Know the Basics

OAIA

Machine Learning & OAIA

Jake Hanley,

Managing Director / Sr. Portfolio Strategist 02/06/2023

 

• OAIA seeks to track a Long-Short index strategy driven by machine learning
• OAIA is a passive ETF, managers follow the machine's recommended trades
• OAIA’s index has a 6-year track record, not a backtest, but a track record, i.e. actual historical performance
• Past performance does not guarantee future results

 
The Teucrium AiLA Long-Short Agricultural Strategy ETF (OAIA) is a  passive exchange-traded fund designed to track the AiLA S033 Index, which is powered by advanced machine learning technology. The index employs a multi-factor regression algorithm to analyze thousands of data points and make daily trade recommendations for agricultural futures contracts. The ETF's portfolio managers, who are experienced human traders[1], receive these recommendations, and execute the trades with the aim of replicating the index performance.

Not New, But Unique
While the use of quantitative analysis, computers, and algorithms in the investment industry is not new, OAIA is unique in that it is the only passively managed, machine learning ETF available. As a passive ETF the portfolio managers are required, by prospectus, to follow the machine-directed trades. Other machine learning strategies are considered active, and they may or may not follow the machine's recommendations.

A Competitive Landscape
It is important to note that while machine learning technology has come a long way, there is still plenty of room for competition in the space.   A strategy’s success ultimately depends on the strategy’s design. "Garbage in, garbage out" is a common phrase in the field of AI, meaning that the output will only be as good as the input. The system design, programming, and testing are all critical to the strategy’s success. 

What’s more, when applying machine learning to investable markets you not only need very capable computer scientist, but you also need financial market acumen. Although machines can identify patterns and correlations quickly, they still require human oversight. For example, humans are better equipped to sort relevant data from irrelevant noise. In the case of OAIA, the AiLA’s designers choose to include factors relevant to corn, such as the relationship between crude oil and ethanol prices, while excluding factors that are not relevant, such as the inter-relationship between butterfly migratory patterns and consumer credit ratings.

From the highest level, we see that applying machine learning to investment management strategies presents a range of potential advantages, including increased accuracy of predictive models, efficient data analysis, and improved risk management. However, it is important to recognize the potential drawbacks, such as over-reliance on automated systems and increased complexity of investment strategies, and ultimately poor system design.

Competitive Advantage
The Teucrium AiLA Long-Short Agricultural Strategy ETF (OAIA) has a competitive advantage, as it tracks the S033 index, which has a proven track record dating back to January 2017. Once again the quality of machine learning output  depends on the quality of the input and the strategy design. The S033 index's, 5-year average return of 17.98%[2], serves as evidence of a well-designed strategy. Still, past performance does not guarantee future results.  There is no guarantee that the strategy will continue to perform as it has.  Additionally,  there is the risk that the fund managers fail to adequately track the S033 index. 

That said, we at Teucrium are excited to be early adopters, incorporating the potential of machine learning into an exchange-traded product.  OAIA is listed on the New York Stock Exchange and available to all investors with a brokerage account.