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We study a large currency cross-section using asset pricing methods that account for omitted-variable and measurement-error biases. First, we show that the pricing kernel includes at least three latent factors that resemble (but are not identical to) a strong U.S. "dollar" factor and two weak high Sharpe ratio "carry" and "momentum" slope factors. Evidence for an additional "value" factor is weaker. Second, using this pricing kernel, we find that only a small fraction of the over 100 nontradable candidate factors considered have a statistically significant risk premium, mostly relating to volatility, uncertainty, and liquidity conditions, rather than macro variables. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

In this article, we investigate the parameter estimation problem for reflected Ornstein–Uhlenbeck processes with mean reversion. Both estimates based on either continuously or discretely observed processes are considered. The explicit formulas for the estimators are derived using the least squares method. Under regular conditions, we obtain the strong consistency and establish the asymptotic normality for the estimators. Simulation results demonstrate that the performance of our proposed estimators for the drift parameters is superior to the moment estimators. The currency exchange rate data is used to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

This paper contributes to the literature by analysing shock propagation mechanisms between world uncertainty, exchange rates and country-specific commodity terms of trade. Using monthly data from 2008 to 2020 for eight commodity currencies' exchange rates, we analyse the impulse responses based on local projections. The study results show that a shock from the exchange rates which are net transmitters of shocks through the direct United States (US) dollar effect causes world uncertainty to rise and subsequently fall due to the indirect commodity terms of trade effect. Also, in response to world uncertainty shock, the exchange rates fall in the risk-on period and subsequently overshoot during the risk-off period when investors seek the safe haven of the dollar. The world uncertainty shock on the exchange rate is predominantly experienced in the economies that largely trade commodities with the US, particularly Russia and Canada. The study finds evidence that the dollar is a prime cause of world uncertainty. Hence, for policy implications, the study discusses that policymakers, investors, or traders pay attention to the dollar which is the main invoicing currency in the international market. [ABSTRACT FROM AUTHOR]

In this study, we use monthly G7 industrial production data, commodity price index data, and commodity currency exchange rate data in a dynamic factor model to examine the global economic factors useful for commodity price prediction. We differentiate between the dynamic factors by specifying a persistent factor and a non‐persistent factor, both as a single global factor using all data and as factors for each category of data. The in‐sample predictive performances of the three persistent factors together are better than the non‐persistent factors and the single global factors. Out‐of‐sample outcomes based on forecast combinations also support the presence of predictive information in the persistent factors for overall commodity prices and for most sub‐categories of commodity price indexes relative to their means. The gains in forecast accuracy are heterogeneous, ranging from 5% to 7% in the 1‐ to 6‐month horizon for overall commodity prices to a high of around 20% for fertilizers in the 12‐month horizon in the recent sample. We further show that the information in the persistent factors, especially in the commodity currency exchange rate‐based persistent factor, can be integrated with other global measures to further improve the predictive performances of the global measures. [ABSTRACT FROM AUTHOR]

ABSTRACT The FOREX market assessment is a big challenge for investors and global risk managers. However, the present study uses daily multicurrency exchange rate returns data from 2007 to 2022 to estimate the learning returns performance of the proposed model to find a safe‐haven currency for optimal investment strategy. The categorical returns are classified into good returns (GRs), bad returns (BRs) and no returns (NRs). Therefore, the present study needs to use a one‐hot‐encoding function to convert a categorical dataset into a numeric format with TensorFlow. The present study proposes a deep neural network‐based multilayer perceptron (DNN‐based MLP) with a backpropagation algorithm to estimate the learning returns performance of the proposed model to find a safe‐haven currency for optimal investment strategy. The findings showed that currency exchange rate return 2 (CERR2) is relatively a safe‐haven currency than currency exchange rate return 1 (CERR1) and currency exchange rate return 3 (CERR3). Moreover, the findings also showed that the proposed model gives optimal learning return performance. This study may assist FOREX investors to modify their investment strategies under shed light of findings of the study. In addition, the findings of the present study may also support global risk managers to revisit their hedging strategies. [ABSTRACT FROM AUTHOR]

This paper examines the involvement of members of South Asian communities in cricket (in Bradford and Leeds, UK). The England and Wales Cricket Board (ECB) identified that despite the high level of interest in cricket within these communities, relatively few were participating in opportunities provided through ECB structures; instead, they were engaged in various forms of 'informal' cricket. Using data from a small-scale survey and group interviews, this paper speaks to issues of diversity and equality utilizing Rowe's theory of sporting capital framed with insights from Critical Race Theory (CRT). We argue that Rowe's model should be refined by incorporating the concepts of cultural competence and cultural wealth. Doing this can safeguard against deficit models of capital that stress what people lack rather than what they possess. This provides the sporting establishment with better insight to how their sport is perceived and engaged with by those outside the mainstream. [ABSTRACT FROM AUTHOR]

In this paper, we study the impairment in monetary policy caused by different forms of global financial cycles. We find that while both equity inflows and outflows cycles do exert influence over monetary policy, the bond inflows cycle does not have a significant impact. Further, we discuss the role of macroprudential policies in mitigating this impairment by using Difference-in-Difference with heterogeneous treatment effects which is robust to presence of heterogeneity across both time periods and groups. We find that FX-based policies such as Capital Restrictions on Foreign Exchange positions and Limits on Foreign Exposure alongside SIFIs and Loan Loss Provisioning are effective in reducing the impairment. [ABSTRACT FROM AUTHOR]

Foreign investment can mitigate the foreign exchange constraint of developing countries. It can also influence the economy's international competitiveness through appreciating or depreciating exchange rates. The exchange rate impact of domestic investment is also not straightforward and depends on some critical factors. These issues of investment often pose a policy dilemma. Against this backdrop, this paper assesses the relative impacts of foreign direct investment (FDI), domestic investment (DI), and external debt on India's real effective exchange rate and the rupee/dollar real rate for the liberalized regime for trade, investment, and exchange rates. The autoregressive distributed lag bounds testing approach to cointegration, followed by its error correction representation, finds that real exchange rate variations are associated with FDI, debt, DI, and some control variables. FDI and debt depreciate real exchange rates, indicating that these have not exacerbated the economy's international competitiveness. However, DI causes real appreciation. These findings are consistent across estimations involving alternative specifications of control variables. Offsetting impacts of FDI and DI is an interesting finding. This can stabilize the exchange rates by undermining appreciating or depreciating exchange rate trends. [ABSTRACT FROM AUTHOR]

In late August 1530, three Florentine merchants formed a partnership specifically to wager on the outcome of the papal election following the death of Pope Sixtus V. Thanks to the survival of an account book compiled by one of the three, Dinozzo Lippi, their undertaking can be examined in detail. This article analyzes the account book within the contexts of Lippi's commercial career, the tradition of betting on papal elections, the specific historical circumstances of the September 1590 conclave, and the practices of commercial speculation in Renaissance Italy. I argue that it reveals not only the internal functioning of the papal betting market but also the intellectual habitat for financial risk taking in premodern Europe prior to the development of mathematical probability theory. Lippi's careful accounting of bets demonstrates how merchants made qualitative probabilistic decisions, revealing how an investment made on the identity of the next pope was no less rational nor speculative than an investment made in currency exchange or maritime insurance. [ABSTRACT FROM AUTHOR]

Copyright of Informatica (03505596) is the property of Slovene Society Informatika and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper studies the housing sector of Hong Kong and the role of collateral constraint in modelling Hong Kong economy, through the lens of a small open economy DSGE model with a currency board exchange rate commitment. By estimating and evaluating the model by Indirect Inference over the sample period of 1994Q1–2018Q3, it is found that the collateral model can match data behaviour. Comparing with the tests generated from the model without collateral, collateral model can match the housing price data better, while the model without collateral fits the general price better. Since collateral constraint acts like an additional transmission channel, it enhances the impact from shocks and housing price is highly determined by housing demand. We further investigate LTV policy, finding it could be applied as macroprudential policy, especially when addressing the problem caused by increase in the US interest rate and the burst in the domestic housing demand, but the government should watch closely to the crowding out effect from export to housing demand and housing investment. [ABSTRACT FROM AUTHOR]

Fluctuations in the international price of crude oil follows the axioms of the market economy, in which the prevailing price level is mostly decided by the demand and supply mechanism as a fundamental element. Oil price shocks has a negative and significant effect on Gross Domestic Product. Oil shocks transmission mechanism to the economy, starting from the effects of demand, supply, and even exchange rate of trade. Another factor having a significant effect on the stability of the financial system is the monetary cycle, which consists of inflation and the effect of exchange rates. The type of data in this study was time series data taken from January 2020 to December 2022 by conducting a documentation study conducted on the publication of monthly transaction reports from the required data. Financial System Stability Index is measured by the Credit Growth Rate of North Sumatra and monthly data from the Monetary Cycle and Macroeconomic Factors of World Oil Price. Inflation Variable had the highest extraction value, meaning that inflation had a significant effect on North Sumatra Financial Stability and this of course must be taken into consideration for the North Sumatra government in overcoming the impact of covid-19 which can disrupt the financial stability of North Sumatra. The variable money velocity was a moderating variable affecting the relationship between currency exchange rates and the financial system stability of North Sumatra. The results found that financial system stability could be realized by limiting the circulation of foreign currency in Indonesia by only granting ownership permits and foreign currency transactions for certain needs. Then the government must also play a serious role in dealing with the symptoms of inflation by ensuring that the supply chain of basic commodities for industrial and household needs can be comprehensively available so that inflation control can be carried out properly, so that the stability of the monetary system in a country can be achieved significantly and sustainably. [ABSTRACT FROM AUTHOR]

The global foreign exchange (FX) market represents a critical and sizeable component of our financial system. It is a market where firms and investors engage in both speculative trading and hedging. Over the years, there has been a growing interest in FX modeling and prediction. Recently, machine learning (ML) and deep learning (DL) techniques have shown promising results in enhancing predictive accuracy. Motivated by the growing size of the FX market, as well as advancements in ML, we propose a novel forecasting framework, the MVO-BiGRU model, which integrates variational mode decomposition (VMD), data augmentation, Optuna-optimized hyperparameters, and bidirectional GRU algorithms for monthly FX rate forecasting. The data augmentation in the Prevention module significantly increases the variety of data combinations, effectively reducing overfitting issues, while the Optuna optimization ensures optimal model configuration for enhanced performance. Our study's contributions include the development of the MVO-BiGRU model, as well as the insights gained from its application in FX markets. Our findings demonstrate that the MVO-BiGRU model can successfully avoid overfitting and achieve the highest accuracy in out-of-sample forecasting, while outperforming benchmark models across multiple assessment criteria. These findings offer valuable insights for implementing ML and DL models on low-frequency time series data, where artificial data augmentation can be challenging. [ABSTRACT FROM AUTHOR]

We show that macroprudential regulation significantly dampens the impact of global financial shocks on emerging markets. Specifically, a tighter level of regulation reduces the sensitivity of GDP growth to capital flow shocks and movements in the Chicago Board Options Exchange's VIX. A broad set of macroprudential tools contributes to this result, including measures targeting bank capital and liquidity, foreign currency mismatches, and risky credit. We also find that tighter macroprudential regulation allows monetary policy to respond more countercyclically to global financial shocks. This could be an important channel through which macroprudential regulation enhances macro‐economic stability. We do not find evidence that capital controls provide similar benefits. [ABSTRACT FROM AUTHOR]

A model for determining the oil market transferability turmoil on the financial markets of the Iranian economy using the dynamic systems approach. At first, data related to oil, gold, stock exchange and foreign exchange were extracted from statistics related to the World Bank, Central Bank and Statistics Center of Iran and were analyzed with statistical analysis and simulation software. Then the research model was constructed using simulation methods and system analysis and the results were analyzed. The oil market in supply and demand for price determination is based on global systemic behavior. this simulation has used the factors affecting oil supply, oil demand, the expectations that shape this supply and demand, as well as macro factors such as macroeconomic indicators of the US economy, sanctions on the oil sector in Iran, the rate of world industry development and the available knowledge on oil substitution. Hidden mechanisms are the main reason for some oil price behaviors. The results of the research have led to the forecast of oil prices in the baseline scenario until 2025. The presence of political problems due to the interconnectedness of parallel markets in Iran causes widespread fluctuations in the currency and gold sectors in the Iranian economy. [ABSTRACT FROM AUTHOR]

The study aimed to validate the necessity of formulating and executing plans for incorporating the concepts of the circular economy into Ukraine's agriculture sector, while considering the impacts of globalisation and problems arising from the war. This study examined the fundamental principles and intellectual underpinnings that differentiate the circular economy from the conventional economic model. The fundamental concept of the circular economy in the agricultural sector was justified, and the primary benefits of implementing this economic model in the field of agriculture were established. The European Commission has approved the strategy for the Common Agricultural Policy for the period 2023-2027. This strategy emphasises the primary responsibilities that EU member states must undertake to implement the principles of the circular economy in agriculture. The primary patterns in the operation of agriculture in Ukraine are recognised, and the significance of the agricultural sector in the framework of gross domestic product (GDP) formation and foreign exchange profits is established. The destruction of infrastructure, mining activities, and occupation of regions resulted in a decline in the cultivated land and animals, leading to a loss in physical productivity. Due to the war, there has been a decline in production and logistics capabilities, resulting in a large fall in the export of agricultural products. Consequently, the profitability of firms in this sector of the Ukrainian economy has also decreased. Ukrainian agricultural firms lack the financial resources to independently support creative development, which includes the implementation of new technology solutions that form the foundation of the circular economy. Considering the effects of globalisation and military conflict, it is justified that prioritising innovation and investment support, particularly by the State, should be a strategic direction for implementing the principles of the circular economy of agriculture in Ukraine. This approach will enhance economic efficiency and create new opportunities. [ABSTRACT FROM AUTHOR]

Exchange rate modeling has always fascinated researchers because of its complex macroeconomic dynamics. This study documents the exchange rate dynamics of major emerging economies after accounting for their macroeconomic cycles and explores the Bayesian Vector Error Correction Model (VECM) Markov Regime switching model, which uses time‐varying transition probabilities. The main objective is to study the exchange rate dynamics of Brazil, Russia, India, China, and South Africa (BRICS) vis‐à‐vis the US dollar. The Bayesian setup uses two hierarchal shrinkage priors, the normal‐gamma (NG) prior and the Litterman prior, for parameters' estimation. These shrinkage priors allow for a more comprehensive assessment of the regime‐specific coefficients. The model performed well in differentiating between the two regimes for all currencies. The Russian ruble was identified to be the most depreciated currency, whereas the African Rand was the most appreciated. The evaluation of model features revealed that many regime‐specific coefficients differed significantly from their common mean. A forecasting exercise was then performed for the out‐of‐sample period to assess the model's performance. A significant improvement was observed over the basic random walk (RW) model and the linear Bayesian vector autoregression (BVAR) model. [ABSTRACT FROM AUTHOR]

Understanding the complex relationship between crude oil futures and exchange rates is essential due to its profound implications for global economies and for making policy decisions worldwide. Previous studies have employed various methodologies to explore this dynamic, yet gaps in understanding persist. In this study, we address this gap by paying special attention to countries like Iran, Singapore, UAE, Venezuela, Iraq, Kazakhstan, Azerbaijan, Angola, Algeria, Pakistan, and Bangladesh. For this purpose, we use several methodologies on monthly dataset from January 1998 to February 2024. Our findings reveal that the exchange rates of Singapore and UAE are notably affected by net fluctuations, while results across other countries exhibit inconsistency. Furthermore, our analysis uncovers evidence of time-dependent and bilateral transmission of shocks between the oil and foreign exchange markets. These findings underscore the intricate interaction between crude oil futures and exchange rates, offering premium insights for policymakers and stockholders alike. [ABSTRACT FROM AUTHOR]

We apply a time-varying parameter VAR (TVP-VAR) extended joint connectedness approach, in addition to the generalized connectedness approach, to understand the connectedness of crude oil futures price and exchange rates of major oil-dependent countries. We find time-varying nature of pair-wise and total connectedness that are usually elevated during events such as COVID-19, Brexit, European sovereign debt crisis and global financial crisis. Both joint and generalized connectedness approaches confirm that Japanese Yen and Russian Ruble are the leading net receiver of the shocks, though the two approaches provide mixed results for some other currencies. Moreover, there is strong evidence of time-varying and bi-directional shock transmissions between oil and foreign exchange markets. We also show that oil price volatility and gold price have predictive power on the connectedness. Lastly, we analyse the policy and portfolio implications. [ABSTRACT FROM AUTHOR]

We use the staggered enactment of anti-recharacterization laws as a plausibly exogenous shock to the value of securitizing collateral through special purpose vehicles (SPVs) and test how collateral values impact corporate risk management. Following the laws' enactment, we find increases in commodity, foreign exchange, and interest rate hedging, especially for firms with exposure to these risks and that rely on SPVs. Supporting the collateral constraints literature, the effect is weaker for firms that likely need the collateral for external financing, such as financially constrained firms. Our findings highlight fluctuations in collateral values as an important consideration in risk management decisions. [ABSTRACT FROM AUTHOR]

The present research paper is focused the widely debated topic related to de-dollarization. It examines the trend of de-dollarization to check if the statements that the dollar is losing its weight and is about to lose its leading position in international trade payments are substantiated. Firstly, the theoretical framework behind the dollarization is explored. Secondly, the factors believed to be the basis of the de-dollarization process have been identified and analyzed, which are related to: geopolitical processes, changes in international payments policy in some BRICS countries, changes in international trade, etc. A performed analysis of the currency turnover in international trade, based on data from official sources, was made through forecast regression, which predicts the development of the share of the dollar in international payments. A correlation matrix was also calculated, showing the correlation links between the dollar and the other leadng currencies. The hypothesis, which is confirmed by the practical research, is that the de-dollarization process is proceeding slowly and uncertainly, and will continue to develop at a low pace leading to insignificant changes in the structure of the currency composition of international payments in the short and medium term. Further research could further explore each of the factors that could lead to a real dedollarisation trend in international payments.

We propose a novel extremal dependence measure called the partial tail-correlation coefficient (PTCC), in analogy to the partial correlation coefficient in classical multivariate analysis. The construction of our new coefficient is based on the framework of multivariate regular variation and transformed-linear algebra operations. We show how this coefficient allows identifying pairs of variables that have partially uncorrelated tails given some other variables in a random vector. Unlike other recently introduced conditional independence frameworks for extremes, our approach requires minimal modeling assumptions and can thus be used in exploratory analyses to learn the structure of extremal graphical models. Similarly to traditional Gaussian graphical models where edges correspond to the nonzero entries of the precision matrix, we can exploit classical inference methods for high-dimensional data, such as the graphical Lasso with Laplacian spectral constraints, to efficiently learn the extremal network structure via the PTCC. We apply our new method to study extreme risk networks in two different datasets (extreme river discharges and historical global currency exchange data) and show that we can extract interesting extremal structures with meaningful domain-specific interpretations. [ABSTRACT FROM AUTHOR]

Utilizing firms in the S&P 500, we study whether greater transparency in the reporting of other comprehensive income (OCI) items, as mandated by ASU 2011-05, resulted in a reduction in information asymmetry, a change in the value relevance of this information, or a change in hedging practice. Our results show that while transparent reporting reduced information asymmetry, firms that engage in cash flow hedging do have greater information asymmetry than their counterparts that do not hedge. We find evidence that investors penalize firm value for greater volatility of OCI relative to net income volatility when reported transparently. When permitted, managers were able to mitigate the negative impact by reporting OCI only in the Statement of Shareholders' Equity. We conclude that managers' concerns regarding potential confusion surrounding OCI volatility following more prominent reporting led to changes in hedging behavior. After transparent reporting, we find a reduced likelihood of foreign currency cash flow (FXCF) hedges and a reduced level of FXCF hedging among firms experiencing the greatest volatility of unrealized hedging gains and losses. [ABSTRACT FROM AUTHOR]

The currency exchange rate is a crucial link between all countries related to economic and trade activities. With increasing volatility, exchange rate fluctuations have become frequent under the combined effects of global economic uncertainty and political risks. Consequently, accurate exchange rate prediction is significant in managing financial risks and economic instability. In recent years, the Transformer models have attracted attention in the field of time series analysis. Transformer models, such as Informer and TFT (Temporal Fusion Transformer), have also been extensively studied. In this paper, we evaluate the performance of the Transformer, Informer, and TFT models based on four exchange rate datasets: NZD/USD, NZD/CNY, NZD/GBP, and NZD/AUD. The results indicate that the TFT model has achieved the highest accuracy in exchange rate prediction, with an R2 value of up to 0.94 and the lowest RMSE and MAE errors. However, the Informer model offers faster training and convergence speeds than the TFT and Transformer, making it more efficient. Furthermore, our experiments on the TFT model demonstrate that integrating the VIX index can enhance the accuracy of exchange rate predictions. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Using a novel data set comprising bid–ask quotes for foreign exchange swaps from individual dealers, we examine the consequences of the Swiss National Bank's sudden termination of the Swiss franc/euro minimum exchange rate in 2015 on other pegged currencies. Our findings indicate a spillover effect as dealer banks began to reassess the risk associated with unexpected peg terminations, subsequently leading to wider bid–ask spreads for pegged currencies. This highlights that, even in strong economies, the credibility of a currency peg is influenced not only by the actions of the respective central bank but also by the stability of other pegged currencies. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01117. [ABSTRACT FROM AUTHOR]

Many studies have examined the asymmetric effect of US dollar-denominated crude oil prices on petroleum product prices. The 'rockets and feathers' argument suggests that a crude price increase raises petroleum product prices more than a corresponding decrease in crude prices lowers product prices. However, for the countries that do not use the US dollar as a medium of exchange, petroleum product prices are also affected by the exchange rates. This paper analysed the asymmetric effects of both US dollar-denominated crude oil prices and exchange rates on local currency-denominated diesel prices for 27 European countries in the short run as well as long run. The overall empirical evidence suggests that, in the short run, diesel prices react more to crude oil price increases than to a decrease, parallel to the 'rockets and feathers' argument. However, contrary to that argument, the long-run adjustment is the opposite. As for exchange rate shocks, again the 'rockets and feathers' argument holds and diesel prices respond more to exchange rate depreciation than appreciation in the short and long run. [ABSTRACT FROM AUTHOR]

Financial market dynamics in the context of the foreign exchange and currency markets have undergone changes through diverse changes and transformations including integration of innovations such as artificial intelligence (AI). Financial market strategies including hedging and pricing strategies through the implementation of AI have been capable of impacting the currency, credit, and financial derivative markets against market exposure risks. AI technology acts as an innovative integration that intends to improve the situation of foreign exchange, credit risks, currency market, and financial derivatives strategies of hedging and pricing through its algorithmic and predictive models. AI's predictive and automating capabilities are among its beneficial and useful aspects that contribute to innovate financial derivatives regarding market exposures and risk management of credit and currency markets by reducing the risk of error and enhancing productiveness and preparedness for risk management within the market. [ABSTRACT FROM AUTHOR]

This research work focused on diaspora remittances and growth of the agricultural sector in Nigeria. Annual time series data on workers remittances, migrant remittances, foreign direct investment and exchange rate were employed in the research. Using econometric techniques (error correction model and the vector auto regression model), the research found that workers remittances, migrant remittances and FDI have increased the output of the agricultural sector in Nigeria. Exchange rate decreased the inflow of official remittances to the agricultural sector. The study concluded that for the period 1990 - 2022, remittances had enhanced the output of the agricultural sector with migrant remittances having the most effect. Thus, the main recommendations was that government should pursue the unified exchange rate policy, intensification and sustenance of the inflow of remittances to the agricultural sector through the provision of a formal channel for Nigerian workers and migrants to send in monies into Nigeria without rigorous hurdles. (C12,F24,Q14). [ABSTRACT FROM AUTHOR]

While guest or honourary authorship in academic papers is a broadly and widely discussed phenomenon in biomedical research, the issue of the use—or abuse—of article-processing charges (APCs) as a form of potential authorship exchange currency, that is, the 'APC ring,' is neither being considered nor discussed. The APC is central to the open-access (OA) movement, specifically the gold OA model. It is conceivable that, in a hyper-competitive academic publishing environment where the number of gold OA journals is growing, a segment of poorly funded researchers aiming to publish in ranked OA journals with out-of-reach APCs might turn to richer or well-funded researchers to cover the APC bill in exchange for authorship. Despite this, no published cases directly documenting APC-for-authorship schemes as a form of guest authorship appear to exist, which seems inconceivable. One possible explanation is that if such unethical behaviour were to be detected by APC-charging OA journals, it might not be reported as such. In this situation, APC-dependent OA journals would be conflicted between receiving a financial lifeline, the APC, and exposing authors that have abused the APC in their journals in exchange for authorship. How would publishers dependent on the APC-based OA model justify receiving APCs derived from an APC ring? Although this form of guest authorship is currently hypothetical, it seems highly likely, so this issue needs greater debate, and if actual case studies exist, these need to be openly and publicly debated to better appreciate how this phenomenon is taking place. [ABSTRACT FROM AUTHOR]

The paper highlights the immediate and delayed impact of certain factors on the exchange rate dynamics in Ukraine. It is proved that exports of food products and raw materials for their production can significantly strengthen the national currency in the long run. Continuous growth in food exports helps to slow down exchange rate appreciation, which ultimately leads to a stronger national currency. Thus, a strategy of focusing on increasing food exports can play an important role in strengthening the Ukrainian currency in the long run, having a positive impact on exchange rate dynamics and contributing to overall economic stability. The study reveals the understanding of the complex relationship between war, food security, and economic stability. Furthermore, the analysis adds a new dimension to the debate on the strategic importance of the agricultural sector for foreign exchange reserves and foreign exchange accumulation. Understanding the relationship between export volumes, world prices, and exchange rate fluctuations can help to better predict and manage currency fluctuations and to determine the extent to which Ukraine's revolving fund capacity can be built. [ABSTRACT FROM AUTHOR]

This paper examines the uncovered interest parity puzzle in Central and Eastern European countries. Apart from investigating baseline UIP regressions, we check for structural breaks in this relationship, scrutinize deviations from the UIP, and employ different estimation methods and models augmented with various risk measures. Moreover, we offer several extensions to the common UIP testing that account for foreign-exchange interventions, the implied volatility of exchange rates, and the limited availability of data on direct measures of market expectations. The study shows that the choice of the reference currency matters for the outcome of the interest parity tests in the CEE economies. In particular, we demonstrate that inconsistencies between the results of the UIP tests vis-à-vis the euro and the US dollar that appear in CEE economies may be accounted for by the movements of the euro-dollar risk premium. This regularity has not been documented in previous studies. Additionally, we show that (a) the FX interventions in Czechia distorted the UIP, (b) the directly measured exchange rate expectations (granular survey data) in Poland do not seem to be informed by the UIP relationship, (c) the limited resilience of CEE economies to rare disasters may plausibly explain deviations from the UIP. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering (17264073) is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Crude palm oil (CPO) is one of the most consumed edible oils in the country, compared to other major agro-commodity oils. This study seeks to investigate the daily price movements of CPO in India based on the degree of movements of external macroeconomic factors such as Brent crude oil price and dollar-based daily exchange rates. The co-relationship between the above variables is studied using multivariate generalized autoregressive conditional heteroskedasticity (GARCH), constant conditional correlation (CCC) and dynamic conditional correlation (DCC) GARCH approach. The results indicate no spillover effects and hence no dependency of CPO price on currency exchange rate. However, there exists some direct impact of global crude oil prices on Indian CPO price fluctuations. Also, the degree of covariance is quite significant among the currencies of Malaysia, Indonesia, and India. This study would help industry stakeholders and practitioners hedge against imminent market risks arising from unanticipated changes in India's palm oil prices. [ABSTRACT FROM AUTHOR]

Many of the great strategies of companies with good plans and program face failure. If the managers’ mental models as the source of their thinking contradict these plans, these plans will not be successful. Managers can increase the probability of success of strategies by shaping their minds and examining and developing their mental image. One of the products with high potential in export and foreign exchange in the country and especially in Khuzestan province is dates, which has many areas of growth and progress in this field by creating an efficient marketing and structuring approach. Important and basic export of Khuzestan dates; Presented a mental model of date export obstacles in Khuzestan province. This research was a type of exploratory mixed research, in the qualitative part based on the theory derived from the data and in the quantitative part based on the descriptive-survey method. The qualitative part of the tool was a semi-structured interview and the quantitative part was based on a questionnaire. The statistical population in the qualitative section included experts, specialists, and date exporters, and saturation was achieved after interviewing 20 people. In this research, the qualitative part was analyzed with Max Kyuda software and the quantitative part was analyzed based on Lisrel software. The results showed that individual thinking; collective thinking; decision-making power; direct individual understanding; type of individual behavior; Creativity; developing a mental image of oneself; Understanding export behavior and simplifying complex issues is one of the obstacles to exporting dates. Based on the impact on the central category of the mental model of date export obstacles, in addition to the quantitative model, the pattern obtained based on the qualitative model was confirmed. Based on the findings, a multi-dimensional marketing system should be created based on the related structure and commercial knowledge to reduce the barriers to date export, and macro laws and regulations can help in improving and speeding up the barriers in this field. [ABSTRACT FROM AUTHOR]

This document outlines the analysis, design, implementation, and benchmarking of various neural network architectures in a short-term frequency prediction system for the FOREX market. Our objective is to emulate the decision-making process of a human expert (technical analyst) through a system that swiftly adapts to market condition changes, thereby optimizing short-term trading strategies. We have designed and implemented a series of LSTM neural network architectures that take exchange rate values as input to generate short-term market trend forecasts. Additionally, we developed a custom ANN architecture based on simulators for technical analysis indicators. We performed a comparative analysis of the results and came to useful conclusions regarding the suitability of each architecture and the cost in terms of time and computational power to implement them. The ANN custom architecture produces better prediction quality with higher sensitivity using fewer resources and spending less time than LSTM architectures. The ANN custom architecture appears to be ideal for use in low-power computing systems and for use cases that need fast decisions with the least possible computational cost. [ABSTRACT FROM AUTHOR]

Cambodia is one of the first two countries that adopted a retail central bank digital currency (CBDC) in October 2020. The design of the CBDC, called the Bakong, is a bit unique. We find a few design flaws that could potentially damage the central bank and then the Cambodian economy as a whole. We show some key statistics from our own survey in 2022 to support our arguments. The Bakong is offered in two currencies, the Khmer Riel (KHR) and the US dollar (USD), as Cambodia has been highly dollarized. We discuss theoretical predictions for the CBDC based on three kinds of substitutes: paper money, bank deposits, and foreign currencies. The third one is specific to the Bakong. Unlike a typical local currency CBDC, the USD Bakong may substitute for the KHR more. Moreover, it has been announced that the retail Bakong is legally not a liability of the central bank, but from the viewpoint of the underlying technology and economics, it is a central bank liability. [ABSTRACT FROM AUTHOR]

Purpose: This paper examines the impact of global crises, including the Global Financial Crisis (GFC), the COVID-19 pandemic, and the subsequent inflation crisis, on the fluctuations of the Real Effective Exchange Rate (REER). The cyclicality of REER has been examined as influenced by economic shocks, highlighting how pandemic-induced economic disruptions have reshaped REER dynamics differently from the more financially triggered fluctuations of the Global Financial Crisis. Design/methodology/approach: The methodology employs a comparative spectral analysis approach, utilizing time-series data to track REER movements across various countries. Findings: The findings indicate that the GFC and the COVID-19 pandemic led to shortening periods of cyclicality. Moreover, there has been a noticeable improvement in the synchronization of REER movements post-GFC, suggesting that economies may converge in their responses to global economic shocks. This convergence implies a potential stabilization of exchange rate movements in the face of future crises, underlining the importance of coordinated monetary policies. Research limitations/implications: To model the REER index, one can use also classical analytical methods such as VAR models, where macroeconomic factors can serve as variables. In spectral analysis itself, other filters like the Hodrick-Prescott filter or applying a spectral window can be used. Practical implications: The conducted study implies an improvement in synchronization among financial systems, with this knowledge, more appropriate and rational monetary decisions can be made, and private entities can better employ hedging strategies against currency exchange rate fluctuations. The study also aids in identifying inflationary pressures and the impact of the global financial system on the inflation index in individual countries. Originality/value: The methods used in the article represent an innovative approach to modeling the REER index, providing new insights into the cyclicality of the index and the shortening periods of its occurrence. The article is addressed both to researchers in this field and to individuals involved with the monetary system and those working in the financial industry. [ABSTRACT FROM AUTHOR]

Illicit financial flows have been an issue of great concern over the past decades due to the challenge they present for economic development in Africa. Illicit financial flows undermine the productivity and growth of African economies as countries lose foreign exchange and tax revenues. Countries lose financial resources needed for development programs, hence undermining social service delivery and retarding poverty reduction. To effectively combat illicit financial flows, it is imperative to examine their determinants. This study seeks to examine the determinants of illicit capital movement in the China‐Africa trade through the mechanisms of trade misinvoicing over the period 1990–2019. The IMF's Direction of Trade Statistics (DOTS) database is used to estimate trade misinvoicing. Estimates using mirror trade data indicate that both exports of Africa to China and imports from China to Africa are mainly underinvoiced. The net effect shows that trade misinvoicing in the China‐Africa trade results in net illicit capital outflow for about 44% of countries in Africa. The results from panel data regressions indicate that tax evasion is one of the major factors behind misinvoicing in China‐Africa trade. In addition, corruption control is found to reduce export underinvoicing, while political stability reduces both export overinvoicing and import overinvoicing. Export misinvoicing increases with the presence of natural resources in the exporting country. Other factors associated with trade misinvoicing in China‐Africa trade include openness to trade, current account deficit, and real exchange rate. The study suggests ways to reduce trade misinvoicing in China‐Africa trade. [ABSTRACT FROM AUTHOR]

Purpose: The use of economic sanctions has grown dramatically in recent decades. Nevertheless, many arguments are presented in the public policy space regarding their effects on target populations. The author presents the first systematic analysis of the effects of sanctions on living conditions in target countries. Design/methodology/approach: This paper provides a comprehensive survey and assessment of the literature on the effects of economic sanctions on living standards in target countries. The author identifies 31 studies that apply quantitative econometric or calibration methods to cross-country and national data to assess the impact of economic sanctions on indicators of human and economic development. The author provides in-depth discussions of three sanctions episodes—Iran, Afghanistan and Venezuela—that illustrate the channels through which sanctions affect living conditions in target countries. Findings: Of the 31 studies, 30 find that sanctions have negative effects on outcomes ranging from per capita income to poverty, inequality, mortality and human rights. The author provides new results showing that 54 countries—27% of all countries and 29% of the world economy— are sanctioned today, up from only 4% of countries in the 1960s. In the three cases discussed, sanctions that restricted the access of governments to foreign exchange limited the ability of states to provide essential public goods and services and generated substantial negative spillovers on private sector and nongovernmental actors. Originality/value: This is the first literature survey that systematically assesses the quantitative evidence on the effect of sanctions on living conditions in target countries. [ABSTRACT FROM AUTHOR]

Successful conduct of monetary policy is known to be critical for ensuring macroeconomic stability. The central banking system of Ethiopia has neither achieved stability in prices nor in the foreign exchange market in the recent years. However, it is unclear how monetary policy decisions translate into important macroeconomic outcomes in Ethiopia. This paper uses descriptive tools and econometric estimates from a structural vector autoregression model based on quarterly time series data for 2006-2020 to address this question. It is shown that reserve money, which is the central bank's operating target, is a weak predictor of macroeconomic goal variables. This observation, allied with the lack of central bank independence, transparency and communication with the public, can help explain the inefficacy of the monetary targeting regime. It is also found that the prevailing structure and development of the financial system is problematic for effective monetary transmission. The results imply that successful monetary policy requires a two-pronged effort: a short-run strategy aimed at revising the monetary policy framework, and a medium- to long-run strategy aimed at reforming the financial services sector. [ABSTRACT FROM AUTHOR]

The aim of this study is to delve into the intricate the mechanism through which alterations in currency exchange rates give rise to shifts in inflation rates, while taking into careful consideration the country's economic cycle. In order to accomplish this objective, we used a dataset that spanned from 1 January 1999 to 1 July 2023, focusing our analytical lens on three specific geographic areas, namely the Eurozone, the United Kingdom, and Canada. In our pursuit of understanding this complex relationship, we employed the Markov Switching Vector Autoregressive model. Our research outcomes can be succinctly encapsulated as follows: in the initial stages, particularly during phases characterized by robust economic growth, the transmission of exchange rate effects onto inflation levels appeared to exhibit a partial impact across all geographic areas under examination. However, during periods marked by economic downturns, both the United Kingdom and Canada displayed a distinctly more comprehensive transmission of these effects. Moreover, the prevailing projections for the forthcoming time horizon, across all the countries encompassed by our study, strongly indicate the onset of an expansionary phase that is projected to extend over a span of 25 months. Lastly, concerning the implications of unexpected disturbances or shocks, it is noteworthy that the response of exchange rates to inflation induced shocks was neither immediate nor as pronounced as the corresponding reaction of inflation to sudden shifts in exchange rates. [ABSTRACT FROM AUTHOR]

Travelers who lack extensive experience or those visiting multiple countries in a short timeframe often need help to differentiate and identify the values of mixed foreign coins. This paper introduces a model that employs You Only Look Once (YOLO) object detection to identify various foreign coins within a single image frame and thoroughly evaluate its performance. The model, developed on Google Colab, has been trained using a dataset of 8,100 images and successfully identifies 18 different classes of coins, including the US dollar, European euro, and Chinese yuan. Implementing the model as a mobile-friendly web application allows users to upload images of their coins, and the application will provide identification results along with the option to receive the latest currency exchange information. The performance metrics scores of the model were 0.892, 0.932, and 0.925 for Precision, Recall, and Accuracy, respectively, showing satisfactory results. [ABSTRACT FROM AUTHOR]

In the ever-evolving landscape of global commerce, marked by the convergence of digital transformation and borderless markets, this research addresses the intricate challenges of currency exchange and risk management. Leveraging Bayesian optimization, the study fine-tunes the random forest algorithm using the extensive Klarna E-commerce dataset. Through systematic analysis, the research uncovers insights into managing currency prediction amid dynamic global markets. Emphasizing the role of Bayesian optimization parameters, the study reveals nuanced trade-offs in model performance. Notably, the optimal simulation, conducted with 14 iterations, 1 job, and a random state set to 684, exhibits a standout performance, showcasing a negative mean squared error (MSE) of approximately -0.9891 and an accuracy rate of 74.63%. The primary objective is to assess the impact of Bayesian optimization in enhancing the random forest algorithm's predictive capabilities, particularly in currency prediction within international e-commerce. These findings offer refined strategies for businesses navigating the intricate landscape of global finance, empowering decision-making through a comprehensive understanding of data, algorithms, and challenges in international commerce. [ABSTRACT FROM AUTHOR]