A large language model-based method using weighted double-well potential support vector regression for foreign exchange rate robust forecasting

Much Ado about global uncertainty: Volatility transmission between US-China tension and African foreign exchange markets

Financial sustainability of small and medium-sized enterprises (SMEs) is a critical component of sustainable tourism development, particularly in emerging tourism destinations. However, SMEs in the hotel sector often face significant financial challenges. This study aims to investigate the financial problems encountered by SME hotels in Şanlıurfa and propose potential solutions to these problems. A structured questionnaire was administered to 42 business owners and managers to assess their perceptions of various financial issues, the use of external financing, access to bank loans, and financial planning habits. The findings reveal high interest rates, foreign exchange rate fluctuations, lack of equity capital, and difficulties in obtaining credit are the most critical financial challenges faced by these companies. In addition, bank loans are the predominant external financing instrument, with a strong preference for short-term credit. Key obstacles to effective bank loan utilization include a lack of transparency, insufficient financial knowledge, and deficiencies in financial documentation. The study suggests that public support should be strengthened to improve financial literacy and planning among SME hotels, offering valuable insights for industry and literature in advancing sustainable tourism.

Large Language Models (LLMs) are increasingly being adopted in business settings; however, there remains a shortage of evaluation tools that account for country-specific regulations, particularly for Romania’s taxation and financial accounting requirements. RO-FIN-LLM is a benchmark designed to test how well LLMs handle Romania-specific regulatory question answering in taxation (including VAT regimes, income/profit tax, microenterprise rules, and other obligations) and financial accounting (including journal entries/monographs, amortization, provisions, and foreign exchange transactions). The benchmark contains questions curated by experts, each including the applicable regulatory time frames and the legal sources for the answers. Evaluation is performed in two protocols: closed-book and open-book with Retrieval Augmented Generation (RAG), using Tavily Search API. Evaluation metrics are represented by rubrics, namely correctness, legal citation quality, and clarity/structure. A subset of answers produced by three models was additionally evaluated by 12 specialists in the financial-accounting domain. In this revision, we also describe a public release plan for the question schema, prompts, and evaluation scripts to support independent reproducibility.

This study investigates the factors influencing export performance in five ASEAN countries Indonesia, Malaysia, the Philippines, Singapore, and Thailand during the 2014-2023 period. The topic is highly relevant given the vital role of exports in sustaining monetary stability and promoting long-term economic growth. The novelty of this research lies in its integrated approach, which simultaneously examines key export-related macroeconomic variables, namely foreign direct investment and inflation, while incorporating foreign exchange reserves as a moderating variable an approach that remains limited in existing ASEAN-focused studies. This analysis uses secondary data obtained from the World Bank and processed using panel data regression methods, including the Common Effect Model, Fixed Effect Model, and Random Effect Model, strengthened by a Moderated Regression Analysis (MRA) approach. The results show that foreign direct investment and inflation significantly influence foreign exchange reserves. Furthermore, foreign exchange reserves have been shown to play a strategic role in strengthening the economic resilience of ASEAN countries and can be used as a reference in formulating monetary and international trade policies.

ABSTRACT This article analyses Turkey’s monetary policy experiment between 2018 and 2023. While central banks globally tightened monetary policy in response to rising inflation, Turkey pursued sustained interest rate cuts, expanded state-directed credit and relied on discretionary intervention in foreign exchange and financial markets. Conventional explanations centred on leadership preferences, institutional erosion or electoral opportunism cannot fully account for the persistence or timing of this unorthodox regime. Drawing on the Growth Models Perspective and critical state theory, the article argues that the experiment emerged from the exhaustion of Turkey’s credit-driven, dependent financialised growth model and the political realignments this exhaustion generated. As external vulnerabilities intensified, sectorally differentiated monetary preferences reshaped the dominant social bloc, giving rise to a coalition favouring low interest rates, credit expansion and discretionary state intervention. This coalition sustained the experiment after 2021 by stabilizing employment and economic activity despite accelerating inflation. However, the internal logic of the experiment intensified balance-of-payments pressures and led to sustained reserve depletion, rendering the regime untenable. After the 2023 elections, monetary policy was gradually recalibrated towards orthodoxy under binding external constraints. The article conceptualizes monetary policy as a coalition-mediated political instrument shaped by structural external constraints.

Fish is one of the most significant animal protein sources, generally acknowledged as a strong source of protein and other nutrients for maintaining a healthy body. They have significant role in nutrition, income, employment and foreign exchange earning of the country. This work attempts to provide information on the morphometric characteristics of Hydrocynus forskahlii in the Lower Benue River, outlining the relationship between length and weight as well as determining the condition factor. Ninety-nine samples of Hydrocynus forskahlii were obtained from local markets in Makurdi town (Wadata and Wurukum Market) and transported to the laboratory for analysis. Morphometric measurements included the Head Length, Total Length, Body Length, Body Weight, Eye Diameter, Standard Length and Total Length; these were obtained using a meter rule and body weight was determined using an electric weighing scale. The length-weight relationship and Condition factor of Hydrocynus forskahlii calculated showed that the species exhibited negative allometric growth (b<3) from the growth exponent values (b) deduced from the log weight-log length relationships plotted, with condition factor (K) value of 1.31, 1.50 and 1.31 for the Months of January, February and March, respectively, an indication that the fish species is well suited to the Benue River. A strong positive correlation (r) was observed between Body Weight and Total and Standard Length (r = 0.5585, r = 0.7219, respectively), while the relationship was weak between Body Weight and Head Length, Eye Diameter and Body Length (r = 0.2615, r = 0.1338 and r = 0.2381, respectively). The morphometric and meristic data obtained from the study of the species show differences in variation of the features but however, provides useful information for the identification of this species and other species within the same family. However, further morphometric studies should include environmental as well as genetic conditions so as to be sure exactly what affects the wellness of the fish species. Also, from the obtained vales of K, which indicate suitable conditions for the well-being of the species in the Benue River, it is recommended that such environmental conditions should be maintained, over exploitation of the fish species should be prevented and dumping of refuse into the River should be checked.

Currency-Hedged Deposits (CHD) were introduced in Türkiye to hedge the currency risk. Hence, it is aimed to provide macroeconomic stability in this country. Nevertheless, the impact of this implication on banks' participation is unclear. This study analyzes the impact of the foreign exchange hedge deposit (CHD) mechanism on the financial performance of participation banks in Türkiye. This study integrates fuzzy multi-criteria decision-making analysis with panel data regression. In this framework, data from these banks for 2021-2023 is considered. First, panel regression analysis is conducted for six participating banks. Second, a Euclidean distance-based CIMAS technique is used to find the most critical criteria. For this purpose, Fermatean fuzzy numbers are considered in this modelling process to handle uncertainties more effectively. The main contribution of this research is the hybrid consideration of panel data regression and fuzzy decision-making analysis. Owing to this combination, the impact of this new implication on bank participation can be more effectively identified. Econometric results indicate that CHD has a positive impact on profitability. On the other hand, risk management and compatibility with interest-free financing are the most critical factors.

ABSTRACT This paper examines the drivers and impacts of extreme capital flow events in emerging markets, with a focus on distinguishing among flow types (portfolio, bank and FDI) and event categories (surge vs. stop). We find that the global financial cycle drives extreme events in portfolio and bank flows, while FDI is more sensitive to domestic factors. Notably, sudden stops in cross‐border capital flows, particularly in bank and FDI flows, have a greater impact on the overall risk interconnectedness of domestic financial submarkets compared to surge events. We also identify the transmission channels: extreme bank flow events increase credit market net risk spillovers, while concurrent extreme capital flow events heighten foreign exchange market net risk spillovers. Further discussion shows that foreign exchange sales and macroprudential policies mitigate the adverse effects of negative global financial cycle shocks, with macroprudential measures demonstrating stronger effectiveness in the medium term.

Religious tourism is a part of overall tourism industry and is a significant driver of Nepalese economy, spurring substantially to the creation of employment, foreign exchange reserve, and promoting cultural exchange. Despites its immense contribution, the systematic study and analysis in this regard is still sparse, scant and even neglected in the Nepalese context. The aim of this paper is to examine the trend and pattern of the tourist arrival and specially focusing on the religious tourist arrivals in Nepal, and discuss its association with business growth of local economy. This study uses the time series data spanning between 1993 to 2023 on the total tourist and religious tourist arrival to examine the trend of religious tourist arrival. The evidence suggests that during the period 1993–1997, the share of religious remained quite low, ranging mostly between one percent to three percent, whereas the late 1997 to early 2000s saw a gradual increase, but the most notable change is observed between the period 2002 and 2004. However, religious tourist arrival between the period 2011 and 2016 showed considerable volatility, with multiple sharp drops, possibly due to disruptive events such as natural disasters or socio-political upheavals seen during the period of constitution of Nepal Promulgation. The period between 2016 to 2020, strong recovery could be observed, ranging religious tourist arrival 14-16 percent, showing optimistic scenario after full-fledged declaration Federal Democratic Republic of Nepal. But, a sharp dip occurred in 2021 due to COVID-19 lockdown and global travel restrictions, but a recovery followed in 2022–2023, with percentages climbing back above 14 percent. The trend of religious tourist shows a steady upward indicating, potentiality for Nepalese economy. It also suggests policy implications for boosting pilgrimage and cultural tourism. The findings highlight that several religious sacred sites including Pashupatinath’s, accounting for a significant proportion of international arrivals.

Purpose: The financial distress of insurance companies listed at the NSE had become a significant concern, as several firms faced difficulties in maintaining solvency and meeting their financial obligations. In recent years, these companies experienced declining profitability, liquidity issues, and capital adequacy challenges. The main objective of this study was to determine the effect of inflation risk on the financial distress of insurance companies listed at Nairobi Securities Exchange in Kenya. The study was anchored on expectations theory of inflation. Methodology: The study employed a descriptive research design. For this study, the population consisted of all six insurance companies listed on the NSE as of December 2024. This study employed secondary data collection methods, gathering comprehensive annual financial and statistical information from the NSE reports, IRA publications, and the official websites of the listed insurance companies. Data were collected for 7 years between 2017 and 2023. Data were analyzed using descriptive and inferential statistics with the aid of STATA 17. The descriptive statistical tools included frequencies, percentages, means, variances, and standard deviations. Inferential statistic tools included Pearson’s Product Moment correlation and the panel regression analysis. Findings: Inflation risk with a coefficient value of 0.391171 and p value of 0.024, therefore positively and significantly affecting the financial distress of insurance companies listed at Nairobi Securities Exchange in Kenya Unique Contribution to Theory, Practice and Policy: Insurance firms should adopt hedging strategies for foreign exchange, strengthen asset-liability matching to manage interest rate exposure, implement inflation-adjusted pricing models, and diversify portfolios to cushion against equity market shocks, while regulators should encourage prudent risk management, promote derivatives markets, and enforce strong capital adequacy frameworks to safeguard financial stability.

How would an expansion in the use of special drawing rights (SDR) affect the currency composition of the international reserve system? This study explores this question by proposing a novel analytical framework based on the analytic hierarchy process (AHP) model. We incorporate the use of SDR as a reserve asset and a denomination into an AHP model to determine the currency structure in global foreign exchange (FX) reserves. We then design scenario simulations to analyze changes in the currency structure of global FX reserves with expansion in the use of SDR. We show that greater SDR use can lead to convergence in the share of each SDR currency in international reserves based on their weight in the SDR. At present, the share of the USD in international reserves exceeds its weight in the SDR, and the share of other SDR currencies, such as the EUR and RMB, is below their respective weights. Hence, expanding SDR use would weaken the reserve position of the USD and strengthen that of the EUR and RMB, making the international reserve system more balanced.

In recent political and policy discourse, a widely circulated claim has asserted that Bangladesh experienced illicit capital outflows averaging approximately USD 16 billion annually between 2009 and 2023, resulting in a cumulative loss of nearly USD 240 billion. This figure, repeatedly cited in media commentary and reinforced by a government-commissioned white paper, has generated substantial public concern, shaped political narratives, and influenced policy debates on governance, corruption, and financial accountability. Given the scale of the alleged outflows relative to Bangladesh’s gross domestic product, foreign exchange reserves, and investment capacity, such claims warrant careful and systematic empirical scrutiny rather than uncritical acceptance. This paper critically evaluates the plausibility of the alleged magnitude of capital flight by situating the claim within Bangladesh’s broader macro-economic trajectory and development outcomes over the same period. Between 2009 and 2023, Bangladesh recorded sustained economic growth, rising per capita income, expanding export earnings, improved social indicators, and increased public investment in infrastructure and human development. These outcomes raise important analytical questions regarding the internal consistency of claims suggesting prolonged, large-scale capital leakage of the magnitude alleged. Employing a mixed-methods approach, the study integrates macroeconomic trend analysis, balance-of-payments indicators, external debt dynamics, reserve accumulation patterns, and comparative assessments using independent global estimates of illicit financial flows. Qualitative analysis further examines how political incentives, methodological opacity, and definitional ambiguities may contribute to the inflation or misinterpretation of capital flight estimates. The findings suggest that while illicit financial flows have undoubtedly occurred, consistent with patterns observed in many developing economies, the scale of such outflows is likely significantly lower than the figures commonly cited in political discourse. The paper argues that conflating legitimate economic leakages, trade mis-invoicing estimates, and politically motivated extrapolations risks distorting public understanding and undermining credible policy formulation. It emphasizes the importance of separating political narratives from evidence-based economic analysis and cautions against framing development challenges solely through sensational aggregate figures. Finally, the study advocates targeted institutional reforms to strengthen financial oversight, trade transparency, and data credibility, while recognizing and preserving Bangladesh’s documented development progress and structural economic gains over the period under review.

This paper develops a framework to predict toxic trades that a broker receives from her clients. Toxic trades are predicted with a novel online learning Bayesian method which we call the projection-based unification of last-layer and subspace estimation (PULSE). PULSE is a fast and statistically-efficient Bayesian procedure for online training of neural networks. We employ a proprietary dataset of foreign exchange transactions to test our methodology. Neural networks trained with PULSE outperform standard machine learning and statistical methods when predicting if a trade will be toxic; the benchmark methods are logistic regression, random forests, and a recursively-updated maximum-likelihood estimator. We devise a strategy for the broker who uses toxicity predictions to internalise or to externalise each trade received from her clients. Our methodology can be implemented in real-time because it takes less than one millisecond to update parameters and make a prediction. Compared with the benchmarks, online learning of a neural network with PULSE attains the highest PnL and avoids the most losses by externalising toxic trades.

Analysis of EUR to USD exchange rates with uncertain time series model and uncertain differential equation

Abstract Long-term prediction of exchange-rate (XR) signals has been an interesting topic in statistics and finance. However, owing to strong fluctuations in XR signals, long-term prediction remains extremely difficult, and no consensus has been reached on an ideal approach that produces the best estimation accuracy. XR signals are known to be highly volatile (chaotic), which makes it difficult to model them via an accurate statistical framework. In this paper, we attempt to uncover the long-term system dynamics behind AUD/USD and EUR/GBP XR signals by modeling them with reduced stochasticity and minimized volatility in the form of a linear stochastic difference equation (LSDE) via the recursive least squares (RLS) regression approach. On the basis of these two well-known XRs, the simultaneous presence of inherent stochasticity and strong volatility makes prediction difficult for XR signals. Our findings indicate that under the use of a sufficiently large training sample size for RLS regression, the LSDE coefficients of XR signals assume values within a very small range (low variance) and behave relatively consistently in time (low volatility), which concurrently suppresses both their stochasticity and chaoticity, enabling long-term prediction under a reduction of more than 60% in the prediction error. This study aims to decrypt XR signal dynamics in terms of the underlying LSDE coefficients and to develop an accurate LSDE model with minimum uncertainty (stochasticity, volatility) that can overcome the hinderance of precise long-term prediction.

Abstract Using confidential daily data, we examine the Bank of Israel's foreign exchange interventions from 2013 to 2019. We find that a 1 billion U.S. dollars (USD) purchase leads to a 0.82% depreciation of the Israeli Shekel (ILS)–a strong effect compared to other studies. We show that this effectiveness can partially be attributed to the limited risk‐taking capacity of global banks. The interventions also widen the negative deviation from covered interest parity and influence the higher‐order moments of risk‐neutral expectations derived from options prices. We find that USD purchases shift the USD/ILS distribution upward and reduce crash risk. Moreover, the options market anticipates and prices in upcoming interventions.

Preference reversal and quantitative easing

This study aims to analyze the effect of Foreign DirectInvestment (FDI) and exchange rates on Gross Domestic Product (GDP) in theASEAN region from an Islamic economic perspective for the period 2014-2024. ASEANis a dynamic region with rapid economic growth, but itfaces significant challenges influenced by foreign investment flows andexchange rate fluctuations. This study uses a quantitative approach with time series and cross-section secondary data in the form of dynamic panel data, as well as usingthe dynamic panel regression analysis method using the FD-GMM model. The data was obtainedfrom the World Bank and ASEAN Statistics. The results show that FDIhas a positive and significant effect on GDP, reinforcing that foreign investmentcan drive economic growth through increased capital, technology transfer, and job creation. Conversely, exchange rates do nothave a significant effect on GDP in the tested data. From an Islamic economic perspective, investment and exchange rates must be carried out in accordance with sharia principlessharia principles in order to provide blessings and benefits. Therefore, in conclusion,an increase in FDI can be a major driver of GDP growth in ASEAN, whileexchange rates need to be managed in a stable manner so as not to cause negative impacts.This study makes an important contribution to economic policy-makingin ASEAN within the framework of sharia for sustainable economic development.

The first review of the ECF was delayed amid program slippages last year. The authorities exceeded the 2024 budget deficit by a sizable margin, and the BSL helped finance the overruns. At the same time, higher-than-expected government spending on imports and energy subsidies substantially depleted the BSL’s foreign exchange reserves. The authorities have since tightened policies, contributing to a sustained decline in inflation and a welcome fall in borrowing costs. However, pressures on reserves remain unabated.