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.

Petroleum Exploration Risk in Prospect Portfolio Selection

2017 ◽  
pp. 40-65
Keyword(s):  
Standard Deviation ◽  
Portfolio Selection ◽  
Six Sigma ◽  
Efficient Frontier ◽  
Sharpe Ratio ◽  
Petroleum Exploration ◽  
Management Approach ◽  
Portfolio Optimisation ◽  
Exploration Risk ◽  
Return Variance

Presented method is applied to petroleum exploration for prospect portfolio selection to achieve investment objectives controlling risk. DMAIC framework applies stochastic techniques to risk management. Optimisation resolves Efficient Frontier of portfolios for desired range of expected return with initially defined increment. Simulation measures Efficient Frontier portfolios calculating mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target limits. Analysis considers mean return, Six Sigma metrics and Sharpe Ratio and selects the portfolio with maximal Sharpe Ratio as initially the best portfolio. Optimisation resolves Efficient Frontier in a narrow interval with smaller increments. Simulation measures Efficient Frontier performance including mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target. Analysis identifies the maximal Sharpe Ratio portfolio, i.e. the best portfolio for implementation. Selected prospects in the portfolio are individual projects. So, Project Management approach is used for control.

Prescriptive portfolio selection: a compromise between fast and slow thinking

2017 ◽  
Vol 9 (2) ◽  
pp. 98-116 ◽  
Author(s):  
Omid Momen ◽  
Akbar Esfahanipour ◽  
Abbas Seifi
Keyword(s):  
Portfolio Selection ◽  
Stock Exchange ◽  
Efficient Frontier ◽  
Fast System ◽  
Content Type ◽  
The Mean ◽  
Selection For ◽  
Mean Variance ◽  
Prescriptive Analysis

PurposeThe purpose of this paper is to develop a prescriptive portfolio selection (PPS) model based on a compromise between the idea of “fast” and “slow” thinking proposed by Kahneman. Design/methodology/approach“Fast” thinking is effortless and comfortable for investors, while “slow” thinking may result in better performance. These two systems are related to the first two types of analysis in the decision theory: descriptive, normative and prescriptive analysis. However, to compromise between “fast” and “slow” thinking, “overconfidence” is used as a weighting parameter. A case study including a sample of 161 active investors in Tehran Stock Exchange (TSE) is provided. Moreover, the feasibility and optimality of the model are discussed. FindingsResults show that the PPS recommendations are efficient with a shift from the mean-variance efficient frontier; investors prefer PPS portfolios over the advisor recommendations; and investors have no significant preference between PPS and their own expectations. Research limitations/implicationsTwo assumptions of this study include: first, investors follow their “fast” system of thinking by themselves. Second, the investors’ “slow” system of thinking is represented by advisor recommendations which are simple expected value of risk and return. Therefore, considering these two assumptions for any application is the main limitation of this study. Moreover, the authors did not have access to more investors in TSE or other financial markets. Originality/valueThis is the first study that includes overconfidence in modeling portfolio selection for the purpose of achieving a portfolio that has a reasonable performance and one that investors are comfortable with.

Research and Development Risk in Projects Selection

2017 ◽  
pp. 66-91
Keyword(s):  
Standard Deviation ◽  
Six Sigma ◽  
Efficient Frontier ◽  
Sharpe Ratio ◽  
Management Approach ◽  
Portfolio Optimisation ◽  
Expected Return ◽  
Return Variance ◽  
Stochastic Techniques ◽  
Development Risk

Elaborated method is applied to R&D for project portfolio selection to achieve investment objectives controlling risk. DMAIC framework applies stochastic techniques to risk management. Optimisation resolves Efficient Frontier of portfolios for desired range of expected return with initially defined increment. Simulation measures Efficient Frontier portfolios calculating mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target limits. Analysis considers mean return, Six Sigma metrics and Sharpe Ratio and selects the portfolio with maximal Sharpe Ratio as initially the best portfolio. Optimisation resolves Efficient Frontier in a narrow interval with smaller increments. Simulation measures Efficient Frontier performance including mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target. Analysis identifies the maximal Sharpe Ratio portfolio, i.e. the best portfolio for implementation. Selected projects in the portfolio are individual projects. So, Project Management approach is used for control.

scholarly journals Cryptocurrency Portfolio Selection—A Multicriteria Approach

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1677
Author(s):  
Zdravka Aljinović ◽  
Branka Marasović ◽  
Tea Šestanović
Keyword(s):  
At Risk ◽  
Standard Deviation ◽  
Portfolio Selection ◽  
Value At Risk ◽  
Selection Process ◽  
Efficient Frontier ◽  
Conditional Value At Risk ◽  
Optimal Portfolios ◽  
Promethee Ii ◽  
Proposed Model

This paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision making model gives the best cryptocurrency portfolio considering the daily return, standard deviation, value-at-risk, conditional value-at-risk, volume, market capitalization and attractiveness of nine cryptocurrencies from January 2017 to February 2020. The optimal portfolios are calculated at the first of each month by taking the previous 6 months of daily data for the calculations yielding with 32 optimal portfolios in 32 successive months. The out-of-sample performances of the proposed model are compared with five commonly used optimal portfolio models, i.e., naïve portfolio, two mean-variance models (in the middle and at the end of the efficient frontier), maximum Sharpe ratio and the middle of the mean-CVaR (conditional value-at-risk) efficient frontier, based on the average return, standard deviation and VaR (value-at-risk) of the returns in the next 30 days and the return in the next trading day for all portfolios on 32 dates. The proposed model wins against all other models according to all observed indicators, with the winnings spanning from 50% up to 94%, proving the benefits of employing more criteria and the appropriate multicriteria approach in the cryptocurrency portfolio selection process.

scholarly journals Pembentukan Portfolio Optimal Untuk Berinvestasi pada Saham Perusahaan Perbankan di Bursa Efek Indonesia dengan Metode Sharpe, Treynor dan Jensen Periode 2013-2017

2020 ◽  
Vol 4 (3) ◽  
pp. 74
Author(s):  
Wilson Wihardi ◽  
Anas Lutfi
Keyword(s):  
Standard Deviation ◽  
Stock Exchange ◽  
Expected Return

The aim of this research is to find out the performance of the banking company stocks in Indonesia Stock Exchange, and which stocks is the best to form out a portfolio. The measurement in used is Sharpe Index, Treynor Index, and Jensen Index. The object in this research is the 10 banking companies with biggest capitalization in Indonesia Stock exchange due on 31 December 2017 or the last day of trading day in 2017. The conclusion of this research are the best banking company stocks based on Sharpe Indes is BBCA, based on Treynor Index is MEGA, and based on Jensen Index is BJBR. The Optimum Portfolio is consisted of 79,4 % BBCA, 16,9 % MEGA, and 3,7 % BJBR. Expected Return of this portfolio is 18,98 % per year and standard Deviation 7,2 %.

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.

UNCERTAINTY PORTFOLIO MODEL IN CROSS CURRENCY MARKETS

2010 ◽  
Vol 18 (06) ◽  
pp. 759-777 ◽  
Author(s):  
WEIJUN XU ◽  
WEIDONG XU ◽  
HONGYI LI ◽  
WEIGUO ZHANG
Keyword(s):  
Portfolio Selection ◽  
Asset Allocation ◽  
Efficient Frontier ◽  
Expected Return ◽  
Fuzzy Variables ◽  
Financial Variables ◽  
Fuzzy Environment ◽  
Exchange Risk ◽  
Asset Selection ◽  
Α Level

Owing to the fluctuations in the financial markets, many financial variables such as expected return, volatility, or exchange rate may occur imprecisely. But many portfolio selection models consider precise input of these values. Therefore, this paper studies a multiobjective international asset allocation problem under fuzzy environment. In our portfolio selection model, both of the return risk and the exchange risk are considered. The coefficient matrices in the objectives and constraints and the decision value are considered as fuzzy variables. The calculation of the portfolio and efficient frontier is derived by considering the exchange risk in the fuzzy environment. An empirical study is performed based on a portfolio of six securities denominated in six different currencies, i.e., USD, EUR, JPY, CNY, HKD, and GBP. The α-level closed interval portfolio [Formula: see text] and the fuzzy efficient frontier are obtained with different values of α ∈ (0, 1]. The empirical results indicate that the fuzzy asset selection method is a useful tool for dealing with the imprecise problem in the real world.

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 Performance, persistence and benchmarks of selected South African unit trusts for the period 1998-2002

2005 ◽  
Vol 36 (4) ◽  
pp. 81-90 ◽  
Author(s):  
G. Oldham ◽  
J. A. Kroeger
Keyword(s):  
South African ◽  
Stock Exchange ◽  
Theory Model ◽  
Convincing Evidence ◽  
Superior Performance ◽  
Arbitrage Pricing Theory ◽  
Cross Sectional ◽  
Fund Managers ◽  
Johannesburg Stock Exchange ◽  
Unit Trust

Fund managers in the South African unit trust industry have an objective of generating strong alpha returns, meaning average annual returns above the respective benchmark. This paper analyses the performance of twenty South African unit trusts, selected from various sectors over the 1998 – 2002 period. In all cases the benchmark used by the funds is the Johannesburg Stock Exchange All Share Index. The well-known Capital Asset Pricing Model and a three-factor Arbitrage Pricing Theory model are used in the analysis. The result shows that only four funds of the twenty analysed were able to generate a superior performance in one or more years of the five-year period. Individual unit trusts were unable to perform consistently for any length of time. The failure of the funds to meet their objective is further analysed in terms of the appropriateness of the JSE All Share Index as the benchmark. In some cases the index was not an appropriate benchmark to measure persistence in performance and sector indices were preferable. In a cross-sectional portfolio analysis there was evidence of overall persistence in performance but this was of short duration, related more to negative than positive persistence in performance. Overall, the results of the analysis do not produce convincing evidence that unit trust fund managers were able to generate consistent above average returns to their investors. Furthermore, it may be preferable from an investor’s viewpoint if fund managers were to target an absolute rather than a relative benchmark.

scholarly journals ANALISIS PENGARUH RISIKO TERHADAP RETURN YANG DIHARAPKAN UNTUK MENENTUKAN PILIHAN BERINVESTASI PADA SAHAM JAKARTA ISLAMIC INDEX (JII)

MOTIVASI ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 200
Author(s):  
Ervita Safitri
Keyword(s):  
Interest Rates ◽  
Sampling Method ◽  
Stock Exchange ◽  
Share Price ◽  
Simple Linear Regression ◽  
Expected Return ◽  
Market Index ◽  
Analysis Technique ◽  
Investment Option ◽  
Capm Model

Purpose - The objective of this study was to assess the risk of the stock return by using CAPM model to determine the investment option at Jakarta Islamic Index in the Indonesia Stock Exchange (BEI) and to find the risk of the return which was expected by CAPM Model.Design/methodology - The population of this study was 52 companies which were listed at JII in 2010-2014. The sample of this study was chosen by using purposive sampling method. The numbers of the companies were 12 companies. Data analysis technique in this study was by using the monthly closing share price dara registered in JII, JII market index, and interest rates of SBI.Findings – The result of this study showed that out of twelve companies, there were four stocks that could be used as the investment option, namely PT. Alam Sutra Reality, tbk, PT. Astra International, tbk, PT. Lippo Karawaci, tbk, PT. Telekomunikasi Indonesia, tbk. The result of hypothesis testing with a simple linear regression t-test found that t value > t table (-24,249>-2,228) with significant value (0,00<0,05) , it indicated that there was a significant influence between beta and CAPM expected return.

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