Benchmark Evolution
Compare a fund against its benchmark on performance, risk, and allocation.
Benchmark Evolution compares a fund's portfolio against a chosen benchmark to show how closely it tracks and where it diverges. It looks at performance, risk, and how the money is allocated, so you can judge whether the fund is behaving as expected relative to its reference index. It answers: is my fund staying in line with its benchmark, and where is it taking different bets?
How it works
It compares the fund against a chosen reference benchmark, either the one named in the prospectus or a custom one, across several time windows. It measures tracking and divergence on return (tracking error, alpha, beta, cumulative and rolling performance), on risk (volatility), and, for bond funds, on fixed-income traits such as duration, average coupon, and average credit rating. It then compares the fund's allocations (top holdings, countries, sectors, currencies, maturities, and ratings) against the benchmark's, so you can see exactly where it is over or under exposed.
What you get
- Performance versus the benchmark over several windows (month-to-date, year-to-date, rolling year, cumulative), with the amount of out- or under-performance.
- Risk comparison: volatility, alpha, beta, and standard deviation against the benchmark.
- For bond funds: interest-rate sensitivity, average coupon, and average credit quality versus the benchmark.
- Allocation gaps versus the benchmark across top holdings, countries, sectors, currencies, maturities, and credit ratings.
How to use it in Spark
The results arrive in your workspace as data. Filter and sort them in a data view, plot the performance and allocation gaps on a canvas, and let a workflow or the Agent act on what stands out.