Market Rates Research Articles

The influence of market and institutional factors on ESG rating disagreement

AbstractThe lack of convergence between rating agencies in the assessment of environmental, social, and governance (ESG) aspects of companies leads to the so‐called ESG rating disagreement. Although this phenomenon causes confusion and uncertainty among investors, it is still little investigated. Previous research has only focused on some determinants of the disagreement, mainly related to nonfinancial disclosure and corporate aspects, while broader determinants remain unexplored. This study aims to fill this gap by analysing the effects of market value, industry sensitivity, and institutional context on disagreement between two different rating providers. To achieve this goal, a cross‐sectional analysis was conducted for 1809 companies from the S&P 1200 Global Index. The results show that companies with a better market rating, belonging to critical sectors and located in countries with a better institutional environment, have a lower level of ESG disagreement.

A landscape in turmoil: characterizing the multi-decadal growth trajectory of brackishwater aquaculture in Medinipur Coastal Plain, India

The spatio-temporal growth trajectory of coastal brackishwater aquaculture (CBA) in the coastal tracts of Purba Medinipur, India and its impending repercussions on the immediate environs, was primarily assessed in this study through application of geostatistics, landscape metrics, and geospatial technologies. Three Community Development (CD) Blocks, namely, Contai-I, Deshapran, and Ramnagar-II were considered to analyze the growth pattern of the area under CBA. Landsat datasets of the assessment years (1991, 2001, 2011, 2021, and 2023) were used to prepare the land use/ land cover (LULC) maps and to derive pertinent landscape metrics of patch and class levels for this region. This brought forward a highly fragmented and dispersive spatial concentration of the CBA farms in the entire study area. Additionally, Census Village-wise growth pattern of CBA was analyzed by conducting a spatial autocorrelation analysis which depicted prominent clustering of villages with a higher concentration of CBA. Results showed that there has been an incessant growth of CBA in the last three decades, however, a sharp drop has been recorded owing to recurrent bouts of diseases, swelling production costs, and a sharp drop-in market rate. The nature of growth and/ or decay of the CBA was predicted for the year 2025 using Cellular Automata and Artificial Neural Network (CA-ANN) model. After careful calibration and validation, the model projected further lessening of the CBA area along with a continued expansion of abandoned aquaculture. Accordingly, ecologically viable livelihood alternatives and environmentally sustainable management measures were suggested for the efficient monitoring of these highly fragile tropical ecosystems.

International transmission of China’s monetary policy

ABSTRACT This paper quantifies the spillover effects and explores the transmission channels in a panel of advanced and emerging economies. Using a panel local projection model to identify Chinese monetary policy shock by the change in the 7-day repo rate in the interest rate swap market, we find that China’s monetary tightening causes a significant drop in global output, with a larger decline in emerging economies than in advanced economies. Moreover, spillovers of Chinese monetary policy mainly depend on the trade channel, while the exchange rate channel and the financial channel are insignificant. To further explain empirical findings, we develop a basic two-country model and unveil the inherent logic.

Artificial Intelligence: A forward-looking vision for a better future for humanity Analytical theoretical study

The world is witnessing a tremendous Revolution in terms of Technological Development, entry into the world of Artificial Intelligence, and the possession of modern technologies in automation and algorithms that are useful for computers and robots, which is certainly necessary and indispensable, as; Progress and development in various fields require the necessity of relying on artificial intelligence technologies and its multiple uses. Despite the advantages of using artificial intelligence, it faces many challenges and risks that face humans as a result of these uses. They are not limited to the various aspects (economic, social, and media) that affect humans from Where only the labor market and unemployment rates, but there are also other risks according to the nature and specificity of the social and cultural context of our Arab societies that must be taken into account when entering the world of artificial intelligence? All of these reasons made the researcher address the research issue and the current research topic This Research aims to Learn the Science of Artificial Intelligence, and provide a forward-looking vision of what a better future for humanity may look like in the future. This is because it is a modern Science that has gained great Importance in recent years for its many applications in various fields. It also aims to identify its importance, benefits, types and concepts associated with it, and reveal the areas of use of Artificial Intelligence applications, how to use them, and the challenges facing its use. This research was devoted to studying the reality of artificial intelligence. In light of the developments to identify the challenges and address them automatically, to develop a future vision about artificial intelligence in the twenty-first century, the research was entitled: Artificial Intelligence: A forward-looking vision for a better future for humanity Keywords:) A Proposed Vision - Artificial Intelligence - Forward-looking vision - Applications of Artificial Intelligence – Technology (

How to conduct monetary policies. The ECB in the past, present and future

We study the evolving operating procedures used by the ECB since its creation. During the period up to 2015, bank reserves were scarce and the ECB, like other central banks, used a corridor system in which the money market rate could fluctuate within the bounds set by the lending and the deposit rates. With the start of Quantitative Easing (QE) the operating procedure evolved into a regime of reserve abundance. This regime has become problematic since the inflation surge forced the central banks to raise the policy rate. The result has been a massive transfer of central banks’ profits (and more) to the banks. We propose a two-tier system of reserve requirements that would only remunerate the reserves in excess of the minimum required. This would drastically reduce the giveaways to banks, allow the central banks to maintain their current operating procedures and make monetary policies more effective in fighting inflation.This paper was presented at the ECB@25 Symposium at Erasmus University, Rotterdam on 16th January 2024. We are grateful to Mary Pieterse-Bloem, Sylvester Eijffinger, Casper de Vries, Charles Goodhart and other participants in the Symposium for comments and suggestions. We also profited from comments and suggestions of an anonymous referee.Previous versions of this paper (De Grauwe and Ji, 2023a, 2023b) profited from comments by Ignazio Angeloni, Peter Bofinger, Robert Holzmann, Pablo Rovira Kaltwasser, Karel Lannoo, Vivien Lévy-Garboua, Anna Lozmann, David Marsh, Wim Moesen, Joachim Nagel, Theo Peeters, Stefan Schmitz, Miklos Vari, and by participants in seminars and presentations at the London School of Economics, King’s College (London), the Bundesbank, the Central Bank of Luxembourg, OMFIF, Sciences Po (Paris), the Austrian National Bank, SUERF, the Polish National Bank and the National Bank of Ukraine.

A geographic information system approach for estimating state‐wide water quality credit need: Application for planned transportation projects in Virginia

AbstractUncertainty in water quality trading (WQT) markets is frequently cited as a deterrent for participation, with few studies focusing on uncertainty in future water quality credit needs. To reduce this uncertainty, we present a geographic information system (GIS)‐based methodology for estimating an upper bound of water quality credit needs for a set of spatially referenced planned construction projects over a large geographic region. We demonstrate the methodology by applying it to estimate future credit needs for the Virginia Department of Transportation's (VDOT) 6‐year improvement program. The results show that 25% of the state's 6‐digit hydrologic unit code (HUC) basins lack sufficient current credit supply to meet the estimated future credit need from VDOT's planned projects alone. Furthermore, while 70% of the 8‐digit HUCs containing planned projects have a sufficient current credit supply to meet VDOT credit needs, this is true for only 20% of the 10‐digit HUCs. Finally, nearly 25% of the planned transportation projects, representing potentially $9 million in credit purchases at current market rates, will be constructed in catchments with impaired water bodies. State regulations will initially limit these projects to trade with credit banks collocated at the 12‐digit HUC level. This application demonstrates how the GIS‐based methodology can be applied to reduce uncertainty about future WQT credit needs and how needs are aligned with current credit supply.

Effect of Mulching as a Weed Management Strategy in Field Production of French Beans (Phaseolus vulgaris L) in Western Kenya

There has been a 2% decrease on French bean (Phaseolus vulgaris L) production in Kenya due to factors such as weeds, pests and diseases and the challenge of controlling them using chemicals that result in high rejection rate or interception in the export market because of chemical residues. The objectives of this study were to evaluate the effect of different mulching materials on the growth and yield of French bean cultivars and to determine the effect of different mulching materials on weed density. Field experiments were carried out at KALRO Kitale, Trans Nzoia county Kenya. Season 1 was carried out during long rains of April and June 2021 and season two during the short rains of August and October 2021. Black polythene and grass mulch were compared with two hand weedings and no weeding in a Randomized Complete Block Design experiment with three replications. Data on growth and yield of French Beans were collected and subjected to ANOVA using GenStat to determine the significant differences between the treatments. The means were separated using Fisher’s Unprotected LSD at 5% significance level. Growth and yield of French Beans was significantly influenced by the treatments (p≤0.05). Plants grown under black polythene and grass mulch had the tallest height and the highest number of leaves and branches as well as number of pods and cumulative pod yield as compared to those that were hand weeded and unweeded. The highest yield of 2138 and 2597 kg/ ha was obtained under black polythene mulch in season 1 and 2 respectively. This was significantly higher than that obtained from grass mulch, hand weeding and unweeding. In conclusion polythene and grass mulch improved growth and yield of French beans and reduced weed density. It is therefore recommended that farmers should adapt mulching as a cultural weed management strategy.

The Impact of Vaccination, Infection and Fatality Rate on ASEAN Air Transport Industry in the Pandemic Period

This study aims to determine the impact of COVID-19 on air connectivity in the Association of Southeast Asian Nations (ASEAN) region, specifically focusing on infection, vaccination and fatality rates. To examine the impact of COVID-19 on the ASEAN air transport industry, a panel data series was created. The panel covered data from 57 airlines with different business models in the 10 ASEAN member states from January 2019 to July 2022 (31 months). The results of the study have shown that there is a significant inverse linear relationship between full-service and low-cost international flight movements, passenger demand and vaccination rate, infection rate and fatality rate. At the country level, Brunei experienced the lowest drop in air passenger demand, followed by the Philippines, Thailand, Malaysia and Cambodia. Other countries (Indonesia, Lao PDR, Myanmar, Singapore and Vietnam) were not significant predictors of passenger demand. The study’s results have indicated that an increase in infection rate has a greater impact on the international air travel market compared to the domestic market. The reduction rate of the domestic market is only half that of the international market, while the fatality rate demonstrated no differences. This study represents a valuable contribution to the existing knowledge of the pandemic’s impact on the air transport industry, focusing on Southeast Asian countries. It provides evidence to help stakeholders in the aviation industry prepare for future related crises. The study concludes that fostering greater cooperation and coordination among ASEAN member states in managing health crises and facilitating the aviation industry can promote economic growth, enhance resilience and strengthen regional integration in the long run. JEL Classification: F02, I30

Evolution of temporal fluctuation scaling exponent in nonstationary time series using supersymmetric theory of stochastic dynamics.

Temporal fluctuation scaling (TFS) is an emergent property of complex systems that relates the variance (Ξ_{2}) and the mean (M_{1}) from an empirical data set in the form Ξ_{2}∼M_{1}^{α_{TFS}}, where the dispersion (fluctuation) of the data has been described in terms of Ξ_{2}. At present, it has been shown that this law of complex systems has different multidisciplinary applications such as characterizing the market rate based on its exponent, explaining the spatial spread of a pandemic or measuring dispersion in a counting process, among others, if it is known how the average value M_{1} of a representative quantity in a system changes. Then, using the path integral formalism and Parisi-Sourlas method, we propose an extension of path integral formalism to understand the origin of the temporal fluctuation scaling and the evolution of its exponent over time in nonstationary time series. To this end, we first show how the probability of transition between two states of a stochastic variable x(t) can be expressed once it is known its cumulant generating function. Also, we introduce a nonlinear term in a cumulant generating function of the form H^{(n)}(p,t;γ)∼p^{n} to obtain a model where the nth moment of the probability distribution evolves arbitrarily. Subsequently, in order to reproduce the temporal fluctuation scaling, a linear combination of H^{(n)}(p,t;γ) with n∈{1,2} is used. Therefore this allows describing how the mean M_{1}(t) and the variance Ξ_{2}(t) of empirical time series evolve. Thence, an analytical expression is deduced for the evolution of the temporal evolution of the temporal fluctuation scaling exponent α_{TFS}(t). Likewise, the validity of the expression found for α_{TFS}(t) is verified with a toy model based on white noise. Finally, this approach is verified in two stock indices (Dow Jones and Sao Paulo stock index) and two currencies (GBP-USD and EUR-USD) with daily data. It is found that this approach accurately captures the evolution of the mean and variance of these four financial derivatives after contrasting the results with a coefficient of determination that depends on H^{(n)}(p,t;γ). Also, it is shown that the temporal fluctuation scaling exponent is a measure of uncertainty or volatility in financial time series.

Game analysis of service quality evolution of online tourism supply chain under PPI participation

ABSTRACT While platform protection insurance (PPI) is extensively employed as an insurance policy in many sharing platforms, research on its influence on the tourism supply chain is lacking. At this point, the quality of online tourism services has taken the brunt of consumer complaints, and new solutions are desperately needed. So, would PPI's involvement increase the quality of online tourism services? In this paper, by constructing an online tourism supply chain consisting of a Tourism Supplier (TS), an Online Tourism agency (OTA), and consumers, we study the conditions of PPI introduction and its impact on online tourism service quality and analyze the behavioral decisions of online tourism supply chain subjects. The study found that in the tourism market with a small amount of demand change, OTA is more willing to introduce PPI, and TS is more inclined to improve service quality, which then lowers the service cost of TS and the level of disclosure of information, the stronger the willingness of OTA to introduce PPI, and the introduction of PPI in the lower PPI penetration rate of the tourism market has a more promotive effect on the TS with lower service cost.

ANALYSIS OF THE EFFECTIVENESS OF THE MONETARY POLICY TRANSMISSION CHANNEL IN INDONESIA WITH A SINGLE TARGET OF INFLATION FOR THE PERIOD 2016:08 - 2022:12

The purpose of this study is to determine The Monetary Policy Transmission Channel In Indonesia With A Single Target of Inflation For The Period 2016:08 - 2022:12. The research method used the Vector Error Correction Model (VECM) for the period August 2016 until December 2022. This study uses secondary data from the Indonesian Central Statistics Agency (BPS) and CEIC (a company providing financial and macroeconomic indicator data). The results of this study show that inflation responses to the shock of variables in the Monetary Channel, Interest Rate Channel, and Inflation Expectation Channel is not very much. Viewed from the result of the Impulse Response Test and Variance Decomposition, the three channels for monetary policy transmission (monetary channel, interest rate channel, and expectation channel) must be more effectively implemented in Monetary Policy decision-making in Indonesia. The interest rate channel is the most effective channel among the three channels. The results of the Impulse Response test and Variance Decomposition prove that inflation responses to the shock of variables in the Interest Rate channel are the strongest and have the least time lag and variance of those variables. The most suitable variable used for an operational target in an interest rate channel is BI-7-Days-Repo-Rate (BI7DR). Based on comparation of the other two variables (deposit rate and interbank money market rate), the results of the Impulse Response test and Variance Decomposition show that BI7DR shock obtains strong and quick inflation responses.

Comparative Study of Malaysian Affordable Housing Policy Initiatives

The Malaysian government has implemented and coordinated affordable housing development initiatives to many targeted groups with the aim to spearhead liveable affordable housing and establish an effective regulatory on affordable housing. In order to focus on the direction as well as formulating guidelines for the development of affordable houses, the National Affordable Housing Policy (NAHP) had taken into account the problems and issues faced by the public especially on the inability to own a house at the market rates. Through this policy, several government initiatives were implemented, including Perumahan Penjawat Awam Malaysia (PPAM), Rumah Wilayah Persekutuan (RUMAWIP) and Projek Perumahan Rakyat (PPR). This study was to identify which initiative among those three that offers the best housing needs alongside its goal of implementation, adequate and good quality of home with conducive amenities and environment, affordability and sustainability. The survey questionnaire that was developed was validated and provided to the general public to gain insight and feedback on the effectiveness of the PPAM, RUMAWIP and PPR initiatives. Therefore, the results were summarized according to the public's satisfaction that may be useful in the housing industry and the government for continuous and improvements to ensure continuity in future studies. Results showed that the favourite housing initiative is PPR however many improvements still need to be improved such as pricing, size, facilities and maintenance. Overall, this study is in line with the targeted Sustainable Development Goal (SDGs) 3 of Good Health and Wellbeing as well as Goal 11 of Sustainable Cities and Communities and others which will benefit all.

Spillovers in the U.S.-China Stock Markets - A Study of Returns and Volatility under Full Sample Periods and Multi-Special Periods

This paper adopts the ARMA-GARCH model and selects the S&P500 and the SSEC to study the return rate and volatility spillover effect of the US stock market(USM) and the Chinese stock market(CSM) in the full sample period, the Chinese stock market crash in 2015 and the duration when coronavirus spread. In both the full sample period and the two specific periods, it is discovered that the USM significantly increases the return on the CSM. While the CSM barely has any impact on the USM. Although the impact is favorable over the whole sample, it is less pronounced during the The pandemic caused by the novel coronavirus and the China's 2015 stock market debacle. In the whole sample, the S&P500 is unaffected by the SSEC's volatility, whereas the SSEC is significantly harmed by the S&P500's volatility. The S&P500's volatility will have a major beneficial influence on the SSEC, but it won't be communicated from the SSEC to the S&P500 during the global spread of COVID-19. Both of the fluctuation transmission to each other were negligible during the 2015 stock market turmoil. For risk management and stock asset allocation, this study can offer important information to financial institutions, everyday individuals, and governments.

Yield rate in the Warsaw office market and its determinants. Further studies

This article is a continuation and extension of a previous study which, to the best of the author’s knowledge, was the first scientific attempt to identify determinants of the yield rate in the Warsaw office market. The paper is based on the Gordon growth model. In this approach, the yield rate of buildings offering office space to let is a function of the risk-free interest rate, the risk premium and a constant rate of growth of generated cash flows. In the article, five different elements of the risk premium were identified (term structure, alternative investments’, market (country) specific, monetary and local office market capacity risk premium). The Error Correction Model was formulated based on quarterly time series data from 2007Q1 to 2021Q2. Most investors in the office market in Poland are financial institutions representing foreign capital. Therefore, the innovation of the paper and its main goal was to define which factors play key roles in determining yield rates in the Warsaw office space market – national or regional/international. However, the selected group of Polish determinants were indicated as having prevailing an impact on the yield rate in the Warsaw office market than the corresponding determinants from the European Monetary Union and the USA. Based on the model, the lead-lag, as well as asymmetric relations, were depicted. Moreover, the use of dummy variables checks, the Chow test and the Markov switching model indicated the presence of structural breaks and the existence of the two regimes in the model.

Neutral Business Assistance and the Limits of Complicity Under International Criminal Law

Business transactions between corporations and actors involved in grave human rights violations present significant challenges for the assessment of corporate criminal liability. This is particularly evident in cases of “neutral business assistance,” which refer to business conduct that appears legitimate on the surface and falls within day-to-day business operations but nonetheless contributes to the crime. An example of neutral business assistance is selling generic goods (for example, computer technology) legally at market rates, without the explicit intent to aid criminal activity, that increases the perpetrator’s capacity to carry out human rights violations. In such cases, discerning the point at which a legitimate business transaction becomes a wrongful act of complicity remains a complex and unresolved issue in international criminal law. The doctrinal requirement for the wrongful act of complicity is that the assistance provided must have a “substantial effect” on the commission of the crime. Traditionally, this assessment has been grounded in a narrow factual analysis that primarily emphasizes the gravity of harm resulting from aiding and abetting. This one-dimensional approach to wrongfulness, however, oversimplifies the ethical complexities of criminal liability. It overlooks broader normative considerations and the positive societal impact of human cooperation. This article challenges the prevailing harm-based paradigm and introduces a more nuanced methodology to assess the wrongfulness of aiding and abetting across various contexts. To do so, the article embraces a broader perspective on the “substantial effect” criterion, one that takes into account the crucial normative dimension of balancing the harmful effects of aiding and abetting with their corresponding social benefits. As a result, the article outlines a refined theory of the actus reus of complicity that enables a more holistic evaluation of accomplices’ conduct.

Technoeconomic Assessment of Gasifier Baking Stoves for Commercial Purposes

The energy supply in Ethiopia is dominated by biomass energy, mainly for household consumption. The development of gasification‐based gasifier baking stoves for energy demand is the subject of this study. The novelty of the gasifier baking stove is its ability to bake food more quickly while using less wood fuel. Biomass fuels are used inefficiently in poorly ventilated kitchens, resulting in indoor air pollution and the consumption of large amounts of wood fuel. Biomass gasifier baking stoves can improve fuel efficiency, baking time, and indoor air pollution while producing char as a byproduct. The proposed new gasifier study shows an average fuel use efficiency of 45% and time savings of 12% compared to Mirt stoves. Furthermore, the grate cover of the biomass gasifier stove is also used to regulate the airflow rate. The primary air that enters the reactor is controlled by a manually operated slide grate cover. The water boiling test and control cooking test were developed to mirror the performance of a modern baking and cooking stove. The baking stove was tested with Eucalyptus globulus as a feedstock. A technoeconomic assessment was conducted on a biomass gasifier baking stove for commercial purposes. For the technoeconomic assessment, we mostly employed the simple payback period projection. The economic analysis was conducted using Ethiopian supply and market rates, which may differ from region to region. The baking stove has an initial capital cost of about 15,100 ETB and a payback period of 2.49 years, which makes it economically viable for those living in remote locations. According to the study, the typical emissions from a biomass gasifier stove running on eucalyptus wood fuel are 0.24 ppm CO and 8.91 ppm CO2. The results of the stove’s economic study demonstrate that using eucalyptus wood fuel results in a shorter payback period. The performance efficiency of the new gasifier stove in terms of wood fuel and time saving as compared to the Mirt stove is 45% and 12%, respectively.

Trends in the artificial intelligence market of the Russian Federation

Artificial intelligence is currently one of the most relevant and discussed topics in the field of technology. This is due to the widespread use of artificial intelligence in various fields of activity. The use of tools and methods of artificial intelligence increases the potential for the development of many fields of activity, including the social, scientific sphere, education, healthcare, industry. In 2021, under the influence of the COVID-19 pandemic, the growth rate of the Russian artificial intelligence market increased. In 2022, due to the difficult economic and political situation, there was a decrease in the growth rate. At the same time, it is most probable that in 2023-2024 the market growth will accelerate due to scientific and technological progress and stabilization of the economic situation. One of the most important factors that influenced the growth of the Russian artificial intelligence market is the state policy in the field of information technology.

An Empirical Study on Factors Affecting the Demand of Life Insurance Policies in Colombo District

The life insurance market is a significant factor that affects the growth of an economy in any country. In developed countries, the life insurance market grows at a fast pace and stimulates the economy. However, most developing countries including Sri Lanka show a low growth rate in the life insurance market. This study focused on identifing the factors for the low demand for life insurance policies in the Colombo district. Primary data were collected using a structured questionnaire and the two-stage cluster sampling technique was utilized to select a sample size of 384. Based on the analysis result of the logistic regression, it was identified that age, family size, monthly income, awareness about policies, and subjective norms of respondents are significant variables that affect demand for life insurance. Moreover, it was revealed that people whose monthly income was more than Rs 90,000 were four times more likely than people with monthly incomes below Rs. 30,00 to be a life insurance policy holder. Also, it was discovered that people aged 50 years or above were three times more likely than the people of age between 20 and 29 years to be a life insurance policy holder. Furthermore, the study found that the awareness of people especially, among the non-policyholders in the Colombo district regarding life insurance, was at a low level, and a considerable number of responds had an unsatisfactory level of confidence about life insurance companies. Thus, it is necessary to take action to establish trust among the people about the insurance company and their policies. It is suggested that awareness programs about the importance of having life insurance in high-risk situations in the modern world and benefits of the life insurance for ordinary people to increase the demand for life insurance should be made available.

Competitiveness of Vietnam tuna export industry in the European market

Export competitiveness is a relatively late research topic, but there has been a rapid increase in the number of studies in the last three decades. To date, this topic is not only a concern of researchers but also businesses, manufacturing industries, and countries, especially policymakers. In this study, we evaluate Vietnam's tuna export competitiveness in the European market through industry competitiveness indicators, including manifest comparative advantage (RCA), export market share (MS), and export price. In addition, the gravity model is used to determine the factors determining the competitiveness of Vietnam's tuna export industry in this market. The research results show that the competitiveness of Vietnamese tuna in the European market is quite high and tends to increase but is still much weaker than leading competitors such as Thailand, Ecuador, and Spain. The deciding factor for competitiveness is the large amount of domestically exploited tuna. Although the product quality is still low compared to major competitors in the market, it has improved rapidly in recent years. In addition, the suitability of tuna products exported from Vietnam to the import market and exchange rate fluctuations favorable to exports are other competitive advantages, among them, the exchange rate is the biggest decisive role. On the contrary, import taxes are the biggest barrier that reduces competitiveness in this market. To improve competitiveness and move towards sustainable development of the tuna export industry, Vietnam needs to make great efforts, especially strictly controlling domestic tuna resources, avoiding overexploitation, and focusing on improving high product quality. Furthermore, Vietnam needs to focus on meeting the commitment conditions in signed free trade agreements, actively research the market, focus on trade promotion policies, and strengthen trade connections with other import countries.

The Return of the Market Models: The Continuous Forward Market (CFM) Rate Model

The Return of the Market Models: The Continuous Forward Market (CFM) Rate Model