Analyst Bias Research Articles

Quantitative evaluation of vitrinite reflectance in shale using Raman spectroscopy and multivariate analysis

The current research builds upon a previously published study that demonstrated the combination of Raman spectroscopy coupled with multivariate analysis (MVA) for the prediction of thermal maturity in coal by evaluating the efficacy of this method for the prediction of thermal maturity in shale. MVA techniques eliminate analyst bias in peak-fitting methods by using the full Raman spectrum, and then extricating the important spectral regions for distinguishing samples and building accurate, robust models. Partial least squares (PLS) regression models were developed using Raman spectra and VRo values (0.58–4.59%) for 53 geographically diverse shale chip samples, and 43 shale powder samples. Separate PLS models were built using Raman spectra from shale chips or powders. The calibration sets were validated using approximately one-third of the samples to rigorously assess the predictive accuracy of the models. The root mean standard error of prediction was 0.24 for the shale chip model, and 0.28 for the shale powder model. The coefficients of determination (R2) for the cross-validated data sets were identical (0.90, chips; 0.90, powders), revealing a strong linearity despite the geographic and age diversity of the samples. This study demonstrates the validity of using PLS models for the prediction of shale VRo from Raman spectra. The MVA method described herein presents a Raman alternative to the VRo industry benchmark for assessing thermal maturity in shale that is not imperiled by the shortcomings and subjectivity of peak-fitting methods.

Market reaction to optimistic bias in the recommendations of chaebol-affiliated analysts

Using the setting of chaebol industrial organizations in Korea, which allows for the study of a unique affiliation between a chaebol group and financial analysts, we examine whether investors react to an optimistic bias in affiliated analysts’ recommendations. Our initial market return tests, abnormal trading volume tests and independent analysts’ reaction tests suggest that investors and independent analysts recognize and discount an optimistic bias in chaebol-affiliated ‘buy’ recommendations. However, long-term market returns are more profitable in terms of affiliated analysts’ ‘buy’ recommendations than independent analysts’ recommendations, which suggests that investors excessively discount chaebol-affiliated ‘buy’ recommendations in the short-term.

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

ABSTRACTWe 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; that is, 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.

Does Adoption of K-IFRS Increase Upward Bias in Analysts’ Earnings Forecasts?

Does Adoption of K-IFRS Increase Upward Bias in Analysts’ Earnings Forecasts?

Has local informational advantage disappeared?

AbstractThis study examines how changes in the information environment affect the informational advantage of geographically proximate agents. The long‐term advantage of local agents disappeared at the turn of the millennium. This is accompanied by the reduction in local bias of institutional investors and equity analysts. However, institutional investors continue to trade local stocks disproportionately more often than non‐local stocks; moreover, their local trades outperform non‐local trades in the short term—even for large and liquid stocks. Our results are consistent with improvements in the information environment shortening the horizon of proximity‐based informational advantage.

손실기업 및 이익기업의 배당지급 여부와 재무분석가의 낙관적인 이익예측편의

손실기업 및 이익기업의 배당지급 여부와 재무분석가의 낙관적인 이익예측편의

Political Cycles and Analyst Bias

We examine the role that political-economic factors play in shaping financial analyst bias using a series of scheduled provincial elections in China. Theory on political business cycles holds that, in a short period prior to these political events, provincial politicians have stronger incentives to bias analyst opinions toward optimism. Consistent with this intuition, we document that analysts are significantly more likely to issue favorable recommendations or revise their recommendations upward during political event periods. In cross-sectional evidence consistent with expectations, we find that the relation between political events and analyst optimism is more pronounced for analysts: covering local state-controlled companies, working for brokerage firms affiliated with local politicians, covering companies in provinces with more potential investment banking business, and working for brokerage firms with less valuable reputations to protect. Supporting that foreign analysts are more immune to local political forces, we find that their recommendations do not become more optimistically biased during political event periods. Analyzing stock returns upon and subsequent to the release of favorable recommendations issued during political event periods reveal that investors perceive such recommendations as less credible, although they fail to fully discount their information value. Reinforcing our main evidence, we also find that financial analysts are more likely to issue optimistic earnings forecasts during political event periods. Collectively, our research implies that politicians successfully distort analyst incentives for political purposes.

Optimistic bias of analysts' earnings forecasts: Does investor sentiment matter in China?

This paper primarily studies the effects of irrational factors (investor sentiment) on analysts' forecast bias and the impacts of rational factors (conflicts of interest) on the sentiment-forecast bias nexus. Empirical findings show that investor sentiment does have significant positive impacts on analysts' forecast bias. This effect still holds after controlling for rational factors (commission relationship, underwriting relationship and reputation factors). Moreover, investor sentiment has more notable impacts on analysts' forecast bias for those who are under the pressure of conflicts of interest, particularly for the commission relationship. The stronger the commission relationship is, the greater the analysts' forecast bias. Our results provide new insight into the mechanism through which investor sentiment affects returns.

The effect of managerial entrenchment on analyst bias

While analyst bias is well documented, its relationship with corporate governance has been neglected. We claim that entrenched management of covered firms significantly increases analyst bias. By using governance index as a proxy for managerial entrenchment, we show that analyst bias increases as managerial entrenchment increases and affiliated analysts do not provide biased research for firms with the least and most entrenched managers due to their reputational capital concerns. Furthermore, our results show that as the channels managers use to pressure analysts get clogged after the regulations that took place between 2000 and 2003, entrenched managers' effect on analyst behavior disappeared.

Characterization challenges for a cellulose nanocrystal reference material: dispersion and particle size distributions

Cellulose nanocrystals (CNCs) have high aspect ratios, polydisperse size distributions, and a strong propensity for aggregation, all of which make them a challenging material for detailed size and morphology characterization. A CNC reference material produced by sulfuric acid hydrolysis of softwood pulp was characterized using a combination of dynamic light scattering (DLS), atomic force microscopy (AFM), transmission electron microscopy, and X-ray diffraction. As a starting point, a dispersion protocol using ultrasonication was developed to provide CNC suspensions with reproducible size distributions as assessed by DLS. Tests of various methods for AFM sample preparation demonstrated that spin coating on a positively charged substrate maximizes the number of individual particles for size analysis, while minimizing the presence of agglomerates. The effects of sample-to-sample variability, analyst bias, and sonication on size distributions were assessed by AFM. The latter experiment indicated that dispersion of agglomerates by sonication did not significantly change the size distribution of individual CNCs in suspension. Comparison with TEM data demonstrated that the two microscopy methods provide similar results for CNC length (mean ~ 80 nm); however, the particle width as measured by TEM is approximately twice that of the CNC height (mean 3.5 nm) measured by AFM. The individual crystallite size measured by X-ray diffraction is intermediate between the two values, although closer to the AFM height, possibly indicating that laterally agglomerated CNCs contribute to the TEM width. Overall, this study provides detailed information that can be used to assess the factors that must be considered in measuring CNC size distributions, information that will be useful for benchmarking the performance of different industrially sourced materials.

Valuation Implications of Accounting Conservatism

This paper examines whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism has a downward effect on reported earnings, it does not have a downward effect on the present value of future cash flows. We examine whether analysts add back the effect of accounting conservatism incorporated in their own earnings forecasts when using these forecasts to estimate target prices. We find that signed target price forecast errors (actual minus forecast) have a significant positive association with the degree of conservatism in earnings, suggesting that on average target prices are biased due to the effect of accounting conservatism. Cross-sectional analysis suggests that more sophisticated analysts undo the effect of conservatism to a greater extent than other analysts, although their target price forecasts also exhibit systematic bias due to conservatism. In additional analyses, we track the analyst's valuation path to understand the mechanism through which unconditional conservatism leads to bias in target prices. We first establish that analysts' earnings forecasts do incorporate the downward effect of accounting conservatism. Based on alternative earnings-based valuation models/heuristics that analysts may use, e.g., the forward P/E and the PEG ratio, we find that analysts fail to add back the effect of accounting conservatism incorporated in their earnings forecasts when deriving their target prices. As a consequence, we find that, for extreme levels of conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that the use of simple valuation heuristics by analysts can inhibit price discovery, especially in the presence of conservative accounting.

Are Analysts Overoptimistic about the Prospects of Sin Firms?

We investigate the association between the bias and accuracy of consensus analysts’ earnings forecasts and whether a firm is a sin firm or not. We measure analyst forecast bias as the difference between the consensus earnings forecast and the actual earnings, scaled by the stock price. We measure analyst forecast accuracy as the negative of the absolute value of the difference between the firms’ forecasted and actual earnings, scaled by the stock price. We find a positive association between the level of forecast optimism and sin firm membership. We find a negative association between the level of forecast accuracy and sin firm membership. Overall, these results imply that analysts tend to issue over-optimistic and less accurate earnings forecasts on sin firms.

Optimism bias in financial analysts' earnings forecasts: Do commissions sharing agreements reduce conflicts of interest?

Implemented in May 2007, the French rules governing commission-sharing agreements (CSAs) consist of unbundling brokerage and investment research fees. The goal of this paper is to analyze the effect of these rules on analysts' forecasts. Based on a sample of one-year-ahead earnings per share forecasts for 58 French firms during the period from 1999 to 2011, we conduct panel data regressions. We show that the analysts' optimistic bias declined significantly after CSA rules, which suggests that these rules are effective at curbing the conflicts of interest between brokerage activities and financial research. Our results are robust to the impact of the Global Settlement and the Market Abuse Directive.

Probability Weighting and Analyst Bias: Theory and Evidence

Analyst forecasting bias is frequently attributed to opportunism. We argue that opportunism is not a necessary condition for bias and propose a simple model, based on research in behavioral economics and psychology, of belief-based probability weighting. The model is used to develop benchmarks which we test empirically. Our model explains the change in the magnitude of forecast bias over the forecast horizon, the percentage of optimistic and pessimistic forecast errors at long horizons, and seemingly counter-intuitive findings around the implementation of Regulation Fair Disclosure. Our results may inform regulators as they attempt to reduce or eliminate analyst forecast bias; eliminating incentives to bias may not lead to statistically unbiased forecasts.

Analyst Forecast Momentum

A great number of academic papers evaluate the potential for incentive-driven bias in sell-side analysts' earnings forecasts. Yet bias does not necessarily invalidate a forecast, nor does it impinge on its relative quality. We find that analysts' forecasts are optimistic relative to recently introduced fundamental alternatives. However, analysts' forecasts have lower absolute deviation and the information in their earnings forecasts has predictive value for near-term stock returns. We propose the latter result as a previously unidentified form of earnings momentum. We find that this form of earnings momentum is even stronger for quarterly forecasts than annual forecasts, suggesting that analysts' have particularly strong incentives directed to forecasting quarterly earnings. Investing with optimistic analysts is a rational investment strategy, rather than a misguided one, when the investment horizon is less than one year.

Does Forecast Bias Affect Financial Analysts’ Market Influence?

Prior studies find that analysts tend to bias their forecasts upward in poor information environments and downward in rich information environments, consistent with attempts to curry favor with management. We find that investors anticipate this behavior by reducing their response to upward forecasts in poor information environments and downward forecasts in rich information environments. Using Hugon and Muslu’s measure of analyst conservatism as an ex ante indicator of individual analysts’ forecast bias tendencies, we show that the stronger return response they find to conservative analysts’ forecast revisions is restricted to poor information environments, where optimistic analyst bias is prevalent. Our results suggest that analysts pay a price in market influence when their forecasts reinforce analysts’ typical forecast bias for the firm’s information environment. Conversely, analysts whose forecasts conflict with the typical bias for the firm are rewarded with larger than average return responses.

Has Local Informational Advantage Disappeared?

This study examines how changes in the information environment affect the informational advantage of geographically proximate agents. We find that the long-term advantage of local agents disappeared at the turn of the millennium. This is accompanied by the reduction in local bias of institutional investors and equity analysts. However, institutional investors continue to trade local stocks disproportionately more often than nonlocal stocks; moreover, their local trades outperform nonlocal trades in the short term -- even for large and liquid stocks. Our results are consistent with improvements in the information environment shortening the horizon of geographic proximity-based informational advantage.

Do analysts cater to investor beliefs via target prices

This study examines analyst target price bias within the framework of catering theory. Given that analyst catering is more probable when the clients of the analyst forecasts are less sophisticated investors who are less likely detect it, we focus on a unique stock market where individual investors rather than institutions are the predominant group and account for 75% of the total security trading. Our results show that analysts do cater to investors via overshooting actual end-of-forecast-period prices even after controlling market sentiment index, analyst and company characteristics. Furthermore, results show that foreign analysts produced more biased target prices compared to domestic peers.

Automated Imaging and Analysis of the Hemagglutination Inhibition Assay.

The hemagglutination inhibition (HAI) assay quantifies the level of strain-specific influenza virus antibody present in serum and is the standard by which influenza vaccine immunogenicity is measured. The HAI assay endpoint requires real-time monitoring of rapidly evolving red blood cell (RBC) patterns for signs of agglutination at a rate of potentially thousands of patterns per day to meet the throughput needs for clinical testing. This analysis is typically performed manually through visual inspection by highly trained individuals. However, concordant HAI results across different labs are challenging to demonstrate due to analyst bias and variability in analysis methods. To address these issues, we have developed a bench-top, standalone, high-throughput imaging solution that automatically determines the agglutination states of up to 9600 HAI assay wells per hour and assigns HAI titers to 400 samples in a single unattended 30-min run. Images of the tilted plates are acquired as a function of time and analyzed using algorithms that were developed through comprehensive examination of manual classifications. Concordance testing of the imaging system with eight different influenza antigens demonstrates 100% agreement between automated and manual titer determination with a percent difference of ≤3.4% for all cases.

Consistent Analyst Expectation Error and Earnings Management: Evidence from China

ABSTRACTUsing data from the Chinese A-share market in 2004–12, we show how cognitive bias of individual analysts led to counterproductive effect in less-developed financial markets. We form an ex ante measure of analysts’ expectation error, a measure suitable for markets with a short history. We find that star analysts tend to be more optimistic than ordinary analysts, and their biased opinions influence other analysts because of analyst herding behavior. Two-stage least square regression results suggest that consistent expectation errors among analysts can lead to earnings management. These insights are valuable to investors and regulators.