scholarly journals Portfolio Construction of Energy-Related Assets

2021 ◽  
Vol 275 ◽  
pp. 01001
Author(s):  
Yifei Feng ◽  
Kexin Li ◽  
Yingxuan Wang
Keyword(s):  
Monte Carlo ◽  
Financial Markets ◽  
Electric Power ◽  
Efficient Frontier ◽  
Minimum Variance ◽  
Portfolio Allocation ◽  
Ratio Method ◽  
Portfolio Construction ◽  
Minimum Variance Portfolio ◽  
Sharp Ratio

Portfolio construction is one of the most fatal issues of modern finance, which can effectively gain returns or reduce risks. This study constructs portfolios in energy-related assets. Specifically, the Monte Carlo simulations are carried out for a hundred thousand times in order to discover the efficient frontier and find the minimum variance and the maximum sharp ratio portfolio. According to the simulations, the American Electric Power possesses the largest share in minimum variance portfolio, while NextEra Energy for sharp ratio method. The results may benefit certain investor in financial markets and shed lights to focus more on portfolio allocation during constructing.

scholarly journals Portfolio Construction for Pharmaceutical Industry

2021 ◽  
Vol 275 ◽  
pp. 03032
Author(s):  
Xiqing Sun ◽  
Baichuan Li ◽  
Huatian Pang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Pharmaceutical Industry ◽  
Efficient Frontier ◽  
Minimum Variance ◽  
Sharpe Ratio ◽  
Portfolio Construction ◽  
Human Beings ◽  
The Monte Carlo Method ◽  
Weighted Model

In finance area, portfolio construction is one of the most vital questions since the primary work of modern finance and attract numerous studies. In this paper, we focused on this issue in pharmaceutical industry since the industry is crucial for human beings. We adopted several methods for portfolio construction, like Equal Weighted Model, Monte Carlo simulation, and maximize Sharpe ratio etc. Specifically, five assets are selected. Then based on the Monte Carlo method, we constructed two optimized portfolios in the framework of the efficient frontier, i.e., portfolios with minimum variance and maximum Sharpe ratio. By analyzing the two portfolios, we found that the NVS accounts for the largest proportions in the optimized portfolio. The results in this paper may shed lights for certain investors who invest in pharmaceutical industry.

Large-scale minimum variance portfolio allocation using double regularization

2020 ◽  
Vol 116 ◽  
pp. 103939 ◽  
Author(s):  
Zhicun Bian ◽  
Yin Liao ◽  
Michael O’Neill ◽  
Jing Shi ◽  
Xueyong Zhang
Keyword(s):  
Large Scale ◽  
Minimum Variance ◽  
Portfolio Allocation ◽  
Double Regularization ◽  
Minimum Variance Portfolio

scholarly journals Application of Markowitz Model on Romanian Stock Market

2017 ◽  
Vol 8 (1) ◽  
pp. 97-103
Author(s):  
Ioana Coralia Zavera
Keyword(s):  
Performance Evaluation ◽  
Stock Market ◽  
Mathematical Models ◽  
Efficient Frontier ◽  
Minimum Variance ◽  
Financial Instruments ◽  
Markowitz Model ◽  
Trading Activities ◽  
Minimum Variance Portfolio ◽  
Over Time

Abstract Performance evaluation of financial instruments has become a concern for more and more economists, while security trading activities have developed over time. “Modern portfolio theory” comprises statistical and mathematical models which describe various ways in order to evaluate and especially analyse profitability and risk of these portfolios. This article offers an application of this type of model on Romanian stock market, the Markowitz model, by focusing on portfolios comprising three securities, and determining the efficient frontier and the minimum variance portfolio.

scholarly journals Índices Valor-Coppead, Carteiras de Ponderação Igualitária e de Mínima Variância

2016 ◽  
Vol 14 (1) ◽  
pp. 45
Author(s):  
Ricardo Pereira Câmara Leal ◽  
Carlos Heitor Campani
Keyword(s):  
Literature Review ◽  
Selection Criterion ◽  
Efficient Frontier ◽  
Minimum Variance ◽  
Sharpe Ratio ◽  
Stock Index ◽  
Stock Selection ◽  
Stock Indices ◽  
Minimum Variance Portfolio ◽  
Complex Methods

This article presents a literature review that justified the creation of the equally weighed and minimum variance Valor-Coppead stock indices and offers details about its calculation. There was no Brazilian stock index with these simple portfolio formation rules attainable by the non-sophisticated investor. An index that uses the minimum variance portfolio in the efficient frontier, with limits on the weights, offers an optimized portfolio less affected by errors in estimates. Equally weighed portfolios with up to 20 stocks displayed a performance superior to that of the majority of Brazilian stock funds and comparable to that of the minimum variance portfolio with constrained weights, but portfolios optimized with more complex methods, may outclass equally weighed portfolios. The previous three or four months Sharpe ratio stock selection criterion is relevant. The literature reviewed supported that the Valor-Coppead indices may become relevant benchmarks for non-sophisticated investors.

Properties of the beta coefficient of the global minimum variance portfolio

2020 ◽  
Vol 8 (1) ◽  
pp. 11-21
Author(s):  
S. M. Yaroshko ◽  
◽  
M. V. Zabolotskyy ◽  
T. M. Zabolotskyy ◽  
◽  
...  
Keyword(s):  
Confidence Interval ◽  
Asymptotic Distribution ◽  
Global Minimum ◽  
Asset Returns ◽  
Minimum Variance ◽  
Benchmark Portfolio ◽  
Beta Coefficient ◽  
Minimum Variance Portfolio ◽  
Global Minimum Variance Portfolio ◽  
Daily Returns

The paper is devoted to the investigation of statistical properties of the sample estimator of the beta coefficient in the case when the weights of benchmark portfolio are constant and for the target portfolio, the global minimum variance portfolio is taken. We provide the asymptotic distribution of the sample estimator of the beta coefficient assuming that the asset returns are multivariate normally distributed. Based on the asymptotic distribution we construct the confidence interval for the beta coefficient. We use the daily returns on the assets included in the DAX index for the period from 01.01.2018 to 30.09.2019 to compare empirical and asymptotic means, variances and densities of the standardized estimator for the beta coefficient. We obtain that the bias of the sample estimator converges to zero very slowly for a large number of assets in the portfolio. We present the adjusted estimator of the beta coefficient for which convergence of the empirical variances to the asymptotic ones is not significantly slower than for a sample estimator but the bias of the adjusted estimator is significantly smaller.

scholarly journals COSMIC COVARIANCE AND THE LOW QUADRUPOLE ANISOTROPY IN THE WMAP DATA

2008 ◽  
Vol 23 (17n20) ◽  
pp. 1489-1497 ◽  
Author(s):  
LUNG-YIH CHIANG ◽  
PAVEL D. NASELSKY ◽  
PETER COLES
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
A Priori ◽  
Gaussian Random Field ◽  
Minimum Variance ◽  
Microwave Background ◽  
Data Release ◽  
Intrinsic Correlation ◽  
Wmap Data ◽  
Cmb Temperature

Low quadrupole power in the cosmic microwave background (CMB) temperature anisotropies has been a puzzle since WMAP data release. In this talk I will demonstrate that the minimum variance optimization (MVO), a methodology used by many authors including the WMAP science team to separate the CMB from foreground contamination, serves not only to extract the CMB, but to subtract the “cosmic covariance”, an intrinsic correlation between the CMB and the foregrounds. Such subtraction induces low variance in the signal via MVO, which in turn propagates into the multipoles, causing a quadrupole deficit with more than 90% CL. As we do not know the CMB and the foregrounds a priori, and their correlation is subtracted by the MVO in any case, there is therefore an unknown error in the quadrupole power even before the cosmic variance interpretation. We combine the MVO and Monte Carlo simulations, assuming CMB is a Gaussian random field, and the estimated quadrupole power falls in [308.13, 401.97] μ K 2 (at 1 − σ level).

Minimum Variance Portfolio Composition

2010 ◽  
Author(s):  
Roger Clarke ◽  
Harindra de Silva ◽  
Steven Thorley
Keyword(s):  
Minimum Variance ◽  
Portfolio Composition ◽  
Minimum Variance Portfolio
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