This paper assesses the role that monetary policy plays in the decision to default using a General Equilibrium model with collateralized loans, trade in fiat money and production. Long-term nominal loans are backed by collateral, the value of which depends on monetary policy. The decision to...

This paper models the important role that repurchase agreements (repos) play in bond market intermediation. Not only do repos allow dealers to finance their activities, but they also increase dealers' ability to satisfy levered client demands without having to adjust their holdings of risky...

We propose a coherent framework using support vector regression (SRV) for generating and ranking a set of high quality models for predicting emerging market sovereign credit spreads. Our framework adapts a global optimization algorithm employing an hv-block cross-validation metric, pertinent for...

This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news,...

We examine the effects of liquidity, default and personal taxes on the relative yields of Treasuries and municipals using a generalized model with liquidity risk. The municipal yield model includes liquidity as a state factor. Using a unique transaction dataset, we are able to estimate the...

In the period prior to the financial crisis, leverage in the financial system increased substantially. This buildup was likely facilitated by, among other factors, a loosening of credit terms related to OTC derivatives and securities financing transactions. However, little or no systematic data...

We study the behavior of the interbank market before, during and after the 2008 financial crisis. Leveraging recent advances in network analysis, we study two network structures, a correlation network based on publicly traded bank returns, and a physical network based on interbank lending...

Estimating the effect of Federal Reserve's announcements of Large-Scale Asset Purchase (LSAP) programs on corporate credit risk is complicated by the simultaneity of policy decisions and movements in prices of risky financial assets, as well as by the fact that both interest rates of assets...

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample...

We use machine learning methods to examine the power of Treasury term spreads and other financial market and macroeconomic variables to forecast US recessions, vis-à-vis probit regression. In particular we propose a novel strategy for conducting cross-validation on classifiers trained with...