The author questions managed-futures performance reports despite his own participation in the industry. He discusses successful funds being more eager to report, departures from the sample and the limitations of self-reported results.
Choose the group before the outcome
An important teaching extension is to fix the cohort at the beginning and follow every member, including those that close or stop reporting. Dropping disappearing members can transform the question from “how did the group perform?” into “how did the survivors perform?”
Worked example
Five fictional funds start a study. Two close after large losses. Reporting only the remaining three does not describe the original five-fund experience.
Case connection
A starting cohort prevents disappearing funds from silently improving the comparison. Missing observations need explicit treatment.
SPIVA: include the missing funds
Source-grounded facts
SPIVA evaluates the whole starting opportunity set, including funds that disappear, to address survivorship bias.
Context
Fund-performance comparisons can quietly change when unsuccessful funds close or merge. SPIVA’s published methodology addresses that problem by retaining the starting opportunity set.
Outcome
Including disappeared funds reduces survivorship bias. It does not make every benchmark choice perfect; it makes the population being evaluated more explicit and harder to improve by hindsight.
- The comparison identifies the eligible fund universe at the beginning of the evaluation period.
- It accounts for funds that disappear rather than comparing only those still present at the end.
- It also uses relevant benchmarks and reports results over specified horizons.
Case analysis
Ask what would happen to the comparison if the worst participants disappeared. If removing them improves the average, the remaining sample is answering a survivor question. Follow the original group and describe how closures, mergers and missing observations are treated. A clear population definition is necessary before arguing about which method outperformed.
Try it
For a performance claim, write who was eligible at the start, who disappeared and how missing observations were handled.