Journal of Finance
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Выпуск N5 за 1993 год
Опубликовано на портале: 02-11-2007Chris I. Telmer Journal of Finance. 1993. Vol. 48. No. 5. P. 1803-32.
The representative agent theory of asset pricing is modified to incorporate heterogeneous agents and incomplete markets. The model features two types of agents who differ up to a nontradable, idiosyncratic component in their endowment processes. Numerical solutions indicate that individuals are able to diversify a substantial portion of their idiosyncratic income risk through riskless borrowing and lending alone. Restrictions on the variability of intertemporal marginal rates of substitution are used to argue that incomplete markets, as modeled here, cannot account for the properties of asset returns that are anomalous from the perspective of representative agent theory
Опубликовано на портале: 07-04-2004Robert F. Engle, Victor K. Ng Journal of Finance. 1993. Vol. 48. No. 5. P. 1749-1778.
This paper defines the news impact curve which measures how new information is incorporated into volatility estimates. Various new and existing ARCH models including a partially nonparametric one are compared and estimated with daily Japanese stock return data. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. Our results suggest that the model by Glosten, Jagannathan, and Runkle is the best parametric model. The EGARCH also can capture most of the asymmetry; however, there is evidence that the variability of the conditional variance implied by the EGARCH is too high.
On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks [статья]
Опубликовано на портале: 07-04-2004Lawrence R. Glosten, Ravi Jaganathan, David E. Runkle Journal of Finance. 1993. Vol. 48. No. 5. P. 1779-1801.
Authors finds support for a negative relation between conditional expected monthly return and conditional variance of monthly return, using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on conditional volatility, and (3) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, we also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional volatility whereas negative unanticipated returns result in an upward revision of conditional volatility.