Potential Proxies

Rev. Date December 12, 2022

What is a proxy and how are they used on Venn?

Sometimes an investment does not have sufficient historical returns data to be analyzed on Venn, as most analytics on the platform require at least 1 year of monthly data[1] for analysis. To enable analysis of such investments, users can opt to use other investments, or “proxies,” that appear to have similar historical return streams to the subject investment. Proxies can be used for three main purposes:

  1. Backfilling or Substitution – users can append proxy returns to investments to lengthen the analysis period. Alternatively, users can “substitute” a given investment with another investment, which will replace the entire return stream with that of the chosen substitute. Adding in a substitute will not delete the originally uploaded data.

  2. Interpolation and Extrapolation – proxies can be used to increase the return frequency from quarterly to daily, and/or to fill the gap between the last reported valuation and today’s by estimating its valuation for investments reported on a lag.

  3. Desmoothing – publicly traded proxies can be used to desmooth private asset returns, decreasing autocorrelation of private assets in an effort to better capture their true economic returns.

What is an example of a proxy?

For example, say a user invested in Manager A, a long-only U.S. Large Cap bottom-up stock picker. The Manager has provided actual returns dating back to 2010. However, the user would like to run analysis on their entire portfolio, including Manager A, going back to 2000. In order to do this, the user could use the S&P 500 Index to proxy the returns of Manager A from 2000-2009.

What are the limitations of a proxy?

Proxies are merely estimates of an investment’s return history and will be less accurate than using an investment’s actual returns. All else equal, the less return history there is for an uploaded investment, the more difficult it will be to find an accurate proxy and therefore the estimates will be less accurate.

How can I select a proxy for an investment on Venn?

Users can select proxies for investments in several places throughout Venn, including:

  1. Library: click the three dots under the Actions column and click “Add a Proxy”

  2. Tearsheet: click “Proxy Data” (“arrow” icon) at the top of the page

  3. Manage Data: click the “gear” icon at the top right of any analysis and then click “Analysis Date Range.” Click “Add a Proxy” for any investment of interest.

When clicking to add a proxy on an investment, users may be prompted to select from Venn’s identified “potential proxies” (if Venn can find a potential match for the investment using the methodology outlined below). Alternatively, users may search for a proxy based on their own preferences. After a proxy has been set, users can view the proxy date range[2] as well as its correlation to the subject investment for the overlapping period.

Users may change or remove proxies at any time through the Library, Investment Analysis, or Manage Data pages. Venn will not automatically change a proxy on users’ behalf, even if the subject investment’s return history becomes sufficient for Venn analysis.

What types of investments can be used as proxies on Venn?

Investments that can be used as proxies include pre-populated investments on Venn such as indices, ETFs, and mutual funds. Additionally, user-uploaded investments can be used as proxies, although such investments will not be used by Venn to suggest potential proxies.

How does Venn help users identify potential proxies?

Venn identifies potential proxies, which users may opt to use, for subject investments. Venn seeks to suggest investments whose return history is pre-populated on Venn and is similar to those of the subject investment, and that might be suitable for use as a proxy.

Please note that Venn will not automatically select a potential proxy for any given investment. Rather, Venn will seek to identify potential proxies, and the user can opt to select one of the identified potential proxies, select a different investment whose returns are available on Venn (including investments uploaded by the user) to use as a proxy, or proceed without a proxy.

Venn will not alert users in the event that the correlation between a selected proxy and the subject investment drops, making it a less accurate proxy. However, users can view the correlation between the investment and selected proxy at any time in Data Management.

What is the minimum number of data points for a subject investment that Venn requires to identify a potential proxy?

Venn requires at least 6 data points[3] to identify a potential proxy.

How does Venn approach identifying potential proxies?

Venn identifies potential proxies by conducting a search through its library of pre-populated investments, such as indices, ETFs, and mutual funds and finding investments that have high match scores with the subject investment. The match score is a proprietary measure between 0% and 100% that is calculated using cosine similarity and tracking error. Potential proxies with higher cosine similarity and lower tracking error (i.e., the volatility of the differences between return streams over time) to the subject investment will result in a higher match score. Venn does not prompt users to select potential proxies with match scores less than 50%.

What is cosine similarity?

Cosine similarity is a measure that is comparable to correlation. It seeks to identify the extent to which two investments move in the same direction. Instead of centering around a return stream’s mean, like correlation does, cosine similarity is centered around zero and measures the cosine of the angle between two data points.

Proxies are for estimation purposes only and have many inherent limitations. The methodology for calculating potential proxies was chosen in our professional judgment, and will not always yield the most accurate available proxy. Our potential proxy suggestions are not a recommendation as to any portfolio, allocation, strategy, or investment nor an offer to purchase or sell any security. We suggest users do their own research to use the public proxy that best fits their own use case.

[1] The minimum amount of data required depends on data frequency and type of analysis. As an example, Venn will require at least 6 months of daily data, 1 year of monthly data, or 3 years of quarterly data (12 data points) for factor analysis.

[2] The proxy date range starts when Venn has data for the proxy and ends when the subject investment data begins.

[3] Daily returns are rolled up to weekly, therefore 6 weeks are required for investments with daily data. 6 months are required for investments with monthly returns. Venn requires a minimum of 3 years, or 12 quarterly returns, for interpolation, extrapolation or desmoothing. Investments with quarterly data cannot be backfilled using a proxy on Venn.

This document highlights certain aspects of this feature. As an overview, it does not discuss all material facts or assumptions. Please see Important Disclosure and Disclaimer Information.

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