ETF Factor Report

Data as of market close on 10/26/2021.

Validea's ETF reports provide factor exposures and other fundamental data for US equity ETFs.
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First Trust Large Cap US Equity Sel ETF (RNLC)

Total Assets: $31,924,900 Expense Ratio: 0.60% Active Share vs. S&P 500: 54.61% Active Share vs. Russell 2000: 99.69% Fee for Active Share: 1.10% Fee for Quality Exposure: 0.82% Highest Scoring Metric: Return on Total Capital
Issuer:First Trust Validea Category: Large-Cap Quality Number of Holdings: 339 Median Mkt Cap (mil): $38,796 Average Mkt Cap (mil): $124,118 Implied Liquidity: $709,895,800 Concentration: 21/100
The investment seeks investment results that correspond generally to the price and yield (before the fund s fees and expenses) of an equity index called the Nasdaq Riskalyze US Large Cap Index (the 'index'). The fund will normally invest at least 90% of its net assets (including investment borrowings) in the common stocks and real estate investment trusts ('REITs') that comprise the index. The index is designed to select dividend-paying securities issued by large capitalization U.S. companies.

Factor Profile

RNLC's exposure to the major factors (100 is highest).

RNLC Sector Exposure

Largest overweights and underweights relative to the S&P 500

RNLC Industry Exposure

Largest overweights and underweights relative to the S&P 500

Comparable ETFs

ETFs with the closest factor profiles to RNLC.

(click ticker to access ETF report and name to compare to current ETF)

Ticker Ticker
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CFA IUS
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Performance Disclaimer: Returns presented on Validea.com are model returns and do not represent actual trading. As a result, they do not incorporate any commissions or other trading costs or fees. Model portfolios with inception dates on or after 12/30/2005 include a combination of back tested and live model returns. The back-tested performance results shown are hypothetical and are not the result of real-time management of actual accounts. The back-testing of performance differs from actual account performance because the investment strategy may be adjusted at any time, for any reason and can continue to be changed until desired or better performance results are achieved. Back-tested returns are presented to provide general information regarding how the underlying strategy behind the portfolio performed in our historical testing. A back-tested strategy has the benefit of hindsight and the results do not reflect the impact that material economic or market factors may have had on advisor's decision-making if actual client assets were being managed using this approach. The model portfolios offered on Validea are concentrated and as a result they will exhibit high levels of volatility and their performance can be substantially impacted by the performance of individual positions.

Optimal portfolios presented on Validea.com represent the rebalancing period that has led to the best historical performance for each of our equity models. Each optimal portfolio was determined after the fact with performance information that was not available at portfolio inception. As a result, an investor could not have invested in the optimal portfolio since its inception. Optimal portfolios are presented to allow investors to quickly determine the portfolio size and rebalancing period that has performed best for each of our models in our historical testing.

Both the model portfolio and benchmark returns presented for all equity portfolios on Validea.com are not inclusive of dividends. Returns for our ETF portfolios and trend following system, and the benchmarks they are compared to, are inclusive of dividends. The S&P 500 is presented as a benchmark because it is the most widely followed benchmark of the overall US market and is most often used by investors for return comparison purposes. As with any investment strategy, there is potential for profit as well as the possibility of loss and investors may incur a loss despite a past history of gains. Past performance does not guarantee future results. Results will vary with economic and market conditions.