This paper examines the role of peer firm disclosures in shaping corporate R&D investments. Drawing on models of two-stage R&D races, I hypothesize that a firm could be either deterred or encouraged by peer disclosure of interim R&D success, depending on peer firms’ R&D strength in the race. Using granular, project-level data on clinical trials in the drug development process, I find that a firm's

In this paper, we price a widely-used financial instrument, the callable range accrual linked to constant maturity swap (CMS) spread, with the least square Monte Carlo method (LSMC) under the generalized swap market model (GSMM). This method, based on the swap rate, does not only provide an intuitive pricing solution, but also captures the characteristics of the swap market, which helps market participants

Using a representative sample and a measure of insurance literacy developed and validated by an insurance supervisor, this study tests the impact of insurance literacy on the holding of insurance products in Italy. We show that insurance literacy influences insurance purchase decisions along with age, marital status, education, employment status, and having children. The greater the literacy, the higher

In this paper, the spillover relationship between different oil shocks and high- and low-carbon assets is investigated through DY and BK spillover methods. It is found that the spillover relationships between them are heterogeneous, with WTI crude oil futures and heating oil futures being highly affected by oil demand and supply shocks, and clean energy sector stocks being highly affected by oil risk

This paper examines the impact of economic uncertainty on IPO activity in 52 countries. Using a dataset of 70,760 IPOs from 1990 to 2021, we find that economic uncertainty (proxied by the World Uncertainty Index) has a negative effect on IPO activity (both IPO count and proceeds). Additionally, we show that a country's institutional quality, characterized using the World Governance Indicators, alleviates

A cryptocurrency is a digital asset maintained by a decentralised system using cryptography. The complex correlations between the cryptocurrencys’ prices may be exploited to understand the market dynamics and build efficient investment portfolios. We use network methods to select cryptocurrencies and the Markowitz Portfolio Theory to create portfolios agnostic to future market behaviour. The performance

This research explored ESG rating changes after stock price crashes and the impact of foreign investor ownership and investment horizons. Using regression analysis and data from Korean listed firms from 2012 to 2020, we observed an improvement in ESG ratings following stock price crashes. However, higher foreign ownership did not necessarily lead to higher ESG ratings in crashed firms, except for those

We introduce a new dimension in constructing relative investor views for the Black-Litterman model by incorporating fear/greed technical indicator predictions as a proxy for investor sentiment in the portfolio construction process. We apply a hybrid CEEMDAN-GRU deep learning model to forecast this indicator and the XGBoost ensemble learning algorithm to forecast returns for ten country ETFs and create

We study the effect of geopolitical risk (GPR) on stock price crash risk and we investigate the mediating role of the ESG factors in this relationship. Using a large international sample of publicly listed firms, we find that higher GPR causes stock price crashes to occur more frequently. This result holds to several robustness checks and to the use of different measures of stock price crash risk and

Oil markets have faced several crises since 1986, with the most recent global economic downturn linked to the Covid-19 pandemic leading to significant demand and supply shocks in the critical oil market. Given that the impact of crises on oil prices has not been uniform we aim to accurately assess oil price volatility during crises by implementing an ARMA(r,s)-Spline-GJR(p,q) model that accounts for

We investigate the impact of the Covid-19 pandemic on global IPO underpricing. Using a sample of 6113 IPOs from 32 countries, we find that firms issued during the pandemic have 17.6% more underpricing than those issued before the pandemic. We also analyze the effect of firm fundamentals, financial intermediaries, and global factors on pandemic-era underpricing. Firms with strong fundamentals and backed

This paper develops a Russia-Ukraine War and Economic Sanctions Sentiment Index (RUWESsent) to reflect the public sentiment and reaction to economic sanction news based on Twitter Sentiments, Google Trend, Wikipedia Trend, and News Sentiments. We then investigate the effect of our proposed aggregate measure of war and economic sanctions induced sentiment on the blockchain and Fintech stocks.Using

Cross-stock momentum builds on the asymmetry in lead-lag linkages and the difference between long-run and short-run contemporaneous co-movements. Data-driven cross-stock linkages generate a monthly alpha of 1.62% (t-stat=10.03). The asymmetry distinguishes cross-stock momentum from factor momentum, and industry momentum is not subsumed by factor momentum. Factor momentum profit is mostly due to the

We develop a model of informational interdependence between entrepreneurs and the real economy, linking economic uncertainty to entrepreneurs’ earning inflation. We show that information acquisition in the real economy discourages earning inflation. With a monopolistic competition structure, earning inflation could be self-fulling with two equilibria. In a dynamic setting, our model characterises self-fulfilling

This paper employs a Markov Switching Regime (MSR) ARDL model to investigate the determinants of future carbon emission returns, considering distinct regimes of mean and volatility. Utilizing daily data from January 16, 2009, to July 1, 2021, we analyze carbon emissions allowances and returns of major energy commodities. We identify two persistent regimes: high returns with low volatility and low returns

We investigate the interconnections between transportation cryptocurrencies and transportation stocks using a wavelet quantile correlation approach. We find transportation cryptocurrencies have a negative relationship with transportation stocks over most conditions and time periods, indicating opportunity for diversifying transportation stocks. However, in contrast, under some conditions, transportation

With a novel dataset of property/casualty (P/C) insurance companies’ sin investments- holdings of bonds and stocks issued by companies involved in producing alcohol, tobacco, and gaming, we find that the presence of military leadership strengthens insurance companies’ adherence to social norms and discourages portfolio allocation to sin investments, especially sin bonds. The reduction effect is more

This paper examines how the performance of low-risk anomalies varies over the FOMC cycle as they are expected to be weaker as uncertainty is resolved following an FOMC meeting. We form a low-minus-high risk portfolio or betting-against-risk (BAR) portfolio, mimicking low-risk anomalies, using four proxies of risk, and find the biweekly pattern of returns for all four BAR portfolios after the FOMC meeting

We examine the predictive value of expected skewness of oil returns for the realized volatility using monthly data from 1859:11 to 2023:04. We utilize a quantile predictive regression model, which is able to accommodate nonlinearity and structural breaks. In-sample results show that the predictive impact of expected skewness on realized volatility can be both positive and negative, with these signs

Schumpeter theorizes that capitalism is characterized by a constant process of creative destruction. Newcomers introduce disruptive innovations and technologies that replace older, less efficient business practices. Thus, established firms must either continually adapt or perish. Christensen (1997) argues that large, established firms cannot innovate as fast as newcomers and thus are likely to perish

The COVID-19 pandemic continues to destroy the carbon market. To alleviate the situation, governments launched vaccination program campaigns. This study aims to predict two carbon pricing features––return and volatility––considering the impacts of the COVID-19 vaccination program. The present study applies the SHAPley Additive exPlanations method of model analysis and interpretability to determine

In this paper, we examine whether newly developed crypto price and policy uncertainty indices based on news coverage (Lucey et al., 2022) are associated with the emergence of bubbles in cryptocurrencies. Using probit regressions, we show that these indices have a higher explanatory power than factors previously considered in the literature. Furthermore, using a random forest model, we show that these

This study adopts the more cutting-edge DMLDID (double/debiased machine learning based difference-in-differences) approach to demonstrate the impact of carbon policy on corporate risk-taking, and the strong conclusion suggests that carbon policy significantly reduces corporate risk-taking. The further analysis concludes that carbon policy negatively impacts corporate risk-taking by reducing investor

This paper investigates the performance of option investments across different stocks by computing monthly returns on at-the-money straddles on individual equities. We find that options with high historical returns continue to significantly outperform options with low historical returns over horizons ranging from six to 36 months. This phenomenon is robust to including out-of-the-money options or delta-hedging

We proposed a new method (GARCH-M-LEV) that captures the asymmetry in the variance and return equations. The development of the model is encouraged by the stylized fact that investors demand a higher risk premium during “bad” volatility periods rather than “good” ones. To study the properties of the obtained estimators, we conducted simulated data analysis, considering a data-generating process characterized

We investigate whether internet message boards convey cryptocurrency-specific information. Using an event study approach and choosing idiosyncratic volatility and price synchronicity as the proxies for cryptocurrency-specific return variation, we find that: idiosyncratic volatility (price synchronicity) significantly decreases (increases) after the message board opening events. In addition, the reverse

We examine the heterogeneous impacts of asset, product, and financial risks on property-casualty insurers' performance and their resilience to the COVID-19 pandemic. To address the potential endogeneity problem in risk taking, a panel dataset of public property-casualty insurers around the world is studied using a two-stage least squares analysis. The results show that asset and product risks enhance

This study utilizes swaptions data to quantify tail risk through the lens of the fixed income derivatives market. We adopt a non-parametric and model-independent approach to characterize tail risks in a three-dimensional space–time object. We further show that the implied tail risk surface has the predictive contents for stock returns, default risk, and economic uncertainty. There is a significant

Supply chain networks can be instrumental in transmitting sustainability levels among connected nodes, particularly from customers to suppliers. In this context, we introduce a third type of node, the focal node which is a constituent of a large index and functions dually as both customer and supplier. Further, it is characterized by its centrality, large size, and high visibility within the network

This paper analyzes the impact of commodity price shocks and global supply chain disruptions on U.S. inflation rates. Based on the idea that the inflationary effect of particular commodities is time-varying, our main contribution is to construct a Cost-Push Commodity (CPC) factor through a genetic algorithm which allows to recursively select the combination of commodity prices that best explain U.S

This study examines the stock price reactions of environmentally responsible stocks during the onset of the 2023 banking crisis, triggered by the collapse of Silicon Valley Bank (SVB). Our findings indicate that stocks poised to benefit from the shift to a low-carbon economy underperformed during the 2023 crisis. This suggests that investors anticipate a slowdown in climate tech development due to

This paper mainly examines the performance of the tail risk (TR) constructed by 19 sub-categories of commodity price indices for predicting gold futures market volatility. Under the framework of the AR model, we compared the predictive capabilities of AR-type models incorporating the TR indicator as an additional explanatory variable against the AR benchmark model without the TR indicator. Our findings

We employ a self-developed dictionary designed to analyze bank financial statements to study the link between disclosure and bank risk in a sample of 225 European banks over the period 2011-2017. Disclosure is associated with reduced default risk for all but the most aggressive risk-taking banks, with the result weakly conditional on capital strength. At the same time, disclosure appears to increase

We analyze the distributional effects of macroprudential policy on mortgage cycles by exploiting the U.K. mortgage register and a 2014 15% limit imposed on lenders' high loan-to-income (LTI) mortgages. Constrained lenders issue fewer and more expensive high-LTI mortgages, with stronger effects on low-income borrowers. Unconstrained lenders strongly substitute high-LTI loans in local areas with higher

This study investigates the quantile dependence and spillovers for return and volatility of Bitcoin and futures of crude oil, copper, natural gas, and gold. We apply quantile vector autoregression and quantile connectedness approaches using a rolling-window method to examine spillover dynamics. The empirical results reveal that return spillovers increase when asset returns deviate from normal market

We show current market practices relating to odd-lot quotes create a large “inside” market where better prices routinely exist relative to the National Best Bid or Offer. We show that odd-lot quotes play a price discovery role, and these quotes provide valuable information to traders with access to proprietary data feeds. Using a XGBoost machine learning algorithm that uses odd-lot data to predict

Using the COVID-19 pandemic as a laboratory, we show that asset markets assign a time-varying price to firms’ disaster risk exposure. The cross-section of stock returns reflected firms’ different exposure to the pandemic, as measured by their vulnerability to social distancing. As predicted by theory, realized and expected return differentials moved in opposite directions, initially widening and then

This study revisits the credit spread puzzle using credit default swap spread changes between 2002 and 2020. We find that credit-related structural variables account for only 13.8% of the variation in credit default swap spread changes. There exists a single dominant common component that explains 49.8% of the regression residuals. Sell-side risk-bearing constraints are closely related to the unknown

This paper studies the impact of the scale of shadow banking financing of enterprises on the credit spreads of bonds. Using corporate bonds in China's capital markets, we find that the scale of funds incorporated by enterprises' shadow banking channels has a significant positive impact on the credit spreads of bonds. We further find that the region, property rights, and profitability of bond-issuing

The pairs trading strategy involves selecting two highly correlated securities to profit from mean reversion. However, the traditional simple threshold method is subjective, random, and ignores nonlinear relationships. This paper proposes a new cointegration deep reinforcement learning (DRL) pairs trading model applied to Dalian Commodity Exchange futures to capture nonlinear relationships and gain

We study the performance of hedge fund firms from 1999 through 2017, employing a holdings-based approach to decompose overall performance into stock selection and three distinct timing abilities: market return, volatility, and liquidity. In particular, we introduce a liquidity timing ability for the first time using a holdings-based measure. In aggregate, we find evidence for stock picking skill that

Using the dispersion in stock returns during the financial crisis as a source of exogenous variation in the wealth of Norwegian entrepreneurs who held listed stocks, I show that adverse shocks to the wealth of business owners had large effects on their firms' financing, employment, and investment. The effects on investment and employment are driven by young firms, who obtain differentially less bank

We examine subjective risk premia implied by return expectations of individual investors and professionals for portfolios of stocks, bonds, currencies, and commodity futures. While in-sample predictive regressions with realized excess returns suggest that objective risk premia vary countercyclically with business-cycle and asset-valuation measures, subjective risk premia extracted from survey data

This paper examines the effect of unemployment insurance benefits (UIB) on corporate tax aggressiveness. Given that aggressive tax avoidance is risky and costly for the firm and its employees, we argue that low state UIB increases workers' exposure to unemployment risk and, hence, influences firms' tax strategies. Our results show a positive relation between tax aggressiveness and UIB. We also find

This study introduces a portfolio theory motivated approach to measuring mutual fund family-level risk diversification. The average cross-fund correlation in idiosyncratic returns measures diversification of idiosyncratic risk, while the correlation of predicted returns from the multifactor model measures factor risk diversification within a fund family. We document a substantial cross-sectional variation

This study investigates how the stock returns of firms that took corporate action against Russia following the onset of Ukraine-Russian war were impacted. We use traditional event-study methodologies to analyze the data. The findings indicate that the firms that opted to act against Russia in the wake of the onset of Ukraine-Russian war experienced a downward trend in cumulative abnormal returns (CARs)

The crypto-asset market has shown variations in efficiency across assets and time, but limited research has explored the driving factors beyond liquidity. Exploiting a dataset of 122 crypto-assets, with imbalanced data, this study investigates the impact of market conditions and inherent asset characteristics on return predictability. Our findings reveal that both factors significantly influence the

This paper builds a theoretical model where corrupt government officials select the optimal amount of government spending directed toward building wealth for themselves and political allies. We refer to this type of government expenditures as rent extraction spending. Our results show that more government corruption leads to higher rent extraction spending, increased inflation, additional taxation

We explore how a supervisor's hierarchical rank affects the extent to which employees’ targets reflect their past performance. Literature documents that supervisors do not fully ratchet targets for past performance, arguably because the commitment not to penalize successful employees with more difficult targets alleviates the severity of the ratchet effect. We argue that commitment is less credible

The economic role of an accounting regime is to increase welfare through its effects – in conjunction with complementary institutions – on firm and household behavior. I review three major streams of the archival literature (real effects; price effects, including value relevance; and costly contracting), in terms of what they can and cannot reveal as proxies for welfare effects. One conclusion is that

We show theoretically that variable production costs reduce systematic risk of firms' cash flows if capital and variable inputs are complementary in firms' production and input prices are procyclical. In our dynamic model, this operating hedge effect is weaker for more profitable firms, giving rise to a gross profitability premium. Moreover, gross profitability and value factors are distinct and negatively

In this study, we have examined the asymmetric dissemination of spillover returns among monetary policy uncertainty and returns of sectoral stocks of different sectors. The essential contribution of this study is the analysis of deviating levels of spillover returns among uncertainty of monetary policy and stocks returns for diverse segments. Additionally, we have applied an advance technique named

FinTech has facilitated the digital transformation of commercial banks, but it has also impacted their micro-risk-taking. This paper investigates the relationship between bank FinTech and micro-risks of commercial banks, including credit, liquidity, and insolvency risks. To overcome the shortcomings of the existing measurements of bank FinTech, this paper establishes an index that covers 148 commercial

This paper studies the dynamics of market integration in government bond markets. We utilise a new approach based on Pukthuanthong and Roll (2009) to investigate time-varying integration in 38 markets. We explore the impact of crisis periods, alongside differences in sample length, region, development and whether EMU and EU markets show obvious different integration from non-EU markets. Finally, we

Employing a sample of suspected stock manipulation cases based on intraday data, we find that higher institutional ownership is associated with a lower frequency of market manipulation, supporting the monitoring effect of institutional investors. This effect persists even when we instrument index reconstitutions as an exogenous determinant of institutional ownership. Further, our findings indicate

This study examines factors that influence auditors’ intention to use blockchain. From the dual-factor perspective, it argues that auditors’ knowledge about the implications of blockchain for auditing enables their intention to use the technology. However, professional skepticism and perceived adequacy of accounting standards present barriers to the use, which reduce the effect of knowledge on use

Abstract not available

Researchers often use regression-based x-Scores (e.g., conservatism C-Score, misstatement F-Score) from a stage 1 model as a dependent variable in stage 2. We argue that this x-Score analysis can cause coefficient biases and interpretation problems because (1) x-Score does not capture new sources of variation, and (2) the estimates often hinge on unacknowledged technical assumptions. Instead, we recommend

We examine the effect of unrealized fair value adjustments resulting from derivatives classified as cash flow hedges on the dividend policy of UK firms. We theorise and empirically demonstrate that companies differentiate between positive and negative fair value adjustments. When unrealised gains are recorded under ‘Other comprehensive income’ firms do not increase dividend payouts; as such it can

This paper examines the linkage between private investments and shocks in economic and financial indicators. Using data from India, we study the return and volatility spillovers from crude price, credit availability, real exchange rate, inflation, output gap, government spending, and economic policy uncertainty to private investments. We combine the ARMA-GARCH model with wavelet multiresolution analysis