We believe 70+ value ETFs traded on NYSE are tracking outdated metrics.
Value indices have been around for decades. Prominent names include S&P 500 Value Index, Russell 3000 Value Index, MSCI World Value Index, and countless more. Financial institutions not only use them as benchmarks for performance comparisons, but also as reflections of their financial products. More than $8 trillion USD are invested in passively managed ETFs that track indices by mirroring their holdings. A significant chunk of passively managed ETFs is composed of value ETFs, ETFs that track value indices as those mentioned above.
What a shame it would be if the indices our financial system relies so heavily upon may actually be outdated. Unfortunately, we feel investors today live that shame.
According to S&P, there are 3 main criteria for a stock to be considered part of a value index: its book value to price ratio (P/B), earnings to price ratio (P/E), and sales to price ratio (P/S). Of the 3, the first is most concerning.
The book value to price ratio compares a company’s market capitalization to its asset values. A low price to book ratio would suggest that a stock is undervalued and hence could be a lucrative investment. A major criticism for this ratio, however, is that it completely disregards the value of intangible assets. Sans the intangible assets, the value of total assets of a company are likely immensely understated.
As of September 2020, the value of intangible assets of the top 10 companies in the world was $10.8 trillion. Given the technological advancements within the business paradigm, companies’ proportion of intangible assets are likely to increase exponentially. In 1975, intangible assets represented only 14% of S&P 500 companies’ assets. In 2018, the percentage was at least 84%.
- Brand Finance. (2020, October). Global Intangible Finance Tracker (GIFT) – an annual review of the world’s intangible value. https://brandirectory.com/reports/gift-2020
With the value of intangible assets potentially understated, the P/B ratios of companies heavily invested in intangibles look unfairly unattractive.
The indices’ limitations do not stop there. Index constituents are first ranked based on their growth and value scores, and then sorted in ascending order of the growth / value rank ratio. The top 33% are placed in the growth index basket; the bottom 33% are placed in the value index basket; and the middle 34% are spread between the two indices depending on their scores. This means that stocks with little value characteristics are often designated to value indices, just because they have low growth ranks.
Furthermore, value indices are rebalanced at long intervals. The S&P 500 Value Index is rebalanced quarterly; the MSCI World Value Index semi-annually; and the Russell 3000 Value Index and the S&P 500 Pure Value Index annually. The inevitably creates time lags between performance realizations and subsequent adjustments. Even if the index issuer realizes securities’ value characteristics have worn out, she needs to wait until the next rebalancing period to adjust the weightings of index constituents.
What does this mean for investors?
Investors who invest in passively managed value ETFs (ETFs that mirror a value index) may be, in essence, investing in a pool of securities that only remotely resemble value stocks. We believe the epitome of value investing would be picking stocks based on not only companies’ sales and earnings, but also on the value of their intangible assets. By indices’ failure to do so, we believe investors may also be failing. Moreover, even if the ETF is carrying stocks that carry little or no “value” characteristics, the issuer must wait until the parent index has been rebalanced appropriately.
Some Investors who have picked this up have been relying upon AI to calculate companies’ intangible assets and invest accordingly. Through machine learning, artificial intelligence may be able to pick up important data in a plethora of fields and attempt to produce accurate projections for stocks’ growth potential. NVQ, of Qraft Technologies, is an ETF that invests in value stocks, depending on their intangibles. (It is rebalanced on a monthly basis.) The AI model, by gauging intangible assets in an aim to correct the traditional value metrics, is up 22.67% since its inception on 12/02/20 on the New York Stock Exchange until 3/31/21.
The performance data quoted represents past performance. Past performance does not guarantee future results. Current performance may be lower or higher than the performance data quoted. The investment return and principal value of an investment will fluctuate so that an investor’s shares, when sold or redeemed, may be worth more or less than their original cost. Returns less than one year are not annualized. Performance data current to the most recent month end may be obtained by visiting qraftaietf.com/nvq.
Market Price: The current price at which shares are bought and sold. Market returns are based upon the midpoint of the last bid/ask spread at 4:00 PM Eastern Time.
NAV: The dollar value of a single share, based on the value of the underlying assets of the fund minus its liabilities, divided by the number of shares outstanding. Calculated at the end of each business day.
Annual Expense Ratio is 0.75%.
Investors should consider the investment objectives, risks, charges and expenses carefully before investing. For a prospectus or summary prospectus with this and other information about the Fund, please call 1-855-973-7880 or visit our website at www.qraftaietf.com. Read the prospectus or summary prospectus carefully before investing.
The Funds are distributed by Foreside Fund Services, LLC
Investing involves risk, including loss of principal. The Funds are subject to numerous risks including but not limited to: Equity Risk, Sector Risk, Large Cap Risk, Management Risk, and Trading Risk. The Funds rely heavily on a proprietary artificial intelligence selection model as well as data and information supplied by third parties that are utilized by such model. To the extent the model does not perform as designed or as intended, the Fund’s strategy may not be successfully implemented and the Funds may lose value. Additionally, the funds are non-diversified, which means that they may invest more of their assets in the securities of a single issuer or a smaller number of issuers than if they were a diversified fund. As a result, each Fund may be more exposed to the risks associated with and developments affecting an individual issuer or a smaller number of issuers than a fund that invests more widely. A new or smaller fund's performance may not represent how the fund is expected to or may perform in the long term if and when it becomes larger and has fully implemented its investment strategies. Read the prospectus for additional details regarding risks.
While it is anticipated that the Adviser will purchase and sell securities based on recommendations by the U.S. Large Cap Database, the Adviser has full discretion over investment decisions for the Fund. Therefore, the Adviser has full decisionmaking power not only if it identifies a potential technical issue or error with the U.S. Large Cap Database, but also if it believes that the recommended portfolio does not further the Fund’s investment objective or fails to take into account company events such as corporate actions, mergers and spin-offs.
QRAFT AI-Enhanced U.S. Large Cap ETF: Companies in the health care sector are subject to extensive government regulation and their profitability can be significantly affected by restrictions on government reimbursement for medical expenses, rising costs of medical products and services, pricing pressure (including price discounting), limited product lines and an increased emphasis on the delivery of health care through outpatient services.
QRAFT AI-Enhanced U.S. Large Cap Momentum ETF: The Fund is subject to the risk that market or economic factors impacting technology companies and companies that rely heavily on technology advances could have a major effect on the value of the Fund’s investments. The value of stocks of technology companies and companies that rely heavily on technology is particularly vulnerable to rapid changes in technology product cycles, rapid product obsolescence, the loss of patent, copyright and trademark protections, government regulation and competition, both domestically and internationally, including competition from foreign competitors with lower production costs. Technology companies and companies that rely heavily on technology, especially those of smaller, less-seasoned companies, tend to be more volatile than the overall market.
QRAFT AI-Enhanced US High Dividend ETF: Securities that pay dividends, as a group, may be out of favor with the market and underperform the overall equity market or stocks of companies that do not pay dividends. In addition, changes in the dividend policies of the companies held by the Fund or the capital resources available for such company’s dividend payments may adversely affect the Fund. In the event a company reduces or eliminates its dividend, the Fund may not only lose the dividend payout but the stock price of the company may also fall.
QRAFT AI-Enhanced U.S. Next Value ETF: The value approach to investing involves the risk that stocks may remain undervalued, undervaluation may become more severe, or perceived undervaluation may actually represent intrinsic value. Value stocks may underperform the overall equity market while the market concentrates on growth stocks. The small- and mid-capitalization companies in which the Fund invests may be more vulnerable to adverse business or economic evens than larger, more established companies, and may underperform other segments of the market or the equity market as a whole. Securities of small- and mid-capitalization companies generally trade in lower volumes, are often more vulnerable to market volatility, and are subject to greater and more unpredictable price changes than larger capitalization stocks or the stock market as a whole.
Alpha – Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index.
AutoML – Short for Automated Machine Learning, AutoML is the automation of the machine learning process to make machine learning jobs simpler, easier, and faster.
Kirin API - Developed by Qraft’s data scientists, integrates multiple vendors to provide both macroeconomic and company fundamentals with the correct point-in-time data.