Research released along with the product announcement indicates that traditional quantitative methods – such as Value-at-Risk (VaR) – for measuring investment risk most often underestimate potential risk.
“The biases are such that the standard deviation of return in a pension fund’s equity portfolio may be understated by 40% or more,” said Robert Kuberek, a senior MD at Wilshire, in a press release. “As a result, the excess value at risk for a conventional equity portfolio may be as much as 5% of the portfolio. For a typical individual investor with a $500,000 retirement nest egg, this could amount to an unintended exposure to loss of as much as $25,000 during a one year period.”
Kuberek stressed that a critical step in the risk measurement process is estimation of the variances and covariances for the variables that drive changes in portfolio value. These numbers, arranged in an array called a matrix, summarize the risk level of the underlying variables, taking into account the tendency of some of the variables to move together, according to the news release. Frequently, the matrix of variances and covariances is estimated using historical returns; however, he noted that when historical returns are used to estimate variances and covariances, noise in the particular sample employed results in errors in the estimated covariance matrix. This means that some of the sample covariances will be smaller and some larger than they really are.
Wilshire’s Structured Hadamard Product Target Shrinkage Estimator (SHaPTSE) program works by adjusting the sample covariance matrix in a way that takes into account things that are known about the true covariance matrix, according to the company. The estimator has been incorporated into the company’s most recent analytical systems – including The Wilshire Atlas, The Wilshire Axiom, The Wilshire Spectrum, and The Wilshire iQuantum – that are available to investment professionals.
Wilshire ( www.wilshire.com ) is a global investment technology, consulting and management firm.