Formation Of Optimal Portfolio Research Articles

Determination of Optimal Stock Portfolio Return by Single Index Model (Case Study on Banking Sector Stocks in Indonesia)

The optimal portfolio is a portfolio chosen by investors from the many options available in the collection of efficient portfolios. To get the optimal proportion, which is the maximum return and minimum risk, it is necessary to analyze the stocks to be selected in the investment model. The research objective is to determine the optimal return, risk, and proportion for each banking stock portfolio in Indonesia in the period February - July 2023. The method used is the Single Index Model. The process of determining the optimal proportion of stocks with the Single Index Model requires stock and market return data as the main basis for applying this method. This study involves the formation of an optimal portfolio of daily closing prices of 46 banking stocks. As a result of this research, there are 5 optimal stocks that meet the criteria for optimal portfolio formation with each fund proportion of 21.43% (BNII), 13.52% (BDMN), 35.02% (BBRI), 23.69% (BTPN), and 6.34% (BBCA). Expected return from optimal stocks is 0.152% and the risk that will be borne by investors is 0.0011% per day.

Research on Optimization of Investment Portfolio in the New Energy Vehicle Industry Chain

The urgent environmental problems caused by global climate change have propelled the rise of the new energy vehicle industry. Nations and business are also focusing on the research and promotion of this industry. Due to the fast development, investors face both promised investment opportunities and complicated challenges. Against this backdrop, a vital issue, which is how to choose the optimal investment portfolio to achieve the maximum possible return while experience the lowest possible risk, arises. This paper collects the closing price of stocks from 5 companies in different sectors of the new energy vehicle industry, with the period from 19 August 2022 to 18 August 2023 and then computes the variance of closing price and average return of the stocks, finally uses the COVAR function in excel to obtain the covariance matrix. After processing the data, the paper applies the Markowitz mean-variance model to obtain the optimal portfolio formation. Results show that this industry may not be a good choice for investors currently since all three portfolios show negative returns, while the negativity do not completely negate the long-term potential of this industry as the development of the industry can be influenced by various factors. It is therefore to conduct deeper research to better understand the industry dynamics and future trend.

Determination of Optimal Portfolio by Calculating Transaction Costs using Genetic Algorithms on the Jakarta Islamic Index

The optimal portfolio is a portfolio that can provide maximum returns at the same level of risk. In investing, the term "high return, high risk" is known, meaning that the higher the return, the higher the risk. Therefore, investors need to develop an optimal portfolio to obtain the maximum return on investment at the same level of risk. This study aims to determine the optimal formation of a stock portfolio by calculating transaction costs using the genetic algorithm method on stocks that are members of the Jakarta Islamic Index. This research uses data of daily return on stocks included in Jakarta Islamic Index from 1 August 2020-1 August 2022. The dataset consists of two variables: the date of observation and daily stock returns. The method used in this study is the minimum variance method and the genetic algorithm. Data analysis was divided into two stages: model formulation and model testing through case studies. The analysis of optimal portfolio formation using genetic algorithms shows that in terms of performance, the minimum variance portfolio is superior to the genetic algorithm portfolio, as indicated by the Sharpe ratio value. Meanwhile, the genetic algorithm portfolio is superior to the minimum variance portfolio regarding transaction costs. The genetic algorithm portfolio can provide a fairly high total return, small transaction costs, and good performance compared to the minimum portfolio. Hence, the genetic algorithm portfolio is worthy of recommendation to investors.

PEMBENTUKAN PORTOFOLIO OPTIMAL INVESTASI MENGGUNAKAN MODEL MARKOWITZ DAN MODEL INDEKS TUNGGAL PADA ASET BEBAS RISIKO DAN ASET BERISIKO

Optimal Portfolio is one way that can be used to determine stock portfolios that generate large returns with the smallest risk. The purpose of this study is to determine the optimal portfolio of risk-free assets and risk assets using the Markowitz Model, Single Index Model and portfolio performance by comparing the resulting rate of return and risk. The research sample used was LQ 45 shares listed on the Indonesia Stock Exchange from August 2014 to July 2019. The sampling technique used was purposive sampling technique, namely the selection of data based on certain criteria in order to obtain a sample of 29 listed companies. The method used is to use the Markowitz Model, the Single Index Model and portfolio performance. From the optimal portfolio formation based on the Method, there are 9 shares included in risk free assets and 20 shares included in risk assets. The results of the analysis show that by using the Single Index Model the return from the optimal portfolio produced is higher than using the Markowitz Model, as well as the risk generated on the Single Index Model is smaller than using the Markowitz Model both on risk-free assets and risk assets, this is assured with the results obtained from portfolio performance.

OPTIMAL PORTFOLIO FORMATION ANALYSIS USING THE SINGLE INDEX MODEL DURING THE COVID-19 PANDEMIC: A Study on The LQ 45 Index on the Indonesian Stock Exchange (IDX)

This study aims to determine the optimal portfolio formation using the single index model method on LQ 45 Index stocks for the period from March 2020 to December 2021. The population in this study consists of all company shares included in the LQ 45 Index during the specified period, totaling 45 stocks. A sample of 36 companies was selected using a nonprobability sampling technique with a purposive sampling method. Data collection was carried out using documentation techniques, primarily focusing on collecting closing stock price data. The data analysis process involved collecting the closing stock price data and utilizing the single index model method to identify an optimal portfolio. The results of this study indicate that 18 company shares were included in the optimal portfolio. These companies are ADRO (7.46%), AKRA (14.51%), ANTM (7.97%), ASII (4.42%), BBNI (3.3%), BBTN (1.8%), BMRI (4.55%), CPIN (1.45%), ERAA (11.14%), EXCL (3.19%), INCO (8.55%), INKP (3.98%), ITMG (5.08%), JPFA (4.86%), JSMR (3.37%), KLBF (8.3%), TKIM (1.85%), and TOWR (4.23%). The expected return for the portfolio is 4.38% per month, with a portfolio risk borne by investors of 0.29% per month. The study suggests that constructing a portfolio with the identified stocks can yield favorable returns. However, it is crucial to regularly reassess and adjust portfolios due to changing market conditions and individual risk preferences. The implications highlight the benefits of using the single index model for portfolio formation. By considering the relationship between individual stocks and the LQ 45 Index, investors can make informed decisions to maximize returns while managing risk. These specific stocks can serve as a starting point for further research in portfolio management.

Analisis Kinerja Portofolio Saham Menggunakan Metode Sharpe, Treynor dan Jensen

The purpose of this study was to determine the optimal stock portfolio performance on the LQ45 stock index on the Indonesia Stock Exchange for the period February 2019- December 2022. The data analysis method uses a single index model to form an optimal portfolio and uses the Sharpe, Treynor, and Jensen index methods to assess performance stock portfolio. Based on the results of the analysis of optimal portfolio formation, it shows that out of 30 samples of LQ45 index stocks, 8 stocks were obtained which included optimal portfolio stocks, namely ERB values > C*, namely ADRO, ANTM, BBCA, BRPT, INCO, INDY, ITMG, & MEDC stocks. the results of the stock portfolio performance appraisal analysis show that of the three portfolio performance appraisal index methods, the calculation of stock performance analysis, the average value of the Sharpe method is 0.1241, while the treynor method is 0.0112, and the Jensen method is 0.0334. The highest performance of the third method is the Sharpe method with an average performance value of 0.1241. So the Sharpe method is the best performance method compared to the Treynor and Jensen methods. The higher the Sharpe index value, the better the performance of the stock portfolio.

Formation of Optimal Portfolio on JII Stock using Sharpe, Treynor, and Jensen Indices during the Period of 2018-2023

Investment is an activity carried out by investors by placing their funds in an asset. The purpose of investment is to gain long-term profits in the future. These profits come from changes in the price of assets in the future, which refers to the increase in the value of an asset over time. Currently, there are several types of investments. However, the type of investment that is quite widely practiced by Indonesian society is stock investment. The Indonesia Stock Exchange (IDX) groups the stocks available in the stock market into several indexes. One index that is currently receiving attention from Indonesian society is the Jakarta Islamic Index (JII). The JII is a collection of shares from companies that adhere to sharia principles in their business operations. Investment activities must be carried out carefully by conducting analysis beforehand so that investors do not make mistakes in choosing the stocks to be purchased. Several popular methods for selecting stocks are the Sharpe, Treynor, and Jensen indexes. These three indexes can be used to select the best stocks based on their respective criteria. This study combine these three indexes to prioritize the formation of a portfolio. The data used in this study is the closing value of stock prices in the JII index from March 2018 to February 2023. The optimization resulted in a composition of 69.17% for MDKA shares, 26.55% for HRUM shares, and 4.28% for BRIS shares of the total portfolio composition.

Analysis of Optimal Portfolio Formation During the Covid-19 Pademic Using the Capital Asset Pricing Model (CAPM) Model for IDX-30 Shares in the 2020 Period

The study used the quantitative descriptive research design. The research population comprised all the stocks listed in the IDX30 index published biannually with a total of 30 stocks. The variables in the study were stock return, market return, stock risk, and market risk. The calculation of the expected return used the capital asset pricing model.The results of the study to find out the optimal portfolio of stocks by using capital asset pricing model were as follows. (1) The stock that made up the optimal portfolio were those of (1 adalah TBIG ( Tower Bersama Infrastructure Tbk.), MDKA (Merdeka Copper Gold Tbk.) dan UNTR ( United Tractor Tbk ) 2) The composition of the proportion of funds formed by using the Composite Stock Price Index as the market return proxy was allocated for the stocks of, 23% allocated for the stocks of TBIG ( Tower Bersama Infrastructure Tbk.) , 45%, allocated for the stocks of) MDKA (Merdeka Copper Gold Tbk.), 32%. allocated for the stocks of UNTR ( United Tractor Tbk ).

Analysis of Stock Selection Model Strategy in Indonesia's Capital Market

The impact of investor behavior and decision-making on investment interest in the Indonesian capital market is ultimately tied to the stock selection model used to form an optimal portfolio. Therefore, this study aims to develop an optimal stock selection model in the Indonesian capital market. And thus, the novelty of this study relates to other studies that demonstrate how to improve investment decisions in the capital market in Indonesia. Whereas previous research focused solely on the associations between variables, this study examines the variables themselves. This investigation was carried out in the Greater Jakarta of Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi). This research utilizes the Fuzzy-Analytical Hierarchy Process (FAHP) methodology. FAHP is the combination of AHP and a fuzzy concept approach. The FAHP method uses qualitative and quantitative data to make decisions. The data collection method employs primary data from the Survey Questionnaire and discussions, secondary data consisting of market data, stock price movement data from the Indonesia Stock Exchange, Indonesian Central Securities Depository, Bank Indonesia, and empirical literature about stock selection models. The results of the analysis indicate that forming the optimal portfolio in the Indonesian capital market involves predicting the price or stock return using a single factor that is thought to impact security. The primary objective assumed to be realized by the optimal portfolio formation approach on the Indonesian capital market is the optimization of stock combinations. Keywords: investor behavior, investor decision-making, capital market, investment, stocks

PEMBENTUKAN PORTOFOLIO OPTIMAL PADA INDEKS SAHAM SYARIAH TERBARU DI PASAR MODAL INDONESIA - IDX SHARIA GROWTH (IDXSHAGROW)

Seeing the needs of capital market industry players, the Indonesia Stock Exchange (IDX) developed an Islamic stock index. The newest type of sharia stock index launched by the IDX is IDX Sharia Growth (IDXSHAGROW). Stock investment requires a strategy to obtain maximum returns with minimal risk, one of which is diversification in portfolio formation. This study aims to form an optimal portfolio on the latest Islamic stock index on the Indonesian capital market, namely IDX Sharia Growth (IDXSHAGROW). The model used is the single index diversification model. The data used is for the period December 1, 2021 to. November 30, 2022 with weekly frequency. The results showed that the 30 shares that are members of IDXSHAGROW have 14 candidate shares. Furthermore, by making a cut-off, 11 stocks were included in the optimal portfolio with each proportion, namely MAPI 25.67%, KLBF 22.04%, AKRA 13.28%, UNTR 12.16%, MPMX 8, 3%, BRMS 4.4%, INCO 3.6%, LPPF 2.93%, ELSA 2.59%, AGII 2.54% and MYOR 2.48%. The optimal portfolio expected return value is 0.0017568 with a variance value of 0.00245 and a standard deviation of 0.04954 at weekly frequency. From the analysis of optimal portfolio formation in this study, the results were quite profitable for investors. This can be seen from the expected return value of the portfolio which is higher than the market value with each risk.

Optimal Portfolio Formation Using Single Index Model on the IDX80 Index for the Period February 2021 – May 2022

The policy of the Central Bank of the United States (US), namely the Fed, in raising its benchmark interest rate, has increased the risk of volatility in global markets and triggered negative sentiment for foreign investors in Indonesia. Foreign investors began to relinquish their ownership up to Rp 3.19 trillion. This caused the risk of falling prices. Therefore, investors need to diversify through the formation of an optimal portfolio to minimize risk and maximize return. This study aims to analyze the formation of the optimal portfolio on the IDX80 index for the period February 2021 - May 2022. This type of research is descriptive using quantitative methods. The sample of this research used a purposive sampling technique. This study uses secondary data with data collection methods, namely documentation and literature study. The data analysis method in this study is a single index model. The results showed that of the 53 stock samples, there were 19 optimal stocks. The expected return portfolio level is 0.20% in one day, while the portfolio risk level is 0.05%.

Analysis of Optimal Stock Portfolio Investment on The LQ45 Index Using the Markowitz Model and Single Index Model

This Markowitz model can overcome the weakness of random diversification. The assumption that increasing the number of shares in a portfolio continuously will provide greater benefits is different from the Markowitz model. This model believes that the addition of stocks continuously in one portfolio, at a certain point, will further reduce the benefits of diversification and will increase the level of risk (Tandelilin, 2010). The Markowitz portfolio also provides quite efficient results because it has a positive expected return value from each portfolio (Supriyadi and Hadmar, 2009). Single Ithe single model is one method for forming a portfolio that can be used by investors. The optimal portfolio analysis technique using the Single Index Model is a security analysis technique that is carried out by comparing the excess return to beta (ERB) to the cut off rate (Ci) of each stock. This study uses a population of issuers that are included in the LQ45 calculation for the period February 2018 - July 2020 with a total sample using the purposive sampling method of 31 samples. Based on the optimal portfolio formation of the Markowitz Model, 4 stocks form a portfolio exexpectedeturn of 0.0074 while for portfolio risk of 0.0428 and the proportion of funds formed is BBCA 50.81%, E XCL 9.83%, ICBP 30, 59%, and KL B F 8, 77. The formation of a single index model portfolio obtained 2 optimal portfolio formations with a portfolio return of 0.1486 and a risk of 0.0873 while the proportion of funds formed by ANTM was 10.5%, and BBCA was 89.5%. Based on the results of the study proves that the single index model can generate a profit of 14.86% with a risk level of 8.73% compared to the Risk-Free Assets Return rate of 5.17%. Meanwhile, the Markowitz model can generate a portfolio return of 0.74% with a portfolio risk of 4.28% not providing optimal returns because the expected return from the Markowitz model portfolio is lower than the Risk-Free Asset Return Rate. Keywords: Markowitz Model, Single Index Model, Portfolio Optimal, Stock

The Financial Technologies Utilization to Increase the Competitive Advantage of Product Marketing

The purpose of this study is to analyze the formation of an optimal stock portfolio and provide the expected rate of return and minimum portfolio risk. This type of research is descriptive with a quantitative approach. The data used in this study is secondary data, consisting of closing prices, market index (LQ45 index), seven-day repo rate, beta and alpha for the periods June 2019-June 2020 and June 2020-June 2021. The data analysis method uses Microsoft Excel program to calculate LQ45 stock index in optimal portfolio formation. The results of the study show that there are seven stocks that perform well and form an optimal portfolio, which can be sorted by stock performance, namely: MIKA (44%); JPFA (24%); ITMG (12%); INKP (11%); INDF (6%); PGAS (1%), and PTPP (2%). which produces an expected portfolio return of 13.00% and a portfolio risk level of 19.22%. Of the ten sample companies used in the study, there were three issuers that were not optimal, namely:INTP;MNCN;and PTBA, due to the value of ERB C.

Comparison Analysis of Optimal Portfolio Formation on Jakarta Islamic Index 70 (JII70) (Markowitz Model and Single Index Model Approach)

This study analyzes the optimal portfolio formation of Islamic stocks on Jakarta Islamic Index 70 (JII70) with the Markowitz and Single Index models. The analysis then compares the proportion of funds, return, and portfolio risk. The subsequent analysis compares the two models' optimal and non-optimal returns and risks. This study uses data on stock prices, dividends, BI-7 Day Reverse Repo Rate, and Composite Stock Price Index for May 2018-September 2021. The research sample is 37 JII70 stock issuers obtained by the purposive sampling technique. The Markowitz model produces 12 combinations, a certain expected return of 0.66% and the best portfolio risk of 3.22%. In comparison, the Single Index Model produces nine stock combinations, the best-expected return of 2.28%, and a certain portfolio risk of 7.53%. Analysis with the Markowitz Model shows no significant difference between stock returns included in the optimal and non-optimal portfolio. However, there is a significant difference between stock risk. In addition, in the Single Index Model, it was found that there was a significant difference between stock returns, including optimal and non-optimal portfolios. However, there was no significant difference between stock risk. The study results can be an essential reference for JII70 investors and stakeholders before and during the Covid-19 pandemic in Indonesia.

Forecasting Startup Return using Artificial Intelligence Methods and Econometric Models and Portfolio Optimization Using VaR and C-VaR

In this paper, we have tried to study the main role of startups in economy, their characteristics, main goals and etc. The main goal of article is prediction of startup's return using artificial intelligence methods such as genetic algorithm (GA) and artificial neural network (ANN). Some global indices such as S&P500, DJAI, and economic indicators such as 10 years Treasury yield, Wilshire 5000 Total Market Full Cap Index along with some other special indicators in startups like team, idea, timing and etc. are used as input variables. GA is used as feature selection and finding the most important variables. ANN is used as an optimization model and prediction of startup's returns. We used econometric models such as regression analysis. We have estimated Value at risk (VaR) and Conditional Value at risk (C-VAR) for considered portfolios including three startups (public company) such as Dropbox, Inc. (DBX), Scout24 SE (G24.DE) and TIE.AS and optimal portfolio formation. The results show that AI based methods are more powerful in prediction of startup's return. On the other hand, VaR and C-VaR models are very beneficial approach in minimizing risk and maximizing return.

Analysis of Optimal Portfolio Formation Using Single Index Model and Stochastic Dominance on Sri-Kehati Index

This study directly applies the Single Index Model and Stochastic Dominance to solve the portfolio selection problem. This study aims to determine the difference in performance between the Single Index Model and Stochastic Dominance. The use of secondary data was used in this study by selecting the sample using the purposive sampling technique. If viewed based on the portfolio return, the single-index model can produce a portfolio return of (1.548%) and a stochastic dominance return of (0.888%). The results show that the value of the Stochastic Dominance portfolio formation has a Treynor index which is 2.22% higher than the Single Index Model with a Treynor index of 2.09%.

Pengambilan Keputusan Investasi Portofolio : Pendekatan Model Indeks Tunggal Saham

Abstract. This study aims to determine the composition of the optimal portfolio formation using the Single Index method on LQ-45 shares in the Indonesia Stock Exchange period 2016 - 2018. This research was conducted on the basis of the increasing number of investors who chose to invest their funds in shares, where this is indicated from the increasing positive sentiment on stock investment compared to other investments. Portfolio formation using the Single Index model is one model that can be used to form optimal portfolios, because with this model portfolios are easily formed to fit the desired investment characteristics and objectives to be achieved. The Single Index method is a method that formulates the existence of elements of return and risk in an investment, where the risk element can be minimized through diversification and combining various investment instruments into a portfolio. By using the Single Index method, investors can take advantage of all available information as the basis for maximizing portfolio formation. The sample selection technique of this study used a purposive sampling method and 19 LQ-45 Index stocks were obtained which were used as the research sample. Based on the results of research to determine the optimal portfolio of shares using the Single Index method shows that the LQ-45 Index Shares that form the optimal portfolio are INCO, BBTN, ICBP, INTP, BMRI, BBNI, BBCA, HMSP, INDF shares , GGRM and TLKM. And this study produced 55 portfolio combinations in which there is one efficient portfolio, 26 portfolios with the same funding weight (50%: 50%). Investors choose an efficient portfolio in accordance with the preferences of the level of profit and risk they bearKeywords - Single Index Model, Optimal Portfolio, Expected Return, LQ-45

“MORE VALUEBLE?” PORTFOLIO MIX: ISLAMIC SOCIAL RESPONSIBILITY STOCK

This research was conducted to analyze the optimal portfolio formation using the Single Index Model method by combining stocks included in the SRI-Kehati Index and listed on the Indonesian Sharia Stock Index (ISSI) with the aim of survival and applying sharia principles then measuring optimal portfolio performance using Sharpe Index, Treynor Index, and Jansen Alpha Index. The object of research used is stocks that are consistently included in the Sri Kehati Index and ISSI for the period December 2018 - December 2019. The results of this study show that the optimal portfolio formed has a higher return compared to the benchmark (IHSG) which is 1.99%, meanwhile, the standard deviation of the portfolio or it can be interpreted as portfolio risk is 1.1%. In performance appraisal, in addition to the Jensen Index, the optimal portfolio formed has better performance than the IHSG.

Optimal Portfolio Formation with Combination of LQ45 Stocks and Corporate Bonds

The objective of investors to invest their money was to maximize return, although they were subject to constraints, primarily risk, so this study aims to provide an alternative to the formation of portfolios and corporate bonds to obtain optimal returns with acceptable risk. The alternative model is to combine Graham's stock selection model with the formation of an optimal portfolio model, namely the Markowitz model. The results of the selection using the Graham model of defensive investors and aggressive investors are 9 and 13 stocks, respectively, of the 45 stocks listed on the LQ45 index. From the selected stocks, the optimal portfolio is formed using the Markowitz model. The results show that the Markowitz model optimizing portfolio provides better performance (reward to variability ratio) than the LQ45 portfolio index with a yield difference of 13.68 – 20.24% per year. Furthermore, the selection of corporate bonds for the optimal portfolio resulted in 8 corporate bonds with a portion of each bond, and this portfolio can generate rates of 8.88% per annum.JEL: G10, G11, G12

The Analysis of Optimal Portfolio Formation: The Evidence from LQ-45 during the Covid-19

The purpose of this research was to determine the shares of the LQ 45 index members that can form an optimal portfolio during the one year of the Covid-19 pandemic, and to determine the proportion of each selected stock as well as the level of return and risk of the resulting portfolio. The method used is the Single Index Model approach. The results of the analysis show that using the Single Index Model approach, the shares of the LQ 45 Index members for the period April 2020 to March 2021 which can form an optimal portfolio consist of: ERAA of 0.3065, INKP of 0.217, ANTM of 0.216795, TKIM of 0.108794, PTPP is 0.058829, INCO is 0.064533, and BBTN is 0.027549 © Review of International Geographical Education