Bridging the gap between stock price and bottom-line accounting numbers

Abstract

We develop a method for extracting ‘other information’ from the articulation between bottom-line accounting numbers and stock prices. We posit that ‘other information’ captures future earnings growth originating from conservative accounting recognition principles as demonstrated by Penman and Zhang (2020) and Penman and Zhu (2022), as well as nonzero net present value investment opportunities. Our findings confirm that ‘other information’ is strongly associated with various proxies for expected future earnings growth and firm risk attributes. Furthermore, we show how a structural expected return model incorporating our ‘other information’ estimates can predict out-of-sample future stock returns and generate sizeable long-short return spreads.