Maria Kalli
- Statistics and Probability top 2%
- Statistical Methods and Inference 3
- Finance top 5%
- Financial Risk and Volatility Modeling 7
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models 6
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- Monetary Policy and Economic Impact 3
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- Complex Systems and Time Series Analysis 4
- Market Dynamics and Volatility 2
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- Forecasting Techniques and Applications 4
- Stock Market Forecasting Methods 2
- Co-authors
- Jim E. GriffinStephen G. WalkerPaul DamienJenny R. BillingsMichael BedfordPaul E. StevensChris FarmerSimon Coulton
- Journals
- SHILAP Revista de lepidopterología (1 paper)Journal of Econometrics (2 papers)Journal of Business and Economic Statistics (2 papers)
- Partner nations
- United KingdomUnited StatesCzechia
In The Last Decade
Maria Kalli
12 papers receiving 316 citations
Peers
Comparison fields: 5 of 73
- Statistics and Probability 163
- Finance 91
- Artificial Intelligence 199
- General Economics, Econometrics and Finance 29
- Computational Mathematics 2
Countries citing papers authored by Maria Kalli
This map shows the geographic impact of Maria Kalli'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 Maria Kalli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Kalli more than expected).
Fields of papers citing papers by Maria Kalli
This network shows the impact of papers produced by Maria Kalli. 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 Maria Kalli. The network helps show where Maria Kalli may publish in the future.
Co-authorship network
The 9 scholars most cited alongside Maria Kalli, 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 | Stock Market Liquidity and Return Predictability: A Bayesian Nonparametric Approach | 2019 | 1 |
| 2 | 2018 | 34 | |
| 3 | 2017 | 2 | |
| 4 | 2016 | 21 | |
| 5 | 2015 | 2 | |
| 6 | 2014 | 10 | |
| 7 | 2013 | 13 | |
| 8 | 2013 | 38 | |
| 9 | 2012 | 2 | |
| 10 | 2011 | 3 | |
| 11 | 2011 | 1 | |
| 12 | 2009 | 202 |
About Maria Kalli
Maria Kalli is a scholar working on Finance, Management Science and Operations Research and Statistics and Probability, having authored 12 papers that have together received 329 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (7 papers), Bayesian Methods and Mixture Models (6 papers), Complex Systems and Time Series Analysis (4 papers), Forecasting Techniques and Applications (4 papers), Statistical Methods and Inference (3 papers), Monetary Policy and Economic Impact (3 papers), Market Dynamics and Volatility (2 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Statistics and Probability (163 citations), Finance (91 citations) and Artificial Intelligence (199 citations). Maria Kalli has collaborated with scholars based in United Kingdom, United States and Czechia. Frequent co-authors include Jim E. Griffin, Stephen G. Walker, Paul Damien, Jenny R. Billings, Michael Bedford, Paul E. Stevens, Chris Farmer, Simon Coulton and Mark F. J. Steel. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Econometrics and Journal of Business and Economic Statistics.
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.