Bitcoin provides its users with transaction-processing services which are similar to those of traditional payment systems. This article models the novel economic structure implied by Bitcoin’s innovative decentralized design, which allows the payment system to be reliably operated by unrelated parties called miners. We find that this decentralized design protects users from monopoly pricing. Competition among service providers within the platform and free entry imply no entity can profitably affect the level of fees paid by users. Instead, a market for transaction-processing determines the fees users pay to gain priority and avoid transaction-processing delays. The article (i) derives closed-form formulas of the fees and waiting times and studies their properties, (ii) compares pricing under the Bitcoin Payment System to that under a traditional payment system operated by a profit-maximizing firm, and (iii) suggests protocol design modifications to enhance the platform’s efficiency. The Appendix describes and explains the main attributes of Bitcoin and the underlying blockchain technology.

This study examines whether a real production activity measure, firm‐level electricity consumption growth, is useful in detecting firm financial misreporting. Identifying proxies for a firm's underlying financial performance that are not a function of the firm's accounting system is essential for detection of misreporting. We propose that the difference between revenue growth and electricity consumption growth (i.e., growth wedge (GW)) is a useful signal of financial misreporting. Using electricity consumption data for Korean firms from 2006 to 2014, we find that the GW is positively associated with discretionary revenues and accruals and the likelihood of financial misreporting as proxied by accounting restatements, qualified audit opinions, and regulatory enforcement actions. The GW provides incremental information over firm characteristics and earnings management signals examined by prior research. Our findings are robust to a battery of additional tests, including within‐firm and industry comparisons that do not require access to cross‐sectional firm‐level electricity data. Overall, our study documents new evidence on the role of a real production activity measure from an independent reporting entity in detecting financial misreporting. Our evidence speaks to the potential usefulness of real activity metrics in forensic economics.

We use brokerage account records to study trading during the Chinese put warrants bubble and find evidence consistent with extrapolative theories of speculative asset price bubbles. We identify the event that started the bubble and show that investors engaged in a form of feedback trading based on their own past returns. The interaction of feedback trading with the precipitating event caused additional buying and price increases in a feedback loop, and estimates of the trading volume due to this mechanism explain prices and returns during the bubble.

On October 26, 2008, Porsche announced a largely unexpected domination plan for Volkswagen. The resulting short squeeze in Volkswagen’s stock briefly made it the most valuable listed company in the world. We argue that this was a manipulation designed to save Porsche from insolvency and the German laws against this kind of abuse were not effectively enforced. Using hand-collected data we provide the first rigorous academic study of the Porsche-VW squeeze and show that it significantly impeded market efficiency. Preventing manipulation is important because without efficient securities markets, the EU’s major project of the Capital Markets Union cannot be successful.

We construct a novel measure of disclosure choice by firms. Our measure is computed using linguistic analysis of conference calls to identify whether a manager's response to an analyst question is a “non‐answer.” Using our measure, about 11% of analyst questions elicit non‐answers from managers, a rate that is stable over time and similar across industries. A useful feature of our measure is that it enables an examination of disclosure choice within a call. Analyst questions with a negative tone, greater uncertainty, greater complexity, or requests for greater detail are more likely to trigger non‐answers. We find performance‐related questions tend to be associated with non‐answers, and this association is weaker when performance news is favorable. We also find analyst questions about proprietary information are associated with non‐answers, and this association is stronger when firm competition is more intense.

Executive bonus plans often incorporate performance measures that exclude particular costs—a practice we refer to as “cost shielding.” We predict that boards use cost shielding to mitigate underinvestment and insulate new managers from the costs of prior executives’ decisions. We find evidence that boards use cost shielding to deter underinvestment in intangibles and encourage managers to take advantage of growth opportunities. We also find that cost shielding tends to be elevated for newly-hired executives, and decreases over tenure. Collectively, our results suggest that boards deliberately choose performance metrics that alleviate agency conflicts.

Cash flow hedge derivatives are an example of an economic transaction that is not fully portrayed in the financial statements in two key ways. First, while changes in the fair value of the derivative are recorded at each reporting date, changes in the value of the underlying purchase or sale commitment are not recorded or disclosed until that transaction occurs. Therefore, until the purchase or sale occurs, the financial statements only portray half of the economic transaction. Second, the gains/losses associated with these derivatives provide an inverse signal about the persistence of firm profitability. We document a method by which financial statement users can partially adjust for these distortions and find evidence that debt investors incorporate information conveyed by cash flow hedge gains/losses into their pricing of new debt issuances. We also find evidence that credit analysts incorporate these adjustments into their firm‐level credit ratings but are unable to find consistent evidence of similar adjustments to credit ratings on new debt issuances. Overall, our results suggest that a subset of sophisticated investors (i.e., those in public debt markets) appear to incorporate information from cash flow hedge accounting into their assessments of firm risk, and that users may benefit from enhanced disclosure about the amount and timing of a firm's future transactions that are exposed to foreign currency, interest rate, or commodity price risk as well as the amount and timing of derivatives that protect the firm from those risks.

We examine how owning a good affects learning and beliefs about its quality. We show that people have more extreme reactions to information about a good they own compared with the same information about a nonowned good: ownership causes more optimistic beliefs after receiving a positive signal and more pessimistic beliefs after receiving a negative signal. Comparing learning to normative benchmarks reveals that people overextrapolate from signals about goods they own, which leads to an overreaction to information; in contrast, learning is close to Bayesian for nonowned goods. We provide direct evidence that this effect is driven by ownership channeling greater attention toward associated information, which leads people to overweight recent signals when forming beliefs. The relationship between ownership and beliefs has testable implications for trade and market expectations. In line with these predictions, we show that the endowment effect doubles in response to positive information and disappears with negative information, and demonstrate a significant relationship between ownership and overextrapolation in survey data about stock market expectations.

Since the global financial crisis, interest rate swap rates, which represent future uncollateralized interbank borrowing, have fallen below maturity-matched Treasury rates. This is surprising, because US Treasuries, which are deemed expensive because of superior liquidity and safety, should produce yields that are lower than those of swap rates. We show, by no-arbitrage, that sovereign default risk explains negative swap spreads even without frictions such as balance sheet constraints, convenience yield, and hedging demand. We support this explanation with an equilibrium model that jointly accounts for macroeconomic fundamentals and the term structures of interest and US credit default swap rates.

Data analytics is transforming our global markets and significantly impacting the financial reporting environment. We investigate how auditors, company managers, and regulation interact with data analytics and one another to affect the diffusion (i.e., development and spread) of data analytics throughout the financial reporting environment. We interview company managers and their audit partners, as well as additional stakeholders, including regulators. We interpret findings from our interviews using theory that highlights the importance of dynamic interactions between people and their environments, which include the prevailing rules (e.g., regulatory guidance). Our findings contribute to the accounting literature and practice by revealing three areas of conflict emerging from stakeholders' disparate preferences for data analytics. First, we uncover growing tensions between managers and audit partners regarding audit fees. Second, we find that managers and auditors believe the lack of accounting regulation specific to data analytics causes confusion and frustration. Finally, auditors report that they strategically leverage data analytics to provide clients with business‐related insights. However, regulators voice concerns that this practice might impair auditor independence and reduce audit quality. These areas of conflict suggest a need to revisit key tensions surrounding the audit function in a contemporary context characterized with significant technological shift.