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The present research paper is focused the widely debated topic related to de-dollarization. It examines the trend of de-dollarization to check if the statements that the dollar is losing its weight and is about to lose its leading position in international trade payments are substantiated. Firstly, the theoretical framework behind the dollarization is explored. Secondly, the factors believed to be the basis of the de-dollarization process have been identified and analyzed, which are related to: geopolitical processes, changes in international payments policy in some BRICS countries, changes in international trade, etc. A performed analysis of the currency turnover in international trade, based on data from official sources, was made through forecast regression, which predicts the development of the share of the dollar in international payments. A correlation matrix was also calculated, showing the correlation links between the dollar and the other leadng currencies. The hypothesis, which is confirmed by the practical research, is that the de-dollarization process is proceeding slowly and uncertainly, and will continue to develop at a low pace leading to insignificant changes in the structure of the currency composition of international payments in the short and medium term. Further research could further explore each of the factors that could lead to a real dedollarisation trend in international payments.

This article introduces a rational expectations model that explains exchange rate dynamics and the predictability of forecast errors using private (aggregated via order flow) and public (probabilities of a binary event) information. We test the model for the periods leading up to the presidential impeachment vote in Brazil, the Brexit Referendum, and Donald Trump's election in 2016. Proxies of the physical probabilities of these events reveal that they are a crucial source of pricing information for the BRL, GBP, and MXN currency pairs with the US dollar. They also explain forecast errors. The information content of order flow changes before and after an actual regime change resolves uncertainty. [ABSTRACT FROM AUTHOR]

This article proposes a framework to model the mutual volatility transmission between multiple assets and multiple trading places in different time zones. The model is estimated using a dataset containing daily returns of three stock indices – the MSCI Japan, the EuroStoxx 50, and the S&P 500 – each traded at three major trading places: the stock exchanges in Tokyo, London, and New York. Strong volatility transmission effects can be observed between New York and Tokyo, whereas current volatility in New York mostly depends on past volatility in New York. For the assets in consideration, spillovers are strong across trading zones, but weak across assets, suggesting a close connection between market places but only a loose volatility link between international stock indices. Volatility impulse response functions indicate a long-lasting and comparably large response of volatility in Tokyo, whereas they suggest a quicker volatility decay in London and New York.

In this study, we examine stock market shocks using a Global Vector Autoregressive (GVAR) model encompassing 26 countries from January 1999 to June 2022. Our findings reveal that i) shocks originating from advanced economies (AD) exhibit greater persistence in generating fluctuations compared to shocks from emerging market economies (EME); ii) negative stock market shocks are associated with devaluations of domestic currencies, endogenous responses of monetary policy, and global recession. Our estimates suggest that stock market fluctuations have significant potential to destabilize international markets, with contagion spreading rapidly. Our approach contributes to existing literature by constructing a comprehensive model of the world economy, simulating aggregate shocks, and assessing the relevance of global shocks based on the level of economic development.

The development of technology and the globalization of financial markets have increased the volatility in financial markets and caused the emergence of risks and uncertainties that have not been previously encountered. Since traditional econometric models cannot fully explain this volatility, nonlinear conditional variance models such as ARCH, GARCH, EGARCH and TARCH are used today. From this point of view, this study aims to determine the most explanatory model that fund managers who are considering investing in the Borsa Istanbul 100 (BIST 100) Index, and academicians doing research on this subject, can use in estimating the BIST 100 Index return volatility. For this purpose, ARCH and GARCH models, as symmetric models, and EGARCH and TARCH models, as asymmetric nonlinear conditional models, are included in the econometric analysis by using the end-of-day values of 2657 observations belonging to the 04.01.2010-28.07.2020 period. According to the empirical results of the study, the TARCH model, which has the highest level of explanatory power, gives the most successful results among related models in revealing BIST 100 Index return volatility.

The war in Ukraine and new sanctions imposed on Russia have affected commodity prices and induced historic moves in exchange rate markets. In this paper, we examine the impact of commodity price shocks related to the war in Ukraine on three currencies (Canadian dollar, euro, and Japanese yen). Using four-hour price data for three commodities (wheat, crude oil, and natural gas) and two exchange rates (EUR/CAD and CAD/JPY) from February 1 to April 30, 2022, the analysis based on the quantile autoregressive distributed lag (ARDL) model suggests a long-run association between higher commodity prices and appreciation of the Canadian dollar against the euro and the yen. Furthermore, the dynamic simulated ARDL model shows a positive impact of commodity price shocks on the value of the Canadian dollar against the euro and the yen, which demonstrates the robustness of our findings. Oil price shocks have almost the same impact on the depreciation of the euro and the yen. The driving forces in the depreciation of the euro and the yen, in addition to higher oil prices, are higher gas prices and higher wheat prices, respectively.

We focus on computing the geopolitical risk index (GPRI) for Nigeria, the largest economy in Africa. The country has faced crises, including Boko Haram insurgency, banditry, kidnapping, EndSARS, and regional secession, affecting trade relationships with other countries. Existing GPR indices do not include Africa, hence the need for this effort. The proposed index considers eight prominent Nigerian newspapers and relevant keywords on a daily basis from Jan 1, 2012, to June 19, 2023. We evaluate the predictability of the index by examining its relationship with Nigeria's currency and stock markets. Our findings reveal a remarkable positive relationship between the rising geopolitical tensions and the volatility of the currency and stock markets. Curbing geopolitical tensions in Nigeria is crucial for financial market stability.

The dominant approach of international organizations and financial institutions to development finance focuses on incentivizing and mobilizing private capital to achieve the international community's goals in terms of economic, social and environmental development while the public sector's financial capacity is supposedly restricted. Yet, this approach dismisses the nature of money as being endogenous, which implies that domestic banking systems can accommodate the demand for finance. The essential constraint, notably from the perspective of low-income countries, is not finance per se but the lack of foreign exchange. To distinguish true from false finance gaps, it is necessary for a country to know whether its investment plans rely on foreign currency. This analysis develops a guide to public investment based on the balance-of-payments-constrained growth model. It helps policymakers develop investment plans by assessing reliance on foreign exchange and the space available to make public investments via the domestic banking system. To illustrate its practical use, the guide is applied to a simple stylized example of a national investment plan. [ABSTRACT FROM AUTHOR]

This study analyzes systemic risk contagion across the euro area by employing the Diebold-Yilmaz and the frequency connectedness methodologies with data from January 1, 1999, to January 25, 2021. We use the daily Composite Indicator of Systemic Stress (CISS) series for 11 countries in the euro area developed by Holló et al. (2012) and calculate the overall connectedness between the series by employing two pioneering approaches. Additionally, we estimate the short-, medium-, and long-cycle connectedness of systemic risk over the study period that covers three financial burst periods: the global financial crisis (GFC), the European sovereign debt crisis (ESDC), and the COVID-19 pandemic. Overall, spillover indexes notably rise around well-known financial/geopolitical events over the study period. Finally, we examine the network connectedness of systemic risk spillovers during the GFC, the ESDC, and COVID-19 periods and thereby compare them. Our results highlight an efficient regulatory mechanism to control systemic risk contagion.

We study the economic value of market timing in foreign exchange (FX) markets, that is, using information about the conditional Sharpe ratio to adjust the notional value of a conditionally mean–variance efficient currency portfolio. Our strategy trades more (less) aggressively when the conditional risk-return trade-off is more (less) favorable. This leads to a significant improvement in the out-of-sample unconditional Sharpe ratio, skewness, and maximum drawdown per 1% expected excess return. The strategy's market timing predicts returns, volatility, and skewness in FX markets. Popular currency pricing factors do not explain the strategy's high average excess returns. Our findings suggest that it is costly to impose leverage or risk (i.e., conditional volatility) limits or other inferior market timing policies when constructing currency trading strategies. [ABSTRACT FROM AUTHOR]

Aviation stock sensitivity to crude oil prices has raised a suspicion of nexus between aviation stocks and crude oil prices. In this paper, the sustainable nexus between oil Prices and aviation stocks in India are analysed. In particular, it is tested whether there is any sustainable long-term co-movement between the stocks of three aviation companies listed on the Indian stock market and crude oil. The oil prices and aviation stocks are decomposed into different time horizons using the methodology of wavelets. The nexus is studied at shorter, medium, and longer time horizons. Broadly, results show that there is some nexus in the short-run, however, sustainable long-run nexus is missing. The results are found to be robust and approximately similar when data from three Indian aviation stocks are used. It is inferred that sustainable long-run movements in aviation stocks should be attributed to the reasons not related to crude oil price changes.

Aim/purpose – The aim of this paper is to present two cases of crises in Greece and Italy and to evaluate the shadow exchange rates of hypothetical new currencies (re)introduced after Grexit and Italexit.

Aim/purpose – This paper investigates the accuracy of leading indicators in the case of the 2001 sovereign default crisis and the 2018 currency turmoil in Argentina.