Journal of Empirical Finance最新文献

Identifying the components of yields is a challenging task for monetary authorities. We use a term structure model with stochastic volatility and eurozone global macro factors to estimate time-varying term premia and short rate expectations for ten countries in the euro area. Unlike previous studies, we explicitly disentangle from these components the convexity effects that have substantial impact on long-term yields in turbulent times. The empirical evidence shows that term premia are significantly positively related to yield volatility across all countries, while term premia and expected short rates react in opposite directions to shocks in eurozone inflation and GDP growth expectations. A connectedness analysis based on variance decomposition suggests that there exist significant cross-country interconnections for the yield components, with the size of the links varying substantially over time and across countries.

We estimate variance decompositions of the real exchange rate ($q$) for 19 currencies based on a present-value relation. At very short horizons, the driving force of $q$ is predictability of the future exchange rate. At long horizons, return predictability drives most variation in $q$, with predictability of interest differentials playing a secondary role. This pattern is especially strong for the Non-G10 currencies. However, the long-run predictability mix associated with the Japanese Yen clearly deviates from the other currencies and is unstable over time. The quantitative simulation of a liquidity-based exchange rate model largely replicates our main empirical findings.

The natural rate of interest, $r^{\ast }$, is an important input to determine the appropriate monetary policy stance. Commonly, the measurement is estimated on a single-country basis, which ignores the international factors that may affect $r^{\ast }$. However, expanding to a multiple-country model adds substantive model complexity. In this paper, I exploit a Bayesian method to build a multi-country state space model, which is an extension of Holston et al. (2017), to jointly estimate $r^{\ast }$ for the G7 countries. Furthermore, in the process of estimating the model, I decompose the country level $r^{\ast }$ into common, regional, and idiosyncratic components and identify the dynamics of each component. I find that across the G7 countries $r^{\ast }$ has been declining since the 1990s and is driven by the common component. I also find the contribution of the idiosyncratic components to $r^{\ast }$ is minor. These results suggest a synchronization of the natural rate of interest across countries since the 1990s, supporting the idea posited in Del Negro et al. (2019) that the low natural rate is due to a rise in the demand for safe and liquid assets.

This paper argues that leasing, as an important but often ignored source of external financing, facilitates the allocation efficiency of finance. We document a large overestimation of measured finance misallocation (Whited and Zhao, 2021) when lease-induced debt is ignored among US manufacturing firms. The losses in real value-added due to finance misallocation drop from 25% to 19% after appropriately adjusting for lease. This amounts to a 6-percentage-point reduction in measured misallocation inefficiency. In the time-series, this inefficiency reduction from lease-adjustment exhibits a strong countercyclical pattern. In the cross-section, we find such reduction presents asymmetric patterns for firms with different size — it is more salient within small firms than in large firms. Leasing improves the allocation of finance by raising the total amount of finance as well as by alleviating inefficient debt-equity combinations across firms. Finally, we find that factoring in lease-induced debt lowers both the level and dispersion of finance costs, consistent with the mitigation effect of lease-adjustment on finance allocation efficiency.

In this study, we investigate the pricing of risks in the cross-section of cryptocurrency returns. In doing so, we decompose total variations into systematic and idiosyncratic components, as well as differentiate jumps from diffusive variations. We show that a hedged portfolio sorted on idiosyncratic diffusive risk yields a weekly return of -1.11%, suggesting the existence of a low idiosyncratic risk anomaly. Subsequently, we examine explanations for this anomaly, and show that limits to arbitrage prevent arbitrageurs from fully correcting the mispricing.

Using a large sample of 4,892 IPOs in the United States, we establish that the level of social capital in the county of the IPO firm's headquarters is negatively associated with the level of IPO underpricing. The results hold for a range of robustness tests, including those addressing endogeneity. Additionally, the relation between social capital and IPO underpricing is weaker among IPO firms with less information uncertainty and stronger for IPO firms with more agency problems. We also show that social capital affects IPO underpricing through changing IPO firms’ earnings management activities. Further, high social capital is associated with a higher likelihood of the IPO being oversubscribed, higher total proceeds raised in the IPO, a greater number of IPO shares issued, and lower total IPO administrative fees. Social capital also influences seasoned equity offerings (SEOs), in the form of lowering SEO underpricing and SEO discount. Overall, our results demonstrate the importance of social capital as an informal contracting mechanism in enhancing the pricing and performance of firm securities issuance.

The paper examines the macroeconomic relevance of the common component of discount rate news in firm-level stock returns for G7 countries (except for Italy, focusing on each country’s index constituents) by applying a hierarchical dynamic factor model to the Campbell and Ammer (1993) return decomposition. This approach offers advantages over alternative investor sentiment indicators and is easily extended to a larger cross-section of countries. Evidence suggests global investor sentiment leads, rather than lags, domestic sentiment and global economic conditions. Investor sentiment predicts economic conditions in-sample and out-of-sample.

Studies have documented that firms in competitive industries tend to invest inefficiently and suffer from booms and busts. We extend the literature by showing that high-sentiment signals from credit markets, an indication of easy money available, prompt firms in competitive industries to borrow and invest more than usual. The resulting excess investments collectively lead to overcapacity and, consequently, to declines in competing firms’ operating and financial performance. In contrast, we find that easy money does not lead to excess investments in consolidated industries. Our findings suggest that competitive industries’ booms and busts are largely driven by easy money from credit markets, and that (easy) financing contributes to their investment inefficiency problem.

We investigate how CEO personality traits moderate the shareholder value creation from corporate acquisitions. First, we document that the likelihood of corporate acquisitions is positively associated with extravert and overconfident CEOs consistent with the evidence of prior literature. Second, and most importantly, we document that stock prices react positively to acquisitions undertaken by conscientious CEOs. This finding is in line with the view that the stock market favors the detailed and planned approach towards acquisitions of conscientious CEOs. Furthermore, stock prices react positively to acquisitions undertaken by extraverted and overconfident CEOs but only after a good prior corporate performance stretch. Our results illustrate that CEO traits are important for the value implication of corporate acquisitions.

We provide new empirical evidence of how financial volatility responds to an increase in economic uncertainty. Consistent with the implications derived from a theoretical equilibrium model in which investors are uncertain about the true state of the economy, our estimates for the contemporaneous effects of uncertainty on volatility are significantly positive, and their magnitudes critically depend on the economic situation and degree of investors’ risk aversion. Specifically, stock return volatility tends to overreact to increased uncertainty during good times when investors are more risk-averse. All these relations remain robust to different uncertainty measures. We further build a simple reduced-form predictive model augmented with uncertainty measure, and find the uncertainty displays additional predictive power for future volatility. Moreover, this improvement is concentrated around bad times with high risk aversion, most of which are located in the NBER-dated recession periods.