Doron Avramov
Associate Professor of Finance |
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Curriculum Vitae (pdf)
Teaching
(Spring 2008):
· BMGT343: Investments; undergraduate level; syllabus
· BUFN700: Investment Management; MBA level; syllabus; Guest lecture on Residential Mortgage Finance
· BMGT808B: Empirical Asset Pricing; PhD level;
Teaching material will be posted at Blackboard.
Research:
Working
papers (comments welcome):
Momentum, Information Uncertainty, and
Leverage – an Explanation Based on Recursive Preferences
(with Satadru
Hore)
Abstract:
Momentum payoffs concentrate
in high information uncertainty and high credit risk firms and are virtually
nonexistent otherwise. This paper rationalizes such momentum concentrations in
consumption based equilibrium asset pricing. In our paradigm, dividend growth
is mean reverting, expected dividend growth is persistent, the representative
agent is endowed with stochastic differential utility of Duffie and Epstein
(1992), and dividend streams are used for both consumption and debt repayment
per Abel (1999). Employing reasonable risk aversion levels we are able to
produce the observational momentum effects. Momentum profitability is large in
the interaction between high levered and risky cash flow firms. It rapidly
deteriorates and ultimately disappears as leverage or cash flow risk
diminishes.
Investing in hedge funds when returns are predictable (with Robert Kosowski, Narayan Naik, and Melvyn Teo) Winner of the Best Paper Award at the 2007 European Finance Association.
Abstract:
This
paper evaluates hedge fund performance through portfolio strategies
that incorporate predictability in managerial skills, fund risk loadings,
and benchmark returns. Incorporating predictability substantially improves
performance for the entire universe of hedge funds as well as various subsets
based on investment styles. Such outperformance is strongest during market
downturns when the marginal utility of consumption is relatively high.
Moreover, the major source of investment profitability is predictability in
managerial skills. In particular, long-only strategies that incorporate
predictable skills outperform their Fung and Hsieh (2004) benchmarks by over 12
percent per year. The economic value of predictability obtains for various
rebalancing horizons and is robust to style adjustments as well as adjustments
for backfill bias, incubation bias, illiquidity-induced serial correlation, and
fees.
Credit ratings
and the cross-section of stock returns (with
Tarun Chordia,
Gergana Jostova, and Alexander Philipov)
Abstract:
Low
credit risk firms realize higher returns than high credit risk firms. This
effect is puzzling because investors pay a premium for bearing credit risk.
This paper shows that the credit risk effect exists only in periods around
credit rating downgrades. Around downgrades, low rated firms experience
considerable negative returns, precipitated by substantial deterioration in
their operating and financial performance, large negative earnings surprises
and analyst forecast revisions, and strong institutional selling. In contrast,
returns do not differ across credit risk groups in stable or improving credit
conditions. Remarkably, the credit risk effect is driven by the lowest rated
stocks which account for less than 4% of the total market cap, suggesting that
there is no pervasive distress factor in the cross section of returns.
Publications and papers accepted for publication
Stock
Return Predictability and Model Uncertainty Journal of Financial
Economics 64 (2002), 423 – 458.
Abstract:
We
use Bayesian model averaging to analyze the sample evidence on return
predictability in the presence of model uncertainty. The analysis reveals
in-sample and out-of-sample predictability, and shows that the out-of-sample
performance of the Bayesian approach is superior to that of model selection
criteria. We find that term and market premia are robust predictors. Moreover,
small-cap value stocks appear more predictable than large-cap growth stocks. We
also investigate the implications of model uncertainty from investment
management perspectives. We show that model uncertainty is more important than
estimation risk, and investors who discard model uncertainty face large utility
losses.
Stock Return
Predictability and Asset Pricing Models Review of Financial Studies
17 (2004), 699-738.
Abstract:
This
paper develops an asset allocation framework that incorporates prior beliefs
about the extent of stock return predictability explained by asset pricing
models. We find that when prior beliefs allow even minor deviations from
pricing model implications, the resulting asset allocations depart considerably
from and substantially outperform allocations dictated by either the underlying
models or the sample evidence on return predictability. Under a wide range of
beliefs about model pricing abilities, asset allocations based on conditional
models outperform their unconditional counterparts that exclude return
predictability.
Investing in Mutual Funds when Returns are Predictable
(with Russ Wermers) Journal
of Financial Economics 81 (2006),
339-377. Discussion of this
paper in The New York Times, November 20 2005: “The Manager Is in a Slump (or
Maybe It’s Just a Phase)” by Mark Hulbert. Discussion
of this paper also appears in “Haaretz”
an Israeli-based newspaper (for Hebrew readers).
Abstract:
This paper analyzes investments in
Asset Pricing Models and Financial Market Anomalies
(with Tarun
Chordia)
Abstract:
This paper derives and implements a
framework in which to test whether conditional asset pricing models, applied to
single securities, can explain the size, value, turnover, and momentum effects
in expected stock returns. In this framework individual stock betas vary with
firm level size and book-to-market as well as with macroeconomic variables. The
evidence shows that under the extensively studied constant beta framework, none
of the models under consideration capture any of the size, value, turnover, and
past return effects, even when returns are risk-adjusted by size, value,
liquidity, and momentum factors. In contrast, when beta is allowed to vary, the
size and book to market effects are often explained, but the explanatory power
of turnover and past return remains robust. The past return or momentum effect
is related to model mispricing that varies with macroeconomic variables,
whereas turnover shows no business cycle patterns.
Predicting Stock Returns (with Tarun Chordia) Journal
of Financial Economics 82
(2006), 387-415.
Abstract:
This paper studies
whether incorporating business cycle predictors benefits a real time optimizing
investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash.
Realized returns are positive when adjusted by the Fama-French and momentum
factors as well as by the size, book-to-market, and past return
characteristics. The investor optimally holds small-cap, growth, and momentum
stocks and loads less (more) heavily on momentum (small-cap) stocks during
recessions. Returns on individual stocks are predictable out-of-sample due to
alpha variation, whereas the equity premium predictability, the major focus of
previous work, is questionable.
An Exact Bayes
Test of Asset Pricing Models with Application to International Markets (with John Chao)
Journal of Business 79
(2006), 293-323.
Abstract:
This paper develops and
implements an exact finite-sample test of asset pricing models with time
varying risk premia using posterior probabilities. The strength of our approach
is that it allows multiple conditional asset pricing specifications, both
nested and non-nested, to be tested and compared simultaneously. We apply our
procedure to international equity markets by testing and comparing the
international CAPM and conditional ICAPM versions of Fama and French (1998).
The empirical evidence suggests that the best performing model is the ICAPM
with the value premium constructed based on global earnings-to-price ratio.
Liquidity and Autocorrelation in Individual Stock Returns
(with Tarun
Chordia and Amit
Goyal) Journal of Finance 61 (2006), 2365-2394.
Abstract:
This paper documents a strong relationship
between short-run reversals and stock return illiquidity, even after
controlling for trading volume. The largest reversals and the potential
contrarian trading strategy profits occur in the high turnover, low liquidity
stocks, as the price pressures caused by non-informational demands for
immediacy are accommodated. Thus, the high frequency negative autocorrelations
are more likely to result from stresses in the market for liquidity. The
contrarian trading strategy profits are smaller than the likely transactions
costs because the high turnover, low liquidity stocks face high transaction and
large market impact costs. This lack of profitability and the fact that the
overall findings are consistent with rational equilibrium paradigms suggest
that the violation of the efficient market hypothesis due to short-term
reversals is not so egregious after all.
The Impact of Trades on Daily Volatility (with Tarun Chordia
and Amit Goyal) Review of Financial Studies 19 (2006), 1241-1277.
Abstract:
This paper proposes a trading-based
explanation for the asymmetric effect in daily volatility of individual stock returns.
Previous studies propose two major hypotheses for this phenomenon: leverage
effect and time varying expected returns. However, leverage has no impact on
asymmetric volatility at the daily frequency and, moreover, we observe
asymmetric volatility for stocks with no leverage. Also, expected returns may
vary with the business cycle, i.e., at a lower than daily frequency. Trading
activity of contrarian and herding investors has a robust effect on the
relationship between daily volatility and lagged return. Consistent with the
predictions of the rational expectations models, non-informational liquidity
driven (herding) trades increase volatility following stock price declines and
informed (contrarian) trades reduce volatility following stock price increases.
The results are robust to different measures of volatility and trading
activity.
Understanding
Changes in Corporate Credit Risk
(with Gergana Jostova and Alexander Philipov) Financial
Analysts Journal 63 (2007)
90-105.
Abstract:
This paper provides new evidence on the
empirical success of structural models in explaining corporate credit risk
changes. A parsimonious set of common factors and firm-level fundamentals,
inspired by structural models, explains more than 54% (67%) of the variation in
credit spread changes for medium (low) grade bonds. No dominant latent factor
is present in the unexplained variation. While our set of variables has lower
explanatory power among high-grade bonds, it does capture most of the
systematic variation of credit spread changes in that category as well. It also
subsumes the explanatory power of the Fama and French (1993) factors among all
grade classes.
Momentum and credit rating (with Tarun Chordia, Gergana Jostova, and Alexander Philipov) Journal of Finance 62, 2503-2520.
Abstract:
This
paper establishes a robust link between momentum and credit rating. Momentum
profitability is large and significant among low-grade firms, but it is
nonexistent among high-grade firms. The momentum payoffs documented in the
literature are generated by low-grade firms that account for less than four
percent of the overall market capitalization of rated firms. The momentum
payoff differential across credit rating groups is unexplained by firm size,
firm age, analyst forecast dispersion, leverage, return volatility, and cash
flow volatility.
Dispersion in analyst's
earnings forecasts and credit rating (with Tarun Chordia, Gergana Jostova, and Alexander Philipov) Forthcoming in Journal of Financial Economics
Abstract:
This paper shows that the puzzling negative
cross-sectional relation between dispersion in analysts' earnings forecasts and
future stock returns is a manifestation of the credit risk effect. In
particular, the profitability of dispersion based trading strategies is
concentrated in a small number of the worst-rated firms and is significant only
during periods of deteriorating credit conditions. In such periods, the
negative dispersion-return relation emerges as low-rated firms experience
substantial price drop along with considerable increase in forecast
dispersion. Moreover, even
for this small universe of worst-rated firms, the dispersion-return relation is
nonexistent when either the dispersion measure or return is adjusted by credit
risk. The results are robust to
previously proposed explanations for the dispersion effect such as short-sale
constraints, illiquidity, and leverage.