Wolfram Barfuss

Personal Details

First Name:	Wolfram
Middle Name:
Last Name:	Barfuss
Suffix:
RePEc Short-ID:	pba2158
	[This author has chosen not to make the email address public]
	https://wbarfuss.github.io/

Affiliation

Institut für Lebensmittel und Ressourcenökonomik
Rheinische Friedrich-Wilhelms-Universität Bonn

Bonn, Germany
http://www.ilr.uni-bonn.de/
RePEc:edi:ilbonde (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Wolfram Barfuss & Janusz Meylahn, 2022. "Intrinsic fluctuations of reinforcement learning promote cooperation," Papers 2209.01013, arXiv.org, revised Feb 2023.

   Cited by:

   1. Jay Armas & Wout Merbis & Janusz Meylahn & Soroush Rafiee Rad & Mauricio J. del Razo, 2023. "Risk aversion can promote cooperation," Papers 2306.05971, arXiv.org, revised Nov 2024.
   2. Hans-Theo Normann & Nina Ruli'e & Olaf Stypa & Tobias Werner, 2025. "Delegate Pricing Decisions to an Algorithm? Experimental Evidence," Papers 2510.27636, arXiv.org.
   3. Ding, Zhen-Wei & Zheng, Guo-Zhong & Cai, Chao-Ran & Cai, Wei-Ran & Chen, Li & Zhang, Ji-Qiang & Wang, Xu-Ming, 2023. "Emergence of cooperation in two-agent repeated games with reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

2. Barfuss, Wolfram & Massara, Guido Previde & Di Matteo, T. & Aste, Tomaso, 2016. "Parsimonious modeling with information filtering networks," LSE Research Online Documents on Economics 68860, London School of Economics and Political Science, LSE Library.

   Cited by:

   1. Seabrook, Isobel & Barucca, Paolo & Caccioli, Fabio, 2022. "Structural importance and evolution: an application to financial transaction networks," LSE Research Online Documents on Economics 117130, London School of Economics and Political Science, LSE Library.
   2. Lu, Ya-Nan & Li, Sai-Ping & Zhong, Li-Xin & Jiang, Xiong-Fei & Ren, Fei, 2018. "A clustering-based portfolio strategy incorporating momentum effect and market trend prediction," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 1-15.
   3. Wang, Yuanrong & Aste, Tomaso, 2023. "Dynamic portfolio optimization with inverse covariance clustering," LSE Research Online Documents on Economics 117701, London School of Economics and Political Science, LSE Library.
   4. Seabrook, Isobel & Barucca, Paolo & Caccioli, Fabio, 2022. "Structural importance and evolution: An application to financial transaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
   5. Tomaso Aste, 2020. "Stress testing and systemic risk measures using multivariate conditional probability," Papers 2004.06420, arXiv.org, revised May 2021.
   6. Yuanrong Wang & Tomaso Aste, 2021. "Dynamic Portfolio Optimization with Inverse Covariance Clustering," Papers 2112.15499, arXiv.org, revised Jan 2022.
   7. Musmeci, Nicoló & Nicosia, Vincenzo & Aste, Tomaso & Di Matteo, Tiziana & Latora, Vito, 2017. "The multiplex dependency structure of financial markets," LSE Research Online Documents on Economics 85337, London School of Economics and Political Science, LSE Library.
   8. Pier Francesco Procacci & Tomaso Aste, 2022. "Portfolio optimization with sparse multivariate modeling," Journal of Asset Management, Palgrave Macmillan, vol. 23(6), pages 445-465, October.
   9. Pier Francesco Procacci & Tomaso Aste, 2018. "Forecasting market states," Papers 1807.05836, arXiv.org, revised May 2019.
   10. Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2018. "Latent Factor Models for Credit Scoring in P2P Systems," MPRA Paper 92636, University Library of Munich, Germany, revised 11 Oct 2018.
       • Ahelegbey, Daniel Felix & Giudici, Paolo & Hadji-Misheva, Branka, 2019. "Latent factor models for credit scoring in P2P systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 112-121.
   11. Nicola, Giancarlo & Cerchiello, Paola & Aste, Tomaso, 2020. "Information network modeling for U.S. banking systemic risk," LSE Research Online Documents on Economics 107563, London School of Economics and Political Science, LSE Library.
   12. Tomaso Aste & T. Di Matteo, 2017. "Sparse Causality Network Retrieval from Short Time Series," Complexity, Hindawi, vol. 2017, pages 1-13, November.
   13. Kaizheng Wang & Xiao Xu & Xun Yu Zhou, 2022. "Variable Clustering via Distributionally Robust Nodewise Regression," Papers 2212.07944, arXiv.org, revised Dec 2022.
   14. Danial Saef & Yuanrong Wang & Tomaso Aste, 2022. "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing," Papers 2208.12614, arXiv.org, revised Sep 2022.
   15. Shahzad, Syed Jawad Hussain & Bouri, Elie & Karim, Sitara & Sadorsky, Perry, 2025. "A partial correlation-based connectedness approach: Extreme dependence among commodities and portfolio implications," Energy Economics, Elsevier, vol. 144(C).
   16. Yuanrong Wang & Antonio Briola & Tomaso Aste, 2023. "Topological Portfolio Selection and Optimization," Papers 2310.14881, arXiv.org.
   17. Yuanrong Wang & Tomaso Aste, 2022. "Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series," Papers 2203.03991, arXiv.org.
   18. Vidal-Tomás, David & Briola, Antonio & Aste, Tomaso, 2023. "FTX's downfall and Binance's consolidation: the fragility of centralised digital finance," LSE Research Online Documents on Economics 119902, London School of Economics and Political Science, LSE Library.
   19. Isobel Seabrook & Fabio Caccioli & Tomaso Aste, 2021. "An Information Filtering approach to stress testing: an application to FTSE markets," Papers 2106.08778, arXiv.org.
   20. Lan, Qiujun & Li, Haojie & Mi, Xianhua & Zhang, Chunyu, 2025. "Optimizing investment strategies: Harnessing the power of K-line complex networks," International Review of Economics & Finance, Elsevier, vol. 99(C).
   21. Nicolò Musmeci & Vincenzo Nicosia & Tomaso Aste & Tiziana Di Matteo & Vito Latora, 2017. "The Multiplex Dependency Structure of Financial Markets," Complexity, Hindawi, vol. 2017, pages 1-13, September.
   22. Douglas Castilho & Tharsis T. P. Souza & Soong Moon Kang & Jo~ao Gama & Andr'e C. P. L. F. de Carvalho, 2021. "Forecasting Financial Market Structure from Network Features using Machine Learning," Papers 2110.11751, arXiv.org.
   23. Pier Francesco Procacci & Tomaso Aste, 2021. "Portfolio Optimization with Sparse Multivariate Modelling," Papers 2103.15232, arXiv.org.
   24. Tomaso Aste, 2021. "Stress Testing and Systemic Risk Measures Using Elliptical Conditional Multivariate Probabilities," JRFM, MDPI, vol. 14(5), pages 1-17, May.
   25. Yang, Liwei & Liu, Rumei & Zhang, Jianing, 2025. "Adaptive online portfolio selection incorporating systematic risk of the financial market," The North American Journal of Economics and Finance, Elsevier, vol. 79(C).
   26. Pier Francesco Procacci & Carolyn E. Phelan & Tomaso Aste, 2020. "Market structure dynamics during COVID-19 outbreak," Papers 2003.10922, arXiv.org.

Articles

1. Wolfram Barfuss & Jonathan F. Donges & Steven J. Lade & Jürgen Kurths, 2018. "When optimization for governing human-environment tipping elements is neither sustainable nor safe," Nature Communications, Nature, vol. 9(1), pages 1-10, December.

   Cited by:

   1. Alan Randall, 2022. "How Strong Sustainability Became Safety," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
   2. Jobst Heitzig & Wolfram Barfuss & Jonathan F. Donges, 2018. "A Thought Experiment on Sustainable Management of the Earth System," Sustainability, MDPI, vol. 10(6), pages 1-25, June.
   3. Alan Randall, 2020. "On Intergenerational Commitment, Weak Sustainability, and Safety," Sustainability, MDPI, vol. 12(13), pages 1-18, July.
   4. Alan Randall, 2021. "Monitoring Sustainability and Targeting Interventions: Indicators, Planetary Boundaries, Benefits and Costs," Sustainability, MDPI, vol. 13(6), pages 1-19, March.
   5. Alan Randall, 2021. "Resource Scarcity and Sustainability—The Shapes Have Shifted but the Stakes Keep Rising," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
   6. Wolfram Barfuss & Janusz Meylahn, 2022. "Intrinsic fluctuations of reinforcement learning promote cooperation," Papers 2209.01013, arXiv.org, revised Feb 2023.
   7. Brias, Antoine & Munch, Stephan B., 2021. "Ecosystem based multi-species management using Empirical Dynamic Programming," Ecological Modelling, Elsevier, vol. 441(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-CBE: Cognitive and Behavioural Economics (1) 2022-09-26
2. NEP-CMP: Computational Economics (1) 2017-01-22
3. NEP-ECM: Econometrics (1) 2017-01-22
4. NEP-ENV: Environmental Economics (1) 2024-04-01
5. NEP-EVO: Evolutionary Economics (1) 2022-09-26
6. NEP-GTH: Game Theory (1) 2022-09-26
7. NEP-ORE: Operations Research (1) 2017-01-22
8. NEP-SOC: Social Norms and Social Capital (1) 2024-04-01

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