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The authors make assessment on RMB valuation and to contribute to the fierce debate on this important issue, which is perceived to have a great effect on the improvement or deterioration in trade balance. A triangular analysis approach is put forward and empirical assessment is made. The paper aims to discuss these issues.

A triangular analysis approach based on no arbitrage conditions for three currencies, and causality and influence analysis.

First, it has been found that the movements in the RMB dollar exchange rate do influence the dollar euro exchange rate and the former do have a causality effect on the latter, in both the long run and the short term. Second, it is implied that the RMB is overvalued vis-à-vis the US dollar, as the analysis suggests that an overvalued euro vis-à-vis the US dollar would imply a kind of overvaluation of the RMB vis-à-vis the US dollar, and by any conventional measures the euro has appeared to be overvalued vis-à-vis the US dollar, especially in the months before the last financial crisis.

First, the peg of the RMB to the US dollar that undervalues the RMB vis-à-vis the US dollar will not help promote China's overall trade balance or export even if undervaluation of currencies can ever help improve nations' terms of trade. Second, no stability in RMB exchange rates can be claimed by pegging the RMB to the US dollar, as the exchange rate of the RMB vis-à-vis currencies other than the US dollar would be as volatile as that between the US dollar and the euro and other convertible currencies.

A new triangular analysis approach in international finance research. First, there is an advantage to adopt this seemingly simple analytical framework: it is highly reliable; no triangular arbitrage conditions have to be met even under exchange controls, whilst PPP may not hold even with flexible exchange rate regimes. Second, it does away with the thinking confined to small open economies that has dominated academic research for so long and is totally inapplicable to the RMB case.

After experiencing long, multiyear surges and slides in past decades, by summer 2013, the dollar had been range-bound against the euro. In this case, by assessing potential capital flows, students consider whether global currency market trends would propel the dollar higher, or if the past few years were just a pause in a much longer dollar depreciation episode. Suitable for both core and elective MBA courses in global financial markets and international finance, this case explores factors pointing to further euro appreciation and to others favoring the dollar. Sorting through mounds of evidence is necessary before forecasting the exchange rate's likely path. Filtering that evidence requires thinking about FX markets, prospective monetary policies, and past and prospective international capital flows.

The growth in euro-denominated bond debt issued by emerging market sovereigns picked up considerably after the Asian currency crises. However, while many emerging market governments now have outstanding euro-denominated issues, the market for this debt remains considerably smaller and less liquid than its US dollar counterpart. This has implications for both investors and sovereigns as they try to balance liquidity and cost of capital considerations against portfolio diversification and exchange rate movements. Broadly speaking, spreads on emerging market bonds across countries tend to move in tandem over time. This chapter takes an introductory look at the market for euro-denominated sovereign debt, and investigates the degree to which spreads on euro-denominated emerging market sovereign debt react to common forces. Following a similar analysis of the US dollar market in McGuire and Schrijvers (2003) (hereafter MS2003), we use principal factor analysis to determine the number of common factors that drive movements in spreads, and then seek to assign meaning to these factors through simple correlations with economic variables.

The digital euro is not a monolithic project. On the contrary, the application fields are broad, and possible solutions are diverse. This chapter provides an overview of use cases, application domains, and infrastructures for the digital euro that differ significantly. A comparison with solutions for the digital dollar and the digital yuan leads to the conclusion that, in the most extreme case, the euro could become a regional currency for Europe. The main reason for this argument is the design and prioritization of current approaches within Europe as well as the European Central Bank’s digital euro project, and that stablecoin approaches seem to be neglected as solutions for the digital euro.

On January 1, 1999, the euro became the common currency of the 11 Member States of the European Union (EU) – Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxemburg, The Netherlands, Portugal, and Spain, to be joined by Greece in 2000. The 12 were joined by Slovenia on January 1, 2007, Malta and Cyprus on January 1, 2008, and Slovakia on January 1, 2009. Estonia was scheduled to be the 17th member of the Eurozone on January 1, 2011, and was admitted to the Eurozone membership in September 2010. Following Slovenia and Slovakia, Estonia is the third former Communist state to join the Euro regime. It is, however, the first former Soviet republic to earn this honor. The remaining East European countries, who were admitted to EU membership by the Treaty of Rome in 2004, will become members of the Eurozone after a process of scrutiny. Each must satisfy the terms of the Maastricht Treaty of 1992. Denmark, Sweden, and the United Kingdom, three of the original EU-15 countries, continue to be outside the Eurozone. However, Sweden and Denmark have limited exchange rate fluctuations with the euro. The United Kingdom has a different story. Its economic structure and its relatively small share of world GDP have become an issue. The declining share of the United Kingdom's pound sterling as an international reserve currency warrants much critical evaluation.

The chapter presents an overview of major currency and international capital market movements after World War II, showing that the movements brought about by US investments in the fifties and sixties that created the offshore Eurodollar bear resemblance to what is now taking place between the United States as the world's investor and China. International money is created in a triangular process of long and short lending intermediated by short borrowing. The imbalances often recorded on US current account are to some extent counterbalanced by the huge returns accruing to businesses of the west. This follows the “dark matter” theory but with the twist that real value is extracted through foreign direct investment in line with the rationale of Eurodollar flows. However, threats are also created in this way. Rather than in superficial notions of instability in currency markets, the high returns on capital abroad have been instrumental both in the deindustrialization of the west and the maintenance of a high rate of consumption through the financialization of the housing market. The eventual overdrive precipitated the crisis starting in 2007, but the dollar relationship with China continues unabatedly.

Robert Mundell is the father of the concept of optimum currency area (Mundell, 1961) and he has since then taught us a great deal more about it (Mundell, 1970, 1999, 2003). President Kennedy reminded his fellow countrymen that it is the strength of the US dollar, bolstered by the strength of the US economy, not the US military arsenal, which contributes to the international leadership of the USA. Saburo Okita sought to explain policy approaches in the framework of economic regional communities in the context of global economic cooperation, and thus responded to the question if we will have one world or several (Okita, 1989, 1994). Indeed, he pioneered the concept of multiple currency areas.

The purpose of this study is to examine the accuracy of combined models with the individual models in terms of forecasting Euro against US dollar during COVID-19 era. During COVID, the euro shows sharp fluctuation in upward and downward trend; therefore, this study is keen to find out the best-fitted model which forecasts more accurately during the pandemic.

The descriptive design has been adopted in this research. The three univariate models, i.e. autoregressive integrated moving averages (ARIMA), Naïve, exponential smoothing (ES) model, and one multivariate model, i.e. nonlinear autoregressive distributive lags (NARDL), are selected to forecast the exchange rate of Euro against the US dollar during the COVID. The above models are combined via equal weights and var-cor methods to find out the accuracy of forecasting as Poon and Granger (2003) showed that combined models can forecast better than individual models.

NARDL outperforms all remaining individual models, i.e. ARIMA, Naïve and ES. By applying a combination of different models via different techniques, the combination of NARDL and Naïve models outperforms all combination of models by scoring the least mean absolute percentage error value, i.e. 1.588. The combined forecasting of NARDL and Naïve techniques under var-cor method also outperforms the forecasting accuracy of individual models other than NARDL. It means the euro exchange rate against the US dollar which is dependent upon the macroeconomic fundamentals and recent observations of the time series.

The findings could help the FOREX market, hedgers, traders, businessmen, policymakers, economists, financial managers, etc., to minimize the risk indulged in global trade. It also helps to produce more accurate results in different financial models, i.e. capital asset pricing model and arbitrage pricing theory, because their findings may not be useful if exchange rate fluctuations do not trace effectively.

The NARDL models have been applied previously in different time series and only limited to the asymmetric or symmetric relationships. This study is using it for the forecasting exchange rate which is almost abandoned in earlier literature. Furthermore, this study combined the NARDL with univariate models to produce the accuracy which itself is a novelty. Moreover, the findings help to enhance the effectiveness of different financial theories as well.