In this paper, we study data from financial markets, using the normalised Mutual Information Rate. We show how to use it to infer the underlying network structure of interrelations in the foreign currency exchange rates and stock indices of 15 currency areas. We first present the mathematical method and discuss its computational aspects, and apply it to artificial data from chaotic dynamics and to correlated normal-variates data. We then apply the method to infer the structure of the financial system from the time-series of currency exchange rates and stock indices. In particular, we study and reveal the interrelations among the various foreign currency exchange rates and stock indices in two separate networks, of which we also study their structural properties. Our results show that both inferred networks are small-world networks, sharing similar properties and having differences in terms of assortativity. Importantly, our work shows that global economies tend to connect with other economies world-wide, rather than creating small groups of local economies. Finally, the consistent interrelations depicted among the 15 currency areas are further supported by a discussion from the viewpoint of economics.
Food security is the cornerstone that ensures the stable development of a country. Based on panel data of 31 provinces (including autonomous regions and municipalities) in China from 2015 to 2019, we use the mediating effect model to explore the mechanism by which food consumption structure affects food security. The results indicate that grain consumption has a significant promoting effect on food security, while plant and animal food consumption have significant inhibiting effects on food security. Furthermore, agricultural R&D and investment play mediating roles in the impact of food consumption structure on food security. Obvious differences exist in the relationship between food consumption structure and food security between urban and rural areas, as well as between Eastern, Central, and Western regions. Animal food consumption had a negative and significant impact on food security, with a stronger effect on rural residents than on urban residents. Compared with the central and western regions, grain consumption and animal food consumption in the eastern region had a stronger marginal impact on food security. This paper enriches and expands the research on influencing factors of food security from the perspective of consumer demand, which has important theoretical value and practical significance for ensuring food security.
The aim of this study is to examine the effect of green investments on air quality for developed and developing European countries. In this context, the short- and long-term effects of green investments on air quality were examined by panel generalized method of moments (GMM) and panel causality method. As a result of the GMM analysis, it has been determined that green investments negatively affect the air quality for both developed European countries and developing European countries in the short term, but this effect turns positive in developed countries in the long term. As a result of the panel causality analysis, two-way causality was determined between air quality and green investments.
The fast-growing urbanization has contributed to the construction sector be- coming one of the major sectors traded in the world stock market. In general, non- stationarity is highly related to most of the stock market price pattern. Even though stationarity transformation is a common approach, yet this may prompt to originality loss of the data. Hence, the non-transformation technique using a generalized dynamic principal component (GDPC) were considered for this study. Comparison of GDPC was performed with two transformed principal component techniques. This is pertinent as to observe a larger perspective of both techniques. Thus, the latest weekly two-years observations of nine constructions stock market price from seven different countries were applied. The data was tested for stationarity before performing the analysis. As a re- sult, the mean squared error in the non-transformed technique shows eight lowest values. Similarly, eight construction stock market prices had the highest percentage of explained variance. In conclusion, a non-transformed technique can also present a better result outcome without the stationarity transformation.
One of the ways to calculate dividend for an investment is by using average lowest balance (ALB) concept. The existing calculation of dividend based on ALB concept can only be done yearly. This paper discusses on the development of a general formula to calculate the accumulated amount for any period of time, based on the ALB concept that considers different yearly dividend rates. The patterns for each variable and coefficient for the calculated yearly accumulated amount were analysed. The general forms of each variable and coefficient were then combined to form the general formula for calculating the accumulated amount. Validity of the general formula is confirmed by calculating the percentage errors and proven by using mathematical induction.
In this paper a class of capital investment problem is considered within the context of mathematical programming. The usual and commonly used approach is presented upon the basis of the next present value criterion, and a branch and bound method is discussed for a model under extended assumptions.
Dalam kertas ini satu kelas masalah pelaburan kapital difikirkan di dalam konteks pengaturcaraan matematik. Pendekatan biasa dan selalu digunakan, dikemukakan berasaskan kriterium Nilai Semasa Berikut dan satu kaedah bercabang dan terbatas dibincangkan untuk satu model di bawah anggapan yang diperluaskan.
The objective of this research is to examine the trends in the exchange rate markets of the ASEAN-5 countries (Indonesia (IDR), Malaysia (MYR), the Philippines (PHP), Singapore (SGD), and Thailand (THB)) through the application of dynamic moving average trading systems. This research offers evidence of the usefulness of the time-varying volatility technical analysis indicator, Adjustable Moving Average (AMA') in deciphering trends in these ASEAN-5 exchange rate markets. This time-varying volatility factor, referred to as the Efficacy Ratio in this paper, is embedded in AMA'. The Efficacy Ratio adjusts the AMA' to the prevailing market conditions by avoiding whipsaws (losses due, in part, to acting on wrong trading signals, which generally occur when there is no general direction in the market) in range trading and by entering early into new trends in trend trading. The efficacy of AMA' is assessed against other popular moving-average rules. Based on the January 2005 to December 2014 dataset, our findings show that the moving averages and AMA' are superior to the passive buy-and-hold strategy. Specifically, AMA' outperforms the other models for the United States Dollar against PHP (USD/PHP) and USD/THB currency pairs. The results show that different length moving averages perform better in different periods for the five currencies. This is consistent with our hypothesis that a dynamic adjustable technical indicator is needed to cater for different periods in different markets.
Renewable energy investments possess great potential for reducing the consumption of fossil fuels influenced by various determinants. This study investigates the individual investors' renewable energy investments' intention within the framework of the theory of planned behaviour (TPB) based on a survey conducted in 3 major states in Malaysia. The results indicate that one's intention to invest in renewable energy investments is influenced by attitude, subjective norm, perceived behavioural control and evaluation of regulatory framework. Risk aversion on the other hand was found to have no effect on investors' intention towards such investments. The findings also reveal that the evaluation of regulatory framework is the most important determinant. This outcome contradicts the outcomes arrived at by the previous studies that focus on investment behaviours or other types of pro-environmentally intention or behaviours. This research also investigates the indirect effects of TPB on explaining investor's intention towards renewable energy investments through the evaluation of regulatory framework. The results indicate that the investors' intention towards renewable energy investments is indirectly influenced by attitude and perceived behavioural control. Subjective norm does not have an indirect effect on investors' intention towards renewable energy investments. This study provides policymakers' important practical implications to improve renewable energy investments.
This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options markets. It applied the hypothetical method in which investors develop depression based on the understanding suggested by various green finance divisions. Furthermore, additional elements like panic, sentiment, and social networking sites may impact the attitude, size, and direction of green finance, subsequently impacting the security prices. We created new emotion proxies based on five groups of information, namely COVID-19, marketplace, lockdown, banking sector, and government relief using Google search data. The results show that (1) if the proportional number of traders' conduct exceeds the stock market, the effect of sentimentality indexes on jump volatility is expected to change; (2) the volatility index component jump radically increases with the COVID-19 index, city and market lockdown index, and banking index; and (3) expanding the COVID-19 index gives rise to the stock market index. Moreover, all indexes decreased in jump volatility but only after 5 days. These findings comply with the hypotheses proposed by our model.
The tourism industry is vulnerable to a range of economic and political factors, which can have both short-term and long-term impacts on tourist arrivals. The study aims to investigate the temporal dynamics of these factors and their impact on tourist arrivals. The method employed is a panel data regression analysis, using data from BRICS economies over a period of 1980-2020. The dependent variable is the number of tourist arrivals, while the independent variables are geopolitical risk, currency fluctuation, and economic policy. Control variables such as GDP, exchange rate, and distance to major tourist destinations are also included. The results show that geopolitical risk and currency fluctuation have a significant negative impact on tourist arrivals, while economic policy has a positive impact. The study also finds that the impact of geopolitical risk is stronger in the short term, while the impact of economic policy is stronger in the long term. Additionally, the study shows that the effects of these factors on tourist arrivals vary across BRICS countries. The policy implications of this study suggest that BRICS economies need to develop proactive economic policies that promote stability and encourage investment in the tourism industry.
The adoption of green construction practices (GCP) has been on the increase in recent years as a means of reducing the negative effects of construction on the natural environment. However, GCP have been discovered to expose the construction workers to numerous health and safety (HS) risks, resulting from a decline in safety investment due to the economic burden associated with its adoption. This study explores the means through which GCP influence the HS performance of construction projects through economic performance. To obtain the views of contractors, a survey questionnaire was developed, and data was collected from project managers and site managers of "class A" contractors, with a response rate of 81.55%. The partial least squares structural equation modeling (PLS-SEM) technique was adopted to analyze the data. The results show that the effect of GCP on HS performance is fully mediated by economic performance. The study concludes that for projects that adopt GCP to have high levels of HS performance, they are required to have an optimal economic performance. Efforts should be intensified by the government in providing subsidies, tax waivers, and other incentives for adopters of GCP to ensure the economic performance of their projects since it guarantees high HS performance.
We had reviewed the current practice in stocks market analysis where stock is represented by its closing price, and then found that this approach may be misleading. In actuality, in the daily activity of stocks market, stock is represented by four prices, namely opening, highest, lowest, and closing prices. Thus, stock is a multivariate time series of those four prices and not a univariate time series of closing price only. In this paper all four prices will be considered. Then, the notion of multivariate time series similarity among stocks will be developed as a generalisation of univariate time series similarity. The results are used to construct stocks network in multivariate setting. To filter the economic information contained in that network, the standard tools in econophysics is used. Furthermore, the topological properties of stocks are analysed by using the most common centrality measures. As an example, Bursa Malaysia data are investigated and we show that the proposed approach can better figure out the real situation compared to the current one.
The study of stock market volatility has been the focus of market participants primarily because most
of the applications in financial economics are concerned with volatility. The economic structure in
Malaysia is divided into three sectors: primary, secondary and tertiary. As the stability of the stock
market is important for businesses, this paper carefully reviews the concept of volatility and analyses
how different business sectors in Malaysia are affected by stock market volatility.
Foreign direct investment (FDI) can boost economic growth and provide job opportunities. FDI inflows in ASEAN+3 countries have dropped markedly, which may affect economic development in the region. Many previous studies have investigated a multitude of factors that can influence FDI, such as market size, inflation, trade openness, corruption, and inflation. Previous studies did not, however, consider environmental degradation as a potential factor. Besides corruption and inflation, imposing stringent environmental regulations, such as carbon pricing and taxes to reduce environmental degradation, might deter foreign investors from the country. This is due to heightened costs for foreign investors, which may cause FDI inflows to drop. To shed some light on the reality of this situation, this study examines whether environmental degradation can significantly affect foreign direct investment in the region. This study includes environmental degradation as a potential factor and employs the panel ARDL approach to analyse data from 1995 to 2019. Results show that environmental degradation, infrastructure, and corruption can affect the inflow of FDI in the long run. In the short run, inflation can affect FDI. The findings of this study can be utilized by policymakers in formulating the right policies to attract more investors. An increase in infrastructure facilities should be considered to attract more foreign investment. It is also vital for governments to reduce corruption and inflation to attract more FDI inflows. Environmental incentives should also be introduced to ensure that attempts to reduce environmental degradation do not affect FDI inflows.
Following decades of reducing greenhouse gas emissions in the transportation industry, most car companies will stop producing petrol cars and promote the development of new energy vehicles in the near future, even in China. This study is based on energy vehicle exports using China's 31 provinces' panel data from 2010 to 2020. Considering that China mainly engages in processing trade, this study analyzes the domestic energy vehicle's export sophistication after deleting intermediate goods, measuring the relationship between export sophistication and industrial upgrading with static and dynamic panel models. Then, heterogeneity tests were deployed to examine the domestic export sophistication of three major economic belts partition. The results revealed that improving export sophistication is conducive to realizing China's industrial upgrading. China's new energy vehicles industry is positively affected by export sophistication, R&D, foreign direct investment, average GDP growth rate, market factors, and human resources over the long run. Regarding regional stratification, domestic export sophistication in the eastern and western regions has more significant effects on promoting industrial upgrading than in the central region. In particular, in western regions, every increase in export sophistication by one unit will bring a significant industrial upgrading effect. Given this, China's new energy vehicles should increase export sophistication to help the country's industrial upgrading.
Mostly, the product manufacturer and activities related to transportation have a greater influence on the supply chain and the environment. Hence, the green investment in water, biodiversity protection, waste treatment, resources, and climate change alleviation help in enhancing industrial production. Thus, for the enhancement of green growth, the industries must adopt green financing by making investments in ecology, climate change, and carbon reduction. Despite having the greatest growth in green supply chain management, still, the implementations of greening the product and processes have not been seen properly in many industries. A bibliometric analysis was conducted through VOS viewer version 1.6.7. of last twenty years (2001-2021). A total of 2385 articles were retrieved from the Scopus database. The results revealed that China, India, Iran, and Taiwan have a vast collection of articles and have very strong international collaborations. The most cited authors were Sarkis, J., Zhu, Q., and Khan, S.A.R. The results also suggest that green supply chain management research was related to the field of engineering, environmental science, energy sciences, social sciences, and business management. Some new areas are discovered like green innovation, green information technology, green productivity, corporate environmental responsibility, green investments, green credit, and green credit policy. As evidenced from our bibliographic database search, it is observed that integrated work on green supply chain management and green finance is limited, and this makes this research work to be novel. This study is beneficial for credit managers and policymakers.
Policy adjustments can help strike a balance between economic growth and environmental sustainability, which has increasingly been the heart to nations and regions throughout the World. This paper examines how public investment affects economic growth, energy consumption, and CO2 emissions in eight ASEAN countries: Cambodia, Myanmar, Malaysia, Indonesia, the Philippines, Singapore, Thailand, and Vietnam. Extension of a Cobb-Douglas production function and application of panel cointegration techniques reveal bidirectional Granger causation between public investment and both private development and CO2 emissions from 1980 to 2019. Public investment Granger causes energy usage, the opposite does not hold statistically. More findings from pooled mean group estimations show a mean-reversion dynamic that corrects disequilibria by 14% yearly. State investment crowds in private sector growth, energy use, and carbon footprint. It also finds an inverted U-shaped relationship between public investment and energy consumption, and a U-shaped relationship between public investment and CO2 emissions, indicating complex regional interactions. It is suggested the implementation of public investment policies that enrich green infrastructure projects to foster growth while minimizing environmental impacts, and encourage a strategic approach to public investment for prioritizing environmental sustainability and thus, achieving Sustainable Development Goals 7 to 9 and 11 to 13 in this region.
The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.
The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.