scholarly journals Optimizing Stock Portfolio with Markowitz Method as a Reference for Investment Community Decisions

2021 ◽  
Vol 2 (2) ◽  
pp. 71-76
Author(s):  
Viona Prisyella Balqis ◽  
Subiyanto Subiyanto ◽  
Sudradjat Supian
Keyword(s):  
Portfolio Optimization ◽  
Multi Objective Optimization ◽  
Expected Return ◽  
Multi Objective ◽  
Portfolio Returns ◽  
Maximum Profit ◽  
The Right ◽  
Stock Portfolio

An investor who wants to invest by avoiding risk makes investors tend to choose investments with the same expected return and the smallest or lowest possible risk. Therefore, investors expect to be able to maximize profits and minimize risk at the same time in investing. In a stock portfolio, it can be done by investing the funds owned by investors into several stocks so that it can reduce the risk of losses that will occur simultaneously. In choosing the right company to invest in with consideration of expected return and risk, a multi-objective optimization with multivariate objects can be used so that it can meet the expectations of investors. The portfolio concept introduced by Markowitz is a portfolio optimization intended for standard investors because it only refers to one explanation of portfolio returns. The Markowitz method can produce an optimal stock portfolio by considering the expected return and risk simultaneously so that the maximum profit can be obtained without eliminating the existing risk.

scholarly journals A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

scholarly journals Sistem Bantu untuk Pengrajin dalam Menentukan Kayu Terbaik Terbaik untuk Bahan Gitar dengan Menggunakan Matode Moora

2021 ◽  
Vol 8 (6) ◽  
pp. 1177
Author(s):  
Tundo Tundo ◽  
Wisnu Dwi Nugroho
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
A Value ◽  
Wood Grain ◽  
The Right ◽  
Moora Method

<p>Penelitian ini bertujuan untuk membantu pengrajin kayu di Dongkelan, Krapyak, Yogyakarta dalam menentukan kayu terbaik untuk dijadikan sebagai bahan gitar, karena sering terjadi keluhan dari para pembeli bahwa bahan yang dijadikan bahan gitar cepat lapuk dan kusam dari segi warnah. Berdasarkan permasalahan tersebut, dicari suatu solusi dengan menggunakan metode <em>Decision Support System</em> <em>Multi Objective Optimization on the basic of Ratio Analysis</em><em> </em>(MOORA) serta dibantu oleh pakar dalam menentukan kriteria yang tepat berkaitan penentuan kayu terbaik yang digunakan dalam pembuatan bahan gitar, setelah berdiskusi panjang ditemukan hasil kriteria yang tepat berdasarkan permasalahan, berupa kriteria kekuatan kayu, serat kayu, tekstur, dan berat kayu. Semua kriteria tersebut, kemudian diproses dengan menggunakan metode MOORA, dengan data yang digunakan sebanyak 29 jenis data kayu, yang diperoleh dari pengrajin yang ada di wilayah tersebut. Setelah diproses, diperoleh hasil 3 kayu terbaik yang layak untuk digunakan sebagai bahan pembuatan gitar secara berurutan dalah kayu Bubinga dengan nilai 18,36785, kayu Bocote dengan nilai 17,33385, dan kayu Eboni dengan nilai 17,33385   dari beberapa pilihan alternatif  kayu yang ada. Membuktikan hasil dari metode MOORA<em>, </em>maka dilakukan responden secara langsung dengan memberikan hasil metode kepada pakar pembuat gitar. Dari 15 pakar pembuat gitar, 13 mengatakan setuju dengan peringkat 3 terbesar, dan 2 mengatakan kurang setuju. Sehingga ditemukan tingkat akurasi berdasarkan penilaian pakar sebesar 86,67 %.</p><p> </p><p><strong>Abstract</strong></p><div><p><em>This study aims to assist wood craftsmen in Dongkelan, Krapyak, Yogyakarta in determining the best wood to be used as guitar material, because there are frequent complaints from buyers that the material used for guitar is rotten quickly and is dull in terms of color. Based on these problems, a solution was sought using the Multi Objective Optimization on the basic of Ratio Analysis (MOORA) Decision Support System method and assisted by experts in determining the right criteria related to determining the best wood used in making guitar materials, after a long discussion found the results. the right criteria based on the problem, in the form of wood strength criteria, wood grain, texture, and wood weight. All of these criteria are then processed using the MOORA method, with the data used as much as 29 types of wood data, which are obtained from craftsmen in the area. After processing, the 3 best woods that are suitable for use as a guitar-making material are Bubinga wood with a value of 18.36785, Bocote wood with a value of 17.333385, and Eboni wood with a value of 17.333385 from several alternative wood choices. . Proving the results of the MOORA method, the respondents directly gave the results of the method to guitar-making experts. Of the 15 expert guitar makers, 13 said they agreed with the third largest ranking, and 2 said they disagreed. So that it found the level of accuracy based on expert judgment of 86.67%. </em></p></div><p><strong><br /></strong></p>

scholarly journals Pemilihan Marketplace Di Masa Pandemi Covid-19 Menggunakan Metode MOORA

2021 ◽  
Vol 6 (2) ◽  
pp. 149
Author(s):  
Sultan Chaeruddin ◽  
Icih Sukarsih ◽  
Respitawulan Respitawulan
Keyword(s):  
Decision Making ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
New Normal ◽  
Multi Objective ◽  
Multi Attribute Decision Making ◽  
The Right ◽  
Almost All ◽  
Moora Method

AbstrakPandemi COVID-19 telah melanda hampir di seluruh dunia. Pandemi ini juga merupakan sebuah masa dimana masyarakat dituntut melaksanakan kebiasaan baru atau dikenal dengan New Normal. Kebiasaan baru ini juga mempengaruhi cara masyarakat dalam berbelanja khususnya berbelanja di marketplace. Dengan memilih marketplace yang tepat maka masyarakat atau konsumen dapat memenuhi kebutuhan seperti produk kesehatan dan rumah tangga yang paling dicari di masa pandemi. Metode Multi Objective Optimization on The Basis of Ratio Analysis atau MOORA adalah salah satu metode dari Multi Attribute Decision Making. Metode MOORA dapat digunakan untuk menentukan rekomendasi marketplace di masa pandemi COVID-19. Hasil yang diharapkan adalah diperoleh alternatif terbaik berdasarkan penilaian masyarakat dan perhitungan menggunakan metode MOORA sehingga dapat terlihat pula perilaku konsumen di masa pandemi dan menjadi masukkan bagi perusahaan marketplace di masa yang akan datang.Kata kunci - Pandemi COVID-19; Marketplace; MOORAThe COVID-19 pandemic has hit almost all over the world. This pandemic is also a period when people are required to carry out new habits, known as the New Normal. This new habit also affects the way people shop, especially shopping in the marketplace. By choosing the right marketplace, the community or consumers can meet needs such as health and household products that are most sought after during a pandemic. The Multi Objective Optimization method on The Basis of Ratio Analysis or MOORA is one of the methods of Multi Attribute Decision Making. The MOORA method can be used to determine marketplace recommendations during the COVID-19 pandemic. The expected result is that the best alternative is obtained based on community assessment and calculations using the MOORA method so that consumer behavior can also be seen during the pandemic and become input for marketplace companies in the future.

scholarly journals IMPLEMENTASI METODE MOORA (MULTI OBJECTIVE OPTIMIZATION ON THE BASIC OF RATIO ANALYSIS) UNTUK REKOMENDASI PEMILIHAN TYPE SEPEDA MOTOR TERBAIK (Studi Kasus : CV. Satu Hati Perkasa)

2020 ◽  
Vol 3 (1) ◽  
pp. 101-113
Author(s):  
Nur Ha Yati
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Transportation Equipment ◽  
A Value ◽  
The Right ◽  
Moora Method

Motorcycle is one of the means of transportation that is loved by the community because it has a small size, fast and the price is not too expensive compared to other transportation equipment. Now many types of motorcycles complete with advantages and advantages. This of course will make it difficult for consumers to make the right choice, according to the desired criteria. To make it easier for buyers to choose the type of motorcycle that suits their needs, a decision support system is designed to recommend the appropriate motorcycle type.This system is built with accurate calculations using the MOORA method (Multi Objective Optimization on The Basic of Ratio Analysis) so that the accuracy of calculations is more guaranteed that is applied using PHP MySQL software. With this system, customers / buyers have no difficulty choosing the type of motorcycle that suits their needs and finances so that it will create a convenient and fast buying and selling process.From the 17 data, it can be seen that the results manually on the recommendation of a motorcycle type can be seen that A_3 is the highest alternative with a value of 27.336773. In other words the A_3 type motorcycle Vario 150 is the best motorcycle.

scholarly journals Risk-Return Analysis on Optimum Portfolio Selection of Islamic Stocks

2021 ◽  
Vol 9 (1) ◽  
pp. 65
Author(s):  
Siti Amaroh ◽  
Chanif Nasichah
Keyword(s):  
Stock Returns ◽  
Portfolio Selection ◽  
Excess Return ◽  
Expected Return ◽  
Portfolio Returns ◽  
Risk Return ◽  
Closing Price ◽  
Stock Portfolio ◽  
Portfolio Return ◽  
Selection Of

<p><em>This study aims to determine the optimum portfolio category and analyze the risk-return on a formed portfolio. Data was taken from eighteen listed companies indexed by Jakarta Islamic Index during 2015-2018. Stock returns are calculated based on the closing price at the end of each month in the period. Sharia Certificate of Bank Indonesia is a proxy of risk-free return, while the market return is measured by the value of the Jakarta Islamic Index. Stocks are sorted by the value of excess return to beta (ERB) from highest to lowest, and to obtain optimal stock portfolio candidates, and the ERB value must be compared with the cut-off rate value. Seven issuers qualify for forming the optimum portfolio of shares. The results show that the optimum portfolio return is greater than the expected return and the expected risk-free return. When compared between individual stock returns and portfolio stock returns, some individual stocks provide higher returns than portfolio returns. However, the risk of individual shares was also higher than the risk of the portfolio. This finding proves that risk can be reduced optimally in Islamic stocks selection by forming an optimum portfolio.</em></p>

CLUSTERING STOCK DATA FOR MULTI-OBJECTIVE PORTFOLIO OPTIMIZATION

2014 ◽  
Vol 13 (02) ◽  
pp. 1450011 ◽  
Author(s):  
NGUYEN CONG LONG ◽  
NAWAPORN WISITPONGPHAN ◽  
PHAYUNG MEESAD ◽  
HERWIG UNGER
Keyword(s):  
Portfolio Optimization ◽  
Portfolio Selection ◽  
Stock Exchange ◽  
Selection Process ◽  
Optimal Number ◽  
Research Field ◽  
Return Rate ◽  
Analysis Model ◽  
Expected Return ◽  
Multi Objective

Portfolio selection is a vital research field in modern finance. Multi-objective portfolio optimization problem is the portfolio selection process that results in the highest expected return rate and the lowest identified risk among the various financial assets. This paper proposes a model that can efficiently suggest a portfolio that is worth investing. First, a cluster analysis model is introduced in order to categorize a huge amount of stock data into several groups based on their associated return rate and the risk. Several validity indexes are used to select the optimal number of clusters/stocks to be included in the portfolio. Finally, the multi-objective genetic algorithm is used to build portfolio optimization with highest return rate and lowest risk. The proposed model is tested on the data obtained from the Stock Exchange of Thailand.

scholarly journals Portfolio Optimization: Some Aspects of Modeling and Computing

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Thanh Nguyen
Keyword(s):  
Portfolio Optimization ◽  
Optimization Problems ◽  
Optimization Method ◽  
Expected Return ◽  
Multi Objective ◽  
Computational Optimization ◽  
Multi Objective Programming ◽  
Computational Aspects ◽  
Mathematical Programming Problems ◽  
Portfolio Return

The paper focuses on computational aspects of portfolio optimization (PO) problems. The objectives of such problems may include: expected return, standard deviation and variation coefficient of the portfolio return rate. PO problems can be formulated as mathematical programming problems in crisp, stochastic or fuzzy environments. To compute optimal solutions of such single- and multi-objective programming problems, the paper proposes the use of a computational optimization method such as RST2ANU method, which can be applied for non-convex programming problems. Especially, an updated version of the interactive fuzzy utility method, named UIFUM, is proposed to deal with portfolio multi-objective optimization problems.

Conditional Value-at-Risk-Based Portfolio Optimization

2019 ◽  
pp. 82-108
Author(s):  
Jhuma Ray ◽  
Siddhartha Bhattacharyya ◽  
N. Bhupendro Singh
Keyword(s):  
At Risk ◽  
Portfolio Optimization ◽  
Value At Risk ◽  
Risk Measures ◽  
Real Life ◽  
Conditional Value At Risk ◽  
Market Theory ◽  
Market Conditions ◽  
Expected Return ◽  
Multi Objective

Over the past few decades, an extensive research on the multi-objective decision making and combinatorial optimization of real world's financial transactions has taken place. The modern capital market theory problem of portfolio optimization stands to be a multi-objective problem aiming at the maximization of the expected return of the portfolio in turn minimizing portfolio risk. The conditional value-at-risk (CVaR) is a widely used measure for determining the risk measures of a portfolio in volatile market conditions. A heuristic approach to portfolio optimization problem using ant colony optimization (ACO) technique centering on optimizing the conditional value-at-risk (CVaR) measure in different market conditions based on several objectives and constraints has been reported in this paper. The proposed ACO approach is proved to be reliable on a collection of several real-life financial instruments as compared to its value-at-risk (VaR) counterpart. The results obtained show encouraging avenues in determining optimal portfolio returns.

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