International Review of Finance最新文献

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.

This article proposes a new unique impulse response function (IRF) measure, or MIRF, based on the popular vector autoregressive model to study interdependency of multivariate time series. Same as the orthogonal IRF, the estimator of MIRF has an analytical form with well-established asymptotics, and is invariant to ordering of series. Compared to alternative unique IRF measures, MIRF does not depend on extreme identifications, and the associated forecast error variance measure is explainable. An illustrative empirical example is also provided.

We analyze why national development banks (NDBs) may provide longer-term loans to firms than private commercial banks (PCBs). If NDB bonds have higher collateral value than PCB bonds, then NDBs may lend longer-term than PCBs. NDBs may enjoy higher recapitalization willingness and capacity by the state and hence greater collateral value than PCBs. Moreover, NDBs may have advantages over state-owned commercial banks if NDB bonds enjoy higher market liquidity. However, NDBs may suffer from poor monitoring quality owing to undue political intervention, thus undermining collateral value. Our study implies that NDBs are not substitutes for but complements to PCBs.

We analyze the impact of soft information on US mortgages for default prediction and provide a new measure for lender soft information that is based on the interest rates offered to borrowers and incremental to public hard information. Hard and soft information provide for a variation in annual default probabilities of approximately 3%. Soft information has a lesser impact over time and time since origination. Lenders rely more on soft information for high-risk borrowers. Our study evidences the importance of soft information collected at loan origination.

The relative importance of credit market development and stock market development in boosting innovation remains a long-standing debate issue. In this study, we document how different types of financial markets development affect heterogeneous innovations. Using a broad sample across 42 developed and emerging economies and a generalized difference-in-differences identification strategy, we find that stock market development leads to significantly higher substantive innovation, especially in young and small firms, but has negative impact on incremental innovation. Conversely, credit market development promotes incremental innovation, especially in mature and large firms, but has negative impact on substantive innovation. Further analyses indicate that stronger shareholder protection enhances the positive impact of stock market on substantive innovation, while stronger creditor rights enhance the promoting effect of credit market on incremental innovation, and even turn the negative impact of credit market on substantive innovation into positive. Our paper provides new insights into the heterogeneous effects of credit market and equity markets on the real economy.

This study examines the Socially Responsible (SR) exchange-traded funds (ETFs) by comparing their risk-adjusted performance with a matched group of conventional ETFs in the U.S. equity market. In contrast to prior studies that focus on actively managed mutual funds, we find that the risk-adjusted returns of SR ETFs are significantly lower than those of conventional ETFs during the 2005–2020 period. Such underperformance is only observed in non-crisis periods but not in economic crisis periods (i.e., the 2020 pandemic recession and 2008 financial turmoil). We attribute the observed underperformance of SR ETFs during the non-crisis periods to their limited diversification of unsystematic risks resulting from various negative or positive screens employed in the funds. We also find that net fund flows of the SR ETFs are less sensitive to past negative performance than are conventional fund flows. Collectively, our findings suggest that, instead of seeking wealth maximization, socially conscious investors may choose SR ETFs to gain non-economic utility.