Download this Paper Open PDF in Browser

The Asymmetric Market Valuation of Nonrecurring Items and Accounting Conservatism

23 Pages Posted: 15 May 2011 Last revised: 19 Jul 2011

Richard Zhe Wang

Eastern Illinois University

Madeline Kay Trimble

University of Mannheim

Date Written: May 13, 2011


This paper investigates the asymmetric market valuation of negative and positive nonrecurring items as explained by accounting conservatism. We argue that special items, also known as nonrecurring operating gains and losses, have asymmetric market valuations, as proxied for by the earning response coefficient (ERC). This paper has two main findings: (1) an asymmetry exists in the valuation of positive and negative special items; and (2) the asymmetry can be explained by the idea of accounting conservatism, which is the tendency that firms report economic losses on a timelier basis than economic gains. The above two findings are supported by our empirical tests, which show that negative special items are more value relevant (i.e. have a higher ERC) than positive ones due to the fact that nonrecurring losses are impounded in earnings much quicker than nonrecurring gains. Thus, negative and positive special items are not valued equally by investors - an asymmetry exists. Furthermore, as the level of conservatism increases within a firm, this asymmetry of market valuation becomes larger, signifying that the value relevance of negative special items increases at a rate greater than that of positive special items.

Keywords: special items, value relevance, accounting conservatism, C-Score

JEL Classification: M40, M41

Suggested Citation

Wang, Richard Zhe and Trimble, Madeline Kay, The Asymmetric Market Valuation of Nonrecurring Items and Accounting Conservatism (May 13, 2011). Available at SSRN: or

Richard Zhe Wang (Contact Author)

Eastern Illinois University ( email )

Charleston, IL 61920-3099
United States

Madeline Kay Trimble

University of Mannheim ( email )

Universitaetsbibliothek Mannheim
Mannheim, 68131

Paper statistics

Abstract Views