Investment fund selection techniques from the perspective of Brazilian pension funds

ABSTRACT The aim of this article was to evaluate the effectiveness of investment fund selection techniques from the perspective of Brazilian pension funds. Asset liability management (ALM) and liability driven investment (LDI) strategies are usually adopted to guide pension fund managers in relation to strategic allocation in asset classes that should compose their investment portfolios and to the liquidity needed in each period, but not specifying in which assets to allocate resources from among the infinity of assets available in the financial market. This article contributes to tactical management in the fixed income and stock segments outsourced via funds and demonstrates that adopting simple indicators can increase investment performance. The article broadens the knowledge on pension fund investment decisions and creates confidence in the adoption of the Sharpe ratio as a technique for choosing investment funds. We analyzed the returns obtained by hypothetical portfolios built using the following techniques: (i) the Sharpe ratio; (ii) the alpha of a multifactor model; (iii) data envelopment analysis (DEA) efficiency; and (iv) the different combinations of these techniques. We considered information on 369 funds from 2013 to 2018, adopting 12 temporal windows for choosing and re-evaluating the portfolios. The returns obtained were compared with the mean actuarial goal of the benefits plans administered by the pension funds, by means of the unplanned divergence (UD). When outsourcing pension fund investments in fixed income and stock investment funds it was verified that the Sharpe ratio contributes significantly to pension fund performance, compared with other indicators and techniques or a combination of them.

European Option Pricing under Wishart Processes

This study deals with a single risky asset pricing model whose volatility is described by Wishart affine processes. This multifactor model with two dependency matrices describing the correlation between the asset dynamic and Wishart processes makes it more flexible enough to fit the market data for short or long maturities. The aim of the study is to derive and solve the call option pricing problem under the double Wishart stochastic volatility model. The Fourier transform techniques combined with perturbation methods are employed in order to price the European call options. The numerical illustrations on pricing predictions show similar behavior of price movements under the double Wishart model with respect to the market price.

Advancing the multifactor model of Stochastic Frontier Analysis

The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.

How to Explain the Cross-Section of Equity Returns through Common Principal Components

In this paper, we propose a procedure to obtain and test multifactor models based on statistical and financial factors. A major issue in the factor literature is to select the factors included in the model, as well as the construction of the portfolios. We deal with this matter using a dimensionality reduction technique designed to work with several groups of data called Common Principal Components. A block-bootstrap methodology is developed to assess the validity of the model and the significance of the parameters involved. Data come from Reuters, correspond to nearly 1250 EU companies, and span from October 2009 to October 2019. We also compare our bootstrap-based inferential results with those obtained via classical testing proposals. Methods under assessment are time-series regression and cross-sectional regression. The main findings indicate that the multifactor model proposed improves the Capital Asset Pricing Model with regard to the adjusted-R2 in the time-series regressions. Cross-section regression results reveal that Market and a factor related to Momentum and mean of stocks’ returns have positive risk premia for the analyzed period. Finally, we also observe that tests based on block-bootstrap statistics are more conservative with the null than classical procedures.

Risk and Performance of European Green and Conventional Funds

This paper analyzes how the risk-adjusted returns of green funds compare to those of conventional funds, between the years 2005 and 2020 for the European Union countries. Additionally, we tested how the performance of green funds correlates to the business cycle, subdividing their performance through expansionary and recessionary times. The findings are summarized as follows: our regression results demonstrated green and conventional funds exhibiting negative abnormal adjusted-returns against the developed world market benchmark for the single-factor and multifactor models. For the European market benchmark, we found environmental mutual funds presenting a positive performance for both models and conventional funds displaying negative results for the single-factor model and positive results for the multifactor model. The factor loadings for green funds indicated a negative load on momentum, book-to-market (HML) and size (SMB) factors, revealing a higher exposure to big and value companies. Subsampling per business cycle exhibited green mutual funds providing higher risk-adjusted returns to investors during crisis periods and mixed results for the non-crisis periods.

Market Premium and Macroeconomic Factors as Determinants of Industry Premium: Evidence from Emerging Economies

In this study, we examine the equity (industry) premium of seventeen nonfinancial sectors covering sample 306 firms using monthly data from January 2002 to December 2018. Two-stage least square (2SLS) method is applied to estimate the macro-based multifactor model. It is found that the market premium and the interest rate factors are significantly affecting the industry equity premium of all the nonfinancial sectors. However, there exists a positive effect of other macroeconomic variables such as money supply, foreign direct investment, and industrial production which is different for the different sectors based on its nature of product and services they offered. The industries based on their product development which are linked to particular macroeconomic variables have more effect than others such as increase in money supply which cannot increase the sale of pharmaceutical products until needed. Similarly, an interesting insight reveals that industries producing seasonal goods, e.g., food producing, are not very much affected by macroeconomic variables but the change in seasons and similar results also revealed for tobacco industry.

Physical Activity Level, Insomnia and Related Impact in Medical Students in Poland

Background: Specific academic environment and time spent on learning may lead to sleep deprivation and a sedentary lifestyle. Insomnia is the most common sleep complaint. The purposes of this study were to describe the prevalence of insomnia in medical students, and to examine physical activity levels and other behavioral factors associated with insomnia in this population group. Methods: We included 308 medical students from Poland. The International Physical Activity Questionnaire (IPAQ) was used to assess physical activity levels and the Athens Insomnia Scale (AIS) was used to assess insomnia among students. A multifactor model of analysis was used to analyze variables related to insomnia. Results: A share of 19.2% of medical students were inactive. Insomnia was reported by 36.8% of students. In the multifactorial model, variables such as smoking cigarettes (ß = 0.21, p < 0.001), consuming energy drinks several times a month (ß = 0.21, p = 0.024), or daily stress (ß = 0.44, p < 0.001) had a negative impact on the quality of sleep of medical students. Conclusions: Most medical students are physically active, however, approximately one-third of the medical students experience insomnia. This sleep problem is reported more often in students who experience daily stress or smoke cigarettes.

Multifactor model of the development of digitalization of corporate business processes

This article provides the results of assessing the factors that impact the cross-sectoral economic and technological effects in the development of digitalization of business processes. The goal of this work is to form a multifactor model for the development of digitalization of corporate business processes and determine the degree of impact of the factors included in this model. The author outlined and tested several hypotheses, the general idea of which is reduced to an assumption that at current stage of economic development in Russia, corporations are actually subject to the emergence of trend in the dynamically changing digital world, which requires quick and effective response to the digital development by increasing investment in digital technologies and intensifying their use in business processes. The empirical framework is comprised on the data provided by the Institute for Statistical Studies and Economics of Knowledge of the Higher School of Economics, as well as Federal State Statistics Service on the current state of digital and business activity. The author conducts a regression analysis for assessing the importance of factors included into the model.; advances and process the hypotheses on the influence of factors upon the index of digitalization and the level of corporate business activity. The acquired results serve as the evidence base for most of the advanced hypotheses, thereby proving the theoretical assumption on the existence of certain consequences of the digital business development. The built multifactor model for the development of digitalization of corporate business processes and assessment of importance of the factors included therein would allow the companies to develop proper solutions aimed at increasing the level of digitalization. The new positions directly depend on the continuous technological changes. As a result, the gap between business needs and competencies of the workforce appears to be the key challenge for the companies.

INCREASING PRODUCTIVITY OF INTERNATIONAL IT-COMPANIES IN THE CONCEPT OF STAFF MARKETING

Labor productivity is one of the main indicators of personnel marketing, which is the basis of labor management. The factors of increase of labor productivity are considered, the attention is focused on models of measurement of labor productivity: multifactor, normative and multicriteria. Thus, the multifactor model is mostly based on reporting data and uses only coefficients and indices to measure performance. The normative method is a process in which employees determine the meters (or their substitutes), coefficients and/or performance indices, and then develop a system for measuring, evaluating, monitoring and improving them. Having a list of performance measures of normative and multifactor methods, we can use the multicriteria method at the following stages of work: determination of performance evaluation criteria; assessment of the relative importance of the criteria; combining performance graphs with the significance of criteria. Advantages and disadvantages of each method were given. The peculiarities of such methods as motivation and nudging were looked through and the magnitude of their impact on the productivity of specialists in the field of information technology are considered. The “Humu Company” has developed a product based on nudge theory, which is actively used by IT companies. Using artificial intelligence and team performance data, “Humu” identifies areas to focus on and then facilitates steps for teams to increase their morale, engagement and efficiency. The activity of the world's leading IT companies is analyzed. They are engaged in software production and provide outsourcing services. Development of servers, platforms and applications are one of the most common areas of activity of companies with the highest revenue in 2020. Regarding the availability of information, productivity was analyzed as the amount of income they bring per employee. An attempt to develop a mechanism to increase productivity in international IT companies through a system of regular feedback is made. Research shows that feedback reduces stress, helps build trust in the team and performs well.

COVID-19, Stock Market, Exchange Rate, Oil Prices, Unemployment, Inflation, Geopolitical Risk Nexus, the Case of the BRICS Nations

This chapter attempts to study the impact of the COVID-19 pandemic on the stock markets of the BRICS nations. Such an exercise will have an important bearing on portfolio allocation in the context of the BRICS. The major contribution of the chapter in the extant literature is to examine based on the multifactor model of the capital asset pricing theory, how uncertainty owing to the pandemic interplay with the geopolitical index to impact the stock market of the BRICS. Further, the major macroeconomic factors are used as control variables. The daily observations were used from 31 December 2019 to 30 December 2020. The results based on the quantile regression model demonstrate the asymmetric response of the stock market to the pandemic. The policy implication that follows from this study is the need for strategic intervention of the central bank to ease the liquidity challenges in the crisis period.