This paper aims to examine the contemporary association between accounting information and a number of measures of systematic (beta) risk that incorporate dynamic market features. The goal is to determine the fundamental accounting drivers of beta and to assess whether their explanatory variable power has changed or declined over time.
Beta estimates are calculated using adjustments for thin‐trading, central tendency, leverage, and time variance. Accounting risk variables are derived from theoretical foundations and prior empirical research, and classified as operating, financial or growth.
Results show a strong association between accounting variables (operating and growth) and systematic risk that is consistent over time, but with some industry and size differences and possible country effects. Accounting variables are able to capture dynamic risk shifts and generally are able to outperform naïve M‐GARCH and industry betas in predicting next year's systematic risk.
Internal management and external decision making enable the development of more efficient ex‐post risk measures, isolating actual risk determinants rather than just determining the level of risk, overcoming the problem that conventional ex‐post measures cannot be used for non‐listed entities, initial public offering firms, or those that do not have sufficient trading history, reduces the noise found in traditional risk estimates that rely on historical security returns, and the development of trading and valuation strategies.
This is the first paper that assesses the association between a range of dynamic risk measures and accounting variables and tests whether this long‐run association has changed over time.
