Zobrazeno 1 - 10
of 1 473
pro vyhledávání: '"Portfolio Allocation"'
Autor:
Pedini, Luca, Severini, Sabrina
Publikováno v:
Studies in Economics and Finance, 2024, Vol. 42, Issue 1, pp. 1-30.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SEF-05-2023-0255
Publikováno v:
China Finance Review International, 2024, Vol. 14, Issue 4, pp. 666-693.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CFRI-05-2024-0229
Autor:
Lee, Don S., author
Publikováno v:
The President's Dilemma in Asia, 2024, ill.
Externí odkaz:
https://doi.org/10.1093/oso/9780192870186.003.0006
Autor:
Pareek, Parikshit a, 1, Sampath, L.P. Mohasha Isuru b, 1, Singh, Anshuman c, 1, Goel, Lalit c, Gooi, Hoay Beng c, Nguyen, Hung Dinh c, ⁎
Publikováno v:
In Energy 30 December 2024 313
Publikováno v:
Journal of Finance and Data Science, Vol 9, Iss , Pp 100097- (2023)
This paper introduces the minCluster portfolio, which is a portfolio optimization method combining the optimization of downside risk measures, hierarchical clustering and cellwise robustness. Using cellwise robust association measures, the minCluster
Externí odkaz:
https://doaj.org/article/40431888d17046918e6ecc30992e1f18
Autor:
Moćić, Branimir D.
Publikováno v:
Management: Journal of Sustainable Business and Management Solutions in Emerging Economies. 28(1):65-78
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1126758
Autor:
Namyeong Lee, Jun Moon
Publikováno v:
IEEE Access, Vol 11, Pp 112577-112589 (2023)
Recently, with the increasing interest in investments in financial stock markets, several methods have been proposed to automatically trade stocks and/or predict future stock prices using machine learning techniques, such as reinforcement learning (R
Externí odkaz:
https://doaj.org/article/8d8658e82d124958bceadd119b268dab
Autor:
Luis Lorenzo, Javier Arroyo
Publikováno v:
Financial Innovation, Vol 9, Iss 1, Pp 1-40 (2023)
Abstract Mean-variance portfolio optimization models are sensitive to uncertainty in risk-return estimates, which may result in poor out-of-sample performance. In particular, the estimates may suffer when the number of assets considered is high and t
Externí odkaz:
https://doaj.org/article/e5733c1cad154e518ee7058ede3bbcc5
Autor:
Michael Pinelis, David Ruppert
Publikováno v:
Journal of Finance and Data Science, Vol 8, Iss , Pp 35-54 (2022)
We find economically and statistically significant gains when using machine learning for portfolio allocation between the market index and risk-free asset. Optimal portfolio rules for time-varying expected returns and volatility are implemented with
Externí odkaz:
https://doaj.org/article/ce89550663b5468daaf99796264690c2
Autor:
Jingying Yang
Publikováno v:
Mathematics, Vol 12, Iss 7, p 1045 (2024)
This study addresses the challenge of estimating high-dimensional covariance matrices in financial markets, where traditional sparsity assumptions often fail due to the interdependence of stock returns across sectors. We present an innovative element
Externí odkaz:
https://doaj.org/article/1f227234d2f941b7a32d85c7694e7822