Oswald, D, Francis, J and Olsson, P (2000) Using mechanical earnings and residual income forecasts in equity valuation. Working Paper. London Business School Accounting Working Paper.
Abstract
We document the reliability of value estimates based on forecasts from firmspecific mechanical models of residual income and of earnings. Reliability refers to the signed and absolute deviation between value estimates and observed market prices, and to the ability of value estimates to explain variation in prices (or the ability of bookscaled value estimates to explain variation in markettobook ratios). For a large sample of firms over 19761997, we find that firmspecific timeseries models of residual income generate estimates of intrinsic values which are significantly less biased, at least as accurate, and explain at least as much, if not significantly more, of the variation in observed prices and markettobook ratios than do value estimates based on firmspecific time series models of earnings or value estimates based on book value of equity alone. For a sample of firms followed by analysts over 19811997, we compare mechanicalbased residual income value estimates with analystbased value estimates. Analystbased value estimates are significantly less biased, but are not more accurate and do not explain more of the variation in prices than mechanical residual income value estimates. The result that firmspecific models of residual income generate relatively reliable measures of intrinsic value differs from prior studies which assume constant persistence and find that mechanicalbased residual income value estimates do not improve on book values alone (Dechow, Hutton and Sloan [1999]) and are dominated by analystbased value estimates (Frankel and Lee [1998]). We show that the difference in results is due to relaxing the assumption that the persistence in residual income is an overtime and crosssectional constant.
More Details
Item Type: | Monograph (Working Paper) |
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Subject Areas: | Accounting |
Date Deposited: | 05 Sep 2023 15:12 |
Last Modified: | 12 Sep 2023 23:52 |
URI: | https://lbsresearch.london.edu/id/eprint/3189 |
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