Investment Performance Evaluation Research Articles

Investment Decision Criteria – Bibliometric Analysis

The present study wants to analyze how the criteria underlying the decision to make an investment in the existing articles in the Web of Science are highlighted through bibliometric analysis. The query resulted in the display of 441 scientific articles. A specific filter applied to our selection was the choice of Citation Topics Meso: Economics, Management, Economic Theory to ensure that the analyzed articles are from the economic field. To determine the correlations regarding the countries of origin of the authors, we used the Co-authorship filter of VOSviewer, having a minimum number of 12 documents/country and a minimum number of 10 citations/country, so out of 71 countries only 16 met the conditions. A first analysis of the phrases used in the 441 articles was carried out with the help of the word cloud, from Wordart, regarding the words contained in the title of the article, the author's keywords, plus keywords and summaries. The second analysis was that of the phrase density, it was carried out through the VOSviewer software by applying the cooccurrence filter, for all keywords, with an appearance of at least 9 times, resulting in 4 clusters with a total of 53 items that define the process of taking decisions, analyze the investor's behavior and the structure that makes the investment, define the sources of investment financing and investment performance evaluation modalities and analyze the risk and uncertainty environment specific to investments. The results of our research can be a starting point for other analyses in the decision-making field of investments by providing keywords to start from.

Reflections of Geopolitical Risk on Foreign Direct Investments: The Case of Türkiye

A way to achieve sustainable economic growth in developing countries is to increase investments with domestic savings. However, not every country has an equal opportunity in terms of domestic savings. The desired level of investment expenditures cannot be reached in countries with a savings gap. In this case, foreign direct investment (FDI) becomes more valuable in meeting countries’ investment needs. Nevertheless, companies may not behave very bravely in their investment actions in other countries. There is a considerable risk and uncertainty avoidance in the nature of investment because uncertainty and risk are accepted as harbingers of instability for a country. Since the main goal of companies is to make a profit, they may start thinking that they will not have the opportunity to make a profit in an unstable economy. Hence, the risk perception in the investment environment must be low for developing countries to become attractive for FDI inflows. Geopolitical risks, as well as economic, political, and strategic risks that countries will be exposed to, are important indicators considered in FDI inflows. Literature research shows that investors are aggressive in investing with a profit appetite and, with exceptions, are sensitive to geopolitical risks. In other words, FDI decreases in countries where geopolitical risks tend to increase. The present study tested the validity of this assumption in the literature for Türkiye. The impact of geopolitical risks on FDI was analyzed with the ARDL Boundary Test Approach for the period 1985-2020. FDI inflows were used as the dependent variable, and the Geopolitical Risk (GPR) Index, a measure of geopolitical risk, was used as the independent variable. Moreover, growth, globalization, and inflation are the other independent variables analyzed. The test results demonstrated the negative effect of the increase in the GPR index on FDI inflows. In terms of the results obtained, the study provides an important perspective on the prioritization of the geopolitical risk factor in the evaluation of foreign investment performance.

Evaluation of private investment performance

In Ethiopia, there has been various economic and political reforms for the last ten years which can motivate private investors. Even though, some improvements have been registered as a result of such reforms, the performance of private sectors became low. This study conducted to evaluate the performances of private investment in regional distribution, sector contribution, and ownership structure and employment creation. The result shows that Most of private investment projects are concentrated around Addis Ababa, with manufacturing and service sectors. In Ethiopia, foreign private projects are capital incentive while Domestic private projects have higher share in employment creation. Emerging regions in the country exhibited small number of private projects as compared to other regions. Identified variables for the study includes private investment, inflation rate, abroad money supply, GDP per capital, interest rate, exchange rate, public investment, and external debt. To enhance the analysis, Econometrics model with OLS using multiple regression was applied. The result shows that GDP per-capital, and external debt have significant positive long run effect on private investment, while broad money supply and average exchange rate have negative long run effect. Broad money supply, GDP per-capital, and external debt have significant short run effect.

Multiagent-based deep reinforcement learning for risk-shifting portfolio management

The growing popularity of quantitative trading in pursuit of a systematic and algorithmic approach to investment has drawn considerable attention among traders and investment firms. Consequently, an effective computational method for evaluating potential risk factors and returns is crucial for the development of algorithmic trading strategies. In traditional finance and financial engineering research, statistical approaches have been widely applied to quantitative analysis. Meanwhile, investor demand for quantitative hedge funds has surged worldwide. In the current study, the multiperiod portfolio selection problem was considered in terms of the realistic transaction cost model, which is a major concern for quantitative hedge fund managers. We developed a dedicated multiagent-based deep reinforcement learning framework with a two-level nested agent structure to determine effective portfolio management methods with different objectives. In addition, we proposed a specially-designed reward function for investment performance evaluation and a novel policy network structure for trading decision-making. To efficiently identify specific asset attributes in a portfolio, each agent is equipped with a refined deep policy network and a special training method that enables the proposed reinforcement learning agent to learn risk transfer behaviors. The results revealed the effectiveness of our proposed framework, which outperformed several established or representative portfolio selection strategies.

Are Investment Managers Worth Their Keep? A 7-year Evaluation of Active and Passive Investment Performance of a University Endowment

This study examined the financial performance of Schreiner University’s actively managed endowment and compared the performance to a hypothetical passive investment strategy. From 2014 to 2020, the actively managed endowment produced a cumulative return of 71.7%. In comparison, the passive, index-based portfolio produced a cumulative return of 72.9%. The actively managed portfolio outperformed the passively managed portfolio in four out of seven years but underperformed overall. The performance results of the assets classes were inconsistent throughout the seven-year period. Additionally, a passive strategy of 60% US equities and 40% US bonds would have resulted in a cumulative return of 98.9% over seven years.

Evaluation of Chinese Transport Infrastructure Investment Performance in Countries along the Belt and Road Initiative

Since the launch of the Belt and Road Initiative (BRI) in 2013, Chinese enterprises have invested heavily in transport infrastructure projects. In order to better promote Chinese overseas transport infrastructure investment (TII) and avoid additional risks, it is necessary to scientifically assess the performance of Chinese TII in countries along the BRI and explore the promotion path of Chinese TII performance. For this reason, we used a superefficient slacks-based measurement (SE-SBM) model to calculate Chinese TII performance based on 5 dimensions, including political environment, economic environment, institutional environment, humanistic environment, and social environment. These 5 dimensions were divided into 14 indicators, and we used quantification with indirect data to quantify all indicators. Then, according to the performance value of selected countries, we classified them into high-, medium-, and low-performance areas. Next, combined with the scale of returns and the shadow price of input indicators, we provided the promotion measures of each performance area. Our analysis generates valuable measures to reduce TII risks and better promote the connectivity of countries along the BRI.

On false discoveries of standard t-tests in investment management applications

Financial managers routinely use the one-sample t-test to evaluate whether the mean returns of investment assets, strategies or funds are significantly different from zero. Simultaneously, however, they often ignore the fact that its application is not generally justified, in other words, that its usefulness depends on the properties of the population. We show by Monte Carlo simulation that, especially in skewed and/or autocorrelated populations, test decisions based on the t-test can be severely biased. More specifically, for sample sizes typically used in investment performance evaluation, the probability of falsely diagnosing a significant mean return–the false discovery rate–is significantly higher than the nominal error probability set in testing. We additionally illustrate that the popular empirical practices of (i) replacing the t-quantile with the standard normal quantile and (ii) removing outliers before conducting the t-test have crucial elevating impact on the false discovery rate.

МЕТОДИЧНІ ЗАСАДИ ДІАГНОСТУВАННЯ РЕЗУЛЬТАТИВНОСТІ МОДЕРНІЗАЦІЇ ПІДПРИЄМСТВ У КОНТЕКСТІ РЕАЛІЗАЦІЇ ІННОВАЦІЙНОГО ПОТЕНЦІАЛУ

The growing dynamism of the intellectualization and logistics of business processes is generating demands for updating the toolkit to assess the enterprise modernization performance and realize its innovative potential. It is argued that the evaluation of modernization efficiency and the design of enterprise innovative development strategies should rely on innovation and R&D trends and achievements. An in-depth study of the external and internal environment in which an enterprise operates helps to reveal the patterns and specifics in its innovation potential assessment paradigm. Thus, the framework to assess the enterprise innovation potential efficiency is based on its production, financial and investment performance evaluation. The consistency in modernization performance suggests following the principles of universality and comparability. Since the use of classical innovation efficiency indicators does not allow for considering the qualitative characteristics of modernization changes, a new framework to assess the modernization performance has been developed which is based on economic and mathematical analysis methods and is aimed at building an integrated index. The integrated index of modernization efficiency will help to determine the modernization potential level, the effects from a range of impact factors on the change of the modernization profile, as well as to reveal the trends of innovative development. This contributes to describing the proposed evaluation framework subject to initial enterprise modernization objectives and its strategic priorities for innovative development. Further research should focus on identifying specific methodological approaches to assessing the performance of modernization changes in line with the overall business strategy to enhance the enterprise innovative potential.

An Evaluation Study on Investment Efficiency: A Predictive Machine Learning Approach

This paper proposes a nonlinear autoregressive neural network (NARNET) method for the investment performance evaluation of state-owned enterprises (SOE). It is different from the traditional method based on machine learning, such as linear regression, structural equation, clustering, and principal component analysis; this paper uses a regression prediction method to analyze investment efficiency. In this paper, we firstly analyze the relationship between diversified ownership reform, corporate debt leverage, and the investment efficiency of state-owned enterprises (SOE). Secondly, a set of investment efficiency evaluation index system for SOE was constructed, and a nonlinear autoregressive neural network approach was used for verification. The data of A-share state-owned listed companies in Shanghai and Shenzhen stock exchanges from 2009 to 2018 are taken as a sample. The experimental results show that the output value from the NARNET is highly fitted to the actual data. Based on the neural network model regression analysis, this paper conducts a descriptive statistical analysis of the main variables and control variables of the evaluation indicators. It verifies the direct impact of diversified ownership reform on the investment efficiency of SOE and the indirect impact on the investment efficiency of SOE through corporate debt leverage.

Comparative Analysis of Methods for Evaluating Efficiency of Regional Investment Policy

The article highlights the issues of methodological tools for evaluating the efficiency of regional investment policy. The article provides international experience of investment policy evaluation and presents the evolution of approaches to evaluating the investment policy of Russian regions and the investment climate. Four approaches are outlined on the basis of domestic methods analyzed: cost-result, rating, integral and complex (qualitative and quantitative). The approach based on evaluation of investment performance and the costs incurred is widely used in Russia. The conclusions are drawn from the research findings: the existing approaches to evaluating the efficiency of investment policy at the regional level have disadvantages and use restrictions. The concluding part contains outlined actions aimed at improving the tools and methods for evaluating the efficiency of investment policy of regional units.

Сравнительный анализ потенциальной предпочтительности различных направлений инвестирования

The article offers the evaluation of investment performance in stock markets, money markets, product markets and others. The comparison is based on the «Return-Risk» Model grounded on the fundamental principles of H. Markowitz’s portfolio analysis. The quantitative comparison is conducted on return-risk ratio as well as return-risk variability intervals. In the formed group of leaders, the return-risk ratio was minimal (0,12) for the money market, and maximal (0,43) for the US stock market. The patterns in focus were grouped as follows: 1. High risk aversion: US branch analysis, currency index models, currency index models (sell) and intercontinental branch analysis.2. Medium risk aversion: US stock market, world stick indexes, precious metals market and exchange goods as a whole.3. Low risk aversion: Russia’s stock market. The practical evaluation of «Return-Risk» Models received for various investment patterns proved their practical validity. The empirical estimators of investment horizons computed for various groups of investment tools are of practical use.

Фонды недвижимости. Количественная оценка эффективности инвестирования

Фонды недвижимости. Количественная оценка эффективности инвестирования

Research on Evaluation Indicator of Effective Assets Investment Efficiency of Power Grid Enterprises under Lean Operation Mode

In 2019, State Grid Corporation proposed the strategic goal of “three-type, two-network, world-class”, requiring all units to focus on the company’s investment effectiveness and focus on promoting the high-quality development of the company and the power grid. Based on the analysis of the electricity reform policy and the company’s strategy, this paper establishes an effective asset investment performance evaluation index for the three-tier power grid enterprises in provinces, cities and counties. Through the research on the quantitative method of indicators, a three-level evaluation model of provinces, cities and counties was established to support the evaluation of investment effectiveness of power grid enterprises. This paper takes the province, city and county three-level units as an example, and extracts data to measure and verify. The evaluation results objectively reflect the effectiveness of power grid assets investment of power supply companies at all levels, and propose investment management based on the calculation results.

KAJIAN EVALUASI KINERJA INVESTASI KABUPATEN GARUT

Based on the National Spatial Planning and Spatial Planning of West Java Province in 2010, the role of Garut Regency is related to the spatial structure policy of the West Java region which sets two regional categories, namely the main area and the supporting area, in this case the Garut Regency as the central supporting region support economic growth in the main region together with the regions of Sukabumi and Cianjur Regencies. In the Provincial Spatial Planning plan that shows the dominant allocation of economic activity, Garut Regency is allocated for dry land agriculture activities, production forests, plantations, and fisheries. Investment Development Policy in Garut Regency is stipulated in the Regional Regulation of Garut Regency Number 14 of 2012 Regarding Investment Chapter III Direction of Investment Policy in the Region.
 The purpose of the Garut Regency Regional Investment Performance Evaluation Study is to provide convenience for the Regional Government in this case the Integrated Investment and Licensing Office and various other parties such as the general public, prospective investors in determining the choice of various alternative investment opportunities. the methodology to be carried out in the Garut Regency Investment Performance Evaluation Study, carried out several analyzes. These analyzes can be seen from the potential conditions (natural resources, human resources), supporting infrastructure, policies and economic conditions in the area around the Garut Regency Investment Area.

English

The study appraised the viability of investing in residential real estate submarket in Lagos State, using the apartments in 1004 Estate as case study with a view to providing a guide for investors and portfolio managers on investment decision-making in Lagos. Lagos, a mega city being a point of attraction to real estate investors makes it necessary to undertake real estate investment performance evaluation. To achieve this, the study ascertained the various risk status of each of the property submarkets and the return strength of the various apartments in 1004 Estate. The study further identified the risk adjusted rate of return of the various apartments in 1004 Estate and also examined the potential of diversifying within residential real estate sub-markets. The study depended largely on secondary sources of information. Data were sourced from the books of the company over a sample period ranging from 2010 to 2017. The data collected were analyzed using descriptive and inferential statistics. The findings show that the risk attached to the various apartments is high and there is strong relationship between the apartments’ returns. This implies that the apartments are not fit to be contained in a portfolio. Recommendations from the study are that diversification should be discouraged within a specific real estate submarket as the apartments are usually affected by similar traits.   Key words: Residential property submarket, investment, return, risk.

European Monetary Union bond market dynamics: Pre & post crisis

The Sharpe ratio emerges as one of the most popular metrics used in the evaluation of investment performance despite the wide range of alternatives that have been proposed by academics and practitioners. In the proposed research, risks and returns are analysed on the European Monetary Union bonds market, with different bonds ratings and maturities, in the period from 2005 to 2017. The past and current trends and patterns in bond returns are defined using the methods of statistic correlation and econometric analysis. It was shown that the bond returns are not normally distributed, and that the return on distribution depends on bond maturity and the economic situation in the market. The relation between volatility and bond maturity and the Sharpe ratio appeared to be non-linear and inconsistent over time. However, the hypothesis about the inverse relation between the Sharpe ratio and bond maturity is not supported by the evidence. Finally, with the help of time-series models it was proven that in the period from 2005 to 2017, the returns on European Monetary Union bonds market declined over time. ARIMA models were used to analyse the residuals from the bond returns.

Predicting Trend of High Frequency CSI 300 Index Using Adaptive Input Selection and Machine Learning Techniques

AbstractHigh-frequency stock trend prediction using machine learners has raised substantial interest in literature. Nevertheless, there is no gold standard to select the inputs for the learners. This paper investigates the approach of adaptive input selection (AIS) for the trend prediction of high-frequency stock index price and compares it with the commonly used deterministic input setting (DIS) approach. The DIS approach is implemented through computation of technical indicator values on deterministic period parameters. The AIS approach selects the most suitable indicators and their parameters for the time-varying dataset using feature selection methods. Two state-of-the-art machine learners, support vector machine (SVM) and artificial neural network (ANN), are adopted as learning models. Accuracy and F-measure of SVM and ANN models with both the approaches are computed based on the high-frequency data of CSI 300 index. The results suggest that the AIS approach using t-statistics, information gain and ROC methods can achieve better prediction performance than the DIS approach. Also, the investment performance evaluation shows that the AIS approach with the same three feature selection methods provides significantly higher returns than the DIS approach.

Characteristics-Based Factors

Recent studies have proposed a large set of powerful characteristics-based factors in the stock market. This study examines the pricing of these factors using portfolios that are formed by directly sorting stocks based on their exposure to these factors. These beta-sorted portfolios have very large ex post factor beta spreads. However, the return spreads between high- and low-beta firms are typically tiny and insignificant (on average, 0.01% per month). More important, we show that the differences between factor-adjusted returns and characteristics-adjusted returns for these beta-sorted portfolios are both economically and statistically significant at about 0.41% per month. In addition, factor-adjusted returns and characteristics-adjusted returns can be significantly different for a large number of anomalies and mutual funds. Our results thus urge cautions regarding the common practice of using factor models such as adjusting for investment style, performance evaluation, and performance attribution.

Research on the investment performance evaluation of corporate venture capital with intuitionistic fuzzy information

Corporate venture capital refers to the direct venture investment in private companies made by non-financial corporations with specific core business. Along with rapid growth of Chinese economy, domestic venture capital has gone through a fantastic development among which corporate venture capital is an outstanding one. The study on the different types of venture captital, especially corporate venture capital, is required by the establishment and improvement of the mutiple-level capital market in China. Only on the basis of through understanding of the traits, advantages and disadvantages of corporate venture capital evaluation, we can set a better platform for its further development, contributing to the promotion of the entire venture capital market. In this paper, we utilize Hamacher operations to develop some intuitionistic fuzzy aggregation operators: intuitionistic fuzzy Hamacher weighted geometric (IFHWG) operator, intuitionistic fuzzy Hamacher ordered weighted geometric (IFHOWG) operator and intuitionistic fuzzy Hamacher hybrid geometric (IFHHG) operator. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the intuitionistic fuzzy multiple attribute decision making problems for investment performance evaluation of corporate venture capital. Finally, a practical example for investment performance evaluation of corporate venture capital is given to verify the developed approach and to demonstrate its practicality and effectiveness.

An Evaluation of Investment Performance of Private Life Insurance Industry in India

Data Envelopment Analysis (DEA) model is used to provide valuable information on investment efficiency of private life insurance industry in India. This study utilizes two inputs (shareholders’ investments and policyholders’ investments) and two outputs (net returns on investments to the shareholders and net returns on investments to the policyholders). This study focuses upon 20 private life insurance companies operating in India over a period of 4 years from 2010-11 to 2013-14. Since this study attempts to maximize output, an output oriented DEA model is used. The study finds that investment efficiency of private life insurance industry has improved on Banker, Charnes and Cooper (BCC) model and Charnes, Cooper and Rhodes (CCR) model. The study further highlights that during all years under study, 15% to 40% life insurance companies have been found on the CRS frontier and 40% to 60% life insurance companies have been found on the VRS frontier. With regard to scale efficiency issues, 15% to 40% companies have een operated at their most productive scale over the study period.