Time Series Analysis 6
- Market Dynamics and Volatility 4
- Co-authors
- Francis X. Diebold (7 shared papers)Torben G. Andersen (7 shared papers)Tim Bollerslev (6 shared papers)Tim Bollerslev (1 shared paper)
- Journals
- Journal of the American Statistical Association (1 paper)Econometrica (1 paper)Multinational Finance Journal (1 paper)The Faculty Digital Archive (New York University) (1 paper)SSRN Electronic Journal (2 papers)
- Partner nations
- United StatesCanadaDenmark
In The Last Decade
Paul Labys
7 papers receiving 5.3k citations
Paul Labys's Hit Papers
Peers
Comparison fields: 5 of 62
- Finance 5.0k
- General Economics, Econometrics and Finance 1.5k
- Economics and Econometrics 4.2k
- Management Science and Operations Research 427
- Statistics and Probability 236
Countries citing papers authored by Paul Labys
This map shows the geographic impact of Paul Labys'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 Paul Labys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Labys more than expected).
Fields of papers citing papers by Paul Labys
This network shows the impact of papers produced by Paul Labys. 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 Paul Labys. The network helps show where Paul Labys may publish in the future.
Co-authors
The 4 scholars most cited alongside Paul Labys, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Modeling and Forecasting Realized Volatility Hit paper breakdown → | 2003 | 2706 |
| 2 | The Distribution of Realized Exchange Rate Volatility Hit paper breakdown → | 2001 | 1621 |
| 3 | Modeling and Forecasting Realized Volatility Hit paper breakdown → | 2001 | 515 |
| 4 | The Distribution of Exchange Rate Volatility | 1999 | 311 |
| 5 | 2001 | 265 | |
| 6 | 2000 | 117 | |
| 7 | 2005 | 19 |
About Paul Labys
Paul Labys is a scholar working on Finance, Economics and Econometrics, General Economics, Econometrics and Finance, Infectious Diseases and Organic Chemistry, having authored 7 papers that have together received 5.6k indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (7 papers), Complex Systems and Time Series Analysis (6 papers), Market Dynamics and Volatility (4 papers), Stochastic processes and financial applications (2 papers) and Monetary Policy and Economic Impact (1 paper). The work is most often cited by research in Finance (5.0k citations), General Economics, Econometrics and Finance (1.5k citations), Economics and Econometrics (4.2k citations), Management Science and Operations Research (427 citations) and Statistics and Probability (236 citations). Paul Labys has collaborated with scholars based in United States, Canada and Denmark. Frequent co-authors include Francis X. Diebold, Torben G. Andersen, Tim Bollerslev and Tim Bollerslev. Their work appears in journals such as Journal of the American Statistical Association, Econometrica, Multinational Finance Journal, The Faculty Digital Archive (New York University) and SSRN Electronic Journal.
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.