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frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information … content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically … exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient …
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frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information … content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically … exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient …
Persistent link: https://www.econbiz.de/10013122082
I generalize the long-run risks (LRR) model of Bansal and Yaron (2004) by incorporating recursive smooth ambiguity aversion preferences from Klibanoff et al. (2005, 2009) and time-varying ambiguity. Relative to the Bansal-Yaron model, the generalized LRR model is as tractable but more flexible...
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We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...
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