Estimation of Equicorrelated Diffusions from Incomplete Data

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The paper derives maximum likelihood parameter estimators for symmetrically correlated Weiner processes observed at discrete intervals. Such processes arise when pricing and determining Value-at-Risk for portfolio derivatives. Cases of driftless and mean-reverting state variables are considered. The procedure is applicable to samples with missing data of any pattern and to high dimensional systems. The estimation procedure is illustrated using a sample of stock prices.
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