Innovation in the asset management industry has largely gone undetected for many years due to its zero-sum characteristics.
That’s because portfolio managers – including quants – prefer to keep their strategies to themselves from competitors for as long as possible, says Kim Hyungsik, CEO of South Korean artificial intelligence (AI) firm Qraft Technologies.
As Qraft unveils its fourth exchange traded fund in the US this month, Hyungsik describes how AI has the opportunity to disrupt the asset management industry.
In the early 1990s, computer scientists and mathematicians discovered a famous strategy now known as STRATEGY C. The first in history, these new group of investors who approached money making with an engineering approach had brought outstanding results when compared to the financial experts in Wall Street.
But as the first and second generation of quantitative funds continued to increase in size and demand, problems started to arise. In a market with zero-sum attributes, most strategies were short-lived and returns from large-scale quant funds had dropped significantly.
To get ahead of the competition, many quant funds relied on hiring more analysts and producing new strategies faster and more effectively. Eventually, the average assets under management (AUM) per quant at large quant funds came to around US$30million and the combined remuneration and overhead costs of each employee exceeded US$500,000. Finding alpha soon became a very costly process.
Quants at large quant funds try to find an excess return strategy by organising data, pre-processing it, and backtesting many ideas. If they believe a momentum strategy might work, they will try to find alpha through multiple versions of back-testing and forward-testing. Numerous iterations are required from different angles – which universe works better, which disclosures work better, which measure-based momentum strategy works better, etc.
Oftentimes, these long trials may turn out to be a dead end, which means they have to start over from scratch. This process is not only time-consuming, but it’s also expensive and to an extent, ineffective.
If there is a way to expedite the research process to find excess return strategies and automatically generate investment strategies without employing thousands of quants, then finding alpha at lower cost is not only possible, but it’s also less time-consuming.
The power of AI
This innovation process can be accomplished with artificial intelligence technology. From data processing to alpha research and order execution, Qraft Technologies has successfully developed innovative AI solutions that have been adopted by major financial institutions and turned into successful AI products and services.
At its core, Qraft’s AI technology is comprised of automatically searching for alpha factors and extracting investment strategies that ultimately lead to high performance portfolios. In a standard investment strategies universe, there are a trillion different ways to form an effective strategy candidate.
It’s one of the reasons why large hedge funds require lots of quants. But with a well-engineered deep learning model, not only can this process become more efficient, but it can also pave the way for AI to find better strategies to outperform the markets.
At Qraft, this AI system has been used to build AI-powered exchange-traded funds (ETFs).
In May last year, we launched our first AI-powered ETFs – Qraft AI-Enhanced US Large Cap ETF and Qraft AI-Enhanced US Large Cap Momentum – and earlier this year, we unveiled the Qraft AI-Enhanced US High Dividend ETF – all on the New York Stock Exchange.
Since inception, all three AI-driven ETFs have outperformed their benchmark indices.
This month, we will be launching our fourth AI-powered ETF – the Qraft AI-Enhanced US Next Value. This is an actively managed ETF that aims to incorporate intangible assets in valuation measures.
Due to the development of information technology, intangible assets have become a critical factor in accurately gauging a company’s value. Current accounting systems overlook the importance of intangible assets, but by properly measuring a company’s R&D, marketing, and intellectual property costs, AI technology can revive the value factor that has been on a downtrend the past decade.
There is so much opportunity for AI to disrupt the asset management industry. For us, this innovation potential has already become a reality set in motion.