Pervin K. Shroff

Leaders and Followers Among Security Analysts: Analysis of Impact and Accuracy

We examine how analysts whose forecasts lag those of timely analysts aid the price discovery process. We classify analysts as lead and follower analysts for a given firm based on the relative timeliness of their earnings forecasts over a two-year period. We find that news in forecasts of lead analysts has a higher price impact relative to that of follower analysts and this difference in impact cannot be explained by analyst reputation or experience. The price impact of follower analysts’ forecasts is significant, although it dissipates as follower analysts become less timely. Moreover, we find that the forecast issued by even the least timely analyst conveys incremental information to the market. The significant market impact of follower analysts arises mostly due to the private information conveyed by their forecast and partly because their forecasts incorporate public information including their predecessor’s forecast. While in general the price impact of the forecast component that mimics prior information is consistent with the post-revision drift documented by prior studies, we find that this impact is significant only when the follower analyst’s forecast confirms the information conveyed by the predecessor analyst. We also find that follower analysts issue more accurate forecasts than lead analysts who appear to trade off accuracy for timeliness. Overall, we conclude that the complementary roles of timely and late forecasters combine the merits of timely and accurate information and facilitate price discovery.

Tests of Long-Term Abnormal Performance: Analysis of Power

In tests of long-term performance, researchers are faced with several research design choices. For instance, when estimating abnormal returns, what specific firm characteristics should be used as matching criteria to select control firms? What weights should be placed on each characteristic? Should an event firm be matched with one control firm or multiple control firms or with a reference portfolio? Should we use the calendar-time portfolio approach? We provide guidance to researchers on these questions by evaluating the power of the test using simulation analyses. We find that the quality of matching when selecting control firms has little impact on the power of the test. Among the alternative approaches studied, the Fama-French calendar-time portfolio approach obtains the highest power in random samples. Interestingly, we find that the higher power of this approach is attributable to the return aggregation method rather than the use of multiple risk factors or the in-sample fit of the model. In most nonrandom samples, the Fama-French approach obtains the highest power – the one exception being samples with extreme event-time clustering. Overall, for a reasonable sample size, the power of the best available methodology to detect economically significant abnormal returns is quite low.

Detection-Controlled Prediction of Accounting Irregularities: Channel Stuffing as an Illustrative Case

Based on a sample of firms that engaged in channel stuffing, we develop a model that predicts the probability of channel stuffing behavior in a broad cross-section of firms. Channel stuffing leads to accelerated revenue recognition by managing “real” activities to achieve short-term revenue and earnings targets. Given that channel stuffing is difficult to detect without the help of whistle-blowers, we control for undetected cases by estimating a bivariate probit model with partial observability. The model simultaneously estimates the effect of incentives, opportunities, and financial performance measures on the probability that a firm engages in channel stuffing and the probability that the channel stuffing activity is detected. Our results show that smaller firms, firms with higher growth opportunities, higher profit margins, and limited accrual management ability are more likely to engage in channel stuffing. A slowdown in receivables collection in the affected quarter serves as a significant indictor of channel stuffing. At the same time, we find that firm size, institutional holdings, Big-4 auditor, and tighter accounting regulation increase the detection probability and in turn reduce the probability of channel stuffing. Further analysis shows that firms that engage in channel-stuffing experience declining sales, production and profitability in future periods, suggesting that this activity achieves short-term benefits only at the price of long-term adverse consequences. Our results show that the power and specification of the bivariate probit prediction model is superior to that of the simple probit model. In an ex post validation analysis, we find that a sub-sample of the population of firms identified as having a high likelihood of channel stuffing by the bivariate probit model (but not by the simple probit model) exhibits future performance reversals that closely parallel those of the actual channel stuffing sample. These results highlight the need to control for the probability of detection to minimize misclassification in studies predicting accounting irregularities that are hard to detect.

Valuation Implications of Unconditional Accounting Conservatism: Evidence from Analysts' Target Prices: Valuation Implications of Unconditional Accounting Conservatism: Evidence from Analysts' Target Prices

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross-sectional analysis suggests that more sophisticated analysts and superior long-term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts’ earnings forecasts are negatively associated with the degree of conservatism, i.e., analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings-based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts’ target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.

Credit Default Swaps and Managers’ Voluntary Disclosure

We investigate how the availability of traded credit default swaps (CDSs) affects the referenced firms’ voluntary disclosure choices. CDSs enable lenders to hedge their credit risk exposure, weakening their incentives to monitor borrowers. We predict that reduced lender monitoring in turn leads shareholders to intensify their monitoring and demand increased voluntary disclosure from managers. Consistent with this expectation, we find that managers are more likely to issue earnings forecasts and forecast more frequently when traded CDSs reference their firms. We further find a stronger impact of CDS availability on firm disclosure when (1) lenders have higher ability and propensity to hedge credit risk using CDSs, and (2) lender monitoring incentives and monitoring strength are weaker. Consistent with an increase in shareholder demand for public information disclosure induced by a reduction in lender monitoring, we find a stronger effect of CDSs on voluntary disclosure for firms with higher institutional ownership and stronger corporate governance. Overall, our findings suggest that firms with traded CDS contracts enhance their voluntary disclosure to offset the effect of reduced monitoring by CDS‐protected lenders.