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This paper investigates whether currency risk is priced differently in the different sectors (industrial, financial, and basic materials) of equity markets in a sample of developed United States of America (USA) and developing economies (Brazil, India, Poland, and South Africa). The paper makes use of the following techniques: (i) Univariate Autoregressive Fractionally Integrated Moving Average and Exponential General Autoregressive Conditional Heteroskedastic (ARFIMA-EGARCH), (ii) the Markov Switching method (MS), and (iii) the Canonical Vine Copulas (C-Vine) techniques. Using a sample of daily data made of the foreign exchange rate against the domestic currency and equity market sectors; our findings show that there is an asymmetry effect between equity markets and the foreign exchange rate: there is a heterogeneous, strong, and positive dependence between the two. Higher equity prices are associated with depreciation of local currencies, according to US dollar (USD) exchange rates. In addition, we find that the selected emerging economies are pricing a positive and considerable currency risk. The pricing of currency risk has a varied effect in both regimes representing the states of the economy. In fact, when currency risk pricing has a beneficial impact on certain sectors of the economy, investors predict better returns.

This paper used the Markov-switching (MS)-based wavelet analysis technique to study the dependence structure and the time–frequency impact of exchange rates on crude oil prices (West Texas Intermediate (WTI)) and stock returns. Daily data from 1 January 2005 to 1 March 2020 were collected for exchange rates, crude oil prices, and the BRICS stock market returns. The findings indicate that crude oil prices display higher volatility compared to stock returns and exchange rates. Furthermore, the wavelet analysis reveals consistent changes in the co-movement patterns of both volatility regimes, albeit with some variations in the time periods and frequency domains. The time–frequency dependence between Brazilian, Indian, and Chinese stock markets and crude oil is significantly influenced by exchange rates, which play a pivotal role in their co-movement in the medium term. The findings reveal that these three countries share economic interests, have strong economic ties and interdependencies, and may be motivated to cooperate during crisis periods. However, when it comes to Russia and South Africa (SA), exchange rates do not exhibit a long-term impact on the co-movement in time–frequency. Therefore, we recommend investors to look for investment opportunities that are less correlated with the co-moving markets.

This paper investigates whether currency risk is priced differently in the different sectors (industrial, financial, and basic materials) of equity markets in a sample of developed United States of America (USA) and developing economies (Brazil, India, Poland, and South Africa). The paper makes use of the following techniques: (i) Univariate Autoregressive Fractionally Integrated Moving Average and Exponential General Autoregressive Conditional Heteroskedastic (ARFIMA-EGARCH), (ii) the Markov-Switching method (MS), and (iii) the Canonical Vine Copulas (C-Vine) techniques. Using a sample of daily data made of the foreign exchange rate against the domestic currency and equity market sectors; our findings show that there is an asymmetry effect between equities markets and the foreign exchange rate: there is a heterogeneous, strong, and positive dependence between the two. Higher equities prices are associated with depreciation of local currencies, according to US dollar (USD) exchange rates. In addition, we find that the selected emerging economies are pricing a positive and considerable currency risk. The pricing of currency risk has a varied effect in both regimes representing the states of the economy. In fact, when currency risk pricing has a beneficial impact on certain sectors of the economy, investors predict better returns.

This paper makes use of the Markov Switching model and the K-Means Cluster analysis to estimate the transition probabilities of social mobility and to analyze the impact of social inequalities on intergenerational social mobility. The dataset is a sample of 44 countries and comprises the 2018 social mobility indices, and the 2018 or latest income inequality measures. The data are collected from the OECD Income and Wealth Distribution Databases, and from the world economic forum. It was found that the likelihood of moving upward or downward the social ladder is minimal in both developed and emerging countries. In addition, the paper found that the hypothesis according to which high-income countries have a higher relative social mobility is not necessarily true. The United States, a high-income country, was found to have a lower social mobility, similar to that of Turkey and South Africa. Furthermore, it was found that when poverty decreases, intergenerational social mobility increases in both lower and higher mobility countries. Policies that promote equality of opportunities at all stages of life are therefore recommended to improve intergenerational social mobility.