Volatility Inference and Return Dependencies in Stochastic Volatility Models

Oliver Pfante and Nils Bertschinger

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Abstract: Stochastic volatility models describe stock returns $r_t$ as driven by an unobserved process capturing the random dynamics of volatility $v_t$. The present paper quantifies how much information about volatility $v_t$ and future stock returns can be inferred from past returns in stochastic volatility models in terms of Shannon's mutual information.

Date: 2016-10
New Economics Papers: this item is included in nep-fmk
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1610.00312

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