Average Annual Return Research Articles

Do clean energy stocks diversify the risk of FinTech stocks? Connectedness and portfolio implications

The FinTech sector is growing rapidly, prompting a need to explore effective investment diversification strategies for stocks in this sector. The existing literature has identified the benefits of using clean energy stocks to diversify stock portfolios and the purpose of this research is to estimate how useful clean energy stocks are for diversifying an investment in FinTech stocks. This study uses a QVAR model to estimate the dynamic return connectedness between FinTech stocks and clean energy stocks for the period September 2016 to April 2024. Total connectedness is time varying and is higher in the tails than at the median. The onset of the COVID-19 pandemic had a large but short-term impact on connectedness. Under normal market conditions, systemic risk increases by 3.5% per year. FinTech is a net transmitter of shocks to nuclear energy but is mostly unaffected by shocks from wind, solar, and nuclear energy stocks illustrating the diversification benefits of these sub-sectors. Portfolio analysis shows that adding solar, wind, and nuclear energy to a portfolio with FinTech can produce higher risk adjusted returns and lower drawdown than an investment solely in FinTech stocks. These results are robust across various portfolio rebalancing frequencies (daily, weekly, monthly). For example, a minimum connectedness portfolio rebalanced daily has an average annual return of 11% and a Sharpe ratio of 0.37. These values are higher than their respective values for an investment solely in FinTech stocks (5.4%, 0.11). Thus, clean energy stocks do provide diversification benefits for investments in FinTech stocks.

Solar irrigation potential in Sub-Saharan Africa: a crop-specific techno-economic analysis

In this study, we introduce an integrated modeling framework that combines a hydrologic model, a biophysical crop model, and a techno-economic model to assess solar irrigation potential in Sub-Saharan Africa (SSA) based on seven commonly grown food crops-maize, wheat, sorghum, potato, cassava, tomato, and onion. The study involves determining the irrigation requirements, location-specific capital investment costs, crop-specific profitability, and the cropland area under various cost scenarios (low and high) and soil fertility (low, moderate, near-optimal, and optimal) scenarios. Our research reveals considerable potential for solar irrigation, with profitability and viable cropland areas that vary according to crop type, irrigation system cost scenarios, and soil fertility levels. Our assessment shows that approximately 9.34 million ha of SSA’s current rainfed cropland are hydrologically and economically feasible for solar irrigation. Specifically, maize and onion display the lowest and highest viability, spanning 1–4 million ha and 29–33 million ha, respectively, under optimal soil fertility conditions. In terms of profitability, maize and onion rank as the least and most economically viable crops for solar irrigation, yielding average annual returns of $50-$125/ha and $933-$1450/ha, respectively, under optimal soil fertility conditions. The lower and upper bounds of profitability and cropland range correspond to high-cost and low-cost scenarios, respectively. Furthermore, our study reveals distinct regional differences in the economic feasibility of solar irrigation. Eastern Africa is more economically favorable for maize, sorghum, tomato, and cassava. Central Africa stands out for onion cultivation, whereas West and Southern Africa are more profitable for potato and wheat, respectively. To realize the irrigation benefits highlighted, an energy input of 940-2,168 kWh/ha/yr is necessary, varying by crop and geographic sub-region of the SSA sub-continent. Our model and its results highlights the importance of selecting the right crops, applying fertilizers at the appropriate rates, and considering regional factors to maximize the benefits of solar irrigation in SSA. These insights are crucial for strategic planning and investment in the region’s agricultural sector.

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Because failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving, and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive AI attempts (4, 5, or 6 services), or the production threshold (20, 15, or 10 kg of milk/d) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves, and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services, and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents (CO2-eq). Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg of milk/d, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AI to €167,670 per 100 cows at a maximum of 6 AI, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/d to €168,190 per 100 cows at a threshold of 20 kg/d. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2-eq per kg of fat- and protein-corrected milk (FPCM) with an increase in a maximum number of AI from 4 to 6 AI. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/d to 0.928 kg CO2-eq/kg FPCM at a threshold of 10 kg/d. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

Greenhouse Gas Emissions, Carbon Footprint, and Grain Yields of Rice-Based Cropping Systems in Eastern China

A multiple cropping system is beneficial for utilizing natural resources, while increasing the grain production and economic outputs. However, its impact on greenhouse gas emissions is unclear. The objective of this study was to evaluate the influence of rice-based cropping systems on methane (CH4) and nitrous oxide (N2O) emissions, the carbon footprint (CF), grain yields, and net economic returns in eastern China. Four treatments were applied: rice–fallow (as a control), rice–milk vetch, rice–wheat, and rice–rapeseed. Methane and N2O emissions were measured every 7 days via static chamber and gas chromatography methods from the 2019 rice season to the 2021 non-rice season. The CF was calculated based on the life cycle assessment. The results showed that multiple cropping systems significantly increased the annual grain yield by 1.2–6.4 t ha−1 and the annual CH4 and N2O emissions by 38–101 kg CH4-C ha−1 and 0.58–1.06 kg N2O-N ha−1, respectively. The average annual net returns for rice–wheat and rice–rapeseed were 131–150% greater than those for rice–milk vetch and rice–fallow. The annual CFs increased in the following order: rice–wheat (19.2 t CO2-eq ha−1) > rice–rapeseed (16.6 t CO2-eq ha−1) > rice–milk vetch (13.9 t CO2-eq ha−1) > rice–fallow (11.5 t CO2-eq ha−1). The CH4 emissions contributed to the largest share of the CF (60.4–68.8%), followed by agricultural inputs (27.2–33.7%) and N2O emissions (2.9–5.9%). Moreover, nitrogen fertilizer accounted for 65.6–72.4% of the indirect greenhouse gas emissions from agricultural inputs. No significant difference in the CF per unit grain yield was observed between the four rice-based cropping systems. The CF per net return of rice–wheat and rice–rapeseed significantly decreased by 37–50% relative to that of rice–fallow and rice–milk vetch. These findings suggest the potential to optimize rice-based cropping systems for environmental sustainability and grain security.

The Main Scientific and Practical Directions and Priorities of Management and Development of the Digital Economy at the Enterprises of Modern Shipbuilding

Theoretical reference: The article outlines some of the main theoretical and empirical aspects of studying the process of digitalization and human capital management of industrial economic entities, including considering the main structural elements of human capital formation/functioning, and the synergistic effect of various structural elements of human capital. Method: The article discusses some main analytical methods for assessing the effectiveness of digitalization processes, including the market capitalization method, a method for assessing intellectual capital based on average annual return on assets (ROA), and a method for estimating the cost of human resources based on computational and analytical indicator of information productivity. Results and Conclusion: The article discusses results around trends in digital transformation for shipbuilding companies and conclusions that the digital economy determines the new role of human resources and capital and that people remain a key success factor for digital enterprises. Implications of research: The research helps outline the main directions and priorities of human resource management and digital economy development at modern shipbuilding enterprises. Originality and value: The research provides a comparative analysis of theoretical and empirical aspects of digitalization and human capital management in the context of the shipbuilding industry, examining computational methods for evaluation. This contributes new perspectives and analysis specific to this industry context.

A portfolio trading system using a novel pixel graph network for stock selection and a mean-CDaR optimization for portfolio rebalancing

Due to the complexity and dynamic nature of financial markets, portfolio management tasks require continuous adaptation with market intelligence. Furthermore, to make profitable trading decisions, it is essential to predict the future performance of the market. To that end, this study proposes a dynamic portfolio trading system in two stages: stock trend prediction and portfolio optimization. In the first stage, although many researchers proposed powerful classification models to predict BUY/SELL trading signals, some scholars only focused on converting time series' features into multichannel images without considering any spatial relationships between features. Considering the relational capacity of graphs, this study proposes a novel image-based classification model, called Pixel Graph Network (PGN), to analyze the constructed images with propagating information from all neighboring pixels, build up a representation of the images as special graphs, and get advantages of a graph-based learning algorithm. In the second stage, stocks with predicted BUY trading signals in the following days, are fed into the Mean–Conditional Drawdown at Risk (M-CDaR) optimization model to prevent any significant drawdown of the investment portfolio. Moreover, a hierarchical feature selection algorithm has been proposed, combined with a continuous trend labeling method to improve the efficiency of the training process. To demonstrate the superiority of our proposed PGN model in comparison with benchmarks, 18 stocks from the New York Stock Exchange (NYSE) are used for numerical experiments. The obtained results show the improvement and effectiveness of the proposed model in both stock trend prediction and portfolio optimization. In terms of financial performance, the proposed PGN+M-CDaR portfolio-based trading system achieves an average annual return of 112%, an average annual Sortino ratio of 10.78, and an average annual Sharpe ratio of 2.79 which are promising to achieve substantial profits while mitigating downside risk.

The Impact of Inflation on Real Estate Investment Perfomance And Effective Investment Decisions

Purpose: This study aims to examine the impact of inflation on key variables of real estate investment performance and investment decisions. Theoretical Reference: This paper considers several models of real estate investment performance indicators because the effect of inflation on key variables of real estate investment performance is an important factor in investment decisions. Since effective investment decision is key to avert investment loss especially during inflation period, this paper follows the suggestions by Otegbulu (2022) and Georgiv, et al (2002) that property incomes and values are not static during periods of inflation bur responds to economic dynamics, and could infact trigger favourable investment opportunities in real estate. This paper therefore follows these models/suggestions of Otegbulu (2022) and Geoargiv, et al, (2002) to examine several real estate investment to offer appropriate reflection of how inflation impacts of incomes from real estate investment. Method: Data collected were analysed using Pearson Correlation Analysis to determine the relationship between inflation rate and real estate investment performance (measured by annual returns). Regression analysis was also employed on the data to determine the level of contribution or degree of impact of inflation on real estate performance. Also data collected on the exchange rate and real estate performance over the study period were analysed using Pearson Correlation Analysis to determine the relationship between exchange rate and real estate investment performance (measured by annual returns on investment). Regression analysis was also employed on the data to determine the degree of impact of exchange rate on real estate investment performance. Data collected for the analysis and hypotheses testing were secondary data over a period from 2005 – 2022. Result: The study reveals that real estate investment market generates average total annual returns of 21.39% under average inflation rate of 12.5%. The test statistics (Pearson Correlation) results shows that the higher the inflation rate, the lower the performance of the real estate investment. Also, the study reveals that as inflation persists causing exchange rate fluctuations, the test statistics (Pearson Correlation) results shows that higher exchange rate causes lower performance of real estate investment. This could be because more than 90% of the real estate construction materials in the study are imported. Conclusion: It is clear and obvious that inflation impacts highly on real estate and capable of distorting projections in property investment. Rational investors must therefore factor in inflation risk in investment decisions. The study has shown that inflation has significant impact on annual returns of real estate and consequently affects investment performance. The study concluded that the higher the inflation, the lower the performance of the real estate investment and that the continuous rise in inflation rate reduces the purchasing power of the local currency leading to local currency devaluation. Also, it was concluded that higher exchange rate causes lower performance of the real estate in terms of annual returns. Research Implications: One of the major implications of the findings from this study is that as inflation raises the volatility of local currency which adversely affect the cost of construction, real estate investment performance is hindered. The risk element increases which could lead to project cost over-run, abandonment or increased vacancy rate. Investors become skeptical in making investment decisions because of uncertainties. Policy makers should put in place policies and guidelines that will attract cross-border investors who can take advantage of the local currency devaluation to improve their real estate investment portfolios. Originality/Value: The relationship between inflation rate, exchange rate and real estate performance (measured by rate of returns on the investment) is of great concern for real estate practitioners and investors. The study is original well thought efforts of the authors as contribution to real estate practice and education in developing economies currently being threatened by rising inflation. It is believed that this study will be very useful to global investors who will like to invest in the study area in particular and other emerging markets in general.

Assessment of the Profitability Indicators of Armenian Commercial Banks and the Forecast of Possible Scenarios to Increase Profitability

Purpose: The main purpose of the study is the comparative analysis of total capital, total assets, net profit, return on assets (ROA), return on equity (ROE) and net interest margin (NIM) of 17 commercial banks operating in Armenia for several years are presented, the advantages and disadvantages of the banks with high and low results in the above-noted indicators have been briefly commented on.
 
 Theoretical framework: Currently, the banking system of Armenia is the most developed one in comparison with other sectors of the economy, as the processes of attracting deposits, providing loans and fulfilling the standards set for commercial banks are regulated in line with the world experience. The object of study is operational environment of the banks.
 
 Design/methodology/approach: The profitability indicators are considered to be the most basic tool for assessing the efficiency of operations carried out by commercial banks. Methodological tools of the study methods were interest income, interest expense and average annual return on profitable assets, which were analyzed separately.
 
 Findings: The relevance of this scientific problem decision is that the negative consequences the COVID-19 pandemic within the business environment of the Armenian banking system have been studied.
 
 Research, Practical & Social implications: In the context of new economic relations, the banking system holds an important part in ensuring the economic growth and economic development of any country, including the Republic of Armenia. Possible ways to increase the profitability of the Armenian banking system were suggested in this study, the existing challenges of the banking system were identified.
 
 Originality/value: Based on the results of the research of the profitability indicators of the RA banking system and the conclusions drawn, several ways of increasing the profitability of banks were proposed.

Extreme downside risk in the cross-section of asset returns

Extreme movements in financial markets are not always reflected equally in individual stocks. Identifying which firms are unable to absorb shocks is a challenge. This paper considers extreme downside risk, an extension to Ang et al.’s (2006) downside risk framework, and the value in separating the sensitivity between extreme and non-extreme downside risk. I find that the cross-sectional average annual excess return between high and low extreme downside exposure stocks is around 3.9%. The extension differentiates itself for young firms or firms that have not experienced a severe crisis, where the risk premium ranges from 2.4% to 10.4%.

Анализ инвестиционной привлекательности сферы недвижимости в условиях санкций

For many decades, solving problems in the field of investment attractiveness has been of great interest and demand at both the micro and macro levels. After all, the development and improvement of the enterprise, industry, region and the state as a whole largely depends on financial investments and investments. So, a special priority in this development is the real estate sector. The achievements of high and high-quality results in this industry contribute to the expansion of urban infrastructure, an increase in the urban population and, as a result, the growth of small and medium-sized businesses, which in one way or another make a significant contribution to the country's economy. This article is aimed at identifying trends and dynamics of investment attractiveness of the real estate sector in modern conditions. The article discusses the essential characteristics and the role of investment attractiveness, the dynamics of the total volume of investments in real estate in the Russian Federation and the volume of investment transactions. The main part of the article also provides an analysis of the volume of real estate investments by segment and an analysis of the average annual return on investment by regions of the Russian Federation. According to the results of the analysis, the regions that have the highest profitability from investing in real estate are determined. The recommendations and target prices for leading companies in the housing and construction market under the conditions of the sanctions policy are described. Also, based on the conducted research, companies that have maintained leading positions in the industry for several years are identified. And in conclusion, conclusions are drawn regarding the state and functioning of the Russian real estate market, as well as the effectiveness of state programs aimed at mitigating and eliminating the impact of external restrictive measures.

Assessment of the Profitability Indicators of Armenian Commercial Banks and the Forecast of Possible Scenarios to Increase Profitability

Purpose: The main purpose of the study is the comparative analysis of total capital, total assets, net profit, return on assets (ROA), return on equity (ROE) and net interest margin (NIM) of 17 commercial banks operating in Armenia for several years are presented, the advantages and disadvantages of the banks with high and low results in the above-noted indicators have been briefly commented on. Theoretical framework: Currently, the banking system of Armenia is the most developed one in comparison with other sectors of the economy, as the processes of attracting deposits, providing loans and fulfilling the standards set for commercial banks are regulated in line with the world experience. The object of study is operational environment of the banks. Design/methodology/approach: The profitability indicators are considered to be the most basic tool for assessing the efficiency of operations carried out by commercial banks. Methodological tools of the study methods were interest income, interest expense and average annual return on profitable assets, which were analyzed separately. Findings: The relevance of this scientific problem decision is that the negative consequences the COVID-19 pandemic within the business environment of the Armenian banking system have been studied. Research, Practical & Social implications: In the context of new economic relations, the banking system holds an important part in ensuring the economic growth and economic development of any country, including the Republic of Armenia. Possible ways to increase the profitability of the Armenian banking system were suggested in this study, the existing challenges of the banking system were identified. Originality/value: Based on the results of the research of the profitability indicators of the RA banking system and the conclusions drawn, several ways of increasing the profitability of banks were proposed.

Economic Analysis of Goat Enterprises in Kathmandu District

This study was conducted in Kathmandu district to perform comparative economic analysis of small and commercial goat enterprises. In the study the average annual return from large enterprises was found to be six times greater than that of small enterprises. The average annual fixed cost of small enterprises was found to be one tenth of that of commercial goat enterprises. The total average annual variable cost of small enterprises was found comparatively less than that of commercial enterprises, which is more than five times less. The per unit goat cost for the small enterprises is also twenty-five hundred less than that of commercial enterprises. The gross profit per year of small enterprise was around sixty thousand rupees with 9.5% gross profit margin ratio while in commercial goat enterprises gross profit per year accounted almost 4 lakh with gross profit margin ratio 10.45%. Similarly, the average benefit cost ratios for small and commercial enterprises were found similar i.e. 1.10 and 1.12 but break even points varied widely as 18.36% and 56% respectively. The study concluded that there is no significant difference in production costs and income among small and commercial goat enterprises present in Kathmandu district testing at 5% level of significance. It also reveals positive aspects of small goat enterprises and at the same time suggests low functional efficiency of commercial goat enterprises in Katmandu district.

High return and low risk: Shaping composite financial investment decision in the new energy stock market

As an emerging market, the new energy stock market is characterized by high volatility and instability, and investors seeking to make investment decisions face significant challenges. To enable investors to diversify risk and obtain more consistent high returns, we have built a composite financial investment decision system that combines portfolio selection, trend forecasting, and quantitative trading. The system takes a sequential, rolling Sharpe ratio calculation and dynamically selects portfolios to reduce risk from market changes and achieve optimal portfolio diversification. Then, the variational mode decomposition (VMD)-bidirectional gated recurrent unit (BiGRU) model is introduced to predict the trend of the portfolio and quantify the trades of the portfolios. Experimental results show that the system can obtain an average annual return of up to 758,508 CNY with a principal capital of 30,000 CNY. Compared with observing the investment ratio of the portfolio statically, selecting the portfolio by calculating the Sharpe ratio continuously and rolling can improve the portfolio return and diversify the risk. In terms of trend forecasting, VMD-BiGRU is shown to greatly improve forecasting performance compared to single gated recurrent unit (GRU) or long short-term memory (LSTM) models. Compared with human-driven trading, quantitative trading has been shown to have the advantage of short holding times, low risk, and high returns by capturing trading opportunities promptly based on the results obtained from predictive models.

The Pollution Premium

ABSTRACTThis paper studies the asset pricing implications of industrial pollution. A long‐short portfolio constructed from firms with high versus low toxic emission intensity within an industry generates an average annual return of 4.42%, which remains significant after controlling for risk factors. This pollution premium cannot be explained by existing systematic risks, investor preferences, market sentiment, political connections, or corporate governance. We propose and model a new systematic risk related to environmental policy uncertainty. We use the growth in environmental litigation penalties to measure regime change risk and find that it helps price the cross section of emission portfolios' returns.

Impact of the Covid-19 pandemic on the choice of investment strategies and investors’ behavior on the Warsaw Stock Exchange – 2017-2020 research findings

Purpose: This paper attempts to reveal the potential differences between the portfolios of dividend-paying companies with growth or value potential and the same portfolios fortified with the financial instruments replicating precious metals or real estate price behavior in a turbulent global economy. Design/methodology/approach: The research objective of this paper is accomplished by means of a thorough literature analysis. Moreover, the authors employ comparative analysis methods to explore the features of stock portfolios held by dividend-paying companies with value or growth potential and portfolios of the companies that are fortified with financial instruments replicating the price behavior of precious metals or real estate and uncover the similarities and differences. Research of the characteristics of financial instrument portfolio variants and comparison between them is conducted by means of standard deviation of the rate of return, coefficient of variation, the Pearson correlation coefficient and the Spearman's rank correlation coefficient. It was also assessed whether the estimated correlation coefficients were statistically significant through the use of a non-parametric correlation coefficient significance test. Findings: The results of the empirical analyses conducted here reveal that the average annual return of portfolios held by dividend-paying companies with value and growth potential is lower than ETFs replicating precious metals. Furthermore, during the turbulent economy of 2020, the inclusion of precious metal assets boosted the rates of return of the Polish dividend-paying companies portfolios. Research limitations/implications: The research was carried out on a limited number of the analyzed companies. Therefore, it could be biased, due to the deterministic stock sampling method. Practical implications: Knowledge of the similarities and differences between dividend- paying companies with value or growth potential and the risk diversification of such companies’ stock portfolios by means of instruments replicating the price behavior of precious metals or real estate is of great importance to both the investors and investment funds' boards. Consequently, one can make better investment decisions. Social implications: Among the paper's social implications, the most important appears to be a possible change in the investors' attitude towards dividend-paying companies with value potential and financial instruments replicating the price behavior of precious metals or real estate. Ultimately, investors’ needs could be better addressed. Originality/value: What is new in the paper is the stock comparison of dividend-paying companies' with value and growth potential with precious metals and real estate-based instruments. The paper also attempts to compare efficiency of investing in the portfolio variants, capturing the effect of the SARS-CoV-2 pandemic, thereby filling our knowledge gap. Keywords: COVID-19 pandemic, precious metals, ETFs, Spearman rank correlation coefficient. Category of the paper: Research paper.

La renta del tabaco, fuente principal de financiación de la Corona en Canarias durante el s. XVIII. Análisis de ingresos y costes

The income or tobacconist was the main source of financing of the Crown in the Canary Islands during the s. XVIII. From its direct administration in 1718 and until the end of the century it generated positive returns that substantially exceeded those obtained by other royal revenues. This paper addresses the main income and costs of the tobacconist and determines its average annual return depending on whether or not the annual income exceeded the figure of reales de vellón 1.5 million of whole value fleece.

Implementation of Magic Formula and Acquirer’s Multiple Stock Investment Strategy in The Indonesia Stock Exchange

The Indonesia Capital Market has experienced a significant increase in investors from 2019 until now. The increase in the number of new Indonesian capital market investors is dominated by people under 30 years who prefer to invest in stocks and mutual funds. This increase in new investors does not follow by high financial literacy. Research regarding financial literacy and investment return in Indonesia showed that financial literacy affects investment return. Therefore, Indonesia’s new investors will most likely experience losses due to their lack of financial literacy. Even though there are equity funds for novice stock investors that help them minimize the error they would make if they invest themselves, they cannot choose the equity funds randomly since most equity funds cannot beat the market benchmark. This study proposed using the Magic Formula and Acquirer’s Multiple as an investment strategy for new investors in Indonesia. Both Magic Formula and Acquirer’s Multiple generated an average annual return greater than the market and Indonesia Equity Funds listed since 2016 with an average return of 26,24% and 26,32% annually. The Sharpe ratio of both methods also generated a higher ratio than the market, where Magic Formula generated an average Sharpe ratio of 0,930 annually, while Acquirer’s Multiple generated an average ratio of 1,038. The acquirer’s Multiple is recommended for novice investors because it outperforms the Magic Formula and the market in terms of actual annual returns and risk-adjusted returns.

The Impact of Macroeconomic Indicators on the Share Prices of Dividend Companies – A Comparative Analysis of Polish and US Issuers for the Period 2016–2020

Abstract Research background: The aim of the article is to compare Polish and US dividend companies with potential growth with dividend companies with potential value, including in the period of economic turbulence caused by the pandemic, and to identify macroeconomic determinants that affect changes in the level of share prices of dividend companies with potential value listed on the stock exchange in Poland and the US. An analysis of the literature and international studies conducted allows us to identify inflation, gross domestic product (GDP), interest rate levels, exchange rate changes, and market P/E and P/BV ratios, as well as the PMI index, as the most important macroeconomic factors. Purpose: The aim of the article was to present research on the impact of macroeconomic indicators on the prices of Polish and US shares of dividend companies, divided into shares with potential value and potential growth for the period 2016–2020. The research was enriched by analyzing the return rate on shares and the risk of the share prices of companies with potential value during the turbulence of the economy caused by the COVID-19 pandemic. Research methodology: The study was conducted using the Spearman rank correlation coefficient and significance test for the Spearman rank correlation coefficient. A non-parametric t-test was carried out to check whether the estimated correlation is statistically significant. Results: The research indicates that Polish and US dividend companies with potential value have lower average annual return rates than dividend companies with potential growth. Referring to the determinants of the share prices of US dividend companies with potential value, it was found that they are significantly determined by inflation and moderately determined by industrial production and GDP, as well as the P/BV ratio. Novelty: The added and application value are the recommendations regarding the attractiveness of investing in Polish dividend companies with potential value as compared to companies from the US market.

Risk and Return Analysis of Selected Flexi Cap Mutual Funds

Mutual funds are considered by the investors as an ideal investment for people who are not having huge sum of money and wish to invest in a portfolio of stocks wherein the share price is quite high. The investors may or may not be aware about the ways investment could be done in stock market and there are different investment options which are available in the market based on a different risk and return. Flexi cap mutual funds offerfund managers a freedom for investing across themes/ sectors and market capitalizations. In Flexi Cap mutual funds, the fund managers could invest on the basis of outlook of market. These schemes generally recommended to the moderate investors for creating wealth over long time period. This study is based on the evaluation of risk and return of different flexi cap mutual funds and compares the performance of these funds so as to find the best flexi cap fund based on different measures of return and risk. Based on the average of the monthly returns, though it is negative, the lowest average negative return is of Aditya Birla and Parag Parikh Flexi Cap mutual funds. The maximum times the highest return has been of Parag Parikh Flexi Cap mutual fund during different quarters. Based on the average Annual return, highest return is of Parag Parikh Flexi Cap mutual fund, followed by UTI Flexi Cap fund, SBI Flexi Cap fund, PGIM Flexi Cap fund and Aditya Birla Flexi Cap mutual fund.

Do Income Stocks Provide Higher Total Return than Growth Stocks? Empirical Data Analysis

The fundamental issue in the investment process is not only how much to invest but also, what stocks to invest. It takes an average investor to make fundamental and/or technical analysis to select the best stock in the market. Of course, the selection dilemma does not lie with which company pays the highest dividends. It lies withwhich stock type (growth or income), provides highest payoff (total return) in the long run. The purpose of this study is to establish whether or not income stocks outperform growth stocks over time, and to offer valuable insights to new and existing investors as towhich path to take when it comes to stock selection. The study takes an empirical approach of analyzing existing data in order to make conceptual contribution to the body of knowledge in the literature of investment finance.In fact, the widespread rally behind dividend-paying stocks is not just a fad but has been supported by empirical evidence (data). Generally, growth stocks provide lesser total returns to the investor than income stocks. A test of mean differences of yields between income and growth stocks saw the yield (4.0) of income stocks almost doubling the yield (2.2) of growth stocks. Analysis of the data further indicatesthat dividends have played significant role in increasing total return in the history of investment. This was evident when average annual equity returns have been lower than 10% during a decade. Further analysis of data also, revealed the consequences of different dividend-policy implementations. The study established that dividend growers and initiators have historically achieved higher total return with less volatility than companies that either maintained or cut their dividend payment. Furthermore, dividend yield appeared to be significant in selecting stocks. Surprisingly, the study found that Stocks in the highest quintile of dividend yields have performed less, relative to stocks in the second quintile over time.