Quantum computers are not yet up to the task of providing computational advantages for practical stochastic diffusion models commonly used by financial analysts. In this paper we introduce a class of stochastic processes that are both realistic in terms of mimicking financial market risks as well as more amenable to potential quantum computational advantages.
The paper studies the nowcasting of Euro area Gross Domestic Product (GDP) growth using mixed data sampling machine learning panel data regressions with both standard macro releases and daily news data.
Feed supplements have recently been touted as an effective means to reducing methane emissions from livestock (e.g., cattle and sheep). In this paper, we examine the environmental implication of this innovation in a supply chain setting.
As deep learning and big data increasingly shape modern artificial intelligence (AI) tools, it is essential to consider the broader impact of integrating AI into workplaces. While AI applications can optimize processes and improve productivity, their long-term effects on workers’ learning curves and overall performance are still underexplored. This paper investigates the intricate relationship between AI-enabled technology and workers’ learning dynamics through a large-scale randomized field experiment conducted on the Instacart platform.
This paper examines the relation between cognitive perceptions of management and firm valuation. We develop a composite measure of investor perception using 30-second content-filtered video clips of initial public offering (IPO) roadshow presentations. We show that this measure, designed to capture viewers’ overall perceptions of a CEO, is positively associated with pricing at all stages of the IPO (proposed price, offer price, and end of first day of trading).
This paper investigates whether greater competition increases or decreases individual bank and banking system risk. Using a new text-based measure of competition, and an instrumental variables analysis that exploits exogenous variation in bank deregulation, we provide robust evidence that greater competition increases both individual bank risk and a bank's contribution to system-wide risk.
The use of simulation methods is not very common in accounting research, even though several authors have pointed to the advantages these methods offer in addressing accounting research questions. In this position paper, I discuss the difficulties encountered when applying simulation methods in accounting research.
In this paper, we examine how connecting to beneficiaries of one’s work increases performance, and argue that beneficiaries internal to an organization (i.e., one’s own colleague) can serve as an important source of motivation, even in jobs that — on the surface — may seem routine and low on potential impact. We suggest that this occurs because words of beneficiaries strengthen one’s sense of belongingness, a key driver of human behavior.
This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. We find strong evidence for regime changes in the risk-return relation.
This paper examines the impact of NPD make/buy choices on product quality using data from the automobile industry. While the business press laments that NPD outsourcing compromises product quality, there is no systematic evidence to support or refute this assertion.
We have little knowledge about the prevalence of irreproducibility in the accounting literature. To narrow this gap, we conducted a survey among the participants of the 2019 JAR Conference on their perceptions of the frequency, causes, and consequences of irreproducible research published in accounting journals.
The Strategic Management Journal encourages studies using qualitative empirical methods that investigate important research questions and phenomena in order to generate new insights. We believe that qualitative research often provides a means of identifying generalizable patterns concerning important questions in the field of strategic management.
We document that prior portfolio choices influence investors’ expectations about asset values, and their future choices. We find that people update more from information consistent with their prior choices, leading to sticky portfolios over time.
The North Carolina Community College System is faced with a major dilemma: how to reduce the time to degree and increase the community colleges’ success or graduation rates, which system-wide now stands at 30% in four years. This research was designed to gain qualitative insights from a sample of recent graduates, that is, students who managed to graduate in four or fewer years, on critical success factors. From the standpoint of strategy development, we assert that building on success may be more productive than focusing on deficits in improving community college completion rates.
There is growing recognition that justice enactment is a complex activity and that managers face significant contextual and situational roadblocks when attempting to enact justice. However, research has not fully examined how managers, in the course of their jobs, can (a) identify and respond to justice-related issues and (b) assemble and synthesize relevant information required to act in a manner consistent with justice rules.
Except for relatively short but intense episodes of high market risk, average idiosyncratic risk (IR) falls steadily after 2000 until almost the end of our sample period in 2017. The decrease has been such that from 2012 to 2017 average IR was lower than any time since 1965.
In this study, we consider the dynamics of crowdfunding project support over time. We propose that people support crowdfunding projects financially when they believe that their contribution will make an impact. Because perceptions of impact are positively related to goal proximity, we predict that support for a crowdfunding project will increase as the project funding approaches its target goal.
We introduce easy to implement regression-based methods for predicting quarterly real economic activity that use daily financial data. Our analysis is designed to elucidate the value of daily information and provide real-time forecast updates of the current (nowcasting) and future quarters.
We propose a quantile-based measure of conditional skewness, particularly suitable for handling recalcitrant emerging market (EM) returns. The skewness of international stock market returns varies significantly across countries over time, and persists at long horizons.
We introduce a new framework that facilitates term structure modeling with both positive interest rates and flexible time-series dynamics but that is also tractable, meaning amenable to quick and robust estimation. Using both simulations and U.S. historical data, we compare our approach with benchmark Gaussian, stochastic volatility, and shadow rate models, where the latter enforces positive interest rates.