Journal of Empirical Finance最新文献

I find on average firms respond to a horizontal merger by investing less in PP&E, labor, and R&D. There is notable heterogeneity among the non-merging rivals. The laggard rivals reduce investments in PP&E, labor, and R&D while the neck-and-neck rivals do the opposite. There is an insignificant change for the leader rivals. These results support Aghion et al. (2005) on the inverted-U relationship between competition and innovation. Also, I show evidence that financial constraints and innovativeness are two factors that drive rivals’ heterogeneous responses. This empirical study sheds light upon the pattern in which horizontal mergers shape industry evolvement.

We investigate the impact of the local banking market structure on the level of corporate cash holdings and the value of cash. We find that, in more concentrated banking markets, firms increase their cash holdings by issuing more equity. The marginal value of $1 cash increases by 10 cents with a one-standard-deviation increase in bank concentration. The positive relationship between bank concentration and value of cash is robust to a rich set of tests such as for firms having access to bond markets or firms using syndicated loans and is more prominent for more financially constrained firms. We also explore the mechanism, and our results suggest that in more concentrated banking markets firms demand more cash to shield against default risk.

We propose a conditional correlation model with long memory dependence and smooth structural change. Previous literature has considered correlation and covariance models with structural change or long memory, but this is the first paper to jointly model both features. The correlation matrix is decomposed into long and short run components. Short run correlations converge hypergeometrically towards a slow moving long run correlation matrix that evolves according to one or more flexible Fourier forms. The model is applied to two data sets: a US equity portfolio; and a US equity, bond, gold and oil portfolio. Model fit and out of sample forecasts over 1 to 60 day horizons support the proposed approach.

We analyze bubble formations in house prices under the COVID-19 pandemic in 382 metropolitan areas in the U.S. with a special attention to the role of population density. We use a robust sieve-bootstrap version of the right-tailed unit root test procedure to identify periods of explosiveness in price–rent ratios across metro areas when controlling for fundamentals such as mortgage debt financing costs and the wealth of households. The bubble tests reveal evidence of explosive house prices during the COVID-19 pandemic but with important cross-area differences. In contrast to earlier bubble episodes, we find that the frequency and size of bubble formations under the pandemic have been stronger in low-density metro areas compared to high-density metro areas.

This paper empirically validates (Constantinides and Ghosh’s, 2017) heterogeneous-agents consumption-based asset pricing model for predicting expected returns in international equity markets. Using the model’s implications, we proxy the unobservable state variable driving income shocks with the principal component of consumption growth cumulants across agents. We confirm that both the level and changes in this cross-sectional consumption risk serve as pricing factors, emphasizing the importance of higher moments like skewness. The estimated structural parameters obtained from the Euler equations are statistically significant and plausible, while the factor risk premium estimates align with theoretical expectations. Our approach effectively explains the emerging versus developed premium, outperforming traditional methods reliant on cross-sectional variance. Our findings, robust across different model specifications and asset menus, highlight the imprecision of consumption-based factor risk premia estimates when limited to developed markets, a limitation mitigated by including emerging markets. The model demonstrates a 60% explanatory power, surpassing the global Fama–French model.

Based on 10 commonly used factors, we construct a novel factor momentum strategy in the Chinese stock market, which earns an annualized return of 9.91 %, with a Sharpe ratio of 1.15. Factor momentum subsumes stock momentum, high-priced momentum, and industry momentum, digests its component factors and a variety of anomalies, and represents the momentum anomaly in China. Furthermore, mispricing correction helps explain factor momentum, which produces stronger returns during higher aggregate idiosyncratic volatility periods as well as among stocks with higher information asymmetry and short-sale constraints. Exposure to factor premiums and the manifestation of predictability determine factor momentum in China.

We examine the drivers of private equity in response to the fully exogenous Covid-19 shock, employing listed private equity as a proxy for traditional non-listed private equity. This approach enables us to reliably measure firm characteristics and performance in real-time. Listed private equity firms, on average, underperformed significantly during the crisis, with a performance drop ranging from 9.2 % to 43.6 %, depending on the model used. However, there is substantial cross-sectional variation driven by unique firm-level attributes including access to capital, liquidity, transparency, and ownership structure. Listed private equity with better access to capital and higher transparency shows resilience during the crisis, while higher illiquidity and opacity exacerbate the negative effects. This study offers early evidence on Covid-19′s impact on private equity firms, highlighting value drivers and performance dynamics of this alternative asset class during a period of extreme tail risk.

This study investigations the relationship between investor attention and stock price crash risk in different markets and different levels of natural-person ownership. Google's search volume is primarily employed as a proxy for investor attention. The empirical results show that the higher investor attention, the higher future crash risk, with this effect being more pronounced among firms listed on the over-the-counter market and firms with a high level of natural-person ownership. This study fills the gap in research on the factors affecting stock price crashes from the perspective of investor behavior.

We examine whether beliefs about climate change affect loan officers’ mortgage lending decisions. We show that abnormally high local temperature leads to elevated attention to and belief in climate change in a region. Loan officers approve fewer mortgage applications and originate lower amounts of loans in abnormally warm weather. This effect is stronger among counties heavily exposed to the risk of sea-level rise, during periods of heightened public attention to climate change, and for loans originated by small lenders. Additional tests suggest that the negative relation between temperature and approval rate is not fully explained by changes in local economic conditions and demand for mortgage credit, or deteriorating quality of loan applicants. By contrast, Fintech lenders partially fill the gap in demand left by traditional lenders when local temperature is abnormally high.