The theme of this paper is the application of linear analysis to simplify and extend convex analysis. The central problem treated is the standard convex program -minimize a convex function subject to inequality constraints on other convex functions. The present approach uses the support planes of the constraint region to transform the convex program into an equivalent linear program. Then the d...

This paper analyzes the ability of both economic variables and moving-average rules to forecast the monthly U.S. equity premium using out-of-sample tests for 1960–2008. Both approaches provide statistically and economically significant out-of-sample forecasting gains, which are concentrated in U.S. business-cycle recessions. Nevertheless, economic variables and moving-average rules capture diff...

With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the expected loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametri...

This paper shows a positive relation between analyst forecast dispersion and future aggregate stock returns, significant and robust. The innovations in forecast dispersions are negatively associated with contemporaneous aggregate returns and changes in discount rates. Decomposing forecast dispersion into “uncertainty” and “information asymmetry” components, I find that the “uncertainty” compone...

Industries are economically linked through customer-supplier trade flows. We show theoretically and empirically that industry shocks propagating along this inter-sectoral trade network can feed back to the originating industry, causing an “echo” – intermediate-term autocorrelation in returns. Adopting techniques from graph theory, we find that the strength of the trade network feedback is a cru...

U.S. stock portfolios sorted on size, momentum, transaction costs, M/B, I/A and ROA ratios, and industry classification show considerable levels and variation of return predictability, inconsistent with asset pricing models. This means that a predictable risk premium is not equal to compensation for systematic risk as implied by asset pricing theory (Kirby 1998). We show that introducing market...

This study evaluates the performance of feed-forward neural networks to model and forecast recovery rates of defaulted bank loans. In order to guarantee that the predictions are mapped into the unit interval, the neural networks are implemented with a logistic activation function in the output neuron. The statistical relevance of explanatory variables is assessed using the bootstrap technique. ...

We estimate a reduced-form model of credit risk that incorporates stochastic volatility in default intensity via stochastic time-change. Our Bayesian MCMC estimation method overcomes nonlinearity in the measurement equation and state-dependent volatility in the state equation. We implement on firm-level time-series of CDS spreads, and find strong in-sample evidence of stochastic volatility in t...