What data is needed to assess Ulcer Index?

Direct answer

To assess Ulcer Index, you need a consistent historical time series and a clear method to convert that series into drawdowns. You also need to document how the data was collected (source and preprocessing), the timeframe and sampling frequency, and the calculation assumptions used to form the index. Because Ulcer Index is sensitive to these choices, you should verify inputs and reproduce the calculation before treating any computed value as meaningful.

Mechanism or definition

Ulcer Index is designed to quantify the “depth” of declines relative to a running peak in a chosen series. In practice, assessment starts with these data inputs:

A defined time series

Usually a price, equity value, or any numeric level series that represents performance over time.
You must define whether the series uses close-to-close values, adjusted values, bid/ask midpoints, or another specific convention.

Time boundaries and sampling frequency

The exact start date, end date, and the interval between observations (for example, daily, hourly, or another fixed step).
If the series is not evenly sampled, you need rules for handling gaps.

Running peak and drawdown calculation inputs

For each observation, compute the running maximum up to that date.
Then compute drawdown as the percentage (or absolute) drop from the running peak to the current value.

Data preprocessing and transformation assumptions

If the series is an instrument with corporate actions or structural changes, you need to use a consistent adjustment method.
Decide whether to use raw values or adjusted values, and keep that choice consistent across comparisons.

The Ulcer Index computation method

Ulcer Index is computed from the drawdowns (commonly using squared drawdown magnitudes and an aggregation across the period).
To assess it, record the precise formula or calculation steps used, including units (percentage vs. decimal) so results can be reproduced.

Evidence or example

A practical assessment checklist focuses on reproducibility, not prediction. For example, if you want to compute Ulcer Index for a specific instrument over a defined period:

Assumption: You choose a daily closing-price series sampled once per trading day.
Input: You collect the closing values for the exact dates in your chosen window.
Provenance: You record where the series comes from (provider, extraction method, and whether values are adjusted).
Timeliness: You verify that the dataset matches the intended historical window and has no accidental mix of later revisions.
Quality check: You confirm there are no missing dates or duplicated timestamps; if there are, you apply a stated rule (for example, exclude the incomplete segments or resample).
Calculation check: You recompute the running peak and the drawdown series, then apply the same aggregation method that produces Ulcer Index.

If two analysts use different timeframes, different sampling frequency, or different drawdown definitions, their Ulcer Index values can differ even when using the “same” underlying instrument. Therefore, the evidence that matters most is the documented method and the ability to reproduce the calculation from the stated inputs.

Limitations and risks

Several failure modes affect Ulcer Index assessment:

Series-definition risk: Changing the underlying series (for example, adjusted vs. unadjusted values, or using a different price convention) changes drawdowns and therefore the index.
Timeframe sensitivity: Ulcer Index is sensitive to the selected period and sampling frequency; historical decline “shape” can be emphasized or diluted by the chosen horizon.
Missing-data risk: Gaps, outliers, and inconsistent timestamp handling can create artificial peaks or drawdowns.
Computation ambiguity: If one calculation uses percentage drawdowns and another uses decimals (or if one squares a different quantity), results won’t be comparable.
Misinterpretation risk: A computed Ulcer Index summarizes past decline behavior for that series and window; historical relationships do not guarantee future outcomes.

Verification or next question

To independently verify Ulcer Index facts, you should be able to answer these readiness questions:

Do you have the exact input series, sampling frequency, and date range?
Are drawdowns defined consistently using the same running peak method?
Is the Ulcer Index formula or aggregation step clearly stated and applied to the same drawdown units?
Have data quality checks been documented (missing points, duplicates, outliers, adjustments)?

If you cannot clearly specify these inputs and assumptions, the safest conclusion is that the computed Ulcer Index value is not independently verifiable.