Least-squares approach to risk parity in portfolio selection

Citations

Cited by:

1. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
2. Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2020. "An optimization–diversification approach to portfolio selection," Journal of Global Optimization, Springer, vol. 76(2), pages 245-265, February.
3. Bernardo K. Pagnoncelli & Domingo Ramírez & Hamed Rahimian & Arturo Cifuentes, 2023. "A Synthetic Data-Plus-Features Driven Approach for Portfolio Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 187-204, June.
4. M. Barkhagen & S. García & J. Gondzio & J. Kalcsics & J. Kroeske & S. Sabanis & A. Staal, 2023. "Optimising portfolio diversification and dimensionality," Journal of Global Optimization, Springer, vol. 85(1), pages 185-234, January.
5. Silvana M. Pesenti & Sebastian Jaimungal & Yuri F. Saporito & Rodrigo S. Targino, 2023. "Risk Budgeting Allocation for Dynamic Risk Measures," Papers 2305.11319, arXiv.org, revised Oct 2024.
6. Giorgio Costa & Roy H. Kwon, 2021. "Data-driven distributionally robust risk parity portfolio optimization," Papers 2110.06464, arXiv.org.
7. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
   • Alexandre Rubesam, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Post-Print hal-03707365, HAL.
8. M. D. Braga & C. R. Nava & M. G. Zoia, 2023. "Kurtosis-based risk parity: methodology and portfolio effects," Quantitative Finance, Taylor & Francis Journals, vol. 23(3), pages 453-469, March.
   • Braga, Maria Debora & Nava, Consuelo R. & Zoia, Maria Grazia, 2022. "Kurtosis-Based Risk Parity: Methodology and Portfolio Effects," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202208, University of Turin.
9. A. Sinem Uysal & Xiaoyue Li & John M. Mulvey, 2024. "End-to-end risk budgeting portfolio optimization with neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 397-426, August.
10. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
11. da Costa, B. Freitas Paulo & Pesenti, Silvana M. & Targino, Rodrigo S., 2023. "Risk budgeting portfolios from simulations," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1040-1056.
    • Bernardo Freitas Paulo da Costa & Silvana M. Pesenti & Rodrigo S. Targino, 2023. "Risk Budgeting Portfolios from Simulations," Papers 2302.01196, arXiv.org.
12. Adil Rengim Cetingoz & Olivier Gu'eant, 2023. "Asset and Factor Risk Budgeting: A Balanced Approach," Papers 2312.11132, arXiv.org, revised May 2024.
13. Eduardo Bered Fernandes Vieira & Tiago Pascoal Filomena, 2020. "Liquidity Constraints for Portfolio Selection Based on Financial Volume," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 1055-1077, December.
14. Giorgio Costa & Roy H. Kwon, 2020. "Generalized risk parity portfolio optimization: an ADMM approach," Journal of Global Optimization, Springer, vol. 78(1), pages 207-238, September.
15. Li, Xiaoyue & Uysal, A. Sinem & Mulvey, John M., 2022. "Multi-period portfolio optimization using model predictive control with mean-variance and risk parity frameworks," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1158-1176.
16. Giorgio Costa & Roy Kwon, 2020. "A robust framework for risk parity portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 447-466, September.
17. Jaehyuk Choi & Rong Chen, 2022. "Improved iterative methods for solving risk parity portfolio," Papers 2203.00148, arXiv.org.
18. Ayse Sinem Uysal & Xiaoyue Li & John M. Mulvey, 2021. "End-to-End Risk Budgeting Portfolio Optimization with Neural Networks," Papers 2107.04636, arXiv.org.
19. Ravi Kashyap, 2024. "The Blockchain Risk Parity Line: Moving From The Efficient Frontier To The Final Frontier Of Investments," Papers 2407.09536, arXiv.org.
20. M. Bayat & F. Hooshmand & S. A. MirHassani, 2024. "Scenario-based stochastic model and efficient cross-entropy algorithm for the risk-budgeting problem," Annals of Operations Research, Springer, vol. 341(2), pages 731-755, October.
21. Miquel Noguer i Alonso & Sonam Srivastava, 2020. "Deep Reinforcement Learning for Asset Allocation in US Equities," Papers 2010.04404, arXiv.org.
22. Anis, Hassan T. & Kwon, Roy H., 2022. "Cardinality-constrained risk parity portfolios," European Journal of Operational Research, Elsevier, vol. 302(1), pages 392-402.
23. Erdinc Akyildirim & Matteo Gambara & Josef Teichmann & Syang Zhou, 2023. "Randomized Signature Methods in Optimal Portfolio Selection," Papers 2312.16448, arXiv.org.
24. Jean-Charles Richard & Thierry Roncalli, 2019. "Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles," Papers 1902.05710, arXiv.org.
25. Wonbin Ahn & Hee Soo Lee & Hosun Ryou & Kyong Joo Oh, 2020. "Asset Allocation Model for a Robo-Advisor Using the Financial Market Instability Index and Genetic Algorithms," Sustainability, MDPI, vol. 12(3), pages 1-15, January.
26. Francesco Cesarone & Fabio Tardella, 2017. "Equal Risk Bounding is better than Risk Parity for portfolio selection," Journal of Global Optimization, Springer, vol. 68(2), pages 439-461, June.
27. Francesco Cesarone & Rosella Giacometti & Manuel Luis Martino & Fabio Tardella, 2023. "A return-diversification approach to portfolio selection," Papers 2312.09707, arXiv.org.