Liu Yang

Misstatement Detection Lag and Prediction Evaluation

Liu Yang, Min Zhu

ABSTRACT Accounting misstatements are often detected with substantial delays, leading to “look-ahead bias” in model predictions if the detection lag is not considered. Moreover, the misstatement data-generating process is evolving due to regulatory regime shifts, further complicating the evaluation of model predictions. …

us, au (code pays fourni par la source)

Home-Country Geopolitical Risk and the Valuation of U.S. Foreign Private Issuers

Joanna Golden, Douglas J. Cumming, Michael Imhof, Liu Yang

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Government procurement and corporate investment efficiency: Evidence from China

Liu Yang, Ran Li

cn (code pays fourni par la source)

Zijing Storage Financial Fraud Case Analysis - Audit Risk Prevention for Listed Companies

Yu Song, Liu Yang

Zijing Storage, as a company listed on the Science and Technology Innovation Board, originally enjoyed a high reputation in the industry for its research and development, design, and development of core technologies for Blu-ray data storage systems, as well as the production, …

cn (code pays fourni par la source)

The opportunities and challenges of generative AI for the development of the accounting Industry

Liu Yang

Against the backdrop of rapid information technology development, generative AI technology has become a key driver in advancing the accounting industry. This paper discusses the opportunities that generative AI, represented by ChatGPT, brings to the accounting industry. These opportunities include driving workflow …

Influencer Marketing on Instagram and TikTok: Entertainment or Deception?

David A. Hyman, David J. Franklyn, Liu Yang, Mohammad Hossein Rahmati

us, ir (code pays fourni par la source)

Government Procurement and Corporate Investment Efficiency: Evidence from Alternative Data in China

Liu Yang, Ran Li

cn (code pays fourni par la source)

Information Transparency and Investment in Follow‐on Innovation*

Jeff Zeyun Chen, Yongtae Kim, Liu Yang, Joseph H. Zhang

ABSTRACT This study examines the role of information transparency in facilitating peer firms' investment in follow‐on innovation. We capture information transparency with both textual and numerical information disclosed in 10‐Ks. Using patent citations to proxy for investment in follow‐on innovation, we predict …

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How do auditors respond to client firms’ technological peer pressure? Evidence from going‐concern opinions

Xiaolu Xu, Liu Yang, Joseph H. Zhang

Abstract We examine whether auditors consider financially distressed clients’ technological peer pressure (TPP) in their going‐concern assessments. While auditing standards highlight the importance of understanding the competitive environment in risk assessments and going‐concern assessments, it is not clear whether and to what …

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Detecting Accounting Fraud with Noisy Labels

Daniel Ahfock, Geoffrey John McLachlan, Liu Yang, Min Zhu

au, us (code pays fourni par la source)

Initial Evidence on the Market Impact of the iXBRL Adoption

Xin Luo, Tawei Wang, Liu Yang, Xinlei Zhao

SYNOPSIS In June 2018, the SEC adopted Inline eXtensible Business Reporting Language (iXBRL), which embeds XBRL data into HTML-formatted annual reports to improve the accessibility and usefulness of the information disclosures to investors. This study assesses the effectiveness of iXBRL by examining …

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Corporate innovation and future earnings: does early patent disclosure matter?

Liu Yang, Joe Zhang

Abstract This study investigates how pre‐grant patent disclosures required by the American Inventors Protection Act (AIPA) affect the value of innovation. The accelerated disclosures instituted by the AIPA may benefit innovative firms by either reducing duplicative R&D projects or by facilitating prompt, …

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