The current paper focuses on how multiple values shape accounting and accountability practices in hybrid organizations. It concentrates on the complex domain of academic spin-offs, more fully described as hybrid knowledge-intensive organizations, aiming to understand how accounting and accountability practices can be constitutive of hybrid academic entrepreneurial logics and identities and how these

This study investigates whether corporate tax avoidance can benefit shareholders when external capital market frictions are high. Using the TED spread as an exogenous shock to firm financial constraint, the study documents that firms tend to reduce their effective tax rates more aggressively when external financing is very costly. This negative relation is stronger in industries more sensitive to TED

Recently, the art market has proposed the trading of NFTs. We focus on these research questions: a) does the increase in the value of cryptocurrencies affect the value of NTFs; b) does the interest of public opinion influence the value of NFTs. We apply causality and spill-over analyses to determine relationships and answers to our research questions. We find that NFTs present peculiar dynamics, unrelated

Bitcoin remains the most popular cryptocurrency and has attracted significant research attention, especially in the hedging and safe-haven literature. As many investors in bitcoin are concentrated heavily in cryptocurrencies as opposed to other assets, a question arises whether alternative cryptocurrencies (altcoins) can used as safe-havens and hedges against Bitcoin? We find that only meme coins offer

We analyze the prospect of cryptocurrency regulation affects cryptocurrency prices, volatility and trading using the Google Trend technique to construct the Crypto Regulation Sentiment Index (CRSX) reflecting investors’ attitude towards Crypto regulation. Our analysis encompasses over 75% of the crypto market's daily activity. We find CRSX has no statistically significant long-term impact on cryptocurrency

Jondeau et al. (2020) find evidence that average stock return skewness predicts stock market returns. Although this evidence is consistent with asset pricing theory, we are not able to replicate this result on a broad sample of stock returns taken from the well-developed euro area stock markets. Nor does accounting for potential slower information dissemination or using two alternative skewness estimators

This paper investigates whether the global financial cycle (GFC) contributes to the bubble-like dynamics in international house prices. Using the recursive unit-root procedure of Philips et al. (2015a, b), we establish a timeline of episodes of housing markets’ exuberance for a panel of 24 countries. Next, we examine the predictive ability of six variables characterizing the GFC as suggested by Miranda-Agrippino

We examine the drivers of Bitcoin volatility and discuss possible future developments, specifically what conditions need to be met for the volatility to decrease. Our instrumental variables analysis implies there needs to be a considerable inflow of small users into the system who are ideally not exchange traders and they do perform small transfers. Increasing exchange volume, on-chain transfers value

We quantitatively describe the main events that led to the Terra project’s failure in May 2022. We first review, in a systematic way, news from heterogeneous social media sources; we discuss the fragility of the Terra project and its vicious dependence on the Anchor protocol. We hence identify the crash’s trigger events, analysing hourly and transaction data for Bitcoin, Luna, and TerraUSD. Finally

Many U.S. private firms choose either a financial statement compilation or review rather than the higher assurance provided by an audit, yet little is known about these choices. We explore economic aspects of private firm choice of less-than-audit levels of assurance applied to GAAP-based financial statements. We find that CPA fees more than double for each increment in assurance. Commonly used financial

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We compare two versions of the US Treasury floating rate note (FRN) price measured in Treasury auctions and in the swap market. Utilizing a proprietary dataset from J.P. Morgan, we find that the actual US Treasury FRNs are traded in premium in comparison with their synthetic equivalents in the swap market, and the premium amounts to four basis points on average. Moreover, they are priced up by four

Cryptocurrency values have recently fallen substantially. Why? We examine the impact of attention on the Russia-Ukraine War, proxied by Google Trends, on cryptocurrencies (and equity) to measure the returns coherences. Using quantile cross-spectral analysis and daily data for February 24, 2022–June 21, 2022, we observe that co-movements between War attention and cryptocurrencies depends on investment

Growing concerns about climate change have generated several ecofriendly investments, including green bonds. This study investigates the impacts of geopolitical, economic and climate policy risks (GPR, EPU and CPU, respectively) on the long-term conventional/energy stock and conventional/green bond correlations using the DCC-MIDAS-X model. We determine that GPR, EPU and CPU impact the correlations

We investigate potential sources of emerging statistical arbitrage opportunities in the Bitcoin market across five exchanges – Binance, Bitfinex, Bitstamp, Coinbase, and Kraken – via the instrumental variables approach to control for apparent endogeneity. We show that arbitrage opportunities arise when the network is congested and Bitcoin prices are volatile. Increased exchanges volume and on-chain

Agency mortgage-backed securities (MBSs) with diverse characteristics are traded in parallel through individualized specified pool (SP) contracts and standardized to-be-announced (TBA) contracts with delivery flexibility. This parallel trading environment generates distinctive effects on MBS pricing and trading: (1) Although cheapest-to-deliver (CTD) issues are present in TBA trading and absent from

A duty of loyalty prohibits fiduciaries from appropriating business opportunities from their companies. Starting in 2000, Delaware, followed by several other states, allowed boards to waive their duty. We show that public firms covered by waiver laws invest less in R&D, produce fewer and less valuable patents, and exhibit abnormally high inventor departures. Remaining innovation activities contribute

We build a model to show that decentralized exchanges (DEX) require less computing power on average than traditional exchanges to accommodate the demand for high-speed trading services. Centralized exchanges acquire excess processing capacity to accommodate activity surges: The idle capacity’s opportunity cost is an externality of low-latency trading. On DEXs, HFTs bid on gas fees in real-time to acquire

We quantify the role of global production linkages in explaining spillovers of U.S. monetary policy shocks on country-sector stock returns. We estimate a structural spatial autoregression (SAR) model that is consistent with an open-economy production network framework. Using the SAR model, we decompose the total impact of U.S. monetary policy on global stock returns into direct and network effects

Bitcoin pricing mechanism is a complex system of interactions between factors that are not standard for traditional financial assets. Its understanding is essential for assessing specific topics, most prominently the interaction between Bitcoin price and network’s hashrate as it directly translates into its power demand and consumption and thus also environmental implications. We examine an intertwined

This paper examines how overconfident CEOs adjust financial report readability (FRR) in response to Regulation Fair Disclosure (RegFD). Our difference-in-differences analysis shows that while being associated with lower readability ex ante, overconfident CEOs increase their firms' FRR relatively to non-overconfident peers after the importance of public disclosure grows due to RegFD adoption. We also

This research proposes a new class of RES-CAViaR (conditional autoregressive value-at-risk) models, that incorporate daily realized volatility and expected shortfall (ES) to forecast VaR and ES simultaneously. We further consider weekly and monthly realized volatilities in the proposed model to approximate a long-memory process. We employ the Bayesian adaptive Markov chain Monte Carlo approach to estimate

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In this paper the dynamics of the Spanish public debt-GDP ratio is analysed during the period 1850–2021. We use recent procedures to test for explosive bubbles in the presence under time-varying volatility (Harvey et al., 2016; Harvey et al., 2019, 2020; Kurozumi et al., 2022) in order to test the explosive behavior of Spanish public debt over this long period. We extend previous analysis of Esteve

This paper studies how accounting treatment of off-balance sheet financing affects the speed of capital structure adjustment. Utilizing a quasi-natural experiment created by Accounting Standards Update (ASU) No. 2016-02 which requires operating lease to be capitalized on the balance sheet, we find that firms adjust to target leverage faster after the announcement of the new standard. We also find that

We examine organizational capital risk on a micro level by identifying 120,017 quasi-voluntary inventor moves between firms over three decades. Consistent with survey results from Eisfeldt and Papanikolaou (2013), we find that a 10% increase in organizational capital results in a 1.8% greater annual exit of firm inventors. Exit risk is higher 1) where employees are more transferable between firms and

The engendering of systemic risk through contagion from stressed firms continues to be of great scholarly interest. While the contribution to systemic risk of enforcement actions against firms in the financial industry, for instance, has received much recent attention, the systemic risk to economies of attacks to firms in energy industries has been much less examined. We assess the impact of the recent

Using proprietary financial data on millions of households, we show that likely-Republicans increased the equity share and market beta of their portfolios following the 2016 presidential election, while likely-Democrats rebalanced into safe assets. We provide evidence that this behavior was driven by investors interpreting public information based on different models of the world. We use detailed controls

Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show

We propose an intermediate-term stock investment strategy based on fundamental analysis and machine learning. The approach uses predictors from the Earnings Power Index (EPI) as input variables derived from cross-sectional and time-series data from a company’s financial statements. The analytical methods of machine learning allow us to validate the link between financial factors and excess returns

This study investigates the implementation of a government of India mandate that requires firms to spend at least 2% of their profits on corporate social responsibility (CSR). The results show that qualifying firms that voluntarily engaged in CSR before the mandate reduce their CSR spending afterward. Despite increasing advertisement expenditure likely to offset the lost signaling value of voluntary

Armstrong et al. (2022) review the empirical methods used in the accounting literature to draw causal inferences. They document a growing number of studies using quasi-experimental methods and provide a critical perspective on this trend as well as the use of these methods in the accounting literature. In this discussion, I complement their review by broadening the perspective. I argue for a design-based

We investigate whether an environmental social governance (ESG) disclosure moderates the relation between ESG controversies and analyst forecast accuracy. The previous literature has shown that ESG controversies increase uncertainty about a firm's future prospects, while ESG disclosure decreases this uncertainty. We therefore take the next step and integrate ESG controversies, ESG disclosure and uncertainty

Postcrisis bank regulations raised market-making costs for bank-affiliated dealers. We show that this can, somewhat surprisingly, improve overall investor welfare and reduce average transaction costs despite the increased cost of immediacy. Bank dealers in OTC markets optimize between two parallel trading mechanisms: market making and matchmaking. Bank regulations that increase market-making costs

Bayesian network theory is used to construct a novel probability-based measure for CEO overconfidence. This measure is estimated by studying the probabilistic correlation between CEO overconfidence and several CEO- and firm-specific determinants of overconfidence, that have been documented in the literature. Using S&P 500 firms over the period 2007–2017, we show that the established Bayesian network

Impact investing and ESG investing are specific “ethical” investing types integrating social, environmental, and moral values with financial goals. Despite receiving heightened scholarly attention, the difference between impact and ESG investing is largely unexamined, and it is not clear how they differ from conventional investment. To explain the differences between ESG, impact, and conventional investing

Achievement drive hypothesis indicates that individuals with higher facial width-to-height ratio (fWHR) are biologically associated with stronger achievement-drive incentives and are hence likely to exhibit better performance. In this study, we examine the relationship between editors' fWHR, an established proxy for achievement drive, and journal performance. Using finance journals as the research

This study explores how banks compete for a mortgage following different information about the same client. We employ inside information about a bank's clients and the information available to an outside bank making a competing offer for 13,080 individual mortgage clients in Norway from 2010 to 2018. We demonstrate that disentangling the effects of the duration of the client‒bank relationship and the

We investigate how the volatility of carbon emission allowance (EUA) prices affects European stock market sectors. We employ a connectedness network analysis on prices of EUA futures and FTSE stock market sector indices and find that the EUA is mostly a net receiver of volatility connectedness and significantly receives volatility across most sectors during the recent European energy crisis.

A smooth difference-in-differences (smooth DID) method is proposed to revisit the effects of banking deregulation in the United States on income distribution. This simpler nonlinear DID model includes a smooth transition function (STF) to determine gradual policy effects on treatment groups. Based on economic implications and a series of tests, the impact of bank deregulation on gradually reducing

This paper examines the “V-Matrix” and provides a wave theory life cycle model of organizations’ adoption of big data. The V-Matrix is based on the big data five “V’s”: Volume, Velocity, Variety, Veracity, and Value and captures and enumerates the different potential states that an organization can go through as part of its adoption and evolution towards big data. We extend the V-Matrix to a state

We study the real effects of certification to demonstrate the value of mandatory certification over and above mandatory disclosure in enhancing investment efficiency. In our model, a firm's manager selects a project to maximize the firm's short-term stock price, which is a function of her certification and disclosure decisions about the outcome of the project. While the manager might be either forthcoming

We assess how investors’ willingness-to-pay (WTP) for sustainable investments responds to the social impact of those investments, using a framed field experiment. While investors have a substantial WTP for sustainable investments, they do not pay significantly more for more impact. This also holds for dedicated impact investors. When investors compare several sustainable investments, their WTP responds

We characterize the unique equilibrium in an economy populated by strategic CARA investors who trade multiple risky assets with arbitrarily distributed payoffs. We use our explicit solution to study the joint behavior of illiquidity of option contracts. Option bid-ask spreads are proportional to risk aversion and risk-neutral variances of option payoffs. Spreads may decrease in risk aversion, physical

This paper investigates a dynamic trading problem with transaction cost and uncertain exit time in a general Markov market, where the mean vector and covariance matrix of returns depend on the states of the stochastic market, and the market state is regime switching in a time varying state set. Following the framework proposed by Gârleanu and Pedersen (2013), the investor maximizes his or her multi-period

This paper investigates the determinants of the stocks and flows (both in- and outflows) of nonperforming loans (NPLs) by considering a bank-specific factor that is not adequately analysed in the literature, namely, bank capital buffers. Using unbalanced panel data with 6,087 bank-year observations for the 2006–2018 period and a two-step system generalised method of moments (GMM) estimation, we find

We study the impact of machine learning (ML) models for credit default prediction in the calculation of regulatory capital by financial institutions. We do so by using a unique and anonymized database from a major Spanish bank. We first compare the statistical performance of five models based on supervised learning like Logistic Lasso, Trees (CART), Random Forest, XGBoost and Deep Learning, with a

Based on traditional macroeconomic variables, this paper mainly investigates the predictability of these variables for stock market return. The empirical results show the mean combination forecast model can achieve superior out-of-sample performance than the other forecasting models for forecasting the stock market returns. In addition, the performances of the mean combination forecast model are also

The cryptocurrency market is an emerging market that is characterized by intense volatility and therefore the study of its dynamics presents increased interest. The present work investigates the issue of the critical dynamics of a financial complex system approaching a crash, by using the Method of Critical Fluctuation (MCF) which is known for its ability to uncover critical dynamics. Specifically

This paper investigates the effect of the COVID-19 pandemic on analysts’ forecast dispersion. We find that analysts’ exposure to the COVID-19 lockdown reduces the dispersion of their forecasts. Along with the forecast dispersion, the number of earnings forecasts issued by treated analysts decreases, supporting the channel of attention distraction. Moreover, there is no significant difference between

We examine the value relevance of board monitoring committees when there are increased corporate reputation risks (CRR) from undesirable media coverage of environmental, social, and governance (ESG) issues. Empirical evidence indicates that monitoring committees can play an effective role in mitigating investors’ negative stock market reactions in this situation. The results are robust across different

We propose a measurement of aggressive stock-selection opportunity based on positive alphas and idiosyncratic volatilities of cross-section stocks, and examine the role of aggressive stock-selection opportunity in predicting stock market returns. For the US stock market, we find that the change of aggressive stock-selection opportunity has a significant and negative coefficient for predicting future

Due to the complexity of the variable annuities products, we rely on numerical resolution to fairly price the guaranteed minimum withdrawal benefit (GMWB) rider. This policy, known as an embedded put option in the life insurance contracts, gives the contract owner the possibility to withdraw a fixed amount for a fixed period. We assume a single premium payment up front. We drive the pricing results

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This paper proposes a method for estimating the expected duration of competitive advantage from emerging technology adoption for the average adopting firm. The proposed method relies on publicly available data (e.g., web search interest, news articles, book titles, and firm disclosures) and integrates elements from diffusion of innovation theory, hype cycles, and resource-based view of competitive

This study examines the effects of firm-level political risk on firm leverage decisions and speed of adjustment. We uncover that firm-level political risk has a negative impact on a firm's total and long-term leverage. We also find that firms facing high political risk tend to prefer debts with short-term maturity. However, firm-level political risk is positively related to debt specialisation, suggesting

This study examines whether terrorist attacks influence corporate investments and firm value. We expect that overconfident CEOs can mitigate the underinvestment problem caused by terrorist attacks because they overestimate the returns on investment. Using measures of terrorist attack proximity in the U.S., we find that firms with non-overconfident CEOs significantly decrease their investment growth

This paper contributes to the fixed income research by identifying determinants of term premium in an emerging market’s treasury bond yields with particular attention on ambiguity. We use Nelson–Siegel yield curves generated from daily bond price quotes as input to construct a three-factor affine term structure model which decomposes observed yields into risk-neutral and term premium components. We

This study examines the impact of local government debt on stock price crash risk. The results show that corporations located in regions with higher levels of local government debt are more likely to have lower future stock price crash risk. This study further finds that a higher intensity of local government debt may crowd out firm-level credit and ultimately improve the quality of corporate information