TY - JOUR
T1 - The time series properties of financial ratios
T2 - Lev revisited
AU - Ioannidis, Christos
AU - Peel, David A.
AU - Peel, Michael J.
PY - 2003/6
Y1 - 2003/6
N2 - This paper re-evaluates the time series properties of financial ratios. It presents new empirical analysis which explicitly allows for the possibility that financial ratios can be characterized as non-linear mean-reverting processes. Financial ratios are widely employed as explanatory variables in accounting and finance research with applications ranging from the determinants of auditors’ compensation to explaining firms’ investment decisions. An implicit assumption in this empirical work is that the ratios are stationary so that the postulated models can be estimated by classical regression methods. However, recent empirical work on the time series properties of corporate financial ratios has reported that the level of the majority of ratios is described by non-stationary, I(1), integrated processes and that the ratio differences are parsimoniously described by random walks. We hypothesize that financial ratios may follow a random walk near their target level, but that the more distant a ratio is from target, the more likely the firm is to take remedial action to bring it back towards target. This behavior will result in a significant size distortion of the conventional stationarity tests and lead to frequent non-rejection of the null hypothesis of non-stationarity, a finding which undermines the use of these ratios as reliable conditioning variables for the explanation of firms’ decisions.
AB - This paper re-evaluates the time series properties of financial ratios. It presents new empirical analysis which explicitly allows for the possibility that financial ratios can be characterized as non-linear mean-reverting processes. Financial ratios are widely employed as explanatory variables in accounting and finance research with applications ranging from the determinants of auditors’ compensation to explaining firms’ investment decisions. An implicit assumption in this empirical work is that the ratios are stationary so that the postulated models can be estimated by classical regression methods. However, recent empirical work on the time series properties of corporate financial ratios has reported that the level of the majority of ratios is described by non-stationary, I(1), integrated processes and that the ratio differences are parsimoniously described by random walks. We hypothesize that financial ratios may follow a random walk near their target level, but that the more distant a ratio is from target, the more likely the firm is to take remedial action to bring it back towards target. This behavior will result in a significant size distortion of the conventional stationarity tests and lead to frequent non-rejection of the null hypothesis of non-stationarity, a finding which undermines the use of these ratios as reliable conditioning variables for the explanation of firms’ decisions.
UR - https://onlinelibrary.wiley.com/doi/10.1111/1468-5957.05201
U2 - 10.1111/1468-5957.05201
DO - 10.1111/1468-5957.05201
M3 - Article
SN - 0306-686X
VL - 30
SP - 699
EP - 714
JO - Journal of Business Fnance and Accounting
JF - Journal of Business Fnance and Accounting
IS - 5-6
ER -