scholarly journals The Errors-in-Variable Model in the Optimal Portfolio Construction

2007 ◽  
Vol 1 (2) ◽  
pp. 49-57 ◽  
Author(s):  
Anna Czapkiewicz ◽  
Małgorzata Machowska
Keyword(s):  
Linear Relationship ◽  
Stock Exchange ◽  
Optimal Portfolio ◽  
Portfolio Construction ◽  
Archival Data ◽  
Conventional Theory ◽  
Variable Model ◽  
Market Portfolio ◽  
Warsaw Stock Exchange ◽  
Portfolio Return

In the paper we consider a modification of Sharpe’s method used in classical portfolio analysis for optimal portfolio building. The conventional theory assumes there is a linear relationship between asset’s return and market portfolio return, while the influence of all the other factors is not included. We propose not to neglect them any more, but include them into a model. Since the factors in question are often hard to measure or even characterize, we treat them as a disturbances on random variables used by classical Sharpe’s method.The key idea of the paper is the modification of the classical approach by application of the errors-in-variable model. We assume that both independent (market portfolio return) as well as dependent (given asset’s return) variables are randomly distributed values related with each other by linear relationship and we build the model used for parameters’ estimation.To verify the model, we performed an analysis based on archival data from Warsaw Stock Exchange. The results are also included.

scholarly journals Efficient Stock Portfolio Construction by Means of Clustering

2018 ◽  
Vol 1 (333) ◽  
Author(s):  
Jerzy Korzeniewski
Keyword(s):  
Stock Exchange ◽  
Investment Decisions ◽  
Portfolio Construction ◽  
Homogeneous Groups ◽  
Novel Technique ◽  
Partitioning Around Medoids ◽  
Warsaw Stock Exchange ◽  
Stock Portfolio ◽  
Stock Market Investment ◽  
Good Number

When investors start to use statistical methods to optimise their stock market investment decisions, one of fundamental problems is constructing a well‑diversified portfolio consisting of a moderate number of positions. Among a multitude of methods applied to the task, there is a group based on dividing all companies into a couple of homogeneous groups followed by picking out a representative from each group to create the final portfolio. The division stage does not have to coincide with the sector affiliation of companies. When the division is performed by means of clustering of companies, a vital part of the process is to establish a good number of clusters. The aim of this article is to present a novel technique of portfolio construction based on establishing a numer of portfolio positions as well as choosing cluster representatives. The grouping methods used in the clustering process are the classical k‑means and the PAM (Partitioning Around Medoids) algorithm. The technique is tested on data concerning the 85 biggest companies from the Warsaw Stock Exchange for the years 2011–2016. The results are satisfactory with respect to the overall possibility of creating a clustering‑based algorithm requiring almost no intervention on the part of the investor.

Fundamental Portfolio Construction Based on Semi-Variance

2013 ◽  
Vol 8 (2) ◽  
pp. 151-162 ◽  
Author(s):  
Anna Rutkowska-Ziarko
Keyword(s):  
Stock Exchange ◽  
Risk Measure ◽  
Equal Treatment ◽  
Rate Of Return ◽  
Portfolio Construction ◽  
Financial Situation ◽  
Markowitz Model ◽  
Synthetic Indicator ◽  
Warsaw Stock Exchange

In models for creating a fundamental portfolio, based on the classical Markowitz model, the variance is usually used as a risk measure. However, equal treatment of negative and positive deviations from the expected rate of return is a slight shortcoming of variance as the risk measure. Markowitz defined semi-variance to measure the negative deviations only. However, finding the fundamental portfolio with minimum semi-variance is not possible with the existing methods.The aim of the article is to propose and verify a method which allows to find a fundamental portfolio with the minimum semi-variance. A synthetic indicator is constructed for each company, describing its economic and financial situation. The method of constructing fundamental portfolios using semi-variance as the risk measure is presented. The differences between the semi-variance fundamental portfolios and variance fundamental portfolios are analysed on example of companies listed on the Warsaw Stock Exchange. 

scholarly journals Comparison of a Modified and Classic Fama-French Model for the Polish Market

2017 ◽  
Vol 17 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Stanisław Urbański
Keyword(s):  
Stock Exchange ◽  
Model Risk ◽  
Modified Model ◽  
State Variable ◽  
Market Portfolio ◽  
Warsaw Stock Exchange ◽  
Portfolio Managers ◽  
Simulation Results ◽  
Comparison Of The Results ◽  
French Model

AbstractThis paper shows a comparison of the results of return, risk, and risk price simulation by a modified and classic Fama-French model. The modified model defines the new ICAPM state variable as a function of the structure of a company’s past financial results. The model tests are run on the basis of stocks listed on the Warsaw Stock Exchange. In light of the classic model the risk price, on the tested market, turned out univariate due to HML, however, in light of the modified model, risk price turned out to be threedimensional due to the proposed factors, and market portfolio. The factors of the modified model, compared with the HML and SMB, are widely perceived by portfolio managers, and the simulation results indicate a greater possibility to use this pricing application by large institutional investors.

scholarly journals PEMBENTUKAN PORTOFOLIO OPTIMAL PADA SAHAM INDEKS IDX80 DENGAN MENGGUNAKAN MODEL MARKOWITZ

2020 ◽  
Vol 9 (4) ◽  
pp. 1614
Author(s):  
Ni Kadek Arista Dewi ◽  
Made Reina Candradewi
Keyword(s):  
Sampling Method ◽  
Stock Exchange ◽  
Secondary Data ◽  
Optimal Portfolio ◽  
Observation Data ◽  
Portfolio Risk ◽  
Analysis Techniques ◽  
Markowitz Model ◽  
Portfolio Return ◽  
Collection Methods

The purpose of this study is to determine the company's shares that are included in the optimal portfolio along with the magnitude of the final fund proportion of each company's shares. This research was conducted at the Indonesia Stock Exchange on company shares that included the IDX80 index from February to September 2019. This study used secondary data with nonparticipant observation data collection methods. The research sample of 74 shares obtained through purposive sampling method with data analysis techniques using the Markowitz model. The results showed that there were 7 shares worthy of being members of the optimal portfolio of Markowitz models on IDX80 index shares. The seven shares included ACES 11.458 percent, HOKI 2.539 percent, ICBP 26.947 percent, PWON 33.071 percent, TBIG 9.541 percent, WIKA 2.760 percent, and WOOD 13.684 percent which gave an expected portfolio return of 1.806 percent with a portfolio risk of 0.705 percent. Keywords: investment, optimal portfolio, IDX80 index, Markowitz model

scholarly journals Studi Komparatif Pembentukan Portofolio Optimal Dengan Stochastic Dominance dan Single Index Model

2019 ◽  
Vol 1 (1) ◽  
pp. 1-12
Author(s):  
Yuni Utami
Keyword(s):  
Stochastic Model ◽  
Stochastic Dominance ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Optimal Portfolio ◽  
Index Method ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Portfolio Return

Purpose- The study aims to see whether there is a difference between the stochastic dominance method and the single index method in forming an optimal portfolio. and seeing which method is more optimal. Methods- The sample used in the study was a real estate and property company listed on jakarta stock exchange for five years period (2013 - 2017). sampling technique in research using purposive sampling and analysis sampling techniques using average difference test (t-test). after being tested with each method both the stochastic model and the single index model, Finding- The results show that there is a difference in return from the formation of an optimal portfolio with the results of the test which results in 0.048 below the significant level of 0.05. and the results of the calculation of portfolio return formed by the stochastic method is 0.0079 smaller than the portfolio return formed by the single index method of 0.0173 which means that the single index method is more optimal than the stochastic model.

scholarly journals An Efficient Portfolio with Several Objectives and Varying Parameters

2018 ◽  
Vol 3 (4) ◽  
pp. 335-350 ◽  
Author(s):  
Mrinal Jana ◽  
Geetanjali Panda ◽  
Neelesh Agrawal
Keyword(s):  
Portfolio Selection ◽  
Stock Exchange ◽  
Selection Model ◽  
Optimal Portfolio ◽  
Objective Functions ◽  
Market Data ◽  
Varying Parameters ◽  
Portfolio Selection Model ◽  
Portfolio Return

We investigate a portfolio selection model with several objective functions, whose coefficients are uncertain and vary between some bounds. A preferable efficient portfolio of the model is obtained, which provides the range within which the portfolio return and the moments would vary. An optimal portfolio for the forecasted returns of stocks is found with actual market data from the Bombay Stock Exchange, India.

scholarly journals ANALISIS EFISIENSI PENENTUAN PORTOFOLIO SAHAM PERUSAHAAN MANUFAKTUR DI PT. BURSA EFEK INDONESIA (BEI)

2017 ◽  
pp. 38-56
Author(s):  
Jonner Pangaribuan
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Efficient Frontier ◽  
Positive Influence ◽  
Optimal Portfolio ◽  
Manufacturing Companies ◽  
Technical Documentation ◽  
Expected Return ◽  
Portfolio Return

companies, as well as the influence of optimal portfolios and efficient manufacturing companies on stock returns in IDX. Benefits gained for investors itself is as an input to invest in stocks is optimal. The population in this study are all companies listed on the Stock Exchange, and the samples used are as many as 152 shares of manufacturing companies are divided into two portfolios based on market capitalization and value of corporate assets. Data collection techniques used by technical documentation, that the financial statements of companies that have previously run for two years ie from 2002 to 2003 observations. The data analysis technique used is multiple linear regression. Based on the results of the regression can be concluded that the higher the premium market significantly increases the risk of a stock portfolio of manufacturing companies. Regression coefficient for the independent variable on the dependent variable ERM portfolio return has a positive influence on the company. From the observations made, the optimal portfolio is the portfolio to be done based on the value of assets, particularly as it offers a great asset portfolio return of 55 percent with a 100 percent risk. Obviously the determination of the optimal portfolio for an investor to do and are applied in the efficient frontier curve is in accordance with the preferences of the investor returns and are willing to bear the risk. Therefore, investors should consider the investment shares of SBI level, analyzing the stock price and the expected return on a portfolio that is offered, as well as selecting a portfolio of shares in accordance with the preferences of the investor.

scholarly journals Optimal Portfolio Construction: Application of Sharpe's Single-Index Model on Dhaka Stock Exchange

2019 ◽  
Vol 16 (1) ◽  
pp. 60
Author(s):  
Imroz Mahmud
Keyword(s):  
Stock Exchange ◽  
Sampling Technique ◽  
Optimal Portfolio ◽  
Portfolio Construction ◽  
Efficient Manner ◽  
Great Opportunity ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Industrial Sectors

This study aims to find whether Sharpe's single-index model of portfolio construction offers better investment alternatives to the investors of the Dhaka Stock Exchange (DSE). For this purpose, month-ended closing price data of 178 companies listed on the DSE, the prime bourse of Bangladesh, and the month-ended index value of DSEX have been used for the period starting from January 2013 to February 2018. The stocks selected for this study belong to 16 industrial sectors, and purposive sampling technique has been used to select these sectors. Sharpe's model formulates a unique cut-off rate and selects the stocks having an excess return-to-beta ratio above that rate. In this study, 54 stocks qualified to be a part of the optimal portfolio. Hence, the proportion of investment to be made on each of the stock is calculated according to the model. The study reveals that three industries occupy a hefty chunk (65.78%) of the proposed investment portfolio. The constructed portfolio offers a monthly return of 2.1489% and carries 1.9516% risk as measured by standard deviation. The beta of the optimal portfolio is only 0.124003. The constructed portfolio outperforms every individual stock as well as the market index in terms of offering the optimal risk-return combinations. Therefore, this five-and-a-half-decade-old model offers a great opportunity for Bangladeshi investors to optimize return and diversify risk in an efficient manner.

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