This study examines the dynamics of structural breaks in Turkey's foreign exchange market and exchange rate regimes using the index of foreign exchange market pressure (EMP) from January 2006 to October 2024. The low negative correlation between the nominal exchange rate and central bank reserves suggests a managed exchange rate regime during this period. The cointegration model with structural breaks identifies three key breaks: November 2008 (global financial crisis), February 2012 (European debt crisis), and February 2022 (post-pandemic economic transformation). From January 2006 to October 2008, a market-oriented floating exchange rate regime was in place. After November 2008, foreign exchange market interventions increased due to the global crisis, deviating from the floating exchange rate regime. Between February 2012 and January 2022, EMP peaked, and policies resembling a fixed exchange rate regime were pursued. In the most recent period (February 2022 to October 2024), foreign exchange interventions decreased, but exchange rate uncertainties remained. Furthermore, post-October 2024, the Japanese Yen was not used for arbitrage. Policy recommendations include strengthening the floating exchange rate regime, better management of foreign exchange reserves, and using reserves only during crises.

Sovereign default events are usually accompanied by a severe currency crisis and hence, increased sovereign credit risk typically prompts a flight of capital, stimulating greater fluctuations in the foreign exchange (FX) market. Further, if sovereign risk is a priced factor in currency returns, then variability in sovereign risk should generate contemporaneous FX volatility. This study investigates the contemporaneous relationship between sovereign credit risk and FX realized volatility, based on a sample of 30 currencies from January 2008 to December 2022. We examine the impact of sovereign credit risk from two different perspectives, i.e. the change and the volatility of sovereign CDS spreads. We find that FX realized volatility is positively associated with i) the change in sovereign risk and ii) the realized volatility of sovereign risk. We also split sovereign risk into a global component and a local component. Our results show that the developed countries tend to exhibit a greater impact from global sovereign risk, whereas emerging countries are more influenced by local sovereign risk.

This paper uses time series Co-Integration methodology and Granger Causality to check the status of financial market interconnectedness in India after the implementation of External Benchmark linked Lending Rate (EBLR) since October 2019 to July 2024. The markets used in the study are Money Market, Foreign Exchange Market, Government Securities Market and Stock Market. The results indicates that the stock market, despite having long-run relationship with all markets had stable relation only with foreign exchange market. Similarly, many pairs of market showed unstable long-run relationship. Causality test demonstrated causality from money market to foreign exchange market and government securities market demonstrating the independence of robust domestic liquidity operation. There is also causality from foreign exchange market to stock market and government securities market. Rest of pairs did not show any causality, showing the necessity of policy reforms to remove the barriers of free capital flow in the financial market. JEL Classification Code: C01, E44, F36

This study explores the predictive power of the sentiment captured in the minutes of the Monetary Policy Council (MPC) meetings regarding the setting of the reference interest rate in Poland. It assesses its usefulness in forecasting the returns on financial markets. The sentiment is computed with the VADER analysis tool. The release of the MPC meeting minutes impacts stock and Treasury bond markets but appears to have negligible effect on the foreign exchange market. Adding the sentiment as a feature enhances the forecast accuracy of daily stock index returns and bond yield changes generated by the LSTM machine learning models.

The foreign exchange market is the largest and most dynamic financial market globally, with exchange rates predominantly influenced by economic factors. U.S. macroeconomic data play a critical role in driving short-term volatility in exchange rates. This study examines the impact of U.S. macroeconomic data releases on short-term volatility in the USD/PLN exchange rate under conditions of imperfect information. The aim is to identify which macroeconomic indicators most significantly affect fluctuations in this currency pair. This research addresses a significant gap in the existing literature, as no prior studies have specifically investigated the effect of six types of U.S. macroeconomic data on the USD/PLN exchange rate within the M30 interval. The findings are intended to provide valuable insights for Forex market participants trading the USD/PLN pair, helping them make more informed investment decisions. The study employs regression and statistical analysis techniques, utilizing a linear regression model with a GARCH process to model the stochastic component. Parameters were estimated using 30-minute exchange rate data for three currency pairs, with the analysis conducted in Stata 15. The results demonstrate that USD/PLN volatility increases following the release of U.S. macroeconomic data. The most notable reactions were observed after the release of Non-Farm Employment Change and Consumer Price Index data, while New Home Sales and Unemployment Claims also triggered significant responses. The COVID-19 pandemic was linked to elevated volatility in the USD/PLN exchange rate, while the outbreak of the war in Ukraine further intensified fluctuations in this currency pair.

This research review paper explores the complex relationship between the removal of energy subsidies and the depreciation of the Nigerian naira under the current democratic government. Energy subsidies have long been a point of contention in Nigeria, with successive governments grappling with the economic, social, and political implications of their removal. The removal of energy subsidies has been touted as a necessary measure to free up government revenue for development projects, but it has also triggered inflation, social unrest, and a free fall of the naira in the foreign exchange market. This review paper examines the historical context of energy subsidies in Nigeria, their impact on the economy, and the theoretical and conceptual frameworks that explain the interaction between subsidy removal and currency depreciation. It also delves into the current administration’s policies on subsidy removal, the challenges posed by the free fall of the naira, and potential strategies for mitigating these issues. The paper concludes with recommendations for sustainable economic reform, focusing on balancing fiscal responsibility with social equity in a democratic context.

Cost overruns are common on long-term construction projects. This is mostly because of inaccurate early estimates and unexpected changes in the economy and finances. In Egypt, the costs of materials like steel, cement, bricks, sand, and aggregates make up a large part of the cost of building. These costs are greatly affected by the state of the economy and the financial markets. Even though the Construction Cost Index (CCI) is a widely used economic indicator around the world, Egypt has not yet made its own CCI official. This study creates a predictive model just for Egypt’s construction industry that aims to predict a localized CCI to improve financial planning and lower risk. The framework uses two deep learning models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), to make predictions about Egypt’s CCI. The models include a wide range of macroeconomic, monetary, foreign exchange market, commodity/energy market and equity market indicators, as well as technical indicators. In Python, advanced statistical methods like correlation analysis, multicollinearity, and stepwise regression are used to make sure that the best features are chosen. The GRU is better at keeping things in balance because it wins on the calibration (Weighted Absolute Percentage Error (WAPE), Bias (mean error)), the absolute error metrics (Mean Absolute Error, Mean Absolute Percentage Error, Symmetric Mean Absolute Percentage Error, and median error), while LSTM is better at squared-loss/association and turning points (Root Mean Squared Error, Mean Squared Error, Coefficient of determination, Directional Accuracy) because it has a slightly tighter variance fit and sign tracking. There is a permutation feature importance analysis for six features in both the GRU Model and the LSTM Model that shows that oil is the most important thing that affects the construction cost index (CCI). The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. They make a big difference in Egypt’s construction industry and meet the need for localized forecasting models in markets.

A country's foreign exchange (forex) policy, which is the cornerstone of its economic structure, encompasses a variety of strategies for controlling the exchange rate of its currency and negotiating the intricacies of the international forex market. The decision between a fixed and floating exchange rate system fundamentally determines the direction of a nation's foreign exchange policy. In a set design, a primary currency or a basket of currencies is used as the basis for the government or central bank's currency peg, which frequently necessitates active interventions to maintain. Although this tactical choice gives the currency's value a perception of stability, it calls for close observation and sporadic market interventions. Conversely, in a floating exchange rate regime, the currency's value is left up to market forces, which consider the fluctuations in supply and demand within the foreign exchange market. Although a floating regime's intrinsic flexibility allows for natural changes, it also increases the currency's volatility. The value of a nation's currency on the international market is determined mainly by its foreign exchange policies. By comparing the situations of Pakistan and Bangladesh, we can understand how disparate foreign exchange policies might affect the values of the two countries' currencies, particularly the US dollar.

The study aims to analyze the volatility behaviour and its spillover effect on Indian foreign exchange rates Indian Rupee (INR), specifically against the Euro (EUR), British Pound (GBP), Japanese Yen (JPY) and US Dollar (USD). The study is based on the Reserve Bank of India (RBI) data from January 2019 to June 2023. A statistical approach suitable for capturing the dynamics of volatility over time, allowing for both short-term and long-term effects, is used. Additionally, a method designed to examine returns, shocks and volatility spillover effects, due to its flexibility in capturing asymmetry in volatility among foreign exchange rates, is employed. The empirical findings show that USD/INR is the most volatile and JPY/INR is the least volatile. As for the spillover effect, it is found that there is a bidirectional volatility linkage between the USD and EUR, suggesting that both currencies have a significant impact on the volatility of the INR exchange rate. This study’s impact goes beyond academic circles, directly influencing real-world practices of hedgers, arbitrators and other market players.

Subject. The article considers the development strategy of the Russian financial market under new economic conditions. Objectives. The purpose is to elaborate theoretical and practical proposals to improve the financial market strategy for boosting investment and economic growth in crisis. Methods. The study rests on strategizing, which allows to propose a number of initiatives to enhance the strategy of the financial market during the crisis period, based on trends, existing competitive advantages and opportunities of the Russian economy. Results. The paper shows the need to continue the transformation of the financial system, based not only on the liberal economic paradigm and recommendations of international institutions on the free movement of capital, but also on the use of its own strategy, aimed at economic development (including in industrial regions), enabling to address environmental factors. Conclusions. In times of crisis, it is necessary to stir up State institutions for development in financial markets, synchronize monetary and fiscal policies, strengthen the regulation of cross-border capital flows, and use the ESG strategies by public companies in Russia. The establishment of some additional restrictions on capital markets and the foreign exchange market by the financial regulator, the support for the ESG approach by State institutions for development and banks will mitigate systemic risks during crisis periods and attract financial resources to long-term investment projects of the real economy, encourage the growth of capitalization of companies, including in regions.

This study offers an in-depth investigation of the interaction effects of oil price uncertainty, economic policy uncertainty, and exchange rate shocks on industrial production for Norway, Russia, Türkiye, and United Kingdom (UK). The findings reveal uncertainty in economic policy and oil prices had a negative interaction effect that makes the commercial ecosystem much less predictable and increases their detrimental effects on industrial production. In addition, volatile foreign exchange market exacerbates the unfavorable effects of erratic oil prices on industrial production, according to a negative interaction effect between oil price uncertainty and a foreign exchange shock. Co-ordinated monetary policies possibly will curtail unceratinties and its adverse economic fallout. Adapting to global economic shifts while maintaining robust frameworks centred on diversification and risk management offers a far more proactive policy approach to industrial production resilience. This research adds great value to policies that mitigate decline in industrial output from external shocks in European economies.

Abstract Extending recent research, this study introduces a novel testing procedure based on modern block bootstrap techniques and maximum likelihood estimation to investigate whether the universal power-law process governing the cross-section of realized foreign exchange (FX) rate variances exhibits a conjoint cutoff. The analysis posits that the maximum likelihood estimator for the exponent of a power law is intrinsically dependent on the selected cutoff. Our innovative test, calibrated to the cross-section of realized daily FX variances, provides evidence for the existence of such a universal cutoff. The findings have significant implications for FX risk management. Specifically, they indicate that (a) the benefits of FX risk diversification may be more constrained than previously assumed, and (b) the extent of power-law behavior in the realized variance risk of the FX market may be substantially underestimated when conventional single-equation models are employed to determine the optimal cutoff for a power law.

The impact of economic policy uncertainty on financial markets is becoming more and more significant. Through big data technology, time series analysis, and machine learning algorithm, the author of this paper discusses the impact of economic policy uncertainty on financial markets, especially under the background that globalization and informatization aggravate the complexity of the global economic environment. The author found that with the increase of economic policy uncertainty, the stock market yield decreases, the credit spread in the bond market expands, and the exchange rate fluctuation in the foreign exchange market intensifies. Based on data from 2010 to 2023, these hypotheses are verified by regression model analysis, and the significant relationship between economic policy uncertainty and financial markets is revealed. The research results provide not only a basis for policymakers to adjust the direction and intensity of policies but also support for investors to better understand market trends and improve the scientific nature of investment decisions.

Profitability of technical trading rules in the Chinese yuan-based foreign exchange market

This article discovers the political-economic aspects of the conflict between Israel and Iran, which escalated after large-scale Israeli strikes on Iranian missile facilities in June 2025 with the involvement of the U.S. military. In the researchanalyzes the impact of military operations and economic sanctions on Iran’s energy sector, strategic industries (such as pharmaceuticals and the production of essential goods), and the management of the country’s foreign exchange market. Special attention was given to Iran’s domestic measures aimed at maintaining social stability under conditions of war and external economic pressure. The paper explores possible scenarios for the conflict’s extension, including a temporary ceasefire and a long-term reorientation of the regional balance of power in favor of Israel and the United States. The research highlights the risks of regional destabilization and global economic shocks, as well as the necessity for a comprehensive diplomatic settlement.

This research investigates the impacts of the financial market on the economic growth in Vietnam. It uses quantitative research methods with 242 participants, including scale testing, KMO testing and Bartlett’s test, Exploratory factor analysis, Confirmatory factor analysis, hypothesis testing and regression analysis. The data is analyzed using SPSS and ANOVA. The findings show that the financial market (consisting of the stock market, foreign exchange market, derivatives market and credit market) does influence economic growth (in terms of production increase, real income increase, economic restructuring, investment and technological development, and improved social welfare). To be more specific, the stock exchange has the biggest impact on economic growth with ß = 0.226. In the authors’ opinion, it is necessary to strengthen the legal framework through update, adjustment and supplement to balance the growth in the banking and non-banking sectors, promote the development of the insurance market, venture capital and microeconomic institutions, raise the awareness of finance and approaches to diversify financial sources for businesses and individuals, improve transparency in the stock market, and innovate business administration to attract more domestic and foreign investments.

This paper investigates the dynamics of volatility spillovers in the South African foreign exchange market across calm and crisis periods, with particular attention paid to the pre- and post-COVID-19 eras. Employing daily exchange rate returns from 2015 to 2025, we apply a Quantile Vector Autoregression (QVAR) model to uncover asymmetries in spillover transmission across the distribution of returns. We evaluate the implications of these spillovers for portfolio performance under three canonical strategies: risk parity, tangency, and naïve equal-weighting. Our findings indicate that the COVID-19 shock intensified volatility spillovers and exacerbated their asymmetry, especially in the lower tail, with pre-COVID period portraying higher volatility compared to the post-COVID period. While risk-based strategies dominate in tranquil markets, equal-weighted portfolios exhibit superior downside resilience under stress, although they ignore risk exposure. These results underscore the importance of accounting for tail-risk-driven interconnectedness in portfolio construction and risk management. This study contributes to the growing literature on volatility spillovers and offers practical insights for managing currency exposure in emerging markets under nonlinear dependence structures.

Exchange rate volatility significantly impacts developing countries' macroeconomic stability in the global economy. This study investigates the effects of exchange rate fluctuations on key macroeconomic indicators, focusing on Indonesia. Using a qualitative descriptive approach with secondary data from institutional sources and an OLS regression analysis, the research examines the challenges faced by developing nations. Findings reveal that exchange rate volatility substantially influences inflation, economic growth, foreign exchange reserves, and the balance of payments. The Indonesian case study (2013, 2018, and 2022–2023) demonstrates that external factors, particularly global monetary policy changes and geopolitical tensions, primarily drive exchange rate pressures. Short-term policy responses, including adjustments to the BI-7 Day Reverse Repo Rate and foreign exchange market interventions, have proven effective for immediate stability. However, long-term macroeconomic resilience necessitates comprehensive strategies such as economic diversification, institutional strengthening, and sustained policy coordination to mitigate the impacts of exchange rate volatility in developing countries.

Market performance is inherently influenced by macroeconomic indicators, notably the foreign exchange rate and inflation rate. The ‎volatility of currency values often leads to price level fluctuations, which in turn may affect the overall behavior of financial markets. This ‎research aims to investigate the influence of foreign exchange volatility, interest rates, GDP, and foreign ownership on stock performance ‎and the inflation rate, by considering the mediating role of the inflation rate. The research method used is Structural Equation Modeling - ‎Partial Least Squares (SEM-PLS) analysis, using secondary data obtained from various trusted sources. The research results show that the ‎variables FEV (X1), IR (X2), GDP (X3), and FO (X4) have a significant influence on the level of SP (Y). Research reveals that the higher ‎the FEV, IR, GDP, and FO values, the higher the SP level. Apart from that, the IR (M) variable was also found to have a positive and ‎significant influence on SP, indicating that an increase in the IR (M) value is associated with an increase in SP. Another interesting finding ‎is the full mediation effect of FEV, IR, GDP, and FO on SP through IR (M). The private and non-profit sectors generally do not have ‎specific policies in place, which makes them more vulnerable to the financial impact of disasters‎.

This research compares the performance of Convolutional Neural Network (CNN) models without optimization and CNN with Grid Search optimization in predicting the Euro exchange rate against the United States Dollar. Data obtained from Yahoo Finance for the period 2018-2023. The results showed that the CNN model with Grid Search optimization provided better performance with an RMSE value of 0.01, MAE of 0.01, MAPE of 0.61%, and R² of 0.8586 on test data, and prediction accuracy reached 99.39%. Grid Search optimization successfully found the best parameters with batch_size 32, dense_units 50, filters 64, kernel_size 3, and learning_rate 0.001. This research proves that hyperparameter optimization can improve the performance of CNN models in predicting currency exchange rates, which can be a decision support tool for foreign exchange market players.