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Goutte S., Klotzner K., Le H.-V., von Mettenheim H.-J. (2024). Forecasting photovoltaic production with neural networks and weather features. Energy Economics, 139. https://doi.org/10.1016/j.eneco.2024.107884

Karathanasopoulos, A., Lo, C. C., Sovan, M., Osman, M., von Mettenheim, H. J., & Skander, S. (2024). A multi-objective optimization metaheuristic hybrid technique for forecasting the electricity consumption of the UAE: A grey wolf approach. Journal of Forecasting, Volume 44 (Issue 1), 242-252. https://doi.org/10.1002/for.3187

Fogel, P., Geissler, C., J. Von Mettenheim, H., & Luta, G. (2023). Applying non-negative tensor factorization to centered data. Bankers, Markets & Investors, 174 (3), 2-13. https://www.cairn.info/revue-bankersmarkets-et-investors-2023-3-page-2.htm

Goutte, S., Grosse, R., Le, H. V., Liu, F., & Von Mettenheim, H. J. (2023). Portfolio management with ESG news sentiment. Bankers, Markets & Investors, 1-2 (172-173), 72-84. https://www.cairn.info/revue-bankersmarkets- et-investors-2023-1-page-72.htm

Goutte, S., Le, H. V., Liu, F., & Von Mettenheim, H. J. (2023). Deep learning and technical analysis in cryptocurrency market. Finance Research Letters, 54, 103809. https://doi.org/10.1016/j.frl.2023.103809

Le, V. H., von Mettenheim, H. J., Goutte, S., & Liu, F. (2022). News-based sentiment: Can it explain market performance before and after the Russia-Ukraine conflict?. The Journal of Risk Finance (ahead-of-print).

Tholl, J., Schwarzbach, C., Pittalis, S., & von Mettenheim, H. J. (2020). Bank funding and the recent political development in Italy: What about redenomination risk?. International Review of Law and Economics, 64, 105932. 

Nguyen, D. K., Sensoy, A., Vo, D. T., & von Mettenheim, H. J. (2021). Does short-term technical trading exist in the Vietnamese stock market? Borsa Istanbul Review, 21(1), 23-35. 

Gleue, C., Eilers, D., von Mettenheim, H. J., & Breitner, M. H. (2019). Decision support for the automotive industry: Forecasting residual values using artificial neural networks. Business & Information Systems Engineering, 61, 385-397.

Dress, K., Lessmann, S., & von Mettenheim, H. J. (2018). Residual value forecasting using asymmetric cost functions. International Journal of Forecasting, 34(4), 551-565.

Government Bond Yield Spreads in the Eurozone: Empirical Evicence from Better Days, to appear in Quantitative Finance, 2018 (with Tobias Basse, Christoph Wegener, Frederik Kunze).

Liu, F., Pantelous, A. A., & von Mettenheim, H. J. (2018). Forecasting and trading high frequency volatility on large indices. Quantitative Finance, 18(5), 737-748.

Gleue, C., Eilers, D., von Mettenheim, H. J., & Breitner, M. H. (2017). Decision support for the automotive industry: forecasting residual values using artificial neural networks.

Wegener, C., Basse, T., Kunze, F., & von Mettenheim, H. J. (2016). Oil prices and sovereign credit risk of oil-producing countries: an empirical investigation. Quantitative Finance, 16(12), 1961-1968.

Wegener, C., von Spreckelsen, C., Basse, T., & von Mettenheim, H. J. (2016). Forecasting government bond yields with neural networks considering cointegration. Journal of Forecasting, 35(1), 86-92.

Von Spreckelsen, C., Von Mettenheim, H. J., & Breitner, M. H. (2014). Steps towards a high-frequency financial decision support system to pricing options on currency futures with neural networks. International Journal of Applied Decision Sciences, 7(3), 223-238.

Von Spreckelsen, C., von Mettenheim, H. J., & Breitner, M. H. (2014). Real-time pricing and hedging of options on currency futures with artificial neural networks. Journal of Forecasting, 33(6), 419-432. 
 

2010-2016 : Professeur de Systèmes d'Aide à la Décision, École d'Économie (Université Leibniz de Hanovre)

2013-2014 : Administrateur des Professeurs Ordinaires de Macroéconomie, Marchés Financiers et Professeur Ordinaire de Banque et Finance (Université Leibniz de Hanovre)