Research in International Business and Finance最新文献

This study provides a comprehensive analysis of the relationship between fan tokens and equities as investment vehicles in football clubs. Using the GO-GARCH methodology to account for time-varying higher-order co-moments, we examine the risk-return characteristics of these assets in different portfolio contexts over the period November 2021-March 2023. Our results show high diversification opportunities between fan tokens and equities, especially with investments in different leagues. Portfolio analysis shows that equities generally outperform fan tokens as an investment vehicle, highlighting the importance of active portfolio management. The study also shows that equities have broader diversification potential than fan tokens when added to a portfolio. Furthermore, Turkish fan tokens have better characteristics than Italian fan tokens, possibly due to the nonfinancial benefits for investors. The results are relevant for both retail and institutional investors, regardless of their risk tolerance profiles.

We investigate the effectiveness of hedge fund activism in addressing inefficient R&D investment and creating long-term value at target firms. Using an endogenous growth model to estimate efficient R&D investment levels, we find target firms exhibit a tendency to overinvest in R&D. The likelihood of being targeted and activism announcement returns increase with R&D overinvestment. Despite observable cuts in R&D expenditure following activism, our analysis shows no significant improvement in R&D efficiency over the subsequent three years. Additional tests, controlling for the activist’s objectives, reputation, and stock selection ability, reveal a negative impact of activism on value creation. Our study offers important insights into how hedge fund activism shapes corporate R&D strategies and highlights challenges in achieving sustainable innovation and value enhancement through activist interventions.

Our study employs network analysis to examine the interconnectedness in the Foreign Exchange market, focusing on 18 key currencies from both advanced and emerging markets from 2017 to 2023. This analysis includes a comparative look at the impact of two major recent crises: the COVID–19 pandemic and the Russia-Ukraine war. The latter is notably marked by increased inflation and uncertainty in economic policies. During the COVID–19 pandemic, we observed a significant level of interconnectedness among the EURO and 17 other currencies, indicating a dense network. In contrast, the period of the Russia-Ukraine war revealed a tendency for countries less engaged in international trade to become more isolated, as seen by their greater distance from the network's centroid. Additionally, we developed the Systemic Contagion Index, which shows a heightened susceptibility to contagion among developed economies during both the COVID–19 and Russia-Ukraine war crises, underscoring the vulnerability of developed countries' currency networks in times of turmoil. This study provides valuable insights for investors and global businesses, offering guidance on assessing currency vulnerability and enhancing their strategies for hedging and managing risks amidst fluctuating market conditions, especially during the high inflation regime.

We investigate the flow-performance relationship by the lens of the investor preferences, applying a mutual fund dataset with an investment objective focused over European and US area. Incorporating a novel measure of asset managers’ market timing ability, we analyze the role played by performance persistence in mutual fund investing decisions by focusing on top performers in a short-time window. Our empirical results showed that preferences strongly influence the returns-flow dynamics when accounting for the asset type, geographical investment focus, and management style tilt, shedding new light on the behavior of certain clustered groups of investors. Furthermore, we find a long-run information effect as a proxy of a positive association between past returns and flows leading by the smart money effect. Surprisingly, we also observe irrational investors’ behavior when chasing for negative performers, likely due to a herding effect or flow persistent hypothesis as a result of the mechanisms of market allocation efficiency, which is likely to be affected by a slowdown functioning in the short-term phase. Robustness analyses confirm overall results.

In this study, we leverage unique, hand-collected data to explore the impact of staggered boards on the likelihood of future stock price crashes. Our analysis shows that companies with staggered boards are at a higher risk of future stock price crashes compared to their counterparts with non-staggered boards, particularly in firms with elevated agency costs and those not state-owned. Additionally, we find that staggered boards exacerbate this risk by failing in their monitoring and advisory capacities. Evidence of this failure emerges through various indicators of diminished oversight, including managerial opportunism, financial reporting manipulation, insider trading, and a rise in both investment and operational inefficiencies. This study not only contributes to the ongoing debate about the implications of staggered boards but also sheds new light on the associated agency costs.

We develop several innovations to bring the best practices of traditional investment funds to the blockchain landscape. Specifically, we illustrate how: (1) fund prices can be updated regularly like mutual funds; (2) performance fees can be charged like hedge funds; (3) mutually hedged blockchain investment funds can operate with investor protection schemes, such as high water marks; and (4) measures to offset trading related slippage costs when redemptions happen. Using our concepts – and blockchain technology – traditional funds can calculate performance fees in a simplified manner and alleviate several operational issues. Blockchain can solve many problems for traditional finance, while tried and tested wealth management techniques can benefit decentralization, speeding its adoption. We provide detailed steps – including mathematical formulations and instructive pointers – to implement these ideas and discuss how our designs overcome several blockchain bottlenecks, making smart contracts smarter. We provide numerical illustrations of several scenarios related to our mechanisms.

Based on the “double random” inspection system implemented by the China Securities Regulatory Commission (CSRC) on accounting firms, our study uses staggered DID method to examine the effect of administrative audit regulation on the quality of corporate accounting information. The results suggest: (1) The administrative audit regulation can effectively improve corporate accounting information quality; (2) The mechanism test reveals that the administrative audit regulation improves the quality of accounting information by improving internal control; (3) Further study reveals that the governance effect of the administrative audit regulation is more pronounced for firms with non-Big four auditing, high risk of misstatement and more agency costs. Our study investigates the governance effect of the CSRC’s random inspection system on the quality of corporate accounting information, providing theoretical and empirical evidence for the effectiveness of administrative audit supervision from the perspective of corporate accounting information system.

This study examines why split bond ratings occur between credit rating agencies with different reputations in Japan. Using a sample of Japanese corporate bonds newly issued during the 2006–2021 period, I find that the ratings assigned by a less reputable Japanese rating agency (JCR) are significantly higher than those by a more reputable Japanese rating agency (R&I) for the same bonds because JCR is likely to rate the creditworthiness of bond issuers more highly than R&I. The disagreement between JCR and R&I over the creditworthiness of issuers causes split bond ratings. Moreover, bonds with multiple split ratings have higher yield spreads.

This paper adopts a versatile conditional correlation approach to explore daily seasonality in the major cryptocurrencies. Given the lack of clear fundamental value in this market and the active online profile of investors, the study also relates cryptocurrency cross-correlations to online market attention and sentiment. Our results highlight that while investor attention has a positive effect, sentiment has a much stronger negative impact on the correlations. These findings can offer interesting insights for investors and regulators, as the influence of market attention and sentiment on the correlations has important implications for portfolio diversification and market stability.

Existing studies on the impact of social media on the information efficiency of capital markets have opposing views. One often-overlooked aspect in these studies is the role of investor interaction, a core feature of social media. To address this gap, we employ social network analysis (SNA) to investigate how investor interactions on Eastmoney, China's largest online stock forum, influence capital market efficiency. Our findings indicate that online investor communication can effectively disseminate firm-specific information through social networks when investor interactions are at a moderate level. However, beyond a certain threshold, heightened interactions contribute to market noise, thereby distorting the stock price discovery process. Our mechanistic analysis reveals that increased investor interactions stimulate irrational emotions at both market and stock levels, ultimately impairing capital market efficiency. This study contributes to social network analysis and behavioral finance by illuminating the impact of online social interactions among retail investors on capital market information efficiency.