過去有關預測系統性風險的研究，最常見的議題不外乎是用何種預測模式對何種產業或經濟個體有較佳的預測性，抑或是系統性風險與會計變數之間的關聯性。然而，無論是使用實際β去預測未來系統性風險，或是利用會計資訊去預測系統性風險。每種預測模式都含有對預測有用之資訊，因此，本研究利用市場模式與會計估計方法所組合而成的混合基礎模型，並以1976至2010年美國上市公司為研究樣本，去探討會計資訊是否對於預測系統性風險具有增額效果。實證結果顯示，多數會計變數在未受到總體經濟變動狀況下，與系統性風險之間的關聯性與預期方向相同，與先前文獻一致。而在混合基礎模型以及單變量迴歸檢定下，發現的確可單獨藉由具有潛在影響力的會計資訊去預測系統性風險，但若要透過會計資訊的輔助提高預測力，會計資訊增額輔助效果則是相較有限的。 In the past, a common issue with systematic risk prediction is which method better predicts systematic risk in industry and economic identity, or the relevance between systematic risk and accounting variables. However, both market-based forecasts and accounting information each contain some useful information for the prediction of systematic risk. Hence, this paper uses a composite forecast model, which combines both methods to investigate the additional effect on predicting systematic risk by accounting information with listed companies in United States from 1976 to 2010. The study shows most variables’ expectation signs would not change under general economic conditions, consistent with previous research. Under the examination of composite forecasts model and univariate regression, we can predict systematic risk by potential accounting information. However, the incremental forecasting effect of accounting information is limited.
