This article develops unbiased weighted variance and skewness estimators for overlapping return distributions. These estimators extend the variance estimation methods constructed in Bod et. al. (Applied Financial Economics 12:155-158, 2002) and Lo and MacKinlay (Review of Financial Studies...

Purpose: The purpose of this study is to develop tree-based binary classification models to predict the likelihood of employee attrition based on firm cultural and management attributes. Design/methodology/approach: A data set of resumes anonymously submitted through Glassdoor’s online portal...

This article develops unbiased weighted variance and skewness estimators for overlapping return distributions. These estimators extend the variance estimation methods constructed in Bod et. al. and Lo and MacKinlay. In addition, they may be used in overlapping return variance or skewness ratio...

We examine to what extent the GICS sector categorization of equity securities may be systematically reconstructed from historical quarterly firm fundamental data using gradient boosted tree classification. Model complexity and performance tradeoffs are examined and relative feature importance is...

We frame linear factor models for asset pricing in a machine learning context and consider a numerical comparison of their performance against ordinary least squares linear regression over a dataset of anomaly portfolios. Specific regression models involved in the comparison include regularized...

This article develops unbiased weighted variance and skewness estimators for overlapping return distributions. These estimators extend the variance estimation methods constructed in Bod et. al. (Applied Financial Economics 12:155-158, 2002) and Lo and MacKinlay (Review of Financial Studies...