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Rare booms and disasters in a multisector endowment economy
, 2013
"... Why do value stocks have higher expected returns than growth stocks, in spite of having lower risk? Why do these stocks exhibit positive abnormal performance while growth stocks exhibit negative abnormal performance? This paper offers a rareevents based explanation, that can also account for facts a ..."
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Cited by 5 (2 self)
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Why do value stocks have higher expected returns than growth stocks, in spite of having lower risk? Why do these stocks exhibit positive abnormal performance while growth stocks exhibit negative abnormal performance? This paper offers a rareevents based explanation, that can also account for facts about the aggregate market. Patterns in timeseries predictability offer independent evidence for the model’s conclusions.
What is the maximum return predictability permitted by asset pricing models?", Working Paper
, 2013
"... This paper investigates whether return predictability can be explained by existing asset pricing models. Using different assumptions, I develop two theoretical upper bounds on the Rsquare of the regression of stock returns on predictive variables. Empirically, I find that the predictive Rsquare is ..."
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Cited by 1 (0 self)
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This paper investigates whether return predictability can be explained by existing asset pricing models. Using different assumptions, I develop two theoretical upper bounds on the Rsquare of the regression of stock returns on predictive variables. Empirically, I find that the predictive Rsquare is significantly larger than the upper bounds, implying that extant asset pricing models are incapable of explaining the degree of return predictability. The reason for this inconsistency is the low correlation between the excess returns and the state variables used in the discount factor. The finding of this paper suggests the development of new asset pricing models with new state variables that are highly correlated with stock returns.
with Disaster Risk and Disappointment Aversion
, 2013
"... In this paper, I combine disappointment aversion, as employed by Routledge and Zin [28] and Campanale, Castro and Clementi [9], with rare disasters in the spirit of Rietz [27], Barro [4], Gourio [16], Gabaix [15] and others. I find that, when the model’s representative agent is endowed with an empir ..."
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In this paper, I combine disappointment aversion, as employed by Routledge and Zin [28] and Campanale, Castro and Clementi [9], with rare disasters in the spirit of Rietz [27], Barro [4], Gourio [16], Gabaix [15] and others. I find that, when the model’s representative agent is endowed with an empirically plausible degree of disappointment aversion, a rare disaster model can produce moments of asset returns that match the data reasonably well, using disaster probabilities and disaster sizes much smaller than have been employed previously in the literature. This is good news. Quantifying the disaster risk faced by any one country is inherently difficult with limited time series data. And, it is open to debate whether the disaster risk relevant to, say, US investors is wellapproximated by the sizable risks found by Barro [4] and coauthors [6, 7, 26] in crosscountry data. On the other hand, we have evidence (see [30], [8], or [11]) that individuals tend to overweight bad or disappointing
ESSAYS ON ASSET PRICING AND PORTFOLIO CHOICE
"... The first chapter “Rare Disasters and the Term Structure of Interest Rates ” offers an explanation for the properties of the nominal term structure of interest rates and timevarying bond risk premia based on a model with rare consumption disaster risk. In the model, expected inflation follows a mea ..."
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The first chapter “Rare Disasters and the Term Structure of Interest Rates ” offers an explanation for the properties of the nominal term structure of interest rates and timevarying bond risk premia based on a model with rare consumption disaster risk. In the model, expected inflation follows a mean reverting process but is also subject to possible large (positive) shocks when consumption disasters occur. The possibility of jumps in inflation increases nominal yields and the yield spread, while timevariation in the inflation jump probability drives timevarying bond risk premia. Predictability regressions offer independent evidence for the model’s ability to generate realistic implications for both the stock and bond markets. The second chapter “Rare booms and disasters in a multisector endowment economy” studies the crosssection of stock returns. Why do value stocks have higher expected returns than growth stocks, in spite of having lower risk? Why do these stocks exhibit positive abnormal performance while growth stocks exhibit negative abnormal performance? This paper offers a rareevents based explanation, that can also account for facts about the aggregate market. Patterns in timeseries predictability offer independent evidence for the
about Rare Disasters
, 2011
"... This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors ’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the likelihood ..."
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This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors ’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the likelihood of rare disasters drop to a much more pessimistic level once a disaster has occurred. Such a shift in beliefs can trigger massive declines in pricedividend ratios. Pessimistic beliefs persist for some time. Thus, belief dynamics are a source of apparent excess volatility relative to a rational expectations benchmark. Due to the low frequency of disasters, even an infinitelylived investor will remain uncertain about the exact probability. Our analysis is conducted in continuous time and offers closedform solutions for asset prices. We distinguish between rational and adaptive Bayesian learning. Rational learners account for the possibility of future changes in beliefs in determining their demand for risky assets, while adaptive learners take beliefs as given. Thus, risky assets tend to be lowervalued and pricedividend ratios vary less under adaptive versus rational learning for
the source. Can TimeVarying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?
, 2012
"... financial support from the Aronson+Johson+Ortiz fellowship through the Rodney L. White Center ..."
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financial support from the Aronson+Johson+Ortiz fellowship through the Rodney L. White Center
Index Option Returns and Generalized Entropy
, 2012
"... I develop a continuum of new nonparametric bounds. They stem from the solution of an optimization problem that is dual to the Hansen and Jaganathan (1991) approach, and are shown to complete the nonparametric bound universe that the literature has so far discovered. Through the lens of these bounds, ..."
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I develop a continuum of new nonparametric bounds. They stem from the solution of an optimization problem that is dual to the Hansen and Jaganathan (1991) approach, and are shown to complete the nonparametric bound universe that the literature has so far discovered. Through the lens of these bounds, I estimate rare event distributions from option market returns. Standard disaster models and their perturbations are shown not able to meet the bounds implied by simple static option trading strategies. Nonetheless, their abilities in magnifying pricing kernel dispersions through tail distortions do seem promising. My results suggest more sophisticated modeling of disaster models to reconcile with the index option data. 1