Research:
Here is some of my current research. Feel free to send me an email (fbelo _at_ umn.edu) for a pdf copy of any of the current working papers. Comments are always welcome!
Working Papers:
"A
Pure Production-Based Asset Pricing Model", (This version:
April 2009) (Conditionally accepted at the Journal of Monetary Economics)
[This
paper is based on my PhD dissertation at the University of Chicago (Thesis
advisors: John Cochrane (chair), John Heaton, Monika Piazzesi and Pietro
Veronesi]
A stochastic
discount factor for asset returns is recovered from equilibrium marginal rates of
transformation of output across states of nature, inferred from the producers'
first order conditions. The marginal rate of transformation implies a novel
macro-factor asset pricing model that does a reasonable job explaining the
cross section of stock returns with plausible parameter values. Using a
flexible representation of the firms' production technology, the producers'
ability to transform output across states of nature is estimated to be high, in
contrast with what is typically assumed in standard aggregate representations of
the firms' production technology.
"Labor
Hiring, Investment and Stock Return Predictability in the Cross Section" (This version: May 2009) (with Santiago Bazdrech and Xiaoji Lin)
We show that firms
with lower labor hiring and investment rates have on average higher future
stock returns in the cross-section of US publicly traded firms. The
predictability holds even after controlling for other known stock return
predictors, varies across firms' technologies and exhibits a clear trend over
time. We propose a production-based asset pricing model with adjustment costs
in both labor and capital inputs to explain the empirical findings. Labor
adjustment costs make hiring decisions forward looking. Convex adjustment costs
imply that the returns of firms that are investing or hiring relatively less
fluctuate more closely with economic conditions. Thus the firms' labor hiring
and investment rates predict stock returns in the data because these variables
proxy for the firms' time-varying conditional beta.
“A Labor-Augmented Investment-Based Asset
Pricing Model” (with Xue Chen and Lu Zhang) (This version: Sep 2009)
We introduce labor
adjustment costs in the q-theory model of expected returns and test the
labor-augmented model using moments of the cross-section of expected stock
returns as well as stock valuation ratios. Adding labor substantially reduces
the pricing errors of the baseline q-theory model across portfolios sorted on
investment-to-assets, book-to-market, asset growth, and labor hiring. The
labor-augmented model also substantially outperforms the baseline model in
explaining the cross-section of stock valuation ratios, especially across
investment-to-assets portfolios. However, neither model can fully capture the
large spread in the valuation ratio observed in the data, especially across the
book-to-market portfolios.
“Inventories and Stock Returns” (with Xiaoji Lin) (This version: Sep 2009)
We show the firm
level physical capital investment and inventory investment rates jointly
predicts stock returns in the cross-section of US publicly traded firms. A
long-short portfolio using physical capital and inventory investment
information generates significant excess returns of about 8% per year. We use
this empirical fact to distinguish between alternative macroeconomic models of
inventory behavior. Among the class of models considered here, we show that a
model with stock out costs as well as adjustment costs in both physical capital
and inventory is the most successful in matching the real quantities side facts
in the data, consistent with Kahn and Thomas (2007). None of the models
examined here, however, can match the asset pricing facts in the data.
“Government Spending, Political Cycles and
the Cross Section of Stock Returns” (with Vito
Gala and Jun Li) (This version: Aug 2009)
Using data from the
Benchmark Input-Output Accounts of the National Income and Product Accounts, we
construct a novel measure of industry's exposure to the government sector. We
document that firms with different exposure earn on average different stock
returns depending on the presidential partisan cycle. During Democratic
presidential terms, firms with high government exposure earn on average higher
stock returns than firms with low government exposure. The reverse holds true
during Republican presidential terms. A long-short cross-sectional investment
strategy that exploits the presidential partisan cycle predictability generates
large excess returns of about 5% per year. The returns of this investment
strategy cannot be explained by risk exposure to standard risk factors as
captured by the unconditional and conditional version of the CAPM and by the
Fama and French (1993) three factors asset pricing models.
Work in Progress:
"Government Size and Asset Prices" (with Antonio Mele)
TBA
"An Argument
for Poor International Risk Sharing" (with Bob Goldstein
and Jianfeng Yu)
TBA
"A Joint
Estimation of Conditional Structural Models and Factor Models" (with Jeremy Graveline, Bob Goldstein
and Fan Yang)
TBA