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Wendy Wijaya and Kuntjoro Adji Sidarto
Portfolio optimization is a mathematical formulation whose objective is to maximize returns while minimizing risks. A great deal of improvement in portfolio optimization models has been made, including the addition of practical constraints. As the number...
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Apichat Chaweewanchon and Rujira Chaysiri
With the advances in time-series prediction, several recent developments in machine learning have shown that integrating prediction methods into portfolio selection is a great opportunity. In this paper, we propose a novel approach to portfolio formation...
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Weiping Wu, Lifen Wu, Ruobing Xue and Shan Pang
This paper revisits the dynamic MV portfolio selection problem with cone constraints in continuous-time. We first reformulate our constrained MV portfolio selection model into a special constrained LQ optimal control model and develop the optimal portfol...
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Mirza Sikalo, Almira Arnaut-Berilo and Azra Zaimovic
In this paper, we compared the models for selecting the optimal portfolio based on different risk measures to identify the periods in which some of the risk measures dominated over others. For decades, the best known return-risk model has been Markowitz?...
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Sabastine Mushori,Delson Chikobvu
Pág. 256 - 264
A dynamic stochastic methodology in optimal portfolio selection that maximizes investment opportunities and minimizes maximum downside risk while taking into account implicit transaction costs incurred in initial trading and in subsequent rebalancing of ...
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Daniel C. Londoño Tamayo, Walter M. Villa-Acevedo and Jesús M. López-Lezama
Optimal reactive power dispatch plays a key role in the safe operation of electric power systems. It consists of the optimal management of the reactive power sources within the system, usually with the aim of reducing system power losses. This paper pres...
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Chunmei Chen, Jianhong (Cecilia) Xia, Brett Smith, Doina Olaru, ... Renlong Han
Pág. 2473 - 2489
It is increasingly recognised that park and ride (PnR) is an efficient travel mode joining private car with public transport system for providing low carbon emissions and better social equity. Departure train stations, as a transfer point of the travel m...
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Minh-Quan Vo, Thu Nguyen, Michael A. Riegler and Hugo L. Hammer
Generative models have recently received a lot of attention. However, a challenge with such models is that it is usually not possible to compute the likelihood function, which makes parameter estimation or training of the models challenging. The most com...
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Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins and R. Christopher Williams
The dynamic modulus of hot mix asphalt (HMA) is a fundamental material property that defines the stress-strain relationship based on viscoelastic principles and is a function of HMA properties, loading rate, and temperature. Because of the large number o...
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Qinpeng Wang and Longfei He
Reducing carbon emissions, including emission abatement outsourcing at the supply-chain level, is becoming a significant but challenging problem in practice. Confronting this challenge, we therefore break down the practice to focus on a low-carbon supply...
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Qinpeng Wang and Longfei He
Reducing carbon emissions, including emission abatement outsourcing at the supply-chain level, is becoming a significant but challenging problem in practice. Confronting this challenge, we therefore break down the practice to focus on a low-carbon supply...
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Werry Febrianti, Kuntjoro Adji Sidarto and Novriana Sumarti
Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MIN...
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Jules Clément Mba, Kofi Agyarko Ababio and Samuel Kwaku Agyei
This paper investigates the robustness of the conventional mean-variance (MV) optimization model by making two adjustments within the MV formulation. First, the portfolio selection based on a behavioral decision-making theory that encapsulates the MV sta...
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Guido Abate, Tommaso Bonafini and Pierpaolo Ferrari
Mean-variance optimization often leads to unreasonable asset allocations. This problem has forced scholars and practitioners alike to introduce portfolio constraints. The scope of our study is to verify which type of constraint is more suitable for achie...
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Kei Nakagawa, Mitsuyoshi Imamura and Kenichi Yoshida
In the field of portfolio management, practitioners are focusing increasingly on risk-based portfolios rather than on mean-variance portfolios. Risk-based portfolios are constructed based solely on covariance matrices, and include methods such as minimum...
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João Frois Caldeira,Marcelo Savino Portugal
Pág. 469 - 504
The traditional models to optimize portfolios based on mean-variance analysis aim to determine the portfolio weights that minimize the variance for a certain return level. The covariance matrices used to optimize are difficult to estimate and ad hoc meth...
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Paulo Coutinho,Benjamin Miranda Tabak
Pág. pp. 243 - 270
We use a mean-variance model to analyze the problem of decentralized portfolio management. We find the solution for the optimal portfolio allocation for a head trader operating in n different markets, which is called the optimal centralized portfolio. Ho...
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Unbreen Arif,Muhammad Tayyab Sohail
Pág. 243 - 255
The development of asset pricing model is attributed to Markowitz (1952) which initiated towards Modern Portfolio Theory (MPT). The whole concept of MPT based on normality of returns assumption but in emerging economies volatility of returns is an import...
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