Estimation of Equicorrelated Diffusions from Incomplete Data

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.