Gregor Kastner

16 papers receiving 438 citations

Peers

Gregor Kastner
Comparison fields: 5 of 58
  • General Economics, Econometrics and Finance 174
  • Finance 193
  • Computational Mathematics 7
  • Statistics and Probability 90
  • Economics and Econometrics 244
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Markus Pelger United States
Sylvia Kaufmann Austria
Bertrand B. Maillet France
Patrick Gagliardini Switzerland
Gael M. Martin Australia
Catherine Doz France
Jean‐Yves Pitarakis United Kingdom
Walter Distaso United Kingdom
Xiaohong Chen United States
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Countries citing papers authored by Gregor Kastner

Since Specialization
Citations

This map shows the geographic impact of Gregor Kastner'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 Gregor Kastner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregor Kastner more than expected).

Fields of papers citing papers by Gregor Kastner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregor Kastner. 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 Gregor Kastner. The network helps show where Gregor Kastner may publish in the future.

Co-authors

The 7 scholars most cited alongside Gregor Kastner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gregor Kastner Line = papers co-authored together Gregor Kastner links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2013180
2 201678
3 201862
4 202044
5 202122
6 201421
7 20199
8
An Optimization Model for Valuating Process Flexibility
20138
9 20137
10 20206
11
Heavy-Tailed Innovations in the R Package stochvol
20155
12 20133
13 20243
14
Efficient Bayesian Inference for Stochastic Volatility (SV) Models [R package stochvol version 3.0.3]
20202
15 20212
16 20252
17 20140
18 20250

About Gregor Kastner

Gregor Kastner is a scholar working on Finance, Statistics and Probability, General Economics, Econometrics and Finance, Management Information Systems and Industrial and Manufacturing Engineering, having authored 18 papers that have together received 454 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (11 papers), Statistical Methods and Inference (7 papers), Monetary Policy and Economic Impact (6 papers), Market Dynamics and Volatility (5 papers), Bayesian Methods and Mixture Models (3 papers), Stochastic processes and financial applications (2 papers), Scheduling and Optimization Algorithms (2 papers) and Forecasting Techniques and Applications (2 papers). The work is most often cited by research in General Economics, Econometrics and Finance (174 citations), Finance (193 citations), Computational Mathematics (7 citations), Statistics and Probability (90 citations) and Economics and Econometrics (244 citations). Gregor Kastner has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Sylvia Frühwirth‐Schnatter, Florian Huber, Maximilian Röglinger, Hedibert F. Lopes, Martin Feldkircher, Anthony N. Rezitis and Wilfried Elmenreich. Their work appears in journals such as Journal of Forecasting, Journal of Statistical Software, Australian Journal of Agricultural and Resource Economics, International Journal of Forecasting and Business & Information Systems Engineering.

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.

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