There are many ways for portfolio managers to quantify and report on the riskiness of a given portfolio. Perhaps the most common measures of risk include standard deviation and its close relation, variance. Tracking error, sometimes neglected compared to other metrics, is an additional measure that provides important information for investors and portfolio managers alike.

The measures of variance and standard deviation alone give portfolio managers, clients and prospective clients information about the dispersion of returns about the mean. Portfolios with lower standard deviations and lower variance produce more reliable returns, with less volatility. This is useful to know, but doesn’t provide a comprehensive view of the riskiness of many portfolios. Tracking error calculations can help fill some of the gaps that would exist were we to use only variance and standard deviation.

### Tracking Error: An additional way to measure risk

A view of portfolio risk that is centered only around the returns of the portfolio itself and the riskiness associated with those returns will provide little if any information on the *comparative* riskiness of the portfolio. This is especially important if the entire point of the portfolio in question is to perform very similarly to a selected group of securities (SPY, for example, is an ETF that aims to perform very similarly if not nearly identically to the SP500), or in some cases to perform inversely to a selected group of securities (this might be used as part of a strategy to hedge the risk of other investments).

Either way, an additional measure is needed to tell managers and clients about whether or not such portfolios are performing as intended. If the goal of a portfolio is to mirror the performance of the broader market, its standard deviation alone does not provide very meaningful information. This brings us to tracking error.

### Tracking Error Basics

Tracking error does not have a neat definition in the way that standard deviation and variance have well agreed upon formulas. There are several different approaches to calculating portfolio tracking error, and the choice of which approach or approaches to use is an important one for portfolio managers.

The most basic measure of tracking error is to take the return of the portfolio or security in question and subtract the return of the benchmark from it. For example, if SPY had returned 1% and the SP500 had returned .5%, we would subtract the two and find that SPY has tracking error of .5%. Keep in mind that there are numerous methods used to calculate tracking error, and this is the most basic.

Later on we’ll discuss other methods and examine the differences in tracking error produced depending on which method is selected.