Incubation bias

What Is Incubation Bias?

Incubation bias is a phenomenon primarily observed in the investment management industry, particularly with regard to mutual funds. It refers to the tendency for fund families to launch multiple new funds privately, operate them for a period, and then only publicly disclose and market those that have performed exceptionally well, while quietly liquidating or merging the underperforming ones. This selective presentation of successful funds creates an inflated perception of skill and higher past returns than would be truly representative of the fund family's overall investment strategy or individual fund performance. It is a significant concern within behavioral finance because it can lead investors to make decisions based on misleading performance records.

History and Origin

The concept of incubation bias gained prominence with increased academic scrutiny of mutual fund performance and the efficient market hypothesis in the late 20th and early 21st centuries. While the practice of launching and weeding out funds existed, its formal identification as a "bias" and its implications for financial data analysis came with research highlighting its statistical impact. Pioneer work in behavioral finance by scholars like Daniel Kahneman and Amos Tversky, who developed prospect theory, laid the groundwork for understanding how cognitive biases can influence financial decision-making, including how investors perceive and react to presented performance.

Academic papers, such as Mark Evans' 2010 study "Mutual Fund Incubation" published in The Journal of Finance, formally documented the existence and magnitude of this bias in mutual fund databases, showing that incubated funds indeed exhibited higher reported returns during their private phase⁵, ⁶, ⁷. The research underscored how fund companies might strategically use incubation to attract assets by showcasing only the "winners."

Key Takeaways

• Incubation bias involves selectively launching and then publicizing only the best-performing new investment vehicles.
• It creates an artificially inflated historical performance record for publicly offered funds.
• This bias can mislead investors into believing a fund or fund manager has greater skill than is truly the case.
• Understanding incubation bias is crucial for accurate investment analysis and effective due diligence.
• Filters for fund age and asset size can help mitigate the impact of this bias in performance studies.

Interpreting the Incubation Bias

Interpreting incubation bias involves understanding that reported past performance of mutual funds, especially for newer funds, may not be a true reflection of the fund manager's long-term ability or the fund family's average capability. When a fund family incubates several funds, the ones that perform poorly are often closed before being offered to the public, effectively removing their poor performance data from the observable universe. This means the universe of publicly available funds is skewed towards successes, giving an illusion of higher average performance.

For investors, this implies that relying solely on historical performance metrics without considering the possibility of incubation bias can lead to unrealistic expectations. It highlights the importance of scrutinizing the track record length, the fund's inception date, and considering whether the observed performance is truly indicative of sustainable alpha or merely a result of this selection bias.

Hypothetical Example

Imagine an asset management firm that decides to launch five experimental sector-specific mutual funds: Fund A, Fund B, Fund C, Fund D, and Fund E. They keep these funds private for three years, allowing them to build a track record.

After three years:

• Fund A gained 25% annually.
• Fund B gained 18% annually.
• Fund C lost 5% annually.
• Fund D lost 10% annually.
• Fund E gained 3% annually.

The firm decides to close Funds C, D, and E due to their subpar performance. They then publicly launch and aggressively market Funds A and B, touting their impressive returns. An unsuspecting investor, seeing only the public performance data for Funds A and B, might conclude that the firm consistently generates high returns. This decision-making based on incomplete information is influenced by incubation bias, where the negative performance of the "incubated" and then eliminated funds is never seen by the public. This practice distorts the true average performance and can lead to misguided capital allocation.

Practical Applications

Incubation bias has significant practical implications across the financial market and for individual investors.

• For Investors: Understanding incubation bias is critical for investors performing portfolio management. It underscores the need to look beyond raw returns and consider the full context of a fund's history, including its age and the practices of the fund family. The U.S. Securities and Exchange Commission (SEC) often highlights various behavioral pitfalls that can affect investor decisions, emphasizing that individuals tend to fall into predictable patterns of destructive behavior, such as favoring the familiar or being influenced by reported past performance³, ⁴. Recognizing incubation bias is part of a broader awareness of cognitive biases that can impact investment choices.
• For Researchers and Analysts: Researchers studying mutual fund performance must account for incubation bias to avoid overstating the persistence of returns or the skill of fund managers. Many studies employ specific methodologies, such as requiring a minimum fund age or asset under management (AUM) threshold, to mitigate this bias when analyzing risk-adjusted returns and other metrics.
• For Regulators: Regulatory bodies monitor practices that could mislead investors. While incubation itself may not be illegal, deliberately misleading marketing based on skewed performance data could be. The SEC provides resources to help investors make informed decisions and warns against common investment scams and pitfalls that prey on behavioral tendencies¹, ².

Limitations and Criticisms

While widely acknowledged in academic circles, critics of studies on incubation bias sometimes point to the difficulty of perfectly isolating its effect from other factors influencing fund performance, such as initial seed capital, early investment opportunities, or the genuinely higher risk-taking nature of new funds. It is argued that some early-stage funds, by nature, might take on higher risk in pursuit of strong initial returns, and that their closure reflects the natural weeding out of unsuccessful ventures rather than a deliberate manipulation of statistics.

However, the consensus within academia is that incubation bias is a real phenomenon that can distort empirical findings related to market efficiency and fund performance persistence. While it does not imply that all funds with strong early performance are subject to this bias, it highlights the need for caution and thoroughness in asset management research and investor decision-making.

Incubation Bias vs. Survivor Bias

Incubation bias and survivor bias are two distinct but related issues in financial research and investment analysis, both falling under the broader umbrella of data biases that can distort perceived investment performance.

Incubation Bias occurs when an investment manager or fund family initiates several funds, operates them for a period without making them publicly available, and then only brings the best-performing ones to market, liquidating or merging the failures. This practice skews the reported historical performance data for the publicly available funds upward, as the records of the poor performers are never seen.

Survivor Bias (also known as survivorship bias) arises when only the data from existing, "surviving" entities (e.g., mutual funds, companies) are included in a study, while data from entities that have failed or ceased to exist are excluded. For example, if a study analyzes the average returns of all mutual funds over the last 20 years, but only includes funds that are still in operation today, it will inherently overestimate the true average return of all funds that existed 20 years ago. This is because all the funds that failed or were liquidated during that period are excluded from the analysis.

The key difference lies in their scope and timing: Incubation bias deals with the pre-public selection and pruning of new funds, creating an artificially strong initial track record. Survivor bias, on the other hand, affects the long-term historical averages by removing the records of funds that failed at any point during the entire study period. Both biases lead to an overstatement of historical returns and can provide a misleading reference point for future expectations.

FAQs

How does incubation bias affect average mutual fund returns?

Incubation bias artificially inflates the average historical returns of publicly available mutual funds because only the top-performing "incubated" funds are brought to market, while underperformers are discarded without their poor results being widely known or included in aggregate data.

Can individual investors identify incubation bias?

Directly identifying incubation bias for a specific fund is challenging for individual investors since the details of privately incubated funds are not public. However, investors can be aware of the potential for this bias, especially when evaluating new funds with very short, impressive track records. Performing thorough due diligence and prioritizing funds with longer, consistent performance history can help.

Is incubation bias illegal?

The act of incubating funds itself is not inherently illegal. However, if fund companies use misleading or incomplete performance data derived from incubation to defraud investors, it could lead to regulatory action. Transparency about fund inception and any past incubation practices is important.

What is the primary motivation behind incubation bias?

The primary motivation behind incubation bias is to attract more assets to mutual funds by presenting only the most successful performers. Strong historical returns are a major factor investors consider, and incubation allows fund families to showcase their "winners" and generate higher inflows.

How do researchers account for incubation bias?

Researchers typically account for incubation bias by applying filters to their financial data sets. Common methods include excluding funds that are too new (e.g., less than 2-3 years old) or those with very small assets under management, as these are often characteristics of funds that may have been subject to incubation.