Is AI the Hope for Active Investing?

December 06, 2021 EST

Have you invested in a fund with a passive strategy?[1] Chances are, you are invested in one right now. Passive funds have been all the rage over the last decade. So much so that they have almost become synonymous with ETFs. It is no wonder as passive funds held over 50% of U.S. publicly traded domestic equites in March of 2021.

In 1973, Burton Malkiel's book, "A Random Walk Down Wall Street" set out the thesis that the average investor was better off indexing the market and riding with its ups and downs rather than trying to beat it or avoid drawdowns. John Bogle, Found of Vanguard, shared the same sentiment when he was quoted, "Owning the stock market over the long term is a winner's game, but attempting to beat the market is a loser's game." Passive funds have sold this, along with the low fees they bring, and have become a staple of many portfolios around the globe.

While the claims made about passive investing vehicles are no doubt valuable and worthwhile, they do not give the full story. This can lead to investors having wrong conclusions about active funds[2]. The first part of the passive investment thesis above tends to assume that investors are only focused on overall returns. While overall performance is something investors want to look at, it is not the only thing. Risk management is also important to many investors. These investors want to reduce drawdowns or smooth out the volatility of the market.

The second main reason many flocks to passive investment vehicles is that research has shown that most active fund managers do not outperform the market consistently. However, what many investors may not know is why. It sounds like managers are just not good at beating that market. In some sense, this is true. However, it is not the whole story. One of the main reasons so many active managers do not beat the market is due to their cost. The return calculations used to compare both active and passive funds show return after fees. Generally, passive funds have much lower fees than active funds. So, it is logical that if active managers lowered their fees, they might be able to beat the market more often, making it a worthwhile investment.

In the article, "Why Active Funds Have Outperformed in Theory But Fallen Short in Practice" Jeffrey Ptak (2018) Jeffrey Ptak shows that between October 1998 to September 2018, stock funds outperformed their index before fees in all but the Morning Star Mid-Cap Blended category. On the risk management side, they found that the Sharpe ratio also outperformed in almost every category and overall. Additionally, "Buttressing these results, we also found that the asset-weighted average would have generated a statistically significant 0.64% annual alpha[3] before fees after controlling for market risk as well as size and value." While these findings were promising, all the excess returns and alpha advantages were eaten up by the fees charged by these active funds. This led to the author's conclusion that it is theoretically possible, but hasn’t worked in the real market.

The possibility of outperformance if active funds could lower their fees is exciting but is it possible? While fund managers could cut their fees, it is quite difficult to cut the talent, whose salaries constitute much of the expense ratio, needed to make the fund successful. Many active mutual funds are now converting to ETFs, offering lower fees and a more transparent view of their holdings. However, it is still to be seen if the lower cost can result in the performance desired.

It is for this reason that Qraft Technologies is powering its portfolios with AI technology. Our AI model seeks to provide active investment portfolios, through our ETF's, in a more cost-efficient manner. By doing this, we hope to provide better risk-adjusted returns as well as outperform the index after fees. QRFT, Qraft's first AI-powered ETF for example has outperformed the S&P 500 Index by 20.83% since its inception and has a Sharpe ratio of 1.26 compared to 1.05 for the S&P 500 index.

Performance data quoted represents past performance and is no guarantee of future results. Investment return and principal value of an investment will fluctuate so that an investor's shares, when redeemed, may be worth more or less than the original cost. Current performance may be lower or higher than the original cost. Returns for periods of less than one year are not annualized. Returns are determined based on the midpoint of the bid/ask spread at 4:00pm Eastern time, when the NAV is typically calculated. Market returns does not represent the returns you would receive if you traded shares at other times.  

Investors cannot directly invest in an index. 

While ETFs used to be almost exclusively passive, active funds are beginning to see growth. Whether it be from new funds or mutual funds converting to ETF’s, a trend is emerging. In the chart below, you can see the growth of the industry since 2008. The last three years have seen a large rise in the number of assets in active funds.

Passive investment strategies play an important role in reaching financial goals and in the market. However, prudent investors should also investigate how active strategies can play a role in reaching those goals as well. Will AI be the tool to allow more active funds to beat the market after fees? Only time will tell, but one thing is for sure, active investing has the potential to play a more important role in the market moving forward.

1. Passive Fund - Passive investing methods seek to avoid the fees and limited performance that may occur with frequent trading. Passive investing’s goal is to build wealth gradually. Also known as a buy-and-hold strategy, passive investing means buying a security to own it long-term. Unlike active traders, passive investors do not seek to profit from short-term price fluctuations or market timing. The underlying assumption of passive investment strategy is that the market posts positive returns over time.

2. Active Investing - Active investing refers to an investment strategy that involves ongoing buying and selling activity by the investor. Active investors purchase investments and continuously monitor their activity to exploit profitable conditions.

3. Alpha – Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index.

Ptak, J. (2018, November 19). Why Active Funds Have Outperformed in Theory But Fallen Short in Practice. Morningstar, Inc.

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 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.