Time-series properties and predictive ability of quarterly cash flows

We provide descriptive and predictive evidence on the time-series properties and predictive ability of quarterly cash flows from operations (CFO) reported in accordance with Statement of Financial Accounting Standards (SFAS) No. 95. Previous work such as Hopwood and McKeown [Hopwood, W.S., & McKeown, J.C., (1992). Empirical evidence on the time-series properties of operating cash flows. Managerial Finance, 18, 62-78] and Lorek, Schaefer and Willinger [Lorek, K.S., Schaefer, T.F., & Willinger, G.L., (1993, January). Time-series properties and predictive ability of funds flow variables.” The Accounting Review, 68, 151-63], among others, has analyzed a proxy series (PCFO) for quarterly cash flows constructed via a relatively simplistic algorithm. We provide new evidence documenting that: (1) the time-series properties of quarterly CFO are at variance with the exclusively seasonal characterization of quarterly PCFO exhibiting both adjacent (quarter-to-quarter) and seasonal (quarter-by-quarter) relationships, (2) the Brown-Rozeff ARIMA model significantly outpredicts the random walk with drift model, seasonal random walk with drift model, and a disaggregated-accrual model, the multivariate time-series regression model (MULT) originally popularized by Lorek and Willinger [Lorek, K.S., & Willinger, G.L., (1996, January). A multivariate time-series prediction model for cash-flow data. The Accounting Review, 71, 81-101], (3) the forecast errors of larger firms are significantly smaller than the forecast errors of smaller firms, and (4) the predictive ability of the Brown-Rozeff model is robust when tested upon an expanded sample of firms (n = 745; 8940 firms/quarter predictions) obtained by eliminating the considerable data requirements of MULT.