Value ETFs constitute some of the largest factor ETFs in the industry with an estimated $360 billion AUM, with the largest having around $85 billion AUM. However, the majority of value ETFs, and therefore the majority of capital parked in these vehicles, track a handful of similar indexes. One of them being the CRSP U.S. Large Cap Value Index[i], and another being the S&P 500 Value Index[ii], with these two indices also sharing many similarities to each other.
With these conditions, we believe it can be difficult to distinguish value ETFs from one another, with most seemingly offering similar value propositions.
NVQ, Qraft’s AI-Powered Value ETF, however, offers a breath of fresh air in a space where innovation has been lagging for a while. Not only does NVQ have a comparatively radical method to value investing, but it has also outperformed the two benchmarks indices that most of the value ETFs closely mimic as well.
This illustration is for informational purposes only and does not represent actual investing results.
Performance data quoted represents past performance and is no guarantee of future results. Current performance may be lower or higher than the performance data quoted. Investment return and principal value will fluctuate so that an investor’s shares, when redeemed, may be worth more or less than original cost. Returns less than one year are not annualized. For current standard performance and expenses, visit https://qraftaietf.com/nvq
The Fund’s performance assumes the reinvestment of all dividends and all capital gains distributions. Investors cannot directly invest in an index.
One of the reasons behind the overperformance of NVQ versus that these indicies is its new approach to valuing intangible assets. This process is made possible by Qraft’s vertical approach to utilizing its proprietary AI.
In the first stage, it can carefully parse vast amounts of data using Qraft’s Kirin API[iii], enabling the utilization of what believes is most appropriate data for a given task. The importance of intangibles in valuation can also change in relation to sector and market conditions. NVQ can use Natural Language Processing[iv] (NLP) to create accurate blended sector labels to assess which the mix of businesses a company may have. Building on this foundation Qraft AI is able to use its data and AI powered processing to assess Return on Research Capital (RORC) using R&D cost, patent, and marketing data.
This entire approach is packaged in a monthly and rebalanced, actively managed ETF, which allows NVQ to be flexible in changing its positions based on not only market conditions but as well as recent news and developments. It provides a unique approach that is both transparent and liquid, which allows investors exposure to a new side to value investing.
The proof in NVQ’s divergence from the value ETF industry norm is shown in its differences in sector weights. A quick glance comparing the composition of sector weights of NVQ and that of the S&P 500 Value Index can visualize the differences between the two approaches to valuation.
The stark differences in sector weighting can only be translated into different holdings as well, which itself will naturally lead to divergences in performance from the norm. This is illustrated by the top 5 holdings of NVQ and its leading competitors in the value ETF category. We believe having a flexible sector strategy is important especially given the current trends in the last few years. With the current uncertainty in yields and rising inflation, it may be difficult for investors to find flexible ways to hedge their investments. Certain sector performances have started to diverge from economic cycles, as was the established norm. So far in 2021, we have seen how many sector thematic ETFs, especially in the tech sector have overwhelmingly underperformed compared to previous years.
With market conditions that many are not familiar with, it may be worthwhile to check out new and different approaches to the same old trick. Without even considering performance, it is clear from the differences in sector weights that NVQ provides an approach that most investors do not have exposure to.
 “81 Value ETF Reports: Ratings, Holdings, Analysis - Etf.com.” Etf.com, https://www.etf.com/channels/value-etfs.
 “The Obvious Flaw in 'Value' Index Funds.” Orbis.com, Orbis, July 2019, https://www.orbis.com/au/adviser/insights/insights/the-obvious-flaw-in-value-index-funds.
[i] CRSP Large Cap US Value Index: Center for Research in Security Prices value version of its US Index.
[ii] S&P 500 Value Index: Measures value stocks using three factors: the ratios of book value, earnings, and sales to price. S&P Style Indices divide the complete market capitalization of each parent index into growth and value segments. Constituents are drawn from the S&P 500.
[iii] Kirin API: Qraft’s proprietary API, integrates multiple vendors to provide both macroeconomic and company fundamentals with the correct point-in-time data.
[iv] Natural Language Processing: Refers to the branch of computer science concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.
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.