Euro Exchange Rate Research Articles

Nonlinear relationships between the participation index and key financial assets: A quantile regression analysis

The Participation Index is essential for assessing market sentiment, investor confidence, and financial market direction. Gold, known for its historical role in protecting wealth and providing a stable asset during economic instability, plays a key role in investment portfolios as an alternative guarantee against financial market fluctuations. The USD and EUR are key current currencies in global economics, affecting international trade, financial transactions, and investment decisions. The purpose of this study is to analyze the complex relationships between the Participation Index (KAT) and three significant financial assets: gold, the US dollar (USD), and the Euro (EUR) using Quantile Regression analysis. Daily data between 16.11.2021-08.08.2023 were used in this study. According to the results; the impact of the euro exchange rate on the "KAT" variable exhibits a positive relationship, which increases as the quantile level rises. The impact of the exchange rate of the United States Dollar (USD) on the variable defined as "KAT" indicates a positive relationship, which intensifies as the quantile level rises. The relationship between gold prices and the "KAT" variable shows a positive strengthening impact as the quantile level increases, and these effects demonstrate a high level of statistical significance.

Oil prices and the euro exchange rate

We use cointegration-based techniques to investigate the relationship between oil prices and the euro effective exchange rate taking also into account the influence of interest rates and stock prices. We find that higher oil prices cause a depreciation in the euro exchange rate (either nominal or real) in the short run. This suggests that during episodes of higher energy prices, the euro area consumer is faced with additional price pressures, as a depreciated euro causes import prices to further rise. Our study also indicates that as stock prices rise in the short and long term, the euro appreciates, while higher oil prices will likely result in overall higher policy rates and lower stock prices.

Synchronization analysis between exchange rates on the basis of purchasing power parity using the Hilbert transform

Synchronization is a phenomenon in which a pair of fluctuations adjusts their rhythms when interacting with each other. We measure the degree of synchronization between the U.S. dollar (USD) and euro exchange rates and between the USD and Japanese yen exchange rates based on purchasing power parity (PPP) over time. We employ a method of synchronization analysis using the Hilbert transform and find that the degree of synchronization is high most of the time, which suggests the establishment of PPP. The degree of synchronization does not remain high across periods with asymmetric economic events such as the U.S. real estate bubble.

Are Turkish pharmaceutical pricing strategies an access barrier to oncology medicines for Türkiye?

Objectives: Cancer diagnosis is increasing day by day all over the world. Deaths due to cancer are among the most common causes of death. Access to cancer drugs is a priority of health policies. The aim of this study is to evaluate access to cancer drugs through drug box sales data by modeling population growth, cancer incidence, and Fixed Euro Exchange (FEE) rate parameters used in drug pricing in Türkiye. Methods: Access to cancer drugs was evaluated by drug box sales figures obtained from IQVIA. Box sales data were classified according to diagnosis codes (ICD-10), reference, or generic status. Consumption of cancer drugs was examined over time with panel regression analysis, taking into account variables of population growth, cancer incidence, and the FEE rate in drug pricing in Türkiye. Results: The incidence of cancer in Türkiye was 215.1 in 2010 and 223.1 (per hundred thousand) in 2017. Whereas there was a 127.02% increase in the real euro exchange rate, there was an 89.6% increase in the FEE rate. With the regression approach, there is a negative relationship between the real and fixed exchange rate difference (RFED) and reference and generic drug consumption data. Medicine access is affected depending on diagnosis codes at different levels. Colorectal cancer medicine sales had negative correlations for each variable, namely, exchange rate, population growth, and cancer incidence. On the contrary, there was a positive correlation between non-small-cell lung cancer and relevant variables. Innovative medicine groups such as monoclonal antibodies and protein kinase inhibitor consumption showed a negative correlation. Conclusion: According to our results, pricing strategy may be an access barrier for oncology medicines in Türkiye. It should be reviewing the pricing policy that is beneficial for oncology medicine access in Türkiye.

Detecting Multiple Level Shifts in Bounded Time Series

The article proposes a sequential statistical procedure to test for the presence of level shifts affecting bounded time series, regardless of their order of integration. The article shows that bounds are relevant for the statistic that assumes that the time series are integrated of order one. In contrast, they do not affect the limiting distribution of the statistic that is defined for time series that are integrated of order zero. The article proposes a union rejection statistic for bounded processes that does not require information about the order of integration of the stochastic processes. The model specification is general enough to consider the existence of structural breaks that can affect either the level of the time series and/or the bounds that limit its evolution. Monte Carlo simulations indicate that the procedure works well in finite samples. An empirical application that focuses on the Swiss franc against the euro exchange rate evolution illustrates the usefulness of the proposal.

Identifying the Probability Distribution of Exchange Rates in Sri Lanka

The exchange rate is one of the main components that represents the status of a country’s economic condition. This study mainly focuses on identifying an appropriate distribution that can capture the asymmetric behaviour of important currency exchange rates related to Sri Lanka. The true behaviour of the exchange rates of USD, EURO, JPY, AUD, GBP, CHF, SGD and CAD in terms of LKR was determined using flexible distributions of generalised lambda distribution (GLD), Normal Inverse Gaussian and Skew-Normal. The parameter estimation was carried out by maximum likelihood estimation (MLE), while for GLD, few more parameter estimation techniques were applied. To understand how well the fitted distributions identify the real behaviour of data, we conducted the goodness-of-fit (GOF) tests. The results from Cramer–Von Mises (CvM) and Anderson–Darling (AD) GOF tests pointed out that the exchange rates data follow a GLD with the parameter estimation of maximum product of spacings (MPS). Further, plots of histograms with theoretical densities, cumulative distribution functions (CDFs) with empirical CDF and Quantile–Quantile plots illustrated the same idea. This study presented the findings based on different suitable parameter estimation techniques and this study is the first investigation on the distribution identification of exchange rates in Sri Lanka. JEL Codes: C12,C13,G10

A study on the risks and efficiency of the forex market based on the detrended fluctuation analysis

Exchange rate fluctuations profoundly impact macroeconomic variables, making them a focal point for policymakers. This study is grounded in the efficient market hypothesis (EMH), asserting that such forecasts offer no utility due to all relevant information being embedded in asset prices. The research problem is rooted in the dynamics of currency exchange rate fluctuations and their impact on the Albanian economy. The research aims to analyse Albanian lek (ALL)/euro (EUR) exchange rate dynamics and their impact on Albania’s economy, assessing market efficiency and providing insights for monetary and fiscal policy design. The method used is a detrended fluctuation analysis (DFA) which consists of a root mean square analysis of a random walking pattern (Peng et al., 1994). This method is used to assess adherence to the weak form of EMH. Findings indicate that the Albanian foreign exchange market closely resembles a random walk, suggesting efficiency during specific periods. The study underscores the exchange rate’s dual impact: its influence on domestic price levels and its broader implications for the real economy and balance of payments. This paper is relevant as it offers crucial insights into currency exchange rate dynamics and their economic impacts, supporting policymakers in improving Albania’s economic stability and market efficiency.

An empirical analysis of the dynamic impact of DeFi on GCC foreign exchange forward markets: portfolio implication

PurposeThis paper aims to investigate the conditional equicorrelation and cross-quantile dependence between the DeFi, European and GCC currency markets (Oman, Qatar, Bahrain, Kuwait, Saudi Arabia and the United Arab Emirates).Design/methodology/approachThis study applies the GARCH-DECO model and cross-quantilogram framework.FindingsThe findings reveal evidence of weak and negative average equicorrelations between the examined markets through time, excluding the COVID-19 outbreak and Russia–Ukraine conflict, which is consistent with the literature examining relationships in different markets. From the cross-quantilogram model, the authors note that the dependence between DeFi, EURO and GCC foreign exchange rate markets is greatest in the short run and diminishes over the medium- and long-term horizons, indicating rapid information processing between the markets under consideration, as most innovations are transmitted in the short term.Practical implicationsFor the pairs of DeFi and currency markets, the static and dynamic optimal weights and hedging ratios are also estimated, providing new empirical data for portfolio managers and investors.Originality/valueTo the best of the authors’ knowledge, this is one of the most important research looking into the conditional correlation and predictability between the DeFi, EURO and GCC foreign exchange markets. More importantly, this study provides the first empirical proof of the safe-haven, hedging and diversification qualities of DeFi, EURO and GCC currencies, and this work also covers the COVID-19 pandemic and the Russia–Ukraine war with the use of a single dynamic measure produced by the GARCH-DECO model. In addition, the directional predictability between variables under consideration using the cross-quantilogram model is examined, which can be capable of capturing the asymmetry in the quantile dependent structure. The findings are helpful for both policymakers and investors in improving their trading selections and strategies for risk management in different market conditions.

Determinants of Ethereum Return: Insights from Bitcoin, Investor Sentiment, and Financial Markets

The study explores the spillover effect on Ethereum one of the leading cryptocurrencies stemming from key variables in the domains of cryptocurrencies, investor sentiment, and traditional financial markets. This paper is the first to analyze the influence of such dominant representatives from diverse, external fields on cryptocurrency. We select bitcoin, the Fear and Greed index, the Standard and Poors 500 index and the United States Dollar to Euro Exchange Rate as representatives to investigate the spillover effect on Ethereum. Utilizing linear regression models and vector autoregressive (VAR) models, we find strong correlations between Ethereums return and that of Bitcoins, along with investor sentiment. However, the influence of financial market variables on Ethereum are found to be virtually static and negligible. This research offers valuable insights to those seeking to forecast or manipulate crypto market movement through analyzing the complex interplay between these variables and Ethereum.

Funding gap in the Hungarian venture capital market

Our study investigates the size of the so-called financing gap in the Hungarian venture capital market, i.e. the amount that can potentially be lent out, which is currently not covered by the Hungarian financial intermediary system on a market basis. The relevant literature will be reviewed to assess the performance and characteristics of the Hungarian market. The Hungarian financial intermediation system, traditionally based on banking, underperforms in all segments of capital market financing, even by Central and Eastern European standards. In our research, we sought to find out whether the available sources of venture capital could meet market needs. Both the number and volume of transactions in the domestic venture capital and private equity markets are low by international standards, and the role of the state is below the average for CEE countries. The novelty of our analysis lies in the fact that there is no similar literature available in Hungary. Our estimation based on linear regression revealed a strong relationship between venture capital investment and current GDP. The difference between the estimated potential risk capital stock and the annual averages zrealized clearly shows the market gap. In addition to the public programmes already implemented, the annual amount of risk capital missing from the domestic market is in the order of EUR 12.5-31.6 million, i.e. roughly HUF 5.1-13.3 billion per year at the euro exchange rate at the time of analysis. If this resource were available, domestic startups would have greater growth opportunities. Our analysis suggests that not only a state presence but even an increase in it, seems justifiable (or at least worth exploring). The research was supported by the National Research, Development and Innovation Office (FK-142492).

The Effect of the Pandemic and the War in Ukraine on the Riskiness of Financial Investments in Three Central European Countries

ABSTRACT The COVID pandemic and the war in Ukraine are extraordinary events causing excessive turbulence in financial markets. Considering the leptokurtic and heteroscedastic properties of returns on financial assets, we examine the suitability of several alternatives for modeling returns to choose the most suitable option to compute the VaR and CVaR for returns of three stock market indices as well as euro exchange rates in Czechia, Poland, and Hungary. Using an appropriate test, we evaluate how the two metrics of VaR and CVaR changed during the pandemic and the war in Ukraine up to June 2022.

Euro area uncertainty and Euro exchange rate volatility: Exploring the role of transnational economic policy

This study examines the relationship between economic policy uncertainty and Euro area exchange rate volatility, focusing on transnational Euro area uncertainty. The study introduces a novel index that captures uncertainty related to Euro area integration. The index is constructed using both traditional and advanced textual analysis methods. By employing a quantile regression framework, findings show that Euro area uncertainty significantly impacts the euro exchange rate's volatility, while national economic policy uncertainty is generally insignificant. The study emphasizes the importance of considering both national and supranational uncertainties when analysing exchange rate volatility, contributing to the existing literature on this subject.

Early warning of exchange rate risk based on structural shocks in international oil prices using the LSTM neural network model

The Russia–Ukraine conflict has caused an external shock to the oil market as the exchange rate risk increased with significant depreciation of major currencies relative to the U.S. dollar (USD). In this paper, structural shocks to oil prices calculated by the Ready (2018) method are introduced in addition to traditional exchange rate predictor variables such as oil prices. Utilising a long short-term memory neural network model, we verify the early warning effect of structural shocks to international oil prices on exchange rate risk in the context of the Russia–Ukraine geo-conflict. We have several empirical findings. First, the variance decomposition method indicates that oil price shocks affect the euro-dollar exchange rate risk. After the conflict between Russia and Ukraine, the euro exchange rate risk continued to rise significantly, mainly affected by supply shocks. Second, compared with traditional prediction models, the LSTM neural network model has a higher prediction accuracy, which is conducive to improving the early warning performance of exchange rate risks and maintaining the stability of the foreign exchange market. Third, the introduction of oil price shock can fully extract and use the information from oil price changes, which significantly improves the learning performance of the oil price early warning model of exchange rate risk. Fourth, the introduction of oil price risk shocks in the whole sample, the introduction of oil price demand shocks before the Russia-Ukraine conflict, and the introduction of oil price supply shocks, especially negative supply shocks, after the conflict between Russia and Ukraine, can warn exchange rate risks more effectively. This study proposes a new method for early warning of exchange rate risk that can help cross-border enterprises and government policymakers to respond to unexpected events and effectively mitigate associated risks.

Fractional cointegration between energy imports to the EURO area and exchange rates to the US dollar

Fractional cointegration between energy imports to the EURO area and exchange rates to the US dollar

Predictability and forecasting performance of major euro exchange rates using a relative PPP-based equilibrium model

Using an alternative approach to the real exchange rate, we investigate the predictability of major currencies against the euro and its predecessors, the EUA and ECU. The unique forecasting methodology is based on deviations from a relative PPP-equilibrium exchange rate (EER), which is constructed from the EERs of individual euro member countries going back to 1974. Testing the mean reverting behavior, we report half-lives of less than two years and some less than one year. Predicting exchange rate movements, we find average success rates of the euro converging toward the constructed EERs of higher than 70%, especially over 12-month horizons and when deviations are large. Employing a linear recursive forecasting methodology, the model statistically significantly outperforms the random walk model at horizons of close to or less than one year and in some cases over a 1-month forecasting horizon. Finally, the forecasting performance increases during crisis periods.

The Effect of the Dollar, Euro, and Sterling Exchange on the Tourism Index in the Turkish Economy

The exchange rate expresses the value of the national currency in terms of foreign currency. While foreign currency is an important investment tool in the portfolio of all kinds of investors in our modern world, it is also one of the most important elements of international trade. In particular, the impact of exchange rates on the tourism sector cannot be ignored. The aim of this study is to examine the relationship between monthly data and BIST tourism index (XTRZM) for the period January 2011 – July 2022 and exchange rates (US Dollar exchange rate, Euro exchange rate and Sterling exchange rate) by using the time series process. Whether there is a relationship between the variables was analyzed by econometric analysis method. In the study, in which the Granger model was applied, it was determined that there was a causal relationship between all four variables. A bidirectional relationship was found only between dollar and sterling exchange rate changes. A unilateral causality relationship was found between all other variables. 

The Euro exchange rate's resistance to the exogenous shock caused by COVID-19

Background: The COVID-19 pandemic represents the greatest exogenous global shock in the last few decades, which has deeply affected the macroeconomic aggregates around the world. Bearing in mind that COVID-19 pandemic is an exogenous shock; its effect on the macroeconomic aggregates will take time to be analysed, while it has a persistent impact on the financial markets. Purpose: One-third of the transactions worldwide includes the Euro. Hence, the main objective of this study is to estimate the Euro exchange rate's resistance to the exogenous shock caused by the COVID-19 pandemic. Study design/methodology/approach: This paper employs the General AutoRegressive Conditional Heteroskedasticity (GARCH) model to examine the EUR/USD exchange rate's resistance to the global exogenous shock caused by the COVID-19. In other words, the authors try to find an answer to question whether the COVID-19 pandemic affects the EUR/USD exchange rate volatility. Finding/conclusions: The results show that the COVID-19 pandemic has no effect on the EUR/USD exchange rate volatility in the long run. These results may confirm our assumption of the resistance of the financial market to the exogenous shock and are useful for anyone needing forecasts of the exchange rate futures movements. The obtained results produce pragmatic expertise in order to manage exchange rate risk and should support policymakers to advance exchange rate policy. Limitations/future research: As a limitation of this study, the authors state the estimation of the Euro exchangeratès resistance to only one exogenous shock, caused by COVID-19. Bearing in mind that in the considered period was also the world economic crises which might have caused a higher volatility then COVID-19, for further research the authors propose an examination of the detailed estimation of the Euro exchangeratès resistance to different exogenous shocks.

Legal consequences of exhaustion of the amount allocated for co-financing of projects under the appeal procedure in the 2021-2027 financial perspective

Analysis and assessment of the legal effects of exhausting the amount allocated for co-financing of projects under the appeal procedure in the system of implementation of the EU cohesion policy in Poland in the 2021-2027 financial perspective. Literature review, analysis of relevant legal regulations and the jurisprudence of administrative courts. The provisions of the Act on the rules for the implementation of tasks financed from European funds in the 2021-2027 financial perspective erroneously equate the exhaustion of the amount allocated for co-financing of projects under a measure or region category with the sum of funds distributed by concluding agreements or issuing administrative decisions on project co-financing. They do not take into account the fact that due to, e.g. the availability of additional financial resources resulting from termination of co-financing agreements or an increase in the euro exchange rate, the exhaustion of the allocation may change until the end of programme’s implementation period. It is necessary to shape the appeal procedure in such a way that will provide the applicants with a real chance of obtaining co-financing, because the implementation and protection of their constitutional rights cannot depend on the exhaustion of the available allocation of financial resources.

Consequences of Russian invasion on Ukraine: evidence from foreign exchange rates

PurposeThe stability of exchange rates facilitates international trade, diminishes portfolio risk, and ensures that economic policies are effective. The war in Ukraine is showing that the European financial system is still fragile to external shocks. This paper examines the consequences of the Russian invasion of Ukraine on five Euro exchange rates. The final goal is to empirically test whether the ruble caused the euro to depreciate with the Russian invasion of Ukraine.Design/methodology/approachThe exchange rates analyzed are Euro/Russian Ruble, Euro/US Dollar, Euro/Japanese Yen, Euro/British Pound, and Euro/Chinese Yuan. The data collected are daily and cover the period from November 1, 2021, to May 1, 2022. In this context, the changes in the FX rates reflect two months of the ongoing war in Ukraine. The FX rates used in the study contain 137 observations indicating five months of daily series.FindingsThe results from impulse response function, variance decomposition, SVAR, and VECM indicate that the EUR/RUB significantly influenced the Euro devaluation. On the other side, the FX rates used in our work altogether hold long-run cointegration. The situation is different in the short run, where only EUR/RUB, EUR/USD, and EUR/CNY possess significant relations with other parities.Originality/valueThe Ruble is not among hard currencies, but its position strengthened during this period due to the importance of Russian gas to the Eurozone. The results indicate that even weak currencies can be influential depending on the geopolitical and economic situation. To this end, diversification remains a valid concept not only in portfolio construction but also for the preservation of the national economy.

Determination of Factors Affecting Dollar and Euro Exchange Rates with Two Dependent Variable MARS Model

Determination of Factors Affecting Dollar and Euro Exchange Rates with Two Dependent Variable MARS Model