Investment in ETFs by Registered Investment Advisors (RIAs) has never been higher. A recent survey conducted by the Financial Planning Association found that 87% of financial advisors recommend ETFs to their clients. The successful use of ETFs by advisors has created a need to accurately provide clients with highly correlated mutual fund and ETF options to help investor clients save money and diversify However, RIAs don’t utilize big data to determine the best ETFs for investment, and therefore are unable to truly determine the best alternative investment options for active mutual funds. Without the correct correlation data, it is impossible to make an informed and knowledgeable investment decision.
The Raltin Big Data Correlations Approach to Providing Alternative ETFs to Mutual Funds
Raltin runs more than 2.5 billion statistical correlations daily which help advisors determine which ETFs correlate with any given mutual fund. This statistical analysis is the best methodology for choosing ETFs as compared to their mutual fund counterparts, and allows advisors to present their clients with better investment options.
The chart below examines three separate mutual funds and the ETFs that have the closest correlations.
|Mutual Fund||Alternative ETF 1 (Correlation Score)||Alternative ETF 2 (Correlation Score)||Alternative ETF3 (Correlation Score)|
|FPURX - Fidelity Puritan Fund||VTI - Vanguard Total Stock Market ETF (0.82)||SCHB - Schwab US Broad Market ETF (0.82)||IWV - iShares Russell 3000 (0.82)|
|VWELX - Vanguard Wellington Fund - Investor||DGRO - iShares Core Dividend Growth (0.86)||VTV - Vanguard Value ETF (0.86)||SCHV - Schwab US Large-Cap Value ETF (0.86)|
|TRBCX - T. Rowe Price Blue Chip Growth Fund Inc.||JKE - iShares Morningstar Large Growth (0.96)||IWF - iShares Russell 1000 Growth (0.96)||MGK - Vanguard Mega Cap Growth ETF (0.96)|
The Fidelity Puritan Fund (FPURX) is a large cap fund with diversified holdings across a variety of sectors. It is more heavily weighted in technology, financial services, and healthcare as compared to other sectors. The correlation between FPURX and the Vanguard Total Market ETF (VTI) is quite obvious, as VTI is not only weighted in the same industries, but its two largest holdings, Microsoft (MSFT) and Amazon (AMZN) are also two of the largest holdings of FPURX. The reason the correlation score of 0.82 is not higher can likely be attributed to the high percentage of government bond holdings in FPURX as compared to the lack of bond holdings in VTI.
The Vanguard Wellington Fund (VWELX) is correlated similarly to the iShares Core Dividend Growth (DGRO) ETF as both have Microsoft (MSFT), JP Morgan (JPM), and Verizon (VZ) in their top 5 holdings.
The Blue Chip Growth Fund from T. Rowe Price (TRBCX), has correlated ETFs with an overwhelmingly high correlation score of 0.96. This correlation can be seen in real-time, as the TRBCX year-to-date return of 11.11% is extremely similar to the JKE return of 12.40% and MGK return of 11.13%.
Making Decisions Using Big Data Analysis
It’s obvious that utilizing such accurate, detailed correlation data to compare mutual funds and ETFs is extremely beneficial for clients and advisors alike. Advisors are provided instant, alternatives to mutual funds without having to process any data themselves. This information can then be used to provide clients better ETF recommendations based on previously discussed and/or utilized mutual funds. This win-win scenario makes Raltin correlation data a critical technology in a RIA’s arsenal.
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