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This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

This paper assesses the co-movement between Pax gold and six fiat currencies. It also investigates the optimal time-varying hedge ratios in order to examine the properties of Pax gold as a diversifier and hedge asset.

This paper examines the volatility spillover between Pax gold and fiat currencies using the framework of wavelet analysis, BEKK-GARCH models and Range DCC-GARCH. Moreover, this paper proposes to use the covariance and variance structure obtained from the new range DCC-GARCH framework to estimate the time-varying optimal hedge ratios, the optimal weighs and the hedging effectiveness.

Wavelet coherence method reveals that, at low frequency, large zone of co-movements appears for the pairs Pax gold/EUR, Pax gold/JPY and Pax gold/RUB. Further, the BEKK results show unidirectional (bidirectional) transmission effects between Pax gold and EUR, GBP, JPY and CNY (INR, RUB) fiat currencies. Moreover, the Range DCC results show that the Pax gold and the fiat currency returns are weakly correlated with low coefficients close to zero. Thus, Pax gold seems to serve as a safe haven asset against the systematic risk of fiat currency markets. In addition, the results of optimal weights show that rational investor should invest more in Pax gold and less in fiat currencies. Concerning the hedge ratios results, the findings reveal that the INR (JPY) fiat currency appears to be the most expensive (cheapest) hedge for the Pax-gold market. However, the JPY’s fiat currency appears to be the cheapest one. As for hedging effectiveness results, the authors found that hedging strategies including fiat currencies–Pax gold pairs are most likely to sharply decrease the portfolio’s risk.

A comprehensive understanding of the relationship between Pax Gold and fiat currencies is crucial for refining portfolio strategies involving cryptocurrencies. This research underscores the significance of grasping volatility transmissions between these currencies, providing valuable insights to guide investors in their decision-making processes. Moreover, it encourages further exploration into the interdependencies of digital currencies. Additionally, this study sheds light on effective contagion risk management, particularly during crises such as Covid-19 and the Russia–Ukraine conflict. It underscores the role of Pax Gold as a safe-haven asset and offers practical guidance for adjusting portfolios across various economic conditions. Ultimately, this research advances our comprehension of Pax Gold’s risk-return profile, positioning it as a potential hedge during periods of uncertainty, thereby contributing to the evolving literature on cryptocurrencies.

This study’s primary value lies in its pioneering empirical examination of the time-varying correlations and scale dependence between Pax Gold and fiat currencies. It goes beyond by determining optimal time-varying hedge ratios through the innovative Range-DCC-GARCH model, originally introduced by Molnár (2016) and distinguished by its incorporation of both low and high prices. Significantly, this analysis unfolds within the unique context of the Covid-19 pandemic and the Russian–Ukrainian conflict, marking a novel contribution to the field.

The COVID-19 pandemic and the onset of the conflict in Ukraine led to a sustained downturn in tourist arrivals (TA) in Russia. This paper aims to explore the influence of geopolitical risk (GPR) and other indices on TA over 1995–2023.

We employ a nonlinear autoregressive distributed lag (NARDL) model to analyze the effects, capturing both the positive and negative shocks of these variables on TA.

Our research demonstrates that the NARDL model is more effective in elucidating the complex dynamics between macroeconomic factors and TA. Both an increase and a decrease in GPR lead to an increase in TA. A 1% negative shock in GPR leads to an increase in TA by 1.68%, whereas a 1% positive shock in GPR also leads to an increase in TA by 0.5%. In other words, despite the increase in GPR, the number of tourists coming to Russia increases by 0.5% for every 1% increase in that risk. Several explanations could account for this phenomenon: (1) risk-tolerant tourists: some tourists might be less sensitive to GPR or they might find the associated risks acceptable; (2) economic incentives: increased risk might lead to a depreciation in the local currency and lower costs, making travel to Russia more affordable for international tourists; (3) niche tourism: some tourists might be attracted to destinations experiencing turmoil, either for the thrill or to gain firsthand experience of the situation; (4) lagged effects: there might be a time lag between the increase in risk and the actual impact on tourist behavior, meaning the effects might be observed differently over a longer period.

Our study, employing the NARDL model and utilizing a dataset spanning from 1995 to 2023, investigates the impact of GPR, gross domestic product (GDP), real effective exchange rate (REER) and economic policy uncertainty (EPU) on TA in Russia. This research is unique because the dataset was compiled by the authors. The results show a complex relationship between GPR and TA, indicating that factors influencing TA can be multifaceted and not always intuitive.

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

This paper examines the main drives of encouraging Iranian investors in the Turkish real estate market, focusing on the interface between push factors and pull factors that drive them abroad.

This paper examines the main drives of encouraging Iranian investors in the Turkish real estate market, focusing on the interface between push factors and pull factors that drive them abroad. For this purpose, the trend of housing price growth in Iran and Turkey was compared. The review of the 11-year trend of rates shows that housing prices in both countries have been continuously rising, and these prices have undoubtedly experienced increasing shocks in Iran. For further analysis, 13 main variables leading to the repulsion of investment in Iran's housing market and 15 variables shaping the attractiveness of investment in Turkey were identified in this sector. Thirty experts subsequently ranked the significant variables based on a closed-end questionnaire using quantitative strategic planning matrix. Examining housing investment elasticity in Turkey also shows that “Turkey's economic stability compared to neighboring countries” and “acquiring Turkish citizenship through real estate investment” are among the most important variables. On the other hand, the pressure variables of housing investment in Iran were “decrease in the value of the Iranian currency in recent years,” “currency price fluctuations” and “severe fluctuations and instability in the Iranian housing market.”

Examining housing investment elasticity in Turkey also shows that “Turkey's economic stability compared to neighboring countries” and “acquiring Turkish citizenship through real estate investment” are among the most important variables. On the other hand, the pressure variables of housing investment in Iran were “decrease in the value of the Iranian currency in recent years,” “currency price fluctuations” and “severe fluctuations and instability in the Iranian housing market.”

From a theoretical standpoint, foreign investment is in support of Turkey and harmful to Iran because the Turkish government is bolstering investment attractiveness to bring increased capital inflows into this country. Practically speaking, Turkey has aimed to create a rational framework for investors by strengthening and changing its economic system, as well as amending existing constitutions in this domain. Nevertheless, Iran resists any changes in its economic system and legislation. Therefore, a wide range of attractiveness and repulsion variables has led to the migration of Iranian investors to Turkey. In the present study, such variables are illuminated.

The Polish economy has undergone major challenges and changes over the past few decades. The country's trade flows, in particular, have become more firmly tied to the country’s Western neighbors as they have grown in volume. This study examines Poland's trade balances in ten Standard International Trade Classification (SITC) sectors versus the United States of America, first testing for and isolating structural breaks in each time series. These breaks are then included in a set of the cointegration models to examine their macroeconomic determinants.

Linear and nonlinear and nonlinear autoregressive distributed lag models, both with and without dummies corresponding to structural breaks, are estimated.

One key finding is that incorporating these breaks reduces the significance of the real exchange rate in the model, supporting the hypothesis that this variable already incorporates important information. It also results in weaker evidence for cointegration of all variables in certain sectors.

This study looks only at one pair of countries, without any third-country effects.

An important country pair's trade relations is examined; in addition, the real exchange rate is shown to incorporate economic information that results in structural changes in the economy. The paper extends the existing literature by conducting an analysis of Poland's trade balances with the USA, which have not been studied in such a context so far. A strong point is a broad methodology that lets compare the results the authors obtained with different kinds of models, both linear and nonlinear ones, with and without structural breaks.

The authors explore the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic.

The authors employ a non-linear autoregressive distributed lag (NARDL) methodology using daily data of the Indonesian economy over the period 2012–2021.

Whilst, over the full sample period, the authors find no cointegration between the exchange rate, the 10-year bond yield and stock market, for the COVID-19 period, evidence of cointegration is present. Furthermore, the results suggest that asymmetric effects are evident both in the short as well as the long run.

To the best of the authors’ knowledge, this is the first time that the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic has been explored in the case of the Indonesian economy.

Introduction: The Stock Exchange is an economic indicator of sustainability in the global market over an extended period. The Indian economy has observed a downfall in foreign currency in quarter 2 of 2022, as per the reports of the International Monitory Fund. The central banks of many countries have been facing crises because of a piercing decline in their reserves, which is additionally affecting their sustainable performance. The Indian economy is one of the most potentially sound economies emerging as a global leader, and this study is an attempt to understand the economy’s vulnerability to foreign factors.

Purpose: The research explores the impact of the US Dollar, EURO and Japanese Yen on Bombay Stock Exchange and the National Stock Exchange Index.

Methodology: Four variables have been considered for the conduct of the study: Sensex, Nifty, inflation and foreign exchange. Sensex and Nifty have been taken as dependent variables, while foreign exchange and inflation have been taken as independent variables.

The regression analysis has been performed using Microsoft Excel: The variables used for the study are monthly values from January 2011 to December 2020. The specific period is selected to avoid the impact of COVID-19 on the stock market, avoiding biases in the results.

Findings: All the variables are affecting the performance of each other up to a certain level.

Practical Implication: The research chapter will help the investor understand the relationship between many variables and their impact on the stock market, which will assist them in gaining higher profits.

The purpose of this study is to analyze the fluctuations in gold prices within the Saudi Arabian market and to develop a reliable forecasting model to aid market participants and policymakers in making informed decisions.

In this study, we employ a rigorous time series analysis methodology, including the ARIMA (Auto Regressive Integrated Moving Average) model, to analyze historical gold price data in the Saudi Arabian market. The approach involves identifying optimal model parameters and assessing forecast accuracy to provide actionable insights for market participants.

The study showcases that the autoregressive properties of past gold prices play a pivotal role in capturing the inherent serial correlation within the market, enabling the ARIMA model to effectively forecast future gold price movements with accuracy.

Our study primarily focuses on quantitative analysis, whereas few qualitative parameters are not included. Future studies may benefit from incorporating qualitative factors and expert opinions to enhance the robustness of gold price predictions and capture the full spectrum of market dynamics.

Participants and policymakers may find this study helpful in navigating the complicated Saudi Arabian gold market. By understanding financial stability and investment decisions more thoroughly, individuals and institutions may be able to manage their portfolios more effectively.

By combining historical insights with advanced ARIMA modeling techniques, this research provides valuable insight into gold price dynamics in the Saudi Arabian market.

This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.