International Review of Finance最新文献

In this study, we construct a directional global financial network using portfolio investment data from more than 200 countries during the first two decades of the 21st century and analyze the properties of the network. Through macroscopic analysis, we show that the network became denser and could be divided into central and peripheral groups. Microscopic analysis shows that, in addition to well-known financial-central countries, relatively less well-known countries played important roles in the global financial network. Further, each country's per capita GDP is positively correlated with its centrality in the network, and the correlation is stronger when measured with inbound investments than when measured with outbound investments.

In a standard continuous time asset pricing model, this paper provides an explosion time characterization of asset price bubbles that extends the existing characterization theorems in the literature from diffusion processes to general semimartingales (which can include jumps). This characterization has a nice economic interpretation, not emphasized in the existing literature.

This study examines the association between institutional investors' corporate site visits (CSVs) and the visited firms' investment efficiency. Using unique CSVs' data from China, this study provides empirical evidence that institutional investors' CSVs lessen the visited firms' corporate investment inefficiency, including both over- and underinvestment. The negative relationship between CSVs and investment inefficiency is less pronounced for firms with higher quality financial reporting and better corporate governance. In addition, CSVs show a decrease in corporate overinvestment by monitoring the risk-taking activities of younger CEOs and expansionary firms, and supervising the use of excess free cash flows. Meanwhile, CSVs could mitigate underinvestment by reducing managerial shirking from entrenched CEOs, such as dual or longer-tenured CEOs. The possible economic mechanism behind this association is that CSVs increase institutional shareholding percentages. All the main findings are robust to a battery of endogeneity and robustness tests.

This paper studies the predictive power of the trend strategy in the international stock market. Using data from 49 markets, we find that a trend signal exploiting the short-, intermediate-, and long-term price information can predict stock returns cross-sectionally in the international market. The significance of the trend strategy is associated with market-level characteristics such as macroeconomic conditions, culture, and the information environment. The trend premium is more pronounced in markets with a more advanced macroeconomic status, a higher level of information uncertainty and individualism, and better accessibility to foreign investors. Nevertheless, the trend strategy only outperforms the momentum strategy in a relatively short horizon.

We examine the predictive value of the uncertainty associated with growth in temperature for stock-market tail risk in the United States using monthly data that cover the sample period from 1895:02 to 2021:08. To this end, we measure stock-market tail risk by means of the popular Conditional Autoregressive Value at Risk (CAViaR) model. Our results show that accounting for the predictive value of the uncertainty associated with growth in temperature, as measured either by means of standard generalized autoregressive conditional heteroskedasticity (GARCH) models or a stochastic-volatility (SV) model, mainly is beneficial for a forecaster who suffers a sufficiently higher loss from an underestimation of tail risk than from a comparable overestimation.

This research explores the distributional and directional predictabilities among Fintech, Bitcoin, and artificial intelligence stocks from March 2018 to January 2021 using nonparametric causality-in-quantile and crossquantilogram approaches. We also examine connectedness across the assets using a quantile VAR approach. The results indicate the existence of bidirectional causality-in-variance between the variables in a normal market. We also find that directional predictability among the assets is oscillatory over time lags. Finally, we observe a strong price connectedness for highly positive and negative changes. These results further document the diversification potential and safe-haven properties of technology-related assets for portfolio investors.

Behavioral finance has uncovered that investor engage emotionally when trading. We investigate how three psychological factors influence purchase and repurchase decisions: representativeness, the influence of prior gains, and reference points. Using trading data of 7200 UK investors we find that purchase decisions are influenced by representative heuristic and repurchase decisions are influenced by both representative heuristic and prior profitability. Further survival analysis showed that investors use the prior selling price as a unique reference point. Investors are more likely to repurchase a stock when trading above its reference point, but more likely to initiate the repurchase when trading below. Investors are influenced by previous experience and engage learning behavior when they seek to reinforce past success. As reference points are inferred but infrequently researched, this research adds to the literature and provides important and robust results for those engaging with financial planning clients.

This paper investigates whether the proximity between mutual funds and firms could explain corporate innovation. I find that local mutual funds tend to increase firms' R&D expenditures and productivity. Firms with greater local ownership produce more patents and patents with bigger impact. The positive relations are more pronounced for firms with low information quality and poor corporate governance. Further, local funds with more innovative firms outperform the ones with less innovative firms. Finally, firms with higher local ownership are less likely to fire CEOs who engage in innovation, which incentivizes CEOs for risky investments.

We study the role of rank-and-file employees on asset prices in the Korean stock market using monthly labor flow data from the national pension subscription descriptions. We find that firms experiencing high net labor outflows have lower future risk-adjusted returns. This return predictability is found to originate mainly from gross labor outflows. We further show that the workers' labor market decisions better reflect information on the firms' fundamentals when firm sales are greater related to wages or when workers can more easily transfer to better jobs. Finally, we confirm the workers' ability to predict firm performance.

This paper examines the predictive power of average skewness, defined as the average of monthly skewness values across stocks, documented by the prior literature for US market returns in an international setting. First, we confirm the validity of the results in the original study and show that the intertemporal relation between average skewness and aggregate returns becomes weaker in an alternative sample period. Second, when we repeat the analysis in 22 developed non-US markets, we find that average skewness has no robust predictive power for future market returns. The loss of forecasting power in the international sample does not depend on the method used to calculate average skewness or the regression specification and is supported by additional out-of-sample tests and subsample analysis.