Michael Grabchak

482 citations
42 papers · 288 · h-index 10

Impact in

  • Finance top 5%
    • Financial Risk and Volatility Modeling
    • Stochastic processes and financial applications
    • Statistical Methods and Inference

Papers in

    • Stochastic processes and financial applications 17
    • Financial Risk and Volatility Modeling 16
    • Bayesian Methods and Mixture Models 9
    • Authorship Attribution and Profiling 3

Michael Grabchak

38 papers receiving 271 citations

Peers

Michael Grabchak
Comparison fields: 5 of 81
  • Finance 129
  • Statistics and Probability 45
  • Management Science and Operations Research 62
  • Mathematical Physics 43
  • Artificial Intelligence 74
Replace Lingjiong Zhu with:
Lingjiong Zhu United States
Krishanu Maulik India
Jaya P. N. Bishwal United States
Jem N. Corcoran United States
Dmitrii Silvestrov Sweden
Areski Cousin France
Hongwei Long United States
Sylvain Delattre France
Fabrizio Leisen United Kingdom
Luca Pratelli Italy
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Citations per field
00.5×2.8×
Lingjiong Zhu · 1×
Citations per year

Countries citing papers authored by Michael Grabchak

Since Specialization
Citations

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

Fields of papers citing papers by Michael Grabchak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Michael Grabchak, 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 Michael Grabchak Line = papers co-authored together Michael Grabchak links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201035
2 201729
3 201625
4 201618
5 201217
6 201415
7 201313
8 201811
9 201310
10 20219
11 20149
12 20168
13 20208
14 20176
15 20116
16 20185
17 20195
18 20185
19 20155
20 20195

About Michael Grabchak

Michael Grabchak is a scholar working on Finance, Artificial Intelligence, Statistics and Probability, Management Science and Operations Research and Mathematical Physics, having authored 42 papers that have together received 288 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (17 papers), Financial Risk and Volatility Modeling (16 papers), Probability and Risk Models (9 papers), Bayesian Methods and Mixture Models (9 papers), Stochastic processes and statistical mechanics (8 papers), Statistical Methods and Inference (7 papers), Authorship Attribution and Profiling (3 papers) and Statistical Distribution Estimation and Applications (3 papers). The work is most often cited by research in Finance (129 citations), Statistics and Probability (45 citations), Management Science and Operations Research (62 citations), Mathematical Physics (43 citations) and Artificial Intelligence (74 citations). Michael Grabchak has collaborated with scholars based in United States, French Guiana and Finland. Frequent co-authors include Zhiyi Zhang, Gennady Samorodnitsky, Lijuan Cao, Éric Marcon, Gabriel Lang, Stanislav Molchanov, Yunfei Xia, Narayan Bhamidipati, Rushi Bhatt and Dinesh Garg. Their work appears in journals such as Statistics and Computing, Journal of Applied Probability, Financial Innovation, Journal of Quantitative Linguistics and Bernoulli.

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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