Annual Conference

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Accounting, Senior Fellows/Fellows

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May 2021

Recent data breach have generated concerns that insiders might use cyber risk related nonpublic information in their trading. Using the staggered adoption of data breach notification laws at the state level, we examine whether mandatory breach disclosure affects insider selling behavior. We find tha...
Keywords: Cybersecurity, Data breach, regulation, Disclosure, insider trading
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Annual Conference

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Accounting

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May 2021

Using a novel dataset containing investors' access of company filings through the SEC's EDGAR system, we show that the abnormal number of IPs searching for firms' financial statements strongly predicts future stock returns and firm fundamentals. A long-short portfolio based on our measure of informa...
Keywords: Information Acquisition, EDGAR Search, SEC Filings
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Annual Conference

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Accounting

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May 2021

This study examines the role of the Securities and Exchange Commission (SEC) in mergers and acquisitions (M&As) involving publicly traded target firms. We find that deals receiving comment letters have an increased likelihood of deal completion and deal price revision, consistent with the SEC re...
Keywords: Information transparency, M&A, SEC, Comment letters, Shareholder welfare, Corporate governance, Deal outcomes
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Annual Conference

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Accounting

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May 2021

We examine the effect of cultural heterogeneity on corporate disclosure time orientation and its capital market consequences. To measure firms’ and investors’ cultural time orientation, we use their home country’s long-term orientation (LTO) and the dominant language future time reference (FTR...
Keywords: Cultural heterogeneity, capital market, liquidity, equity
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Annual Conference

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Accounting

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May 2021

We introduce the Minimum Description Length (MDL) principle in performing tasks of pattern recognition and anomaly detection in bookkeeping data. MDL principle underlies many machine learning applications in practice, especially in unsupervised settings. We report and summarize recently developed MD...
Keywords: Pattern Recognition, Anomaly Detection, Bookkeeping, Minimum Description Length Principle, machine learning, Graph mining
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