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The role of money and monetary policy of the central bank in pursuing macroeconomic stability has significantly changed over the period since the end of World War II. Globalization, liberalization, integration, and transition processes generally shaped the crucial milestones of the macroeconomic development and substantial features of economic policy and its framework in Europe. Policy-driven changes together with variety of exogenous shocks significantly affected the key features of macroeconomic environment on the European continent that fashioned the framework and design of monetary policies.

This chapter examines the key basis of the central bank’s monetary policy on its way to pursue and preserve the internal and external stability of the purchasing power of money. Substantial elements of the monetary policy like objectives and strategies are not only generally introduced but also critically discussed according to their accuracy, suitability, and reliability in the changing macroeconomic conditions. Brief overview of the Eurozone common monetary policy milestones and the past Eastern bloc countries’ experience with a variety of exchange rate regimes provides interesting empirical evidence on origins and implications of vital changes in the monetary policy conduction in Europe and the Eurozone.

This study constructs time series model, artificial neural networks (ANNs) and statistical topologies to examine the volatility and forecast foreign exchange rates. The Mauritian forex market has been utilized as a case study, and daily data for nominal spot rate (during a time period of five years spanning from 2014 to 2018) for EUR/MUR, GBP/MUR, CAD/MUR and AUD/MUR have been applied for the predictions.

Autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedasticity (GARCH) models are used as a basis for time series modelling for the analysis, along with the non-linear autoregressive network with exogenous inputs (NARX) neural network backpropagation algorithm utilizing different training functions, namely, Levenberg–Marquardt (LM), Bayesian regularization and scaled conjugate gradient (SCG) algorithms. The study also features a hybrid kernel principal component analysis (KPCA) using the support vector regression (SVR) algorithm as an additional statistical tool to conduct financial market forecasting modelling. Mean squared error (MSE) and root mean square error (RMSE) are employed as indicators for the performance of the models.

The results demonstrated that the GARCH model performed better in terms of volatility clustering and prediction compared to the ARIMA model. On the other hand, the NARX model indicated that LM and Bayesian regularization training algorithms are the most appropriate method of forecasting the different currency exchange rates as the MSE and RMSE seemed to be the lowest error compared to the other training functions. Meanwhile, the results reported that NARX and KPCA–SVR topologies outperformed the linear time series models due to the theory based on the structural risk minimization principle. Finally, the comparison between the NARX model and KPCA–SVR illustrated that the NARX model outperformed the statistical prediction model. Overall, the study deduced that the NARX topology achieves better prediction performance results compared to time series and statistical parameters.

The foreign exchange market is considered to be instable owing to uncertainties in the economic environment of any country and thus, accurate forecasting of foreign exchange rates is crucial for any foreign exchange activity. The study has an important economic implication as it will help researchers, investors, traders, speculators and financial analysts, users of financial news in banking and financial institutions, money changers, non-banking financial companies and stock exchange institutions in Mauritius to take investment decisions in terms of international portfolios. Moreover, currency rates instability might raise transaction costs and diminish the returns in terms of international trade. Exchange rate volatility raises the need to implement a highly organized risk management measures so as to disclose future trend and movement of the foreign currencies which could act as an essential guidance for foreign exchange participants. By this way, they will be more alert before conducting any forex transactions including hedging, asset pricing or any speculation activity, take corrective actions, thus preventing them from making any potential losses in the future and gain more profit.

This is one of the first studies applying artificial intelligence (AI) while making use of time series modelling, the NARX neural network backpropagation algorithm and hybrid KPCA–SVR to predict forex using multiple currencies in the foreign exchange market in Mauritius.

This chapter explains dollarization process in Turkey by an extended portfolio model where dollarization is determined by the relative rates of return of domestic and foreign currencies denominated assets, expected change in the exchange rate, exchange rate risk, and credibility of current economic policies. The econometrics results are in line with the intuitive predictions of the model. We have found that interest rate differential and the expected exchange rates are the dominant variables in determining dollarization. This chapter also provides evidence of inertia in the process of dollarization in Turkey.

We investigate fluctuations in the nominal effective exchange rates (NEERs) of East Asian currencies and the Asian monetary unit (AMU), which is computed as a weighted average of East Asian currencies during the global financial crisis. We find that NEERs were more stable for countries that continued to follow a currency basket system during the global financial crisis.

Furthermore, we investigate the relationships among NEERs, AMU, and AMU deviation indicators, which indicate the extent of the deviation in the exchange rate of each East Asian currency from a benchmark rate given in terms of the AMU. By comparing NEERs with a combination of AMU and AMU deviation indicators, we find that there is a strong relationship between them, both before and after the global financial crisis. These results indicate that a coordinated exchange rate policy aimed at stabilizing the AMU deviation indicators will be effective in stabilizing the NEERs of East Asian currencies. In this respect, the AMU deviation indicators, which indicate intraregional exchange rates among East Asian currencies, play a crucial role.

Because NEER trade weights are widely similar among East Asian currencies, a policy aimed at stabilizing a home currency against its NEER may lead to a coordinated exchange rate policy without a common consensus among East Asian countries. In the future, however, coordinated monetary policies should be considered along with coordinated exchange rate policies.

This paper investigates the dependence structure and market risk of the currency exchange rate portfolio from the Malaysian ringgit perspective.

The marginal return of the five major exchange rates series, i.e. United States dollar (USD), Japanese yen (JPY), Singapore dollar (SGD), Thai baht (THB) and Chinese Yuan Renminbi (CNY) are modelled by the Bayesian generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model with Student's t innovations. In addition, five different copulas, such as Gumbel, Clayton, Frank, Gaussian and Student's t, are applied for modelling the joint distribution for examining the dependence structure of the five currencies. Moreover, the portfolio risk is measured by Value at Risk (VaR) that considers the extreme events through the extreme value theory (EVT).

The finding shows that Gumbel and Student's t are the best-fitted Archimedean and elliptical copulas, for the five currencies. The dependence structure is asymmetric and heavy tailed.

The findings of this paper have important implications for diversification decision and hedging problems for investors who involving in foreign currencies. The authors found that the portfolio is diversified with the consideration of extreme events. Therefore, investors who are holding an individual currency with VaR higher than the portfolio may consider adding other currencies used in this paper for hedging.

This is the first paper estimating VaR of a currency exchange rate portfolio using a combination of Bayesian GARCH model, EVT and copula theory. Moreover, the VaR of the currency exchange rate portfolio can be used as a benchmark of the currency exchange market risk.

The most prominent and persistent problems of our global monetary system are instability and imbalances. We propose an international monetary model to solve these problems while at the same time move the model closer to Maqāṣid Sharīʿah (objectives of Sharīʿah). We name this an organic global monetary model or abbreviated as OGM. OGM is an international monetary model directly built on the national monetary system of each member country so that the two can co-exist.

Model design, theory and literature.

The model can eliminate interest rates at the central bank level, create non-tradable international money, and make a more stable international monetary system.

Original.

Recent research indicates that the random walk hypothesis (RWH) approximately describes the behavior of major dollar exchange rates during the post‐1973 float. The present analysis seeks to examine the profitability of currency futures trading rules that assume that spot exchange rates can be adequately modeled as a driftless random walk.

Two random walk currency futures trading rules are simulated over all available data from the period 1984‐2003. In both cases, the investor buys currencies selling at a discount and sells those selling at a premium, as the RWH implies. The two rules differ only in the way they allocate the hypothetical investor's resources among long and short foreign currency positions.

Results show that an investor who used these trading strategies over the past decade would have enjoyed large cumulative gains, although periods of profit were interrupted by periods of substantial loss.

The findings encourage the hope that profitable random‐walk‐based strategies for currency futures trading can be devised. The simulation results have important implications for those willing to hedge, borrowers, and speculators.

This paper provides evidence that purchasing futures contracts on currencies priced at a discount and selling futures contracts priced at a premium has generally been a profitable trading strategy during the last two decades of floating exchange rates.

Discusses the way countries can operate their exchange rate policies. Covers areas such as fixed exchange rates, floating rates and pegged rates, citing the advantages and disadvantages of each. Considers the example of the Euro‐zone countries and the problems they face. Looks at countries which use official dollar‐linked systems. Outlines the three primary types of risk exposure, transaction, economic and translation and presents some examples of how companies have mitigated risk. Briefly looks at rate forecasting. Concludes that a global market could lead to fewer currencies.

Since the early 1980s, currency options have become a popular means for hedging foreign currency positions or speculating on anticipated movements in exchange rates. Yet, they can also be used to enhance the forecasting of exchange rates. Corporate forecasts of exchange rates involve two tasks: (1) a point estimate of a currency's exchange rate, and (2) a confidence interval that suggests the degree of uncertainty associated with the point estimate forecast. A currency forward or futures price is often used as the point estimate required. The confidence interval is commonly developed by using the historical volatility of exchange rate movements. However, an alternative method is to use the market's anticipated volatility in developing the confidence interval. Scott and Tucker (1990) have shown that the volatility implied from contemporaneous currency option prices is a better forecast of future volatility than historical measures. Therefore, a confidence interval implied by currency options should also be more reliable. Our objective is to illustrate how confidence intervals can be developed from currency option information. Given the degree of difficulty in forecasting exchange rates, more reliable confidence intervals could greatly improve managerial decisions.