Mika Meitz
Impact in
- Finance top 5%
- Financial Risk and Volatility Modeling
- Stochastic processes and financial applications
-
- Monetary Policy and Economic Impact
Papers in
-
- Statistical Methods and Inference 7
- Statistical Distribution Estimation and Applications 5
- Statistical Methods and Bayesian Inference 2
- Finance 14
- Financial Risk and Volatility Modeling 14
- Stochastic processes and financial applications 2
Mika Meitz
20 papers receiving 277 citations
Peers
Comparison fields: 5 of 40
- Finance 223
- General Economics, Econometrics and Finance 110
- Statistics and Probability 107
- Economics and Econometrics 138
- Management Science and Operations Research 22
Countries citing papers authored by Mika Meitz
This map shows the geographic impact of Mika Meitz'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 Mika Meitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mika Meitz more than expected).
Fields of papers citing papers by Mika Meitz
This network shows the impact of papers produced by Mika Meitz. 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 Mika Meitz. The network helps show where Mika Meitz may publish in the future.
Co-authorship network
The 5 scholars most cited alongside Mika Meitz, 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 | 2024 | 1 | |
| 2 | 2023 | 0 | |
| 3 | 2021 | 2 | |
| 4 | 2021 | 10 | |
| 5 | 2020 | 14 | |
| 6 | 2018 | 1 | |
| 7 | 2018 | 1 | |
| 8 | 2018 | 1 | |
| 9 | 2016 | 25 | |
| 10 | MODELING THE EURO–USD EXCHANGE RATE WITH THE GAUSSIAN MIXTURE AUTOREGRESSIVE MODEL | 2014 | 1 |
| 11 | 2014 | 20 | |
| 12 | 2013 | 4 | |
| 13 | 2012 | 9 | |
| 14 | 2010 | 4 | |
| 15 | 2008 | 1 | |
| 16 | 2008 | 64 | |
| 17 | 2008 | 9 | |
| 18 | 2006 | 6 | |
| 19 | Five contributions to econometric theory and the econometrics of ultra-high-frequency data | 2006 | 12 |
| 20 | 2005 | 78 |
About Mika Meitz
Mika Meitz is a scholar working on Statistics and Probability, Finance, General Economics, Econometrics and Finance, Economics and Econometrics and Artificial Intelligence, having authored 21 papers that have together received 297 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (14 papers), Statistical Methods and Inference (7 papers), Monetary Policy and Economic Impact (6 papers), Statistical Distribution Estimation and Applications (5 papers), Market Dynamics and Volatility (4 papers), Bayesian Methods and Mixture Models (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Stochastic processes and financial applications (2 papers). The work is most often cited by research in Finance (223 citations), General Economics, Econometrics and Finance (110 citations), Statistics and Probability (107 citations), Economics and Econometrics (138 citations) and Management Science and Operations Research (22 citations). Mika Meitz has collaborated with scholars based in Finland, Türkiye and Sweden. Frequent co-authors include Pentti Saikkonen, Timo Teräsvirta, Helmut Lütkepohl, Aleksei Netšunajev and Markku Lanne. Their work appears in journals such as Econometric Theory, Econometrics Journal, Scandinavian Journal of Statistics, Journal of Time Series Analysis and Journal of Multivariate Analysis.
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.