Evaluating the effectiveness of model specifications and estimation approaches for empirical accounting-based valuation models created by Yun Shen and Andrew W. Stark

This study considers the effectiveness of different model specifications and estimation approaches for empirical accounting-based valuation models in the UK. Primarily, we are interested in the accounting determinants of market value and, in particular, whether accounting-based valuation models can be estimated that not only have in-sample explanatory power but also potentially can be used as a tool of financial statement analysis in developing useful estimates of value out-of-sample. This requires models to be estimated on one sample, and tested for effectiveness on a different sample. Then, issues of model specification arise, together with choosing between methods of estimating the empirical models, in identifying the effectiveness of each combination. Using the criteria of bias and accuracy to capture effectiveness, we suggest estimation methods and models that, overall, provide the most effective models in this context.