Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice

We improve both the specification and estimation of firm-specific betas. Time variation in betas is modeled by combining a parametric specification based on economic theory with a non-parametric approach based on data-driven filters. We increase the precision of individual beta estimates by setting up a hierarchical Bayesian panel data model that imposes a common structure on parameters. We show that these accurate beta estimates lead to a large increase in the cross-sectional explanatory power of the conditional CAPM. Using the betas to forecast the covariance matrix of returns also results in a significant improvement in the out-of-sample performance of minimum variance portfolios.asset pricing; portfolio choice; time-varying betas; Bayesian econometrics; panel data

Modeling the dynamics of inflation compensation

This paper investigates the relationship between short-term and long-term inflation expectations using daily data on inflation compensation. We use a flexible econometric model which allows us to uncover this relationship in a data-based manner. We relate our …ndings to the issue of whether inflation expectations are anchored, unmoored or contained. Our empirical results indicate no support for either unmoored or …rmly anchored inflation expectations. Most evidence indicates that inflation expectations are contained

Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice

We improve both the specification and estimation of firm-specific betas. Time variation in betas is modeled by combining a parametric specification based on economic theory with a non-parametric approach based on data-driven filters. We increase the precision of individual beta estimates by setting up a hierarchical Bayesian panel data model that imposes a common structure on parameters. We show that these accurate beta estimates lead to a large increase in the cross-sectional explanatory power of the conditional CAPM. Using the betas to forecast the covariance matrix of returns also results in a significant improvement in the out-of-sample performance of minimum variance portfolios

Influence of the Assembly State on the Functionality of a Supramolecular Jagged1-Mimicking Peptide Additive

Expanding the bioactivation toolbox of supramolecular materials is of utmost relevance for their broad applicability in regenerative medicines. This study explores the functionality of a peptide mimic of the Notch ligand Jagged1 in a supramolecular system that is based on hydrogen bonding ureido-pyrimidinone (UPy) units. The functionality of the peptide is studied when formulated as an additive in a supramolecular solid material and as a self-assembled system in solution. UPy conjugation of the DSLJAG1 peptide sequence allows for the supramolecular functionalization of UPy-modified polycaprolactone, an elastomeric material, with UPy-DSLJAG1. Surface presentation of the UPy-DSLJAG1 peptide was confirmed by atomic force microscopy and X-ray photoelectron spectroscopy analyses, but no enhancement of Notch activity was detected in cells presenting Notch1 and Notch3 receptors. Nevertheless, a significant increase in Notch-signaling activity was observed when DSLJAG1 peptides were administered in the soluble form, indicating that the activity of DSLJAG1 is preserved after UPy functionalization but not after immobilization on a supramolecular solid material. Interestingly, an enhanced activity in solution of the UPy conjugate was detected compared with the unconjugated DSLJAG1 peptide, suggesting that the self-assembly of supramolecular aggregates in solution ameliorates the functionality of the molecules in a biological context