Reel Steal, a movie released in 2011 in the US, is a story of a robot fighting league where human-controlled robots battle for fame. The story centers around a pro boxer, pushed out of the sport after the robots take it over. With Artificial Intelligence developing and deployed in a variety of different industries, many people wonder about the possibility they could suffer the same fate. Financial traders are no exception. So, will the future of financial markets be different AI's competing against each other with no place for humans?
Recently, the Managing Director of Qraft AI ETFs was on CNBC Squawk box and was asked the same question. He answered, "While AI won't replace human portfolio managers entirely, we think it could help improve their returns". If the future of the markets will not only be AI, what will the role be for both it and humans?
In Francis's opinion, humans are best at looking at the long-term future. We are much better at predicting which technologies, strategies, and companies will be best for the future. Humans can see trends, culture, and recognize problems that the companies of the future might solve. These are things that an AI is not good at doing.
On the other hand, AI is particularly good at processing substantial amounts of data and finding patterns that humans normally cannot. It can not only look at patterns but also at combinations of patterns, finding things that would likely take humans (and many of them) a long time to find in a short amount of time. Much like bond yields, which normally have less volatility when closer to the maturity date, Qraft believes that AI is better at shorter-term investment horizons, where they believe it is possible to find predictable market patterns.
This is one reason why most Qraft ETFs (QRFT, AMOM, and NVQ) are rebalanced each month. The AI seeks to find the factors that can help give more depth and width to traditional investment strategies through this period. Since traditional factors are already incorporated into many portfolios, it could be harder to find alpha* through those traditional means. Once more people use the same strategy, it often becomes built into the price, and price discovery erodes. This does not mean that current strategies are no longer valid.
However, since many of these strategies use only a few input values and trust on linear methods, this may not be optimal. This makes it possible to find new investment opportunities that may seem invisible to humans. With the input from multiple data sources, AI seeks to find greater prediction accuracy, while staying adaptable to new information. It does this by taking in several types of data and passing them through several nodes1. In a matter of hours, the AI can test millions of combinations and give outputs that can be back-tested for viability. This is how AI seeks to find the invisible investment opportunities that humans cannot see.
The AI might not be able to tell if EV's will be the future or if bitcoin will be widely adopted in the world, but it has the potential to optimize a universe of stocks, and, as it learns, create a nimbler portfolio. While it is true that AI will likely impact our lives in many ways, it seems a place for humans in the market will still exist. In that case, maybe the better movie to compare it to would be Iron Man. With the AI as Jarvis for humans when they participate in the market.
* Alpha is a measure of the active return on an investment, the performance of that investment compared with a suitable market index.
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.
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.