ABSTRACT
The Turn of the month (ToM) effect is a calendar anomaly when the majority of returns of an asset are con-centrated into several days around the end of the old month and the start of the new one. Until now, the investigation of the ToM effect has mainly been focused on the stock markets. However, this paper investigates the presence of the ToM effect in eight key agricultural commodity markets (cocoa, coffee, corn, cotton, rice, soybean, sugar, wheat), using three different alternatives of the ToM window, during the 2001–2021 time period. The results show a statistically significant ToM effect in the rice, coffee, and sugar markets. Further results show that the ToM pattern changed during the COVID-19 pandemic, and that, in the case of commodities with a statistically significant ToM effect, the ToM effect can be efficiently used to beat the buy & hold investment strategy convincingly. © The authors.
ABSTRACT
As China attaches increasing importance to its ecological environment, ecology-related industries have become essential to China’s national economy. However, in the current national economic accounting practice, the ecological industry (eco-industry) is not independent, and the ecological service value ecology creates is currently not within the scope of national economic accounting. To clarify the impact of the development of the eco-industry on the whole regional economy, this paper takes Beijing as the study area. For the first time, the input–output analysis method is adopted to differentiate the eco-industry as an independent sector. Moreover, the ecosystem services value is integrated into the eco-industry, and each coefficient is quantitatively analyzed from an industrial-chain perspective. The results show that the eco-industry exerts a good pulling effect on the regional economy. The inputs and outputs of the eco-industry clearly tend to focus on eco-environmental and public-service-related industries, followed by industries for which ecological development can create value. Judging from the entire regional economy, ecological investment significantly impacts both the education and financial industries. Ecological investment can promote socio-economic development, achieving a 1.318 increase in regional GDP per unit of eco-investment. The results imply that the development of the eco-industry in China should be boosted further and social capital investment should be attracted. Finally, this paper provides a scientific basis for policymakers to better understand the overall situation of both the eco-industry and industry linkages and guide them to develop relevant ecological investment strategies.
ABSTRACT
Turn of the month (TOM) is a widely recognized anomaly and studied majorly in the context with equity markets. However, the global mutual fund market has not been much exposed to empirical testing of the TOM anomaly and the implication thereof. This study has dual objectives of not only investigating if the TOM effect persists in the world of equity mutual funds but also proposing an investment strategy to exploit the TOM anomaly to mutual fund investors. The study examines 40 equity mutual funds across 6 different geographies and 2 multi-geographic segments. For the sample period of 15 years (2005-2020), crucially covering financial crisis as well as an outbreak of the Covid-19 pandemic this study confirms a statistically significant effect of TOM for 23 out of 40 funds. Based on findings, the paper proposes a staggered investment strategy to investors in mutual funds for entry and exit to exploit the TOM effect for return enhancement.
ABSTRACT
The purpose of the study is to reveal the specifics of the turbulent business environment formed by the COVID-19 pandemic, as well as to substantiate the most effective strategies for adapting companies to ensure their rapid adaptation to new conditions. The authors proved that the COVID-19 pandemic has created a new turbulent environment for business activities (due to the suddenness and intensity of infection with the virus;high level of globalization;inclusion of each individual;blocking and reduced socio-economic mobility;uncertainty of the timing and consequences of the spread of the virus). The authors determined that the pandemic qualitatively strengthened the trend associated with “slowing down globalization” and consolidating the diversification of world centers of influence, and also became a catalyst for a number of structural shifts. The authors analyze the possibilities of implementing various strategies for adapting companies in a turbulent business environment. It is concluded that an ambivalent strategy, which allows companies to use separate elements of the cost reduction strategy and investment strategy at different stages of adaptation, has the greatest potential for effective implementation by companies in conditions of turbulence. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The purpose of our study was to investigate the relationship between business strategy, organizational culture, and market satisfaction. This study focused on Korean companies entering Africa and companies wishing to enter Africa and analyzed the satisfaction of companies with the African market focusing on internal environmental conditions. In terms of data, we collected 183 usable samples from companies. In order to analyze the data, we used structural equation modeling using AMOS 25.0. Based on the results, first, we can see that there is a positive relationship between business strategy and organizational culture. Moreover, there is also a positive relationship between business strategy and market satisfaction. Lastly, we found a positive relationship between organizational culture and market satisfaction. These study results give the following implications in establishing investment strategies for Korean companies entering Africa or willing to enter, which are in the midst of macroscopic environmental changes.
ABSTRACT
In the aftermath of the COVID-19 pandemic, non-core investments are gaining traction amongst institutional investors due to the shifting preference towards investment vehicles that position higher on the risk–return curve. Non-listed value-add real estate funds in Japan are one such vehicle. This research develops a comprehensive bespoke benchmark total return index using the ANREV database to reflect the performance of Japan-focussed non-listed value-add real estate funds. We compare the performance of such funds with that of other asset classes and perform portfolio and regression analyses. We conclude that there are several advantages to investing in those funds, including: (1) strong absolute total return performance, (2) competitive risk-adjusted performance, and (3) significant portfolio diversification potential in a mixed-asset portfolio context. The strategic implications for real estate investors are also assessed.
ABSTRACT
The study analyzes the performance levels achieved by Romanian wholesaler SMEs from Hunedoara County and to advance some practical courses of action designed to support local entrepreneurs in improving efficiency and in embracing circular economy (CE) practices. We employed cluster and discriminant analyses with a focus on providing an accurate classification of trade SMEs, according to their performance. Three distinct classifications of SMEs resulted in: (i) a class of enterprises displaying high levels of the rates of return, whose business owners exhibited an increased risk appetite and applied investment policies focusing on future development by means of incorporating digital instruments;(ii) a class of SMEs displaying average levels of rates of return, which manage to survive in situations of crisis through maintaining the position previously gained on the market;and (iii) a class of SMEs exhibiting a precarious financial position and employing defensive strategies, with managers who are reluctant to take risks in the innovation processes. Furthermore, we present a cloud computing solution which was tailored for one of the companies from our sample that appeared to be the most likely to carry out the transition from the average SME performance class to the higher class. The main advantages that are brought about by the IT solution in terms of environmental sustainability consist of: improvements in energy efficiency, the decrease in carbon footprints, the lowering of operational costs and the diminishing of the amount of e-waste.
ABSTRACT
In 2015, the governments of 193 United Nations member states adopted the 2030 Agenda for Sustainable Development, followed by the Paris Agreement. Their detailed solutions assume the inclusion of the concept of sustainable finance into investment decision-making processes, including directing capital towards sustainable investments and stopping climate change. The main subject of the study is sustainable finance, which is one of the pillars of the sustainable development of the global economy, which has also become an important objective of the European Union, enshrined in the Treaty of Lisbon. The main aim of the paper is an extrapolation of risks appearing in the unstable environment of credit institutions, which are increasingly boldly directing their expectations on their inclusion in the sustainable finance concept implementation. The empirical research included in the first stage a questionnaire survey, while in the second one, a quantitative comparative analysis. The research was aimed at verifying the research hypothesis stating that after the global financial crisis, banks meet the new prudential capital regulations, however by their inclusion in the concept of green finance, they will increase a share of mitigation in the bank risk management strategy. The research, carried out in the Polish banking sector, has shown that domestic banks meet all prudential requirements resulting from the new capital norms. However, investment strategies, based on the composition of the portfolio in accordance with the principles of sustainable finance and on high rates of return in the long term, will change banks’ resilience to key risks from the perspective of sustainable development.
ABSTRACT
Index tracking consists of mimicking a benchmark performance with a portfolio formed by a subset of assets contained in the index. Due to the cardinality constraint, obtaining an optimal solution for this problem can be impractical as the number of stocks in the index grows. Then, meta-heuristics, such as genetic algorithms, can obtain good solutions in a reasonable time, making it possible for the investor to run different configurations of the problem before deciding to rebalance or not his portfolio. Also, to evaluate an investment strategy, it is important to perform backtests considering different risk scenarios, especially in crisis scenarios, with a high volatile market. This work aims to analyze the integration of hybrid and pure genetic algorithms and two optimization models in a high volatility market scenario, the Brazilian market index IBOVESPA during the COVID-19 pandemic. We observed that the hybrid algorithms returned competitive solutions, tracking IBOVESPA even closer than the CPLEX solution on the linear model for a non-rebalancing strategy. However, they were not competitive in a rebalancing strategy, with solutions presenting a gap of more than 100% relative to the general-purpose solver solution. © 2021 IEEE
ABSTRACT
The Volatility Index (VIX) is a real-time index that has been used as the first measure to quantify market expectations for volatility, which affects the financial market as a main actor of the overall economy that is sensitive to the environmental and social aspects of investors and companies. The VIX is calculated using option prices for the S&P 500 Index (SPX) and is expressed as a percentage. Taking into account that VIX only shows the implicit volatility of the S&P 500 for the next 30 days, the authors develop a model for a near-optimal state trying to avoid uncertainty and insufficient accuracy. The researchers are trying to make a contribution to the theory of socially responsible portfolio management. The developed approach allows potential investments to make decisions regarding such important topics as ethical investing, performance analysis, as well as sustainable investment strategies. The approach of this research allows to use deep probabilistic convolutional neural networks based on conditional variance as a linear function of errors with the aim of estimating and predicting the VIX. For this purpose, the use of technical indicators and economic indexes such as Chicago Board Options Exchange (CBOE) VIX and S&P 500 is considered. The results of estimating and predicting the VIX with the proposed method indicate high precision and create a certainty in modeling to achieve the goals.