n Investment Analysts Journal - Modelling systematic risk and return using accounting-based information
|Article Title||Modelling systematic risk and return using accounting-based information|
|© Publisher:||Taylor & Francis|
|Journal||Investment Analysts Journal|
|Author||M. Bergesen and M. Ward|
|Publication Date||Jan 1996|
ISI Social Science
The study explored the linkages between the financial parameters of a firm derived from reported accounting data, and systematic risk as described by estimated market beta coefficients. The relationships between financial variables and risk proposed by previous theoretical and empirical research were tested for 135 JSE-listed Industrial companies, in each of three consecutive 5-year periods. Correlation analysis and stepwise multiple regression were used to establish significant explanatory beta models. Strong positive associations with risk were found for measures of firm growth, profitability, leverage and the variabilities of earnings and cashflows. Significant negative relationships emerged for liquidity, stock turnover and dividend yield. <br>Secondly, the linkages between the same financial parameters and observed equity returns were tested in a multifactor asset-pricing model for the same sample. Measures of firm growth, profitability and size were positively correlated to share returns, while the variabilities of earnings and cashflows as well as debtors' collection period were negatively related. <br>For both betas and equity returns, correlations with financial parameters improved for portfolios of shares. Several of the significant financial variables were derived from cashflow-based data, as opposed to standard accrual-accounting values. While significant regression models emerged for risk and return in each of the 5-year analysis periods, they were non-stationary across the periods. Consequently, fairly poor predictive performance was observed for the models over consecutive time intervals. Nevertheless, it was apparent that certain classes of fundamental financial data were strongly related to beta as a measure of systematic risk, and to ex post share returns.
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