SearcharxivSearch

arXiv · 2410.13878

Damages and Materiality: Effects on voluntary disclosure

Abstract

How should a court resolve a shareholder--management dispute following a materially significant price decline when it is suspected that management, at an earlier point in time, failed to update the market by disclosing a privately observed material event? A foundational result in this literature (Dye, 2017) shows that if a court publicly commits to increasing damages awards in an effort to deter nondisclosure, the policy may have a perverse effect: management may rationally choose to disclose even less. Schantl and Wagenhofer (2024) attribute this outcome to the pure insurance effect, whereby shareholders benefit from higher damages payments. They show that this result may be mitigated if management also face a fixed, exogenous reputational cost of nondisclosure. However, these reputational costs are independent of the model's equilibrium; furthermore, they assume that the court eventually observes the true state of the world with certainty (delayed omniscience by the court), and do not account for standards of materiality, which differ across legal systems. In contrast, we develop a dynamic continuous-time model in which both damages and materiality standards are endogenous. We show that, as damages awards increase, a previously unrecognized dynamic effect emerges: management rationally switch to a candid (full) disclosure strategy. Moreover, raising the materiality threshold induces this switch earlier, thereby increasing the extent of voluntary disclosure. Our analysis therefore demonstrates that regulators should recognize the complementary effects of damages and materiality standards. We further characterize what we term the legal consistency zone, in which higher damages awards, coupled with an appropriately chosen materiality standard, endogenously increase voluntary disclosure.

Explore related subjects

Keep this discovery

BibTeXRIS

Miles B. Gietzmann, Adam J. Ostaszewski. 2024-10-02. Damages and Materiality: Effects on voluntary disclosure. https://arxiv.org/abs/2410.13878

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

AI for AI: Optimizing Additional Infrastructure Build-out to Power Artificial Intelligence Data Centers

The twenty-first century's transformative technology, artificial intelligence, is increasingly constrained by the twentieth century's transformative technology, the electricity grid. Rapid growth in electricity demand from data centers is leading to higher electricity prices, without a compensating supply-side response. We develop a framework linking data-center load growth, available generation capacity, and market-clearing prices to understand this phenomenon. We first analyze a deterministic model to show how differing estimates of demand and supply growth rates affect prices. We then model the expansion of new data centers and their associated electricity demand, together with build-outs of new electricity supply, as stochastic processes,resulting in probabilistic distributions of supply, demand, and prices rather than a single forecast. Finally, we formulate generation expansion as a stochastic control problem in which a revenue-maximizing investor dynamically chooses the intensity of supply-side investments. The analysis highlights a central challenge of the data-center build-out: even when rapid demand growth increases the need for new generation, the uncertainties related to load forecasts, development execution risks, and value cannibalization from overbuilding capacity may weaken incentives to invest at the pace required to keep electricity prices stable.

q-fin.GN

Measuring DeFi Risk

Decentralized finance (DeFi) lending has grown from nonexistent in 2017 to nearly 40 billion US Dollars in deposited funds in May 2022. Using cryptocurrency as collateral, the platforms match speculative margin trading with yield-seeking depositors lending coins pegged to the dollar (stable coins). Depositors receive claims guaranteed by a basket of collateral, akin to new stable coins. We develop a framework requiring only knowledge of aggregate deposits and borrowings to measure overall system risks to lenders and borrowers. Using evidence from major protocols, the measures identify an increase in system fragility beyond prudent levels around mid 2021, with a potential loss of peg for extreme variations in coin prices. Overall, the model offers an easily implementable aggregate risk metric capturing the perspectives of synthetic investors and offers early warning signals as the industry is moving from deposits guaranteed by collateral to fiat money.

q-fin.GN

Historical Reflections on Interest Rates and the Emergence of the Yield Curve

This text grew out of a historical introduction initially written for a study of interest rates in cryptocurrency markets. The difficulty of defining a term structure for a currency without a conventional bond market led naturally to a more fundamental question: under what historical conditions does a yield curve become observable at all? Credit existed long before modern money, and interest-bearing loans are documented as early as ancient Mesopotamia. For much of history, the surviving evidence lacks the institutional features that facilitate reliable comparisons of interest rates by maturity: standardised debt instruments, sufficiently homogeneous borrowers, regular issuance over a range of maturities, observable market prices, and liquid secondary markets. We trace the gradual emergence of these conditions from ancient Mesopotamia, Greece, and Rome, through medieval and early modern Europe, to the development of modern sovereign debt markets in the nineteenth and twentieth centuries.

q-fin.GN