Mind the Gap 2026

Source: Morningstar, author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group and funds of funds. The "alternative" category group also includes funds assigned to the "nontraditional equity" category group. 

New to this year’s study is a supplemental case study in which we analyze three newer ETF types that have been popular with investors in recent years—buffer ETFs, leveraged single-stock ETFs, and crypto ETFs. We found mixed results over the periods we assessed. 

Encouragingly, investors in buffer ETFs, which use derivatives to generate returns within a specified range over a designated outcome period, fared well, with the average dollar gaining more than the ETFs did in aggregate. 

Leveraged single-stock ETF investors notched lofty dollar-weighted gains but still failed to top the unleveraged returns of the stocks they reference. 

Lastly, investors in crypto ETFs struggled to time their transactions, with their aggregate dollar-weighted return significantly lagging the ETFs’ aggregate total returns.

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025. Data for buffer and leveraged single-stock ETFs covers the three-year period ended Dec. 31, 2024. Data for crypto ETFs covers the Jan. 11, 2024 to Dec. 31, 2025 period. Gap numbers may not match differences in returns due to rounding. 

Most reported total returns are time-weighted, meaning they assume a lump-sum investment made at the beginning of the measurement term that’s held throughout the whole period to the end. But investor returns can be a more telling measure because they include the impact of cash inflows and outflows. 

Investor returns are essentially an internal-rate-of-return calculation that accounts for periods when investors have more dollars invested, which will carry more weight in their overall results. Our annual "Mind the Gap" study compares the aggregate dollar-weighted and time-weighted returns of nearly 23,000 individual US open-end funds and ETFs. The difference between them, or “gap,” represents the portion of funds’ total returns that have been forgone because of the timing and magnitude of transactions investors made during the 10-year study horizon. 

To be sure, inopportunely timed purchases and sales—buying high or selling low on impulse, for instance—can hold back investor returns. But even laudable practices like investing a portion of every paycheck or regularly rebalancing can open a gap between investor results and reported total returns. Given that nuance, it's not advisable to view this study's findings as a parable of "dumb money" or definitive proof of individual investors' fallibility. 

Also, it is a truism that for the theoretical “total market,” there can be no “gap,” as for every buyer, there is a seller, meaning one’s shortfall is another’s surplus. Nor should timing effects be interpreted as literal opportunity costs. For instance, the investor who bought a fund after it had risen sharply, for reasons or circumstances outside their control, hasn’t “lost” out on those earlier gains. Rather, their dollars earn whatever comes next, even if that return lags the fund’s total return for the full period. 

Notwithstanding that, we’d note that the US open-end fund industry, large and significant as it is, is still only a subset of the global market. In addition, as further described in the Methodology section, we limit the study to funds and ETFs that existed as of Jan. 1, 2016, excluding those that came after. Given this, the zero-sum total-market truism won’t necessarily hold for it as theory might suggest. 

Moreover, while gaps might not evidence bad behavior or constitute actual costs investors incurred, it is still useful to examine the extent to which, and why, investors have succeeded in capturing their funds' returns. While such insights will not necessarily fully close the gap between investor and total returns, they might help investors avoid the types of decisions that can hold back dollar-weighted returns. 

With that in mind, this study addresses not just the question of how wide the investor return gap is but also how it can vary based on numerous important factors, including a fund’s category group, Morningstar Category, investment type (open-end fund versus ETF), management style (active versus index), fees, return volatility, tracking error (versus its benchmark), and cash flow volatility. 

And so, in the pages that follow, this study delves into those factors, the key findings surrounding them, and the takeaways for investors seeking to capture as much of their funds' returns as possible. 

• The average dollar invested in US stock funds and ETFs earned 8.7% per year over the 10 years ended Dec. 31, 2025, while those funds earned 9.9% per year, with that 1.2-percentage-point annual “gap” stemming from the timing and magnitude of investors’ cash flows during the 10-year period. 
• The 1.2-percentage-point per year gap, which is equivalent to around 12% of funds’ aggregate total return over this period, is similar to the shortfall we estimated over the 10 years ended Dec. 31, 2023 and 2024, if a bit narrower than the gaps over the decades ended Dec. 31, 2021 and 2022. 

Source: Morningstar; author’s calculations. Data as of Dec. 31 of 2021-25. Excludes "commodities" category group and funds of funds.

• We’ve consistently found the return of the average dollar invested in funds lags the funds’ buy-and-hold return, the difference stemming from the timing and magnitude of investors’ buys and sells.
• That gap can reflect suboptimal behavior, such as return chasing, but also contextual factors such as the setting investments are being made in. 
• Investors can narrow this gap by holding the line on transactions, especially discretionary, ad-hoc trading in response to recent events; regimenting transactions using approaches like dollar-cost averaging or a systematic withdrawal plan; holding fewer, more widely diversified funds; and in certain cases, opting for strategies that automate routine tasks like rebalancing. 

• US stock funds had the highest dollar-weighted and total returns in absolute terms (12.8% and 13.3% per year, respectively) and municipal-bond funds the lowest (1.1% and 2.2% annually, respectively). The average dollar made money in every category group over the 10-year period. 
• From a percentage standpoint, US stock and allocation fund investors earned the largest share of their funds’ aggregate total returns (97% and 92%, respectively) while municipal-bond, alternative, and taxable-bond fund investors captured the smallest portion (49%, 62%, and 65%, respectively). 

Source: Morningstar. Data as of Dec. 31, 2025. Excludes "commodities" category group. The "alternative" category group also includes funds assigned to the "nontraditional equity" category group. The category group figures include funds of funds, but the “overall” figures exclude funds of funds to avoid double-counting. Gap numbers may not match differences in returns because of rounding. 

• The trends by category group were more-or-less consistent with what we have observed in the past, with narrower gaps in absolute terms among US stock and allocation funds and wider gaps among alternative and sector equity funds.  

Source: Morningstar. Data as of Dec. 31, 2025. Excludes "commodities" category group. Beginning with the 10-year period ended Dec. 31, 2024, the "alternative" category group also includes funds assigned to the "nontraditional equity" category group. We have displayed the gaps for “nontraditional equity” for the prior rolling 10-year periods for comparability purposes. The category group figures include funds of funds, but the “overall” figures exclude funds of funds to avoid double-counting. Gap numbers may not match differences in returns because of rounding.

• In dollar terms, US stock fund investors had arguably the most profitable decade in fund history, earning more than $12 trillion in cumulative gains over the 10-year period based on our estimates. This reflects the category group’s large size ($5.7 trillion in net assets at the period’s outset), US stock funds’ robust aggregate total returns over the decade (13.3% per year), and fairly stable flows, which allowed the asset base to compound to a greater extent. 
• Among the largest categories by assets, the large-blend category had the narrowest gap in absolute and percentage terms, with the average dollar earning essentially all the funds’ aggregate total return, while the large-growth category claimed the largest dollar-weighted (15.0% per year) and total return (15.9% annually).
• Diversified emerging-markets funds saw the largest shortfall in absolute terms (negative 1.0 percentage point), while investors in intermediate core-plus bond funds captured the smallest share (67%) of the funds’ aggregate total returns.  

Source: Morningstar; author's calculations. Data as of Dec. 31, 2025. Excludes funds of funds from tallies of assets by category, explaining absence of categories from the "allocation" US category group. Gap numbers may not match differences in returns due to rounding.

• This year’s study adds to evidence that investors have tended to fare better with relatively simple, stand-alone options like allocation funds or portfolio bulwarks like US stock funds, where we saw narrower timing gaps. This success can hinge on where and how investors are utilizing such funds—for instance, a brokerage account versus a retirement plan menu—but their success in capturing these funds’ total returns has been a recurring trend. 
• On the other hand, we’ve seen investors continue to struggle with potentially more complex building-block strategies such as alternatives, which have chronically suffered from larger timing gaps. It’s notable that strategies like these are less likely to be featured on retirement plan menus or be held in target-date funds, contexts associated with greater investor success. Rather, they are more likely to be used on an ad-hoc or standalone basis, which could lead to timing errors. 
• With respect to the largest categories by assets, the findings largely mirrored the results at the broader category group level, with narrower gaps among popular US equity categories such as large blend, reflecting the central role such strategies often play in asset allocation, as well as other factors, and somewhat wider gaps in certain fixed-income and foreign-stock peer groups. 

• ETFs earned higher dollar-weighted (9.5% per year) and aggregate total (11.2% annually) returns than open-end funds (8.5% and 9.6% per year, respectively), but the gap was wider for ETFs (negative 1.6 percentage points per year) than for open-end funds (negative 1.2 percentage points annually). 
• ETFs exhibited wider timing gaps than open-end funds in all but one category group (municipal bond), with international stock ETFs seeing the widest gap in absolute terms (negative 2.5 percentage points per year) and taxable-bond ETFs the biggest gap in percentage terms (the 1.4-percentage-point gap was equivalent to around half the aggregate return). (This excludes alternative ETFs, which are a tiny cohort.) 
• Among open-end funds, US stock funds notched the highest investor (12.7% per year) and aggregate total returns (13.2% per year) while municipal-bond funds suffered the lowest dollar-weighted (1.1% annually) and time-weighted returns (2.2% per year). With respect to ETFs, excluding alternatives, it was largely the same story: U.S. equity ETFs paced the field, with the average dollar earning 13.2% per year compared with a 13.7% aggregate annual total return whereas municipal-bond ETFs earned just a fraction of that (1.1% and 1.9% annual dollar-weighted and total returns, respectively). 

Source: Morningstar; author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group. Funds of funds excluded from overall figures to avoid double-counting. Gap numbers may not match differences in returns due to rounding. 

• The average dollar invested in active funds gained 7.5% per year, which was around 1.6 percentage points less per year than the 9.2% aggregate annual total return the funds earned over the decade ended Dec. 31, 2025.
• Index funds earned a higher dollar-weighted return than active funds (10.3% per year), but this still fell shy of the funds’ aggregate annual time-weighted return (11.4%), leaving a 1.1-percentage-point per year gap.
• Active fund investors captured a slightly higher percentage of their funds’ aggregate total returns than index fund investors across most category groups, with the notable exception of US equity where the return of the average dollar invested in index funds nearly matched the funds’ overall total return. 

Source: Morningstar; author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group and funds of funds. “Allocation” category group not shown in table because virtually all “allocation” funds are assigned to the “active” management style. Gap numbers may not match differences in returns due to rounding. 

• Investors should be mindful of the potential trade-offs involved in easily traded ETFs, one of them being larger timing costs. This year’s study finds the gaps between the average dollar’s return and the buy-and-hold return are often wider among ETFs, notwithstanding those vehicles’ other advantages when compared with traditional open-end funds. 
• There’s no strong evidence of a link between management style—active or passive—and timing gaps. Rather, it appears that management style subordinates to other factors, such as how and where investors access and utilize a strategy. Put another way, investors might be just as prone to mistime their investments in a very low-cost index fund in a brokerage account as they are to correctly time their buys and sells of a more costly active fund held within a retirement account or that’s bought or sold per a systematic purchase or withdrawal plan. 

• Over the 10 years ended Dec. 31, 2025, the average dollar invested in the cheapest quintile of funds earned around 9.3% per year. That was about 1.0 percentage point per year less than the funds’ 10.3% aggregate annual total return, a narrower margin than the 1.2-percentage-point gap separating the priciest funds’ annual dollar-weighted and aggregate total returns. 
• The average dollar invested in the priciest funds captured a smaller percentage of their total returns (84.0%) compared with the cheapest funds (90.0%) and the costliest funds earned significantly lower dollar-weighted (6.2% per year) and aggregate total returns (7.4% annually) than the least-expensive funds.  

Source: Morningstar, author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group. The "alternative" category group also includes funds assigned to the "nontraditional equity" category group. The category group figures include funds of funds, but the “Overall” figures exclude funds of funds to avoid double-counting.  

• As in past studies, we found a stronger relationship between funds’ volatility and investors’ success capturing the funds’ total returns: The less volatile the fund, the smaller the gap tended to be (0.4 percentage points per year for the least-volatile quintile) and vice versa for more-volatile funds (more than 2.0 percentage points annually for the most-volatile quintile). 
• Over the decade ended Dec. 31, 2025, the most-volatile funds earned substantially lower dollar-weighted (5.8% per year) and aggregate total (8.0% annually) returns than the least-volatile funds (11.2% and 11.6% per year, respectively).
• This relationship held most strongly among alternative funds (where the least volatile funds captured 98% of the funds’ aggregate total returns versus negative 159% for the most-volatile funds), international equity funds (94% and 66%, respectively, and municipal-bond funds (64% and 18%, respectively). 

Source: Morningstar, author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group. The "alternative" category group also includes funds assigned to the "nontraditional equity" category group. The category group figures include funds of funds, but the “Overall” figures exclude funds of funds to avoid double-counting.  

• Like management style, that is, active versus index, fees appear to play at best an indirect role in explaining the size of timing gaps. While the cheapest funds had a smaller gap and captured more of their funds’ total returns than the priciest funds, the differences were modest overall. Investors might be prone to overtransact in cheaper and costlier funds alike, similar to what we observed when examining differences in gaps between traditional open-end funds and ETFs. It’s likelier that other factors—such as where and how investors utilize a low-cost or pricey fund—have a stronger bearing on investor success than fees alone. 
• That’s in marked contrast to the relationship between volatility and timing gaps. In short, more-volatile funds appear to push investors’ buttons, potentially inducing them to trade more often to their detriment, whereas less-volatile funds might be less prone to misuse. This has been one of the more vivid and enduring findings from the study through the years. 
• That doesn’t constitute a call to avoid more-volatile funds. Rather, it underscores the importance of being clear-minded and acting with resolve when investing in streakier, somewhat less-predictable funds, knowing that the sheer magnitude of such moves could spark a desire to buy or sell, with all the attendant risks of mistiming those transactions. 

• Funds with higher tracking error (versus their style-specific index) exhibited slightly wider timing gaps than those that hewed closer to their benchmarks. 
• All told, the aggregate total return of funds that deviated the most from their indexes was around 3.7 percentage points per year less than funds with the least tracking error. 
• The average dollar in the highest tracking-error funds earned roughly 4.4 percentage points less annually than the average dollar in the funds that strayed the least.  

Source: Morningstar, author's calculations. Data as of Dec. 31, 2025. Excludes "commodities" category group. The "alternative" category group also includes funds assigned to the "nontraditional equity" category group. The category group figures include funds of funds, but the “Overall” figures exclude funds of funds to avoid double-counting. 

• Funds with more-volatile cash flows (specifically, the volatility of monthly net flows as a percentage of net assets, which proxies for trading activity) tended to earn lower dollar-weighted returns than funds with more-stable cash flows. 
• The return of the average dollar invested in funds with the most stable cash flows lagged the funds’ aggregate total return by 1.3 percentage points per year, which was 0.6 percentage points narrower than the gap for funds with the most volatile cash flows (negative 1.9 percentage points). 
• Funds with more volatile cash flows also tended to earn lower dollar-weighted and total returns in absolute terms: The average dollar invested in the quintile of funds with the most-volatile cash flows earned about 1.9 percentage points per year less (6.6% annually) than funds in the least-volatile quintile (8.5% per year). Correspondingly, the funds with the most-volatile cash flows earned a lower aggregate total return (8.5% annually) than funds with the most-stable cash flows (9.8% per year). 

• There’s some evidence of a link between tracking error and timing gaps, though it wasn’t overwhelmingly strong, especially when other potentially conflating factors—such as volatility of returns—are taken into consideration. That said, it’s advisable to at least consider the degree to which a strategy is likely to stray from its index and peers, as it appears such deviations can induce inopportune purchases and sales that lead to wider timing gaps. 
• It was a similar story for cash flow volatility: Investors in funds with less-volatile cash flows tended to capture a larger share of those funds’ total returns, if not to a resounding degree. Though cash flow volatility isn’t a fund attribute per se—as the manager exerts little or no influence over the timing and magnitude of investors’ trades in aggregate—it can serve as a measure of how overtransacting can corrode dollar-weighted returns. 

That concludes the core Mind the Gap study. In this section, we supplement the core study with this case study in which we analyze the dollar-weighted returns of several emerging ETF types, including: 

• Buffer ETFs: Invest in derivative instruments to target returns in a specified range over a designated outcome period
• Leveraged single-stock ETFs: Invest in derivative instruments to deliver some multiple of a reference stock’s return for a single day
• Crypto ETFs: Invest directly in digital currency 

These ETFs proved popular with investors, attracting $165 billion in aggregate net inflows from investors in the five years ended Dec. 31, 2025.  

Source: Morningstar Direct. Data as of Dec. 31, 2025. Includes all ETFs in Morningstar’s defined outcome, trading-leveraged equity (limited to single-stock ETFs only), and digital assets categories over the period. 

The question is how investors in these ETFs fared in dollar terms. To address that, we compiled net asset, flow, and return data for the three-year period ended Dec. 31, 2025 (leveraged single-stock ETFs and buffer ETFs) and the five-year period ended Dec. 31, 2025 (buffer ETFs only), as well as for the Jan. 10, 2024 to Dec. 31, 2025 period (crypto ETFs only). Using this data, we estimated each ETF type’s aggregate dollar-weighted and total returns. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31,/2025. Limited to “defined outcome” ETFs that existed as of Jan. 1, 2023 (three-year period) or Jan. 1, 2021 (five-year period). Gap numbers may not match differences in returns due to rounding. 

These ETFs’ strong dollar-weighted returns appear to owe to two main factors. First, flows clustered around the month in which the outcome period starts and ends. This made the pattern of demand more akin to buy and hold than other investment types where flows might be more irregular or episodic. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025."Specified Month" is the month corresponding to the month mentioned in each buffer ETF's name; average monthly flow derived as sum of all flows in specified months divided by 60; calculation is same for other 11 months but with 660 as the divisor. 

Second, it appears investors in these ETFs benefited from fortuitous timing, especially in 2022. Stocks and bonds took a drubbing that year, but the losses were largely confined to the January to June period. This portended well for investors in the “July” buffer ETFs, for instance, who concentrated their purchases in that month and shortly thereafter, just as performance began to stabilize. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2022. "July" buffer ETFs defined as "defined outcome" ETFs with "July" in the name; growth of $10,000 represents cumulative growth of July buffer ETFs' monthly returns in 2022, with ETFs weighted by their net assets as of Dec. 31, 2021. 

Unfortunately, it was a different story for investors in leveraged single-stock ETFs. To be sure, over the three-year period ended Dec. 31, 2025, these ETFs produced lofty dollar-weighted returns that nearly matched the ETFs’ aggregate total return. But the results varied dramatically at the individual ETF level, reflecting the idiosyncratic nature of demand for these strategies.

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025. Direxion Daily AAPL Bull 2X Shares (AAPU); Direxion Daily AMZN Bull 2X Shares (AMZU); Direxion Daily GOOGL Bull 2X Shares (GGLL); Direxion Daily MSFT Bull 2X Shares (MSFU); Direxion Daily TSLA Bull 2X Shares (TSLL); GraniteShares 1.25x Long Tsla Daily (TSL); GraniteShares 2x Long AAPL Daily (AAPB); GraniteShares 2x Long COIN Daily (CONL); GraniteShares 2x Long META Daily (FBL); GraniteShares 2x Long NVDA Daily (NVDL). Gap numbers may not match differences in returns due to rounding. 

For instance, we estimate that Direxion Daily GOOGL Bull 2x Shares earned a 105.6% annual dollar-weighted return, which exceeded the ETF’s total return by nearly 24 percentage points per year. Conversely, the average dollar invested in GraniteShares 2x Long COIN Daily ETF lost more than 38.0% per year, based on our estimates, despite the fact the ETF earned a 47.6% annual return over this span. 

Also, while these ETFs aren’t meant to be held longer than a day, it’s still noteworthy that the return of the average dollar invested in these ETFs often failed to exceed the unlevered return of the reference stocks themselves over the three-year period. All told, these ETFs’ aggregate dollar-weighted return lagged the composite stocks’ return by 1 percentage point per year. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025. Direxion Daily AAPL Bull 2X Shares (AAPU); Direxion Daily AMZN Bull 2X Shares (AMZU); Direxion Daily GOOGL Bull 2X Shares (GGLL); Direxion Daily MSFT Bull 2X Shares (MSFU); Direxion Daily TSLA Bull 2X Shares (TSLL); GraniteShares 1.25x Long Tsla Daily (TSL); GraniteShares 2x Long AAPL Daily (AAPB); GraniteShares 2x Long COIN Daily (CONL); GraniteShares 2x Long META Daily (FBL); GraniteShares 2x Long NVDA Daily (NVDL). Gap numbers may not match differences in returns due to rounding. 

Lastly, we estimated the dollar-weighted returns of the first batch of bitcoin ETFs from January 2024, when they listed, through Dec. 31, 2025, finding the average dollar gained about 22% annually, or nearly 14 percentage points less per year than the ETFs earned in aggregate. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025. Limited to spot bitcoin ETFs in the digital assets category that existed as of Jan. 11, 2024. Gap numbers may not match differences in returns due to rounding. 

Though the results varied by individual ETF, the large aggregate shortfall appears to be attributable to investors piling into one ETF, iShares Bitcoin Trust ETF, after bitcoin had already rallied substantially.

This more than offset the Grayscale Bitcoin Trust ETF’s positive timing gap, which seems to have arisen for the opposite reason—investors withdrawing capital soon after the ETF launched in January 2024, before bitcoin began to falter, with at least some of those proceeds likely having been reinvested in the other eight crypto ETFs that launched that month. 

Source: Morningstar Direct; author's calculations. Data as of Dec. 31, 2025. Limited to spot bitcoin ETFs in the digital assets category that existed as of Jan. 11, 2024. Gap numbers may not match differences in returns due to rounding. 

Morningstar recently furnished updated data to the Wall Street Journal for a story on these crypto ETFs’ dollar-weighted returns through June 30, 2026. (“The Mind Games that Investors Can’t Stop Playing” by Jason Zweig; July 10, 2026.) 

As of that date, we estimate that the average dollar invested in these ETFs had lost around 5.8% per year since Jan. 2024, which was more than 14 percentage points less than the ETFs’ 8.5% per year aggregate total return over that span. 

Source: Morningstar Direct; author's calculations. Data as of June 30, 2026. Limited to spot bitcoin ETFs in the digital assets category that existed as of Jan. 11, 2024. 

This poor result appears to stem from ill-timed purchases and sales, with the biggest inflows coming after bitcoin had already streaked higher (in the 2024’s first quarter and again in the first half of 2025), followed by redemptions in more-recent periods amid a downturn in the cryptocurrency’s price, effectively locking-in losses. 

Source: Morningstar Direct; author's calculations. Data as of June 30, 2026. Limited to spot bitcoin ETFs in the digital assets category that existed as of Jan. 11, 2024. 

We find that investors captured most, but not all, of their funds’ aggregate total returns over the decade ended Dec. 31, 2025. The average dollar earned 8.7% per year over that span, or about 1.2 percentage points per year less than the funds’ 9.9% aggregate annual total return. This finding is consistent with the results of prior studies, which also found gaps over the rolling 10-year periods ended Dec. 31, 2021, 2022, 2023, and 2024. 

Here is a summary of our key findings and takeaways by major factor we assessed as part of the study:  

Morningstar's annual "Mind the Gap" study compares funds' dollar-weighted returns with their time-weighted returns to see how large the gap, or difference, has been over time. 

We use a portfolio-based methodology to pool funds' net assets and monthly flows to an aggregate level. We then estimate the pool's dollar-weighted returns using an internal-rate-of-return calculation that represents the constant monthly rate of return that makes the pool's beginning net assets equal its ending assets with all monthly cash flows accounted for. This estimate approximates the return of the average dollar in the pool over the study period. 

It is important to note that this estimate is not a proxy for the average investor's dollar-weighted return, as this will depend on the particular magnitude and timing of an individual investor's purchases and sales, which is beyond the scope of this study.  

Each pool consists of all share classes of all eligible funds and ETFs that existed at the beginning of the study period, in this case, as of Jan. 1, 2016. This includes funds that were merged or liquidated during the study period. We incorporate obsolete funds by aggregating their beginning assets and monthly flows through their final partial month of existence. In the case of liquidated funds, we carry the fund's terminal net assets forward to the end of the study, which is akin to assuming these assets were held in cash. With respect to merged funds, we treat the final net assets before the fund is merged as a transfer to the acquiring fund.  

While we attempt to correct for survivorship bias, we do not correct for creation bias, as the study captures net assets, cash flows, and returns only for funds that existed at the start of the study period. In other words, we exclude funds that launched after Dec. 31, 2015, from the study.  

The study also excludes funds in the "commodities" and "miscellaneous" category groups, as well as any fund lacking complete net assets, monthly net flows, or monthly net return data through the end of the study period or, if an obsolete fund, its final month of existence. For brevity, we've folded funds in the "nontraditional equity" category group into the "alternatives" category group.  

We include funds of funds in the category group pools, and thus, their dollar-weighted and total returns are reflected in the aggregate category group investor return and total returns shown. (The vast majority of funds of funds belong to the "allocation" category group.) However, to avoid double-counting, we exclude funds of funds from the overall investor return and total return calculations. 

To derive each pool's aggregate total return, we compound each constituent fund's beginning net assets by its monthly net returns to the end of the study period. We sum these values to arrive at the pool's aggregate ending net assets, which we compare with its beginning net assets to arrive at the total return for the study period.     

For purposes of aggregating the total returns of obsolete funds, we incorporate the monthly returns of liquidated funds through the terminal month and assume the returns are zero thereafter. With respect to merged funds, we incorporate the monthly net returns of the acquired fund through the month before it merges and then assume it inherits the monthly net returns of the acquiring fund thereafter. 

The study includes investor returns and total returns for both mutual funds and ETFs. ETFs can be used as trading vehicles, but our data uses monthly asset data rather than daily data. Given that ETFs do not report changes in net assets attributable to dividend reinvestments, we adjust reported flows by an assumed reinvestment rate that's tailored to each category group. (We make the same adjustment for open-end funds if the fund doesn't separately report reinvestments.) 

(For more detailed information on Morningstar's approach to estimating funds' monthly net flows, please see Morningstar's "Estimated Net Cash Flow Methodology" dated Aug. 31, 2018.) 

Because investor returns over shorter periods aren't as meaningful, we focus the study on long-term results. The aggregate numbers shown in the study are based on the 10-year period ended Dec. 31, 2025, but we also show results for each of the most recent five 10-year periods. This historical data allows investors to see trends in investor return gaps over time.