Benjamin Graham, Warren Buffett, Charlier Munger, and Seth Klarman are all extraordinary investors and they have one crucial commonality – value investing.
A value investor picks stocks that appear to be trading for less than their intrinsic value. Just as savvy shoppers will buy clothes on sale, savvy value investors treat stocks the same way. Of course, stock discounts are not as transparent as clothes discounts, as stocks do not post their sale percentages or original values.
Although value investing has been profitable for many decades, it appears the strategy has been faltering in recent years. The failure could be attributable to multiple factors; from the tech bubble of the 1990s to the recent pandemic in 2020.
But what if the reason is because the traditional metrics for value calculations are just too outdated? What if the lenses of the investing gurus we religiously followed are now too blurry?
One of the major financial metrics value investors rely upon is the price-to-book ratio1, which compares a company’s market value to its asset valuations. The lower the ratio is, the better the potential price is for value investors. The more accurately this ratio is measured, the more likely value investing would succeed.
It could be said that the traditional asset valuation metric is potentially misleading. By immediately overlooking R&D and SG&A as expenses, the traditional metrics largely disregard the value of intangible assets2.
As of September 2020, the value of intangible assets of the top 10 companies in the world was $10.8 trillion as of 10/22/2020 according to Brand Finance, a leading brand valuation consultancy. Given the technological advancements within the business paradigm, companies’ proportion of intangible assets are increasing exponentially. In 1975, intangible assets represented only 14% of S&P 500 companies’ assets. As of 12/31/2018, the percentage was at least 84%, according to Aon and Ponemon Institute. Perhaps this is potentially the reason why value investors got away without regarding intangibles 40 years ago.
- Brand Finance. (2020, October). Global Intangible Finance Tracker (GIFT) – an annual review of the world’s intangible value. https://brandirectory.com/reports/gift-2020
- Ross, J. (2020, February 11). Intangible Assets: A Hidden but Crucial Driver of Company Value. Visual Capitalist. https://www.visualcapitalist.com/intangible-assets-driver-company-value/
1. Price-to-book ratio – P/B ratio compares a company’s market value to its book value. The market value of a company is its share price multiplied by the number of outstanding shares.
2. Intangible assets – an intangible asset is an asset that is not physical in nature. Goodwill, brand recognition and intellectual property, such as patents, trademarks, and copyrights, are all intangible assets.
It may sound like a big ask for the average investor to valuate companies’ intangibles. Hence, many retail investors have been relying upon ETFs to invest in value stocks. One popular option is iShares S&P 500 Value ETF (IVE), a passively managed ETF that tracks the S&P 500 value index. While the fund holds large assets under management and high liquidity, it is far from perfect, as returns are humble and the index the fund utilizes potentially outdated valuation methods as described above.
Perhaps, the whole valuation process is out of a man’s reach. How can one possibly compute values that are almost impossible to quantify? This question is why some investors are newly turning to robots. Through machine learning, artificial intelligence can pick up important data in a plethora of fields and produce accurate projections for stocks’ growth potential. NVQ, of Qraft Technologies, is an ETF seeks to that invest in value stocks, depending on their intangibles. The AI model, by attempting to gauge intangible assets 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.
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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.