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.
Copyright is held by the author(s).
You are free to copy, distribute and transmit this work under the following conditions: You must give attribution to the work (but not in any way that suggests that the author endorses you or your use of the work); You may not use this work for commercial purposes.
Member of collection