MantaRisk supports composite benchmarks to, for instance, run a performance attribution analysis against a benchmark made of 60% SPY and 40% AGGG for instance.

Step 1 - Create a Synthetic Instrument

The first step is to create a composite benchmark is to create a synthetic instrument which will be used to reference it throughout the system. To do so, a call to the PUT history endpoint is required with a payload such as this:

{
  "instrument": {
    "instrument_code": "MyUniqueCode",
    "asset_class": "C",
    "currency": "USD",
    "name": "My Composite Benchmark"
  }
}

Step 2 - Find Your User Feed API ID

Call the GET history/api endpoint and store the apiid associated with the api_name "User Feed". This is the unique API ID associated with your account which allows you to enter your own time series.

Step 3 - Create the Composite Benchmark

To compose the benchmark, a call to the PUT index endpoint must be made. In this case:

• instrument_code will be MyUniqueCode
• apiid will be the API ID you stored in step 2

The payload here will look like this:

[
  {
    "apiid": 8,
    "instrument_code": "CSSPX_XSWX",
    "ratio": 0.6,
    "decompose": true
  },

  {
    "apiid": 8,
    "instrument_code": "AGG_ARCX",
    "ratio": 0.4,
    "decompose": false
  }
]

The decompose flag indicates whether the instrument should be used as is or decomposed into its individual holdings when we are carrying the analysis.

Step 4 - Run the Performance Attribution Analysis

Finally, the GET index/attribution endpoint must be called to carry the analysis, with the following parameters:

• client_reference the reference of your portfolio (see the Portfolio Creation section for more details)
• instrument_code as per Step 1
• apiid as per Step 2
• horizon period over which the analysis will be carried. All analytics will be expressed in relation to this period
• model see Performance Attribution Models for more details