AI-powered ETF

Exchange-traded funds (ETFs) have enjoyed spectacular growth since 1990. ETFs were first introduced in Canada in 1990 and launched in the U.S. three years later.
Lower cost, better liquidity, and easier trading are the top three reasons that have driven the explosive growth of ETF popularity among all investors today.
ETFs benefit investors by offering diversification, tax efficiency, wide varieties, highly transparent, real-time pricing, and low investment minimums.

What is An AI-Powered ETF?

An AI-power ETF is an actively managed exchange-traded fund that has a manager or team making decisions on the underlying portfolio allocation. Such an ETF will have a benchmark index, but managers may change sector allocations, market-time trades, or deviate from the index as they see fit. It produces investment returns that outperform but do not perfectly mirror the underlying index.

The future of ETF innovation will expand the investment opportunity set, reduce investment costs, and outperform its respective benchmark with data-driven intelligent algorithms.
Asset allocation ETFs offer a simple way to build a diversified portfolio for investors. When such ETFs are powered data-driven intelligent algorithms, they become AI-powered ETFs.
AI-powered ETF innovation has just started in recent years. While the performance of leading ETFs are promising, the choices are still limited.
Some results are far from satisfactory when they are compared to benchmarks. For example, a well-known ETF (symbol: SECT) utilizing a dynamic sector rotation strategy did poorly (shown below).

AI-Powered ETF Assessment Criteria

Intelligence - how does it incorporate machine learning, data analytics, Fuzzy-logic, AI rules, and innovation?
Strategy - how good the ETF portfolio strategy is in terms of discipline, theme, diversification, scheduled rebalancing, and intelligent trigger adjustment?
Cost - what is the competitiveness of the ETF expense ratio?
Performance - what is the ETF historical performance as compared to the benchmark, upside capture, downside capture, maximum drawdown, and performance consistency?
Correlation - how does the ETF price movement behave as compared to the major indices in up and down market conditions?
Efficiency - how good is the ETF tax efficiency in terms of turnover of underlying ETFs?
Liquidity - what is the ETF trading volume, bid-ask spread, tracking errors, AUM, and option availability?

Institutional investors are increasingly interested in applying sophisticated trading strategies to launch actively managed ETFs.
We are committed to helping investors and firms in researching, reviewing, and designing the best AI-powered ETFs.
Please contact us at AFIEA (Advisory for Financial Innovation, Evaluation, and Assessment) for identifying the areas for improvement and designing better AI-powered ETFs for the future.
Based on the above-defined Robo-advisor assessment criteria, we have analyzed and reviewed the following selected asset allocation ETFs and leading AI-powered ETFs available in the market today. Detailed analysis reports on each listed Robo-advisor are available to financial institutions upon request.