Risk-minimizing hedging strategies under restricted information: The case of stochastic volatility models observable only at discrete random times
This paper studies risk-minimizing hedging strategies in a diffusion model with a stochastic volatility driven by a Markov process \(X\), when the price process can only be observed at the jump times of a Cox process whose intensity is also driven by \(X\). This is rewritten as a problem of hedging under restricted information as in the reviewer's paper [cf. \textit{M. Schweizer}, Math. Finance 4, 327-342 (1994; Zbl 0884.90051)], and the Markovian structure of \(X\) reduces this to solving an integro-partial differential equation. Under suitable assumptions, the involved conditional expectations can also be computed by filtering techniques.
scientific article; zbMATH DE number 1370338