Performance of forward-looking value drivers in stock screening: making automated recommendations based on future forecasts

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dc.contributor Aalto University en
dc.contributor Aalto-yliopisto fi Puro, Lauri 2011-11-14T11:23:15Z 2011-11-14T11:23:15Z 2009
dc.description.abstract PURPOSE OF THE STUDY The purpose of this study is to analyze different value drivers and their capability of explaining future stock returns. The value drivers are evaluated based on their performance using backward- and forward-looking data. The forward-looking value drivers are tested both with perfect foresight, i.e. actual future fundamentals, and with analyst forecasts. The main objective is to find the best value drivers that can be used to create automatic stock recommendations based on future forecasts. Finally, the performance of these auto-recommendations is compared against the performance of analysts’ own consensus stock recommendations. DATA In this study, the US stock market data is used as the primary source of data. The data is gathered from Compustat and CRSP databases and it covers years 1975-2007. In total, the sample consists of 98,688 company-year combinations. The average number of stocks in a single year is 2,990. This data is complemented with equity analyst forecasts and recommendations gathered from I/B/E/S database. RESULTS The main finding of this study is that the P/E ratio and to some extent the PEG ratio are good forward-looking value drivers that provide significant stock screening potential when applied to earnings forecasts of good quality. However, when applying analyst consensus forecasts these value drivers do no result in significantly better performance than using only backward-looking value drivers with historical financial figures. Despite the relatively low performance in absolute terms the auto-recommendations made with the value driver approach outperform significantly the consensus recommendations of the analysts. As a conclusion, investors and analysts would be better off making recommendations based on systematic value drivers rather than the current ad-hoc methods. fi
dc.format.extent 87
dc.format.mimetype application/pdf en
dc.language.iso fi en
dc.title Performance of forward-looking value drivers in stock screening: making automated recommendations based on future forecasts fi
dc.type G2 Pro gradu, diplomityö fi Kauppakorkeakoulu fi School of Economics en
dc.contributor.department Department of Accounting and Finance en
dc.contributor.department Laskentatoimen ja rahoituksen laitos fi
dc.subject.keyword value drivers
dc.subject.keyword stock screening
dc.subject.keyword analyst forecasts
dc.subject.keyword perfect foresight
dc.subject.keyword auto-recommendations
dc.identifier.urn URN:NBN:fi:aalto-201111181152
dc.type.dcmitype text en
dc.programme.major Finance en
dc.programme.major Rahoitus fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Pro gradu tutkielma fi
dc.subject.helecon rahoitus
dc.subject.helecon financing
dc.subject.helecon osakkeet
dc.subject.helecon shares
dc.subject.helecon arviointi
dc.subject.helecon evaluation
dc.subject.helecon ennusteet
dc.subject.helecon forecasts
dc.ethesisid 12108 2009-06-15
dc.location P1 I

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