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 A Mean-Variance Portfolio Selection Model with Interval-Valued Possibility Measures

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yunyun Sui ◽  
Jiangshan Hu ◽  
Fang Ma
Keyword(s):  
Portfolio Selection ◽  
Return Rate ◽  
Selection Model ◽  
Expected Return ◽  
Interval Numbers ◽  
Numerical Example ◽  
Mean Variance Portfolio ◽  
Portfolio Selection Model ◽  
Mean Variance ◽  
Interval Valued

In recent years, fuzzy set theory and possibility theory have been widely used to deal with an uncertain decision environment characterized by vagueness and ambiguity in the financial market. Considering that the expected return rate of investors may not be a fixed real number but can be an interval number, this paper establishes an interval-valued possibilistic mean-variance portfolio selection model. In this model, the return rate of assets is regarded as a fuzzy number, and the expected return rate of assets is measured by the interval-valued possibilistic mean of fuzzy numbers. Therefore, the possibilistic portfolio selection model is transformed into an interval-valued optimization model. The optimal solution of the model is obtained by using the order relations of interval numbers. Finally, a numerical example is given. Through the numerical example, it is shown that, when compared with the traditional possibilistic model, the proposed model has more constraints and can better reflect investor psychology. It is an extension of the traditional possibilistic model and offers greater flexibility in reflecting investor expectations.

scholarly journals Unit trusts and portfolio selection on the Johannesburg Stock Exchange

1982 ◽  
Vol 13 (4) ◽  
pp. 169-175
Author(s):  
K. J. Carter ◽  
J. F. Affleck-Graves ◽  
A. H. Money
Keyword(s):  
Standard Deviation ◽  
Portfolio Selection ◽  
Stock Exchange ◽  
Efficient Frontier ◽  
Expected Return ◽  
Earnings Volatility ◽  
Johannesburg Stock Exchange ◽  
Market Index ◽  
Efficient Portfolios ◽  
Unit Trust

The application of the standard techniques of portfolio selection on the 34 sectors comprising the JSE All Share index is undertaken for the three equal non-overlapping five-year periods between February 1965 and January 1980. Efficient portfolios in each period which carry the same risk as the market index are seen to outperform the market substantially. Portfolios chosen at random to span the efficient frontier in each period reveal the consistent inefficiency of 10 sectors over the 15-year period. Three of these sectors, namely Mining Holding, Mining Houses and Industrial Holding are shown to be favoured in the Association of Unit Trusts portfolio relative to these sectors' proportion of the market. On the presumption that unit trust managers attempt to act efficiently, holding these sectors is only justified if the measure of risk used in the portfolio selection algorithm, namely standard deviation of expected return, is less appropriate than other measures of risk such as earnings volatility. If standard deviation of expected return is a more appropriate measure of risk in the selection of efficient portfolios, it must be concluded that the large sophisticated investors managing the unit trusts act inefficiently.

scholarly journals A Reference Point Approach to Bi-Objective Dynamic Portfolio Optimization

2009 ◽  
Vol 3 (2) ◽  
pp. 73-85 ◽  
Author(s):  
Bartosz Sawik
Keyword(s):  
Portfolio Selection ◽  
Reference Point ◽  
Stock Exchange ◽  
Integer Program ◽  
Selection Problem ◽  
Mixed Integer ◽  
Mixed Integer Program ◽  
Expected Return ◽  
Portfolio Selection Problem ◽  
Dynamic Portfolio Optimization

The portfolio selection problem presented in this paper is formulated as a biobjective mixed integer program. The portfolio selection problem considered is based on a dynamic model of investment, in which the investor buys and sells securities in successive investment periods. The problem objective is to dynamically allocate the wealth on different securities to optimize by reference point method the portfolio expected return and the probability that the return is not less than a required level. In computational experiments the dataset of daily quotations from the Warsaw Stock Exchange were used.

scholarly journals A Convex-Risk-Measure Based Model and Genetic Algorithm for Portfolio Selection

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Weijia Wang ◽  
Jie Hu ◽  
Ning Dong
Keyword(s):  
Genetic Algorithm ◽  
Portfolio Optimization ◽  
Portfolio Selection ◽  
Optimization Model ◽  
Stock Exchange ◽  
Risk Measure ◽  
Convex Risk Measure ◽  
Proposed Model ◽  
Portfolio Optimization Model ◽  
Set Up

A convex risk measure called weighted expected shortfall (briefly denoted as WES (Chen and Yang, 2011)) is adopted as the risk measure. This measure can reflect the reasonable risk in the stock markets. Then a portfolio optimization model based on this risk measure is set up. Furthermore, a genetic algorithm is proposed for this portfolio optimization model. At last, simulations are made on randomly chosen ten stocks for 60 days (during January 2, 2014 to April 2, 2014) from Wind database (CFD) in Shenzhen Stock Exchange, and the results indicate that the proposed model is reasonable and the proposed algorithm is effective.

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.

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.

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.

scholarly journals Portfolio Optimization Based on Clustering in Indonesia Stock Exchange: A Case Study of The Index LQ45

2021 ◽  
Vol 1 (1) ◽  
pp. 59-70
Author(s):  
Bakti Siregar ◽  
F. Anthon Pangruruk
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Portfolio Optimization ◽  
Stock Exchange ◽  
Minimum Variance ◽  
Clustering Method ◽  
Expected Return

In general portfolio, optimization is a technique for selecting the proportion of assets to make a better portfolio by maximizing the expected return while also minimizing the risk. In this research, the k-means clustering method is used to classify stocks are listed on the LQ45 Index and select stocks whose has prices tend to be increased. Then the Markowitz approach is used to analyze the performance of optimization portfolio models that have a minimum variance in expected return and risk. After understanding the performance of this portfolio optimization, future works will be able to apply this model in cloud computing or artificial intelligence. In addition, investors will develop a better view of the latest performance of the stocks are listed in the LQ45 index and support them decide which stocks should be included in their portfolios, thus prevent wrong decisions.

scholarly journals Multi-Objective Optimization Models to Design a Responsive Built Environment: A Synthetic Review

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 486
Author(s):  
Mattia Manni ◽  
Andrea Nicolini
Keyword(s):  
Energy Efficiency ◽  
Selection Process ◽  
Spatial Scales ◽  
Scientific Journal ◽  
Research Field ◽  
Building Envelope ◽  
Optimization Models ◽  
Multi Objective Optimization ◽  
Simulation And Optimization ◽  
Multi Objective

A synthetic review of the application of multi-objective optimization models to the design of climate-responsive buildings and neighbourhoods is carried out. The review focused on the software utilized during both simulation and optimization stages, as well as on the objective functions and the design variables. The hereby work aims at identifying knowledge gaps and future trends in the research field of automation in the design of buildings. Around 140 scientific journal articles, published between 2014 and 2021, were selected from Scopus and Web of Science databases. A three-step selection process was applied to refine the search terms and to discard works investigating mechanical, structural, and seismic topics. Meta-analysis of the results highlighted that multi-objective optimization models are widely exploited for (i) enhancing building’s energy efficiency, (ii) improving thermal and (iii) visual comfort, minimizing (iv) life-cycle costs, and (v) emissions. Reviewed workflows demonstrated to be suitable for exploring different design alternatives for building envelope, systems layout, and occupancy patterns. Nonetheless, there are still some aspects that need to be further enhanced to fully enable their potential such as the ability to operate at multiple temporal and spatial scales and the possibility of exploring strategies based on sector coupling to improve a building’s energy efficiency.

Pengaruh Faktor Fundamental, Risiko Sistematis Dan Ekonomi Makro Terhadap Return Saham Syariah Yang Tergabung Di Jakarta Islamic Index (JII) Pada Periode 2010 – 2014

2017 ◽  
Vol 24 (1) ◽  
pp. 54-70
Author(s):  
Hasanah Setyowati ◽  
Riyanti Ningsih
Keyword(s):  
Exchange Rate ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Secondary Data ◽  
Analysis Model ◽  
Macroeconomic Factors ◽  
Return On Equity ◽  
Equity Ratio ◽  
Regression Techniques ◽  
The Exchange Rate

This study aimed to obtain empirical evidence on the influence of fundamental factors, systematic risk and macroeconomics on the returns Islamic stock of companies incorporated in the Jakarta Islamic Index in 2010-2014. The variables used were the fundamental factors that are proxied by Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER); Systematic risk is proxied by Beta Shares; macroeconomic factors is proxied by the inflation rate and the exchange rate. The samples of this study are the enterprises incorporated in Jakarta Islamic Index (JII) at the Indonesian Stock Exchange. The sampling method was using purposive sampling. There were 12 samples of Islamic stocks that meet the criteria to be used as samples. The analysis model used is multiple linear regression techniques and the type of data used is secondary data. The study found that all variables, which are Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER), Beta stock, inflation and the exchange rate do not significantly affect the return of sharia stock either simultaneously or partially.

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