Prior academic research on hedge funds focuses predominately on fund strategies in relation to market timing, stock picking, and performance persistence, among others. However, the hedge fund industry lacks a universal classification scheme for strategies, leading to subjective fund...

We present a structured portfolio optimization framework with sparse inverse covariance estimation and an attention-based LSTM network that exploits machine learning (deep learning) techniques. We shrink Wishart volatility towards a Graphical Lasso initial covariance estimator and solve the...

The Bayes-Stein model provides a framework for remedying parameter uncertainty in the Markowitz mean-variance portfolio optimization. The classical version, however, suffers from estimation errors of model components and fails to consistently outperform the naive 1/N asset allocation rule. We...

Banking is a popular topic for empirical and methodological research that applies operational research (OR) and artificial intelligence (AI) methods. This article provides a comprehensive and structured bibliographic survey of OR- and AI-based research devoted to the banking industry over the...

Bank failure prediction is a popular topic that requires highly accurate results. We contribute to the literature by determining whether models based on the crisis data are suitable for predicting bank failure during a stable period and which predictors can be held for long-term forecasting. In...