Firms that subscribe to our optional rebranding service can have added, to their semi-bespoke versions of the software, proprietary sets of market assumptions and asset classes. These assumptions will then be available to all of the advisers and clients who use their rebranded version of Voyant.
Two Files are Required to Define Market Assumptions and Asset Classes
To add new set of market assumptions and asset classes to a client configuration, the Voyant Development Team will need two files from the client:
1. An investment averages file, defining the asset classes together with the average and standard deviation for each.
Example File - Investment averages
2. A correlation coefficients file defining the correlation coefficient matrix between each of the asset classes.
Example File - Correlation Coefficient
*Both files should be provided to Voyant in a comma-separated value (.csv) format.
The Investment Averages File
The investment averages file should contain the average and standard deviations for each asset class in the new set of market assumptions.
The investment averages file should contain the average and standard deviations for each asset class in the new set of market assumptions.
Asset classes are defined by their presence as columns in the investment averages file. Each class must be formatted in all caps with an underscore used to represent spaces (e.g. SUB-INVESTMENT_GRADE_BONDS). Voyant will parse these column names smartly, for example:
UK_LARGE_CAP_STOCKS will be parsed and displayed in Voyant as “UK Large Cap Stocks”;
SUB-INVESTMENT_GRADE_BONDS will be parsed and displayed in Voyant as “Sub-investment Grade Bonds”
One asset class, CASH, is required.
There is no limit on the number of asset classes; however, fifteen is the recommended maximum. Introducing over fifteen classes may affect their display in the Voyant user interface.
There is no limit on the number of asset classes; however, fifteen is the recommended maximum. Introducing over fifteen classes may affect their display in the Voyant user interface.
The resulting investment averages file should be similar in format to the example shown below.
Note - The Growth Character is for Finametrica so, if you don't use Finametrica, it's not needed. If you do use Finametrica, the 'Growth Character' refers to the degree to which an asset class is a 'growth' asset vs. a 'defensive' asset. 0 means 100% defensive. 1 means 100% growth. It’s how Finametrica classifies the risk profile of an asset class and, thereby, an asset allocation.
Formatting requirements:
The following example shows how an investment averages file should be formatted.
• The header row should contain asset classes formatted in all caps, with spaces replaced with underscores.
• Asset classes, which serve as the column headings, must be formatted in all caps with underscores used to represent spaces.
• CASH is a required asset class with all other being client defined.
• There is no maximum limit on the number of asset classes; however, having over fifteen classes may affect their display in the Voyant user interface.
• The Investment Averages file should be sent to Voyant in a comma-separated value (.csv) format.
• Column headings must be upper-cased.
Please note that the values shown are test data, used only for purposes of example.
The Correlation Coefficient File
The correlation coefficients file defines the correlation coefficient matrix between each of the asset classes in the market assumptions set. Asset class names used in this file must match, verbatim, those defined in the investments averages file.
The correlation coefficient indicates the strength and direction of a linear relationship between two random variables. The correlation coefficient ranges from +1, indicating a perfect positive linear relationship, to -1, indicating a perfectly negative linear relationship.
One major caveat applies to the use of a correlation coefficient matrix in Voyant. The correlation coefficient must be positive definite. For this reason, the correlation coefficient matrix cannot be random, as random numbers usually result in matrices that are not positive-definite.
One recommended way compute the correlation coefficients for a data set is to use the Excel CORREL function on the historical prices for each combination of asset classes.
1. Take the historical prices (dating back as far as possible) for each asset class and add them to an Excel spreadsheet.
2. Use Excel functions to compute an average and standard deviation for each asset class.
3. Then using the historical prices for each combination of 2 asset classes, use the Excel CORREL function to compute the correlation coefficient for the asset pair.
The resulting matrix should be similar in arrangement to the example shown on the following page.
Formatting requirements:
The following example shows how a correlation coefficients file should be formatted.
The following example shows how a correlation coefficients file should be formatted.
• The header row and row labels must contain asset classes formatted in all caps, with spaces replaced with underscores.
• The names of asset classes must match, verbatim, those defined in the accompanying Investment Averages file.
• The Correlations Coefficients file should be sent to Voyant in a comma-separated value (.csv) format.
Please note that the values shown are test data, used only for example.
Adding model portfolios to your firm's White Label