Advanced Index Tracking Error Calculator

Calculator Inputs

Enter aligned portfolio and benchmark returns. Use one value per line. The calculator supports percent or decimal input formats.

Portfolio Name

Benchmark Name

Return Format

Frequency

Custom Periods per Year

Annual Fee Adjustment

Use percent if percent format is selected. Use decimal if decimal format is selected.

Standard Deviation Method

Highlight basis-point thinking during review

Portfolio Returns

Benchmark Returns

Period Labels

Optional. Use one label per line, such as months, weeks, or custom observation names.

Formula Used

Tracking error measures how consistently a portfolio differs from its benchmark. First compute each period’s active return:

Active Return_i = Portfolio Return_i − Benchmark Return_i − Fee Adjustment per Period

Then compute the standard deviation of those active returns:

Tracking Error (Periodic) = √[ Σ(Active Return_i − Mean Active Return)² / (n − 1) ]

If population mode is selected, the denominator becomes n instead of n − 1.

Annualized tracking error is: Tracking Error (Annualized) = Tracking Error (Periodic) × √(Periods per Year).

How to Use This Calculator

Enter a portfolio name and benchmark name for clearer result labels.
Paste portfolio returns into the first textarea, one observation per line.
Paste the matching benchmark returns into the second textarea.
Select whether your inputs are percentages or decimals.
Choose the frequency, or select custom and define periods per year.
Optionally include an annual fee adjustment to model net performance drift.
Choose sample or population standard deviation.
Submit the form to see tracking error, active return metrics, the chart, and download options.

Example Data Table

Month	Portfolio Return	Benchmark Return	Active Return
Jan	1.20%	1.00%	0.20%
Feb	0.80%	0.70%	0.10%
Mar	-0.40%	-0.30%	-0.10%
Apr	1.10%	1.00%	0.10%
May	0.50%	0.60%	-0.10%
Jun	1.60%	1.40%	0.20%

This sample matches the default values prefilled in the form. You can replace them with your own return history immediately.

FAQs

1. What does tracking error actually measure?

It measures the volatility of active returns, meaning how much a portfolio’s return pattern deviates from its benchmark over time. Lower values indicate tighter benchmark replication.

2. Is lower tracking error always better?

Not always. Passive index funds usually want low tracking error. Active managers may accept higher tracking error when trying to outperform the benchmark through deliberate positioning.

3. Why do annualized and periodic tracking error differ?

Periodic tracking error reflects the input interval, such as monthly or weekly. Annualized tracking error scales that dispersion by the square root of periods per year for easier comparison.

4. Should I use sample or population standard deviation?

Sample deviation is common when your observations represent a subset of possible outcomes. Population deviation fits cases where the full relevant dataset is already included.

5. Why include a fee adjustment?

Fees can create consistent underperformance versus an index. Applying a fee adjustment helps model net tracking behavior when your raw portfolio return series is pre-fee.

6. Can I use daily, weekly, or monthly data?

Yes. Just choose the matching frequency. The calculator uses that setting to annualize tracking error and active return correctly.

7. What is the information ratio shown here?

It equals annualized active return divided by annualized tracking error. It indicates how much active return was generated per unit of benchmark-relative risk.

8. What happens if my portfolio and benchmark lists differ in length?

The calculator stops and asks for aligned observations. Tracking error requires one benchmark value for every portfolio return in the same period.