Figure 1: US-domiciled funds of funds. The
denominator for the blue dashed line is all US-domiciled mutual funds.
Source: Authors’ calculations based on data from
Morningstar.
Line graph showing two trends from 2010 to 2023 at a quarterly frequency: 'Share of mutual fund industry' (left axis, in percent) and 'Net asset market value' (right axis, in $Tr). The share of mutual fund industry increases from about 5% to 10% over the period. Net asset market value grows from around $0.5 trillion to $2.5 trillion, with a sharp increase after 2020.
Figure 2: US-domiciled funds of funds as a share of all
US-domiciled mutual funds. Source: Authors’ calculations based
on data from Morningstar.
Stacked bar graph showing the percentage of mutual fund net assets from 2010 to 2023 at a quarterly frequency, divided between target-date funds and non-target-date funds. The graph shows a steady overall increase from about 5% in 2010 to over 10% by 2023. Target-date funds (light blue) consistently make up the larger portion, growing from about 2.5% to 8% over the period. Non-target-date funds (dark blue) show a smaller but steady increase, rising from about 2% to 2.5% of net assets. The combined total reaches its peak around 2019-2020 before slightly declining and stabilizing.
Figure 3: Fund of funds’ year-end portfolio allocations to
bond mutual funds and equity mutual funds. Source: Authors’
calculations based on data from Morningstar.
Stacked bar graph showing the percentage distribution of bond funds and equity funds from 2010 to 2023, with annual data points. Equity funds (light orange) consistently make up the larger portion, ranging from about 50% to 70% of the total. Bond funds (dark orange) comprise the remaining 30% to 50%. The ratio remains relatively stable over the years, with a slight increase in equity fund share towards the end of the period. The graph shows 14 annual observations, one for each year from 2010 to 2023.
Figure 4: Persistence in fund of funds’ portfolio allocations.
The unit of observation is a fund of funds in a month. The data cover
2010-2023, excluding March 2020. The large orange dots in each plot show
the weighted averages for each of 20 bins, where each observation is
weighted by the net asset value of the fund of funds. For legibility,
the data are censored at −5 to remove a
few observations when funds of funds held short positions. Source:
Authors’ calculations based on data from Morningstar.
(a) Bond funds
(b) Equity funds
The unit of observation is a fund of funds in a month. The data cover 2010-2023, excluding March 2020. The large orange dots in each plot show the weighted averages for each of 20 bins, where each observation is weighted by the net asset value of the fund of funds. For legibility, the data are censored at $-5$ to remove a few observations when funds of funds held short positions. Source: Authors' calculations based on data from Morningstar. Panel (a) -- Scatter plot comparing lagged equity allocation (x-axis) to equity allocation (y-axis), both in percentages from 0 to 100%. The plot shows a strong positive correlation, with thousands of small black dots forming a dense diagonal line from the bottom left to the top right. Orange dots showing the weighted averages for each of 20 bins, where each observation is weighted by the net asset value of the fund of funds, are evenly spaced along this diagonal. The relationship appears nearly linear, suggesting that current equity allocations closely match their lagged values. Panel (b) -- Scatter plot comparing lagged bond allocation (x-axis) to current bond allocation (y-axis), both ranging from 0 to 100%. The plot shows a strong positive correlation with thousands of small black dots forming a dense diagonal line from the bottom left to the top right. Orange dots showing the weighted averages for each of 20 bins, where each observation is weighted by the net asset value of the fund of funds, are evenly spaced along this diagonal. The relationship appears nearly linear, indicating that current bond allocations closely match their lagged values.
Figure 5: Bond and equity fund cumulative returns
February—March 2020. The solid lines show the weighted-average
daily cumulative returns of equity funds and bond funds for all funds
that were held by funds of funds at the end of 2019. The weights in the
calculations are each fund’s daily net asset market value. The dashed
line shows the cumulative return on the S&P500. The dot-dashed line
shows the cumulative return on Fidelity’s Total Bond ETF, which is a
broad-based basket of US fixed income securities. Source: Authors’
calculations based on data from Morningstar.
The solid lines show the weighted-average daily cumulative returns of equity funds and bond funds for all funds that were held by funds of funds at the end of 2019. The weights in the calculations are each fund's daily net asset market value. The dashed line shows the cumulative return on the S&P500. The dot-dashed line shows the cumulative return on Fidelity's Total Bond ETF, which is a broad-based basket of US fixed income securities. Source: Authors' calculations based on data from Morningstar. Line graph showing cumulative returns for four financial instruments at a daily frequency from February 1 to April 1. The graph includes bond funds held by funds of funds (solid orange line), equity funds held by funds of funds (light orange line), S&P500 index (solid black line), and Fidelity’s Total Bond ETF (dashed black line). All instruments start at 0% return and remain close to 0% until mid-February. Then, equity-related instruments (equity funds and S&P500) fall steeply, reaching about -30% by mid-March. Bond funds and the bond ETF decline later and by less, reaching around -10%. Towards April, all returns show a slight recovery.
Figure 6: Portfolio rebalancing by funds of funds in March
2020. The unit of observation is a fund of funds. The y-axes
show allocations at the end of March 2020, the x-axes show their
allocations at the end of February 2020 (upper panels) and December 2019
(lower panels). The large orange dots in each plot show the weighted
averages for each of 20 bins, where each observation is weighted by the
net asset value of the fund of funds. Source: Authors’ calculations
based on data from Morningstar.
(a) Bond funds
(b) Equity funds
The unit of observation is a fund of funds. The y-axes show allocations at the end of March 2020, the x-axes show their allocations at the end of February 2020 (upper panels) and December 2019 (lower panels). The large orange dots in each plot show the weighted averages for each of 20 bins, where each observation is weighted by the net asset value of the fund of funds. Source: Authors' calculations based on data from Morningstar. Panel (a) -- Scatter plot comparing equity allocations of funds of funds in February 2020 (x-axis) to March 2020 (y-axis), both as percentages from 0 to 100%. The plot shows a strong positive correlation with small gray dots forming a diagonal line from bottom left to top right. Large orange dots represent weighted averages for 20 bins, weighted by net asset value. The relationship is nearly linear, indicating that most funds maintained similar equity allocations from February to March 2020. Panel (b) -- Scatter plot comparing bond allocations of funds of funds in February 2020 (x-axis) to March 2020 (y-axis), both as percentages from 0 to 100%. The plot shows a strong positive correlation with small gray dots forming a diagonal line from bottom left to top right. Large orange dots represent weighted averages for 20 bins, weighted by net asset value of the fund of funds. The relationship is nearly linear, indicating that most funds maintained similar bond allocations from February to March 2020.
Figure 7: Bond and equity fund cumulative net flows
February—March 2020. This figure shows the cumulative net flows
for all share classes separately for (a) bond funds and (b) equity funds
of all funds that were held by funds of funds at the end of 2019. Each
panel shows cumulative net flows as a percent of total net assets as of
February 3, 2020. The red solid line is the cumulative net flows of all
share classes. The green dotted line is the cumulative net flows of
share classes with more than 15 percent of total net assets held by
funds of funds at the end of 2019. And the blue dashed line is the
cumulative net flows of share classes not held by funds of funds at the
end of 2019. Source: Authors’ calculations based on data from
Morningstar.
This figure shows the cumulative net flows for all share classes separately for (a) bond funds and (b) equity funds of all funds that were held by funds of funds at the end of 2019. Each panel shows cumulative net flows as a percent of total net assets as of February 3, 2020. The red solid line is the cumulative net flows of all share classes. The green dotted line is the cumulative net flows of share classes with more than 15 percent of total net assets held by funds of funds at the end of 2019. And the blue dashed line is the cumulative net flows of share classes not held by funds of funds at the end of 2019. Source: Authors' calculations based on data from Morningstar. Two-panel line graph showing cumulative net flows for bond and equity funds held by funds of funds (FOFs) at a daily frequency from February to April 2020. The panels illustrate different flow patterns for bond and equity funds, with FOF-held share classes showing more extreme movements in both cases. Panel (a) -- Bond fund share classes: Three lines show cumulative net flows as a percentage of total net assets. All start at 0% in early February. Before March 1, share classes held >15% by FOFs (dotted green line) start to fall, while share classes not held by FOFs (dashed blue line) and all share classes (solid red line) remain close to 0%. Around March 7, share classes not held by FOFs (dashed blue line) and all share classes (solid red line) begin to drop. All three series fall steadily, reaching about -4% for share classes not held by FOFs, about -5% for all share classes, and about -7% for share classes held >15% by FOFs. Panel (b) -- Equity fund share classes: Three lines again represent different share classes. All start at 0% in early February. Before March 1, share classes held >15% by FOFs (dotted green line) start to rise, while share classes not held by FOFs (dashed blue line) and all share classes (solid red line) start to fall. All three series change steadily, reaching about 1.5% for share classes held >15% by FOFs, about -1% for all share classes, and about s‑1.5% for share classes not held by FOFs.
Figure 8: Regression coefficients from estimating equation 10. The figure
shows the weekly \(\beta^w\)
coefficients that measure the differential cumulative net flows on the
share classes that were largely held by funds of funds compared to other
share classes within the same fund. The shaded regions indicate
95 percent confidence intervals. Source: Authors’ calculations based on
data from Morningstar.
The figure shows the weekly $$\beta^w$$ coefficients that measure the differential cumulative net flows on the share classes that were largely held by funds of funds compared to other share classes within the same fund. The shaded regions indicate 95~percent confidence intervals. Source: Authors' calculations based on data from Morningstar. Line graph showing weekly regression coefficients from February 9 to March 29, 2020, for bond and equity funds’ share classes. The coefficients measure the differential cumulative net flows on share classes largely held by funds of funds compared to other share classes within the same fund. Two lines with shaded confidence intervals are shown: 1. Bond funds (solid blue line): Starts near zero, then sharply declines from late February, reaching about -6 by late March. 2. Equity funds (dashed orange line): Remains close to zero until late February, then gradually increases to about 4 by late March. Both lines have widening 95% confidence intervals (shaded areas) as time progresses, but indicate that the coefficients are statistically significantly different from zero from early March. The bond fund line shows a clear negative trend, while the equity fund line shows a positive trend.
Figure 9: Bond fund cumulative net flows February—March
2020. This figure shows the cumulative net flows as a percent
of total net assets as of February 3, 2020 for the share classes of bond
funds that were held by funds of funds at the end of 2019. Source:
Authors’ calculations based on data from Morningstar.
This figure shows the cumulative net flows as a percent of total net assets as of February 3, 2020 for the share classes of bond funds that were held by funds of funds at the end of 2019. Source: Authors' calculations based on data from Morningstar. Line graph showing cumulative net flows for bond fund share classes at a daily frequency from February 1 to April 1, 2020. The y-axis shows percentages from -8% to 2%, and the x-axis shows dates. The graph illustrates differential impacts on bond fund flows based on ownership structure during the early stages of the COVID-19 pandemic. Four categories of share classes are represented by different colored lines: 1. All share classes (solid pink line) 2. Share classes with more than 15 percent held by FOFs (dashed green line) 3. Institutional share classes not held by FOFs (dashed blue line) 4. Non-institutional share classes not held by FOFs (dotted purple line) All lines start at 0% in early February and remain stable until early March. Share classes with more than 15 percent held by FOFs begins to decline in late-February, reaching about -8% by April 1. By contrast, the other three lines start to decline only in early-March, and by April 1: - All share classes and non-institutional classes not held by FOFs fall to around -5% - Institutional classes not held by FOFs show the least decline, to about -4.5%
Figure 10: Allocations of funds of funds’ portfolios to bond funds and
equity funds. The boxplots in panels (a) and (b) show the
distribution across funds of funds of allocation to bond funds and
equity funds, respectively. Source: Authors’ calculations based on data
from Morningstar.
(a) Bond funds
(b) Equity funds
The boxplots in panels~(a) and~(b) show the distribution across funds of funds of allocation to bond funds and equity funds, respectively. Source: Authors' calculations based on data from Morningstar. Two panel graph showing box plots that compare the percentage allocations of non-Target Date Funds (nonTDF) and Target Date Funds (TDF) from 2005 to 2022. Each panel shows annual data with side-by-side box plots for each year. Panel (a) compares allocations to bond funds and panel (b) compares allocations to equity funds. Panel (a) -- Both fund types show an overall increasing trend in their median allocations to bond funds over time. nonTDF (dark blue) consistently have higher median allocations and larger interquartile ranges compared to TDF (light blue). For nonTDF, the median increases from about 15% in 2005 to around 25% by 2022, with the interquartile range expanding over time. TDF show a more pronounced increase, with the median rising from about 10% in 2005 to approximately 15% by 2022. The interquartile range for TDF also expands but remains smaller than nonTDF throughout. Both fund types display long whiskers, indicating significant variability in allocations, especially in later years. Panel (b) -- Both fund types maintain relatively stable median allocations to equity funds over time, with TDF (light blue) consistently showing higher median allocations compared to nonTDF (dark blue). For nonTDF, the median remains around 60% throughout the period, with a slight decrease towards the later years. The interquartile range is relatively consistent over time. TDF show higher median allocations, staying around 70% for most of the period. The interquartile range for TDF is generally larger than for nonTDF, indicating more variability in allocations. Both fund types display long whiskers, suggesting significant variability in allocations across different funds. The maximum allocations for both types often reach close to 100%.
Figure 11: Allocations of funds of funds’ portfolios to funds within the
same fund family. Panel (a) shows the aggregate allocations to
non-target-date funds (nonTDFs) and target-date funds (TDFs). The
boxplots in panel (b) show the distributions across funds of funds for
nonTDFs and TDFs. Source: Authors’ calculations based on data from
Morningstar.
(a) Aggregate
(b) Distribution across funds of funds
Panel~(a) shows the aggregate allocations to non-target-date funds (nonTDFs) and target-date funds (TDFs). The boxplots in panel~(b) show the distributions across funds of funds for nonTDFs and TDFs. Source: Authors' calculations based on data from Morningstar. Two-panel figure that shows allocations of funds of funds' portfolios to funds within the same fund family, comparing non-target-date funds (nonTDFs) and target-date funds (TDFs) at an annual frequency from 2010 to 2022. Panel (a) -- Aggregate: A stacked bar chart displays yearly allocations. TDFs (light blue) consistently have slightly higher allocations than nonTDFs (dark blue). Both fund types show relatively stable allocations over time, with TDFs around 95-100% and nonTDFs around 85-90%. Panel (b) -- Distribution across funds of funds: A box plot compares the distribution of allocations. TDFs show higher median allocations and smaller interquartile ranges compared to nonTDFs. Both fund types display long whiskers, indicating significant variability. TDF medians remain around 95-100% while nonTDF medians are more variable, ranging from about 80-95%.
Figure 12: Expense ratios for funds of funds. The boxplots show
the distribution across funds of funds of expenses divided by total
assets. Source: Authors’ calculations based on data from
Morningstar.
(a) Liabilities-assets expense ratios
(b) Liabilities expense ratios
(c) Assets expense ratios
The boxplots show the distribution across funds of funds of expenses divided by total assets. Source: Authors' calculations based on data from Morningstar. Three-panel figure showing expense ratios for funds of funds, comparing non-target-date funds (nonTDFs) and target-date funds (TDFs) from 2010 to 2022. Each panel uses box plots to display the distribution across funds of funds within nonTDFs (dark blue) and TDFs (light blue). The panels report different expense ratio calculations. (a) Liabilities-assets expense ratios: Box plots show a wide range of values, centered around 0%, with both positive and negative ratios. nonTDFs (dark blue) generally have higher medians and wider ranges compared to TDFs (light blue). Both fund types show increasing variability over time. (b) Liabilities expense ratios: Box plots display positive ratios ranging from about 0.2% to 0.8%. nonTDFs consistently show higher medians and larger interquartile ranges than TDFs. Both fund types exhibit a slight downward trend in median ratios over time. (c) Assets expense ratios: Box plots reveal ratios mostly between 0.2% and 0.8%. nonTDFs generally have higher medians than TDFs, but the difference narrows over time. Both fund types show a decreasing trend in median ratios and increased variability towards 2022.
Figure 13: Persistence in fund of funds’ portfolio allocations.
For legibility, the data were censored at −5 to remove a few observations when funds of
funds held short positions. Data are monthly for all funds of funds from
2010-2023. Source: Authors’ calculations based on data from
Morningstar.
(a) Bond funds
(b) Equity funds
For legibility, the data were censored at $-5$ to remove a few observations when funds of funds held short positions. Data are monthly for all funds of funds from 2010-2023. Source: Authors' calculations based on data from Morningstar. Two-panel figure illustrating the persistence in fund of funds' portfolio allocations for bond and equity funds from 2010-2023. The figure consists of two scatter plots, comparing lagged allocations to current allocations for non-target-date funds (nonTDF) and target-date funds (TDF). (a) Bond funds: A scatter plot shows a strong positive correlation between lagged and current bond allocations. Both nonTDF (dark blue dots) and TDF (light blue dots) form a dense diagonal line from 0% to 100%, indicating high persistence in bond allocations. The relationship appears nearly identical for both fund types. (b) Equity funds: A similar scatter plot for equity allocations also demonstrates a strong positive correlation. The pattern closely resembles the bond fund plot, with a dense diagonal line of both nonTDF and TDF dots from 0% to 100%. This indicates high persistence in equity allocations for both fund types. In both plots, the dots are densely packed along the diagonal, suggesting that most funds maintain very similar allocations over time. There's no clear visual difference between nonTDF and TDF persistence patterns.
Figure 14: Net asset value of funds of funds separated by the
share of their portfolios held in open-end mutual funds. Each
fund of funds is bucketed based on its individual holdings and the net
asset values are summed across funds within each bucket. Source:
Authors’ calculations based on data from Morningstar.
Each fund of funds is bucketed based on its individual holdings and the net asset values are summed across funds within each bucket. Source: Authors' calculations based on data from Morningstar. Stacked bar chart showing the net asset value of funds of funds at an annual frequency from 2005 to 2023, categorized by the share of their portfolios held in open-end mutual funds. The y-axis represents net asset value in trillions of dollars, ranging from 0 to 3. Four categories are color-coded from lightest to darkest purple: 1. <=35% (lightest purple) 2. 35%--65% 3. 65%--95% 4. >=95% (darkest purple) The chart demonstrates a clear upward trend in total net asset value over time, with significant growth especially after 2015. The >=95% category (darkest purple) shows the most dramatic increase, dominating the top of each bar by 2023. In 2005, the total net asset value was below $0.5 trillion, fairly evenly distributed across categories. By 2023, it exceeded $2.5 trillion, with the >=95% category accounting for the majority.
Figure 15: Total holdings of funds of funds by share in
open-end mutual funds. Panel A shows the holdings of funds of
funds that have at least 65 percent of their total portfolio in open-end
mutual funds. Panel B shows the holdings of funds of funds that have
less than 65 percent of their total portfolio in open-end mutual funds.
Data are as of year end. Source: Authors’ calculations based on data
from Morningstar.
Panel~A shows the holdings of funds of funds that have at least 65~percent of their total portfolio in open-end mutual funds. Panel~B shows the holdings of funds of funds that have less than 65~percent of their total portfolio in open-end mutual funds. Data are as of year end. Source: Authors' calculations based on data from Morningstar. Two-panel figure showing total holdings of funds of funds by share in open-end mutual funds at an annual frequency from 2005 to 2023. Each panel is a stacked bar graph with the bars divided into different asset classes: - Bond (dark blue) - Equity (light blue) - Mutual Fund (teal) - Other Holdings (green) - Unidentified Holding (yellow) Panel A: Bar graph displaying holdings of funds of funds with at least 65 percent of their total portfolio in open-end mutual funds. The y-axis shows values in trillions of dollars, ranging from 0 to 2.5. There's a clear upward trend, with holdings increasing from about 0.5 trillion in 2005 to over 2 trillion by 2023, with particularly rapid growth after 2015. Virtually all holdings are in open-end mutual funds (teal). Panel B: Stacked bar graph showing holdings of funds of funds with less than 65 percent of their total portfolio in open-end mutual funds. The y-axis ranges from 0 to 0.5 trillion dollars. The bars also exhibit an upward trend, but with lower total values compared to Panel A. The mutual fund category (teal) makes up the largest portion of these holdings, growing from nearly zero in 2005 to about 0.3 trillion by 2023. The next largest portions are bonds (dark blue) and equity (light blue) with virtually no other or unidentified holdings.
Figure 16: Comparing Morningstar and Z.1 Financial
Accounts. The lines show estimates of the total net asset
market value of US-domiciled mutual funds. Data are as of quarterly.
Source: Morningstar and FRED.
The lines show estimates of the total net asset market value of US-domiciled mutual funds. Data are as of quarterly. Source: Morningstar and FRED. Line graph comparing total net asset market value of US-domiciled mutual funds at an quarterly frequency from 2010 to 2023 across data sources. The y-axis shows values in trillions of dollars, ranging from about 5 to 25 trillion. Three data series are presented: 1. Morningstar (solid red line): Shows the highest values overall, peaking at nearly 25 trillion in 2021. 2. Morningstar excluding Funds of Funds (FOFs) (dashed green line): Follows a similar trend to the full Morningstar data but with slightly lower values. 3. Z1 Financial Accounts (dashed blue line): Closely tracks the Morningstar excluding FOFs data. All three series show a general upward trend from 2010 to 2023, with notable volatility in 2020 and 2021. The graph illustrates a sharp drop in early 2020, followed by a rapid recovery and peak in 2021, then another decline in 2022 before rising again in 2023.
Figure 17: Distributions of funds of funds’ holdings. Each
panel shows year-end distributions across funds of funds. Panel (a)
shows the number of mutual funds held. Panel (b) shows the maximum
weight of a holding as a percent of the total market value of the fund
of funds’ holdings. Panel (c) shows the average weight of individual
holdings as a percent of the total market value of the fund of funds’
holdings. And Panel (d) shows the overall net asset value of funds of
funds. The red dots in Panel (d) are the means of the distributions.
Source: Authors’ calculations based on data from Morningstar.
(a) Number of open-end mutual funds held
(b) Maximum weight in portfolio
(c) Average weight in portfolio
(d) Size of funds of funds by net asset value
Each panel shows year-end distributions across funds of funds. Panel~(a) shows the number of mutual funds held. Panel~(b) shows the maximum weight of a holding as a percent of the total market value of the fund of funds' holdings. Panel~(c) shows the average weight of individual holdings as a percent of the total market value of the fund of funds' holdings. And Panel~(d) shows the overall net asset value of funds of funds. The red dots in Panel~(d) are the means of the distributions. Source: Authors' calculations based on data from Morningstar. Four-panel figure containing box plot graphs at an annual frequency from 2005 to 2023. Each graph shows yearly data points, with boxes representing interquartile ranges and whiskers extending to minimum and maximum values, excluding outliers. The box plots show the distribution across funds of funds of the open-end mutual funds held in their portfolios. Panel (a) Number of open-end mutual funds held: Generally ranging between 5 and 20, with a slight increasing trend over time. Panel (b) Maximum weight of each fund in a fund of funds’ portfolio: Mostly between 20% and 40%, relatively stable over the years. Panel (c) Average weight of a fund in a fund of funds’ portfolio: Typically between 5% and 15%, with some fluctuation but no clear trend. Panel (d) Size of funds of funds by net asset value: Showing an increasing trend from less than $1bn to over $2bn, with red dots indicating mean values above the boxplots.
Figure 18: Portfolio allocations of funds held by funds of
funds. Each figure is a histogram of the number of funds held
by funds of funds as a function of those funds’ allocations to bonds
and/or equity. Panel (a) shows the funds’ allocations to bonds and
equity combined. Panel (b) shows the funds’ allocation to equity only.
Panel (c) shows the funds’ allocation to bonds only. Allocations are as
of December 31, 2019 based on all the open-end mutual funds held by
funds of funds on December 31, 2019. Source: Authors’ calculations based
on data from Morningstar.
(a) Allocation to bonds and equity
(b) Allocation to equity
(c) Allocation to bonds
Each panel shows year-end distributions across funds of funds. Panel~(a) shows the number of mutual funds held. Panel~(b) shows the maximum weight of a holding as a percent of the total market value of the fund of funds' holdings. Panel~(c) shows the average weight of individual holdings as a percent of the total market value of the fund of funds' holdings. And Panel~(d) shows the overall net asset value of funds of funds. The red dots in Panel~(d) are the means of the distributions. Source: Authors' calculations based on data from Morningstar. Three-panel figure showing how funds held by funds of funds allocate their portfolios to bonds and equity. Three histograms show the number of funds (x-axis) versus allocation percentage (y-axis). (a) Allocation to bonds and equity: Most funds clustered near 100% allocation. (b) Allocation to equity: Bimodal distribution with peaks near 0% and 100%. (c) Allocation to bonds: Inverse of equity allocation, with peaks near 0% and 100%.
Figure 19: Fund of funds’ portfolio allocations to bond funds
and equity funds. The figure shows the distribution of the
ratio of equity funds to bond funds allocation across funds of funds,
with the median value indicated by the red dashed vertical line. The
distribution is censored at five to focus on the bulk of the
distribution and its median value. Source: Authors’ calculations based
on data from Morningstar.
The figure shows the distribution of the ratio of equity funds to bond funds allocation across funds of funds, with the median value indicated by the red dashed vertical line. The distribution is censored at five to focus on the bulk of the distribution and its median value. Source: Authors' calculations based on data from Morningstar. A histogram showing the distribution of equity fund to bond fund allocation ratios across funds of funds. The x-axis shows the ratio values from 0 to 5, while the y-axis represents frequency density. The distribution is right-skewed with its highest concentration around 0.5-0.7, peaking at approximately 0.65 on the y-axis. A vertical red dashed line at 2.2 indicates the median allocation ratio. The frequency gradually decreases as the ratio increases, with a long tail extending to the right. The graph is censored at a ratio of 5 to focus on the main distribution.
Figure 20: Fraction of share classes held by funds of funds at the end
of 2019. These histograms show the distribution across share
classes of funds held by funds of funds, conditional on at least one
share class being held. Source: Authors’ calculations based on data from
Morningstar.
(a) All share classes of funds held by funds of
funds
(b) Share classes with non-zero holdings by funds of
funds
These histograms show the distribution across share classes of funds held by funds of funds, conditional on at least one share class being held. Source: Authors' calculations based on data from Morningstar. Two-panel figure with each panel showing the distribution across share classes of funds held by funds of funds, conditional on at least one share class being held. Panel (a) -- "All share classes of funds held by funds of funds" exhibits a very skewed distribution. There's an extremely tall bar near 0.0 on the x-axis (reaching about 6000 share classes), indicating that most fund share classes have minimal ownership by funds of funds (FOFs). A much smaller cluster appears around the 1.0-1.2 range. Panel (b) -- "Share classes with non-zero holdings by funds of funds" shows a more detailed view of the distribution when FOF ownership exists. This reveals a bimodal pattern - one group with low ownership percentages (0.0-0.2 range, peaking around 400 share classes) and another smaller group with high ownership (0.9-1.2 range, reaching about 200 share classes).
Figure 21: Funds of funds long and short holdings.
Data are annual as of year end. Source: Authors’ calculations based on
data from Morningstar.
A bar chart showing the evolution of funds of funds' long and short holdings as of year end in trillions of dollars at an annual frequency from 2005 to 2023. The chart uses a stacked bar format with pink bars representing long holdings and darker pink/magenta bars representing short holdings. Long holdings show a clear upward trend, starting at approximately $0.25 trillion in 2005 and growing steadily to peak at around $2.5 trillion in 2020, with slight fluctuations in the last few years shown. Short holdings remain minimal throughout the entire period, barely visible at the bottom of each bar.