Advice Engine on Deep Alpha Ad...

Asset Classes

4min

Asset classes are the key building blocks to configure the advice engine and build portfolio models. Deep Alpha advice engine provides full flexibility to define which asset classes will be used to build portfolios. Read more about Portfolio Modelο»Ώο»Ώ

Usage of asset classes

The asset classes are used in a portfolio model to construct your portfolios. The amount of asset classes available to you depends on your investment universe and how you want to construct your portfolios. Read more about Investment Universeο»Ώ

Each selected asset class is associated with a benchmark. See the section under "available benchmarks" for more information. If you select a benchmark with short history, we have functionality for patching the timeseries when building your portfolio model.

In DAAP your asset classes are often referred to as category and will have:

  • Defined equity share used for optimizing portfolios and asset allocation analysis
  • Defined MainAssetClass (Equity vs Fixed Income)
  • Defined SubAssetClass (Your selected name for the asset class)
  • Index ticker - Ticker for the benchmark we use to calculate on the asset class
  • Setting on whether you want to hedge the index for calculation purposes
  • Patching index ticker - Defines which ticker we are patching data with to get long enough history
  • Expected return (Select between historical return or houseview)

Available benchmarks

Data feed benchmarks

We have integration to and offer a datafeed on benchmark. We can offer a wide range of benchmarks that can be used to support your selected asset classes with data. Licence of the usage of benchmarks may vary, depending on the benchmark of your choice. The usage of the benchmark data is also restricted to the usage in DAAP. Reach out to your Quantfolio representative for more information.

Custom benchmarks

If you have benchmarks that are unavailable for our data feeds and/or you want to provide this data yourself, we support usage of custom benchmarks. In order to use this functionality, you need to integrated towards our Time Series API, to set up your datafeed.