Additional Evidence on the Incremental Information Content of Cash Flows and Accruals: The Impact of Errors in Measuring Market Expectations.
发现基于历史序列和交叉依赖关系的市场预期代理变量比随机游走模型更准确，且能检测到经营现金流相对于应计项目的更高估值，这种差异在随机游走模型中无法发现。
Abstract This study evaluates the relation between security returns and funds-based earnings components. We document that proxies for market expectations of the components that are based on measures of historical serial- and cross-dependencies are substantially more accurate than random-walk proxies. Moreover, we detect significantly higher valuations of the operating cash flow component of earnings, relative to current accruals, when market expectations are represented using the dependency-based predictions. Such differential valuation is not detectable for random-walk representations. Contrary to results in Ali (1994), we find incremental information in unexpected cash flows over the whole spectrum (moderate and extreme) of unexpected cash flow realizations.