Markus Haas

1.2k citations
23 papers · 566 · h-index 9

Impact in

Papers in

Markus Haas

23 papers receiving 533 citations

Peers

Markus Haas
Comparison fields: 5 of 48
  • Finance 454
  • General Economics, Econometrics and Finance 175
  • Economics and Econometrics 378
  • Statistics and Probability 68
  • Management Science and Operations Research 46
Replace Patrick Gagliardini with:
Patrick Gagliardini Switzerland
Giorgio Calzolari Italy
Christos Agiakloglou Greece
Jialin Yu United States
Nour Meddahi France
Jean‐Guy Simonato Canada
Robert L. Kimmel United States
Roman Liesenfeld Germany
Jesper Lund Denmark
Genaro Sucarrat Norway
Markus Haas relative to Patrick Gagliardini Switzerland Patrick Gagliardini's profile →
Citations per field
00.5×2×3×3.8×
Patrick Gagliardini · 1×
Citations per year

Countries citing papers authored by Markus Haas

Since Specialization
Citations

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

Fields of papers citing papers by Markus Haas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 4 scholars most cited alongside Markus Haas, 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 Markus Haas Line = papers co-authored together Markus Haas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004352
2 201234
3 200929
4 200828
5 201321
6 200618
7 201015
8 201813
9 200610
10 20079
11 20157
12 20094
13
Do investors dislike kurtosis
20074
14 20094
15 19894
16 20093
17 20083
18 20082
19
Analyzing and Exploiting Asymmetries in the News Impact Curve
20062
20 20081

About Markus Haas

Markus Haas is a scholar working on Finance, Economics and Econometrics, Statistics and Probability, General Economics, Econometrics and Finance and Management Science and Operations Research, having authored 23 papers that have together received 566 indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (16 papers), Market Dynamics and Volatility (13 papers), Complex Systems and Time Series Analysis (8 papers), Statistical Distribution Estimation and Applications (6 papers), Monetary Policy and Economic Impact (5 papers), Bayesian Methods and Mixture Models (2 papers), Digitalization, Law, and Regulation (2 papers) and Criminal Law and Policy (2 papers). The work is most often cited by research in Finance (454 citations), General Economics, Econometrics and Finance (175 citations), Economics and Econometrics (378 citations), Statistics and Probability (68 citations) and Management Science and Operations Research (46 citations). Markus Haas has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Marc S. Paolella, Stefan Mittnik, Bruce Mizrach and Christian Pigorsch. Their work appears in journals such as Studies in Nonlinear Dynamics and Econometrics, The North American Journal of Economics and Finance, Journal of Financial Stability, Journal of Econometrics and Applied Mathematics and Computation.

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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