Professor James Ohlson lecture
Concepts and Practice of Equity Valuation, 6 May 2014
James Ohlson is Professor of Accounting at the New York University Stern School of Business. He has also held faculty positions at Stanford University, University California Berkeley, Columbia University and Arizona State University, and visiting positions at INSEAD, the London School of Economics, National Taiwan University and the Stockholm School of Economics, where he was awarded an Honorary Doctoral Degree.
Prof Ohlson is currently a visiting Chaired Professor at Polytechnic University in Hong Kong and has part-time appointments as an Adjunct Professor at Cheung Kong GSB in Beijing and Manchester Business School in the UK. He holds a Bachelor degree in social sciences and a Master degree in political science from the University of Stockholm, and an MBA and a PhD from UC Berkeley. He has been awarded a Regent Professorship at the Arizona State University and the Chang Jiang Scholar award in China, and from the American Accounting Association (AAA) an Educator of the Year award, a Seminal Contribution award, and two Notable Contributions to the Literature:
- James A. Ohlson (1980),Financial ratios and the probabilistic prediction of bankruptcy, Journal of Accounting Research, vol.18, no.1, pp.109-131 (3237 citations).
- James A. Ohlson (1995), Earnings, book values, and dividends in equity valuation, Contemporary Accounting Research, vol.11, no.2, pp.661-687 (3758 citations).
For a detailed biography see http://people.stern.nyu.edu/johlson/.
Prof James Ohlson's work focuses on the analysis of accounting data particularly within the context of equity valuation. In this lecture he will demonstrate the implementation of equity valuation in practice using data that is publicly available and retrieved from Yahoo!Finance at two recent points in time, April 2013 and March 2014. The approach provides perfectly synchronized data, for about 500 firms, relevant in an equity valuation context. Two broad, interrelated questions are addressed.
First, to what extent does a standard textbook valuation model that focuses on forecasted earnings support the observed actual values? The median of the absolute valuation error is 22%, and it is about the same for the two years. By comparing actual and intrinsic (model) values, one can also forecast the revision in the forecasts of the EPS in the second financial year. That is to say, if a stock 'looks cheap' it often reflects that there is a too optimistic EPS forecast, to be confirmed later on with a downward revision.
Second, does the data support a CAPM approach to determining risk and the valuation model's discount factor? The evidence is generally supportive. Betas correlate materially with PEGs (about 45%), which in turn allows for an estimate of the risk premium (about 4%). Results also show that the model valuation errors correlate positively with the beta risk; valuations of risky stocks tend to be intrinsically more ambiguous. Similar to evidence related to earnings revisions in the second financial year, apparent over-(under-) valuation points toward a potential error in the beta, and thus beta will be revised downward (upward) a year later.
The lecture is of interest to both academics and practitioners, from accounting, finance and related discisplines.
Welcoming drinks are offered from 18:00. Dinner will be served around 18:30. The lecture starts at about 19:00 followed by discussion. The event is concluded at about 21.30.
The lecture will take place at the University of Sydney Business School CBD Campus (building C13B), Level 17, 133 Castlereagh Street, see interactive map.
Reservation is essential by Wednesday 30 April 2014. Places are limited and are booked on a first-come first-served basis following the completion of the online RSVP form.
The event is ajoint initiative between the MEAFA research group (contact: Dr Demetris Christodoulou, MEAFA General Convenor) and the Accounting Foundation (contact: A/Prof Sandra van der Laan, Academic Director of the AF). Administrative enquiries should be directed to firstname.lastname@example.org.