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2009 (9)

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Book
Confidence Risk and Asset Prices
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Year: 2009 Publisher: Cambridge, Mass. National Bureau of Economic Research

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Book
Learning and Asset-Price Jumps
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Year: 2009 Publisher: Cambridge, Mass. National Bureau of Economic Research

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Book
Empirical Evaluation of the Long-Run Risks Model for Asset Prices
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Year: 2009 Publisher: National Bureau of Economic Research

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Digital
Confidence Risk and Asset Prices
Authors: ---
Year: 2009 Publisher: Cambridge, Mass National Bureau of Economic Research

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Abstract

In the data, asset prices exhibit large negative moves at frequencies of about 18 months. These large moves are puzzling as they do not coincide, nor are they followed by any significant moves in the real side of the economy. On the other hand, we find that measures of investor's uncertainty about their estimate of future growth have significant information about large moves in returns. We set-up a recursive-utility based model in which investors learn about the latent expected growth using the cross-section of signals. The uncertainty (confidence measure) about investor's growth expectations, as in the data, is time-varying and subject to large moves. The fluctuations in confidence measure affect the distribution of future consumption given investors' information, and consequently influence equilibrium asset prices and risk premia. In calibrations we show that the model can account for the large return move evidence in the data, distribution of asset prices, predictability of excess returns and other key asset market facts.


Digital
Learning and Asset-Price Jumps
Authors: ---
Year: 2009 Publisher: Cambridge, Mass National Bureau of Economic Research

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Abstract

We develop a general equilibrium model in which income and dividends are smooth, but asset prices are subject to large moves (jumps). A prominent feature of the model is that the optimal decision of investors to learn the unobserved state triggers large asset-price jumps. We show that the learning choice is critically determined by preference parameters and the conditional volatility of income process. An important prediction of the model is that income volatility predicts future jumps, while the variation in the level of income does not. We find that indeed in the data large moves in returns are predicted by consumption volatility, but not by the changes in the consumption level. We show that the model can quantitatively capture these novel features of the data.


Digital
An Empirical Evaluation of the Long-Run Risks Model for Asset Prices
Authors: --- ---
Year: 2009 Publisher: Cambridge, Mass National Bureau of Economic Research

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We provide an empirical evaluation of the forward-looking long-run risks (LRR) model and highlight model differences with the backward-looking habit based asset pricing model. We feature three key results: (i) Consistent with the LRR model, there is considerable evidence in the data of time-varying expected consumption growth and volatility, (ii) The LRR model matches the key asset markets data features, (iii) In the data and in the LRR model accordingly, past consumption growth does not predict future asset prices, whereas lagged consumption in the habit model forecasts future price-dividend ratios with an R2 of over 40%. Overall, our evidence implies that the LRR model provides a coherent framework to analyze and interpret asset prices.


Book
Learning and Asset-Price Jumps
Authors: --- ---
Year: 2009 Publisher: Cambridge, Mass. National Bureau of Economic Research

Loading...
Export citation

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Bookmark

Abstract

We develop a general equilibrium model in which income and dividends are smooth, but asset prices are subject to large moves (jumps). A prominent feature of the model is that the optimal decision of investors to learn the unobserved state triggers large asset-price jumps. We show that the learning choice is critically determined by preference parameters and the conditional volatility of income process. An important prediction of the model is that income volatility predicts future jumps, while the variation in the level of income does not. We find that indeed in the data large moves in returns are predicted by consumption volatility, but not by the changes in the consumption level. We show that the model can quantitatively capture these novel features of the data.

Keywords


Book
Confidence Risk and Asset Prices
Authors: --- ---
Year: 2009 Publisher: Cambridge, Mass. National Bureau of Economic Research

Loading...
Export citation

Choose an application

Bookmark

Abstract

In the data, asset prices exhibit large negative moves at frequencies of about 18 months. These large moves are puzzling as they do not coincide, nor are they followed by any significant moves in the real side of the economy. On the other hand, we find that measures of investor's uncertainty about their estimate of future growth have significant information about large moves in returns. We set-up a recursive-utility based model in which investors learn about the latent expected growth using the cross-section of signals. The uncertainty (confidence measure) about investor's growth expectations, as in the data, is time-varying and subject to large moves. The fluctuations in confidence measure affect the distribution of future consumption given investors' information, and consequently influence equilibrium asset prices and risk premia. In calibrations we show that the model can account for the large return move evidence in the data, distribution of asset prices, predictability of excess returns and other key asset market facts.

Keywords


Book
An Empirical Evaluation of the Long-Run Risks Model for Asset Prices
Authors: --- --- ---
Year: 2009 Publisher: Cambridge, Mass. National Bureau of Economic Research

Loading...
Export citation

Choose an application

Bookmark

Abstract

We provide an empirical evaluation of the forward-looking long-run risks (LRR) model and highlight model differences with the backward-looking habit based asset pricing model. We feature three key results: (i) Consistent with the LRR model, there is considerable evidence in the data of time-varying expected consumption growth and volatility, (ii) The LRR model matches the key asset markets data features, (iii) In the data and in the LRR model accordingly, past consumption growth does not predict future asset prices, whereas lagged consumption in the habit model forecasts future price-dividend ratios with an R2 of over 40%. Overall, our evidence implies that the LRR model provides a coherent framework to analyze and interpret asset prices.

Keywords

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