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Abstract: We analyze the announcement risk premia on the US market. Our evidence suggests that between September 1987 and March 2023, 99% of the overall cumulative risk premia on the Russell 3000 index is earned on days when data on 17 important macroeconomic variables are released (46% of all trading days). The average return on those days is 6.7 bps compared to 0.9 bps earned on days without any announcements. We show how the premia changes across different industries. A trading strategy holding long positions in equities on announcement days and long positions in risk-free assets on non-announcement days has more than 2 times higher Sharpe Ratio over a simple buy-and-hold strategy on equities. We also document how the risk premia of well established asset pricing factors, e.g., beta and size, changes between announcement and non-announcement days.

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Abstract: Fundamental anomalies are explored, for the first time, in the Moroccan stock market. The sample includes non-financial companies from July 2001 to June 2020. We carry out, initially, sorts of returns on anomaly indicators, then, we follow through a regression analysis using a fixed-effect model and the system generalized method of moments methodology. The findings emphasize a significantly positive relationship between returns and the book-to-market ratio and a significantly negative relationship between returns and each of the price-to-earnings and the price-to-cash flow ratios. Regarding the size and the leverage effects, the findings highlight their absence. Finally, we cannot ascertain the existence of a positive or negative price-to-sales effect considering the contradictory results of the tests.

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Abstract: Earnings are crucial indicators for investors and decision-makers. This study examines how seven key earnings attributes - Accrual Quality, Persistence, Predictability, Smoothness, Timeliness, Conservatism, and Value Relevance - affect market valuation, measured by Tobin’s Q, for Portuguese listed firms over three decades. Considering firm characteristics like size, capital structure, capital intensity, growth opportunities, insider ownership, and holding structures, along with industry and year fixed effects, we analyze the relationship between earnings quality and firm value. Using data from 46 non-financial firms listed on the Lisbon Stock Exchange from 1987 to 2016, we find that accrual quality, predictability, and smoothness positively impact firm value, with accrual quality being the most significant. These findings are important for investors, financial managers, and stakeholders, highlighting the role of earnings quality in investment decisions and firm valuation.

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Abstract: We propose that the variance of the log price-earnings ratio is useful in capturing time variation for expected returns, based on our novel second-order dynamic price-earnings ratio model. We demonstrate that the volatility of the log price-earnings ratio significantly predicts positive future stock returns, in various horizons and frequencies, and both in-sample and out-of-sample. We show that the volatility of the log price-earnings ratio significantly predicts negative macroeconomic activities. Further analysis suggests that the volatility of the log price-earnings ratio is correlated with important economic state variables, economic uncertainty, quantity of risk and price of risk.

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Abstract: In the wake of increasing global emphasis on sustainability, understanding the financial implications of ESG performance has become crucial. This study aims to investigate the relationship between ESG performance and stock performance among STOXX Europe 600 companies from 2010 to 2022. Our baseline analysis finds no significant effect of ESG ratings on stock performance when controlling for the Five Fama-French Factors and Momentum. However, a meta-regression of 864 parameter combinations reveals substantial sensitivity to analysis parameters, with varying results favoring either "brown" or "green" companies. Using multiple linear regression analyses, we assess various parameters such as portfolio weighting, score calculation, and return lag. These findings highlight the need for more rigorous robustness tests and parameter comparisons in ESG performance studies.

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Abstract: A firm’s corporate social performance (CSP), which encompasses pursuing various environmental (E), social (S), and governance (G) objectives alongside financial goals, could affect is financial stability or level of financial distress. This study investigates the relationship between the level of firm financial distress and ESG performance, as well as the latter’s subcomponents, for South Africa as example of an emerging market. Further, the difference in this relationship is tested for periods of both stronger and weaker GDP growth, using a sample of 79 companies listed on the Johannesburg Stock Exchange (JSE) during the period 2008 to 2023. Using panel regression methodology, it is found that particularly in periods of stronger economic growth, increased firm CSP performance is correlated with a lower level of financial stability. This result is consistent with previous US evidence, and is relevant to firm management, regulators and investors in their decision making regarding CSP.

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Abstract: We present a novel investigation by studying the role of supply chain network on firms' Environmental, Social, and Governance (ESG) performance as well as on financial performance. Our analysis employs comprehensive financial, board, ESG and supply chain data making an unbalanced panel of 3,028 US publicly traded firms spanning fiscal years from 2005 to 2021. Results from panel data regressions show that a large supply chain network exerts a positive and significant effect on ESG ratings, whereas the effect on financial performance is positive but not always significant. To corroborate our results, we use two different supply chain network measures; namely the number of nodes and the eigenvector centrality, while we use various financial performance measures such as stock returns, ROA, ROE, ROS, and Tobin's Q. The results appear consistent.

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Abstract: The article aims to identify the topological properties of the network of CBM&As executed by CEECs in 2009–2023. It uses network analysis tools to measure structural power through degree, betweenness, and eigenvector centrality methods. The results indicate that CEECs have become more interconnected, with CBM&A activities tripling. The financial, high technology, and industrial sectors were major acquirers and targets. Over the past 15 years, the position of the financial sector has increased as the acquirer, while the importance of the high technology sector has increased significantly as the target. Throughout the period under review, the economies of CZE, LTU, LVA, POL, and SVK occupied the most central place and form the core of this network. Apart from the aforementioned countries, DEU, RUS, ROU, USA, and GBR received a large inflow of foreign capital, while entities from EST and HUN invested heavily abroad through CBM&A.

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Abstract: Based on the debt capacity theory and pecking order theory, this paper examines the effect of equity overvaluation on the choice of payment method in mergers and acquisitions in the Japanese market. Using a sample of 3,052 M&As from 2006 to 2023, our Probit regression analysis shows that equity overvaluation significantly positively influence the cash payments. Our path analysis provides further evidence that debt issuance is an important mechanism through which equity overvaluation affects cash payment. The results hold after considering potential endogeneity issues using propensity score matching and instrumental variable methods. Unlike the previous view of utilizing overvalued equity for stock payments, our evidence support that Japanese firms use overvalued equity to enhance their debt capacity and thus choose cash payments.

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Abstract: This study examines the implied underpricing for firms going public by merging with a Special Purpose Acquisition Company (SPAC), in direct comparison to IPOs. Our data reveals a structural change in the SPAC market that has brought about important IPO-like characteristics to underpricing behavior in SPAC mergers. Underpricing for SPAC mergers, which is rare before the structural change, becomes prevalent, and large underpricing tends to also exhibit high cross-sectional variation. We use Markov Regime Switching Model to confirm the occurrence of the structural change, and identify the timing as June 2020. Further analyses on the determinants of underpricing show that factors that exert differential effects on underpricing for SPAC mergers relative IPOs no longer affect the two markets in significantly different ways after June 2020. Overall, the study offers extensive evidence of a structural change that has assimilated underpricing behavior of SPAC mergers to that of traditional IPOs.

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Abstract: This paper examines the impact of geopolitical risk on mergers and acquisitions activity across a broad group of countries. The study used the World Uncertainty Index (WUI) given for 40 countries from the 2008 to 2023 and the data on M&A, which included more than 400,000 transactions. The results show that WUI change and real GPD value significantly impact the number of transactions in a buyer country for both cross-border and domestic deals. Aspect that emerged from the study is the possibility that for foreign investors, inflation in the target country may play a lesser role and may be more dependent on the overall economic situation, as indicated by the significance of stock exchange index change. The most significant finding is the reverse effect of WUI: it discourages foreign investment for acquirers, while for targets, increasing geopolitical risk in the country boosts foreign transactions within that country.

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Abstract: We investigate the effect of the implementation of resolution reforms on the implicit subsidy of banks across 19 jurisdictions. Following Gandhi and Lusting (2015), we measure banks’ government implicit subsidy using equity abnormal returns. We find that the implementation of bank resolution reforms does not reduce the implicit guarantee of large banks. However, we document an increase in the abnormal returns of non-large banks after the implementation of these resolutions, suggesting a reduction in their implicit subsidies. Non-large banks also reduce their risk-taking compared to large banks. Both sets of findings indicate that, while resolution regulations alter the perceived implicit guarantees for non-large banks, they do not impact investors’ perceptions of TBTF for large banks. Our inferences are robust to the endogeneity of the implementation of resolutions reforms. These findings alert regulators to the potential ineffectiveness of resolution policies in changing investors’ beliefs about TBTF.

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Abstract: Macroprudential policy aims to enhance financial stability and to address liquidity risk by implementing measures to enhance resilience to liquidity shocks. This paper aims to empirically test what is the effect of macroprudential policy on liquidity risk of European Economic Area banks. Using an unbalanced panel covering a sample of over 8000 observations in 2005-2022 we find a reduction in liquidity risk measured both as assets to deposits ratio (LiquidADST), as well as in the liquidity risk exposure ratio (LRE) in response to a tightening of macroprudential policy. This effect is delayed and appears in the second year after the policy change. Our findings contribute to the literature by providing new insights to research on macroprudential policy. They are important for policymakers responsible for safeguarding financial stability, because we show that the effects of macroprudential policy on liquidity are heterogeneous and depend on the instruments applied.

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Abstract: In this paper, we examine the effect of excess liquidity on bank stability in India. We employ both linear and non-linear regressions to examine the effect of excess liquidity on bank stability considering a sample period of 2006-2020. We find that reaction of bank stability to total excess liquidity and voluntary excess liquidity to be positive and statistically significant, in case of all banks put together. We observe heterogenous effects of different types of excess liquidity on bank stability of public sector banks and private sector banks. We also find non-linearity in the effects of excess liquidity on bank stability. We provide policy implications of our study.

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Abstract: The paper presents a cross-sectional analysis of systemic risk and its impact on the total capital ratios (TCRs) of 120 systemically important European banks, combining the panel vector autoregression models with ΔCoVaR. The study covers the European public debt crisis, Brexit, the COVID-19 pandemic, and the war in Ukraine. We confirm that in all turbulent periods, systemic risk has a significant positive effect on the TCR in the periods leading to crisis and a strong negative effect in its aftermath. Systemic risk reverses the impact of macroeconomic factors, while banks' ability to build robust capital no longer depends on the housing market dynamics. Our results indicate spillovers of systemic-risk-induced effects on the TCR between the US and Europe for both listed and unlisted banks. Importantly, we present empirical evidence confirming that the war in Ukraine affects banks’ TCRs similarly to previous crises.

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Abstract: Bitcoin has attracted great attention from academics and investors. However, there is a lack of knowledge about the drivers of Bitcoin market efficiency. This paper aims to study the effect of behavioural factors on the dynamics of Bitcoin market efficiency. Therefore, a novel approach to the dynamics of market efficiency is proposed. This approach is based on the Hurst exponents estimated by Multifractal Detrended Fluctuation Analysis. The investigated behavioural factors are investor uncertainty proxied by economic policy uncertainty indexes and investor attention based on the Google Trends data. The relationship between these variables and the dynamics of market efficiency is estimated using the Autoregressive Distributed Lag model. The findings indicate that investor sentiment is positively associated with the dynamics of Bitcoin market efficiency. Besides, it is noticed that the level of market illiquidity negatively affects the dynamics of Bitcoin market efficiency. The research may be useful for investors and regulators.

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Abstract: We performed a systematic review of decentralised autonomous organization (DAO)-based venture capital (VC) whitepapers. Blockchain technology has spawned novel applications beyond just cryptocurrencies, including DAO, especially considering its potential as funding vehicles. While research on DAOs' governance and applications thrives, their use as VC instruments remains underexplored. Using a systematic review of ten prominent DAO VC whitepapers, we identify ten key components of best practice: registration, permissioned access, token-based voting, staking, separation of strategic and operational votes, dynamic voting duration, adaptive quorum systems, "rage quit" mechanisms, organizational support structures, and comprehensive whitepaper sections. Our findings contribute to two crucial aspects of VC studies. Firstly, we illuminate how blockchain technology fosters trust within the investment ecosystem, potentially mitigating information asymmetries and opportunistic behaviour prevalent in traditional VC settings. Secondly, we highlight the potential of blockchain-based DAO VC to democratize access to capital and address resource imbalances.

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Abstract: Liquidation cascades are the self-reinforcing process by which waves of liquidations of assets pledged as collaterals for loans depreciate collaterals’ prices that leads to further liquidations. These market dynamics jeopardize financial stability. This is even more so when the asset borrowed, and the asset pledged as collateral are of the same class and exhibit high level of volatility. Traditional finance (or TradFi) designed numerous mechanisms to mitigate risks of liquidation cascades over decades, such as intermediation, credit scoring and relationship lending. The core characteristics of decentralization and pseudonymity of blockchain-based credit transactions preclude reusing these efficient mitigation tools but compel designing new mechanisms and tools. The goal of the paper is to expose and discuss the limits of the main existing mechanisms to mitigate risks of liquidation cascades in decentralized finance (or DeFi).

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Abstract: This paper aims to investigate if and how this transition has affected the dependencies between Ethereum and various energy portfolios, including both green and dirty assets. As proxies for dirty energy, we include Brent oil futures prices, West Texas Intermediate crude oil prices, and the MSCI World Energy Index. The clean energy sector is approximated by clean energy ETFs such as the First Trust NASDAQ Clean Edge Green Energy Index Fund, SPDR S&P Kensho Clean Power ETF, and S&P Global Clean Energy Index. Our data sample spans three years, with the date of the Merge at the center of the sample. We find that the correlations between Ethereum prices and the prices of clean energy sources decrease after the Merge. For dirty energy assets, no significant change was observed. Investors' reaction to the Merge in the short term was negative and significant.

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Abstract: In this study, we propose a new predictor of stock returns based on the distance between the end-of-month price and past 10-day moving average, which we term short-term moving-average distance (SMAD). Our measure is motivated by the recency bias and the belief-adjustment model that decision makers are prone to the recency bias in updating their beliefs. While extreme short-term prices are salient to investors, they tend to overreact to the information embedded in SMAD, resulting in a negative return predictability. We empirically confirm this prediction. We next show that the return predictability of SMAD is stronger among stocks with higher salient payoffs, thus providing the supportive evidence for the salience theory in explaining the SMAD premium. Finally, we show that an advantage of SMAD is its effectiveness in predicting the return premia of ten mispricing anomalies.

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Abstract: We use technical indicators, which are traditionally applied to stocks, to explore the predictability of equity ETFs in a random forest classification model. Our analysis suggests that technical signals constructed from stocks can forecast ETFs' future performance. We find that, without risk adjustment, equity ETF long-short portfolios achieve a monthly mean return of up to 0.76%, with a t-statistic of 2.75. In line with limits to arbitrage, we find that the level of market efficiency influences the predictability of technical indicators. It is evidenced that Chinese-focused ETFs outperform US-focused ones when applying the prediction model. Moreover, our findings are robust to different model settings.

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Abstract: This paper shows that sparse factor models fail to capture the predictive patterns in S&P500 index options; rather a high-dimensional stochastic discount factor (SDF) is necessary. Studying a set of 54 option-based factors, our empirical findings suggest that all of them contribute to the SDF. A non-sparse SDF-implied mean-variance efficient portfolio spans the highest mean-variance efficient frontier among all benchmark models, yielding fewer pricing errors for option return anomalies. Factors such as the maturity slope and factor momentum, along with characteristic-based factors exploiting the spreads in embedded leverage, vega, theta, time-to-maturity, and options prices, contribute the most to the SDF.

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Abstract: Theoretical studies find that optimistic investors, who overweight the probabilities of better outcomes, can survive and influence asset prices even in a competitive market. To study the impact of optimistic investors on the cross-section of expected stock returns, I define the measure of attractiveness to optimists of a stock based on rank-dependent probability weighting. In both portfolio-level and firm-level analyses, I find an economically and statistically significant negative relation between the measure of attractiveness to optimists and the expected stock return even after controlling for a set of control variables in the cross-section of U.S. stock returns. Furthermore, this framework both conceptually and empirically subsumes the MAX effect, one of the most common characteristics for lottery-type stocks.

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Abstract: Policymakers in emerging economies are increasingly concerned that global ESG scoring firms based in developed countries are ‘unfairly punishing’ their companies by assigning lower scores compared to those in developed countries. This study investigates and provides empirical evidence supporting this concern. Using panel regression analysis on a comprehensive cross-country sample of 7,904 listed firms from 2002 to 2022 across 50 countries, we find that corporate ESG scores in developing economies are significantly lower than those in developed economies. Further analysis indicates that this disparity is linked to institutional bias and measurement issues within ESG scoring agencies, stemming from information asymmetry. Our empirical evidence also suggests that ESG scoring agencies can mitigate these information problems by incorporating analyst coverage and experience into their algorithms. Thus, the biases affecting the credibility of corporate credit and corporate governance ratings also extend to corporate ESG scores.

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Abstract: This study investigates the relationship between the environmental, social, and governance (ESG)-related skill sets of firms’ directors and ESG performance. Looking at S&P 1500 firms from 2009 to 2022, my analysis does not support the notion that directors' ESG skills enhance firms' ESG performance, and I uncover a trend of "competency washing" among firms. Specifically, when examining ESG dimensions including environmental, human capital, and others, I find no evidence that directors' skill sets contribute to improved corporate ESG performance; such skills may actually lead to worse firm ESG outcomes. However, I do reveal evidence indicating that director skill sets in ESG increase the likelihood of incorporating ESG objectives into CEO contracts. Additionally, when segmenting my sample into S&P 500 firms and those outside the index, I find that firm size matters — directors' ESG skill sets are more influential in affecting CEO contracts within S&P 500 firms.

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Abstract: This study evaluates ESG performance at the country level and its link to economic growth. We ask two main research questions. First, does a country’s economic growth depend on its ESG performance? Second, does a country’s ESG performance depend on its GDP? We consider a range of indicators to evaluate ESG performance based on alternative methodologies to check their robustness. We find that the countries that joined the EU in 2004 or later have weaker ESG performance than Western European countries have; however, the decisive factors are social and governance issues, not environmental issues. These indications are robust in various settings. Further results reveal the existence of Granger causality between ESG performance and economic growth; however, ESG performance is proven to impact economic growth only in the middle to long term.

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Abstract: The main objective of this paper is to fill an identified research gap by examining the relationship between environmental, social and governance (ESG) performance and dividend payouts. We use a panel regression model based on data from companies on the Stoxx Europe 600 Index in 2010-2022. The model incorporates sustainability variables, such as environmental, social and governance pillar scores, alongside the ESG controversies score. The aggregated ESG score has a statistically significant and positive influence on the dividend payout ratio (DPR). When examining particular pillar scores, the impact of the social pillar is both significant and positive, whereas the effects of the other pillars are insignificant. The effect of the ESG controversies score on the DPR is statistically significant and negative. The incorporation of this score into the model does not change the effect of the social pillar score, although it changes the effect of the aggregated ESG score.

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Abstract: The importance of climate risk for business and finance is increasingly recognized in the extant literature. Ginglinger, 2020; Kotz et al., 2024; World Economic Forum, 2024). Task Force on Climate Change-related Financial Disclosures (TCFD) argues that climate change is “one of the most significant, and perhaps most misunderstood, risks that organizations face today” (TCFD, 2017, p.3). A growing body of literature is focusing on the impact of climate vulnerability/climate risk on firm performance and financial decisions. They analyzed the impact of climate vulnerability/climate risk on firm performance (Addoum et al., 2020; Anton, 2021; Cevik and Miryugin, 2023; Huang et al., 2018; Pankratz et al., 2019), cost of equity (Balvers et al., 2017; Huynh et al., 2020), cost of debt (Javadi and Masum, 2021), capital structure (Elnahas et al., 2018; Ginglinger and Moreau, 2019; Zhou and Wu, 2023), cash holdings (Brahmana and Kontesa, 2023; Javardi et al., 2023; Lee et al., 2023; Li et. al, 2024; Yu et al., 2022; Zhang et al., 2023), working capital management (Ahmad et al., 2023), and investment decision (Kanagaretnam et al., 2022). However, empirical evidence on the impact of climate change on firms’ financial decisions is scarce. The paper aims to assess the impact of climate vulnerability (CV) on the dividend policy adopted by European listed firms over the time frame 2010-2021. Employing a panel logit model, it has been found that firms are less likely to pay dividends if they are located in countries more exposed to climate vulnerabilities. I extend the empirical analysis by analyzing the impact of climate vulnerability on the level of dividend payments (measured by dividend payout ratio and dividend yield). The results of the Prais-Winsten regression model with Panel Corrected Standard Errors (PCSE) show that climate vulnerability statistically increases dividend payments. Overall, the empirical results highlight the importance of climate change for the decision-making framework at the firm level.

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Abstract: This study explores the impact of director’s financial expertise on dividend payout ratio, based on 499 listed companies in Vietnam from 2008 to 2019. Using pooled ordinary least square (pooled OLS), fixed effect model (FEM), and generalized least square (GLS) regressions, we find that the financial expertise of director significantly influences dividend payout. We also find a positive relationship between director’s expertise and company’s leverage. These findings suggest a significant nexus between director’s financial expertise and corporate management which includes financing and distributing decisions. Accordingly, we can consider the financial literacy of the board and senior management a factor to evaluate the company’s performance.

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Abstract: On the basis of 460 non-financial public companies from a bank-based economy with the dominant role of bank financing as a source of debt, we find a negative relationship between the shareholdings of motivated institutional investors and the firm’s reliance on bank debt. The observed relation seems to reflect the substitution effect in monitoring insiders between motivated institutional investors (playing the role of minority shareholders) and banks (as debtholders). We find this relationship to hold mostly for transparent companies as they don’t benefit much from disclosing private information to banks and thus can easily replace bank debt with other sources of financing. Furthermore, it holds mostly for companies suffering from substantial agency problems and thus with greater monitoring needs. Moreover, we document that the observed effect is stronger for motivated institutions with higher monitoring effectiveness. Additionally, we show that companies substituting bank monitoring with institutional monitoring experience firm value increase.

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Abstract: The aim of this paper is to examine relationships between ownership structure and the market value of Central European banks from 11 countries between 2007-2021. The ownership structure refers to two elements. Firstly, it is a concentration of ownership, which is taken into account by analyzing the presence of a majority shareholder. Secondly, we consider a shareholder's country of origin. We find that the presence of a majority shareholder is related to the higher market value of banks. We also find a positive relationship between the presence of a foreign shareholder and the market value of banks.

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Abstract: The purpose of this study is to analyze the performance efficiency of Iranian private commercial banks.The study employs Data Envelopment Analysis (DEA) models, specifically the Constant Returns to Scale (CCR) with input orientation and the Variable Returns to Scale (BCC) with input orientation, to scrutinize performance efficiency relative to the banking sector's average efficiency ratio. The findings indicate that the performance of Decision Making Units (DMU) is superior in BCC models when contrasted with CCR models. Nevertheless, given the regulatory framework governed by the Central Bank of Iran, CCR-I was employed for performance estimation. The CCR-I analysis spanning the years 2020 to 2023 reveals that only two banks consistently demonstrated full efficiency performance, attaining a 100% efficiency score across all years. The observed fluctuations in banks' efficiency performance are attributed to disparities between the growth or reduction in inputs and corresponding augmentation or diminution in outputs.

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Abstract: We study risk and performance in banks in the context of boards of Central Europe, boasting a high share of female directors. Our sample covers over 170 commercial banks from 11 post-communist countries between 2007 and 2021. We find that having women on executive boards has important implications for both bank risk and performance. Executive boards with at least two women in the past three years have markedly lower credit risk and less volatile ROA, while reporting a significantly higher levels of ROA and ROE. Banks meeting the gender quota regulations for 40% of female directors in supervisory boards also show lower risk and higher profits, but the effects are smaller and less universal. Banks with 33% female directors in total boards report lower risk that is similar to banks with female executive directors, but the effect on profitability is not visible. Lastly, we also demonstrate that larger boards are associated with lower bank risk, both in terms of general bank stability and credit risk. The size effects do not change our main results on gender diversity.

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Abstract: This comprehensive study explores the historical trajectory of Africa's diverse trade policies and the notable rise of Foreign Bank Presence (FBP). Focusing on 28 African nations from 2000 to 2020, the research utilizes a two-step System Generalized Method of Moments (SGMM) analysis to unveil the positive impact of international trade (INTTRADE) and its merchandise and service components, on Economic Development (ECONSDEV). FBP emerges as a significant positive catalyst for ECONSDEV in Africa, exerting a substantial moderating influence on the relationship between INTTRADE and ECONSDEV, especially notable for merchandise and service trade. The study advocates for policymakers to harness FBP's trade finance services, such as letters of credit and guarantees, to mitigate risks in merchandise trade and leverage currency management services for managing foreign exchange risks associated with service transactions. This strategic use of financial services will contribute to the promotion of economic development through trade.

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Abstract: Over the past few decades, commodity financialization has been trending in financial markets. Initially, institutional investors were not allowed to participate in the Indian commodity futures market. However, from the year 2017, SEBI allowed their participation in the commodity futures markets on Category III AIFs, Portfolio Management Services, and Mutual Funds. Direct participation of foreign traders with exposure to physical commodity markets in India was permitted for hedging purpose. This unique setting in the Indian context allows for testing the impact of financialization on commodity futures markets. Empirical studies show the intricate relationships of financialization and increased correlation between equities and commodities during times of crisis. Therefore, the study aims to investigate the interlinkages between commodity futures and the stock markets, particularly post-SEBI regulation and assess the presence and also contagion effect of financialization in Indian commodity markets.

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Abstract: The study explains the interactions between energy prices and financial stability by analyzing the organization of power and gas derivatives clearing in Europe. Quantitative and qualitative analysis of clearing house’s collateral composition fluctuations, particularly during the 2022 energy crisis, allowed identifying considerable challenges to managing both the liquidity and counterparty risk stemming from the process of commodity clearing. Cointegration techniques were also used to run a sensitivity analysis of the required margin calls and default fund contributions. Findings confirm procyclicality of collateral requirements and the fact that their level may become very problematic to manage by both energy companies, their clearing banks and the central counterparty itself.

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Abstract: Information on firms’ risk management practices (risk disclosures) are vital for investors to make informed decisions, but the manner in which this information is presented can affect its decision-usefulness. This study contributes to the existing discourse by providing empirical evidence on the value relevance of narrative risk disclosures, specifically how narrative complexity, as measured by readability, affects the value relevance of risk disclosures. This study employs panel regression analyses on a sample of 200 companies listed on the Johannesburg Stock Exchange for the time period 2005 to 2022. The findings suggest that readability is an important control variable for decision-usefulness in value relevance studies.

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Abstract: This study examines the effects of mergers and acquisitions on the intangible assets and financial performance of acquiring agribusiness firms based in emerging countries. This study uses data from 25 companies operating in the agriculture industry in emerging countries, covering the period from 2015 to 2020. In order to investigate these effects, this study uses data envelope analysis (DEA) and the Tobit model, along with sample t-tests. The analysis compares the values of intangible assets and the financial performance of firms before and after mergers & acquisitions. The findings of this study reveal insights into how M&A activities influence the intangible assets and financial performance of acquiring agribusinesses in emerging economies. The results reveal a positive change in intangible assets and financial performance after a merger or acquisition. There can be many other strategic advantages to acquiring firms while they acquire or merge their businesses in developed countries.

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Abstract: The article investigates the use of extended tags (extensions) in XBRL based on financial statements of Polish listed companies. It is motivated by concerns that erroneous company-specific extensions to the ESEF taxonomy reduce the transparency of financial reporting, thereby eliminating main benefits of XBRL. Using a sample of 1,356 extensions over the period 2020 to 2022, results show that most extensions were incorrect. The most common errors included creating unauthorized extensions and selecting anchors too wide in accounting meaning. The statistical analysis indicated a significant difference in the number of substantive errors across the three evaluated years. The decreasing trend suggests a consistent improvement in errors reduction over time. This study contributes to the literature by detailed examining extensions that cannot be automatically detected using a dedicated application and addresses the issue of anchoring extensions, a key difference between tagging requirements in the US and the EU.

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Abstract: The main goal of this study is explore the relation between increase in profit shifting value and macro variables such as GDP, the size and income of a country and compare these relations among countries. Before this we re-estimate profit shifting value according to the methods based on the macro approach of UNCTAD (2015a, 2015b) and Janský and Palanský (2019). These studies cover various time frames between 2009 and 2016 and they end in a year when the OECD/G20 Inclusive Framework on Base Erosion and Profit Shifting was initiated. Later the number of countries/ jurisdictions participating in OECD/G20 IF on BEPS has risen from over 60 to over 140. In this study we revise profit shifting methods for a large sample of countries in order to see how much of it there has been in later years and which countries are the most important sources of it.

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Abstract: Appreciating the undeniable role of innovation in productivity and growth, it is crucial to know whether the IP box efficiently impacts R&D or profit-shifting. With a quantitative meta-analysis approach, it checks the effects of IP box implementation on royalties’ payment directions. We study IP box attractiveness for royalties paid from Poland to non-residents as a cost of IP box non-implementing in home countries. Using tax data on over 25,000 payments to non-residents in 2012-2019 applied to the knowledge-capital model, we confirm the IP box policy's higher attractiveness than R&D hubs based on top universities’ knowledge. Thus, it seems justified to implement an IP box to retain IP income in host countries. However, the unexpected effect of IP box implementation is that preferential income taxation wins over competition with higher R&D investment and the quality confirmed by academic ranks.

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Abstract: The paper investigates the banking sector’s profit-shifting scale and determinants in Poland, applying static and dynamic (GMM – General Method of Moments) panel regressions to bank-level administrative tax data of withholding taxed payments to non-residents from 2012 to 2019. We explore tax policy, regulatory, and macroeconomic drivers in banks’ reported profit shifting. We provide insights into how enhanced tax regulation can influence risk management, particularly in regions with developing financial markets. We note that international tax differences cause a geographical distribution of profits, with low-tax jurisdictions attracting disproportionately high profits. This research highlights the critical role of international cooperation in creating a more equitable tax landscape. This article results from a research project financed by the National Centre for Research and Development in Poland GOSPOSTRATEG-I/0029/2021-00 “The monitoring of innovation performance of firms and regulatory impact assessment: developing tools to support economic policy”

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Abstract: This paper aims to identify the determinants, effects and trade-offs of different channels of profit-shifting from Poland. We contribute by exploring a quasi-experimental setting due to the changes in Poland’s withholding tax and ATAD regulations. We use a administrative tax data on passive income payments to 110,907 non-residents from 134 countries. The unique panel data set allows for in-depth analysis of payers’ performance, free cash flow, capex, firm growth, leverage and debt capacity. We prove tightened WHT regulations have reduced passive flows from manufacturers. However, separately transferred interests or royalties increased. On the contrary, services have reduced passive flows due to dividends, interest and royalties to countries that introduced ATAD CFC model A or B in 2018-2019. Although services lose more on performance than manufacturing due to profit-shifting, there are trade-offs as foreign equity injections add to their growth.

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Abstract: We use Propensity Score Matching to explore whether there are differences in amounts of taxes and taxable profits reported by multinational and domestic companies. We find that estimated parameters on the variable measuring the foreign ownership display positive signs and are significant for the sample that includes only firms reporting positive profits in the case of regressions where dependent variables are ratios of taxes and taxable profits to total assets. This means that foreign firms pay higher taxes compared to domestic firms and report higher taxable profits. However, in case of a larger sample that includes also firms that report negative or zero profits the estimated parameter on foreign ownership variable is significant only when the dependent variable is the ratio of taxes to total assets. This means that foreign firms pay higher taxes compared but there are no differences between foreign and domestic firms with respect to taxable profits.

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Abstract: This study investigates the efficiency of green bonds as a financial instrument for promoting renewable energy production, with a specific focus on their performance during the Covid-19 pandemic. Using a sample of 55 countries from 2014 to 2022, we find that green bond issuance positively impacts overall renewable energy generation. However, when examining specific sources of green energy, we find that wind energy benefits the most from green bond financing, while estimates show only marginal significance for hydro energy and no significance for solar energy. Finally, we observe that the efficiency of green bonds diminished during the Covid-19 pandemic, but this effect was not uniform across all energy sources.

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Abstract: During the COVID-19 pandemic, government restrictions caused substantial shifts in travel patterns and population movement. This research examines the relationship between travel behavior and stock market responses across 11 countries, by observing the impact of population mobility on stock market returns and volatility. The Google Community Mobility Index is used to gauge the population mobility to 6 destinations. The daily data are observed during the February 2020 – October 2022. The research finds a noteworthy impact of travel intensity on stock market volatility. Specifically, the results clearly indicate that the level of population mobility has significantly affected the stock market volatility at the industry level. In addition, when considering the stay-at-home restrictions during the severe outbreak period, the results confirm the significant relationship between population mobility and stock market volatility. These findings help investors in the stock market minimize the risks of asset allocation, particularly during the period of market uncertainty.

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Abstract: ABSTRACT This study examined the role of the Big Five personality traits and risk perception profiles among a sample of corporate managers con- cerning their subjective wellbeing (SWB) and corporate management practices during the Covid-19 pandemic. Two hundred and fifty-five chief executive officers (CEOs) and chief financial officers (CFOs) of companies listed on the main market of the Warsaw Stock Exchange (WSE) in Poland participated in the study by completing the Satisfaction with Life Scale, Positive and Negative Affect Scale, Ten-Item Personality Inventory, Stimulation-Instrumental Risk Inventory, and a business survey on the Covid-19 pandemic’s impact on company management. Latent profile analysis revealed the existence of diverse profiles among the participants regarding personality traits and risk perception, which were variously related to their SWB and managerial practices during the pandemic.

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Abstract: This study examines the reallocation of credit to less risky clients by banks across Brazilian municipalities in response to the COVID-19 pandemic, employing a difference-in-differences (DiD) approach. We leverage the heterogeneous timing and intensity of COVID-19's impact on Brazilian cities to establish causality. Additionally, we investigate bank characteristics associated with a more pronounced credit reallocation, including bank size, control structure, and capital indices. Our findings reveal a bank credit portfolio reallocation toward clients in inland cities, where the impact of the Pandemic was less significant when compared with Brazilian state capitals. Branches of inland cities with highly concentrated local credit markets where large banks dominate, and total outstanding credit is relatively underdeveloped had a more pronounced credit shift. Our results evidence that the bank financing channel did not cushion the effects of COVID-19 in the real economy, potentially becoming a pro-cyclical component.

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Abstract: This article analyzes the UK monetary policy operated by the Bank of England to control inflation, with insights applicable to other central banks. It is structured around five main themes. First, it examines empirical evidence on the Bank of England’s success in targeting a 2% inflation rate without detailed regression analysis. Second, it critiques the use of Dynamic Stochastic General Equilibrium (DSGE) models, including VAR model modifications, in understanding monetary transmission mechanisms. Third, it compares the monetary policies of Japan, the EU ECB, and the US within their macroeconomic contexts. Fourth, it critically analyzes the UK's current monetary, fiscal, and financial market policies from both theoretical and empirical perspectives. Finally, it recommends shifting from an inflation-rate targeting policy to one focused on Nominal Gross Domestic Product (NGDP) targeting.

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Abstract: This study aims to examine whether a reserve requirement system constrains bank behavior. In Japan, a system is applied to certain regional banks where required reserve ratios are imposed based on the amount of their deposits. Using a natural experiment, we perform a bunching estimation to examine whether this reserve requirement system decreases bank deposits. To the best of our knowledge, this study is the first to examine the effects of reserve requirement systems through bunching estimation. Our results demonstrate that the reserve deposit system depresses bank deposits, resulting in a decline in total deposits. However, this phenomenon is not observed during periods of unconventional monetary policies. This study highlights an important consideration when discussing changes in the reserve requirement system.

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Abstract: Lending interest rate plays a crucial role in the financial system. However, the recent global economic crises and shocks from monetary policy have destabilized the lending interest rate in the financial markets of most Sub-Saharan Africa (SSA) countries. This paper thus, examines the effect of monetary policy on lending interest rate in SSA by employing the panel vector autoregressive (VAR) model based on a sample of 23 countries in SSA using quarterly panel data for the period 2013Q1 to 2022Q4. The paper finds that monetary policy has a profound effect on lending interest rates in the sub-region. This paper offers valuable insights into how monetary policy shocks translate to lending interest rate in SSA. The paper recommends that, governments and monetary authorities in SSA pursue credible monetary policy to ensure a sound macroeconomic environment in order to boost the activities of the financial sector in the sub-region.

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Abstract: In recent years, new studies have shown that above a certain level, there is a negative relationship between financial development and economic growth. Above that level, finance becomes unsustainable in the sense that it undermines economic growth by increasing the likelihood of a financial crisis. Why do countries ever reach that level? In this article, I draw on a new strand of literature, Law and Macro-Finance, to suggest that countries which incentivize debt investments are more likely to experience financial crises and recessions. That is because debt is cyclical and the failure to mitigate its cyclical impacts is more likely to exacerbate the boom and busts phase of the cycle. The goal of this article is to assess the case for the promotion of an integrated field of Law and Macro-Finance as an area of research looking at the role of debt and its regulation in the cycle.

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Abstract: We examine the volatility spillovers and the time-frequency dependence between crude oil and stock sectors of US and China using wavelet coherence and asymmetric bivariate BEKK GARCH models. We also rely on the effects of the recent global health crisis (COVID-19) on spillover effects and portfolio management. The results show evidence of strong positive co-movements between WTI oil and US sector stock returns at medium and low frequency particularly in 2020Q1. Oil leads the US sector stocks irrespective of frequencies. As for China, we find significant long-term co-movements between oil and Chinese sector stock returns. The lead-lag relationships between oil and Chinese sectors are mixed and frequency-sensitive. More importantly, the results show significant shocks and volatility transmission between oil and sector stock of US and China. The size and the intensity of shocks and volatility transmission is higher during the pandemic than before.

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Abstract: In the paper, we aim to identify and assess the transmission mechanisms of geopolitical uncertainty on the semiconductor sector of the US and Chinese stock markets. First, we propose three different measures of uncertainty based on the three dimensions of price (one-factor Sharpe model), return, and conditional variance of ARMA-GARCH models. We then assess the synchronisation of the US and Chinese markets using moving correlation coefficients. Next, we assess the transmission of geopolitical uncertainty from equity markets to the semiconductor sector. Finally, we analyse the adjustment mechanisms of geopolitical uncertainty transmission to stock market uncertainty using VAR models and Granger causality. In this last step, we also analyse impulse response functions. Our dataset consists of market data of the semiconductor industry in the US and China for the period from 1990 to 2024. We also use the Geopolitical Risk (GPR) index proposed by Caldara and Iacoviello (2021).

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Abstract: The economies of each State are increasingly interconnected and depend on international trade not only for sales markets but above all for the supply of raw materials necessary for the functioning of the production complex of each countries. The intricate set of connections and transactions was put to the test during the conflict between Russia and Ukraine given that these are countries with notable raw materials and strongly dedicated to exports. The BEKK and VECM models were used to analyze whether volatility affects stock markets. The results show that lagged shocks and volatility significantly and positively influence the current conditional volatility of commodities and stock returns during all periods. The Granger causality test shows the presence of cointegration relationships. The findings suggest that the war significantly effected stock prices and exacerbated volatility.

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Abstract: This article examines three groups of indices representing the green economy sector to identify the presence in their quotations of the euphoria phase which is characteristic for price bubbles. The indices were analysed by market type, geographic region and sector. The study was conducted on 31 indices from the NASDAQ OMX Green Economy from September 1, 2005 to April 8, 2024. The dynamic time warping method was used for the analysis. The conclusions include the finding that the green economy market is not currently in the euphoria phase. The COVID-19 pandemic caused 20 out of the 31 analysed indices to enter the euphoria phase, leading to significant increases in green economy indices. Furthermore, the effectiveness of the dynamic time warping method in determining the end of the euphoria phase was demonstrated. The average return 30 days after the end of the euphoria phase was -8.8%.

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Abstract: This paper introduces the concept of newswire tone-overlay, which adjusts traditional commodity signals based on the level of optimism or pessimism in commodity newswires. By implementing the novel tone-overlay allocation strategy on 26 commodities using traditional allocation signals, we demonstrate that the resulting long-short portfolios yield substantial performance gains compared to the corresponding plain-vanilla traditional portfolios. Our findings indicate that newswire tone offers short-term predictive power for commodity futures returns beyond well-known commodity characteristics. The tone-overlay portfolios harness a temporary mispricing that reflects an overreaction of commodity futures prices to commodity-specific newswire tone. The outperformance of the tone overlay strengthens with the salience of the newswire tone, in line with theories of limited investor attention.

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Abstract: Drawing from a comprehensive and unique dataset encompassing both quantitative and qualitative weather risk measures, the study finds that both numerical and textual representations of weather risk can predict future credit risk, expected stock returns, and firm fundamentals. To explore the textual dimension of weather risk, this paper utilizes advanced natural language processing (NLP) techniques, including Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec, and leverages Large Language Model (LLM) such as BERT (Bidirectional Encoder Representations from Transformers). To conduct the empirical analysis, this study utilizes Artificial Intelligence (AI) using TensorFlow/Keras, Deep Learning (DL), and Machine Learning (ML).

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Abstract: We extract firms’ cyber risk with a machine learning algorithm measuring the proximity between their disclosures and a dedicated cyber corpus. Our approach outperforms dictionary methods, uses full disclosure and not devoted-only sections, and generates a cyber risk score uncorrelated with other firms’ characteristics. We find that a portfolio of US-listed stocks in the high cyber risk quantile generates an excess return of 18.72% p.a. Moreover, a long-short cyber risk portfolio has a significant and positive risk premium of 6.93% p.a., robust to all factors’ benchmarks. Finally, using a Bayesian asset pricing method, we show that our cyber risk factor is the essential feature that allows any multi-factor model to price the cross-section of stock returns.

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Abstract: This article performs a comparative analysis of traditional and selective hedging strategies in commodity futures markets. Traditional hedging is aimed solely at reducing the risk of the commodity spot positions, whereas selective hedging additionally pursues economic gains by engaging in speculation based on the hedger’s prediction of the commodity futures return. We construct selective hedges using diverse forecasting approaches that range from the naïve historical average to more sophisticated techniques such as machine learning. The hedging strategies are assessed through the lens of hedging effectiveness based on the expected mean-variance utility of the hedged returns. Out-of-sample results for 24 commodities endorse traditional over selective hedging, as the latter increases risk but fails to generate additional returns. The findings survive various reformulations of the hedges, longer estimation windows, and alternative rebalancing frequencies, inter alia.

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Abstract: This study aims to explore CEO’ personal values and identify the extent to which such values could be crucial to comprehending environmentally sustainable business practices. Based on logistic regression analysis of 139 observations of American companies we provide an novel insight into psychological factors driving a CEO’s behaviour towards environmental performance. We show that the effects of self-transcendent values is not straightforward, with Benevolence showing positive, while Universalism showing negative effects on probability of company to establish environmentally sustainable practices. The positive effect of Self-enhancement values and Openness-to-change values on environmentally sustainable practices is confirmed.

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Abstract: Enterprises that reduce their consumption of raw materials and production of pollution should observe the resulting high degree of environmental efficiency, which is understood as the minimisation of energy and water consumption, carbon dioxide production and waste. High environmental efficiency should translate positively into their financial performance. Our study compares the environmental efficiency of companies listed on the regulated markets of the European Union and its impact on their market value. We use the non-parametric DEA method and the Ohlson Valuation Model to assess the impact of environmental efficiency on companies’ market value. The research sample includes public companies from the 27 EU Member States listed on their respective stock exchanges during the period 2014–2023. Data come from the Refinitiv Eikon database. The research shows that while the surveyed companies cannot be considered environmentally efficient, there is a positive relationship between environmental efficiency and market value.

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Abstract: Achieving net zero is the only way to avoid the irreversible impact of global warming. More firms have recognized the importance of and have declared their commitment to net zero. By estimating the carbon risk premium in a cross-section of 1,100 listed firms that have declared a commitment to net zero as of December 2022 worldwide, we find that after firms declare a net zero commitment, the carbon risk premium may increase or decrease depending on firms’ transition readiness. Institutional investors further divest from high-emitting firms that declare a net zero commitment, channeling carbon risk into stock markets.

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Abstract: This paper examines the impact of green finance development on sustainable economic growth. Using a two-step dynamic System Generalized Methods of Moments for a panel of 54 African countries over the period, 2004 - 2022, we provide interesting empirical findings. Our results show that green financial development has a significantly direct positive effect on sustainable economic growth. We find that stronger institutional quality improves sustainable economic growth. Moreover, the quality of institutions serves as a moderating mechanism through which green financial development affects sustainable economic growth. This paper shows the important policy implications of promoting sustainable growth through green financial development and better institutions in the African economies.

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Abstract: Using extensive transaction and money laundering detection data, at a globally important financial institution, we investigate the efficacy of including aspects of national culture in formulating anti-money laundering predictions. For corporate and individual accounts, Hofstede individualism scores of the country in which a customer is resident, or from which a wire is sent/received, are of first-order importance. When combined with account and transaction data; as well as even a proprietary institutional algorithm, individualism scores continue to determine the models’ predictive performances. Our finding of the efficacy of profiling in AML compliance underscores the need for stringent and enforced data protection safeguards, which can serve to ensure an individual’s fundamental right to privacy.

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Abstract: This paper analyzes the role of the media in shareholder voting on management proposals. Management proposals deal with many critical corporate decisions, and shareholder dissent votes communicate information and have significant consequences for management. The results consistently show that both media coverage and sentiment significantly impact shareholder voting on management proposals. Media is an essential source of information, and shareholders rely more on media when there is more information asymmetry. More media coverage and positive sentiment increase shareholder support for management. Media coverage reduces information asymmetry and allows shareholders to make informed decisions. The instrumental variable approach is used to address the endogeneity issue with media variables.

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Abstract: This paper examines the impact of the power of chief executive officer (CEO) on firms’ environmental sustainability from the lens of waste management, an underexplored but important driver of environmental sustainability. Drawing on the approach/inhibition theory of power, we argue that powerful CEOs are likely to engage in risk-taking behavior and exercise greater control over resources. Therefore, they may prioritize short-term profits over long-term sustainability. By employing data of firms listed in 37 countries from 2002 to 2019, we find that CEO power is positively associated with the level of waste generated, implying that companies with powerful CEOs tend to produce more waste. Further analysis reveals that relationship is more pronounced for firms with low governance quality and those operating in environmentally non-sensitive industries. Our findings are robust to alternative estimation techniques, variable measurement, cross-sectional analyses, and endogeneity tests. This research provides novel insights into the role of CEO power and informs stakeholders, regulators, and policy makers about the impact that powerful CEOs may have on environmental sustainability.

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Abstract: The research was conducted in 35 European countries. The sample selected for the study includes all fundraising in the fintech sector for each of the countries. Annual data from the period between 2013 and 2022 was used. The dependent variable is the total deal size and the independent variables are the sub-indices of the Global Innovation Index (business environment, education, investment, knowledge workers, knowledge impact). The research method used was the panel data model with fixed effects. The results show that the coefficients for knowledge workers, knowledge impact, business environment and education all have a significant negative impact on total deals size in the fintech sector. The limitations of the study is the use of the annual data from the period between 2013 and 2022, and its exclusive focus on Europe.

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Abstract: We examine the effect of short selling on small retail investor's trading behavior and stock liquidity. Employing a unique setting that permits short selling on a selected group of securities (i.e., the pilot stocks) in an economy with heavy participation of retail investors, we document that the pilot stocks experience a significant decrease in trading by small retail investors. We further document that this short selling induced shift in investor participation contributes to the reduction in the liquidity of these stocks. The evidence suggests that the change in investor participation is an important underlying mechanism that short selling affects market quality, which has largely been overlooked in prior empirical literature that focuses on developed markets. Our findings offer empirical support to the classical adverse selection market micro-structure theory of informed short selling (e.g., Glosten and Milgrom, 1985, Easley and O'hara, 2004).

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Abstract: This study aims to provide an analysis of liquidity across a wide range of cryptocurrencies, going beyond well-known assets like Bitcoin and Ethereum to include smaller capitalization and less liquid cryptocurrencies. We examine and compare different methods for estimating liquidity and spread. Traditional liquidity measures, such as those proposed by Corwin & Schultz (2012) and Abdi & Ranaldo (2017), are evaluated alongside machine learning techniques. We use highfrequency data to compute benchmark liquidity measures, which serve as the basis for assessing the accuracy of both traditional and machine learning estimators. In addition, we examine the robustness of these measures during periods of higher market volatility.

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Abstract: We follow McGroarty et al. (2007) and disentangle the bid-ask spread of Bitcoin traded at Bit-stamp against the US dollar into the private information, buy-sell imbalances and price clustering components. We use the transaction data from March 2022 through February 2023 and nest the analysis within the GMM and quantile regression frameworks. We show the impact of the tick size update from USD 0.01 to USD 1.00 on those components, effected in August 2022, and reveal how their shares in the spread vary across the centiles of Bitcoin’s price change distribution.

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Abstract: We investigate whether measuring stock liquidity based on an ordered fuzzy numbers representation of a limit order book allows investors to develop a profitable investment strategy. We examine the data from companies listed in the WSE from 2014 to 2021. We apply several methods commonly used in asset pricing studies to obtain our baseline results and supplement them with a battery of robustness checks. Our strategy which utilises a liquidity measure based on OFNs generates weekly return of 0.184% (0.199%) for equal- (value-) weighted portfolios, which translates into an annual return of 9.568% (10.348%). This return remains positive after adjusting for risk and considering trading costs and short-sales restrictions. The strategy outperforms and generates a Sharpe ratio several times higher than the market buy-and-hold strategy. These results are useful for investors and portfolio managers as they may help them improve their investment strategies.

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Abstract: The 2023 parliamentary elections in Poland were exceptionally competitive. Although the polls were predicting the incumbents’ victory, it was rather uncertain as to which coalition would rule the country in the aftermath of elections. The eventual victory of the opposition parties can be therefore considered as a quasi-random event that allows to test for causal effects of such victory. By employing an event study methodology, this paper examines how an unexpected success of a pro-democratic block or, reversely, an unexpected failure of a populist government is discounted by local stock markets. The results show that the (potential) removal of the populist government in Poland leads to abnormal positive returns at the Warsaw stock exchange. We further complement the short-term results with Bayesian structural time-series models to show how the Warsaw Stock Exchange evolved over a longer time horizon.

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Abstract: The possibility of contemporaneous events hampers inference about differential effects of a quasi-experimental event across firms. We show that this possibility consistently causes high false positive rates in tests of differences in short-term event-driven stock returns -- nearly 50\% at the 1\% significance level in some cases. Clustering standard errors (e.g., by industry) is an inadequate solution. Researchers should instead use the distribution of pre-event return relationships to test for significance. We introduce a novel GLS-based variant of this testing strategy, show that it increases power substantially over OLS-based variants, and provide a Stata module that implements both.

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Abstract: This paper investigates the behavior of stock prices around the ex-dividend date in Europe over the period 2018-2022. In the early months of the COVID-19 pandemic in 2020, an important fraction of firms cut, suspended or reduced their dividend payments, leading to a shortage. We find that the magnitude of abnormal returns around the ex-dividend date is significantly larger during this period compared to regular times as dividend-seeking investors searched for the remaining payers. This pattern is amplified for high-yield dividends and in countries that have imposed a short-selling ban. Our results are consistent with a price pressure explanation and contrast from standard explanations derived in an efficient market framework.

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Abstract: Implementing an event study methodology for the February 2022 Russian invasion of Ukraine and for the October 2023 Hamas attack on Israel, we look at the stock returns of the globe’s largest arms-producing and military services companies. Our analysis finds that these two recent military actions had sharply different impacts upon financial markets. Arms companies averaged ten percentage points of cumulative abnormal returns (CAR) after the Russian invasion but CAR after the Hamas attack was indistinguishable from zero. Given that the Hamas attack was a surprise to nearly everyone, but the Russian attack was the accumulation of a building tension, the results are even more paradoxical, as the anticipated attack had substantial impacts on financial markets while the surprise attack had no apparent impact. We argue that the results can be explained by the reaction of policymakers.

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Abstract: Using 5-minute high-frequency data around the clock, inclusive of trading and non-trading periods, this study is the first to comprehensively examine information bias, leverage effects of asymmetric innovation shocks, and return- and volatility-connectedness between six major developed equity markets and seven leading cryptocurrencies between August 5, 2019, and January 31, 2023. We employ different GARCH- and VAR-based asymmetric and symmetric econometric tools and study all major recent market-stress periods. We find that the leverage effect in equities (cryptocurrencies) is manifested in the pre-Covid (post-Covid) period. Several short-lived, permanent, and transformed long-lived relationships are evident during the sample period, indicating their time-varying behavior. Notably, Germany and ETH (Germany, UK, and TRX) were the main receivers, whereas BAT, EOS, LTC, and BTC (Australia, BAT, and EOS) were the main transmitters of volatility shocks during the full sample (post-Covid) period.

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Abstract: This paper deals with the analysis of inflation in the financial returns by using fractional integration and model-free connectedness methods. Using data from 22 countries from April 1958 to November 2023, we group the countries into highly, medium and lowly correlated returns. The results indicate that 10 countries, among members of G12 are listed among high-medium correlated inflation returns. G7 countries are listed with high-medium inflation returns, of which France, Germany, Italy, and the USA are net shock transmitters, while Canada, Japan and the UK are net shock receivers. Total connectedness indices are positively related to the correlations and the connectedness are found to increase astronomically towards the late 2020 due to economic and financial market integrations. Global financial crisis such as the 2007-2009, and the COVID-19 pandemic have further reset integration of economic variables.

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Abstract: We analyze the connectedness between 96 banks from 25 countries between January 02, 2006, and December 29, 2023. We use a Quantile Autoregression Vector (QVAR) model to estimate the bank stock markets network. Our results reveal that banking markets are closely interconnected across the time and quantiles of the distribution of volatility, especially for extreme quantiles. We identify the markets and banks that offer significant advantages to diversifying risk, and those that transmit the largest spillovers and induce financial contagion within the network in different scenarios. Global Systematically Important Banks are the most connected banks in moderate or low volatility scenarios, and the least connected in high-risk scenarios. US and Japanese banks are the main shocks transmitters in high- volatility quantiles, while banks from emerging countries provide diversification benefits in moderate and low risk scenarios. These results have important implications for investment decision-making and financial stability policies.

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Abstract: From 2020 to 2023, energy markets faced significant upheavals. This study examines the connectedness of oil, coal and natural gas prices during the COVID-19 crisis and Global Energy Crisis (GEC). Using a time-varying VAR model, results indicate that energy markets saw a temporary increase in connectedness during the COVID-19 crisis, with initial asynchronicity between energy prices and connectedness. The GEC saw greater synchronicity between energy prices and connectedness. Oil consistently led in transmitting spillovers, weakening during COVID-19 but strengthening during the GEC. Coal remained a follower throughout. Natural gas spillovers to oil and coal increased during COVID-19 but decreased during the GEC. WTI and Brent crude oil were dominant net transmitters, while the influence of Urals oil diminished significantly during the GEC due to bans on Russian imports. European natural gas benchmarks emerged as net transmitters, unlike other regional price benchmarks which are net recipients.

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Abstract: We explore the impact of research design choices on the profitability of Machine-learning investment strategies. Results from more than a thousand strategies show that considerable variation is induced by methodological choices on strategy returns. The non-standard errors of machine-learning strategies are often higher than the standard errors and remain sizeable even after controlling for some high-impact decisions. While eliminating micro-caps and using value weighted portfolios reduces non-standard errors, their size is still quantitatively comparable to the traditional standard errors.

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Abstract: Using the indicators proposed by Using the Eni Enrico Mattei Foundation, and the Italian network of the Sustainable Development Solutions Network (SDSN Italia) to monitor the 17 sustainable development objectives in the various Italian cities, in this paper we wonder which of these indicators have the greatest impact in determining the price of non-residential properties built in the various Italian provinces. Moreover, as input variables we also considered the crime rate of the Italian provincial capitals, the per capita GDP and the frequency of sales. We used the dataset to train a supervised machine learning algorithm that was able to predict sale prices efficiently and accurately. We then used the trained model and the SHapley Additive exPlanations approach to assess the importance of each variable in the dataset with respect to the sale prices. Finally, we used causal inference to understand how policy measure may affect prices.

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Abstract: This study explores the use of Generative AI, specifically OpenAI’s ChatGPT, for fore- casting the impacts of severe weather events on stock returns. Employing prompts that assess textual weather descriptions, ChatGPT, a powerful generative AI large language model (LLM), provides predictions incorporated into econometric mod- els. Results show that when ChatGPT forecasts negative stock impacts from storms, larger, more profitable firms with lower leverage and higher liquidity experience lower subsequent returns, suggesting investor underreaction to weather risk. Chat- GPT’s predictive abilities are stronger during favorable economic conditions like up- trends, low volatility, and robust employment growth, implying investor underreac- tion amid bullish sentiment.

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Abstract: We propose CTREND, a new trend factor for cryptocurrency returns, which aggregates price and volume information across different time horizons. Using data on more than 3,000 coins, we employ machine learning methods to exploit information from various technical indicators. The resulting signal reliably predicts cryptocurrency returns. The effect cannot be subsumed by known factors and remains robust across different subperiods, market states, and alternative research designs. Moreover, it survives the impact of transaction costs and persists in big and liquid coins. Finally, an asset pricing model incorporating CTREND outperforms competing factor models, providing a superior explanation of cryptocurrency returns.

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Abstract: We study the effect of board gender diversity (BGD) on short sales activity in an international sample of European countries. We find a positive association between short sale activity and the share of female board members. To mitigate causality concerns, we use the mandatory introduction of gender board quotas in European countries as a natural experiment and implement a staggered and stacked difference-in-difference research design. We confirm that the evidence is causal and that BGD positively affects short sale activity. We find that the mechanism that explains why short sellers react to BGD is through liquidity. We further show that cross-sectional heterogeneity in normative acceptance of gender diversity is essential.

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Abstract: The study aims to investigate the effect of the age of the board of directors on firm performance of nonfinancial French firms. Firm performance is measured as a natural logarithm of Tobin’s Q (market-based measure). The sample covers the period from 2005 to 2023. Results of the study indicate that the board of director's age has a significant negative effect on firm performance and this effect is more obvious for firms having more growth opportunities. The results remain unchanged after employing alternative measures of firm performance, namely, market-to-book value of equity. Findings suggest that growing firms need quicker decisions and increasing age is facing major cognitive decline, resulting in delayed decisions and reluctance to make bold decisions that lead to lower firm performance.

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Abstract: The study analyses the glass cliff phenomenon in the Polish capital market, which suggests that poor financial performance increases the risk of departure of female board members. The research sample includes 355 companies listed on the Warsaw Stock Exchange as of the end of 2023, which gives 11,223 individual observations. Our results show that women in financially stronger companies tend to have shorter board tenure than their male counterparts. It contradicts the glass cliff phenomenon. Moreover, the research gives evidence that other factors, such as regulations, company size, and ownership affect the tenure on corporate boards.

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Abstract: The aim of this study is to analyse the link between the national diversity of the board and firm risk. Using the sample of companies listed on stock exchanges in Estonia, Latvia, Lithuania, and Poland we explore the effect of the annexation of Crimea by Russia in 2014 on the national board heterogeneity and the company’s risk over the years 2011 through 2017. In our results, we report that the national diversity of the board has an impact on firm risk. Specifically, higher national board heterogeneity is associated with lower firm risk. Surprisingly, despite initial expectations of increased geopolitical risk, we provide evidence that a company’s risk decreases after the annexation of Crimea. Moreover, we find that this geopolitical event does not affect the relationship between the national diversity of the board and firm risk.

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Abstract: We use a dynamic moral hazard model where a firm’s owner delegates corporate tax strategy to an agent in a setting with random tax inspections. The principal cannot observe gross profits or the agent’s efforts to reduce taxes. Inspections are random and might not occur. Illegal strategies are penalized upon inspection, but the authorities cannot see the evasion amount. The optimal contract includes terminal compensation and a tax reduction strategy. Without inspections, a risk-averse owner avoids contracting if the agent’s effort costs or profit volatility are too high. With inspections, the optimal compensation includes a risk premium for inspection risk and a lump-sum loss contingent on inspection. The tax strategy becomes less aggressive over time as expected penalties increase. Using calibrated U.S. corporate tax data, the model indicates that the agent’s compensation for the tax strategy is 37.8% of the expected benefits.

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Abstract: We study the effect of controlling shareholder on innovation using the data on newly registered trademarks. We find that the effect depends on the nature of controller. Specifically, if the controller is the government, such as in a state-owned enterprise (SOE), controller has negative impact on innovation output. On the other hand, if the controller is a private shareholder, the authoritative power of the controller has positive impact on innovation. We further find that institutional investors mitigate agency cost of innovation in SOEs, however, the role is limited for non-SOEs.

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Abstract: Investors frequently criticise Japanese corporations for excessive cash holdings. On aggregate, cash holdings have increased over time. At the same time, many large-cap Japanese firms' businesses have become more international. However, there is substantial variation in cash holdings between firms and within firms over time. This research examines how international factors influence firms' cash holdings via the precautionary motive, particularly, through overseas sales, foreign ownership and cultural differences between the parent corporation and its overseas affiliates. Random effects within-between regression is used to examine both the relationships within firms over time and between firms in the cross-section. Internationalisation through a higher proportion of overseas sales has a positive relationship with cash holdings, but a greater proportion of foreign shareholders is associated with lower cash holdings within firms over time. The relationship between cash holdings and cultural heterogeneity is dominated by positive within-firm effects.

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Abstract: In recent years, the rule of law has become increasingly important, particularly in the European Union. The EU has even implemented the rule of law conditionality regulation. State-owned enterprises have also grown in importance. Since the Great Financial Crisis, the term "state capitalism" has regained popularity. Some scholars believe that there is a link between state-owned enterprise decisions and country-level rule of law. We have addressed this issue in the context of corporate investment. We conducted our analyses on a sample of 302 matched companies operating in the EU between 2014 and 2021 (2,096 observations). Our findings indicate that the higher the level of rule of law in a country, the more companies invest. We find no correlation between state shareholder ownership and corporate investment rates. Furthermore, we discover no evidence that the rule of law moderates the relationship between the state-owner and investment rates.

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Abstract: Various studies highlight negative effects of dominant market players and high market concentration, yet these effects on the financial market have been largely unexplored. This study focuses on market dominance in the European ETF market. Using monthly data from 2008–2018 on 350 ETFs (more than 70% of the entire ETF market) we examine the influence of market power and concentration of individual funds on financial outcomes (expense ratio, tracking error, premium). Our findings reveal that while higher market power of an ETF provider is associated with an increase in total expense ratio, greater market concentration leads to a decrease in tracking error. These results underscore the trade-offs present in financial markets, where market dominance results in higher costs for investors but also greater efficiency in tracking performance. Our study makes a significant contribution to understanding of how market structure impacts financial innovation and investor outcomes in ETF market.

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Abstract: This research significantly enhances our understanding of the role of green energy ETFs in portfolio optimization. It provides practical insights into the advantages and disadvantages of diversifying into green assets. The study utilizes a TVP-VAR model and multivariate portfolio techniques to analyze risk contagion between traditional stocks and green energy ETFs and assess hedging efficacy. Spanning from January 17, 2020, to March 28, 2024, the research updates knowledge in three geographical areas – China, the European Union, and the United States and examines the connectedness between green and energy ETFs markets and conventional stocks. Our findings show that using multivariate portfolio techniques in the ETF market can help reduce investment risk. Additionally, the study sheds light on how changes in information transmission between energy and green energy ETFs and traditional equities affect the market. These insights can be valuable for investors looking to navigate the renewable energy sector.

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Abstract: Drawing on an extensive analysis of 2,386 research papers, this study elucidates the primary themes prevalent in past studies on venture capital and private equity. Our comprehensive analysis of a significant number of papers facilitates a quantitative analysis yielding fundamental metrics such as citation scores, influential authors, and seminal publications. By combining both bibliometric and bibliographic methodologies, our paper provides an integrate overview of findings from diverse studies, unveiling predominant themes in the discourse on venture capital and private equity. Augmented by insights into financial market innovations sourced from pertinent literature, we extrapolate future research directions in these domains. The implications of our results extend to borrowers, lenders, and stakeholders within the venture capital and private equity landscape, offering insights for informed decision-making and strategic planning.

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Abstract: We examine the American, European, Japanese, Chinese and Polish stock markets. We show that the forecasted, formed portfolios of a representative investor of the mutual fund market generate returns in light of the Merton’s ICAPM, and the use of fundamental analysis does not allow for obtaining above-average returns. We also present that the structure of past long-term financial results can be modeled by the proposed fundamental functional FUN. We express the presumption that the average returns on the U.S. markets since 2007, and in European market since 2010 are in line with the ICAPM, which confirms the market efficiency. This can be a significant indication, especially for investment fund managers. We conclude that returns on the Japanese and Chinese markets do not confirm the efficiency of these markets.

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Abstract: Motivated by the increasing prominence of cryptocurrencies and their potential impact on traditional and renewable energy assets, this research aims to uncover the extent and nature of Bitcoin's influence on these critical financial sectors. The study employs various advanced analytical methods, including Vector Autoregression (VAR), Dynamic Time Warping (DTW), and Random Forest (RF) to analyze the relationships and predict future returns. The findings indicate that Bitcoin exhibits high volatility and distinct market behavior compared to gold and clean energy assets, with moderate correlations particularly observed with solar and wind energy. The VAR and RF models demonstrate effectiveness in capturing general trends during stable periods but struggle with high volatility, highlighting the challenges in forecasting Bitcoin's returns. DTW results show that Bitcoin has the closest temporal alignment with solar energy, suggesting some interconnectedness driven by broader market trends.

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Abstract: The ongoing interest on exposing the predictive components in returns, the necessity for absolute accuracy and reliability in forecasting along with the impressive advancement in computing power, have transferred the attention in the use of machine learning techniques for forecasting purposes. However, studies on the field are yet to include pure finance predictors when forecasting returns through AI. Our research tries to cover this gap by employing both the simple and the modified versions of the most well-known predictors. Our analysis goes a step further by integrating additional predictors, that is combining behavioral and stress indexes with the basic dividend-price ratio and earnings-price ratio, grounded in the long-run equilibrium relationships present in the examined variables. Our data set focuses on the S&P 500 index. Our key findings include the forecasting superiority of the modified ratios in all forecasting horizons, regardless of the methodological route followed.

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Abstract: Business finance, and common language dictionaries with sentiment directionality as collection of 92000+ keywords are used to acquire 1150 random keywords (575 positive, 575 negative) to retrieve 10 years of Google SVI per keyword. Sorting by Google Search results, top 50 timeseries are forecasted 6 months using Seasonal Naïve. We produce a sentiment index based on historical and forecasted data, to be used as an exogenous predictor to the forecasting of stock returns of 500 randomly selected US stocks from various industries. We utilize NBEATS based deep neural architecture and LSTM based recurring neural network along with endogenous technical variables, and further categorize stocks by characteristics, and generate two sub-portfolios–large, old, profitable, and dividend-yielding firms versus small, young, unprofitable, and non-dividend yielding firms–to find the former sub-portfolio with more accurate forecast, while latter to be more statistically significant, with aforementioned sentiment index.

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Abstract: This paper introduces an advanced asset pricing model employing the Mixed Data Sampling (MIDAS) methodology to integrate high-frequency and low-frequency data for more precise market analysis. The model leverages daily and monthly data on stock returns, and economic variables to enhance predictive accuracy. Preliminary findings suggest that the MIDAS approach significantly improves the explanatory power for asset returns, capturing both short-term market fluctuations and long-term economic trends. This innovative model provides a dual perspective that can better inform risk assessment and portfolio management strategies, potentially transforming traditional asset pricing methods.

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Abstract: This paper focus on advances to legal and regulatory challenges in the digital insurance era, focusing on the UK insurance industry, with developments of the regulatory environment and prudential supervision. It presents a critical analysis of existing supervisory practices from the PRA for the UK re-insurance sector, inclusive of the Lloyd’s of London. The aim of this analysis performed is to comment on gaps identified from the latest PRA’s approach to insurance supervision and the New Insurer Start-Up Unit Guide. Overall, this research examines the approach and practices of UK regulators towards the prudent supervision of insurance startups and insuretchs. It describes their evolution, differing characteristics with proposals for future developments to ensure their sound prudential risk management. The ultimate aim of this research is to provide insights to the insurance practice, adding to the literature about enhancements to prudential regulation.

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Abstract: The regulatory and legal responses to the major accounting fraud that have occurred in the world's major economies have been addressed by various authors. However, the experience from the perspective of the social reality protagonists of an emerging economy country in Latin America, which has experienced similar situations related to cases of fraud with high public impact, as is the case of Chile, is not yet known. The research tries to understand the preparation level that the country has to effectively deter corporate frauds, and to know if the experience of the European Union can be a reference to face this problem. Exploratory qualitative study with a phenomenological design structured on the basis of in-depth interviews with key informants from the legal and academic fields, with experience mainly in criminal law, civil law and Chilean and comparative European administrative law.

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Abstract: Firms that adopt a ‘code of ethics’ targeted towards senior financial officers (CEFO firms) in response to SOX Act Section 406 have higher valuations (Tobin’s q) than a matched sample of firms of similar size, operating in the same industry that have not yet adopted such a code of ethics (non-CEFO firms). Tracing the mechanism, higher valuations for CEFO firms result from both low risk-adjusted rates and higher cash flows. In turn, higher cash flows for CEFO firms result from increased profitability and lower compliance costs. CEFO firms also benefit from a lower probability of shareholder disputes and shareholder concerns. These results are consistent with models of integrity that predict that firms’ commitment to ethical behavior is associated with better performance.

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Abstract: Improving information transparency and monitoring corporate commercial activities are the core content of commercial reform, which is conducive to creating a good commercial environment and promoting high-quality economic development. Over the past decade, the Chinese government implemented a series of digital technologies to accelerate the process of commercial reform. To explore its economic effectiveness, we examine how it impacts firms’ stock price crash risk. We find that the commercial reform that applies digital technologies mitigates stock price crash risk and achieves so via enhancing information quality and monitoring for firms. This finding is more prominent for firms with higher levels of digitalization and innovation and those with weaker internal governance. Overall, our findings highlight a potential benefit of applying digital technologies to regulatory reform, encouraging governments to adopt digital tools to improve information environments and monitoring for firms, and thereby promoting a more stable and efficient capital market.

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Abstract: Antoniou et al. (2016) introduced investor sentiment into the analysis of the beta-return relationship, to examine the linear upward-sloping relationship predicted by the CAPM. Their U.S.-focused study showed low beta stocks outperform high beta stocks during optimistic periods and the reverse during pessimistic periods. The purpose of our research is to extend this analysis globally, to explore the impact of temperature and latitude on investor sentiment, beta, and stock returns. Our findings reveal that globally, beta-sorted portfolios show a smaller, statistically insignificant performance gap between low and high-beta stocks, differing from U.S.-based models. We found the significant influence of beta on stock returns was less evident. While considering temperature, we found high temperatures boosted stock returns in warm-climate countries during optimistic periods, while low temperatures negatively affected stock returns in cool-climate countries during pessimistic periods.

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Abstract: The Russia-Ukraine war is still ongoing at full intensity, but it can already be estimated that the economic consequences of the conflict on Russian investors are staggering. From October 2021 to the end of March 2022, as geopolitical tensions intensified and the specter of war loomed large, the Russian stock market witnessed a loss exceeding 80% of its value. Despite the global trend of diminishing home bias among investors in recent decades, Russian equity investors have steadfastly maintained a predominantly local investment focus. In this study, we present evidence of the substantial escalation in the cost of home bias for Russian investors in the wake of the recent war with Ukraine. This case should serve as a warning to other countries' investors, private as well as institutional with under diversified portfolios.

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Abstract: The present study examines the contribution of the analysts to the Idiosyncratic Volatility (IVOL) effect. It finds that the negative IVOL effect is more prominent in the stocks covered by the analysts than in the non-covered stocks, as the high IVOL stocks attract favorable recommendations. The simultaneous impact of consensus recommendations and IVOL on the subsequent returns is negative. Furthermore, the favorable recommendations for high IVOL stocks are prominently visible when the firm size is small. Institutional ownership and market sentiment do not significantly impact the analysts' recommendations for high IVOL stocks. The analyst recommendations continue to be optimistically biased towards IVOL stocks over a period of time. Thus, it can be inferred that the favorable analyst recommendations contribute toward negative IVOL spread. The findings draw attention to the inefficient information dissemination by the analysts.

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Abstract: The objective of the article is to calculate Conditional Drawdown-at-Risk Beta and Expected Regret of Drawdown Beta, accounting for the drawdowns of the STOXX Europe 600 index in the period 2014-2023. These drawdown betas show the impact of unprecedented events of the COVID-19 crisis, the Russian invasion of Ukraine, and the Israeli-Palestinian conflict. Similar to the standard beta, the drawdown betas relate the expected return of an asset to the expected return of the market, but are based on the concept of drawdown (decline in the value from a peak to a subsequent low). The numerical results show that drawdown betas are sensitive to market distress during unexpected events. The drawdown betas may have negative values and work as safe-haven assets for investors during financial crises, while the standard beta is positive. We provide a case study demonstrating the approach for European markets.

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Abstract: Green finance is crucial in combating environmental degradation, yet the diversity in national policies is often overlooked. This paper compares green finance initiatives in Poland and Uzbekistan, examining policy adaptation and efficiency in Central and Eastern Europe and Central Asia. Through qualitative coding and thematic analysis of policy documents, articles, and reports, the study identifies key similarities and differences. Using policy diffusion and entrepreneurship ecosystems as conceptual frameworks, it reveals that both nations, despite varying economic development stages, are transitioning from fossil fuels to renewables. They employ diverse financial instruments tailored to their unique challenges. The study highlights differing stakeholder involvement and suggests that specialized tools like blue bonds could enhance water resource management. Understanding policy diffusion and entrepreneurial ecosystem restructuring is essential for effective green finance initiatives.

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Abstract: This paper explores the relationship between microfinance and economic development using a cross-country dataset of 60 developing countries for the period 2000-2018. We employ the Panel VAR model, estimated by the generalized method of moments (GMM). Microfinance institution (MFI) indicators are categorized into social performance variables and financial performance variables. Social performance variables include the number of clients (NOB) and the percentage of women borrowers (PFB), while financial performance indicators consist of the portfolio at risk (PAR), operational self-sufficiency (OSS), and operating expenses (OPX). Economic development is assessed using the HDI, which integrates economic indicators like GNI with social indicators such as life expectancy at birth (LE) and educational attainment (EDI). Our findings indicate that social performance variables positively influence economic development, and shocks to financial performance variables significantly impact the HDI. Additionally, our results confirm the existence of a Granger causal relationship.

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Abstract: More researchers have emphasized the importance of financial literacy and personal finance education, including researchers in South Africa; however, it is a struggle to find public higher education institutions and basic education institutions that offer personal financial management as part of their curriculum. The question is where and how can the students acquire the knowledge and skill to effectively manage their financial affairs for the betterment of the quality of their lives, let alone guiding and nurturing the implementation of that knowledge. Literature reviews and researchers have focused on individual aspects of financial management education and financial literacy. As a result, the three necessary spheres, namely, financial literacy, financial intelligence, and self-efficacy, have been neglected. It is the intention of this study to narrow that gap.

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Abstract: Since around 1980, a growing importance of financial markets has been observed in many OECD countries. In recent decades, the share of the value added by the financial sector as the percentage of GDP increased in some countries. Moreover, during the same period, it was observed that non-financial enterprises increasingly became intertwined with financial markets. Some scholars refer to these phenomena as the process of financialisation and, within this framework, study the consequences of the development of financial markets. The aim of this paper is to research the relationship between financialisation and income inequality in OECD countries. Income inequality, as measured by the Gini coefficient or income share held by the top 1%, has worsened in many OECD countries in the last four decades. Preliminary results support the hypothesis that financialisation has contributed to an increase in income inequality in in selected high-income OECD countries.

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Abstract: We used actual risk-taking behavior demonstrated by real financial market participants as a measure of risk aversion and examine the link between risk aversion and demand for non-life insurance in three contextual settings: when economy is functioning normally; when economy is impaired and 3) when negative market condition is witnessed. We used initial dataset of thirty-three OECD countries over the period from 2007 to 2016 and employ bias-corrected bootstrapping technique to create a big dataset with 11,731 observations. We argue that big dataset derived from bias-corrected bootstrapping technique will generate unbiased and efficient regression estimates. We found that when economy is functioning normally, risk averse individuals/corporations will seek non-life insurance to cushion themselves from transactions and bankruptcy costs. Our results also showed that in the event of economic impairment, individuals’ confidence in the financial system will decline making them seek private arrangements.

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Abstract: Micro-takaful programs aim to support marginalized B40 populations, but they have struggled to reach low-income groups, including asnaf. Government limitations may hinder the provision of free micro-takaful. This study explores the potential of using zakat funds to finance micro-takaful programs and provide protection for asnaf. The research conducted in the Petaling District revealed that takaful operators are generally receptive to the idea of zakat-based micro-takaful. While existing offerings are satisfactory, they may fall short of fully addressing asnaf needs. Potential concerns exist regarding the integration of zakat and micro-takaful. The study suggests that collaboration between takaful operators, zakat institutions, and stakeholders like the government is crucial for successful implementation. Zakat-based micro-takaful has the potential to provide significant financial protection to the asnaf community.

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Abstract: This study examines households' digital-euro adoption process in the euro area. It adopts a novel and simple approach to estimate the upper bounds of the short-term adoption rate in the euro area. The model indicates that, in the best-case scenario, the maximum retail digital euro’s adoption rate at the euro-area level is less than 4% of the euro area banks’ total liabilities and approximately 17% of its quarterly GDP. The findings are critical for the domain as policymakers could use them to adjust their impact studies over the banking sector. Additionally, this study proposes a new hypothesis regarding the parity of funding sources for digital-euro accounts (cash reserves to deposits ratio). It concludes that the impact on the euro area's financial stability would be slightly less significant than what is quantified in the existing specialized literature.

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Abstract: This paper investigates the impact of global financial risk on uncovered interest parity (UIP) premia in four Central and Eastern European (CEE) economies. Building on recent developments in the measurement of global financial risk, the study employs local projections that incorporate both external factors and local macroeconomic conditions. We find that global risk-on/risk-off shocks have positive, economically significant, but temporary effects on UIP premia in CEE economies. These effects typically exhibit peak-and-trough patterns, with some variation across countries, and are more pronounced for currency excess returns versus the US dollar than the euro. Importantly, we demonstrate that the transmission of global risk to UIP premia in CEE countries is primarily driven by adjustments in exchange rates rather than shifts in interest rate differentials. We interpret our findings using insights from an imperfect financial markets framework in the context of vulnerable economies.

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Abstract: Given the rising use of the US dollar in international trade, this paper examines how dollar financing affects firms’ trade behaviors from the perspective of cross-currency basis (CCB), a country-specific indicator of dollar borrowing cost for firms outside the United States. Using a multi-dimensional fixed effect model and two Bartik-like instrument identifications, I utilise the disaggregated firm level trade data from Chile between 2009 and 2022, and find that easier ac- cess to dollar liquidity increases both firms’ imports and exports, highlighting the important role that dollar liquidity plays in shaping firms’ trading behaviors after the global financial crisis. When probing further, I find that CCB works as a better dollar liquidity indicator than the intensively studied broad dollar index. An additional analysis with China echoes the finding from Chile, providing further evidence on the effect of dollar liquidity on trade beyond the scope of Chile.

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Abstract: In this research I analyze the influence of retail financial markets on the development of financial sector on the data for 39 countries for the period 1990–2018. To measure retail markets development a composite indicator is constructed. Then this indicator is included in the models of the size of non-retail financial markets. The results show that, on the one hand, development of retail markets (households credit market, life insurance market and private pension funds) stimulates the development of non-retail financial markets (corporate lending market, stock market and non-life insurance market) as they have a role of resources of funds. On the other hand, overheating of retail credit market has a negative impact on the stability of the banking sector and subsequently leads to a reduction of corporate credit market. At the same time, excessively rapid growth of life insurance market may hinder development of other segments.

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Abstract: The phenomenon of unsustainable public debt among African countries in recent years has kindled significant interest among policymakers, researchers, and governments in prudent financial and debt management strategies. This study seeks to find out how cross‐country effective public debt policy and the quality of budgetary and financial management systems influence the accumulation of public debt among African countries. The generalized method of moments estimation technique was deployed. The study depended on secondary annual data spanning from 2005 to 2022 for 36 countries in Africa. The study found that improvement in the CPIA debt policy rating index will reduce public debt percentage of GDP among African countries. Also, improvement in the CPIA quality of budgetary and financial management rating index will reduce public debt percentage of GDP among African countries. The study recommends that African states comprehensively institutionalise public debt management frameworks, and adequately implement these frameworks to the latter.

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Abstract: The growing global concern about climate change has spurred scholars and policymakers to investigate the intricate relationship between economic activity and environmental impacts. This study, which uses carbon emission (CO2) aims to explore the connection between gross domestic product (GDP), export growth (EG), and real interest rates (INT) in Malaysia. The study employs Autoregressive Distributed Lag (ARDL) regression to analyze 1988–2018 data. The analysis reveals a positive and significant link between gross domestic product (GDP) and CO2 emissions in both the long and short run. In contrast, real interest rates (INT) did not show any significance in the long run but negatively affected CO2 emissions in the short run, while export growth (XG) did not show any significance in the long and short run. These findings enrich the academic understanding of the issue and have significant implications for policy-making, particularly for the central bank in formulating monetary policy.

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Abstract: We present a novel framework for modeling credit risk frictions in syndicated lending through options, focusing extending a regime change model. Departing from the seminal Merton model, we utilize an approach based on barrier option formulae to analyse the effects of borrower risk-shifting behavior. We introduce a bond with regime change possibilities when a barrier is crossed. Risk-shifting is identified when the value of the loan crosses a predefined threshold relative to its initial borrowing value. Our sensitivity analysis, conducted on stylized syndicated loans, reveals that lead lenders have incentives to deter risk-shifting by the borrower, particularly through dividend distributions, as such behavior may jeopardize future collaborations. Additionally, our findings framework indicate that the vigilance of the lead bank in monitoring syndicated loans tends to increase with loan maturity and volatility.

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Abstract: We derive the explicit price of a perpetual American put option that is cancelled at the last passage time of the underlying asset above a fixed level. The asset's price follows a geometric spectrally negative Lévy process. We demonstrate that the optimal exercise time occurs when the asset price first falls below a certain optimal threshold. Additionally, we discuss potential extensions to this model, such as options cancelled at the first passage of the drawdown process, and introduce a modified Least Squares Monte Carlo method for pricing general time-capped options.

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Abstract: The evolving risk landscape presents significant challenges for both private and public entities. Traditional risk sharing is defined by the relationship between policyholder and insurance companies. However, emerging risks such as climate change and cyber threats, along with increasingly severe events, are now additionally being underwritten by the capital markets. In these cases, (re)insurers or brokers often hedge their risks through catastrophe or cyber bonds. Therefore, a characteristic of this market is that it primarily involves tail risks. Due to their uncorrelated nature with capital market risks, these alternative investment products offer attractive portfolio diversification opportunities and high returns, which traditional pricing and factor models cannot adequately explain. This study presents a comprehensive pricing model for various societal risks. By applying the model to real-world data, such as hurricane losses and cyber risks, it proves effective in determining accurate market prices. The study places particular emphasis on pricing...

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Abstract: Implied volatility is quoted by market makers for OTC foreign exchange options. It builds a volatility surface that allows pricing of all vanilla contracts. The paper presents a model that explains implied volatility changes in three dimensions: as a volatility level, a slope of the volatility curve and a slope of the volatility smile. The long term time series from the EUR/PLN market are used to calibrate the model. The evidence shows a tight interdependence between prices of option strategies. The interdependence can be used to build error correction models based on cointegration of time series. In the models ATM volatility is explained by spot returns and historical standard deviation. Moreover the shape of volatility curve and volatility smile are explained by the level of ATM volatility. The models have significant forecasting value quantified as a directional quality measure. The error correction component improves a correctness of forecasting decisions.