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...

Regulations leading up to the financial crisis of 2007-2009 provided incentives for banks shift their risk profiles toward less regulated areas. We focus on the case of operational risk which went from being a relatively benign and largely unregulated risk type to a major risk that now accounts...

We examine the relationship between leverage and the weighted-average cost of capital (WACC) for U.S. banks. Ignoring tax effects, leverage appears to have virtually no impact on the WACCs of too-big-to-fail banks. We find significant differences in this relationship across different...

Using account level credit-card data from six major commercial banks from January 2009 to December 2013, we apply machine-learning techniques to combined consumer-tradeline, credit-bureau, and macroeconomic variables to predict delinquency. In addition to providing accurate measures of loss...

Using Roberts (2015) loan-level data from 2000 to 2011, we find that the inception of CDS trading on reference firms' debt is associated with a decreased number and lower probability of amendments, restatements, and rollovers to existing lenders of bank loans. Reference firms are also less...

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...

Using account level credit-card data from six major commercial banks from January 2009 to December 2013, we apply machine-learning techniques to combined consumer-tradeline, credit-bureau, and macroeconomic variables to predict delinquency. In addition to providing accurate measures of loss...

We examine the effect of credit default swaps (CDS) trading on debt specialization. We argue that reference firms in CDS contracts exhibit higher debt concentration in comparison to firms that do not have CDS traded on them as a way to minimize creditor conflicts and costs in bankruptcy. Our...