Risk management has become increasingly important in the financial world. Considering its importance, it is necessary to measure these risks. The financial market uses two risk measures: Value at Risk (VaR) and Expected Shortfall (ES). After the subprime crisis, the market began to emphasize ES instead of VaR. The hypothesis of this paper to be tested is that longer periods provide better information than shorter, more recent periods for measuring ES volatility to hedge trades. The ES can be adopted using parametric, semi-parametric, and non-parametric methods, and the analyses of the log return indicators started on 3 January 2000 and ended on 5 May 2023. The analyses carried out to evaluate these log return indicators covered the period from 6 May 2023 to 1 August 2025, where it was found that the exchange rate volatility of the Brazilian Real exceeded the VaR limits and even reached the Expected Shortfall risk zone. Then, a different analysis was performed, starting on 11 March 2020 and ending on 5 May 2023. This second analysis, as the first analysis, was carried out to evaluate these log return indicators that covered the period from 6 May 2023 to 1 August 2025. In this latest period analysis, the exchange rate volatility of the Brazilian Real reached the Exchange Shortfall risk zone in a different way compared to the first way. All three types of methods—parametric, non-parametric, and semi-parametric—show distinct behaviors depending on the period evaluated. The hypothesis was rejected, but the hedging strategies should account for asset volatility. The software used to calculate the estimators was Microsoft Excel 365 and Stata 14.2.

Background: Indonesia’s energy landscape currently pivots between two bifaceted issues: the stagnation of the national energy transition and the inefficiencies of decentralized waste management. Despite East Java producing 9.27 million tons of dry-milled rice (GKG) in 2024, the resulting 1.85 Mt of rice husk remains an underutilized bio-resource. This wasted potential coincides with a sluggish renewable energy trajectory, where the 15.25% share by mid-2025 significantly trails the 23% national target. Methods: A data-driven framework integrating feedstock characterization, experimental data, and literature benchmarks was applied to evaluate catalytic fast pyrolysis and upgrading pathways for rice husk. Machine-learning-assisted correlation analysis and multi-objective optimization (NSGA-II) were used to benchmark key process variables, product yields, and fuel quality trade-offs. Findings: The technical foundation, built on detailed feedstock characterization, reveals that the CFP process yields ~46.9 wt% bio-oil, which is further refined to a 32.2 wt% biodiesel-equivalent yield. To enhance operational precision, various ML algorithms were evaluated; the Extra Trees model coupled with Non-dominated Sorting Genetic Algorithm II (NSGA-II) demonstrated superior predictive performance with an R2 of up to 0.96 and an RMSE <1 MJ/kg for calorific value prediction, showing strong accuracy for O/C ratio and CO2 fraction estimation. Techno-economic assessment confirms the framework's viability for pilot-scale implementation, projecting a positive NPV of IDR 50.4 million, an IRR of 23.78%, and a 2.93-year payback period. While sensitivity analysis highlights exchange rate volatility as a key financial risk, the model successfully positions farmers as active stakeholders in the value chain. Conclusion: The integrated CFP–ML framework demonstrates technical and economic viability for decentralized rice husk valorization, positioning farmers as active stakeholders in the renewable energy value chain and offering a scalable, bottom-up solution to support Indonesia’s energy transition in agricultural regions. Novelty/Originality of this article: By synthesizing mechanistic process design with data-driven decision support, this study provides a scalable, bottom-up pathway for decentralized waste-to-energy systems in agricultural regions.

Exchange rate volatility continues to shape global economies in profound ways, affecting everything from international trade and investment decisions to overall financial stability as markets become more interconnected. While researchers have produced a wealth of studies—building on classics like Purchasing Power Parity and relying heavily on tools such as Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Vector Autoregression (VAR) models—few have stepped back to map the entire field systematically. This study applied a bibliometric review to examine the exchange rate volatility knowledge base. The data was collected from the Scopus Database, including a sample set of 336 articles based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)'s systematic review techniques. The findings show that there has been increasing interest in this research area, evidenced by the increase in articles published. Based on this analysis, the United States, the United Kingdom, and Germany are the most prolific in providing information to the research on exchange rate fluctuations by way of articles published in the three peer-reviewed journals most commonly referenced: the Journal of Econometrics, the Journal of International Money and Finance, and the Journal of forecasting. Several gaps were uncovered, such as research published on emerging countries, the limited number of collaboration networks that exist between some authors (and countries), and new areas of research that are gaining importance in the evolving financial markets, including digital currencies and innovations in fintech. By delivering a clear, visually engaging overview, this review solidifies the knowledge base on exchange rate volatility and inspire more inclusive, innovative, and practically relevant future work. In view of this, researchers should expand studies on exchange rate volatility to underexplored regions, especially Africa and Latin America, to better understand institutional and economic influences. Incorporating advanced methods like machine learning and big data analytics can enhance prediction models and practical applications of exchange rate volatility theory in global contexts.

Modern market conditions are characterized by a high degree of uncertainty and instability, which creates significant challenges for companies planning to introduce new products to the market. Financial instability, manifested in the volatility of exchange rates, inflationary processes, a decrease in the purchasing power of the population, and a transformation of consumer preferences, requires companies to take a special approach to developing marketing strategies. In such conditions, the successful launch of a new product into the market becomes not only a matter of competent positioning and promotion, but also a strategic task that requires a comprehensive analysis of the market situation, flexibility in decision-making, and effective risk management.

This paper explores the connection between the growth rate of India's pharmaceutical exports over a year and various economic markers foreign direct investment (FDI) in pharmaceuticals, patent applications, and the exchange rate. With the use of annual data from 1995 to 2023, the investigation uses Ordinary Least Squares (OLS) estimation following stationarity confirmation via unit root tests. The results indicate that there is a statistically significant adverse effect of exchange rate volatility on export performance, whereas the FDI inflows and patent filings effects are statistically not significant. The results indicate that although macroeconomic stability in currency value is crucial to export growth, other variables such as FDI and innovation indicators are probably too short-term or will need complementary enabling policies to show their export contributions. The research makes a contribution to the literature by presenting empirical evidence on short-run dynamics among innovation, investment, and trade in India's pharmaceutical industry and presenting policy implications for improving global competitiveness.

Exchange rate volatility and Vietnam’s green product exports: does financial liberalisation in partner countries matter

Financial Sanction, Exchange Rate Volatility and Macroeconomic Variables (Case of Iran)

Inflation in Türkiye has been high since 2021. This paper investigates the sources of this inflation and the impact of mitigating exchange rate volatility. Two main findings emerge. First, there has been a significant divergence in inflation dynamics across CPI components since late 2021—in particular, services inflation has exhibited more inertia than goods inflation, a result that stands out in both historical and cross-country contexts. The persistence in services inflation has been generally broad-based, with rental services playing an important role. Second, exchange rate shocks are estimated to have a smaller impact on services inflation than on goods inflation. The peak services inflation response to a nominal exchange rate shock is estimated to be fairly muted, at just one-tenth the size of the shock. Indeed, since mid-2023, there has been an unusually sharp rise in the relative price of services, as goods inflation has been more sensitive to exchange rate movements. These findings suggest that when inflation persistence—especially in services—is relatively high, inflation stabilization may require complementary policies to break inertia beyond a stable currency.

External debt sustainability in Egypt under exchange rate volatility risks

This study examines the persistent global problem of time and cost overruns in hydropower projects, with emphasis on India. Although hydropower is central to renewable energy strategies and grid stability, project implementation is often hindered by major delays and budget escalations. Since 2000, international data indicate average cost overruns above 30% and schedule delays over 18% (Ansar et al., 2014). The research identifies the root causes of these overruns, evaluates their prevalence in India, reviews case studies, compares national and global trends, and analyses factors such as regulatory complexity, geological challenges, technological integration, and managerial practices. It also highlights best practices to improve project outcomes. Both technical and non-technical factors drive overruns. Technical contributors include complex engineering demands, construction inefficiencies, procurement delays, contractor underperformance, and frequent rework (Debnath, 2025). Nontechnical drivers include environmental and social issues, lengthy approval processes, community opposition, political instability, natural disasters, funding constraints, and global disruptions (Debnath, 2025). Cost escalations stem from direct factors—rising material prices, design changes, unforeseen site conditions, and inaccurate estimates—and indirect ones such as inflation, interest burdens, exchange rate volatility, increased overheads, and contractual disputes (Flyvbjerg, 2006). Case studies from India and abroad show varied causes, including difficult geology, social resistance, land acquisition challenges, financial gaps, and weaknesses in planning and design (World Bank, 2020). These overruns affect not only project viability but also economic development, environmental sustainability, and societal welfare. Addressing them requires comprehensive mitigation across all project stages: rigorous planning, strong risk management, effective contract administration, strict construction oversight, and early stakeholder engagement. Adoption of technologies like BIM and digital project management tools can further enhance efficiency (International Hydropower Association, 2021). Sustainable and resilient hydropower development depends on improved governance, technology uptake, and supportive policy frameworks (Central Electricity Authority, 2022).

This study investigates the relationship between foreign trade and economic growth in Nigeria. The objectives of the study are to; determine the effects of import growth rate, export growth rate, trade openness and exchange rate on Nigeria's economic growth. Using an ex-post facto research design and log-linear regression on secondary time-series data from 1985 to 2023, the study found that, import growth and export growth positively influence economic growth, with imports showing a stronger elasticity, indicating Nigeria's growth is largely import-driven. Trade openness was found to have a negative and significant impact on GDP, suggesting that high import dependency and limited export diversification expose the economy to external shocks. A positive relationship was observed between exchange rate and GDP, largely reflecting increased Naira earnings from dollar-denominated oil exports. The findings reveal that, despite the potential benefits of foreign trade, structural weaknesses, such as overdependence on crude oil, exchange rate volatility, and inefficient trade policies, undermine Nigeria's developmental gains. The study recommended amongst others, prioritizing export diversification beyond oil and strategically managing trade openness to promote economic growth.

The study examined exchange rate volatility and inflation rate in Nigeria. This research work is purely based on desk research where the researchers reviewed and discussed what other scholars have done on the subject matter in identifying and analyzing information. The study found that, foreign exchange volatility significantly influences inflation in Nigeria, primarily through imported inflation and altered consumer behaviour. Also, persistent fluctuations in the Naira’s value pose challenges to price stability and economic growth. Higher import costs driven by currency depreciation led to increased prices for consumers, eroding purchasing power and creating economic uncertainty. Thus, to mitigate the adverse effects of foreign exchange volatility on inflation, Nigeria must implement comprehensive strategies, including enhancing domestic production capacity, promoting currency stability, and diversifying the economy away from oil dependence. Furthermore, stabilizing the exchange rate, diversifying the economy, and strengthening institutional frameworks will help Nigeria manage forex volatility and maintain sustainable inflation levels, fostering economic resilience.

This study empirically analyzes the effects of macroprudential and monetary policies on key macroeconomic variables, as well as the interactions between the two policies. To this end, a Panel Vector Autoregression model with exogenous variables (PVARX) was employed using data from OECD countries and the Eurozone-19. The PVARX model includes the macroprudential policy index, industrial production index, consumer price index, producer price index, call rate, and household credit as endogenous variables, while the U.S. federal funds rate and the New York Stock Exchange volatility index (VIX) are treated as exogenous variables. For the Eurozone-19, since a common macroprudential policy index is not available, a new aggregate index was constructed by applying GDP-weighted averages of member countries’ macroprudential policy indices. The estimation results indicate that both contractionary macroprudential and monetary policy shocks exert negative effects on major macroeconomic variables such as output and household credit. Macroprudential policy tends to tighten in response to positive shocks to output and prices. This suggests that during economic expansions, when credit growth risks intensify, regulatory tools such as the countercyclical capital buffer (CCyB) are reinforced, and when inflation rises, liquidity-absorbing measures such as the reserve requirement (RR) are strengthened. Monetary policy responds to inflationary shocks by raising policy rates, implying that it has been primarily oriented toward price stability. Moreover, interest rates rise in response to macroprudential policy shocks, indicating that monetary policy generally acts in coordination with macroprudential policy among the countries analyzed.

Abstract Even though several theoretical studies suggest that the relationship between uncertainty and investment may be nonlinear, potentially following an inverted U-shaped curve, empirical research typically employs investment models that assume a linear link between investment and uncertainty. Unlike the existing empirical literature, this study examines the effect of exchange rate uncertainty on private aggregate investment employing nonlinear modelling procedures. Specifically, we aim to investigate the threshold effects in the investment-uncertainty relationship by applying a Panel Smooth Transition Regression approach. To this end, we use a large panel dataset of 54 countries, encompassing both industrialized and developing economies, over the period 1980–2022. Our findings strongly support the theoretical argument that the link between exchange rate volatility and investment is nonlinear. We find that exchange rate volatility negatively affects private aggregate investment when the level of volatility is high. However, exchange rate volatility does not have a significant effect on investment at low degrees of exchange rate uncertainty.

inflation rate and exchange rate volatility alongside the increase in interest towards investments within the cryptocurrencies market. This study examines how Bitcoin prices, gold prices, Turkey’s Consumer Price Index, and USD/TL exchange rate affected the returns and volatility of the BIST 100 stock market between February 2021 and March 2025. Methodology- This article applies various econometric models, which include E-GARCH, Markov regime-switching, Bayesian impulse response analysis. Findings– E-GARCH analysis reveals that the effect of Bitcoin and gold prices on the volatility of BIST 100 is insignificant, while the effect of Turkish CPI and USD/TL exchange rate is significant and positive. The analysis of the Markov regime-switching model reveals that for the first regime (high volatility), BIST 100 returns are only influenced by USD/TL. In the second regime (low volatility), the significant negative impact is caused by Bitcoin, while the positive impacts are caused by gold, USD/TL exchange rate, and inflation on BIST 100 returns. The Bayesian impulse response analysis reveals that the initial positive impacts are caused by Bitcoin, USD/TL exchange rate, and CPI, while the impact of gold is negative. At the start of Bayesian impulse response analysis, the largest positive impact is caused by Bitcoin, which decreases as the influence of the USD/TL exchange rate increases. At the end of analysis, the impact of Turkish CPI is found to be the largest on BIST 100 returns. Conclusion- On the whole, the results indicate that although Bitcoin and gold have differential effects on BIST 100 returns depending on market conditions, the primary determinants of BIST 100 returns are the inflation rate and USD/TL exchange rate

The renewable energy (RE) sector in Malaysia has developed rapidly with the implementation of government policies, such as theNational Energy Transition Roadmap (NETR) and the Malaysia Renewable Energy Roadmap (MyRER). This study is based entirely ondata sources from the literature review and policy. Approximately 45 sources were identified, reviewed, and assessed systematicallybetween 2010 and 2025. The overall challenges in the renewable energy sector are addressed in this article through the financial, policy,and infrastructural barriers that confine large-scale uptake. A critical examination of recent studies and official reports is conducted toidentify long-standing impediments and assess the effectiveness of national policies in realising Malaysia’s renewable energy objectives.The identified impediments include high initial investment demands, an uncertain policy regime, limited institutional support, andfinancing challenges, which are among the major constraints to sector development. The study further emphasises the role of governmentintervention, private investment, and public–private partnership in the successful execution of RE projects. With Malaysia aiming for 70%renewable capacity by 2050, the industry still faces macroeconomic headwinds, including volatile exchange rates, rising interest rates,and inflationary pressures. The research contributes to the field of knowledge by offering insights into the renewable energy challengesof Malaysia and providing concrete recommendations for enhancing policy environments, improving access to funding, and promotinginter-stakeholder coordination.

Cocoa is a strategic commodity that contributes significantly to Indonesia’s agricultural export performance. However, its export performance has fluctuated due to global price dynamics, exchange rate volatility, and variations in export volume. This study analyzes Indonesia’s cocoa export performance from 2015 to 2024 using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The secondary data include export volume, export value, average export price, and the rupiah exchange rate against the U.S. dollar. The SEM-PLS results indicate that export volume has a strong and significant positive effect on export value (β = 0.64, p = 0.000), demonstrating that increases in export quantity play a major role in enhancing Indonesia’s cocoa export performance. Export price shows a positive but marginal effect (β = 0.28, p = 0.056), suggesting that price movements contribute to export value but are not statistically significant at the 5% level. Meanwhile, the exchange rate has a significant negative effect on export value (β = −0.47, p = 0.001), indicating that rupiah depreciation tends to suppress cocoa export performance. The model explains 74.2% of the variance in export value (R² = 0.742), reflecting strong predictive capability. These findings provide an empirical basis for formulating data-driven strategies to strengthen Indonesia’s cocoa export performance through improvements in production capacity, pricing strategies, and exchange rate stability.

This study explores the dynamic relationship between trade, foreign direct investment (FDI), population growth, carbon emissions, exchange rates, and economic growth for Ghana from 1990 to 2020 using the annual frequency. The study employs the autoregressive distributed lag (ARDL) model, augmented with variance decomposition, impulse response, and causality tests to estimate both the short-run and long-run effects of the variables. The empirical results shows that FDI and CO₂ emissions have a positive long-run impact on economic growth, while exchange rate volatility and trade openness have a negative short-run impact on economic growth. The term for the error correction confirmed the presence of a stable equilibrium in the long run. Furthermore, the results show that the economic growth of Ghana remains associated with a higher environmental pollution, reflecting the first phase of the environmental Kuznets curve (EKC) hypothesis. The growth in population has marginal but persistent impacts from the impulse response models, showing that the population pressure without productivity increases in the short term. Additionally, the model converges at eight to ten periods, a result which shows that the economy adjusts to exogenous shocks, and returns to the long-run equilibrium as time progresses. Policy suggestions also incline towards further promoting green investment channels, environmental regulations, and adjusting trade and FDI policies in order to promote sustainable development.

This study examines the economic implications of currency devaluation for Small and Medium-Scale Enterprises (SMEs) in the Gwagwalada Area Council of the Federal Capital Territory, Nigeria. SMEs are critical to Nigeria’s economy, contributing substantially to GDP and employment, yet they remain highly vulnerable to exchange rate fluctuations. Using a descriptive survey design, data were collected from 200 SME owners and managers and analysed with descriptive statistics and hypothesis testing. Findings reveal that currency devaluation significantly undermines the financial performance of SMEs by raising operational costs and lowering profitability, though no significant relationship with productivity levels was found. Interestingly, devaluation encouraged greater reliance on locally sourced inputs, fostering some growth of indigenous firms. However, high dependency on imported machinery and raw materials leaves SMEs exposed to foreign exchange volatility. The study recommends targeted government interventions, including financial support and policies promoting local manufacturing, to mitigate adverse effects.

Controlling and preventing cost overruns in defense construction projects remain a core, ongoing challenge for project managers. Due to the strategic significance of these endeavors and the numerous factors that drive cost increases in construction, extensive research has been conducted on this subject. Literature review indicates that the identification of cost overrun factors often relies solely on literature review and expert interviews. This research utilizes the Failure Mode and Effects Analysis (FMEA) technique, treating the identified causes of cost overrun as potential failure events. The identified factors are subsequently ranked using the Risk Priority Number (RPN) index. Finally, these factors are categorized, and corresponding risk response scenarios are proposed for their prevention or control. The resulting ranking clearly indicates that external macroeconomic shocks, specifically General Inflation (RPN=810) and Currency Exchange Volatility (RPN=729), represent the most significant threats due to their high inherent severity and difficulty of detection. This research thus provides a prioritized framework, demonstrating that effective cost management in this sector requires a strategic shift toward contractual and financial engineering to buffer against systemic instability, rather than focusing solely on internal project execution efficiencies.