Purpose – Prior research on underwriter reputation treats underwriters as the unit of analyzing, while the purpose of this paper is to analyze underwriter reputation effects after introducing discretion of underwriters’ employees. Specially, this paper investigates the damage on underwriter...

Purpose: The paper is to explore crowdfunding success determinants from the reward menu design aspect, distinguishing from extant studies focusing on characteristics of project creators or crowdfunding projects and funding dynamics. Both the number of reward options and price differentiation of...

Purpose: Research in tourism and hospitality industry marketing has identified many highly effective applications of social media. However, studies in the existing literature do not enable a comprehensive understanding of this phenomenon because they lack a theoretical foundation. Therefore,...

Statistical inferences for sample correlation matrices are important in high dimensional data analysis. Motivated by this, this paper establishes a new central limit theorem (CLT) for a linear spectral statistic (LSS) of high dimensional sample correlation matrices for the case where the...

I use classification-based machine-learning methods to decompose 32 anomaly payoffsinto risk exposures and mispricing. The component driven by risk earns statistically insignificantreturns, despite its efficacy in explaining the time-series variation in anomaly payoffs.The mispricing component...

We study the SABR stochastic volatility model with the volatility-of-volatility parameter ν . We provide a method to expand the price C_SABR(S, K, ν, σ, τ ) of a European call in this model as a Taylor series in ν , C_SABR(S, K, ν, σ, τ ) = C_BS(S,K, σ, τ ) ν C₁ ν²C₂ . . . ν^kC_k O(ν<sup>k...

We use machine learning to construct a statistically optimal and unbiased benchmark for firms' earnings expectations. We show that analyst expectations are on average biased upwards, and that this bias exhibits substantial time-series and cross-sectional variation. On average, the bias increases...