Juho Kanniainen
- Management Science and Operations Research top 1%
- Economics and Econometrics top 2%
- Finance top 2%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Co-authors
- Alexandros IosifidisMoncef GabboujNikolaos PassalisAnastasios TefasAvraam TsantekidisDat Thanh TranHaiyuan YangSaku Mäkinen
- Topics
- Complex Systems and Time Series Analysis (30 papers)Financial Markets and Investment Strategies (28 papers)Stochastic processes and financial applications (19 papers)
In The Last Decade
Juho Kanniainen
71 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 100
- Management Science and Operations Research 535
- Economics and Econometrics 420
- Finance 392
- Electrical and Electronic Engineering 214
- Artificial Intelligence 176
Countries citing papers authored by Juho Kanniainen
This map shows the geographic impact of Juho Kanniainen'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 Juho Kanniainen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juho Kanniainen more than expected).
Fields of papers citing papers by Juho Kanniainen
This network shows the impact of papers produced by Juho Kanniainen. 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 Juho Kanniainen. The network helps show where Juho Kanniainen may publish in the future.
Co-authorship network of co-authors of Juho Kanniainen
This figure shows the co-authorship network connecting the top 25 collaborators of Juho Kanniainen. A scholar is included among the top collaborators of Juho Kanniainen 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 Juho Kanniainen. Juho Kanniainen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 11 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 9 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 10 | |
| 12 | Feature Engineering for Mid-Price Prediction Forecasting with Deep Learning | 1 |
| 13 | 38 | |
| 14 | 162 | |
| 15 | 14 | |
| 16 | 17 | |
| 17 | Forecasting the Diffusion of Innovation: A Stochastic Bass Model with Log-Normal and Mean-Reverting Error Process | 1 |
| 18 | Option Pricing Under Joint Dynamics of Interest Rates, Dividends, and Stock Prices | 2 |
| 19 | 10 | |
| 20 | Solving financial differential equations using differentiation matrices | 6 |
About Juho Kanniainen
Juho Kanniainen is a scholar working on Finance, Management Science and Operations Research and Economics and Econometrics, having authored 82 papers that have together received 1.1k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (30 papers), Financial Markets and Investment Strategies (28 papers) and Stochastic processes and financial applications (19 papers). The work is most often cited by research in Management Science and Operations Research (535 citations), Finance (392 citations) and Computational Mathematics (9 citations). Juho Kanniainen has collaborated with scholars based in Finland, Denmark and Greece. Frequent co-authors include Alexandros Iosifidis, Moncef Gabbouj, Nikolaos Passalis, Anastasios Tefas, Avraam Tsantekidis, Dat Thanh Tran, Haiyuan Yang, Saku Mäkinen, Robert Piché and Frank Emmert‐Streib. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.
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.