We examine U.S. publicly traded bank holding companies (BHCs) that failed during the 2007-2009 global financial crisis. Using consolidated data at the BHC level and 10-K filings, we investigate the determinants of bank failures during this period using nonlinear machine learning (ML). The...

We study Roll's (1992) conjecture that there may exist an implicit value in index-tracking (IVIT) relative to forming mean-variance (MV) optimal portfolios under estimation error. While index-tracking portfolios are deemed MV inefficient ex-ante, it is unclear whether this is the case when...

The equity of too-big-to-fail banks could be deemed less risky due to implicit government guarantees. However, such guarantees could also amplify a moral hazard problem that induces large banks to take excessive risk. If such risk is mispriced by the market due to the increased complexity of...

We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the...

We conduct a horse race using three asset return volatility estimates: the sample variance, the exponential smoother used by RiskMetrics, and the generalized autoregressive conditional heteroskedasticity (GARCH). Our results are performed in both univariate and multivariate analysis. Our goal is...

It is common to come across SAS or Stata manuals while working on academic empirical finance research. Nonetheless, given the popularity of open-source programming languages such as R, there are fewer resources in R covering popular databases such as CRSP and COMPUSTAT. The aim of this article...

This paper considers the optimal hedge ratio problem under estimation risk. Due to incomplete information, the decision-maker evaluates the opportunity cost of hedging using exchange-traded funds or notes (ETF/Ns). Using a back-testing procedure over the last five years and 13 different hedging...

Naive asset allocation and other ad-hoc techniques are commonly practiced by fund managers in the industry. Such strategies, however, are deemed mean-variance (MV) sub-optimal according to modern portfolio theory. Nonetheless, taking estimation risk into considerations, such practices are...