Exchange Risk Research Articles

Neural networks and ARMA-GARCH models for foreign exchange risk measurement and assessment

Neural networks and ARMA-GARCH models for foreign exchange risk measurement and assessment

Hedge Accounting Disclosures and Sustainable Growth of Listed Deposit Money Banks in Nigeria

The primary problem facing listed deposit money banks in Nigeria is their struggle to achieve sustainable growth in a volatile economic environment. This study investigated the impact of hedge accounting disclosures on the sustainable growth of these banks, focusing on commodity hedge disclosure, interest rate hedge disclosure, and foreign exchange rate disclosure, while controlling for market capitalization. Using an ex post facto research design, the study analyzed secondary data from 11 selected banks over a period of 10 years from 2014 to 2023. The method of data analysis was random effect regression technique. The findings revealed that commodity hedge disclosure (COMD) and interest rate hedge disclosure (INTD) have significant positive effects on the sustainable growth rates of listed deposit money banks in Nigeria. Conversely, foreign exchange rate disclosure (FEXD) has a significant negative effect on sustainable growth, indicating that high levels of foreign exchange risk exposure, when disclosed, may reduce investor confidence and perceived stability. The study concluded that hedge accounting disclosures significantly impact sustainable growth of listed deposit money banks in Nigeria. It recommended the management of listed deposit money banks in Nigeria should enhance commodity and interest rate hedge disclosures to improve the quality of foreign exchange risk communication.

Bitcoin arbitrage and exchange default risk

We investigate how exchange default risk and liquidity affect Bitcoin cross-exchange arbitrage opportunities. Analyzing minute-level data from 16 cryptocurrency exchanges (April 2013–April 2024), we find arbitrage opportunities last longer when higher-risk exchanges have higher prices, as traders are cautious of default risks. There is a strong positive relation between capital flows from high-risk to low-risk exchanges and arbitrage opportunities, showing a preference for safer exchanges. Liquidity accelerates arbitrage by enabling faster execution, but high transaction fees and blockchain congestion slow capital transfers. The paper highlights exchange risk, liquidity, and transaction costs as key factors in Bitcoin market efficiency.

The Utilization of Blockchain for Data Security for the Chronic Pain Physician.

The COVID-19 pandemic accelerated the surge in medical data utilization, notably impacting chronic pain management given its enormous economist cost. While the collection and use of data enhances research and care quality, data exchange risks compromising integrity and privacy, exemplified by the Change Healthcare cyberattack. Here, we review the potential of blockchain for the utilization for cybersecurity in the healthcare system with an emphasis on the field of chronic pain. Blockchain technology emerges as a potential solution, offering decentralized, secure, and immutable data management. Blockchain ensures transparency, integrity, and data privacy, which is crucial in healthcare. Smart contracts may offer automated, secure management of implantable neuromodulation devices such as spinal cord stimulators and intrathecal pumps. Blockchain's potential in pharmaceutical supply chain integrity is exemplified in preliminary efforts ensuring that the medication retrieved by the patient is indeed the intended medication. Despite limitations such as speed of transactions, blockchain presents innovative avenues for healthcare security and quality improvement, necessitating further development for widespread implementation. Blockchain's applicability is not only applicable to chronic pain management, but can be used in medicine as a whole.

Bat (Chiroptera) viruses of Russia and neighboring countries

Aim. To analyze the diversity of bat viruses in Russia and neighboring countries. To identify the main vectors of these pathogens and possible ways of introduction into the territory of the Russian Federation.In Russia the RNA sequences of 36 Coronaviridae, 8 Rhabdoviridae and 3 Astroviridae have been obtained from bats. In neighboring countries, RNA/DNA sequences of viruses in bats have been found in Norway (2), Finland 14), Poland 42), Ukraine (8), Georgia (46), Kazakhstan (29), China (5.645) and Japan (109). The dsequences which have been discovered belong to 30 families (Table 1). An increase in the number of sequences obtained over the past year has been observed in Russia and China. The absolute majority of sequences belong to the Coronaviridae family (62.96 %).The available data on bat viruses in Russia indicate the need to develop and implement a state interdisciplinary programme dedicated to this problem. The greatest danger is posed by Rhabdoviridae: mortalities after infection have been recorded in Russia. The data obtained also indicate that the main vectors of viruses are representatives of the genera Eptesicus, Myotis, Nyctalus, Rhinolophus and Vespertilio. The risk of virus exchange and transmission is most likely to be between the western part of Russia and European countries.

Foreign Exchange Risk Analysis and The Futures Hedging Strategy Construction--- The Case Study of Amazon

This paper explores the foreign exchange risk encountered by Amazon.com Inc. and proposes corresponding futures hedging strategies. With global market uncertainties, foreign exchange risk significantly impacts the financial performance of multinational companies like Amazon. The paper analyzes Amazon's foreign exchange risk factors, highlighting that the primary risks stem from international business revenues and holdings of foreign currency cash equivalents and marketable securities. Based on these risk factors, the study proposes several potential hedging strategies, including forward market hedging, futures hedging, and exchange rate options hedging. Forward market hedging mitigates risk by agreeing to exchange currencies at a predetermined rate in the future; futures hedging avoids counterparty default risk through standardized contracts; and exchange rate options hedging offers flexibility by allowing the exercise to be abandoned if the exchange rate moves favorably. The paper further develops a specific futures hedging strategy based on several key assumptions, including efficient market hypothesis, zero transaction costs, unlimited liquidity, and the absence of risk-free arbitrage opportunities. The strategy involves shorting futures contracts; if the exchange rate declines at maturity, the hedge is successful and profitable; if the exchange rate rises, the hedge is unsuccessful, resulting in a loss. The findings suggest that using futures contracts for hedging enables Amazon to stabilize its financial performance in case of market uncertainties, protecting it from adverse impacts of foreign exchange risk. Despite discrepancies between actual sales data and forecasts, the hedging strategy still demonstrates its effectiveness in maintaining financial stability.

Assessment of the Risks of Zoonotic Infection at the Primatology Centre of the Interdisciplinary Medical Research Centre of Franceville in Gabon.

Non-human primate (NHPs) conservation sites could be sites of exchange of pathogens involved in infectious diseases. It is important to assess the potential risks associated with this type of structure. The objective of this study was to carry out a risk assessment of the Primatology Centre housed in the Interdisciplinary Centre for Medical Research of Franceville (CIRMF). A questionnaire was administered to the centre's staff to assess the risk associated with each workstation, followed by a review of the various pathogens identified in NHPs. The data were analysed using two diagrams: the Kiviat diagram and the Pareto diagram. Based on our results, a variety of pathogens such as viruses, bacteria and parasites, potentially transmissible to humans, were described in the NHPs at the Primatology Centre of CIRMF. The position most exposed to zoonotic risks was that of animal handlers. The Primatology Centre of CIRMF is a potential transfer site for the transfer of zoonotic agents. To avoid the risk of parasite exchange between staff and animals, the implementation of biosecurity measures is essential.

디지털 무역환경에서 우리나라 중소수출기업의 대금결제 위험관리가 결제위험 관리성과에 미치는 영향: 거래 파트너십 구축지향의 조절효과

Purpose: The purpose of this study is to analyze the relationship between payment risk management and the performance of SME exporters in the digital trade environment. Research design, data, and methodology: In total, 1500 questionnaires were distributed, 200 questionnaires were returned, and 191 were utilized after excluding questionnaires with dishonest or inappropriate responses. Empirical analysis to derive the research results was conducted using the Smart PLS ver. 4.1 statistical package for structural equation modeling. Results: First, credit risk management, B2B trade receivables management, and strategic foreign exchange risk management were found to have a significant impact on payment risk management performance. Second, orientation toward building trade partnerships was found to positively moderate the relationship between payment risk management and payment risk management performance. Conclusions: This study provides guidance on the factors that small and medium-sized enterprise exporters should adopt for managing payment risks, and it is expected to contribute to strengthening export competitiveness by providing practical measures.

Vietnam's exports to Korea and the real exchange rate: Post-crisis evidence from the multiple threshold nonlinear autoregressive distributed lag model

In this study, the asymmetric effects of the real exchange rate on Vietnam's exports to Korea were investigated using the multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model. As a result, the MTNARDL model exhibited enhanced estimation accuracy compared to the single-threshold nonlinear autoregressive distributed lag (NARDL) model. Furthermore, the aggregate bias problem was solved using individual export data for 16 major industries instead of relying on the overall export value data. The results revealed the substantial asymmetric impact of real exchange rate fluctuations in the short and long run. Fluctuations in the real exchange rate boosted Vietnam's exports to the Republic of Korea in the long run, with minimal negative influence. This indicates that the depreciation of the Vietnamese dong against the United States (US) dollar encouraged exports in some industries but limited exports in others. However, the short-term effect of the real exchange rate remains uncertain, as it could be either negative or positive depending on the industry and threshold level. The diverse impacts of the real exchange rate fluctuations on exports across industries were attributed to factors such as the capacity to absorb foreign exchange risks, product heterogeneity, and the ease of adjusting inputs and production for each sector. Therefore, these findings may help policymakers develop Vietnam-specific policies to address long- and short-term changes in the threshold levels of real exchange rate fluctuations.

Explainable machine learning for financial risk management: two practical use cases

We explore the potential of machine learning (ML) models applied in two financial risk management areas, i.e., credit risk management and financial risk hedging, through two practical use cases. This comparative study starts with the issue of explainability in complex ML models used in peer-to-peer lending for credit risk management. The first use case examines the limitations of using Kernel-SHAP with dependent features and evaluates different methods for estimating these dependencies using the Lending Club dataset. Our results suggest that accounting for feature dependence improves the understanding and robustness of prediction explanations. The second use case investigates a dynamic method for hedging foreign exchange risk in international equity portfolios, emphasizing the importance of accurate forecasts of currency returns. The analysis demonstrates that predictions yielded by ML models can significantly enhance the hedging of portfolios against currency risk. These findings highlight the transformative potential of advanced ML models in financial risk management, showcasing their capability to improve financial risk measurement and management. Further, our study outlines future research directions to advance this field.

A Risk Management Strategy under Transfer Pricing for Multi-National Supply Chain along the Belt and Road Initiative

The “Belt and Road Initiative” (BRI) drives international trade more and more frequently, making exchange rates and taxes unavoidable issues for multi-national companies. Thus, exchange risk uncertainty and tax saving planning should be considered in the operational decisions of a multi-national supply chain. This paper constructs a Stackelberg game model with four composite modes to explore the risk-taking and hedging strategy of retailers with reference-dependent psychology. The results show that: (1) exchange rate risk is transmitted through all subjects under the cost-plus transfer pricing strategy, while it is transmitted only between headquarters and retailers under the resale-price transfer pricing strategy. (2) No matter which subject bears the exchange rate risk, the motivation is stronger under the resale-price transfer pricing strategy. (3) The effect of futures hedging exchange rate risk is influenced by retailer reference-dependent psychology. When the reference dependence coefficient is low, and the risk of positive exchange rate fluctuations is too high, the retailer chooses to hedge its exchange rate risk. At this time, the transfer pricing strategy should shift to cost-plus, and the exchange rate fluctuation range that each entity can afford is larger than before hedging.

Auditing challenges in light of foreign exchange risks

Auditing challenges in light of foreign exchange risks

Setting up a sovereign wealth fund to reduce currency crises

This paper assesses whether and how setting up a sovereign wealth fund has a buffer effect against currency crises. Using an innovative dynamic logit panel model framework and a unique dataset covering 34 emerging countries over the period 1989–2019, we empirically show that sovereign wealth funds reduce the occurrence of currency crises. This result is robust to different econometric specifications, alternative definitions of sovereign wealth funds, controlling for currency crisis risk factors, and income level sampling. Our findings have important implications for financial stability and for policymakers, who could further exploit the potential of sovereign wealth funds to better manage foreign exchange risks.

Measuring systemic risk in Asian foreign exchange markets

This paper measures systemic risk in eight Asian foreign exchange markets between 2015 and 2021. We define systemic risk as the risk of significant devaluation in a large number of currencies. Our measures, derived using a time-varying factor copula model, can take into account heterogeneous and dynamic dependencies among markets. Our empirical findings reveal that (1) systemic risk spiked during the US-China trade conflict and the COVID-19 pandemic; (2) Among the currencies studied, the Japanese yen contributes most to systemic risk, while it is the least vulnerable to systemic shocks; (3) Higher levels of regional trade and financial integration increase a currency's vulnerability to systemic risk in the Asian foreign exchange markets.

Hedging global currency risk: A dynamic machine learning approach

We propose a dynamic method to hedge foreign exchange risk of international equity portfolios. The method is based on the currency return forecasts derived from a set of alternative machine learning models, built on the main factor components of the currency return time series. To illustrate our method, we take the perspective of a US portfolio manager investing in a global equity portfolio of developing and developed economies. The analysis of several model performance indicators, back-tested on data from 27 October 2008 to 30 December 2022, allows to conclude that accurate predictions of global currency factor returns, such as those obtained with non linear machine learning models, can improve currency risk hedging of global equity portfolios.

Managing foreign exchange risk: Strategies and techniques in international financial management

El presente estudio examina las creencias y prácticas en torno a la gestión del riesgo cambiario en una muestra heterogénea de participantes. En el contexto contemporáneo de una economía mundial altamente interconectada, la gestión eficaz del riesgo cambiario ha cobrado la máxima importancia para las empresas a fin de proteger su estabilidad financiera y mejorar su competitividad. Mediante el uso del diseño de investigación descriptivo, el estudio abordó las cuestiones con un conjunto diverso de factores demográficos, como el género, la edad y la formación académica, proporcionando información sobre los diversos puntos de vista presentes en las empresas examinadas. El principal objetivo de la investigación descriptiva es proporcionar una descripción y un estudio exhaustivos de las características vinculadas a un determinado acontecimiento, y lo hace sin modificar ningún factor. El análisis de los datos se llevó a cabo con el programa SPSS para la estadística descriptiva, técnicas de dispersión, ANOVA y análisis de modelos de ecuaciones estructurales con IBM AMOS para comprobar las hipótesis. Los resultados del estudio revelan un panorama polifacético de percepciones. Los encuestados muestran perspectivas predominantemente desfavorables con respecto a las técnicas de gestión del riesgo cambiario aplicadas por sus respectivas organizaciones. Se oponen con vehemencia a la aplicación activa de métodos de cobertura, a la utilización competente de instrumentos financieros y a la evaluación periódica de los planes de cobertura. Sin embargo, mantienen una postura neutral a la hora de evaluar la influencia de estas tácticas en los resultados financieros. En resumen, esta investigación pone de relieve la importancia de los esfuerzos continuos encaminados a mejorar la gestión del riesgo cambiario en las empresas. Las organizaciones pueden atravesar con eficacia el intrincado panorama financiero mundial y limitar la influencia de los cambios de divisas en sus resultados financieros abordando de forma proactiva las dificultades reconocidas y fomentando una cultura de mejora continua.

Financial Strengthening Strategies in Increasing Company Competitiveness Multinational

In the era of globalization, multinational companies face complex challenges and opportunities in various jurisdictions. Financial strengthening is a key strategy to increase a company's competitiveness in a dynamic global market. This research examines how efficient financial management, managing foreign exchange risks, optimizing capital structure, and investing in technology can support the stability and growth of multinational companies. Through in-depth literature analysis, this research highlights the importance of integrated and holistic financial strategies to ensure liquidity, reduce risks and maximize profits. With a sustainable and responsible approach, multinational companies can achieve competitive advantage and contribute to inclusive global economic development.

Identification of Bacteria from Public Toilets of Modern Market (Goico) in Musanze Town, Rwanda

Background: Bacteria are present on all surfaces, to which they were carried by many direct and indirect methods of transmission. A toilet is simply a receptacle into which both solid and liquid waste of human origin, in the form of urine and excreta are discharged. In public toilets, complete strangers mix and use the same sanitary facilities, with all the related risks of bodily fluid exchange, contamination and organism transmission. Unhygienic use of the toilet’s facilities may cause urine and fecal residues after use to serve as a major reservoir or source of human pathogen, which may in turn bring about disease outbreak. Aim: This study aimed at Identification of Bacteria from Public Toilets of Modern Market (Goico) In Musanze Town, Rwanda Method: This cross-sectional study was conducted to identify bacteria from GOICO market toilets. About 40 samples; 20 from male and 20 from female toilets were collected and transported to INES-clinical microbiology laboratory for microbiological analysis. Laboratory techniques including culture, gram stain, biochemical tests and antibiogram were performed. Results: The most predominant bacteria isolated was S. aureus (31.43%), followed by S. typhi (20%), Streptococcus(15.71%), E. coli(12.86%), P. aeuriginosa(10%), P. mirabilis(7.14%), C. freundi(1.43%), S. epidermidis (1.43%). It was noted that female toilets were more contaminated (51.43%) than male toilets (48.57%). All gram positive and gram-negative bacteria were sensitive to Gentamicin. Almost all bacteria except P. mirabilis were sensitive to Norfloxacin, gram negative showed a resistance to Vancomycin and Novobiocin. Conclusion: These results should alert public toilets users that extreme caution must be executed while using these toilets, as they may be a source of pathogenic bacteria. The best way to keep a toilet and its seat free of bacteria is to clean it with bleach. Otherwise, keep the bacteria at bay by washing your hands, and if you just don't trust that toilet seat, wipe it down with a disinfectant or antibacterial wipe before you sit. Keywords: Bacteria, Public toilets, E. coli, S. typhi, Urinary tract

Neobanks in emerging markets: a risk assessment

Neobanks have risen as popular digital challengers to incumbent banks, especially in emerging markets (EMs) where the banking sector is often characterized by oligopolies. This article first estimates the value of Nubank and StoneCo in Brazil, two of the fastest-growing neobanks in Brazil. Normalizing revenue growth assumptions from their financial data, valuation models uncover that Nubank could be overvalued by about two times, whereas StoneCo could be undervalued by 80% of its fair value, as of March 19, 2024. This article then discusses firm-specific (high cumulative net operating losses, low long-term operating margins, high borrowing costs) and adherent macroeconomic (political uncertainty, foreign exchange risks, high equity risk premia) risks in EMs that explain the volatility in Nubank’s and StoneCo’s stock prices. These risks are instructive for understanding the challenges facing the business model of neobanks in EMs.

The Measures to Solve the US Subprime Crisis and Inspirations

This paper focuses on the subprime mortgage crisis in the United States at the beginning of the 21st century, and analyzes how this crisis was formed through chain transmission from the perspective of financial bonds in the real estate industry. The paper focuses on the Federal Reserve's policy adjustments and the collapse of the banking system, in order to elucidate the severe impacts of the subprime crisis on the US financial system. Through data collection and attribution analysis, it intends to provide methods for preventing similar crises from happening again, including diversifying policy tools, strengthening supervision, foreign exchange risk management, etc., and provide certain suggestions for the stable operation and resilience of the national financial system.