Norbert Fogarasi

Department of Networked Systems and Services

Budapest University of Technology and Economics

Budapest, Hungary

 

Email: fogarasi AT hit DOT bme DOT hu

URL: http://www.hit.bme.hu/~fogarasi/

 

Research Interests: Mathematical finance, computational finance, neural networks, heuristic optimization, scheduling theory

PhD Topic: OnePageSummary, Thesis Booklet, Dissertation

 LinkedIn, Google Scholar, ResearchGate, Scopus, ORCiD, SSRN, MTMT, ODT

Selected Publications


1. Fogarasi, N., Levendovszky, J. (2012) A simplified approach to parameter estimation and selection of sparse, mean reverting portfolios. Periodica Polytechnica, 56/1, 21-28. DOI

2. Fogarasi, N., Levendovszky, J. (2012) Improved parameter estimation and simple trading algorithm for sparse, mean-reverting portfolios. Annales Univ. Sci. Budapest., Sect. Comp., 37, 121-144.

3. Fogarasi, N., Tornai, K., & Levendovszky, J. (2012) A novel Hopfield neural network approach for minimizing total weighted tardiness of jobs scheduled on identical machines. Acta Univ. Sapientiae, Informatica, 4(1), 48-66. arXiv

4. Tornai, K., Fogarasi, N., & Levendovszky, J. (2013) Improvements to the Hopfield neural network solution to the total weighted tardiness scheduling problem. Periodica Polytechnica, 57/1, 57-64. DOI

5. Fogarasi, N., Levendovszky, J. (2013) Sparse, mean reverting portfolio selection using simulated annealing. Algorithmic Finance, 2/3-4, 197-211. DOI

6. Fogarasi, N. (2014) Polynomial time heuristic optimization methods applied to problems in computational finance. PhD dissertation. DOI

7. Ivanyi, A., Fogarasi, N. (2017) On partial sorting in restricted rounds. Acta Univ. Sapientiae, Informatica, 9(1), 17-34. DOI

8. Ceffer, A., Fogarasi, N., & Levendovszky, J. (2018) Trading by estimating the quantized forward distribution. Applied Economics, 50/59, 6397-6405. DOI

9. Ceffer, A., Levendovszky, J., & Fogarasi, N. (2019) Applying Independent Component Analysis and Predictive Systems for Algorithmic Trading. Computational Economics, 54/1, 281-303. DOI

10. Racz, A., Fogarasi, N. (2022) Trading sparse, mean reverting portfolios using VAR(1) and LSTM prediction. Acta Univ. Sapientiae, Informatica, 13(2), 288-302. DOI

11. Udvarnoki, Z.A., Fath, G., & Fogarasi, N. (2023) Quantum advantage of Monte Carlo option pricing. Journal of Physics Communications, Accepted. DOI

12. Racz, A., Fogarasi, N. (2024) Improved Sparse Mean Reverting Portfolio Selection Using Simulated Annealing and Extreme Learning Machine. Contemporary Economics, 18(3), 336-351. DOI

13. Racz, A., Fogarasi, N. (2024) Efective Convergence Trading of Sparse, Mean Reverting Portfolios. Computational Economics, Accepted. DOI

 

Conference Presentations

 

1. Fogarasi, N., Levendovszky, J. (2012) Combinatorial methods for solving the generalized eigenvalue problem with cardinality constraint for mean reverting trading. 9th Joint Conf. on Math and Comp. Sci. February 2012 Siofok, Hungary

2. Ceffer, A., Levendovszky, J., & Fogarasi, N. (2016) Applying ICA and NARX networks for algorithmic trading. ISCEF May 2016 Paris, France

3. Racz, A., Fogarasi, N. (2024) Selection and LSTM based trading of sparse, optimal portfolios using the VAR(p) model. 2nd Workshop on Intelligent Infocommunication Networks, Systems and Services, 2024 Budapest, Hungary DOI

 

Technical Reports

 

1. Fogarasi, N. (2003) Option pricing primer. Technical Report

2. Fogarasi, N. (2003) Non-gaussian option pricing. Technical Report

3. Fogarasi, N. (2003) Option pricing using neural networks. Technical Report