*Accounting-Based Valuation and "Other Information"—A simultaneous equations approach

• In Event: Accounting's Role in Asset Pricing

Abstract

This paper develops and tests a simultaneous equations model for deriving income forecasts as input for accounting based valuation models. Accounting based valuation models, like the Ohlson (1995) model, are frequently applied in empirical studies. Empirical evidence shows that models using analysts’ forecasts as ‘other information’ in the Ohlson model exhibit a higher explanatory power for market values than models using only historical accounting data. Instead of using analysts’ forecasts we derive forecasts of operating income based on observable data contained in the firms’ reporting, like order backlog, and other publicly available information qualifying as ‘other information’. Due to the interdependencies between the different drivers of operating income, a simultaneous equations model (SEM) is required. When comparing out-of-sample forecasts derived from the SEM with simple benchmark models (autoregressive model, random walk model), we find evidence that in years around economic changes and instability, like the years 2000 and 2009, the SEM produces more accurate forecasts of operating income. In years of stable and continuous development, the SEM and the benchmark models produce similar forecast errors. These results indicate that the application of the more complex model is worthwhile the effort particularly in volatile times in order to increase forecast accuracy. Comparison with analysts’ forecasts of operating income shows no superiority of the SEM, but in volatile times, especially in the year 2009, the SEM’s and analysts’ errors converge. Further, we find that integrating the SEM forecast as ‘other information’ in the Ohlson model increases the explanatory power for current market values and returns compared to simpler versions without ‘other information’ or with direct proxies for ‘other information’.

Authors

• Iris Bergmann, Universität Augsburg

• Wolfgang Schultze, Universität Augsburg