Disclosure Processing Costs and Crash Risk: Evidence from Risk Factor Disclosures

Posted: 23 Jul 2019 Last revised: 13 Nov 2020

See all articles by Leonard Leye Li

Leonard Leye Li

UNSW Australia Business School, School of Accounting

Zihang Ryan Peng

University of New South Wales

Date Written: May 21, 2019

Abstract

We study the relationship between disclosure processing costs and stock price crash risk using the setting of risk factor disclosure (RFD). We posit that, given the high disclosure processing costs of RFDs and differential investors’ information processing abilities, sophisticated investors can deduce more useful information from RFDs than other investors. Therefore, as more information is disclosed in RFDs, larger divergence of opinion arises, foreshadowing higher stock price crash risk. Consistent with this prediction, we find that the amount of information disclosed in a firm’s RFDs is positively associated with its future stock price crash risk. We also document an increase in short-sellers trading activities and divergence of opinions after the filing of 10-Ks with more RFDs. In addition, the positive association between RFDs and crash risk is more pronounced when short sellers face more binding trading constraints and higher arbitrage risks. Finally, we provide evidence that integration costs of RFDs appear to be the main obstacle to disclosure processing. Our findings are related to regulators’ concern about the effectiveness of RFDs and contribute to the literature on stock price crash risk by suggesting that more downside disclosure may not pre-empt future stock price crash risk.

Keywords: Disclosure processing costs, Risk factor disclosure, Stock price crash risk

JEL Classification: D91, G12

Suggested Citation

Li, Leonard Leye and Peng, Zihang Ryan, Disclosure Processing Costs and Crash Risk: Evidence from Risk Factor Disclosures (May 21, 2019). Available at SSRN: https://ssrn.com/abstract=3423472

Leonard Leye Li (Contact Author)

UNSW Australia Business School, School of Accounting ( email )

UNSW Sydney Australia
Sydeney, NSW 2052
Australia

HOME PAGE: http://https://www.unsw.edu.au/staff/leonard-leye-li

Zihang Ryan Peng

University of New South Wales ( email )

Kensington
High St
Sydney, NSW 2052
Australia

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