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While changes in stock prices are said to affect exchange rates, exchange rate changes are also said to affect stock prices. The purpose of this paper is threefold. First, the authors review all empirical literature by dividing them into two groups of univariate and multivariate studies. Second, a table which summarizes the main features of each study is provided to help future researchers to have easy access to summary of each study. Finally, a new direction for future research is proposed. This new direction relies upon non-linear ARDL approach and shows how to investigate symmetric vs asymmetric effects of exchange rate changes on stock prices.

The paper reviews existing published work and provides suggestions for future research.

The paper reviews existing published work and provides suggestions for future research. An application reveals that exchange rate changes have asymmetric effect on stock prices.

This is the first review paper on the relation between exchange rates and stock prices.

The purpose of this paper is to evaluate selected West African currencies/US dollar exchange rates for the evidence of volatility spillover. Specifically, the paper examines West African CFA franc, Gambian dalasi and Nigerian naira exchange rates in relation to the USD, for any evidence of shock and volatility spillover.

The author employs multivariate GARCH (1,1)–BEKK model which enables the evaluation of the interaction within the volatility of two or more series because of its capability to detect volatility spillover among time series observations, as well as the persistence of volatility within each series.

The major findings of this study are as follows: there is evidence of volatility clustering in West African CFA franc, Gambian dalasi and Nigerian naira exchange rates in relation to the USD. There is evidence of bi-directional shock and volatility spillover between the Nigerian naira and West African CFA franc/USD exchange rates, and uni-directional shock spillover from the Gambian dalasi to the West African CFA franc/USD exchange rates. There is, however, no evidence of exchange rate shock and volatility spillover between Nigerian naira and Gambian dalasi.

Although considerable literature exists on the volatility of exchange rate in West Africa and comparative analysis of exchange rates volatility in few countries of West Africa, there is absence of empirical studies on exchange rate volatility spillover among countries in the region. Since containing exchange rate volatility is one of the major objectives of monetary policy, understanding the nature and direction of exchange rate volatility spillover would propel formulation exchange rate policies that would minimise exchange rate uncertainty and entrench sustainable development. In addition, the nature of exchange rate volatility spillover between West African countries would provide basis for international traders and foreign portfolio investors to develop effective strategies for hedging against exchange rate shocks that are propagated across countries by designing appropriate risk management techniques.

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.

The purpose of this paper is to provide an extensive review of the monetary model of exchange rate determination which is the main theoretical framework on analyzing exchange rate behavior over the last 40 years. Furthermore, we test the flexible price monetarist variant and the sticky price Keynesian variant of the monetary model. We conduct our analysis employing a sample of 14 advanced economies using annual data spanning the period 1880–2012.

The theoretical background of the paper relies on the monetary model to the exchange rate determination. We provide a thorough econometric analysis using a battery of unit root and cointegration testing techniques. We test the price-flexible monetarist version and the sticky-price version of the model using annual data from 1880 to 2012 for a group of industrialized countries.

We provide strong evidence of the existence of a nonlinear relationship between exchange rates and fundamentals. Therefore, we model the time-varying nature of this relationship by allowing for Markov regime switches for the exchange rate regimes. Modeling exchange rates within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. These results show that linearity is rejected in favor of an MS-VECM specification which forms statistically an adequate representation of the data. Two regimes are implied by the model; the one of the estimated regimes describes the monetary model whereas the other matches in most cases the constant coefficient model with wrong signs. Furthermore it is shown that depending on the nominal exchange rate regime in operation, the adjustment to the long run implied by the monetary model of the exchange rate determination came either from the exchange rate or from the monetary fundamentals. Moreover, based on a Regime Classification Measure, we showed that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases. Finally, it is shown that fundamentals are not only significant within each regime but are also significant for the switches between the two regimes.

The results are of interest to practitioners and policy makers since understanding the evolution and determination of exchange rates is of crucial importance. Furthermore, our results are linked to forecasting performance of exchange rate models.

The present analysis extends previous analyses on exchange rate determination and it provides further support in favor of the monetary model as a long-run framework to understand the evolution of exchange rates.

The authors analyze the relationship between exchange rate fluctuations of a number of major currencies and its impact on US stock market returns, as proxied by the S&P 500. Many studies have explored this topic since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This study takes a different look at this hypothesis and investigates the pairwise relationship between various exchange rates and the United States stock market returns (S&P 500 INDEX) from January 2000 to December 2019.

The authors test the data for unit roots using Phillip-Perron method. They use Johansen cointegration model to determine whether returns on S&P 500 are integrated with S&P 500. They use the VAR/VECM analysis to test whether there are any interdependencies between exchange rates and stock market return. Finally, they use various GARCH models, including the EGARCH and TGARCH models, to determine whether there exist volatility spillovers from exchange rate fluctuations in various markets to the volatility in the US stock market.

Using GARCH modeling, the authors find volatility in Australian dollar, Canadian dollar and the euro impact market return, and the volatility of Australian dollars and euro spills over to the volatility of S&P 500. They also find that the spillover is asymmetric for Australian dollars.

One of the limitations could be that the authors use different bivariate GARCH models rather than the MV-GARCH models. For future project(s), they plan to do this analysis from the perspective of a European Union or a British investor and use returns in those markets to see the impact of exchange rates on those markets. It would be interesting to know how the relationship will change during periods of financial crises. This could be achieved by employing structural break methodology.

Many studies have explored the relation between stock market returns and exchange rates since the early 1970s with varied results and with no evidence that clearly explains the relationship between exchange rates and stock market returns. This paper contributes by adding to the existing literature on impact of exchange rate on stock returns and by providing a detailed and different empirical analysis to support the results.

This paper examines and dissects eight popular conjectures about exchange rates. The conjectures are: there exists a systematic linkage between economic fundamentals and exchange rates; flexible exchange rates are unstable due to destabilising speculation; flexible exchange rates are excessively volatile; the foreign exchange market is efficient; purchasing power parity holds; volatile exchange rates are harmful to trade; depreciating exchange rates trigger a “vicious” inflationary circle; and countries with current account deficits have depreciating exchange rates. The main message is that there is weak theoretical and empirical support for the majority of the conjectures. Only one proposition, relative PPP has strong empirical support but its policy relevance is weakened by the difficulty of interpreting departures from PPP. The remaining group for which there is inconclusive support presents the greatest challenge to research and policy as it includes the first conjecture.

This study aims to examine the impact of macroeconomic fundamentals on exchange rates of selected South Asian economies during 1981-2013.

The authors have used two econometric approaches to the data. For the pooled sample, estimated generalized least square (EGLS) and the two-stage least square method are applied. For the panel data, the authors have used the panel generalized method of moments and ordinary least squares (OLS) methods.

The results suggest that macroeconomic factors have a significant impact on exchange rates. The robust findings highlight that improvements in domestic economic and political systems are crucial for a successful exchange rate policy.

The existing literature on exchange rate fundamentals have either focused on exchange rates and international trade or investigated the relationship for the developed economies. Covering a period of more than three decades, and using both pooled and panel estimations, our study is unique in terms of its focus on the South Asian economies.

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.

The assignment of targets to instruments in developing countries cannot satisfactorily follow any simple universal rule. Which approach is appropriate is influenced by whether the economy is dominated by primary exports, by the importance of the domestic bond market and bank credit, by the extent of existing restriction in foreign exchange and financial markets, by the presence or absence of persistent high inflation, and by the existence or non‐existence of an active international market in the country's currency. Eighteen observations and maxims on stabilisation policy are tentatively drawn (pp. 64–8) from the material reviewed, and the maxims are partly summarised (pp. 69–71) in a schematic assignment, with variations, of targets to instruments.