Beckers, Steliaros and Thomsosn Flashcards
Herding:
Describe the problems with analysts earnings forecast referred to in the study by beckers, stliaros and thmoson, referring to possible causes of these problems. Outline the results of the emerical analyss carried out by becker et al, and comment on the implications of these results for users of analysits earnings forecast.
Herding is described as the phenomen that analyst following each other.
This has been evidenced in prior literature through low dispersion in analysts forecast, as analyst forecast are less different than expected. This is more pronounced If earnings are difficuilt to predict and less pronounced in experienced analysts
In order to proof herding BST looked on the RCF (Ratio of coeffient variation) and RHL (ratio of standartised high low ranges). Both ratios are describing the dispersion of two year ahead forecast to one year ahead forecasts. In the absece of herding they should be >1, however they showed that both are below 1.
Possible explanation for this as that analyst talk with each other and rather tend go with the flow than doing the what nobody is doing (behavioral finance)
Optimism:
Describe the problems with analysts earnings forecast referred to in the study by beckers, stliaros and thmoson, referring to possible causes of these problems. Outline the results of the emerical analyss carried out by becker et al, and comment on the implications of these results for users of analysits earnings forecast.
is described as the phenomen that forecast earnings exceed actual outcomes on average.
There is empirical evidence that this upward bias s larger for long horizons (e.g. 1 year) than for short horizons (e.g. 1 month). Earnings forecast do outperform eal return, which is proof for optimism. This can be emiricaly analyst by looking on the following criteria:
FB =( Forecast earnings – actual earnings) / Actual earnings
In their analysis they have shown that the bias is positive and increases when lenghting the horizon
Possible reasons why analysts persistently overestimate future earnings:
• It may help the analysts employer to generate brokerage business by encouraging investors to buy shares
• It may help the analysts emplyers to remain on good terms with firms for which it provides sercixes (e.g. corporae finance advisory work)
• It may also helo the analyst to remain on good terms with the staff of the tracked firm, on whom he/she might rely for information
Inaccuracy in Forecast:
Describe the problems with analysts earnings forecast referred to in the study by beckers, stliaros and thmoson, referring to possible causes of these problems. Outline the results of the emerical analyss carried out by becker et al, and comment on the implications of these results for users of analysits earnings forecast.
is the error of either direction, overestimates or underestimates. It is mainly asscociated with
• the magnitude of forecast change;
• analyst dispersion (disagreement among analysts); l
• ength of forecast horizon;
• size of company (average forecast error is smaller for large and well tracked firms=
- By calculating the forecast error and forecast bias, they confirm the prevalence of optimism in the consensus numbers. It could also safely assume the, both herding and optimism help explain the low forecast accuracy.
They found out that the forecast error increases significantly with:
• Analyt forecast dispersion
• Stock return volatitlty
• and reduced significantly with:
• number of analyst following the firm
- in the above regression model, there is no strong evidence that market cap (firm size) has a significant impact
Key research Question of the Article:
- In fact systematic biases affecting earnings forecast are well documented but anayst appear unable, on average to correct them. Earnings surprises are rather the norm than the exception as they should be. Stock prices continue to react to forecast errors, although they are somehow expectitable.
- The analyses of forecast erros was incomplete so BST wanted to know In particular, the relative importance of country and industry effects on earning forecast errors. The objective of their analysis was to identify which cahracteristics (all else being equal) are associated with higher than average consensus earning forecast erros and bias.
- The study is the first that simulatneiously tested the impact of country effects, sector influences and other fundamental company characterisitcs on earnings forecast.
Results
- Forecast eeror and forecast optimism increase with dispersion in analyst forecasts and with historical stock return volatiltity. An increase in the number of analysts, all else being equal decreases the forecase eeror. Market cap has not significant impanct on companys concensus earnings forecast accuracy.
- In the past, significant geographical differences existed in earnings forecast accuracy. In particular, analyst focusing on the core Euroland countries of France, Germany and Itlay showed significantly poorer acctucy in earnings forecasts that did analysts focusing on other eurioean countries in the mid 1990s. These geopraohical differences have now broadly disappeard and earnings forecast erroe ni longer reflects any significant country effects.
- Earnings forecast accuracy exhibits significant sector effects: On average, the forecast for the consumer nondurables, health care, public uitlityies and transportation sectors were significantly more correct in the period studied than were those for the other industries These sector effects completely disappeared, however as the forecase horizon shortened.
- One month before the earnings announcement date, only analyst dispersion and stock price volatility remained significantly positively related to forecaset bias.
Implication
- This information will benefit sell side analyst by enabling them to identify which consensus estimates are more likely to be wrong. It will also help investment mangers indentify the companies that have a higher likelihood of being misprices.
- So possible adjustments can be made to
