Do product market threats affect analyst forecast precision?

We examine how product market threats influence the precision of analyst forecasts. Greater competitive threats may make forecasting more difficult by increasing the uncertainty regarding future cash flows and by influencing the quality of financial disclosure. Using a firm-specific measure of product market threats (i.e., fluidity), we find that analysts are more likely to be less precise forecasting earnings for highly fluid firms and that the lack of precision is not fully explained by performance volatility. Our findings further suggest that firms with fluid products have lower accruals quality and that they are more likely to withheld information regarding contract terms and sales from major customers. Cross-sectional analysis further suggests that the effect of fluidity on analyst forecasts is more pronounced when firms have flexibility in disclosure choices. Using significant changes in tariff rates as a quasi-natural experiment, we find that analyst forecast precision is significantly lower following tariff reductions.     

Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics

Understanding if credit risk is driven mostly by idiosyncratic firm characteristics or by systematic factors is an important issue for the assessment of financial stability. By exploring the links between credit risk and macroeconomic developments, we observe that in periods of economic growth there may be some tendency towards excessive risk-taking. Using an extensive dataset with detailed information for more than 30 000 firms, we show that default probabilities are influenced by several firm-specific characteristics. When time-effect controls or macroeconomic variables are also taken into account, the results improve substantially. Hence, though the firms’ financial situation has a central role in explaining default probabilities, macroeconomic conditions are also very important when assessing default probabilities over time.     

An Empirical Analysis of Growth Options of Japanese Electronics Firms

This paper provides some empirical support of real option models of corporate flexibility based on the analysis of the panel of Japanese electronics firms covering fiscal years 1999–2008. I apply random effect regression techniques and explain market value of firms’ growth options using several uncertainty proxies and firm-specific variables. Important contribution of the current study lies in empirical examining of the critical parameters of real option analysis of determinants of a firm’s investment behavior based on simple but effective structural model of multiple American-type options.     

Intangible investment and the importance of firm-specific factors in the determination of earnings

We examine the effect of intangible investment on earnings noncommonality, defined as the extent to which a firm’s earnings performance is determined by firm-specific factors versus market and industry factors. Such insight is important in determining the appropriate weighting of these factors when forecasting a firm’s earnings. For a sample of US firms over the 1980–2006 period, we find that earnings noncommonality is positively associated with intangible asset intensity. This finding is consistent with the resource-based view of the firm, which posits that intangible investments allow firms to differentiate themselves economically from their rivals. We also find that separable recognized intangibles contribute more to earnings noncommonality than do either goodwill or R&D, perhaps because separable recognized intangibles are more likely to arise from contractual or legal rights and thus are less susceptible to expropriation by rival firms. Finally, we find that the positive impact of R&D on earnings noncommonality is significantly greater for those industries where patents and other legal mechanisms are most effective in protecting R&D. This result suggests that the success of intangible investment as a differentiation strategy depends largely on the effectiveness of mechanisms used to protect intangible investments from expropriation.     

PREDICTING SYSTEMATIC RISK WITH MACROECONOMIC AND FINANCIAL VARIABLES

We analyze the predictive power of several macroeconomic and financial indicators in forecasting quarterly realized betas of 30 industry and 25 size and book-to-market portfolios. We model realized betas as autoregressive processes of order 1 and include lagged values of macroeconomic and financial indicators as exogenous predictor variables. In out-of-sample forecasting exercises, forecasts using bond market variables as exogenous predictors statistically outperform forecasts from a benchmark model without any exogenous predictors. These forecasts based on bond market variables also economically outperform benchmark forecasts by providing better performance in hedging the market risk of portfolios.     

Within-industry timing of earnings warnings: do managers herd?

An earnings surprise can be caused by a combination of firm-specific factors and market or industry factors. We hypothesize that managers have an incentive to time their warnings to occur soon after their industry peers’ warnings to minimize their apparent responsibility for earnings shortfalls. Using duration analysis, we find that firms accelerate their warnings in response to peer firms’ warnings. We conduct several tests to control for alternative explanations for warning clustering (for example, common shocks and information transfer) and conclude that the observed clustering is primarily due to herding. Our study is one of the first to empirically examine managers’ herding behavior and the first to document clustering of bad news. Moreover, we provide a multi-firm perspective on managers’ disclosure decisions that alerts researchers to consider or control for herding when they examine other determinants of managers’ disclosure decisions.     

系统性风险与企业财务危机预警——基于前沿机器学习的新视角

本文采用Logit回归模型以及随机森林模型、梯度提升模型等前沿机器学习方法,深入考察系统性风险指标对我国企业财务危机的预测能力。结果表明,系统性风险对中下游企业的财务危机具有显著的预测能力,而基于因子分析构建的系统性风险指标,结合随机森林模型可取得更好的预测效果。本文进一步区分财务危机的不同成因并发现,基于随机森林模型和Logit回归模型的预测框架能够对我国大多数财务危机事件进行有效预警。在此基础上,本文对我国上市企业监管提出相关建议,从而为完善金融风险处置机制提供一定参考。     

The heterogeneous impact of macroeconomic information on firms' earnings forecasts

This paper re-examines the role of macroeconomic information in forecasting firm earnings. We adopt a Fama–MacBeth regression model with the important extension of including information from over 140 macroeconomic variables that enter into the model in a reduced dimension form as a consequence of common factor analysis. The resulting factor-augmented model is then used to evaluate the importance of macroeconomic information on earnings forecasts for U.S. firms from 1962 to 2009. The same model is also examined for each individual time window and industry subsample. The results reveal a clear and heterogeneous impact of macroeconomic information on firm-specific earnings forecasts, and that these effects differ markedly during certain periods and across industries. In addition, when compared to analyst forecasts, we show that our model is generally more accurate over longer forecast horizons. The results of the identified heterogeneous impacts are used to define the conditions under which macroeconomic information becomes important for the firm.     

Lead indicator models and UK analysts' earnings forecasts

This study examines the predictive ability of models which adjust random walk forecasts of corporate earnings, to incorporate past changes in economic lead indicators. The results suggest that changes in the broad money supply measure M4 contain predictive ability, beyond equivalent changes in other lead indicators or an individual firm's earnings. When forecasts from the broad-money model are compared with forecasts generated by financial analysts a size effect is evident: the superiority of analysts' forecasts is apparent much earlier for large firms than for small firms. This result is consistent with studies suggesting a size-related differential in the collection and dissemination of information by market participants.     

Personal Lending Relationships

I identify the effects of personal relationships on loan contracting using executive deaths and retirements at other firms as a source of exogenous variation in executive turnover. After plausibly exogenous turnover, borrowers choose lenders with which their new executives have personal relationships 4.1 times as frequently, and loans from these lenders have 20 basis points lower spreads and 12.5% larger amounts. Personal relationships benefit firms across loan terms, especially during macroeconomic downturns. Increased financial flexibility from personal relationships insulated firms from financial shocks during the recent financial crisis: they exhibited less constrained investment and were less likely to layoff employees.     

Creative destruction and firm-specific performance heterogeneity

Traditional U.S. industries with higher firm-specific stock return and fundamentals performance heterogeneity use information technology (IT) more intensively and post faster productivity growth in the late 20th century. We argue that this mechanically reflects a wave of Schumpeter's creative destruction disrupting a wide swath of industries, with successful IT adopters unpredictably undermining established firms. This validates endogenous growth theory models of creative destruction and suggests intensified creative destruction as explaining findings associating greater firm-specific performance variation with higher per capita GDPs, economy growth rates, accounting standards, financial system development, and property right protection.     

Inventories,sales uncertainty,and financial strength

We investigate the empirical linkages between sales uncertainty and firms’ inventory investment behavior while controlling for firms’ financial strength. Using large panels of manufacturing firms from several European countries we find that higher sales uncertainty leads to larger stocks of inventories. We also identify an indirect effect of sales uncertainty on inventory accumulation through the financial strength of firms. Our results provide evidence that financial strength mitigates the adverse effects of uncertainty.     

Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.     

The role of hedge funds as primary lenders

We examine the role of hedge funds as primary lenders to corporate firms. We investigate both the reasons and the implications of hedge funds’ activities in the primary loan market. We examine the characteristics of firms that borrow from hedge funds and find that borrowers are primarily firms with lower profitability, lesser credit quality, and higher asymmetric information. Our results suggest that hedge funds serve as lenders of last resort to firms that may find it difficult to borrow from banks or issue public debt. We also examine the effect of hedge fund lending on the borrowing firms and find that borrowers’ profitability and creditworthiness improve subsequent to the loan. This beneficial effect of hedge fund lending is corroborated by our finding of positive abnormal returns for borrowers’ stocks around the loan announcement date. Overall, our findings are consistent with hedge funds adding value through their lending relationships and financial markets perceiving these activities as good news for the firms.     

Economic shock,owner-manager incentives,and corporate restructuring: Evidence from the financial crisis in Korea

We examine how owner-managers incentives and firm-specific measures of corporate governance affect restructuring decisions during an economy-wide shock. Using a large sample of Korean firms that had experienced a severe financial crisis during 1997–1998, we find that the likelihood of restructuring is negatively related to the divergence of cash flow rights and control rights of controlling shareholders, and that the announcements of restructuring by chaebol firms with such divergence are greeted more negatively by investors. However, firm-specific measures of corporate governance such as total debt, bank loans, and equity ownership by unaffiliated financial institutions mitigate these negative effects, thereby influencing firms to choose value-maximizing restructuring policies. Our results suggest that the controlling shareholders' incentives to expropriate other investors are high during an economic shock. Our results also highlight the importance of corporate governance in mitigating such expropriation incentives, and provide important implications for the role of corporate governance during an economic shock, such as the 2007–2008 global financial crisis.     

Global financial crisis and emerging issues for public policy

We study the effect of relationship lending on small firms' failure probability using a uniquely rich data set comprised of information on individual loans of a large number of small firms in Colombia. We control for firm-specific variables and find that small firms involved in long-term liaisons with commercial banks have a significantly lower probability of becoming bankrupt than otherwise identical firms not involved in a long-term credit relationship. We also find that small firms with multiple banking relationships face a lower failure hazard than otherwise identical firms involved in a unique long-term relationship.     

Corporate credit risk modeling and the macroeconomy

Despite a surge in the research efforts put into modeling credit and default risk during the past decade, few studies have incorporated the impact that macroeconomic conditions have on business defaults. In this paper, we estimate a duration model to explain the survival time to default for borrowers in the business loan portfolio of a major Swedish bank over the period 1994–2000. The model takes both firm-specific characteristics, such as accounting ratios and payment behaviour, loan-related information, and the prevailing macroeconomic conditions into account. The output gap, the yield curve and consumers’ expectations of future economic development have significant explanatory power for the default risk of firms. We also compare our model with a frequently used model of firm default risk that conditions only on firm-specific information. The comparison shows that while the latter model can make a reasonably accurate ranking of firms’ according to default risk, our model, by taking macro conditions into account, is also able to account for the absolute level of risk.     

Does alternative data reduce stock price crash risk? Evidence from third-party online sales disclosure in China

This study empirically investigates the effect of releasing alternative data on firm-specific price crash risk. Using the public launch of a firm's third-party online sales data in a well-known Chinese financial database as an exogenous shock, we find that stock price crash risk significantly decreases with the disclosure of third-party online sales data. The results are robust to a series of endogeneity corrections and robustness checks. We also find that the reduction of stock price crash risk is due to the decrease in managers' bad news withholdings and the increase in the accuracy of market expectations. In addition, the negative association between third-party online sales disclosure and crash risk is more pronounced for firms with weaker external governance, higher earnings volatility, greater likelihood of sales manipulation, and lower book-to-market ratio. Our findings yield important implications for a comprehensive understanding of the information disclosure effect of online sales data in the capital market and the mechanisms to reduce stock price crash risk.     

An Empirical Analysis of the Effect of Financial Distress on Trade Credit

This paper studies the use of supplier's trade credit by firms in financial distress. Trade credit represents a large portion of firms’ short‐term financing and plays an important role in financial distress. We find that firms in financial distress use a significantly larger amount of trade credit to substitute for alternative sources of financing. Firms that are smaller, with less market power, and with more unique products tend to use more trade credit financing when in distress. We also find that firms that significantly increase their trade payables when in financial distress, experience an additional drop of at least 11% in sales and profitability growth over the previously documented 21% average drop for financially troubled firms.