Jochen Papenbrock

951 total citations · 1 hit paper
27 papers, 536 citations indexed

About

Jochen Papenbrock is a scholar working on Finance, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, Jochen Papenbrock has authored 27 papers receiving a total of 536 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Finance, 13 papers in Economics and Econometrics and 6 papers in Management Science and Operations Research. Recurrent topics in Jochen Papenbrock's work include Financial Markets and Investment Strategies (11 papers), Complex Systems and Time Series Analysis (9 papers) and Stock Market Forecasting Methods (6 papers). Jochen Papenbrock is often cited by papers focused on Financial Markets and Investment Strategies (11 papers), Complex Systems and Time Series Analysis (9 papers) and Stock Market Forecasting Methods (6 papers). Jochen Papenbrock collaborates with scholars based in United Kingdom, Italy and Switzerland. Jochen Papenbrock's co-authors include Dimitri Marinelli, Paolo Giudici, Niklas Bussmann, Elia Landi, Marco Mugnaini, Tommaso Lisini Baldi, Riccardo Moretti, Marco Pavone, Ansgar Koene and Ada Fort and has published in prestigious journals such as Computer, IEEE Sensors Journal and Quantitative Finance.

In The Last Decade

Jochen Papenbrock

25 papers receiving 487 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Explainable Machine Learning in Credit Risk Management

2020 222 citations Niklas Bussmann, Paolo Giudici et al. Computational Economics profile →

Peers

Jochen Papenbrock

AI

EE

ACCOU

MSOR

FINAN

Emanuela Raffinetti Italy

Arash Bahrammirzaee France

Bertrand K. Hassani France

Jia Zhai China

Dimitri Marinelli Italy

Niklas Bussmann Italy

Amir E. Khandani United States

Bruno Miranda Henrique Brazil

Matthew Dixon United States

Emanuela Raffinetti Italy

Jochen Papenbrock

219 ×1.0

AI

145 ×0.9

EE

88 ×0.5

ACCOU

146 ×0.9

MSOR

92 ×0.6

FINAN

Citations per year, relative to Jochen Papenbrock Jochen Papenbrock (= 1×) peers Emanuela Raffinetti

Countries citing papers authored by Jochen Papenbrock

Since Specialization

Citations

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

Fields of papers citing papers by Jochen Papenbrock

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jochen Papenbrock

This figure shows the co-authorship network connecting the top 25 collaborators of Jochen Papenbrock. A scholar is included among the top collaborators of Jochen Papenbrock 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 Jochen Papenbrock. Jochen Papenbrock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Landi, Elia, Tommaso Lisini Baldi, Jochen Papenbrock, et al.. (2025). Sensorization of Soft Robot Joints for Accurate and Durable Bending Measurement. IEEE Sensors Journal. 25(10). 18180–18191. 1 indexed citations

2.

Landi, Elia, Tommaso Lisini Baldi, Jochen Papenbrock, et al.. (2025). Sensorizing Flexible Joints for Soft Robots: a Feasibility Study. CINECA IRIS Institutional Research Information System (IRIS Istituto Nazionale di Ricerca Metrologica). 1–6.

3.

Landi, Elia, Tommaso Lisini Baldi, Riccardo Moretti, et al.. (2024). A Method for Sensing Passive Joints of Robotic Extra Fingers for Trajectory Tracking. Use Siena air (University of Siena). 562–567. 4 indexed citations

4.

Mariani, Riccardo, Francesca Rossi, Rita Cucchiara, et al.. (2023). Trustworthy AI—Part 1. Computer. 56(2). 14–18. 4 indexed citations

5.

Mariani, Riccardo, Francesca Rossi, Rita Cucchiara, et al.. (2023). Trustworthy AI—Part II. Computer. 56(5). 13–16. 1 indexed citations

6.

Papenbrock, Jochen, et al.. (2022). Financial Risk Management and Explainable, Trustworthy, Responsible AI. Frontiers in Artificial Intelligence. 5. 779799–779799. 38 indexed citations

7.

Papenbrock, Jochen, et al.. (2021). Adaptive Seriational Risk Parity and Other Extensions for Heuristic Portfolio Construction Using Machine Learning and Graph Theory. Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences). 3(4). 65–83. 7 indexed citations

8.

Papenbrock, Jochen, et al.. (2021). Matrix Evolutions: Synthetic Correlations and Explainable Machine Learning for Constructing Robust Investment Portfolios. Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences). 3(2). 51–69. 11 indexed citations

9.

Bussmann, Niklas, Paolo Giudici, Dimitri Marinelli, & Jochen Papenbrock. (2020). Explainable AI in Fintech Risk Management. Frontiers in Artificial Intelligence. 3. 26–26. 112 indexed citations

10.

Bussmann, Niklas, Paolo Giudici, Dimitri Marinelli, & Jochen Papenbrock. (2020). Explainable Machine Learning in Credit Risk Management. Computational Economics. 57(1). 203–216. 222 indexed citations breakdown →

11.

Marinelli, Dimitri, et al.. (2020). Interpretable Machine Learning for Diversified Portfolio Construction. SSRN Electronic Journal. 5 indexed citations

12.

Marinelli, Dimitri, et al.. (2020). Understanding Machine Learning for Diversified Portfolio Construction by Explainable AI. SSRN Electronic Journal. 5 indexed citations

13.

Papenbrock, Jochen, et al.. (2020). Matrix Evolutions: Synthetic Correlations and Explainable Machine Learning for Constructing Robust Investment Portfolios. SSRN Electronic Journal. 2 indexed citations

14.

Bussmann, Niklas, Paolo Giudici, Dimitri Marinelli, & Jochen Papenbrock. (2019). Explainable AI in Credit Risk Management. SSRN Electronic Journal. 20 indexed citations

15.

Papenbrock, Jochen, et al.. (2016). Tail-risk protection trading strategies. Quantitative Finance. 17(5). 729–744. 9 indexed citations

16.

Papenbrock, Jochen, et al.. (2015). Handling risk-on/risk-off dynamics with correlation regimes and correlation networks. Financial markets and portfolio management. 29(2). 125–147. 23 indexed citations

17.

Lohre, Harald, et al.. (2014). The Use of Correlation Networks in Parametric Portfolio Policies. SSRN Electronic Journal. 3 indexed citations

18.

Papenbrock, Jochen, et al.. (2013). Handling Risk On/Risk Off Dynamics with Correlation Regimes and Correlation Networks. SSRN Electronic Journal. 2 indexed citations

19.

Papenbrock, Jochen. (2011). Asset Clusters and Asset Networks in Financial Risk Management and Portfolio Optimization. Repository KITopen (Karlsruhe Institute of Technology). 11 indexed citations

20.

Papenbrock, Jochen, et al.. (2009). Price calibration and hedging of correlation dependent credit derivatives using a structural model with α-stable distributions. Applied Financial Economics. 19(17). 1401–1416. 1 indexed citations

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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