Andreas Simon

Target price forecasts: Fundamental and non-fundamental factors

This paper reveals both fundamental and non-fundamental factors play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term growth are shown to be important explanatory variables for target prices; equally, the following salient non-fundamental factors are also shown to explain target price levels and especially target price biases: the 52-week high price and recent market sentiment. Here, increases in the 52-week high and market sentiment measures of one standard deviation correspond to increases in positive target price bias of 4.8% and 14.7%, respectively. Initially our analysis is constrained to analysts who provide long-term growth forecasts, however, our findings are robust to the removal of this constraint and the broader set of analysts. Our analysis reveals that analysts place greater weight on these non-fundamental factors in settings with greater task complexity and/or resource constraints, and when they rely on valuation heuristics as opposed to more rigorous valuation methodology, and that this greater weight is associated with increased optimistic bias. Finally, our results show that analysts’ target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent market sentiment in the target price formation process.

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.

An analysis of persistence in analyst's relative forecast accuracy

We examine the persistence in analysts’ relative earnings forecast accuracy. When analysts are ranked into forecast accuracy quintiles, calculated over all the firms they cover in each year, we find that 52% (45%) of superior (inferior) analysts, i.e. analysts in the lowest (highest) quintile, remain in this quintile in the subsequent period. We show that a variable we develop and denote as forecasting complexity, i.e. the extent to which analysts’ earnings forecasts vary when predicting a firm’s earnings, is important in explaining variation in the persistence of the relative forecast accuracy of analysts. When we control for forecasting complexity, the probability of analyst relative forecast accuracy to persist is reduced by about half. This reduced persistence, however, measures true forecasting ability. When we form portfolios using recommendations of analysts identified as superior in two consecutive periods, controlling for forecasting complexity, we find significant abnormal returns after adjusting for the Fama–French and momentum factors.