ABSTRACT
This chapter presents several methods of estimating the parameters needed for portfolio analysis. The most straightforward approach to estimating parameters of return distributions is to use empirical estimators based on observed returns. The same basic approach used to estimate return means and standard deviations may be used to estimate a covariance or correlation of the returns on different assets. Students are often interested in estimating the means, standard deviations, and correlations for the returns, or excess returns, on several assets. When describing the sample mean vector and the sample covariance matrix, it is often convenient to express them in terms of a data matrix. The exponentially weighted moving average (EWMA) approach may be applied to estimation of the mean vector and covariance matrix of a set of asset returns. The Monte Carlo method is used to estimate properties of the sampling distributions of a number of estimators.
