This study informs the academic and policy debate on the policy effectiveness of exchange rate interventions on exchange rate levels and volatility. Using a constructed data set comprising daily data on exchange rates, monetary policy fundamentals, exchange rate intervention dates and magnitudes of those interventions as well as financial news speculation of such interventions, we empirically estimate the policy effectiveness of Bank of Japan interventions in the exchange rate over the 12-year period between 2010 and 2022. This allows us to investigate the policy effectiveness of a variety of exchange rate interventions, or news of exchange rate interventions, across different time-horizons. We find that policy interventions in the yen exchange rate are more effective over short-horizons than long-horizons, more effective when the policy objective is a competitive devaluation of the yen rather than a revaluation, and more effective at influencing the level of the yen against major world currencies other than the US dollar. In fact, for the yen-dollar rate, we find that policy interventions may have the unintended consequences of weakening the yen (when the policy intention is to strengthen it) and increasing volatility in the yen-dollar exchange rate.

The COVID-19 crisis, which occurred in 2020, brought crisis events back to the attention of scholars. With the increasing frequency of crisis events, the influence of crisis events on stock markets has become more obvious. This paper focuses on the impact of the subprime crisis, the Chinese stock market crash crisis and the COVID-19 crisis on the volatility and risk of the world’s major stock markets. In this paper, we first fit the volatility using EGARCH model and detect asymmetry of volatility. After that, a VaR model is calculated on the basis of EGARCH to measure the impact of the crisis event on the risk of stock markets. This paper finds that the subprime crisis has a significant influence on the risk of the stock market in China, US, South Korea, and Japan. During the COVID-19 crisis, there was little change in the average risk of each country. But at the beginning of the COVID-19 crisis, there was a significant increase in the risk of each country’s stock market. The Chinese stock market crash crisis had a more pronounced effect on the Chinese and Japanese stock markets and a lesser effect on the US and Korean stock markets.

This paper investigates the factors influencing credit growth in Kosovo, focusing on the relationship between credit activity and key economic variables, including GDP, FDI, CPI, and interest rates. Its analysis targets loans issued to businesses and households in Kosovo, employing a VAR model integrated into a VEC model to investigate the determinants of credit growth. The findings were validated using OLS regression. Additionally, the study includes a normality test, a model stability test (Inverse Roots AR Characteristic Polynomial), a Granger causality test for short-term relationships, and variance decomposition to analyze variable shocks over time. This research demonstrates that loan growth is primarily driven by its historical values. The VEC model shows that, in the long run, economic growth in Kosovo leads to less credit growth, showing a negative link between it and GDP. Higher interest rates also reduce credit growth, showing another negative link. On the other hand, more foreign direct investment (FDI) increases credit demand, showing a positive link between credit growth and FDI. The results show that loans and inflation (CPI) are positively linked, meaning higher inflation leads to more credit growth. Similarly, more foreign direct investment (FDI) increases credit demand, showing a positive link between FDI and credit growth. In the long term, higher inflation is connected to greater credit growth. In the short term, the VAR model suggests that GDP has a small to moderate effect on loans, while FDI has a slightly negative effect. In the VAR model, interest rates have a mixed effect: one coefficient is positive and the other negative, showing a delayed negative impact on loan growth. CPI has a small and negative effect, indicating little short-term influence on credit growth. The OLS regression supports the VAR results, finding no effect of GDP on loans, a small negative effect from FDI, a strong negative effect from interest rates, and no effect from CPI. This study provides a detailed analysis and adds to the research by showing how macroeconomic factors affect credit growth in Kosovo. The findings offer useful insights for policymakers and researchers about the relationship between these factors and credit activity.

This study highlights the importance of social capital within third sector organizations, as in other sectors of the economy, and confirms the influence of social capital on human capital. In this case, it contributes to the analysis of the structure and quality of relationships among members of a social organization, which enables motivation and commitment to collective action. Based on exploratory and confirmatory factor analysis, from a 45-item survey applied to 190 workers in social organizations; the constructs were reconfigured for the construction of the model of organizational social capital, was carried out using the structural equation methodology. It is argued that the cognitive and structural dimensions of social capital affect its relational dimension in terms of identification, trust and cooperation, which in turn influences worker motivation and other key aspects of human capital. The relational dimension, measured by workers’ identification, trust, and cooperation, has significant effects on their motivation and work engagement, which leads to important practical considerations for human resource policies in these organizations. The article contributes to the existing literature on human capital management by exploring the perception of workers in nonprofit organizations that are part of Ecuador’s third sector.

In order to diversify a portfolio, find prices, and manage risk, derivatives products are now necessary. There is a lack of understanding of the true influence of derivatives on the behavior of the underlying assets, their volatility consequences, and their pricing as complex instruments. There is a dearth of empirical research on how these instruments impact company risk exposures and inconsistent findings. This study examines corporate derivatives’ impact on stock price exposure and systematic risk in South African non-financial firms. Using a dataset of listed firms from 2013 to 2023, we employ Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to assess the effect of derivatives on return volatility and beta, a measure of systematic risk. Additionally, we apply the Generalized Method of Moments (GMM) to address potential endogeneity between firm characteristics and derivatives use. Our findings suggest that firms using derivatives experience lower overall volatility and reduced systematic risk compared to non-users. The results are robust to various control factors, including firm size, leverage, and macroeconomic conditions. This study fills a gap in the literature by focusing on an underrepresented emerging market and provides insights relevant to global risk management practices.

This study uses a Time-Varying Parameter Stochastic Volatility Vector Autoregression (TVP-SV-VAR) model to conduct an empirical analysis of the dynamic effects of China’s stock market volatility on the agricultural loan market and its channels. The results show that the relationship between stock market and agricultural loan market volatility is time varying and is always positive. The investor sentiment is a major conduit through which the effect takes place. This time-varying effect and transmission mechanism are most apparent between 2011 and 2017 and have since waned and stabilized. These have significant implications for the stable and orderly development of the agricultural loan market, highlighting the importance of the sound financial market system and timely policy, better market monitoring and early warning system and the formation of a mature and sound agricultural credit mechanism.