The Art of Balancing Tracking Error and Investment Goals

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Is There a “Good” Tracking Error?

The question of what constitutes a “good” tracking error depends on individual investment objectives and tolerance for deviation. While a low tracking error is typically desired for passive strategies, striving for zero tracking error is neither practical nor always beneficial.

A direct index that replicates all of the constituents of a benchmark would have the lowest tracking error, but it can be impractical, expensive and complex to maintain. Also, when implementing any kind of personalization or tax loss harvesting, the tracking error is likely to go up. The acceptable level of tracking error, therefore, depends on the investor’s priorities. Some investors might prioritize minimal deviation from a benchmark, while others might be willing to accept higher tracking error for greater tax efficiency or personalization. But a good rule of thumb should be to aim for <1% for simple Direct Indexing with minimal personalization.

Balancing Tracking Error with Primary Objectives

The key to successful portfolio management is effectively balancing tracking error with other primary objectives like personalization, tax efficiency, and cost considerations. At Alphathena, we understand these competing needs, and that is why our multi-step optimization framework is specifically designed to achieve this balance.

Personalization: Investors often seek to align their investments with their values, such as through ESG-focused portfolios. Personalizing a portfolio by excluding certain securities or sectors inevitably impacts tracking error. The more personalized a portfolio is, the more deviation one can expect from the benchmark index. Our platform allows real time feedback so advisors and investors can make informed decisions about the tradeoff between personalization and tracking error.

Tax Efficiency: Tax loss harvesting can be a major advantage of direct indexing. However, frequent tax loss harvesting can increase tracking error. By strategically selling securities at a loss to offset capital gains, we can reduce tax liabilities. Our optimization framework at Alphathena aims to minimize tracking error while maximizing tax benefits. Our platform allows investors to see the efficient frontier and how this optimization plays out.

Cost Considerations: Transaction costs and the complexity of managing a large number of securities must also be taken into account. Creating a synthesized index with fewer securities can help make direct indexing more efficient. However, it is important that the reduction of the securities is done smartly by using our exposure driven approach rather than just selecting the top-weighted securities.

The Alphathena Approach: Optimizing for Your Goals

Our multi-stage optimization process is designed to address these challenges effectively. By separating security selection from allocation optimization, we offer greater flexibility in personalization and improved investor experience. Our approach allows investors to maintain a low tracking error, even with a reduced number of securities. Our system incorporates real-time feedback on tracking error to enable investors and advisors to make informed decisions that are consistent with their goals.

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