Could real‐time big data help unravel material firm events? How would it compare with firm disclosure and traditional media in terms of timeliness and completeness? Could big data provide incremental value‐relevant information for investors? With these questions in mind, we use a novel data set of cell phone “pings” (i.e., geolocation signals from mobile devices) to track production disruptions (outages)––material events for U.S. oil refineries. We first validate the construct by examining the effects of outages on local gas prices and firms’ accounting performance. Our main analyses show that (1) refining firms do not voluntarily disclose refinery outages identified by cell phone pings; (2) traditional media cover only a small portion of ping‐based outages; (3) the stock market finds ping‐based outages to be value relevant but incorporates the information with delay. Further analysis suggests that given the incomplete media coverage and lack of firm disclosure, investors appear to learn the financial impact of such outages through subsequent earnings announcements. Our evidence has implications for regulators such as the U.S. Energy Information Administration and the Securities and Exchange Commission as they continue to evaluate both the compliance and usefulness of disclosures for material firm events such as production disruptions.

In December 2004, the Financial Accounting Standards Board (FASB) mandated the use of a fair value–based measurement attribute to value employee stock options (ESOs) via Financial Accounting Standard (FAS) 123‐R. In anticipation of FAS 123‐R, between March 2004 and November 2005, several firms accelerate the vesting of ESOs to avoid recognizing existing unvested ESO grants at fair value in future financial statements. We find that the likelihood of accelerated vesting is higher if (1) acceleration has a greater effect on future ESO compensation expense, especially related to underwater options, and (2) firms suffer greater agency problems, proxied by fewer blockholders, lower pension fund ownership, and top five officers holding a greater share of ESOs. We also find a negative stock price reaction around the announcement of the acceleration decision. Furthermore, stock returns are significantly negative before the new vesting dates and positive afterward, suggesting that vesting dates could have been backdated.

We show that network advantages constitute an important intangible asset that goes unrecognized in the financial statements. For a sample of e–commerce firms, we find that network advantages created by Web site traffic have substantial explanatory power for stock prices over and above traditional summary accounting measures such as earnings and book value of equity. Also, network advantages are positively associated with one–year–ahead and two–year–ahead earnings forecasts provided by equity analysts. When we allow network advantages to be endogenously determined by managerial actions, we find that at least part of the value relevance of network effects stems from the presence of affiliate referral programs and higher media visibility.

In this study we investigate the valuation implications of managerial actions undertaken by 57 Internet firms engaged in Business‐to‐Business (B2B) e‐commerce. We classify 3,007 managerial actions undertaken by our sample firms between the firm’s IPO date and September 30, 2000 into nine action categories: (1) acquisition of major customers, (2) introduction of new products and services, (3) promotional and marketing actions, (4) actions taken to address the concerns of stakeholders such as employees and the community at large, (5) announcements of technology, marketing, and distribution alliances, (6) completion of acquisitions, (7) expansion into international markets, (8) management team building actions, and (9) organizational changes. In the short window tests, we find a significant increase in stock price volatility over a three‐day event window surrounding the announcement of almost all actions suggesting that announcement of managerial actions provides value‐relevant information to the stock market. In the long window tests, we use factor analysis to group the counts of managerial actions taken by each firm over its post‐IPO life into two broad managerial initiatives—market penetration and organization building. These two initiatives explain a substantial portion of the cross‐sectional variation in the firms’ post‐IPO life stock market returns beyond that explained by both reported earnings and analysts’ forecasts of future earnings and revenues. Thus, investors appear to supplement relatively meager accounting information with data about the cross‐sectional intensity of managerial actions in setting stock prices of B2B Internet firms.

We examine whether vocal markers of cognitive dissonance are useful for detecting financial misreporting. We use speech samples of CEOs during earnings conference calls, and generate vocal dissonance markers using automated vocal emotion analysis software. We begin by assessing construct validity for the software‐generated dissonance markers by correlating them with four dissonance‐from‐misreporting proxies obtained in a laboratory setting. We find a positive association between these proxies and vocal dissonance markers generated by the software, suggesting the software's dissonance markers have construct validity. Applying the software to CEO speech, we find that vocal dissonance markers are positively associated with the likelihood of irregularity restatements. The diagnostic accuracy levels are 11% better than chance and of similar magnitude to models based solely on financial accounting information. Moreover, the association between vocal dissonance markers and irregularity restatements holds even after controlling for financial accounting and linguistic‐based predictors. Our results provide new evidence on the role of vocal cues in detecting financial misreporting.

We experimentally study the deception detection capabilities of experienced auditors, using CEO narratives from earnings conference calls as case materials. We randomly assign narratives of fraud and nonfraud companies to auditors as well as the presence versus absence of an instruction explaining that cognitive dissonance in speech is helpful for detecting deception. We predict this instruction will weaken auditors’ learned tendency to overlook fraud cues. We find that auditors’ deception judgments are less accurate for fraud companies than for nonfraud companies, unless they receive this instruction. We also find that instructed auditors more extensively describe red flags for fraud companies and more accurately identify specific sentences in narratives that pertain to underlying frauds. These findings indicate that instructing experienced auditors to be alert for cognitive dissonance in CEO narratives can activate deception detection capabilities.