Asset Class Group Scores Tactical Allocation Custom Models

We're excited to announce the addition of custom Asset Class Group Scores models into our Model Builder tool on September 30, 2024. This functionality will allow you to create custom tactical allocation models based on our Asset Class Group Scores asset allocation report. 

What is Asset Class Group Scores?

Asset Class Group Scores is one of our asset allocation reports that uses NDW's fund scores to help you identify the strongest areas of the market from a relative strength perspective. To develop the Asset Class Group Scores rankings, we assign every fund in the NDW database to the appropriate investment category and average the fund scores of every fund in that category. The report is designed to help you tactically overweight areas of strength and underweight areas of weakness. 

How do Asset Class Group Scores models work?

Asset Class Group Scores models allow you to create a rules-based tactical allocation strategy designed to systematically overweight the areas of the market with the highest relative strength. 

What can I include in an Asset Class Group Scores model?

There are 44 investment categories eligible to be included in an Asset Class Group Scores model with a maximum of 15 investment categories included in a single model. This allows you to expand beyond the 6 asset classes available in Custom DALI models so you can create more granular strategies. In addition to creating strategies for asset class rotation, you are able to include sectors, size & style categories, fixed income sectors, and more. 

Within each investment sleeve, you can include any type of asset from the NDW database, including NDW models, custom models, ETFs, Mutual Funds, and stocks. 

When would I use Asset Class Group Scores models over the other model types?

Asset Class Group Scores vs. DALI

• You prefer Asset Class Group Scores to DALI
  • DALI, which is based on the Matrix, and Asset Class Group Scores, which is based on fund scores, react to market changes differently and at different speeds. You may prefer the way one reacts and choose that as the basis for your tactical allocation strategy. 
• You want to go a level deeper than custom DALI models allow
  • Asset Class Group Scores models allow you to rank sectors, size & style categories, and other sub-asset class categories that are not currently available in custom DALI models

Asset Class Group Scores vs. Static Allocation

You want to tactically overweight sleeves of your portfolio when they are in favor from a relative strength perspective. 

Asset Class Group Scores vs. Matrix/FSM

You want to create a top-down relative strength model

• While Matrix and FSM models will likely naturally allocate to the highest relative strength market segments, the allocations will be determined through an entirely bottom-up process. To create a top-down process or to ensure minimum allocations to specific market segments, Asset Class Group Scores would be a better option.  

How does an Asset Class Group Scores model determine it's allocation?

The allocation for an Asset Class Group Score model works identically to how DALI model allocations are determined. 

1. Each investment category is assigned a minimum and maximum allocation
2. All investment categories are filled to their minimum allocation
3. The remainder of the allocation is allocated based on the investment categories' average fund scores
   1. Whichever investment category is ranked first is filled to its maximum allocation or as far as possible
   2. If any allocation remains, the category ranked second is filled to its maximum or as far as possible
   3. This is repeated until the portfolio is fully allocated

How do I build an Asset Class Group Scores model?

An overview of the process for creating a model is below. For more complete information, reference this help center article. 

1. Go to the Custom Models page
2. Select Create New Model and choose the 'ACGS' model type
3. Select your investment categories, set minimum and maximum allocations for each, and choose your evaluation frequency 
4. Select the investments that make up the allocation to each investment category
5. Set Your Backtest Parameters
6. Run Your Backtest
7. Save Your Model