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Given the difficulties in finding significant exchange rate exposure in the extant literature, this paper attempts to resolve the so-called “exposure puzzle” by investigating whether currency movements have any significant impact on international industry returns.

This paper utilizes the multivariate Generalized AutoRegressive Conditional Heteroskedasticity (MGARCH) methodology to estimate both symmetric and asymmetric exchange rate exposures for each industry common across 12 countries simultaneously.

The empirical results show that exchange rate exposure is not only statistically significant but also economically important based on the estimation of an asymmetric three-factor exposure model using MGARCH methodology. This is an extremely important finding as it suggests that the “exposure puzzle” may not be a puzzle at all once a better methodology is utilized in the estimation.

Because this study tries to resolve the exchange rate exposure puzzle by focusing on whether exchange rate movements affect ex-post returns as opposed to ex ante expected returns and given the significant exposures with respect to different risk factors found in the study, it is interesting to see if any of these risk factors commands a risk premium. In other words, a natural extension of this study is to test whether any of these risk factors is priced in international industry returns.

The findings of the study have interesting implications for international investors who would like to diversify their portfolios across different industries and are concerned about whether the unexpected movements in the bilateral exchange rates will affect their portfolio returns in addition to its interest rate and world market risk exposures.

The study utilizes the MGARCH methodology, which has not been fully exploited in the exchange rate exposure literature.

The aim of this paper is threefold: (1) to develop a new measure of investor sentiment rational (ISR) of developing countries by applying principal component analysis (PCA), (2) to investigate co-movements between the ten developing stock markets, the sentiment investor's, exchange rates and geopolitical risk (GPR) during Russian invasion of Ukraine in 2022, (3) to explore the key factors that might affect exchange market and capital market before and mainly during Russia–Ukraine war period.

The wavelet approach and the multivariate wavelet coherence (MWC) are applied to detect the co-movements on daily data from August 2019 to December 2022. Value-at-risk (VaR) and conditional value-at-risk (CVaR) are used to assess the systemic risks of exchange rate market and stock market return in the developing market.

Results of this study reveal (1) strong interdependence between GPR, investor sentiment rational (ISR), stock market index and exchange rate in short- and long-terms in most countries, as inferred from (WTC) analysis. (2) There is evidence of strong short-term co-movements between ISR and exchange rates, with ISR leading. (3) Multivariate coherency shows strong contributions of ISR and GPR index to stock market index and exchange rate returns. The findings signal the attractiveness of the Vietnamese dong, Malaysian ringgits and Tunisian dinar as a hedge for currency portfolios against GPR. The authors detect a positive connectedness in the short term between all pairs of the variables analyzed in most countries. (4) Both foreign exchange and equity markets are exposed to higher levels of systemic risk in the period of the Russian invasion of Ukraine.

This study provides information that supports investors, regulators and executive managers in developing countries. The impact of sentiment investor with GPR intensified the co-movements of stocks market and exchange market during 2021–2022, which overlaps with period of the Russian invasion of Ukraine.

This paper examines the reaction of the Egyptian stock market to two substantial devaluations of the Egyptian pound (EGP) in 2022 and tests the informational efficiency of the Egyptian market.

The paper uses the event study framework to analyze the significance and direction of abnormal returns of the leading index of the Egyptian stock market (EGX30) on and around the devaluation days. It employs both the constant mean model and the market model to estimate the normal returns of the EGX30. Additionally, the paper uses data on two equity indices, one global and one for emerging markets, as benchmarks for normal returns.

The paper finds that the Egyptian stock market experienced significant positive abnormal returns on the devaluation days of the EGP in March and October of 2022, indicating a positive market reaction to the devaluation. Furthermore, evidence suggests that the Egyptian market may not be informationally efficient as significant positive abnormal returns were observed two weeks before and two weeks after the devaluation day, suggesting news leaks and delayed reactions, respectively.

This study is the first to examine the impact of the recent two devaluations of the EGP in 2022 on the Egyptian stock market. It complements existing literature by analyzing the immediate market reaction to two consecutive devaluations in an African country. Furthermore, the paper evaluates the efficiency of the Egyptian market in processing information related to exchange rates.

This study aims to analyze the volatility spillover effects of crude oil, gold price, interest rate (yield) and the exchange rate (USD (United States Dollar)/INR (Indian National Rupee)) on inflation volatility in India.

This study uses the multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models (Baba, Engle, Kraft and Kroner [BEKK]-GARCH and dynamic conditional correlation [DCC]-GARCH) to examine the volatility spillover effect of macroeconomic indicators and strategic commodities on inflation in India. The monthly data are collected from January 2000 till December 2020 for the crude oil price, gold price, interest rate (5-year Indian bond yield), exchange rate (USD/INR) and inflation (wholesale price index [WPI] and consumer price index [CPI]).

In BEKK-GARCH, the results reveal that crude oil price volatility has a long time spillover effect on inflation (WPI). Furthermore, no significant short-term volatility effect exists from crude oil market to inflation (WPI). However, the short-term volatility effect exists from crude oil to inflation while considering CPI as inflation. Gold price volatility has a bidirectional and negative spillover effect on inflation in the case of WPI. However, there is no price volatility spillover effect from gold to inflation in the case of CPI. The price volatility in the exchange rate also has a negative spillover effect on inflation (but only on CPI). Furthermore, volatility of interest rates has no spillover effect on inflation in WPI or CPI. In DCC-GARCH, a short-term volatility impact from all four macroeconomic indicators to inflation is found. Only crude oil and exchange rate have long-term volatility effect on inflation (CPI).

In an economy, inflation management is an essential task. The findings of the current study can be beneficial in this endeavor. The knowledge of the volatility spillover effect of all the four markets undertaken in the study can be significantly helpful in inflation management, especially for inflation-targeting policy.

It is observed that no other study has addressed this issue. We do not find any other research which studies the volatility spillover effect of gold, crude oil, interest rate and exchange rate on the inflation volatility. The current study is novel with a significant contribution to the vast knowledge in this context.

This study aims to investigate the determinants of Islamic stock returns listed on Jakarta Islamic Index (Indonesia) between 2008 and 2018.

This study uses a quantile bounded autoregressive distributed lag (QBARDL) model to uncover relevant relationships.

This study finds that the Dow Jones Islamic Market Index, gold returns, world oil prices and exchange rates are the determinants of the Indonesia’s Islamic stock returns. However, the relationship is time varying developing intra-/inter-quantile bounded.

Integration of the Islamic stock returns with the real economic indicators changes over time. The findings have important implications for the policymakers, the fund managers and the investors to anticipate consequences when considering the macroeconomic conditions before participating in the Indonesian Islamic stock market.

Using a QBARDL, this study finds that the Islamic stock returns have on net and “time-varying intra-/inter-quantile developing” relationship with its determinants as data quantiles progressed from 25% to 75%.

Introduction: The Stock Exchange is an economic indicator of sustainability in the global market over an extended period. The Indian economy has observed a downfall in foreign currency in quarter 2 of 2022, as per the reports of the International Monitory Fund. The central banks of many countries have been facing crises because of a piercing decline in their reserves, which is additionally affecting their sustainable performance. The Indian economy is one of the most potentially sound economies emerging as a global leader, and this study is an attempt to understand the economy’s vulnerability to foreign factors.

Purpose: The research explores the impact of the US Dollar, EURO and Japanese Yen on Bombay Stock Exchange and the National Stock Exchange Index.

Methodology: Four variables have been considered for the conduct of the study: Sensex, Nifty, inflation and foreign exchange. Sensex and Nifty have been taken as dependent variables, while foreign exchange and inflation have been taken as independent variables.

The regression analysis has been performed using Microsoft Excel: The variables used for the study are monthly values from January 2011 to December 2020. The specific period is selected to avoid the impact of COVID-19 on the stock market, avoiding biases in the results.

Findings: All the variables are affecting the performance of each other up to a certain level.

Practical Implication: The research chapter will help the investor understand the relationship between many variables and their impact on the stock market, which will assist them in gaining higher profits.

This 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).

This study applies the GARCH-DECO model and cross-quantilogram framework.

The 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.

For 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.

To 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.

Exchange rate volatility is an important factor affecting investors and policymakers. This study aims to examine the impact of uncertainties, in terms of changes in economic policy, monetary policy and global financial markets, on exchange rate volatility.

The study uses the GARCH (1,1) univariate model to calculate exchange rate volatility. Economic and monetary policy uncertainties are measured using news-based indices, while global financial market volatility is measured using the implied volatility index. Panel autoregressive distributed lag modeling is used to analyze the impact of uncertainty on exchange rate volatility in the short and long run. The sample consists of 26 developed and emerging markets from 2005 to 2020.

The study finds that economic policy uncertainty significantly increases exchange rate volatility. Similarly, global financial market uncertainty leads to increased exchange rate volatility. The effect of US monetary policy uncertainty reduces exchange rate volatility.

This research contributes to the existing literature on exchange rate fluctuations by examining the impact of uncertainties on exchange rate volatility. The study uses novel news-based indices for measuring economic and monetary policy uncertainties and includes a broader sample of emerging and advanced markets. The findings have important implications for investors and policymakers.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.