Exchange Risk Research Articles

Risks in AGRIGULF's Agricultural Export Settlement Business and Its Management

This paper is primarily a case-based study. It takes Gulf Modern Agriculture Development Co., Ltd (hereinafter referred to as AGRIGULF) as the object of research, and adopts the case study method and field interview method to sort out the company's agricultural products export business and common settlement methods and so on. Through field visits and investigation, data collection, and collation, identify and analyze the risks of the company's agricultural export settlement business. Finally, corresponding risk management suggestions are put forward at four levels, namely, country risk, foreign exchange risk, product quality change risk, and credit risk, which are expected to provide certain references for the sustainable development of China's agricultural export enterprises

Foreign exchange risk and audit pricing: Evidence from U.S. multinational corporations

Foreign exchange volatility challenges auditors for not only demanding more audit efforts but also imposing heightened audit risk. We first show foreign exchange risks increase cash flow uncertainty and reduce financial reporting quality, supporting our premise that foreign exchange risks increase audit risk. Next, we find audit fees are higher for MNCs with greater exposure to foreign exchange volatility, but not when MNCs use financial hedging against foreign exchange risk. Furthermore, we show that the impact of foreign exchange risk on audit fees is attenuated by auditor MNC expertise, auditor busyness, and MNC’s operation diversity, whereas the impact is exacerbated for companies facing high pressure to avoid missing earnings targets and for auditors with high market concentration. Overall, our study provides novel evidence of the implications of MNCs’ exposure to foreign exchange risk on financial reporting and auditing, thereby enriching our understanding of MNCs.

Forecasting implied volatilities of currency options with machine learning techniques and econometrics models

AbstractDeveloping an effective modeling framework to minimize foreign exchange (FX) risk is of vital importance for hedgers and traders in FX markets. In this study, we compare the ability of long short-term memory (LSTM) models to that of random forest and several time series models for forecasting EURUSD implied volatility across the volatility surface. As our literature study argues, there are only a few published papers on this subject. We find that the LSTM model is the best model for shorter option maturities, while the AR-GARCH model is superior when the maturities increase. We observe that the LSTM model is able to capture immense and immediate changes in implied volatility, which is important for hedging against significant shifts in FX rates.

Volatility connectedness on the central European forex markets

We perform a comprehensive assessment of volatility connectedness between the currencies of Central European (CE) countries using high-frequency data from 2009 to 2022. We provide evidence of asymmetries in connectedness that are dominated by negative volatility, especially during periods of economic distress. We also detect statistically significant economic or political events that lead to increased volatility connectedness. Plus, we document the impact of global shocks, not local ones. Further, the existing lag in the response of the spillover index to stressful events offers an opportunity to effectively hedge foreign exchange risk and to use the CE currencies as hedging tools. Finally, in terms of market-specific factors, liquidity dominates uncertainty as a connectedness driver. Our results are robust with respect to volatility measures and provide direct policy implications for portfolio composition and hedging.

A secure and efficient UAV network defense strategy: Convergence of blockchain and deep learning

Unmanned Aerial Vehicles (UAVs) are highly versatile and efficient tools utilized across diverse industries for data collection. However, they are vulnerable to wireless communication and data exchange risks, including unauthorized access, data theft, and network attacks. To address these problems, we introduce a secure and reliable UAV network service architecture that incorporates blockchain and deep learning to provide more secure and efficient network services for UAVs. We propose a UAV cluster identity management module by combining blockchain, encryption algorithms, and digital signatures to enhance the security of UAV communication data transmission. Then, based on machine learning, deep learning, and malicious process detection technology, we propose a real-time secure situational awareness system for UAV cluster terminal devices to enhance the security of the operating environment for UAVs. Finally, we propose a data-trustworthy interconnection platform based on blockchain, smart contracts, and consensus algorithms to realize secure and efficient sharing and transmission of terminal data. The results of the experiments demonstrate the feasibility and effectiveness of our UAV network service architecture.

Impact of Automobile Companies Stock Returns on Indian Stock Market Indices with Special Reference to Nifty Fifty Index

The Nifty Fifty Index has a free-float market capitalization-weighted index.it represents the weighted average of the top 50 Indian companies listed on the National Stock Exchange ,and it is one of the main stock indices being used in India, besides the BSE Sensex of the Bombay Stock Exchange. The Nifty 50 index represents 62% of the free float market capitalization of the stocks listed in the NSE (NATIONAL STOCK EXCHANGE) as on September 30,2022.sectors ‘s stocks are performing more consistently and provide high return with high risk in (NSE)NATIONAL STOCK EXCHANGE ,these stocks are emerging as most reliable stock in capital market. Nifty Fifty Index also influenced by the variation in Automobile Industry which happened due to market fluctuation .The Automobile Sector has influenced by micro and macro indicators So in this, researcher found a relationship between Nifty Fifty Index and different selected Automobile companies by the application of some statistical tools like as regression to examine the impact of different companies stock return on Nifty fifty Index and correlation to check the relationship between Nifty Fifty and Automobile Sector Companies. And for this study data of 18 years from 1 January 2003 December 2022 has been taken. After the application of test this can be concluded that nifty fifty Index have impact of Automobile companies’ stock return variation on it and Nifty fifty index and Automobile companies are highly positively correlated with each other. At last it can be recommended that one variable can be used for forecasting another variable. So it can be concluded that development of economy and capital market has a relationship with performance of Automobile Industry in stock market and its return providing capacity. This study is going to be helpful for those investors who prefer to invest in Automobile Sector.

人民币汇率变动与上市公司外汇风险暴露——基于双变量GJR-GARCH模型的实证分析

人民币汇率变动与上市公司外汇风险暴露——基于双变量GJR-GARCH模型的实证分析

Risk managers on managing foreign exchange risk

Risk managers on managing foreign exchange risk

Risk managers on managing foreign exchange risk

Risk managers on managing foreign exchange risk

Broken Hill Proprietary Billiton report: Analysis Available Strategy to Hedging Risks by Using Futures Contracts, Foreign Exchange Futures

With the development of multinational companies, plenty of companies confront enough problems in financial management. This paper using real figure analysis method to conclude companies financial problems. After data analysis, we found Broken Hill Proprietary Billiton as one of the multinational company, it faced enough problems as commodity price risk, currency exchange rate risk and interest rate risk. In this case, hedging strategies with derivatives are used to minimize the risks of financial loss. Futures contract can be used to deal with commodity price risk and risks of currency exchange risk by locking in price and reduce uncertainty of market movements. Finally, contrast advantages and disadvantages for each strategy. After analysis of Broken Hill Proprietary Billiton, it could provide enough strategies to alleviate financial risks for multinational companies.

Analisis Risiko Nilai Tukar Mata Uang Asing Dengan Menggunakan Metode Value at Risk (VAR) Pada Bank Muamalat Indonesia

This study aims to measure the maximum potential loss or VaR value for each type of Foreign Exchange based on the calculation results for 1 day, 5 days, and 20 days at Bank Muamalat Indonesia and determine the implementation of risk management applied by Bank Muamalat Indonesia to deal with foreign exchange risk. The research method in measuring Value at Risk of foreign exchange rates uses quantitative methods. The type of data that the author uses in this study is secondary time series data on foreign exchange rates of USD, JPY, EUR, and SAR at Bank Muamalat Indonesia. during the time period 2 January 2018 to 31 December 2018. Data analysis techniques in the study were carried out in several stages, namely calculating exchange rate returns, volatility and daily value at risk. The results showed that the maximum exchange rate risk borne in 1 day, 5 days and 20 days with a 95% confidence level. The implementation of underlying in foreign exchange transactions at Bank Muamalat Indonesia refers to the National Sharia Council regulation No.96 / DSN-MUI / IV / 2015 concerning Sharia Hedging Transactions (Al-Tahawwuth Al-Islami / Islamic Hedging) on Exchange Rates. Bank Muamalat has conducted hedging cooperation with PT Kharisma Pemasaran Bersama Nusantara (KPBN) or Indonesia Commodity (Inacom) on 05 December 2019 as a form of Foreign Exchange Rate risk management.

The uncertainty of RMB exchange rate expectation and foreign investment: Evidence from Cross-border M&As in China

This paper investigates the causal effect of the RMB exchange rate expectation uncertainty on corporate cross-border mergers and acquisitions (M&As) using China's A-share listed firms from 2005 to 2022. The results show that the increasing RMB exchange rate expectation uncertainty significantly promotes corporate cross-border M&As. A one-unit standard deviation of the RMB exchange rate expectation is associated with a 0.140-unit standard deviation increase in corporate cross-border M&As. The results are robust for replacing core variables, changing estimation methods, model setting, and addressing endogenous problems. The above effect is more pronounced for firms engaging in discontinuous M&As, partial M&As, higher operational and exchange risks, lower financing constraints, and firms located in Eastern regions. We also find that increased risk-taking capacity and greater market competition are essential channels through which RMB exchange rate expectation uncertainty promotes corporate cross-border M&As. This paper offers a fresh insight into the role of exchange rate expectations in promoting cross-border M&A activities and optimizing resource allocation in international markets.

The Impact of RMB Exchange Rate Fluctuation on China's Air Conditioning Industry

Based on the background of China's current trade with other countries is becoming increasingly close, the study of exchange rate stability on the impact of China's trade with other countries to promote China's economic stability has a certain theoretical significance. In the study of air conditioning industry import and export trade factors affecting the attention of the national exchange rate is very important, in the two countries trade relations, the exchange rate is a measure of the two countries to buy, sell the price of the product of the vital factors, exchange rate changes for the enterprise will bring a certain degree of impact, stabilization of the exchange rate for the promotion of our country and the trade of other countries in the long term and good cooperation has important practical significance. The air-conditioning manufacturing industry is a very representative research object. The cost-sensitive home appliance industry is a labor-intensive industry, which provides a huge number of jobs for China and creates a huge amount of foreign exchange income. At the same time, the home appliance industry, as a representative of China's manufacturing industry, faces industrial upgrading pressure and is in the maturity of a fully competitive industry, which has been severely impacted by exchange rate changes. It is of great significance to correctly measure and analyze the foreign exchange risk exposure of the import and export of the air-conditioning industry and its influencing factors. From a micro point of view, enterprises can be based on foreign exchange risk exposure situation targeted adjustment of financial strategies, strategies and management methods. From a macro point of view, the country can be based on the overall foreign exchange risk exposure characteristics of home appliances to formulate the correct macroeconomic policy.

A Study of Bayesian Quantile Regression for Forecasting RMB Exchange Rates

Accurate forecasting of the RMB exchange rate is crucial for global financial market participants. This study proposes a Bayesian quantile regression approach to enhance the forecasting method. This paper uses RMB and US dollar exchange rate data from the State Administration of Foreign Exchange from 2018 to 2022 to build a Bayesian quantile regression model and empirically analyze the RMB exchange rate forecast. The results show that the proposed Bayesian quantile regression model yields accurate forecasts, with a root mean squared error (RMSE) of 1.8329 and a mean absolute error (MAE) of 1.2988. Furthermore, robustness and sensitivity analyses confirm the model's reliability. The findings of this study have practical implications for financial market participants and policymakers in managing and responding to foreign exchange risk.

Risk Assessment of the Banking Industry under the COVID-19 Crisis

This paper shows that increased bank asset liquidity does not necessarily reduce risk-taking. The help provided by the government in the epidemic crisis has also been provided after the damage occurred. On the other hand, the merger of banks is not a good thing for low-risk banks. Regulators should conduct frequent financial reports on banks to ensure that the risk of sudden default due to weak supervision is reduced. Foreign exchange risk management is especially important for banks involved in cross-border transactions and foreign exchange business. Reasonable control of the market exchange rate prohibits the impact of the foreign exchange black market on the market. The COVID-19 epidemic has led to fluctuations and instability in global exchange rates and the banking industry. For the foreign exchange transaction risks caused by exchange rate fluctuations, banks usually need various foreign exchange derivatives instruments to ensure that foreign exchange risks are effectively managed.

Effect of Liquidity Shock on Financial Performance of Listed Commercial Banks in Nairobi Securities Exchange, Kenya

A strong banking system is essential to the stability and expansion of the economy. However, all banks face significant risks in the unpredictably volatile environment of today, encompassing credit risk, interest rate risk, operational risk, liquidity Shock, market risk, and foreign exchange risk. Liquidity Shock is one of many risks that commercial banks that are listed in the Nairobi Securities Exchange (NSE) are subjected to. This risk can have a significant effect on the financial performance of these banks. As such, the purpose of the study was to analyze the effect of liquidity Shock on financial performance of commercial banks listed in Nairobi Securities Exchange. An independent variable, liquidity shock contribute to this risk. This study concentrated on commercial banks which are listed in the Nairobi Securities Exchange market (NSE, 2022); and utilized data from 2013-2022. The study was anchored on liquidity shock theory, A quantitative research design was used for the study. The study adopted a Census, which included all the 11 commercial banks listed in the NSE for the period 2013 to 2022 due to availability of data. Secondary data was collected from the reported financial statements of respective commercial banks for the period 2013 to 2022. Obtaining published financial statements from each of the listed commercial banks on the NSE over a ten-year period – yearly is part of the data collection process. In order to analyze the relationship between liquidity Shock and financial performance of commercial banks with NSE listings, the data was subjected to panel regression analysis. To statistically describe the data, measures of central tendency, dispersion, and position was used. To determine whether the data adhered to the conventional least square assumptions, diagnostic tests were utilized. 

A novel multifactor clustering integration paradigm based on two-stage feature engineering and improved bidirectional deep neural networks for exchange rate forecasting

Accurate exchange rate forecasting is of great importance for foreign exchange investment, hedging foreign exchange risk and international economic transactions. However, it is extremely challenging to make accurate forecasts for exchange rates because of their high volatility, nonlinearity, and non-stationarity. Based on this, this paper proposes a multifactor clustering integration paradigm for exchange rate prediction. From the classical theory of exchange rate determination, a comprehensive library of factors affecting the exchange rate is constructed. A two-stage feature engineering is constructed to capture the stable structure of features. In order to enable features to be learned adequately and to improve algorithmic efficiency and predictive performance, a novel clustering integration paradigm is constructed to improve the stability of the model. The framework builds different predictive sub-models for different data, and then embeds Bayesian optimization algorithms into the bidirectional deep neural networks. Finally, the output results of different sub-models are integrated using nonlinear integration techniques. In addition, the superiority of the proposed model is verified using eight comparative models. The results of the empirical analysis show that the average percentage error of our proposed model is the lowest among all the comparative models (0.412648 %, 0.515348 %, and 0.329892 % on the three datasets, respectively). Compared to the standard LSTM, the average percentage error is at least 88 % lower, proving the effectiveness of the proposed model. It can help investors to make better decisions in the international financial markets.

The role of natural gas in setting electricity prices in Europe

The EU energy and climate policy revolves around enhancing energy security and affordability, while reducing the environmental impacts of energy use. The European energy transition has been at the centre of debate following the post-pandemic surge in power prices in 2021 and the energy crisis following the 2022 Russia-Ukraine war. Understanding the extent to which electricity prices depend on fossil fuel prices (specifically natural gas) is key to guiding the future of energy policy in Europe. To this end, we quantify the role of fossil-fuelled vs. low-carbon electricity generation in setting wholesale electricity prices in each EU-27 country plus Great Britain (GB) and Norway during 2015-2021. We apply econometric analysis and use sub/hourly power system data to estimate the marginal share of each electricity generation type. The results show that fossil fuel-based power plants set electricity prices in Europe at approximately 58% of the time (natural gas 39%) while generating only 34% of electricity (natural gas 18%) a year. The energy transition has made natural gas the main electricity price setter in Europe, with gas determining electricity prices for more than 80% of the hours in 2021 in several countries such as Belgium, GB, Greece, Italy, and the Netherlands. Hence, Europe’s electricity markets are highly exposed to the geopolitical risk of gas supply and natural gas price volatility, and the economic risk of currency exchange.

Large firm effect in enterprise risk management

AbstractMicro-level risk awareness affects macro-level financial stability as well. Thus, the corporate risk management practice impacts the exposures and the potential fragility of an economy. While corporate risk management is accepted to create value in an imperfect market, the effect of the firm size is not straightforward. Smaller, financially constrained firms can benefit more by engaging in risk management programs, but larger corporations face more complex risks and have more resources for this activity. Empirical studies on risk management focusing mainly on the US market, highlight a positive relation between the firm size and the quality of risk management that includes not just the hedging of financial risks, but the concept of integrated risk management as well. The aim of this paper is two-fold: first, to summarize the existing literature on corporate risk management with a special focus on the effect of corporate size; second, to contribute to the existing literature by investigating a Central European market, Hungary. The findings are similar to those of the existing global literature, as derivatives usage, and applications of an integrated risk management concept increase with firm size. Although all firms in the sample manage their foreign exchange risk, interest rate hedging and more sophisticated derivatives, like options, are much less widespread in Hungary, compared to the US and Asian peers. The size effect is proven for the objective criteria of risk management quality by comparative analysis and a structured modelling framework, however, the subjective self-evaluation was uncorrelated to the size.

Macroeconomic Indicators and Financial Performance of Insurance Firms Listed at the Nairobi Securities Exchange

Purpose: The general objective of the study was to determine how macroeconomic variables affected the financial performance of insurance firms listed on the Nairobi Securities Exchange. The study's specific goals were to identify how inflation, interest rates, exchange rates and gross domestic product affected those same companies' financial performance.
 Methodology: A descriptive survey research design was used for the investigation. All the six insurance companies listed on the Nairobi Securities Exchange made up the study's target group hence a census-style analysis. The panel regression model was used in the investigation and relied on secondary information that was gathered using a data collection sheet. The five-year period covered by the data was from 2017 to 2021.
 Findings: According to the report, insurance is severely impacted by inflation. There was a general increase in exchange rates and there was a fluctuation in the economic growth. From the findings, the study concludes that the insurance companies were operating on economic conditions that became increasingly challenging as shown by increasing inflation rates. The CBR and lending rates showed a general downward trend in the five years’ period, the exchange rates in the Kenyan economy were changing rapidly, there were major changes in the economic performance of the Country emanating from various occurrences including global oil crisis and COVID-19 pandemic. Despite the harsh economic conditions, the NSE listed insurance companies posted healthy financial performance as shown by ROA values above 5%.
 Unique contribution to theory, practice and policy: The study recommends that the NSE listed insurance companies to make ample adjustment for inflation so that during seasons of high inflation the firms do not run at a loss. The study also recommends the NSE listed insurance companies firms to employ strategies where they can purchase more futures contracts on government bonds or interest rate futures in order to be able to lock-in interest rate and hedge their various portfolios. The NSE listed insurance companies are also recommended to mitigate the exchange rate risks by hedging the foreign exchange risk by purchasing spot contract to cushion against any negative swing. The government through line ministries of finance and planning should undertake measures to ensure good performance of the economy.