International Review of Finance最新文献

This research investigates the effect of sentiment on the time-series and cross-section of mean, variance and correlation of asset returns to examine how investor sentiment creates predictable variations in financial markets. Based on the method proposed by Baker and Wurgler (2007, Investor sentiment in the stock market, Journal of Economic Perspectives 21, 129-152), we build composite sentiment indexes with a focus on international markets. Our time-series results show that optimistic (pessimistic) sentiment leads to overpricing (underpricing) and that variance and correlation of asset returns increase when investors are pessimistic. Our cross- section results suggest that these effects tend to become more pronounced for stocks with more exposure to sentiment or the market.

Using listed Japanese firms, we examine changes in R&D investment decisions during periods of high economic policy uncertainty and politics uncertainty (EPU). We find that under high EPU, firms are more persistent in their previous R&D investment and reduce their responsiveness to sales growth, while the mechanism of EPU occurs mainly through fiscal policy. We also identify heterogeneities in ownership structure and find that high director ownership encourages R&D in firms with greater growth opportunities despite higher EPU. Moreover, Japanese directors suffer from the “quiet life problem,” which further reduces their incentive to change R&D investment during periods of EPU.

Existing studies show that firms with large macroeconomic risk do not earn higher returns, incompatible with the theoretical predictions of standard economic models. Using a broad set of macro-related factors, we find the January seasonality of the macroeconomic risk–return relation. Firms with high macro risk deliver higher returns than firms with low risk in January, that is, the positive risk–return trade-off holds. Conversely, the negative risk–return relation is observed in non-January months. The seasonal variation in the macro risk–return relation cannot be explained by existing January effects, including the tax-loss selling, window dressing, and pronounced gambling preference around New Year.

Earnings announcement (EA) poses a non-diversifiable risk to investors. This study examines whether investors demand higher returns for stocks with high systematic EA risk. We find evidence that systematic EA risk is priced, however, the premium is realized only during periods with intensified cash-flow news. Specifically, we construct an ex-ante measure of expected information intensity (EII) and find that in the subsample of high-EII firms, those with high systematic EA risk earn significantly higher future returns. Controlling for known risk factors, stocks with high systematic EA risk outperform those with low systematic EA risk by 0.43% in monthly Fama–French five-factor alpha. We also confirm the well-documented announcement premium, i.e., high-EII firms outperform low-EII firms and show that the EA risk premium is distinct from the announcement premium. To exploit both premiums, a feasible strategy of long stocks with both high-EII and high systematic EA risk and short stocks with low-EII yields monthly 0.81% five-factor alpha.

This study examines the association between individualistic culture and firm default risk across countries. Using a sample of 15,225 firms across 32 countries over the 2005–2018 period (115,464 firm-year observations), we find that firms based in countries with high levels of individualism are associated with greater default risk. Our results are robust to a battery of endogeneity and other robustness checks. In additional analyses, we show that risk-taking behavior is a channel through which individualism impacts firm default risk. We also find that the effect of individualistic culture on firm default risk is weak in countries with stringent bankruptcy laws. Overall, the findings of this study can improve our understanding of the impact of major informal institutions, such as individualistic culture, on manager behavior, which has significant implications for firms operating in global financial markets.

Investigating the transition from the London interbank offered rate (LIBOR) to the secured overnight financing rate (SOFR) and considering the documented volatility of SOFR, this study examines the dynamic nature and potential drivers of the SOFR by analyzing both the SOFR–EFFR (effective Federal Funds rate) and SOFR–IOER (interest on excess reserves) spreads. The results reveal noteworthy correlations between the SOFR and end-of-month anomalies and Federal Reserve market interventions in the repo market. These effects persist even after controlling for other variables, such as the amount of outstanding Treasury securities, Treasury General Account balance, and net repo transactions by primary dealers. Investors in SOFR-linked instruments should be mindful of the possible impact of these factors.

This paper dissects investor sentiment into two distinct components: structured sentiment and unstructured sentiment, based on their underlying driving factors. Employing an extension of the classic noise trader model, our analysis reveals a negative relationship between market returns and both types of sentiment—structured and unstructured. Additionally, we find a positive association between market volatility and fluctuations in these sentiment components. Furthermore, the impact of fluctuations in unstructured sentiment on market volatility becomes more pronounced as the proportion of noise traders increases. Importantly, our theoretical assertions are robustly supported by empirical data.

This study analyzes the time-varying dependence between U.S. leveraged loan and debt markets within a highly linked financial system using a quantile-based time-varying connectedness framework to determine the hedging benefits of leveraged loans for financial investors at various quantiles. Based on daily closing price data from November 28, 2008 to October 3, 2023, the evidence demonstrates considerable (moderate) spillovers across the leveraged loan and debt markets for severe (normal) occurrences, with additional results indicating symmetric interaction. In terms of risk spillover, we also affirm the dominance of short-term fixed-income instruments over leveraged loans and long-term bonds. These findings indicate that no hedging or diversification occurred among the investigated markets.

We introduce the info-metrics approach to empirical asset pricing under ambiguity. We apply relative entropy as a pseudo-metric of model discrepancy, and generalized maximum entropy as a principle of statistical inference, to cross-sectional asset pricing tests. We show that a single-factor market representation of the CAPM under ambiguity can explain the cross-section of U.S. stock returns without the aid of additional risk factors. The additional factors can be interpreted as compensations for idiosyncratic ambiguity. The approach can also recover the market price of ambiguity that sets a lower (entropy-based) bound on stock prices, which can be understood as investors' “margin of safety” against extreme market events.