The nature, causes and consequences of financial analysts’ forecasts in the UK

This thesis consists of three empirical chapters that investigate the nature, reasons and consequences of financial analysts’ forecasts in London Stock Exchange. The first empirical chapter examines the rationality and accuracy of financial analysts’ forecasts. Results show that analyst forecasts are overall optimistic, but not as extreme as the literature suggests. However, analysts seem to converge to a more rational position the closer they get to the announcement date. Despite no evidence of relationship is found between forecast error and prior year change in earnings per share, analysts are believed to be systematically revising their forecasts downwards as the time approaches the earnings’ announcement date. The second empirical chapter attempts to study the factors that contribute to the forecast error and in particular earnings management. Results show that earnings management positively affects the magnitude of the forecast error, that is, when earnings are manipulated the forecast error appears to be bigger. However, this positive impact appears to be driven by accruals earnings management and not by real earnings management. Moreover, forecasts seem to be more optimistic for companies that manage their earnings downwards through accruals. These findings reveal that analysts may not be as biased as the literature claim, instead, they are probably victims of earnings management. The third empirical chapter examines whether financial analysts’ forecast is a major component of market sentiment and tests how this contribution can affect cross sectional returns. Results confirm that analysts releasing higher than average earnings per share forecasts lead to higher sentiment levels. Inconsistent with previous literature, short term stock returns are significantly positively affected by sentiment levels, but growth stocks appear to be more sensitive to shifts in sentiment than value stocks.

Level dc:type.qualificationlevel

PhD thesis

Grantor dc:publisher.institution

Middlesex University

Year dc:date.issued

2018

Author dc:creator

• Baher, O.

Identifier

oai:repository.mdx.ac.uk:879y8

OAI identifier oai:identifier

oai:repository.mdx.ac.uk:879y8