Portfolio Yield Research Articles

Construction of a Sparse Covariance Matrix Based on Statistical Data Analysis and Its Use in Choosing an Optimal Portfolio of Securities

Purpose of the study. The aim of the study is to develop a new method for finding an optimal portfolio of securities based on suboptimization using a sparse covariance matrix, and to create a program based on it to automate the procedure for selecting an investment strategy.Materials and methods. The paper presents one of the possible formalizations of a two-criterion investment problem – setting the problem for the maximum expected portfolio yield with an upper limit on the standard deviation. At the same time, the calculation of the standard deviation of a portfolio with a sparse matrix of covariances of financial instruments’ yields is justified. A solution to a two-criterion problem based on the use of the Karush-Kuhn-Tucker optimality conditions is given. All necessary primary calculations and studies are performed in Microsoft Excel; the functions of the Python programming language are used for automation and implementation of the graphical interface.Results. The analysis of the methods used to make investment decisions was carried out and the use of each of them for specific stock market data was justified. To automate analytical approaches to finding the optimal investment strategy with full, partial and absent correlation dependence, a program and a graphical interface were created using the Python programming language libraries. The software product was tested on the example of the investment process with real data of the Russian stock market. The initial data in this study were quotes of shares of Russian companies for the period from 01.01.2019 to 31.12.2021, taken from the Yahoo Finance website. The choice of each of the shares was based on the results of the fundamental and technical analysis.Conclusion. As a result of the conducted research, it was established that the proposed method of finding the optimal strategy using a sparse covariance matrix is a suitable tool for an active investment strategy. The technical implementation of the proposed method - the use of the Python programming language to create a graphical interface – allows automating the process of constructing an investment strategy.

Optimal Investments in the Portfolio Yield Reactive (PYR) Model

We evolved our past Portfolio Yield Reactive (PYR) model to provide a competitive system with infiltration of categorical information and fundamentals into advanced higher-order moments that support more objective portfolio selection aided by intelligent computing. The system of the PYR model searches for hidden corporate performance prototypes in big data from accounting and financial statements. The PYR model restricts malicious patterns, such as hoaxes, noise, and manipulation, incorporated into a novel optimal portfolio selection method.

МОДЕЛИРОВАНИЕ РАСПРЕДЕЛЕНИЯ ДОХОДНОСТИ ОТ ИНВЕСТИЦИЙ В ПОРТФЕЛЬ АКЦИЙ

In the modern world, understanding and the ability to predict investment returns comes to the fore for investors. Modeling the profitability of a stock portfolio using the mathematical Monte Carlo method involves the use of random numbers and statistical data to predict possible investment returns. The method analyzes the simulation of market scenarios, allowing you to assess the likely change in the structure of instruments and the portfolio as a whole. This article examines the distribution of profitability of a portfolio consisting of nine shares of companies in different sectors of the economy. The formation of a diversified investment portfolio relies on the fixed asset pricing model, the standard deviation of stock returns and the Black-Letterman model to determine the weights of stocks in the portfolio. Using the Pythonbased Monte Carlo method allowed thousands of simulations to be performed and a histogram of the portfolio yield distribution to be constructed. Combining mathematical methods helps to predict the profitability of an investment portfolio and form a more attractive diversified portfolio, taking into account the goals of the investor.

The Research on the Application of CAPM Model in Chinese Stock Market

With the improvement of living standards, more and more people tend to use their savings to make stock investment, and how to make good use of precious capital for project investment, industrial support policy of the government how to develop practical, make the flow of resources efficiently has the development potential and competitive enterprise project, which requires us to make accurate judgment and the correct decision. By adopting the method of regression analysis, carries on the empirical analysis of China's securities market sampling, shows that, by using statistical analysis methods, this study can select a relatively appropriate market portfolio yield, improve the accuracy of asset value and asset allocation, which is an effective and analytical obstacle to the use of Capital Asset Pricing Model (CAPM) to the China's capital market. And then put forward some model to analyze the enlightenment of capital and asset pricing for the stock market. The study draws a conclusion that the beta of a stock plays a decisive role in investing. Stocks with different beta values are selected according to different stock market conditions in order to achieve the best expected annualized return.

Internal audit in microfinance institutions‐ evidence from transitional and developing economies

AbstractMicrofinance institutions (MFIs) are hybrid organisations that strive to balance business and social goals. This paper examines the determinants of the internal audit (IA) function in MFIs, with particular emphasis on the business goals, specifically efficiency, productivity, regulation and the gross portfolio yield. We also investigate whether the establishment of an IA function is associated with MFI's focus on their social objectives relating to outreach, and women director appointments. Multivariate regression results from 1025 MFIs across 63 countries show that MFIs' focus on their social objectives is related to their propensity to establish an IA function. Thus, outreach and women director appointments are positively related to the establishment of an IA function. Similarly, in terms of the performance emphasis, the gross portfolio yield (inefficiency) increases (decreases) the likelihood of establishing an IA, but productivity and regulation have no effect. The findings suggest that MFIs' dual focus on social and business objectives impacts the establishment of internal audits. The results are robust to various measurements and estimations.

OPTIMAL ALLOCATION OF PENSION FUNDS. SENSITIVITY ANALYSES OF THE ADJUSTED SHARPE RATIO

In order to optimally manage pension funds, an optimal portfolio is constructed under various constraints. The Sharpe and adjusted Sharpe ratios are calculated. An assessment of the symmetry and spread coefficients of the optimal portfolio yield is made. A sensitivity analysis of the optimal portfolio is performed and founded that when using the Sharpe ratio as a decision criterion, the optimal limit for the country and asset is 35%, while under RA law it is 15%, and the obtained result is stable with respect to symmetry and spread.

Is Fama-French five factor model better than the three factor model——Empirical evidence from the US stock market

This paper takes the listed companies in the US stock market from July 1993 to October 2021 as a sample to compare the predictive ability of the three-factor model and the five-factor model. The main conclusions are as follows: Firstly, the correlation between the factors of the three factor model and the five factor model is not significant. Second, using the three factor model to test the profitability effect and investment style effect, it is found that there are still significant profitability effect and investment style effect in the US stock market after 1993 after the adjustment of the three factor model. To some extent, this shows that the five factor model is better than the three factor model in predicting the US stock market returns after 1993.Third, through the redundancy test of the factors in the five factor model, it is found that after the adjustment of several other risk factors, the US stock market still has significant market risk, scale effect, profitability effect and investment style effect, but the HML factor is a redundant factor for explaining the stock portfolio yield. Fourth, by comparing the effectiveness of HML, RMW and CMA factors, it is found that the coefficients of CMA factors are not significant, indicating that CMA factors cannot explain the portfolio return rate of the US stock market.

Portfolio rebalancing based on a combined method of ensemble machine learning and genetic algorithm

PurposeThis paper presents a combined method of ensemble learning and genetics to rebalance the corporate portfolio. The primary purpose of this paper is to determine the amount of investment in each of the shares of the listed company and the time of purchase, holding or sale of shares to maximize total return and reduce investment risk.Design/methodology/approachTo achieve the goals of the problem, a two-level combined intelligent method, such as a support vector machine, decision tree, network Bayesian, k-nearest neighbors and multilayer perceptron neural network as heterogeneous basic models of ensemble learning in the first level, was applied. Then, the majority vote method (weighted average) in the second stage as the final model of learning was collectively used. Therefore, the data collected from 208 listed companies active in the Tehran stock exchange (http://tsetmc.com) from 2011 to 2015 have been used to teach the data. For testing and analysis, the data of the same companies between 2016 and 2020 have been used.FindingsThe results showed that the method of combined ensemble learning and genetics has the highest total stock portfolio yield of 114.12%, with a risk of 0.905%. Also, by examining the rate of return on capital, it was observed that the proposed method has the highest average rate of return on investment of 110.64%. As a result, the proposed method leads to higher returns with lower risk than the purchase and maintenance method for fund managers and companies and predicts market trends.Research limitations/implicationsIn the forthcoming research, there were no limitations to obtain research data were easily extracted from the site of Tehran Stock Exchange Technology Management Company and Rahvard Novin software, and simulation was performed in MATLAB software.Practical implicationsIn this paper, using combined machine learning methods, companies’ stock prices are predicted and stock portfolio optimization is optimized. As companies and private organizations are trying to increase their rate of return, so they need a way to predict stock prices based on specific indicators. It turned out that this algorithm has the highest stock portfolio return with reasonable investment risk, and therefore, investors, portfolio managers and market timers can be used this method to optimize the stock portfolio.Social implicationsThe homogeneous and heterogeneous two-level hybrid model presented in the research can be used to predict market trends by market timers and fund managers. Also, adjusting the portfolio with this method has a much higher return than the return on buying and holding, and with controlled risk, it increases the security of investors’ capital, and investors invest their capital in the funds more safely. And will achieve their expected returns. As a result, the psychological security gained from using this method for portfolio arrangement will eventually lead to the growth of the capital market.Originality/valueThis paper tries to present the best combination of stock portfolios of active companies of the Tehran Stock Exchange by using the two-level combined intelligent method and genetic algorithm.

Optimizing a portfolio of agri-environmental investments

Purpose. The purpose of the article is to substantiate theoretical-and-methodological provisions for building investment portfolios in agribusiness by the criterion of minimizing environmental risk of selected investment-financing strategies.
 Methodology / approach. In the article, on the basis of the dialectical method of cognition, the following methods were used: abstract-logical – in the systematization of scientific papers on the problem of diversification and optimization of the agricultural investment portfolio; system analysis and comparison – in the study of portfolio theories and concepts; computational and constructive – in the analysis of environmental-and-economic factors of the profitability of agricultural land use; economic-and-mathematical modeling – in the process of modeling the optimal portfolio of agri-environmental investments by the criterion of minimizing the risk of a particular investor, caused by the action of soil degradation factor in Sumy region. The materials of the Main Department of Statistics in Sumy region and the Sumy regional branch of the Institute of Soil Protection of Ukraine have formed the informational basis of the research.
 Results. The optimization of the agri-environmental investment portfolio is due to the modification of the approach by the American Economist H. Markowitz “risk-return analysis” and its adaptation to the conditions of real investment. The paper uses a conservative approach to investment, which involves the construction of portfolios on the criterion of minimizing investment risk due to the influence of soil degradation for a particular investor. This factor requires the determination of the investor’s environmentally related risk, which manifests itself in the following directions: a) a decrease in crop yield due to the action of the factor of high soil pH; b) a decrease in the sales price for crop products because of contamination with heavy metals; c) an increase in the cost of agricultural production in deteriorated ecological conditions. Evaluation of agribusiness investment attractiveness on environmental-and-economic grounds provides for the consideration of the above areas from the standpoint of state, banking, foreign investment and self-investment. Assessment of investment quality identification is performed on the basis of calculation of the investor’s income elasticities to environmental risks on the example of Sumy region, which provides investment rationality decisions in the field of agricultural land use, considering environmental factors. It is substantiated that the highest investment quality is characterized by the bank’s investment financing strategy.
 Originality / scientific novelty. The methodological approach to the definition of investor’s environmental risk in agricultural land use is improved. It is calculated considering the influence of factors of environmental destruction of land and soil resources (soil pH, pollution with heavy metals, etc.) on sources of profit, as well as with the definition of returns on investment resources (crop yield, ecological sales price, and income). The system of environmental-and-economic indicators in the formation of the investment portfolio is substantiated, including the following: the structure of investments, which is developed considering the influence of the environmental factor; portfolio investment risk due to environmental factors; and the investment portfolio yield adjusted for the level of environmental risk which provides an assessment of the investment attractiveness of agricultural land use on an environmental-economic basis. A methodical approach to substantiate investment decisions in the agriculture of the Sumy region is proposed, which along with considering the environmental factor, is in calculating the elasticities of investor’s income to the environmental-and-economic risks, which increase the correctness of financial decision-making.
 Practical value / implications. Theoretical-and-methodological provisions and conclusions obtained in the study can be used to justify the direction of investment capital in the field of agricultural land use, considering the level of environmental-and-economic constraints.

Operational Self Sufficiency of Bangladeshi Micro Finance Institutions: Do The Managerial Factors Matter?

Microfinance is not only a financial indicator but also a social indicator. The sustainable growth of this area depends to a large extent on its financial as well as operational sufficiency. The goal of this study is to evaluate the managerial factors that influence Operational Self Sufficiency (OSS) of Micro Finance Institutions (MFIs) in Bangladesh. Managerial factors are age of MFIs, size of MFIs, portfolio at risk, operating cost ratio, loan portfolio to assets, borrowing cost ratio, financial cost ratio, breadth of outreach, savings loan ratio and portfolio yield. The study is based on a balanced panel data set of 180 observations from top 20 MFIs which are gathered from yearly published information of sample MFIs over the period of 2009–2017. Collected data have been analyzed by ordinary least squares regression method and fixed effects regression model. The empirical results reveal that operating cost ratio, savings loan ratio and portfolio yield affect the OSS of sample MFIs. Among the variables, portfolio yield has highly significant positive effect; operating cost ratio has highly significant negative effect; savings loan ratio has some significant negative effect on OSS of the selected MFIs. Thus, it can be concluded that managerial factors influence the sustainability of MFIs in terms of OSS. The value of R2 is 47.45%, signifies that the explanatory variables could clarify 47.45% of the variations in OSS. The conclusion recommends that MFIs should increase its loan portfolio by simplifying distribution of loan; increasing portfolio yield; enhancing workforce productivity & efficiency; and optimum allocation of resources to reduce operating costs and to increase yield. It also recommends that MFIs should reduce borrowing costs, which will thereby reduce the total costs. They should not compromise the capability to uphold functioning for the underprivileged. As MFIs are contributing as a cushion of the economic system, they should reconsider taking loan from banks in addition their least cost sources of fund from government.

ANALISIS PERBANDINGAN KINERJA ANTARA PORTOFOLIO OPTIMAL MODEL MARKOWITZ DAN MODEL INDEKS TUNGGAL (COMPARATIVE ANALYSIS OF PERFORMANCE BETWEEN OPTIMAL PORTOFOLIO MARKOWTIZ MODEL AND SINGLE INDEX MODEL)

The purpose of this study is to determine the composition of stocks, the amount of funding proportion, and optimal portfolio performance formed using Markowitz Model and Single Index Model and to determine whether there are differences in optimal portfolio performance established using Markowitz model and Single Index model based on real simulation or test based statistics. The population in this study is the stock of LQ-45 Group in Indonesia Stock Exchange with the number of selected samples of 30 stocks. Sampling is done by using purposive sampling method. This type of research is simulation and verifikatif (hypothesis testing). The data used are secondary data in the form of monthly stock price data from 2016 to 2019. The analysis technique used is descriptive with the application of portfolio analysis using Markowitz Model and Single Index Model. Hypothesis testing was done by using independent sample t-test. Based on the results of analysis on the real simulation of optimal portfolio performance formation found that the composition of stock s and the proportion of funds formed optimally there is a difference between the Markowitz Model and the Single Index Model, the optimal portfolio yield rate using the Markowitz Model is higher than the optimal portfolio yield using the Index Model Single, and optimal portfolio risk levels using the Markowitz model is higher than the optimal portfolio risk level using the Single Index Model. But statistically the test of optimal portfolio performance formed using Markowitz Model and Single Index Model is not significantly different.

The Analysis of Optimal Stock-Bond Portfolio Strategy: Empirical Study in LQ 45 Index Companies and Government Bonds Listed on Indonesia Stock Exchange

This study aims to analyze the strategy in determining the optimal stocks portfolio performance through Single Index Model technique from LQ 45 Index stocks and optimal bonds portfolio performance of bonds through Buy and Hold technique from government bonds in Indonesia Stock Exchange in the 2014-2018 period. The strategy generates performance which generally consists of optimal return (yield), risk and portfolio proportion. The population used in the study are companies stock in LQ 45 Index which produced 23 samples and government bonds produced 7 samples. The methodology research in this study is descriptive analysis. The type of data used in this study is quantitative and data sources of this study is secondary data. Purposive sampling method used as the sampling method. This research found that optimal stock portfolio performance with expected return and optimal portfolio risk values at 0.01497 and 0.006395 while optimal bonds portfolio performance showed optimal portfolio yields and risk with values at 0.090063991 and -0.003063991. The proportions of fund that invested in the optimal stock portfolio are BBCA (27%), GGRM (12%), TLKM (11%), ICBP (14%), PTBA (5%), UNVR (10%), BBRI (9%), BBNI (6%), BMRI (5%) and UNTR (2%) while the optimal bonds portofolio proportions are FR0073 (90%) and FR0072 (10%).

ANALISIS PEMBENTUKAN PORTOFOLIO OPTIMAL PADA SUB SEKTOR PERKEBUNAN DAN SUB SEKTOR PERBANKAN YANG TERDAFTAR DI BURSA EFEK INDONESIA

Penelitian ini bertujuan untuk mengetahui kombinasi portofolio yang optimal pada sub sektorperkebunan dan sub sektor perbankan yang terdaftar di Bursa Efek Indonesia, yang dilakukan denganmelihat tingkat keuntungan yang diharapkan (expected return) dan risiko (deviasi standar) yangdihasilkan oleh kombinasi portofolio setiap tahun. Permasalahan yang dikemukakan dalam penelitianini adalah bagaimana kombinasi portofolio yang optimal dapat dibentuk dari sub sektor perkebunandan sub sektor perbankan yang terdaftar di Bursa Efek Indonesia di tahun 2010-2014. Metodepenelitian ini menggunakan Coefficient of Variation (CV), menentukan probabilitas saham di masing-masing sub sektor pada setiap perusahaan yang dikombinasikan, serta portofolio efisien dengan begitumaka portofolio optimal dapat dibentuk dengan mudah. Hasil penelitian menunjukkan penentuanportofolio dengan menggunakan portofolio optimal tersebut menghasilkan probabilitas saham SMARsebesar 0,05 atau 5% dan probabilitas saham SDRA sebesar 0,95 atau 95% dengan risiko portofoliosebesar 0,460 dan return ekspektasian portofolio sebesar 0,393. Sedangkan kombinasi portofolio yangtidak optimal yang menghasilkan probabilitas saham GZCO sebesar -0,19% dan probabilitas sahamSDRA sebesar 1,19% dengan risiko portofolio sebesar 0,472 dan return ekspektasi sebesar 0,569.

A Canary in the Payout-Rate Coal Mine

In this article, we create a capital markets-based indicator to trigger when a discussion about changing portfolio payout rates may be appropriate. Although the payout rate is often a calendar agenda item for foundations and endowments, volatility in capital markets may cause a deluge of ad hoc payout discussions that may decrease the effectiveness of investment committees. Recent market performance provides a poor foundation for decisions related to a sustainable payout. The most sustainable portion of the investment return is the portfolio yield. We construct a metric using equity and bond market yields as a quantitative leading indicator of when a payout-rate discussion may be warranted. While this methodology might be more of a resource to university-affiliated or public foundations, which have complete discretion over the level of the payout rate, private foundations might find understanding the sustainable payout of a portfolio useful in determining the potential erosion of the corpus caused by an unsustainable payout rate.

A learning curve of the market: Chasing alpha of socially responsible firms

This paper explores stock market reactions to corporate social performance. We construct a value-weighted portfolio based on the list of “100 Best CSR companies in the world” published on the Forbes’ website by Reputation Institute. This portfolio yields statistically significant annual abnormal returns of 1.81% and 1.26%, by controlling for Carhart four factors and Fama-French five factors, respectively (2.41% and 1.84%, respectively for an equal-weighted portfolio). Moreover, such abnormal returns decrease as time passes, especially after the inaugural publication of the CSR lists in 2013. Furthermore, we find that companies with better social performance are more likely to have positive earnings surprises, and that their returns are more sensitive to earnings surprises. The results have three implications: firstly, CSR reputation contributes positively to a firm's short-term superior equity performance; secondly, the CSR lists facilitate market correction of mispricing intangibles such as CSR reputation — abnormal returns decrease as the market gradually learns about the value of firms’ social performance; lastly, the paper contributes to the socially responsible investing (SRI) screens and provides guidance for investors who would like to do well financially by doing good socially.

Microfinance Failures: the Case of Microfinance in West African Economic and Monetary Union

This paper investigates on the determinants of MFIs’failure in WAEMU. It carries out the analysis on the panel data from 2000-2014 by estimating logit regression of this probability. It reveals that the driven factors of the probability of being unsustainable for these institutions are related to the poor risk management and the poor management of the operating expense. These factors are administrative expense ratio and Portfolio at risk for more than thirty days that have a positive effect on this probability. At a lower level, the depth of financial system has also a positive effect. Some factors such as Equity, portfolio yield, and the MFIs type (NGOs and Credit Union) have a negative effect on the probability of being unsustainable. One of the main findings is related to the indicators of outreach used here. In effect, the size of loan and the number of borrowers influence negatively and significantly the probability of failure.

Outreach and performance of microfinance institutions: the importance of portfolio yield

ABSTRACTIn this paper, we examine the interaction between social outreach and financial return in microfinance. Running multivariate regression models and using 1,805 observations of microfinance institutions between 2004 and 2013, we find strong evidence suggesting that institutions with more social engagement – in terms of outreach to the poor – earn higher portfolio yields. We also find that measures of outreach are associated with increased operating expenses. As return figures are influenced by both costs and yield, and because both increase to a similar degree with the depth of outreach, these two effects lead to a zero sum result on return measures. This finding could explain why existing studies assessing the interaction between social outreach and different measures of financial performance in microfinance (such as return on assets/equity, operating expenses, operational self-sufficiency) have not produced consistent results.

Sollten Follower bevorzugt professionellen oder privaten Tradern folgen?

Social trading platforms offer their users an innovative form of delegated portfolio management. Users have the opportunity as so-called traders to share their investment strategies with followers through the platform. Based on comprehensive empirical data of 183 investable portfolios of the social trading platform “Wikifolio”, this study provides new insights on the return and risk characteristics of different types of investors: portfolios of private individuals can achieve significantly higher returns and better risk-return ratios than the portfolios of media companies and professional asset managers. The differences in portfolio yield and risk characteristics could be based on selection and market timing effects.

What affects portfolio yield of microfinance institutions? Evidence from Bangladesh

Despite the success and rapid growth of the microfinance industry worldwide, there has been very little sign of any abatement of the high interest rates. High interest rates in microfinance rescind consumer benefits and limit the outreach of microfinance institutions (MFIs). Hence, the aim of this study is to identify the determinants of portfolio yield by examining a longitudinal data of 169 MFIs from Bangladesh. The data are collected from the annual reports of the Microcredit Regulatory Authority (MRA) and cover the period from 2009 and 2014. Based on empirical results, the study found that sources of funds are optimally used in the microfinance industry in Bangladesh. Among other institutional characteristics and macroeconomic factors, only operating cost and inflation were found to be positively significant to portfolio yield, supporting the conventional views. Policy implications are further discussed.

Analisis Portofolio Optimal Saham Indeks Lq-45 Dengan Model Indeks Tunggal Di Bursa Efek Indonesia

Rational investors invest in efficient stocks, the stocks that have high return with minimum risk. The sample in this study using the stocks in the group LQ-45 index during the period February 2013-July 2013. The purpose of the study was to establish the optimal portfolio and to know the difference between stock returns and the risk of candidate and non-candidate portfolirn On Equity (ROE).The results showed there were 15 stocks that become candidate in a portfolio out of 45 stocks studied with the cut of point value -2.7-7. Optimal portfolio is formed by 15 stocks that have excess returns to beta (ERB) which is greater than the risk-free return (Rf).The largest proportion of funds owned by PT Kalbe FarmaTbk i.e 16,2 %, and the smallest proportion of the funds owned by PT Bank Central Asia Tbk i.e 0,1101288%. Rational investor would prioritize to invest in securities that have a the largest proportion of the funds, because of that large proportion of funds so we will be getting higher profit with the certain risks as well.Investors that will invest theirs funds into these 15 companies that have formes this optimal portfolio would get portfolio profit 2,1-7 and portfolio risk -2.7-7. That portfolio profit is not far different with the expected return of each individual stock. So despite using LQ-45 stocks that have the biggest marketing capitalization and the most liquid infact it has not guarante that investors would gain their expectation of getting portfolio return as what they expected.Risk portfolio of 2,1-7 is smaller than the risk level of each individual stock . Although the establishment of the optimal portfolio yield expected return of portfolio which is not much different with thereturn of individual stock,but still provide the benefit of diversification that is beneficial for reducing the risk of each individual stock