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The Pricing of Accruals Quality with Expected Returns: Vector Autoregression Return Decomposition Approach

The Journal of Industrial Distribution & Business / The Journal of Industrial Distribution & Business, (E)2233-5382
2020, v.11 no.3, pp.7-17
https://doi.org/https://doi.org/10.13106/jidb.2020.vol11.no3.7
YIM, Sang-Giun

Abstract

Purpose: This study reexamines the test on the pricing of accruals quality. Theory suggests that information risk is a priced risk factor. Using accruals quality as the proxy for information risk, researchers have tested the pricing of information risk. The results are inconsistent potentially because of the information shock in the realized returns that are used as the proxy for expected returns. Based on this argument, this study revisits this issue excluding information-shock-free measure of expected returns. Research design, data and methodology: This study estimates expected returns using the vector autoregression model. This method extracts information shocks more thoroughly than the methods in prior studies; therefore, the concern regarding information shock is minimized. As risk premiums are larger in recession periods than in expansion periods, recession and expansion subsamples were used to confirm the robustness of the main findings. For the pricing test, this study uses two-stage cross-sectional regression. Results: Empirical results find evidence that accruals quality is a priced risk factor. Furthermore, this study finds that the pricing of accruals quality is observed only in recession periods. Conclusions: This study supports the argument that accruals quality, as well as the pricing of information risk, is a priced risk factor.

keywords
Vector Autoregression, Return Decomposition, Accruals Quality, Cost of Equity

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The Journal of Industrial Distribution & Business