Tracking Error and Tracking Risk

Tracking error is a measure of how closely a portfolio follows its benchmark. A tracking error of zero means that the portfolio exactly follows its benchmark. The benchmark could be an index such as S&P 500 index. Let’s say the S&P 500 index provides a return of 6% and your portfolio tracking the S&P 500 index earns 4% returns. The tracking error is calculated as follows:

In our example, the tracking error will be:

Tracking error = 4% - 6% = -2%

Morningstar defines tracking error as trailing returns.

Tracking Risk: Tracking error sometimes also refers to tracking risk, which is the standard deviation of returns of the portfolio to benchmark returns over a period of time. This is a more commonly used method of calculating tracking error.

Tracking error is an important measure for investors to know how well the portfolio is replicating the index. A low tracking error indicates the portfolio is closely following the benchmark. A high tracking error means the portfolio is moving away from the benchmark index. Investors desire a low tracking error.

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Data Science in Finance: 9-Book Bundle

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
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  • Credit Risk Modelling With R
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  • Machine Learning in Finance using Python

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